{{Adams | number = ML16293A280 | issue date = 08/22/2016 | title = Radiological Survey and Dose Assessment Report for the Western New York Nuclear Service Center and Off-Site Areas in Follow Up to Aerial Gamma Radiation Survey Conducted in 2014, Rev. 0, Reference 18 | author name = | author affiliation = MJW Technical Services, Inc | addressee name = | addressee affiliation = NRC/NMSS, State of NY, Energy Research & Development Authority, NRC/NRR | docket = 05000201, P00M-032 | license number = | contact person = | package number = ML16293A155 | document type = Environmental Report | page count = 1217 }}

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{{#Wiki_filter:Reference 18-USEPA Exposure Factors Handbook (EPA. 1997) Reference 18, USEPA Exposure Factors Handbook, 1997. c " ,,, , , ' U.S. Environmental Protection Agency .National :center_for: Environmental Assess;ment,-. ,.,,,, :Offic_e * 'anc:J;_ ,, ' " -,, ' -,' ' ; , ' ' " \' __ ,, :* v, *, ,'*, ,*' I EFHI 1*111 [ii] [?E E [!I kjJ Table of Contents Chapter 1 Introduction

Chapter 3 Drinking Water Intake *Chapter 5 Inhalation Route Chapter 7 Body Weight Studies Chapter 9 Intake of Fruits and Vegetables Chapter 11 Intake of Meat and Dairy Products Chapter 13 Intake Rates for Various Home Produced Food Items Chapter 15 Activity Factors Chapter 17. Residential Building Characteristics / I Chapter 2 Variability and* Uncertainty Chapter 4 Soil Ingestion and Pica 6 Dermal Route Chapter 8 Lifetime Chapter 10 Intake of Fish and Shellfish [rJ Chapter 12 Intake of Grain Products Chapter 14 Breast Milk Intake [jJ Chapter 16 Consumer Products Glossary /

About the Handbook The National Center for Environmental Assessment has prepared this handbook to address factors commonly used in exposure assessments. This handbook was first published in 1989 in response to requests from many EPA Program and Regional offices for additional guidance on how to select values for exposure assessments: This document provides a summary of the avaiJable data on consumption of drinking water; consumption of fruits, vegetables, beef, dairy products, and fish; soil ingestion; inhalation rates; skin surface area; soil adherence; lifetime; activity patterns; body weight; consumer product use; and the reference residence. The handbook is equipped with a number of tools meant to help the user navigate through the

Exposure Factors Handbook. The following is a description of these tools. Some of the links appear throughout the document will transport the user to another portion of the handbook. An indication that the user has encountered a hypertext link is that the hand in the A?obe Acrobat Reader will change to a hand with a pointing finger or an arrow. Arrow buttons at the top of the screen are part of the Adobe Acrobat Reader program and will . . . allow the user to move through files which have been opened. These arrows include: This button will move the user to the first page of a file .. This button will move the user to the previous page. This button will move the user to the next page. This button will move the user to the last page of a file. This button will move the user to the last view displayed on the computer monitor. This button will magnify the view on the screen. Push the button, move the mouse to the portion of the screen the user wants magnified, and click the left mouse button. The user will need to use the last view button (the double arrow pointing to the left above) to maneuver from the tables to the text of the Exposure Factors Handbook. A more convenient way of maneuvering between the tables and text is being explored. At the left of each page in the Exposure Factors Handbook, the user will find a Bookmarks Panel containing bookmarks to jump to any other chapter, table, appendix, or figure in the handbook.

EFH PREFACE The National Center for Environmental Assessment (NCEA) of EPA's Office of Research and Development (ORD) has prepared this handbook to address factors commonly used in exposure assessments. This handbook was first published in 1989 in response to requests from many EPA Program and Regional offices for additional guidance on how to select values for exposure factors. Several events sparked the efforts to revise the Exposure Factors Handbook. First, since its publication in 1989, new data have become available. Second, the Risk Assessment Council issued a memorandum titled, "Guidance on Risk Characterization for Risk Managers and Risk Assessors," dated February 26, 1992, which emphasized the use of multiple descriptors of risk (i.e., measures of central tendency such as average or mean, or high end), and characterization of individual risk, population risk, important subpopulations. A new document was issued titled "Guidance for Risk <;;haracterization," dated February 1995. This document is an update of the guidance issued with the 1992 policy. Third, EPA published the revised Guidelines for Exposure Assessment in 1992. As part of the efforts to revise the handbook, the EPA Risk Assessment Forum sponsored a two-day peer involvement workshop which was conducted during the summer of 1993. The workshop was attended by 57 scientists from academia, consulting firms, private industry, the States, and other Federal agencies. The purpose of the workshop was to identify new data sources, to discuss adequacy of the data and the feasibility of developing statistical distributions and to establish priorities. As a result of the peer involvement workshop, three new chapters were added to the handbook. These chapters are: Consumer Product Use, *Residential Building Characteristics, and Intake of Grains. This document also provides a summary of the Exposure Factors Handbook August 1997 EFH available data on consumption of drinking water; consumption of fruits, vegetables, beef, dairy products, grain products, and fish; breast milk intake; soil ingestion; inhalation rates; skin surface area; soil adherence; lifetime; activity patterns; and body weight. A new draft handbook that incorporated comments from the 1993 workshop was published for peer review in June 1995. A peer review workshop was held in July 1995 to discuss comments on the draft handbook. A new draft of the handbook that addressed comments from the 1995 peer review workshop was submitted to the Science Advisory Board (SAB) for review in August 1996. An SAB workshop meeting was held December 19-20, 1996, to discuss the comments of th.e SAB reviewers. Comments from the SAB review have been incorporated into the current handbook. Exposure Factors Handbook August1997 EFH FOREWORD The National Center for .Environmental Assessment (NCEA) of EPA's Office of Research and Development (ORD) has five main functions: (1) providing risk assessment research, methods, and guidelines; (2) performing health and ecological assessments; (3) developing, maintaining, and transferring risk assessment information and training; (4) helping ORD set research priorities; and (5) developing and maintaining resource support systems for NCEA. The activities under each of these functions are supported. by and respond to the needs of the various program offices. In relation to the first function, NCEA sponsors projects aimed at developing or refining techniques used in exposure assessments. This handbook was first published in 1989 to provide statistical data on the various factors used in .assessing exposure .. This revised version .of the handbook provides the up-to-date data on these exposure factors. The recommE:lnded values are based solely on our interpretations of the available data. In* many situations different values may be appropriate to use in consideration of policy, precedent or other factors. Exposure Factors Handbook Michael A. Callahan Director National Center for Environmental Assessment Washington Office August 1997 EFH AUTHORS, CONTRIBUTORS, AND REVIEWERS The National Center for Environmental Assessment (NCEA), Office of Research and Development was responsible for the preparation of this handbook. The original document was prepared by Versar Inc. under EPA Contract No. 68-02-4254, Work Assignment No. 189. John Schaum, of NCEA-Washington Office, served as the EPA Work Assignment Manager, providing overall direction and coordination of the production effort as well as technical assistance and guidance. Revisions, updates, and additional preparation were provided by Versar Inc. under Contract Numbers 68-D0-0101, 68-D3-0013, and 68-D5-0051. Russell Kinerson and Greg Kew have served as EPA Work Assignment Managers during previous efforts of the update process. Jackie Moya served as Work Assignment Manager for the current updated version, providing overall direction, technical assistance, and serving as contributing author. AUTHORS Patricia Wood Linda Phillips Aderonke Adenuga Mike Koontz

Harry Rector Charles Wilkes Maggie Wilson DESKTOP PUBLISHING Susan Perry WORD PROCESSING Valerie Schwartz Exposure Assessment Division Versar Inc. Springfield, VA Exposure Factors Handbook GRAPHICS Kathy Bowles Jennifer Baker CD-ROM PRODUCTION Charles Peck August 1997 EFH CONTRIBUTORS AND REVIEWERS The following EPA individuals have reviewed and/or have been contributing authors of this document. Michael Dellarco Robert McGaughy Amy Mills Jacqueline Moya Susan Perlin Paul Pinsky John -Schaum Paul White Amina Wilkins Chieh Wu The following individuals were Science Advisory Board Reviewers: Members Dr. Joan Daisey Lawrence Berkley Laboratory Berkley, California Dr. Paul Bailey Mobil Business Resources Corporation Paulsboro, New Jersey Dr. Robert Hazen State of New Jersey Department of Environmental Protection and Energy Trenton, New Jersey Dr. Timothy Larson Department of Civil Engineering University of Washington Seattle, Washington Dr. Kai-Shen Liu California Department of Health Services Berkeley, California Exposure Factors Handbook Dr. Paul Uoy Environmental Occupational Health Sciences Institute Piscataway, New Jersey Dr. Maria Morandi University of Texas School of PubliG
Health Houston, Texas Dr. Jonathan M. Samet The Johns Hopkins University *Baltimore, Maryland Mr. Ron White American Lung Association Washington, D.C. Dr. Lauren Zeise California Environmental Protection Agency Berkeley, California August 1997
Federal Experts Dr. Richard Ellis U.S. Department of Agriculture Washington, D.C. EFH Ms. Alanna J. Moshfegh U.S. Department of Agriculture Washington, D.C. An earlier draft of this document was peer reviewed by a panel of experts at a peer-review workshop held in 1995. Members of the Peer Review Panel were as follows: Edward Avol Department of Preventive Medicine School of Medicine University of Southern California James Axley School of Architecture Yale University David Burmaster Alceon Corporation Steven Colome Integrated Environmental Services Michael DiNovi Chemistry Review Branch U.S. Food & Drug Administration Dennis Druck Environmental Scientist Center of Health Promotion & Preventive Medicine U.S. Army J. Mark Fly Department of Forestry, Wildlife, &
Fisheries University of Tennessee Larry Gephart Exxon Biomedical Sciences, Inc. Exposure Factors Handbook Patricia Guenther Beltsville Human Nutrition Research Center U.S. Department of Agriculture P.J. (Bert) Hakkinen Paper Product Development & Paper Technology Divisions The Proctor & Gamble Company Mary Hama Beltsville Human Nutrition Research Center U.S. Department of Agriculture Dennis *Jones Agency for Toxic Substances & Disease Registry John Kissel Department of Environmental Health School of Public Health & Community Neil Klepeis Information Systems & Services, Inc. August 1997 EFH Andrew Persily National Institute of Standards & Technologies Barbara Petersen Technical Assessment Systems, Inc. Thomas Phillips Research Division California Air Resources Board Paul Price Chem Risk John Risher Division of Toxicology The Agency for Toxic Substances & Disease Registry John Robinson University of Maryland Peter Robinson The Proctor & Gamble Company Exposure Factors Handbook P. Barry Ryan Department of Environmental & Occupational Health Rollins School of Public Health Emory University Val Schaeffer U.S. Consumer Product Safety Commission Brad Shurdut DowElanco John Talbott U.S. Department of Energy Frances Vecchio Beltsville Human Nutrition Research Center U.S. Department of Agriculture August 1997 EFH The following individuals within EPA have reviewed an earlier draft of this document and provided valuable comments: OFFICE REVIEWERS/CONTRIBUTORS Office of Res.earch and Development Maurice Berry Jerry Blancato Elizabeth Bryan Cu,rtis Dary Office of Emergency and Remedial Response* Office of Pollution, Pesticides and Toxic Substances Office of Water Office of Air Quality Planning and Standards EPA Regions Stan Durkee Manuel Gomez Wayne Marchant Sue Perlin James Quanckenboss Glen Rice Lance Wallace Jim Konz Pat Kennedy Cathy Fehrenbacker Denis Borum Helen Jacobs Warren Peters Steve Ehlers -Reg. VI Maria Martinez -Reg. VI Mike Morton -Reg. VI Jeffrey Yurk -Reg. VI Youngmoo Kim -Reg. VI . In addition, the National Exposure Research Laboratory (NERL) of the Office of Research and Development of EPA made an important contribution to this handbook by conducting additional analyses of the National Human Activity Pattern Survey (NHAPS) data. EPA input to the NHAPS data analysis came from Karen A. Hammerstrom and Jacqueline Moya from NCEA-Washington Office; William C. Nelson from NERL-RTP, and Stephen C. Hern, Joseph V. Behar (retired), and William H. Englemann from NERL-Las Vegas. Exposure Factors Handbook August 1997 EFH The EPA Office of Water made an important contribution by conducting an analysis of the USDA Continuing Survey of Food Intakes by Individual (CSFll) data. They provided fish intake rates for the general population. The analysis was conducted under the direction of Helen Jacobs from the Office of Water. ) Exposure Factors Handbook-August 1997 Figure 1-2. Road Map to Exposure Factor Recommendations RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION/ RATINGS TABLE Ingestion Inhalation Dermal (All Routes) Human Characteristics (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics Figure 1-2. Road Map to Exposure Factor Recommendations RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION /RATINGS TABLE Ingestion Inhalation Dermal (All Routes) Human Characteristics (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics Drinking Water Intake Rate Fruit and Vegetable Intake Rate Meat and Dairy Intake Rate Fish and Shellfish Intake Rate Soil Intake Rate Grain Intake Figure 1-2. Road Map to Exposure Factor Recommendations RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION I RA TINGS TABLE Drinking Water Intake Rate Children Pregnant Women High Activity Fruit and Vegetable Intake Rate Meat and Dairy Intake Rate _?:.:;;2:::::.....----;--Homegrown Foods Ingestion Breast milk Intake Rate Inhalation Dermal (All Routes) Human Characteristics (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics Fish and Shellfish Intake Rate Soil Intake Rate Grain Intake 3 3.6/3-35 Figure 1-2. Road Map to Exposure Factor Recommendations .. RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION/ RA TINGS TABLE Ingestion Inhalation Dermal (All Routes) Human Characteristics (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics Drinking Water Intake Rate Fruit and Vegetable Intake Rate -.:......._ Various Demographic Groups _Age, Meat and Dairy Intake Rate Region, Season, Urbanization, Race Fish and Shellfish Intake Rate Soil Intake Rate Grain Intake II 9 9.3/9-30 Figure 1-2. Road Map to Exposure Factor Recommendations RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION /RATINGS TABLE Inhalation Dermal {All Routes) Human Characteristics (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics Drinking Water Intake Rate Fish and Shellfish Intake Rate Soil Intake Rate Grain Intake II 11 11.4/11-31 F 12RdM tE * *
Fact Recommendations RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION/ RATINGS TABLE Inhalation Dermal (All Routes) Human Characteristics (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics Drinking Water Intake Rate Fruit and Vegetable Intake Rate Breast milk Intake Rate Fish and Shellfish Intake Rate Soil Intake Rate Grain Intake II 13 13.5/13-72 Figure 1-2. Road Map to Exposure Factor Recommendations RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION/ RATINGS TABLE Drinking Water Intake Rate Fruit and Vegetable Intake Rate Meat and Dairy Intake Rate I f Homegrown Foods nges ion Breast milk Intake Rate------Inhalation Dermal (All Routes) Human Characteristics (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics Fish and Shellfish Intake Rate Soil Intake Rate Grain Intake Nursing Infants II 14 14.6114-14 Figure 1-2. Road Map to Exposure Factor Recommendations RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION/ RATINGS TABLE Drinking Water Intake Rate Fruit and Vegetable Intake Rate Meat and Dairy Intake Rate Homegrown Foods Ingestion Breast milk Intake Rate Inhalation Dermal (All Routes) Human Characteristics {All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics Fish and Shellfish Intake Rate Soil Intake Rate Grain Intake General Population Freshwater Recreational Marine Recreational Subsistence II II II II 10 10 10 10 10.10.1 /10-87 10.10.3/10-89 10.10.2/10-88 10.10.4/10-90 Figure 1-2. Road Map to Exposure Factor Recommendations RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION/ RATINGS TABLE Drinking Water Intake Rate Fruit and Vegetable Intake Rate Meat and Dairy Intake Rate _µ.'2:::=-----Homegrown Foods Ingestion Breast milk Intake Rate Fish and Shellfish Intake Rate Soil Intake Rate Grain Intake Children Adults Pica Children Various Demographic Groups-Age, Region, Season, Urbanization, Race Inhalation Dermal (All Routes) Human Characteristics {All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics 4 4.7/4-21 Figure 1-2. Road Map to Exposure Factor Recommendations RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION/ RATINGS TABLE Drinking Water Intake Rate Fruit and Vegetable Intake Rate Meat and Dairy Intake Rate fa==------;--Homegrown Foods Ingestion Breast milk Intake Rate Fish and Shellfish Intake Rate Soil Intake Rate Grain Intake Children Adults Pica Children Various Demographic Groups -Age, Region, Season, Urbanization, Race Inhalation Dermal (All Routes) Human Characteristics (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics II 12 12.3/12-24 Figure 1-2. Road Map to Exposure Factor Recommendations RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION /RATINGS TABLE Ingestion Inhalation Dermal (All Routes) Human Characteristics (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics . Inhalation Rate Children High Activity 5.2.4/5-23 5.

EXPOSURE ROUTE Ingestion Inhalation (All Routes) Human Characteristics (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics Figure 1-2. Road Map to Exposure Factor Recommendations EXPOSURE FACTOR *Adults -Children POPULATION VOLUME RECOMMENDATIONS/ CHAPTER RA TINGS TABLE PAGE NOS. 6. 6-8/6-25 6. 6-8/6-27 Figure 1-2. Road Map to Exposure Factor Recommendations RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION I RA TINGS TABLE Ingestion Inhalation Dermal (All Routes) <Body Weight Human Characteristics Lifetime (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics Figure 1-2. Road Map to Exposure Factor Recommendations RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION I RA TINGS TABLE Ingestion Inhalation Dermal _Adults (All Routes) <Body Weight -=======::::::;::=Children Human Characteristics Lifetime (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics 7 . 7.3f7-12 Figure 1-2. Road Map to Exposure Factor Recommendations ' RECOMMENOA TIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION/ RATINGS TABLE Ingestion Inhalation Dermal (All Routes) < Body Weight Human Characteristics Adults Lifetime (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics Children 8 8.2/8-3

Figure 1-2. Road Map to Exposure Factor Recommendations RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION I RATINGS TABLE Ingestion Inhalation Dermal (All Routes) Human Characteristics (All Routes) Activity Factors Activity Patterns Children Mobility Adults (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics Adults Population Mobility -========Children Ill Ill Ill 15 15 15 15.4.1/15-172 15.4.2/15-173 15.4.3/15-175 Figure 1-2. Road Map to Exposure Factor Recommendations RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION/ RA TINGS TABLE Ingestion Inhalation Dermal (All Routes) Human Characteristics (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics .----Frequency of UseAmount Used-------'--Adults --Adults Ill 16 16.4 Figure 1-2. Road Map to Exposure Factor Recommendations* RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION/ RATINGS TABLE Ingestion Inhalation Dermal (All Routes) Human Characteristics (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) ----Water Use --Residential """2:::::---Air Exchange Rates -----======-----General Population Building House Volumes Building Characteristics * '--**-**-***----*--*----Ill 17 17.6/17-32, 17-33 Glossary GLOSSARY Absorption fraction (percent absorbed) -The relative amount of a substance that penetrates through a barrier into the body, reported as a unitless fraction. Accuracy-The measure of the correctness of data, as given by the difference between the measured value and the true or. standard value. Activity pattern (time use) data -Information on activities in which various individuals engage, length of time spent performing various activities, locations in which individuals spend time and length of time spent by individuals within those various environments. Air exchange rate -Rate of air leakage through windows, doorways, intakes and exhausts, and "adventitious openings" (i.e., cracks and seams) that combine to form the leakage configuration of the building envelope plus natural and mechanical ventilation. Ambient -The conditions surrounding a person, sampling location, etc. Analytical uncertainty propagation -Examines how uncertainty in individual parameters affects the overall uncertainty of the exposure assessment. The uncertainties associated with various parameters may propagate through a model very differently, even if they have approximately the same uncertainty. Since uncertainty propagation is a function of both the data and the model structure, this procedure evaluates both input variances and model sensitivity.

As consumed intake rates -Intake rates that are based on the weight of the food in the form that it is consumed. Average daily dose -Dose rate averaged over a pathway-specific period of exposure expressed as a daily dose on a per-unit-body-weight basis. The ADD is used for exposure to chemicals with.non-carcinogenic chronic effects. The ADD is usually expressed in terms of mg/kg-day or other mass/mass-time units. Best Tracer Method (BTM) -Method for estimating soil ingestion that allows for the selection of the most recoverable tracer for a particular subject or group of subjects. Selection of the best tracer is made on the basis of the food/soil (F/S) ratio. Boneless equivalent -Weights of meat (pork, veal, beef) and poultry, excluding all bones, but including separable fat sold on retail cuts of red meat.
Carcass weight -Weight of the chilled hanging carcass, which includes the kidney and attached internal fat (kidney, pelvic, and heart fat), excludes the skin, head, feet, and unattached internal organs. The pork carcass weight includes the skin and feet but excludes the kidney and attached internal fat. Chronic intake -The long term period over which a substance crosses the outer boundary of an organism without passing an absorption barrier. Comparability-The ability to describe likenesses and differences in the quality and relevance of two or more data sets. Consumer-only intake rate -The average quantity of food consumed per person in a population composed only of individuals who ate the food item of interest during a specified period. Exposure Factors Handbook August 1997 Glossary Contaminant concentration -Contaminant concentration is the concentration of the contaminant in the medium (air, food, soil, etc.) contacting the body and has units of mass/volume or mass/mass. Creel Census -Approach used by fishery managers to obtain haNest data collected onsite from single anglers or from larger-scale commercial type operations. Deposition -The removal of airborne substances to available surfaces that occurs as a result of gravitational settling and diffusion, as well as electrophoresis a.nd thermophoresis. Diary study-SuNey in which individuals are asked to record food intake, activities, or other factors in a diary which.is later used to evaluate exposure factors associated with specific populations. Distribution -A set of values derived from a specific population or set of measurements that represents the range and array of data for the factor being studied. Dose -The amount of a substance available for interaction with metabolic processes or biologically significant receptors after crossing the outer boundary of an organism. The pofential dose is the amount ingested, inhaled, or applied to the skin. The applied dose is the amount of a substance presented to an absorption barrier and available for absorption (although not necessarily having yet crossed the outer boundary of the organism). The absorbed dose is the amount crossing a specific absorption barrier (e.g., the exchange boundaries of skin, lung, and digestive tract) through uptake processes. Internal dose is a more general term denoting the amount absorbed without respect to specific absorption barriers or exchange boundaries. The amount of a chemical available for interaction by any particular organ or cell is termed the delivered dose for that organ or cell. Dose-response relationship -Ttie resulting biological responses in an organ or organism expressed as a function of a series of doses.
Dressed weight -The portion of the *harvest brought into kitchens for use, including bones for particular species. Dry weight intake rates -Intake rates that are based on the weight of the food consumed after the moisture content has been removed. Employer tenure -The length of time a worker has been with the same employer. Exposed foods -*Those foods that are grown above ground and are likely to be contaminated by pollutants . deposited on surfaces that are eaten. Exposure duration -Total time an individual is exposed to the chemical being evaluated. Exposure Assessment -The determination or estimation (qualitative or quantitative) of the magnitude, frequency, or duration, and route or exposure. Exposure concentration -The concentration of a chemical in its transport or carrier medium at the point of contact. Exposure pathway-The physical course a chemical takes from the source to the organism exposed. Exposure route -The way a chemical pollutant enters an organism after contact, e.g., by ingestion, inhalation, or dermal absorption.
Exposure Factors Handbook August 1997 Glossary Exposure scenario -A set of facts, assumptions, and interferences about how exposure takes place that aids the exposure assessor in evaluating estimating, or quantifying exposures. Exposure -Contact of a chemical, physical, or biological agent with the. outer boundary of an organism. Exposure is quantified as the concentration of the agent in the medium in contact integrated over the time duration of the contact. Exposure duration -Length of time .over which contact with the contaminant lasts. General population -The total of individuals inhabiting an area or making up a whole group. Geometric mean -The nth root of the product of n values. Homegrown/home produced foods -Fruits and vegetables produced by home gardeners, meat and dairy products derived form consumer-raised livestock, game meat, and home caught fish. \ Inhaled dose -The amount of an inhaled substance that is available for interaction with metabolic processes or biologically significant receptors after crossing the outer boundary of an organism. Insensible water loss -Evaporative water losses that occur during breastfeeding. Corrections are made to account for insensible water loss when estimating breast milk intake using the test weighing method. Intake -The process by which a substance crosses the outer boundary of an organism without passing an . absorption barrier (e.g., through ingestion or inhalation).
Intake rate -Rate of inhalation, ingestion, and dermal contact depending on the route of exposure. For ingestion, the intake rate is simply the amount of food containing the contaminant of interest that an individual ingests during some spedfic time period (units of mass/time). For inhalation, the intake rate is the rate at which contaminated air is inhaled. Factors that affect dermal exposure are the amount of material that comes into contact with the skin, and the rate at which the contaminant is absorbed. Internal dose -The amount of a substance penetrating across absorption barriers (the exchange boundaries) of an organism, via either physical or biological processes (synonymous with absorbed dose). lnterzonal airflows -Transport of air through doorways, ductWork, and service chaseways that interconnect. rooms or zones within a building. Lifetime average daily dose -Dose rate averaged over a lifetime. The LADD is used for compounds with carcinogenic or chronic effects. The LADD is usually expressed in terms of mg/kg-day or other mass/mass-time units. Limiting Tracer Method (L TM) -Method for evaluating soil ingestion that assumes that the maximum amount of soil ingested corresponds with the lowest estimate from various tracer elements. Local circulation -Convective and adjective air circulation and mixing within a room or within a zone. Mass-balance/tracer techniques -Method for evaluating soil intake that accounts for both inputs and outputs of tracer elements. Tracers in soil, food, medicine and other ingested items as well as in feces and urine are accounted for. Exposure Factors Handbook August 1997 Glossary Median value -The value in a measurement data set such that half the measured values are greater and half
are less. Microenvironment -The combination of activities and locations that yield potential exposure. Moisture content.-The portion of foods made up by water. The percent water is needed for converting food intake rates and residue concentrations between whole weight and dry weight values. Monte Carlo technique -A repeated random sampling from the of values for each of the parameters in a generic (exposure or dose) equation to derive an estimate of the distribution of (exposures or doses in) the population. Occupational mobility -An indicator of the frequency at which workers change from one occupation to another.
Occupational tenure -The cumulative number of years a person worked in his or her current occupation, regardless of number of employers, interruptions in employment, or time spent in other 'Occupations. Pathway-The physical course a chemical or pollutant takes from the source to the organism exposed. Per capita intake rate -The average quantity of food consumed per person in a population composed of both individuals who ate the food during a specified time period and those that did not. Pica -Deliberate ingestion of non-nutritive substances such as soil. Population mobility-An indicator of the frequency at which individuals move from one residential location to another. Potential dose -The amount of a chemical contained in material ingested, air breathed, or bulk material applied to the skin. Precision -A measure of the reproducibility of a measured value under a given set of circumstances. Preparation losses -Net cooking losses, which include dripping and volatile losses, post cooking losses, which involve losses from cutting, bones, excess fat, scraps and juices, and other preparation losses which include losses from paring or coring. Probabilistic uncertainty analysis -Technique that assigns a probability density function to each input parameter, then randomly selects values from each of the distributions and inserts them into the exposure equation. calculations produce a distribution of predicted values, reflecting the combined impact of variability in each input to the calculation. Monte Carlo is a common type of probabilistic Uncertainty analysis. Protected foods -Those foods that have outer protective coatings that are typically removed before consumption. Random samples -Samples selected from a statistical population such that each sample has an equal probability of being selected. Range -The difference between the largest and smallest values in a measurement data set. Recreational/sport fishermen -Individuals who catch fish as part of a sporting or recreational activity and not for the purpose of providing a primary source of food for themselves or for their families. Exposure Factors Handbook August 1997 Glossary Representativeness -The degree to which a sample is, or samples are, characteristic of the whole medium, exposure, or dose for which the samples are being used to make inferences. Residential volume -The volume {m3) of the structure in which an individual resides and may be exposed to airborne contaminants. ' Residential occupancy period -The time (years) between a person moving into a residence and the time the person moves out or dies. Resource utilization -For any quantity Y that is consumed by individuals in a population, the percentiles of the "resource utilization distribution" of Y can be formally defined as follows: YP (R) is the pth percentile of the
resource utilization distribution if p percent of the overall consumption of Y in the population is done by individuals with consumption below YP (R) and 100-p percent is done by individuals with consumption above Yµ(R). . Retail weight equivalent-Weight of food as sold through retail foodstores; therefore, conversion factors are . used to correct carcass weight to retail weight to account for trimming, shrinkage, or loss of meat and chicken at retail outlets. Route -The way a chemical or pollutant enters an organism after contact, e.g., by ingestion, inhalation, or dermal absorption. Sample -A small part of something designed to show the nature or 'quality of the whole. Exposure-related measurements are usually samples of environmental or ambient *media, exposures of a small subset of a population for a short time, or biological samples, all for the purpose of inferring the nature and quality of parameters important to evaluating exposure. Screening-level assessments -Typically examine exposures that Vl(ould fall on or beyond the high end of the expected exposure distribution. Sensitivity analysis -Process of changing one variable while leaving the others constant to determine its effect on the output. This procedure fixes each uncertain quantity at its credible lower and upper bounds (holding all others at their nominal values, such as medians) and computes the results of each combination of values. The results help to identify the variables that have the greatest effect on exposure estimates and help focus further information-gathering efforts. Serving sizes -The quantities of individual foods consumed per eating occasion. These estimates may be useful for assessing acute exposures. Soil adherence -The quantity of soil that _adheres to the skin and from which chemical contaminants are available for uptake at the skin surface.
Subsistence fishermen -Individuals who consume fresh caught fish as a major source of food. Test weighing -A method for estimating breast milk intake over a 24-hour period in which the infant is weighed before and after each feeding without changing its clothing. The sum of the difference between the measured weights over the 24-hour period is assumed to be equivalent to the amount of breast milk consumed daily. Total tapwater-Water consurried directly from the tap as a beverage or used in the preparation of foods and beverages (i.e., coffee, tea, frozen juices, soups, etc.). Exposure Factors Halldbook August 1997 Glossary Total fluid intake-. Consumption of all types of fluids including tapwater, milk, soft drinks, alcoholic beverages, and water intrinsic to purchased foods. Tracer-element studies -Soil ingestion studies that use trace elements found in soil and poorly metabolized in the human gut as indicators of soil intake. Uncertainty-Uncertainty represents a lack of knowledge about factors affecting exposure or risk and can lead to inaccurate or biased estimates of exposure. The types of uncertainty include: scenario, parameter, and model. Upper percentile -Values at the upper end o_f the distribution of values for a particular set of data. Uptake -The process by which a substance crosses an absorption barrier and is absorbed into the body. Variability-Variability arises from true heterogeneity across people, places or time and can affect the precision of exposure estimates and the degree to which they can be generalized. The types of variability include: spatial, temporal, and inter-individual. Ventilation rate (VR) -Alternative term for inhalation rate or breathing rate. Usually measured as minute volume, i.e. volume (liters) of air exhaled per minute. Volume of exhaled air (VJ -Product of the number of respiratory cycles in a minute and the volume of air respired during each respiratory cycle (tidal volume, VT). Exposure Factors Handbook August 1997 Volume I..., General Factors EFH Chapter 1 -Introduction 1. INTRODUCTION 1.1. PURPOSE 1.2. INTENDED AUDIENCE 1.3. BACKGROUND 1.3.1. Selection of Studies for the Handbook 1.3.2. Using the Handbook in an Exposure Assessment 1.3.3. Approach Used to Develop Recommendations for Exposure Factors 1.3.4. Characterizing Variability 1.4. GENERAL EQUATION FOR CALCULATING DOSE 1.5.. RESEARCH NEEDS 1.6. ORGANIZATION REFERENCES FOR CHAPTER 1 APPENDIX 1A Table 1-1. Table 1-2. Table 1-3. Table 1A-1. Considerations Used to Rate Confidence in Recommended Values Summary of Exposure Factor Recommendations and Confidence Ratings Characterization of Variability in Exposure Factors Procedures for Modifying IRIS Risk Values for Non-standard Populations Figure 1-1. Figure 1-2. Schematic of Dose and Exposure: Oral Route Road Map to Exposure Factor Recommendations Exposure Factors Handbook August 1997 EFH Volume I -General Factors Chapter 1 -Introduction 1. INTRODUCTION 1.1. PURPOSE The purpose of the Exposure Factors Handbook is to: ( 1) summarize data on human behaviors and characteristics which affect exposure to environmental contaminants, and (2) recommend values to use for these factors. These recommendations are not legally binding on any EPA program and should be interpreted as suggestioris which program offices or individual exposure assessors can consider and modify as needed. Most of these factors are best quantified on a site or situation-specific basis. The handbook has strived to include full discussions of the issues which assessors should consider in deciding how to use these data and recommendations. The handbook is intended to serve as a support document to EPA's Guidelines for Exposure Assessment (U.S. EPA, 1992a). The Guidelines were developed to promote consistency among the various exposure assessment activities that are carried out by the various EPA program offices. This handbook assists in this goal by providin.g a consistent set of exposure factors to calculate dose. Purpose *IBummarize data on human behaviors and characteristics affecting exposure *ffiecommend exposure factor values 1.2. INTENDED AUDIENCE The Exposure Factors Handbook is addressed to exposure assessors inside the Agency as well as outside, who need to obtain data on standard factors needed to calculate human exposure to toxic chemicals. 1.3. BACKGROUND This handbook is the update of an earlier version prepared in 1989. Revisions have been made in the following areas: * * *
addition of drinking water rates for children; changes in soil ingestion rates for children; addition of soil ingestion rates for adults; addition of tapwater consumption for adults and children; Exposure Factors Handbook August 1997 Volume I-General Factors EFH Chapter 1 -Introduction * * * * *
* * * * * *
addition of mean daily intake of food class and subclass by region, age and per capita rates; addition of mean moisture content of selected fruits, vegetables, grains, fish, meat, and dairy products; addition of food intake by class in dry weight per kg of body weight per day; update of homegrown food intake; expansion of data in the dermal chapter; update of fish intake data; expansion of data for time spent at residence; update of body weight data; addition of body weight data for infants; update of population mobility data; addition of new data for average time spent in different locations and various, microenviron-ments; addition of data for occupational mobility; addition of breast milk ingestion; addition of consumer product use; and addition of reference residence factors . ( Variation Among Studies This handbook i$ a compilation of available data from a variety of different sources. With very few exceptions, the data presented are the analyses of the individual study authors. Since the studies included in this handbook varied in terms of their objectives, design, scope; presentation of results, etc., the level of detail, statistics, and terminology may vary from study to study and from factor to factor. For example, some authors used geometric means to present their results, while others used. arithmetic means or distributions. Authors have sometimes used different terms to describe the same racial populations. Within the constraint of presenting the original material as* accurately as *possible, EPA has made an effort to present discussions and results in a consistent manner. Further, the strengths and limitations of each study are discussed to provide the reader with a better understanding of the uncertainties associated with the values derived from the study.
1.3.1. Selection of Studies for the Handbook Information in this handbook has been summarized from studies documented in the scientific literature and other available sources. Studies were chosen that were seen as useful and appropriate for estimating exposure factors. The handbook contains summaries of selected studies published through August 30, 1997. Exposure Factors Handbook August 1997 --

EFH Volume I-General Factors Chapter 1 -Introduction General Considerations Many scientific studies were reviewed for possible inclusion in this handbook. Studies were selected based on the following considerations:

Level of peer review: Studies were selected predominantly from the reviewed literature and final government reports. Internal or interim reports were therefore avoided.
Accessibility: Studies were preferred that the user could access in their e'ntirety if needed.
Reproducibility: Studies were sought that contained sufficient information so that methods could be reproduced, or at least so the details of the author's work could be accessed and evaluated.
Focus on exposure factor of interest:
Studies were chosen that directly addressed the exposure factor of interest, or addressed related. factors that have significance for the factor under consideration. As an example of the latter case, a selected study contained useful ancillary information concerning fat content in fish, although it did not directly address .fish consumption.
Data pertinent to the U.S.: Studies were selected that addressed the U.S.* population. Data from populations outside the U.S. were sometimes included if behavioral patterns and other characteristics of exposure were similar.
Primary data: Studies were deemed preferable if based primary data, but studies based on secondary sources were also included where they offered an original analysis. For example, the handbook cites studies of food consumption based on original data collected by the USDA National Food Consumption Survey.
Current information: Studies were chosen only if they were sufficiently recent to represent current exposure conditions. This is an important consideration for . those factors that change with time.
Adequacy of data collection period: Because most users of the handbook are primarily addressing chronic exposures, studies were sought that utilized the *most appropriate techniques for collecting data to characterize long-term behavior.
Validity of approach: Studies utilizing experimental procedures or approaches that more likely or closely capture the desired measurement were selected. In Exposure Factors Handbook August 1997 Volume I -General Factors EFH Chapter 1 -Introduction general, direct exposure data collection techniques, such as direct observation, personal monitoring devices,* or other known methods were preferred where available. If studies utilizing direct measurement were not available, studies were selected that rely on validated indirect measurement methods such as surrogate measures (such as heart rate for inhalation rate), and use of questionnaires. If questionnaires or surveys were used, proper design and procedures include an adequate sample size for the population under consideration, a response rate large enough to avoid biases, and avoidance of bias in the design of the instrument an.d interpretation o(the results.
Representativeness of the population: Studies seeking to characterize the national population, a particular region, or sub-population were selected, if appropriately representative of that population. In cases where data were limited, studies with limitations in this area were included and limitations were noted in the handbook.
Variability in the population: Studies were sought that characterized any variability within populations.
Minimal (or defined) bias in study design: Studies were sought that were designed with minimal bias, or* at least if biases were suspected to be present, the direction of the bias (i.e., an over or under estimate of the parameter) was either stated or apparent from the study design. *
Minimal (or defined) uncertainty in the data: Studies were sought with minimal uncertainty in the data, which was judged by evaluating all the considerations listed above. At least, studies were preferred that identified uncertainties, such as those due to inherent variability in environmental and exposure-related parameters or possible measurement error. Studies that documented Quality Assurance/Quality Control measures were preferable. Key versus relevant studies Certain studies described in this handbook are designated as "key," that is, the most useful for deriving .exposure factors. The recommended values for most exposure factors are based on the results of the key studies. Other studies are designated ... relevant," meaning applicable or pertinent, but not necessarily the most important. This distinction was made on the strength of the attributes listed in the "General Considerations." For example, in Chapter 14 of Volume Ill, one set of studies is deemed to best address the attributes listed and is designated as "key." Other applicable studies, including foreign data, believed to have value to handbook but having fewer attributes, are designated "relevant." Exposure Factors Handbook August 1997 Volume I-General Factors EFH Chapter 1 -Introduction Key vs. Relevant Studies *D<ey studies used to derive recommendations *ffielevant studies included to provide additional perspective 1.3.2. Using the Handbook in an Exposure Assessment Some of the steps for performing an exposure assessment are (1) determining the pathways of exposure, (2) identifying the environmental media which transports the contaminant, (3) determining the contamina.nt concentration, (4) determining the exposure time, frequency, and duration, and (5) identifying the exposed population. Many of the issues related to characterizing exposure from selected exposure pathways have been addressed in a riumber of existing EPA guidance documents. These include, but are not limited to the following: * ' . * * * * * * *
Guidelines for Exposure Assessment (U.S. EPA 1992a); Dermal Exposure Assessment: Principles Applications (U.S. EPA 1992b); Methodology for Assessing Health Risks Associated with Indirect Exposure to Combustor Emissions (U.S. EPA, 1990); Risk Assessment Guidance for Superfund (U.S. EPA, 1989); Estimating Exposures to Dioxin-Like Compounds (U.S. EPA, 1994); Superfund Exposure Assessment Manual (U.S. EPA, 1988a); Selection Criteria for Mathematical Models Used in Exposure Assessments (U.S . EPA 1988b); Selection Criteria for Mathematical Models Used in Exposure Assessments (U.S . EPA 1987); . Standard Scenarios for Estimating Exposure to Chemical Substances During Use of Consumer Products (U.S. EPA 1986a); Pesticide Assessment Guidelines, Subdivisions Kand U (U.S. EPA, 1984, 1986b ); and Methods for Assessing Exposure to Chemical Substances, Volumes 1-13 (U.S. EPA, 1983-1989). These documents may serve as valuable information resources to assist in the assessment of exposure. The reader is encouraged to refer to them for more detailed discussion.
Exposure Factors Handbook August 1997

Volume I-General Factors EFH Chapter 1 -Introduction In addition to the references listed above, this handbook discusses the recommendations provided by the American Industrial Health Council (AIHC) -Exposure Factors Sourcebook (May 1994) for some of the major exposure factors. The AIHC Sourcebook summarizes and evaluates statistical data for various exposure factors used in risk assessments. Probability distributions for specific exposure factors were derived from the available scientific literature using @Risk simulation software. Each factor is described by a specific term, such as lognormal, normal,* cumulative type, or triangular. Other distributions included Weibull, beta logistic, and gamma. Unlike this handbook, however, the Sourcebook does not provide a description and evaluation of every study available on each exposure factor.

Most of the data presented in this handbook are derived from studies that targeted (1) the general population (e.g., USDA food consumptin surveys); and (2) a sample population from a specific area or group (e.g., Calabrese's et al. (1989) soil ingestion study using children from the Amherst, Massachusetts, area). Due to unique activity patterns, preferences, practices and biological differences, various segments of the population may experience exposures that are different from those of the general population, which, in many cases, may be greater. It is necessary for risk or exposure assessors characterizing a diverse population, to identify and enumerate certain groups within the general population who are at risk for greater contaminant exposures or exhibit a heightened sensitivity to particular chemicals. For further guidance on addressing susceptible populations, itis recommended to consult the EPA, National Center for Environmental Assessment document Socio-demographic Data Used for Identifying Potentially Highly Exposed Subpopulations (to be released as a final document in the Fall of 1997).
Most users of the handbook will be preparing estimates of exposure which are to be
combined with factors to estimate risk. Some of the exposure factors (e.g., life time, body weight) presented in this document are also used in generating response relationships. In order to develop risk estimates properly, assessors must use dose-response* relationships in a manner consistent vvith exposure conditions. Alth.ough, it is beyond the scope of this document to explain in detail*how assessors shquld address this issue, a discussion (see Appendix A of this chapter) has been included which describes how dose-response factors can be modified to be consistent with the exposure factors for a population of interest. This should serve as a guide for when this issue is a concern. 1.3.3. Approach Used to Develop Recommendations for Exposure Factors As discussed above, EPA first reviewed all pertaining to a factor and determined relevant and key studies. The key studies were used to derive recommendations for the values of each factor. The recommended values were derived solely from EPA's interpretation of the available data. Different values may be appropriate Exposure Factors Handbook August 1997 ,, J EFH Volume I -General Factors Chapter 1 -Introduction for the user to select in consideration-of policy, precedent, strategy, or other factors such as site-specific information. EPA's procedure for developing recommendations was as follows:
Recommendations and Confidence Ratings *CRecommendations based on data from single or multiple key studies *DJariability and limitation of the data evaluated *CRecommendations rated as low, medium, and high confidence 1. Key studies were evaluated *in terms of both quality and relevance to specific tions (general U.S. population, age groups, gender, etc.). The criteria for assessing the quality of studies is described in Section 1.3.1. 2. If only one.study was classified as key for a particular factor, the mean value from that study was selected as the recommended central value for that population. If there were multiple key studies, all with reasonably equal quality, relevance, and study design information were available, a weighted mean (if appropriate, considering sample size and other statistical factors) of the studies were chosen as the recommended mean value. If the key studies were judged to be unequal in quality, relevance, or study design, the range of means were presented and the user of this handbook must employ judgment in selecting the most appropriate value for the population of interest In cases where the national population was of interest,-the mid-point of the range was usually judged to be the most appropriate value. 3. The variability of the factor across the population was discussed. If adequate data were available, the variability was described as either a series of percentiles or a distribution. 4. Limitations of the data were discussed in *terms of data limitations, the range of circumstances over which the estimates were (or were not) applicable, possible biases in *the values themselves, a statement about parameter uncertainties (measurement error, sampling error) and model or scenario uncertainties if models or scenarios have been used in the derivation of the recommended value. 5. Finally, EPA assigned a confidence rating of low, medium or high . to each recommended value. This rating is not intended to represent an uncertainty analysis, rather it represents EPA's judgment on the quality of the underlying data used to derive Exposure Factors Handbook August 1997 Volume I-General Factors EFH Chapter 1 -Introduction the recommendation. This judgment was made using the guidelines shown in Table 1-1. Table 1-1 is an adaptation of the General Considerations discussed earlier in Section 1.3.1. Clearly this is a continuum from low to high and judgment was used to determine these ratings. Recommendations given in this handbook are accompanied by a discussion of the rationale for their rating. Table 1-2 summarizes EPA's recommendations and confidence ratings for the various exposure factors. It is important to note that the study elements listed in Table 1-1 do not have the same weight when arriving at the overall confidence rating for the various exposure factors. The relative weight of each of these elements depend on the exposure factor of interest. Also, the relative weights given to the elements for the various factors were subjective and based on the professional judgement of the authors of this handbook. In general, most studies would rank high with regard to "level of peer review," "accessibility," "focus on the factor of interest," and "data pertinent to the U.S." These elements are important for the study to be included in this handbook. However, a high score of these elements does not necessarily translate into a high overall score. Other elements in Table 1-1 were also examined to determine the overall score. For example, the adequacy of data collection period may be more important when determining usual intake of foods in a population. On the other hand, it is not as important for factors where long-term variability may be. small such as tapwater intake. In the case of tapwater intake, the currency of the data was a critical element in determining the final rating. In addition, some exposure factors are more easily measured than others. For example, soil ingestion by children is estimated by measuring, in the feces, levels *of certain elements found in soil. Body weight, however, can be measured directly and it is, therefore, a more reliable measurement. This is reflected in the confidence rating given to both of these factors. In general, the better the methodology used to measure the exposure factor, the higher the confidence in the value. 1.3.4. Characterizing Variability This document attempts to characterize variability of each of the factors. Variability is characterized in one or more of three ways: (1) as tables with various percentiles or ranges of values; (2) as analytical distributions with specified parameters; and/or (3) as a qualitative discussion. Analyses to fit standard or parametric distributions (e.g., normal, log normal) to the exposure data have not been performed by the authors of this handbook, but have been reproduced in this document wherever they were found in the literature. Recommendations on the use of these distributions are made where appropriate based on the adequacy* of the supporting data. The list of exposure factors* and the way that variability has been characterized (i.e., average, upper percentiles, multiple percentiles, fitted distribution) are presented in Table 1-3. The term upper percentile is used Exposure Factors Handbook August 1997 EFH Volume I -General Factors Chapter 1 -Introduction throughout this handbook and it is intended to represent values in the upper tail (i.e., between 90th and 99.9th percentile) of the distribution of values for a particular exposure factor. An attempt was made to present percentile values in the recommendations that are consistent with the exposure estimators defined in the Exposure Guidelines (i.e., mean, 50th, 90th, 95th, 98th; and 99.9th percentile). This was not, however, always possible because either the data available were limited for some factors, or the authors of the study did not provide such information. It is important to note, however, that these percentiles were discussed in the Exposure Guidelines within the context of risk descriptors and not individual exopusure factors. For example, the Guidelines stated that the assessor may derive *a high-end estimate of exposure by using maximum or near maximum values for one or more sensitive exposure factors, leaving others at their mean value. The use of* Monte Carlo or other probabilistic analysis require a selection of distributions or histograms for the input parameters. Although this _handbook is not intended to provide a complete guidance on the use of Monte Carlo and other probabilistic . . analyses, the following should be considered when using such techniques:
The exposure assessor should only consider using probabilistic analysis when there are credible distribution data (or ranges) for the factor under consideration. Even if these distributions are known, it may not be necessa.ry to apply this technique. For example, if only average exposure values are needed, these can often be computed accurately by using average values for each of the input parameters. Probabilistic analysis is also not necessary when conducting assessments for screening purposes, i.e., to determine if unimportant pathways can be eliminated. In this case, bounding estimates can be calculated using maximum or near maximum values for each of the input parameters.
It is important to note that the selection of distributions can be highly site specific and will always involve some degree of judgment. Distributions derived from national data may not represent local conditions. To the extent possible, an assessor should use distributions or frequency histograms derived from local surveys to assess risks locally. When distributional data are drawn from national or other surrogate population, it is important that the assessor address the extent to which local conditions may differ from the surrogate data. In addition to a qualitative statement of uncertainty, the representativeness assumption should be appropriately addressed as part of a sensitivity analysis.
Distribution functions to be used in Monte Carlo analysis may be derived by fitting an appropriate function to empirical data. In doing this, it should be recognized Exposure Factors Handbook August 1997 Volume I-General Factors EFH Chapter 1 -Introduction that in the lower and upper tails of the distribution the data are scarce, so that several functions, with radically different shapes in the.extreme tails, may be consistent with the data. To avoid introducing errors into the analysis by the arbitrary choice of an inappropriate function, several techniques can be used. One way is to avoid the problem by using the empirical data itself rather than an analytic function. Another is to do separate analyses with several functions whicli . have adequate fit but form upper and lower bounds to the empirical data. A third . way is to use truncated analytical distributions. Judgment must be used in choosing the appropriate goodness of fit test. Information on the theoretical basis for fitting distributions can be found in a standard statistics text such as Statistical Methods for Environmental Pollution Monitoring, Gilbert, R.O., 1987, Van Nostrand Reinhold; off-the-shelf computer software such as Best-Fit by Palisade Corporation can be used to statistically determine the distributions that fit the data.
If only a range of values is known for an exposure factor, the assessor has several options. -keep that variable constant at its central value; --assume several values within the range of values for the exposure factor; -calculate a point estimate(s) instead of using probabilistic analysis; and -assume a distribution (The rationale for the selection of a distribution should be discussed at length.) There are, however, cases where assuming a distribution is not recommended. These include: --. data are missing or very limited for a key parameter -examples include: soil ingestion by adults; -.,. data were collected over a short time period and may not represent long term trends (the respondent usual behavior) -examples include: food consumption surveys; activity pattern data; --data are not representative of the population of interest because sample size was small or the population studied was selected from a local area and was
therefore not representative of the area of interest -examples include: soil ingestion by children; and --ranges for a key variable are uncertain due to experimental error or other limitations in the study design or methodology -examples include: soil ingestion by children. GENERAL EQUATION FOR CALCULATING DOSE The definition of exposure as used in the Exposure Guidelines (U.S. EPA, 1992a) is "condition of a chemical contacting the outer boundary of a human." This means contact with the visible exterior of a person such as the skin, and openings such as the mouth, Exposure Factors Handbook August 1997 EFH Volume I -General Factors Chapter 1 -Introduction nostrils, and lesions. The process of a chemical entering the body can be described in two* steps: contact (exposure), followed by entry (crossing the boundary).* The magnitude of exposure (dose) is the amount of agent available at human exchange boundaries (skin, lungs, gut) where absorption takes place during some specified time. An example of exposure and dose for the oral route as presented in the the EPA Exposure Guidelines is shown in Figure 1-1. Starting with a general integral equation for exposure (U.S. EPA 1992a), several dose equations can be derived depending upon boundary assumptions. One of the more useful of these derived equations is the Average Daily Dose (ADD). The ADD, which is used for many noncancer effects, averages exposures or doses over the period of time over which exposure occurred. The ADD can be calculated by averaging the potential dose (Dp01) over body weight and an averaging time. Total Potential Dose ADDpot ' Body Weight x Averaging Time For cancer effects, where the biological response is usually described in terms of lifetime probabilities, even though exposure does riot occur over the entire lifetime, doses are often presented as lifetime average daily doses (LADDs). The LADD takes the form . of the Equation 1-1 with lifetime replacing averaging time. The LADD is a very common term used in carcinogen risk assessment where linear non-threshold models are employed. The total exposure can be expressed as follows: Total Potential Dose ' .C x IR x ED Where: C = Contaminant Concentration IR = Intake Rate ED = Exposure Duration (Eqn. 1-2) Contaminant concentration is the concentration of the contaminant in the medium (air, food, soil, etc.) contacting the body and has units of mass/volume or mass/mass.
The intake rate refers to the rates of inhalation, ingestion, and dermal contact depending on the route of exposure. For ingestion, the intake rate is simply the amount Exposure Factors Handbook August 1997 Volume I -General Factors EFH Chapter 1 -Introduction of food containing the contaminant of interest that an individual ingests during some specific time period (units of mass/time).* Much of this handbook is devoted to rates of* ingestion for some broad classes of food. For inhalation, the intake rate is the rate at which contaminated air is inhaled. Factors that affect dermal exposure are the amount of material that comes into contact with the skin, and the rate at which the contaminant is absorbed. The exposure duration is the length of time that contaminant contact lasts. The time a person lives in an area, frequency of bathing, time spent indoors versus outdoors, etc. all affect the exposure duration. The Activity' Factors Chapter (Volume Ill, Chapter 15) gives some examples of population behavior patterns, which may be useful for estimating exposure durations to be used in the exposure calculations. When the above parameter values remain constant over time, they are substituted directly into the exposure equation. When they change with time, a summation approach is needed to calculate exposure. In either case, the exposure duration is the length of time exposure occurs at the concentration and intake rate specified by the other parameters in the equation. Dose can be expressed as a total amount (with units of mass, e.g., mg) or as a dose rate in terms of mass/time (e.g., mg/day), or as a rate normalized to body mass (e.g., with units of mg of chemical per kg *of body weight per day (mg/kg-day)). The LADD is usually expressed in terms of mg/kg-day or other mass/mass-time units. In most cases (inhalation and ingestion exposure) the dose-response parameters for carcinogen risks have been adjusted for the difference in absorption across body barriers between humans and the experimental animals used to derive such parameters. Therefore, the exposure assessment in these cases is based on the potential dose with no explicit correction for the fraction absorbed. However, the exposure assessor needs to make such an adjustment when cc;ilculating dermal exposure and in other specific cases when current information indicates that the human absorption factor used in the derivation of the dose-response factor is inappropriate. The lifetime value used in the LADD version of Equation 1-1 is the period of time over which the dose is averaged. For carcinogens, the derivation of the dose-response parameters usually assumes no explicit number of years as the duration of a lifetime, and* the nominal value of 75 years is considered a reasonable approximation. For exposure estimates to be used for assessments other than carcinogenic risk, various averaging periods have been used. For acute exposures, th.e administered doses are usually averaged over a day or a single event. For nonchronic non cancer effects, the time period used is the actual period of exposure. The objective in selecting the exposure averaging time is to express the exposure in a way which can be combined with the dose-response relationship to calculate risk. Exposure Factors Handbook Augrist 1997 EFH Volume I-General Factors Chapter 1 -Introduction The body weight to be used in the exposure Equation 1-1 depends on the units of the exposure data presented in this handbook. For food ingestion, the body weights of the surveyed populations were known in the USDA surveys and they were explicitly factored into the food intake data in order to calculate the intake as grams per day per kilogram body weight. In this cas.e, the*body weight has already been included in the "intake rate" term in Equation 1-2 and the exposure assessor does not need to explicitly include body weight. The units of intake in this handbook for the ingestion of fish, breast milk, and the inhalation of air are not normalized to body weight. In this case, the exposure assessor needs to use (in Equation 1-1) the average weight of the exposed population during the time when the exposure actually occurs. If the exposure occurs continuously throughout an individual's life or only during the adult ages, using an adult weight of 71.8 kg should provide sufficient accuracy. If the body weight of the individuals in the population whose r.isk is being evaluated is non-standard in some way, such as for children or for generation immigrants who may be smaller than the national population, and if reasonable values are not available in the literature, then a model of intake as a function of body weight must be used. One such model is discussed in Appendix 1 A of this chapter. Some of the parameters (primarily concentrations) used in estimating exposure are exclusively site specific, and therefore default recommendations could not be used. The food ingestion rate values provided in this handbook are generally expressed as "as consumed" since this is the fashion in which data are reported by survey respondents. This is of importance because concentration data to be used in the dose equation are generally measured in uncooked food samples. In most situations, the only practical choice is to use the "as consumed" ingestion rate and the uncooked concentration. However, it should be recognized that cooking generally results in some reductions in weight (e.g., loss of moisture), and that if the mass of the contaminant in the food remains constant, then the' concentration of the contaminant in the cooked food item will increase. Therefore, if the "as consumed" ingestion rate and the uncooked concentration are used in the dose equation, dose may be underestimated. On the other hand, cooking may cause a reduction in mass of contaminant and other ingredients such that the overall concentration of contaminant does not change significantly. In this case, combining* cooked ingestion rates and uncooked concentration will provide an appropriate estimate of dose. Ideally, food concentration data should be adjusted to account for changes after cooking, then the "as consumed" intake rates are appropriate. In the absence of data, it is reasonable to assume that no change in contaminant concentration occurs after cooking. Except for general population fish consumption and home produced foods, uncooked intake rate data were not available for presention in this handbook. Data on the general population fish consumption have been presented in this handbook (Section 10.2) in both "as consumed" and uncooked basis. It is important for the assessor to be aware Exposure Factors Handbook August 1997 Volume I -General Factors EFH Chapter 1 -Introduction of these issues and choose intake rate data that best matches the concentration data that is being used. The link between the intake rate value and the exposure duration value is a common source of confusion in defining exposure scenarios. It is important to define the duration estimate so that it is consistent with the intake rate: The intake rate can be based on an in,dividual event, such as 129 g of fish eaten per meal (U.S. EPA, 1996). The duration should be based on the number of events or, in this case, meals. The intake rate also can be based on a long-term average, such as 10 g/day. In this case the duration should be based on the total time interval over which the exposure occurs. The objective is to define the terms so that when multiplied, they give the appropriate estimate of mass of contaminant contacted. This can be accomplished by basing the intake rate on either a long-term average (chronic exposure) or an event (acute basis, as long as the duration value is selected appropriately. Consider the case in which a person eats a 129-g fish meal approximately five times per month (long-term average is 21.5 g/day) for 30 years; or 21.5 g/day of fish every day for 30 years. (129 g/meal)(5 meals/mo)(mo/30 d)(365 d/yr)(30 yrs) = 235,425 g (21.5 g/day)(365 d/yr)(30 yrs) = 235,425 g Thus, a frequency of either 60 meals/year or a duration of 365 days/year could be used as long as it is matched with the approp.riate intake rate. 1.5. RESEARCH NEEDS In an earlier draft of this handbook, reviewers were asked to identify factors or areas where further research is needed. The following list is a compilation of areas for future research identified by the peer reviewers and authors of this document:
The data and information available with respect to occupational exposures are quite limited. Efforts need to be directed to identify data or references on occupational exposure. Further research is necessary to refine estimates of fish consumption, particularly by subpopulations of subsistence fishermen. Exposure Factors Handbook August 1997

( EFH Volume I -General Factors Chapter 1 -Introduction

Research is needed to better estimate soil intake rates, particularly how to extrapolate short-term data to chronic exposures. Data on soil intake rates by adults are very limited. Research in this area is also recommended. Research is also needed to refine methods to calculate soil intake rate (i.e., inconsistenci_es among tracers and input/output misalignment errors indicate a fundamental problem with the methods). Research is also needed to obtain more data to better estimate soil adherence. In cases where several studies of equal quality and data collection procedures are available for an exposure factor, procedures need to be developed to combine the data in order to create a single distribution of likely values for that factor. Reviewers recommended that the handbook be made available in CD ROM and that the data presented be made available in a format that will allow the users to conduct their own analysis. The intent is to provide a comprehensive factors tool with interactive menu to guide users to areas of interest, word searching features, and data base files. *
Reviewers recommended that EPA derive distribution functions using the empirical data for the various exposure factors to be used in Monte Carlo or other probabilistic analysis.
Research is needed to derive a methodology to extrapolate from short-term data to long-term or chronic exposures.
Reviewers recommended that the consumer products chapter be expanded to include more products. A comprehensi'V'e literature search needs to be conducted to investigate other sources of data.
Breastmilk intake.
More recent data on tapwater intake.
SAB recommended analysis of 1994 and 1995 CSFll data. Exposure Factors Handbook August 1997 \

Volume I-General Factors EFH Chapter 1 -Introduction 1.6. ORGANIZATION The handbook is organized into three volumes as follows: Volume 1-General Factors Chapter 1 Chapter 2 Chapter 3 Chapter 4 Chapter 5 Chapter 6 Chapter 7 *Chapter 8 Volume II -Ingestion Factors Chapter 9 Chapter 10 Chapter 11 Exposure Factors Handbook Provides the overall introduction to the handbook. Presents an analysis of uncertainty and discusses methods that can be used to evaluate and present the uncertainty associated with exposure scenario estimates. Provides factors for estimating human exposure . through ingestion of water. Provides factors for estimating exposure through ingestion of soil. Provides factors for estimating exposure as a result of inhalation of vapors and particulates. Presents factors for estimating dermal exposure to environmental contaminants that come in contact with the skin. Provides data on body weight. Provides data on life expectancy. Provides factors for estimating exposure through ingestion of fruits and vegetables. Provides factors for estimating exposure through ingestion offish. Provides factors for estimating exposure through ingestion of meats and dairy products. Auwst 1997 EFH Chapter 12 Chapter 13 Chapter 14 Volume Ill -Activity Factors Chapter 15 Chapter 16 Chapter 17 Volume I -General Factors Chapter 1 -Introduction Presents data for estimating exposure through ingestion of grain products. Presents factors for estimating exposure through ingestion of home produced food. Presents data for estimating exposure through ingestion of breast milk. Presents data on activity factors (activity patterns, population mobility, and occupational mobility). Presents data on consumer product use. Presents factors used in estimating residential exposures. Figure 1-2 provides a roadmap to assist users of this handbook in locating recommended values and confidence ratings for the various exposure factors presented in these chapters. A glossary is provided at the end of Volume Ill. Exposure Factors Handbook August 1997 Volume I -General Factors EFH Appendix JA APPENDIX 1A RISK CALCULATIONS USING EXPOSURE FACTORS HANDBOOK DATA AND DOSE-RESPONSE INFORMATION FROM THE INTEGRATED RISK INFORMATION SYSTEM (IRIS) Exposure Factors Handbook August 1997 Volume I -General Factors EFH Appendix JA APPENDIX 1A RISK CALCULATIONS USING EXPOSURE FACTORS HANDBOOK DATA AND DOSE-RESPONSE INFORMATION FROM IRIS 1. INTRODUCTION When calculating risk estimates for a specific population, whether the entire national population or some sub-population, the exposure information (either from this handbook or from other data) must be combined with dose-response information. The latter typically comes from the IRIS data base, which summarizes toxicity data for each agent separately. Care must be taken that the assumptions about population parameters in the response analysis are consistent with the population parameters used in the exposure analysis. This Appendix discusses procedures for insuring this consistency. In the IRIS derivation of threshold based dose-response relationships (U.S. EPA, 1996), such as the RfD and the RfCs based on adverse systemic effects, there has generally been no explicit use of human exposure factors. In these cases the numerical value of the RfD and RfC comes directly from animal dosing experiments (and occasionally from human studies) and from the application of uncertainty factors to reflect issues such as the duration of the experiment, the fact that animals are being used to represent. humans and the quality of the study. However in developing cancer dose-response (D-R) assessments, a standard exposure scenario is assumed in calculating the slope factor (i.e., human cancer risk per unit dose) on the basis of either animal bioassay data or human data. This standard scenario has traditionally been assumed to be typical of the U.S. population: 1) body weight= 70 kg; 2) air intake rate= 20 m3/day; 3) drinking water intake = 2 liters/day; 4) lifetime= 70 years. In RfC derivations for cases involving an adverse effect on the respiratory tract, the air intake rate of 20 m3/day is assumed. The use of these specific values has depended on whether the slope factor was derived from animal or human epidemiologic data:

Animal Data: For dose-resopnse (D-R) studies based on animal data, scale animal doses to human equivalent doses using a human body weight assumption of 70 kg. No explicit lifetime adjustment is necessary because the assumption is made that events occurring in the lifetime anir:nal bioassay will occur with equal probability in a human lifetime, whatever that might happen to be.
Human Data -In the analysis of human studies (either occupational or general population), the Agency has usually made no explicit assumption of body weight or human lifetime. For both of these parameters there is an implicit assumption Exposure Factors Handbook August 1997 Appendix JA EFH Volume I-General Factors that the population usually of interest has the same descriptive parameters as the population analyzed by the Agency. In the rare situation where this assumption is known to be wrong, the Agency has made appropriate corrections so that the dose-response parameters represent the national average population.
When the population of interest is different than the national average (standard) population, the dose-response parameter needs to be adjusted. In addition, when the population of interest is different than the population from which the exposure factors in this handbook were derived, the exposure factor needs to be adjusted. Two generic examples of situations where these adjustments are needed are as follows: A) Detailed study of recent data, such as are presented in this handbook, show that EPA's standard assumptions (i.e., 70 kg body weight, 20 m3/day air inhaled, and 2 L/day water intake) are inaccurate for the national population and may be inappropriate for populations under consideration. The handbook addresses most of these situations by providing gender-and age-specific values and by normalizing the intake values to body weight when the data are available, but it may not have covered all possible situations .. An example of a sub-population with a different mean body weight would be females, with *an average body weight of 60 kg or children with a body weight dependent on age. Another example of a non-standard sub-population would be a sedentary hospital population with lower than 20 m3/day air intake rates. B) The population variability of these parameters is of interest and it is desired to estimate percentile limits of the population variation. Although the detailed methods for estimating percentile limits of exposure and risk in a population are beyond the scope of this document, one would treat the body weight and the intake rates discussed in Section$ 2 to 4 of this appendix as distributions, rather than constants. ""--2. CORRECTIONS FOR DOSE-RESPONSE PARAMETERS The correction factors for the dose-response values tabulated in the IRIS data base for carcinogens are summarized in Table 1A-1. Use of these correction parameters is necessary to avoid introducing errors into the risk analysis. The second column of Table 1A-1 shows the dependencies that have been assumed in the typical situation where the human dose-response factors have been derived from the administered dose in animal studies. This table is applicable in most cases that will be encountered, but it is not applicable when: a) the effective dose has been derived with a pharmacokinetic model and b) the dose-response data has been derived from human data. In the former case, the subpopulation need to be incorporated into the model. In the latter case, the correction factor for the dose-response parameter must be evaluated on a case-by case basis by examining the specific data and assumptions in the derivation of the parameter. Exposure Factors Handbook . August 1997 Volume I -General Factors *EFH Appendix JA As one example of the use of Table 1A-1, the recommended value for the average consumption of tapwater for* adults in the U. S. population derived in this document* (Chapter 3), is 1.4 liters per day. The drinking water unit risk for dichlorvos, as given in the IRIS information data base is 8.3 x 10-6 per µg/I, and was calculated from the slope factor assuming the standard intake, lw5, of 2 liters per day. For the United States population drinking 1.4 liters of tap water per day the corrected drinking water unit risk should be 8.3 x 1 o-6 x (1.4/2) = 5.8 x 1 o-6 per µg/I. The risk to the average individual is then estimated by multiplying this by the average concentration in units of µgll. Another example is when the risk for women drinking water contaminated with dichlorvos is to be estimated. If the women have an average body weight of 60 kg, the correction factor for the drinking water unit risk is (disregarding the correction discussed in the above paragraph), from Table 1A-1, is (70/60)213 = 1.11. Here the ratio of 70 to 60 is raised to the power of 2/3 .. The corrected water unit risk for dichlorvos is 8.3 x 1 o-6 x 1.11 = 9.2 x 1 o-6 per µg/I. As before, the risk to the average individual is estimated by multiplying this by the water concentration. When human data are used to derive the risk measure, there is a large variation in the different data sets encountered in IRIS, so no generalizations can be made about global corrections. However, the typical default exposure values used for the air intake of an air pollutant over an occupational lifetime air intake is 10 m3/day for an 8-hour shift, 240 days per year with 40 years on the job. If there is continuous exposure to an
ambient air pollutant, the lifetime dose is usually calculated assuming a 70-year lifetime. 3. CORRECTIONS FOR INTAKE DATA When the body weight, WP, of the population of interest differs from the body weight, WE, of the population from which the exposure values in this handbook were derived, the following model furnishes a reasonable basis for estimating the intake of food and air (and probably water also) in the population of interest. Such a model is needed in the absence of data on the dependency of intake on body size. This occurs for inhalation data, where the intake data are not normalized to body weight, whereas the model is not needed for food and tap water intakes if they are given in units of intake per kg body weight. The model is based on the dependency of metabolic oxygen consumption on body size. Oxygen consumption is directly related to food (calorie) consumption and air intake and indirectly to water intake. For mammals of a wide range of species sizes (Prosser and Brown, 1961 ), and also for individuals of various sizes within a species, the oxygen consumption and calorie (food) intake varies as the body weight raised to a power between 0.65 and 0.75. A value of 0.667-= 2/3 has been used in EPA as the default value for Exposure Factors Handbook August 1997 EFH Volume I-General Factors Appendix JA adjusting cross-species intakes, and the same factor has been used for intra-species intake adjustments. [NOTE: Following discussions by an interagency task force (Federal Register, 1992), . the agreement was that a more accurate and defensible default value would be to choose the power to 3/4 rather than 2/3. A recent article (West et al., 1997) has provided a theoretical basis for the 3/4 power scaling. This will be the standard value to be used in future assessments, and all equations in this Appendix will be modified in future risk assessments. However, because risk assessors now use the current IRIS information, this discussion is presented with the previous default assumption of 2/3]. With this model, the relation between the daily air intake in the population of interest, I/= (m3/dayt, and the intake in the population described in this handbook, IA E = (m3/day)E is: 4. CALCULATION OF RISKS FOR AIR CONTAMINANTS The risk is calculated by multiplying the IRIS air unit risk, corrected as described in Table 1A-1, by the air concentration. But since the correction factor involves the intake in the population of interest (I/), that quantity must be included in the equation, as follows: (Riskt= (air unit riskt x (air concentration) = (air unit risk)5 x (1//20) x (70/WP)213 x (air concentration) = (air unit risk)5 x [( 1/ x (WP/WE)213/20)] x (70/WP)213 x (air concentration) = (air unit risk)5 x (IA E/20) x (70/WE)213 x (air concentration) In this equation the air unit risk from the IRIS data base (air unit risk)5, the air intake data in the handbook for the populations where it is available (IA E) and the body weight of that population (WE) are included along with the standard IRIS values of the air intake (20 m3/day) and body weight (70 kg). For food ingestion and tap water intake, if body weight-normalized intake values from this handbook are used, the intake data do not have to be corrected as in Section 3 above. in these cases, corrections to the dose-response parameters in Table 1A-1 are sufficient. Exposure Factors Handbook August 1997 Volume I-General Factors EFH ApeendixlA 5. REFERENCES Federal Register. (1992) Cross-species scaling factor for carcinogen risk assessments based on equivalence of (mg/kg-day)314* Draft report. Federal Register, 57(109): 24152-24173, June 5, 1992. Prosser, C.L.; Brown, F.A. (1961) Comparative Animal physiology, 2nd edition. WB Saunders Co. p. 161. U.S. EPA. (1996) Background Documentation. Integrated Risk Information System (IRIS). Online. National Center for Environmental Assessment, Cincinnati, Ohio. Background Documentation available from: Risk tnformation Hotline, National Center for Environmental Assessment, U.S. EPA, 26 W. Martin Luther King Dr. Cincinnati, OH 45268. (513) 569-7254 West, G.B.; Brown, J.H.; Enquist, B.J. (1997) A general model of the origin of allometric scaling laws in biology. Science 276:122-126. Exposure Factors Handbook August 1997 Table 1-1. Considerations Used to Rate Confidence in Recommended Values CONSIDERATIONS HIGH CONFIDENCE LOW CONFIDENCE Study Elements Level of peer review The studies received high level of peer The studies received limited peer review. review (e.g., they appear in peer reyiew journals). Accessibility The studies are widely available to the The studies are difficult to obtain (e.g., draft public. reports, unpublished data). Reproducibility The results can be reproduced or The results cannot be reproduced, the methodology can be followed and methodology is hard to follow, and the evaluated. author(s) cannot be located. Focus on factor of interest The studies focused on the exposure factor The purpose of the studies was to of interest. characterize a related factor. Data pertinent to U.S. The studies focused on the U.S. The studies focused on populations outside population. the U.S. Primary data The studies analyzed primary data. The studies are based on secondary sources. Currency The data were published after 1 g90. The data were published before 1980. Adequacy of data collection period The study design captures the The study design does not very accurately measurement of interest (e.g .. , usual capture the measurement of interest.
consumption patterns of a population). Validity of approach The studies used the best methodology There are serious limitations with the available to capture the measurement of approach used. interest. Study sizes The sample size is greater than 100 samples. The sample size is less than 20 samples. The sample size depends on how the target population is defined. As the size of a sample relative to the total size of the target population increases, estimates are made with greater statistical assurance that the sample results reflect actual characteristics of the target population. Representativeness of the population The study population is the same as The study population is very different from population of interest. the population of interest.* Variability in the population The studies characterized variability in the The characterization *af variability is limited. population studied. Lack of bias in study design Potential bias in the studies are stated or The study design introduces biases in the (a high rating is desirable) can be determined from the study design. results. Response rates In-person interviews The response rate is greater than 80 The response rate is less tha.n 40 percent. Telephone interviews percent. The response rate is less than 40 percent. Mail surveys The response rate is greater than 80 The response rate is less than 40 percent. percent. The respnose rate is greater than 70 percent. Measurement error The study design minimizes measurement Uncertainties with the data exist due to errors. measurement error. Other Elements Number of studies The number of studies is greater than 3. The number of studies is 1. Agreement betwee*n researchers The results of studies from different The results of studies from different researchers are in ameement. researchers are in disaqreement.
Differences include aoe, sex, race, income, or other demoqraohic parameters.

Table 1-2. Summary of Exposure Factor Recommendations and Confidence Ratings EXPOSURE FACTOR RECOMMENDATION CONFIDENCE RATING Drinking water intake rate 21 ml/kg-day/1 .4 Uday (average) Medium 34 mlfkg-day/2.3 Uday (90th percentile) Medium Percentiles and distribution also included Means and percentiles also included for pregnant and lactating women Total fruit intake rate 3.4 g/kg-day ( per capita average) Medium 12.4 g/kg-day (per capita 95th percentile) Low Percentiles also included Means presented for individual fruits Total vegetable intake rate 4.3 g/kg-day (per capita average) Medium 10 gfkg-day (per capita 95th percentile) Low Percentiles also included Means presented for individual vegetables Total meat intake rate 2.1 g/kg-day ( per capita average) Medium 5.1 g/kg-day (per capita 95th percentile) Low Percentiles also included Percentiles also presented for individual meats Total dairy intake rate 8.0 g/kg-day (per capita average) Medium 29.7 g/kg-day (per capita 95th percentile) Low Percentiles also included Means presented for individual dairy products Grain intake 4.1 g/kg-day (per capita average) High 10.8 g/kg-day (per capita 95th percentile) Low in long-term upper percentiles Percentiles also included Breast milk intake rate 742 ml/day (average) Medium 1,033 ml/day (upper percentile) Medium Fish intake rate General Population 20.1 g/day (total fish) average High 14.1 g/day (marine) average High 6.0 g/day (freshwater/estuarine)average High 53 g/day (total fish) 95th percentile long-term Medium Percentiles also included Serving size High 129 g (average) High 326 g (95th percentile) Recreational marine anglers Medium 2 -7 g/day (finfish only) Recreational freshwater Medium 8 g/day (average) Medium 25 g/day (95th percentile) Native American Subsistence Population Medium 70 g/day (average) Low 170 a/dav 195th nercentile) Table 1-2: Summary of Exposure Factor Recommendations and Confidence Ratings (continued) EXPOSURE FACTOR RECOMMENDATION CONFIDENCE RATING Home produced food intake Total Fruits Medium (for means and short-2.7 g/kg-day (consumer only average)° term distributions) 11.1 g/kg-day (consumer only 95th percentile) Low (for long-term distributions) Percentiles also included Total vegetables 2.1 (consumer only average) 7.5 g/kg-day (consumer only 95th percentile) Percentiles also included Total meats 2.2 g/kg-day (consumer only average) 6.8 g/kg-day (consumer only 95th percentile) Percentiles also included Total dairv products 14 g/kg-day (consumer only average) 44 g/kg-day (consumer only 95th percentile) Percentiles also included Inhalation rate Children (<1 year) High 4.5 m3/day (average) Children (1-12 years) High 8.7 m3/day (average) Adult Females High 11.3 m3/day (average) Adult Males High 15.2 m3/day (average) Surface area Water contact (bathing and swimming) High Use total body surface area for children in Tables 6-6 through 6-8; for adults use Tables 6-2 through 6-4 (percentiles are included) Soil contact (outdoor activities) High Use whole body part area based on Table 6-6 through 6-8 for children and 6-2 through 6-4 for adults (percentiles are included) Soil adherence Use values presented in Table 6-16 depending on Low activity and body part (central estimates only) Soil ingestion rate Children Medium 100 mg/day (average) 400 mg/day (upper percentile) Adults Low 50 mg/day (average) Pica child Low 10 g/day Life expectancy 75 years High Body weight for adults 71.8 kg High Percentiles also presented in tables 7-4 and 7-5 Body weights for children Use values presented in Tables 7-6 and 7-7 (mean High and percentiles) Body weights for infants (birth to 6 Use values presented in Table 7-1 (percentiles) High months\ Table 1-2. Summary of Exposure Factor Recommendations and Confidence Ratings (continued) EXPOSURE FACTOR RECOMMENDATION CONFIDENCE RATING Showering/Bathing Showering time High 10 min/day (average) 35 min/day (95th percentile) (percentiles are also included) Bathing time High 20 min/event (median)

45 min/event (90th percentile) Bathing/showering frequency High 1 shower event/day Swimming Frequency High 1 event/mo nth Duration High 60 min/event (median) 180 min/event (9oth percentile) Time indoors Children (ages 3-11) Medium 19 hr/day (weekdays) 17 hr/day (weekends) Adults (ages 12 and older) Medium 21 hr/day Residential High 16.4 hrs/day Time outdoors Children (ages 3-11) Medium 5 hr/day (weekdays) 7 !ir/day (weekends) Adults Medium 1.5 hr/day Residential High 2 hrs/day Time spent inside vehicle Adults 1 hr 20 min/day Medium Occupational tenure 6.6 years (16 years old and older) High Population mobility *9 years (average) Medium 30 years (95th percentile) Medium Residence volume 369 m' (average) Medium 217 m3 (conservative) Medium Residential air exchange 0.45 (median) Low 0.18 I conservative) Low Table 1-3. Characterization of Variability in Exposure Factors Exposure Factors Average Upper percentile Multiple Percentiles Fitted Distributions Drinking water intake rate T T T T Total fruits and total vegetables intake T T T rate Qualitative discussion for long-tenn Individual fruits and individual vegetables T intake rate Total meats and dairy products intake T T T rate Qualitative discussion for long-tenn Individual meats and dairy products T intake rate Grains intake T T T Breast milk intake rate T T Fish intake rate for general population, T T recreational marine, recreational freshwater, and native american Serving size for fish T T T Homeproduced food intake rates T T T Soil intake rate T Qualitative discussion for long-tenn Inhalation rate T T Surface area T T T Soil adherence T Life expectancy T Bodyweight T T T Time indoors T Time outdoors T Showering time T T T Occupational tenure T Population mobility T T T Residence volume T Residential air exchange T Table 1A-1. Procedures for Modifying IRIS Risk Values for Non-standard Populations**b IRIS Risk Measure [Units] Slope Factor [per mg/(kg/day)] Water Unit Risk [per µg/I] Air Unit Risk: A. Particles or aerosols [per µg/m3], air concentration by weight Air Unit Risk: B. Gases [per parts per million], air concentration by volume,
W = Body weight (kg) lw = Drinking water intake (liters per day) IA= Air intake (cubic meters per day) IRIS Risk Measure is Proportional to:b (Ws)113 = (?0)113 No explicit proportionality to body weight or air intake is assumed. b W5, lw5*, IA5 denote standard parameters assumed by IRIS 0 Modified risk measure= (CF) x IRIS value WP, lwP* I/ denote non-standard parameters of the actual population Correction Factor (CF) for modifying IRIS Risk Measures:0 1.0 ppm by volume is assumed to be the effective dose in both animals and humans.

Potential Dose Mouth Intake Applied Dose G.l. Tract Uptake Internal Dose Metabolism I I Biologically Effective Dose + Organ Figure 1-1. Schematic of Dose and Exposure: Oral Route Source: U.S. EPA, 1992a Effect Figure 1-2. Road Map to Exposure Factor Recommendations RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION/ RATINGS TABLE Ingestion Inhalation Dermal (All Routes) Human Characteristics (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics Figure 1-2. Road Map to Exposure Factor Recommendations 1 RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION /RATINGS TABLE Drinking Water Intake Rate Ingestion Fruit and Vegetable Intake Rate Meat and Dairy Intake Rate Homegrown Foods Breast milk Intake Rate Inhalation Dermal (All Routes) Human Characteristics (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics Fish and Shellfish Intake Rate ' Soil Intake Rate Grain Intake Figure 1-2. Road Map to Exposure Factor Recommendations RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION/ RATINGS TABLE Ingestion Inhalation Dermal (All Routes) Human Characteristics (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics Drinking Water Intake Rate Children Pregnant Women High Activity Fruit and Vegetable Intake Rate Meat and Dairy Intake Rate Fish and Shellfish Intake Rate Soil Intake Rate Grain Intake 3 3.6/3-35 Figure 1-2. Road Map to Exposure Factor Recommendations ' RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION t RA TINGS TABLE Ingestion Inhalation Dermal (All Routes) Human Characteristics (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics Drinking Water Intake Rate Fruit and Vegetable Intake Rate Various Demographic Groups -Age, Meat and Dairy Intake Rate Region, Season, Urbanization, Race Fish and Shellfish Intake Rate Soil Intake Rate Grain Intake II 9 9.3/9-30 Figure 1-2. Road Map to Exposure Factor Recommendations RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION /RATINGS TABLE Drinking Water Intake Rate Fruit and Vegetable Intake Rate Various Demographic Groups -Age, Meat and Dairy Intake Rate ------Region, Season, Urbanization, Race L&:2::::::__----Homegrown Foods Ingestion Breast milk Intake Rate Inhalation Dermal (All Routes) Human Characteristics (All Routes) Activity Factors (All Routes) Consumer Produc\ Use (All Routes) Residential Building Characteristics Fish and Shellfish Intake Rate Soil Intake Rate Grain Intake II 11 11.4/11-31 F 12 R dM t E * *

F R ndations RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION/ RATINGS TABLE Inhalation Dermal (All Routes) Human Characteristics (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics Drinking Water Intake Rate Fruit and Vegetable Intake Rate Fish and Shellfish Intake Rate Soil Intake Rate Grain Intake II 13 13.5/13-72 Figure 1-2. Road Map to Exposure Factor Recommendations RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION/ RA TINGS TABLE Drinking Water Intake Rate Fruit and Vegetable Intake Rate Meat and Dairy Intake Rate 1 f Homegrown Foods nges ion Breast milk Intake Rate------Inhalation Dermal (All Routes) Human Characteristics (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics Fish and Shellfish Intake Rate Soil Intake Rate Grain Intake Nursing Infants II 14 14.6/14-14 Figure 1-2. Road Map to Exposure Factor Recommendations RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION/ RA TINGS TABLE Drinking Water Intake Rate Fruit and Vegetable Intake Rate Meat and Dairy Intake Rate Homegrown Foods Ingestion Breast milk Intake Rate Inhalation Dermal (All Routes) Human Characteristics (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics Fish and Shellfish Intake Rate Soil Intake Rate Grain Intake General Population Freshwater Recreational Marine Recreational Subsistence II II II II 10 10 10 10 10.10.1/10-87 10.10.3/10-89 10.10.2/10-88 10.10.4/10-90 Figure 1-2. Road Map to Exposure Factor Recommendations RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION I RA TINGS TABLE Drinking Water Intake Rate Fruit and Vegetable Intake Rate Meat and Dairy Intake Rate Homegrown Foods Ingestion Breast milk Intake Rate Fish and Shellfish Intake Rate Soil Intake Rate Grain Intake Children Adults Pica Children Various Demographic Groups -Age, Region. Season, Urbanization, Race Inhalation Dermal (All Routes) Human Characteristics (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics 4 4.7/4-21 Figure 1-2. Road Map to Exposure Factor Recommendations RE COMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION/ RATINGS TABLE Ingestion Inhalation Dermal (All Routes) Human Characteristics (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics Drinking Water Intake Rate Fruit and Vegetable Intake Rate Meat and Dairy Intake Rate Fish and Shellfish Intake Rate Soil Intake Rate Children Adults Pica Children Various Demographic Groups -Age, Region, Season, Urbanization, Race Grain Intake II 12 12.3/12-24 Figure 1-2. Road Map to Exposure Factor Recommendations RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION/ RATINGS TABLE Ingestion Inhalation . ------Inhalation Rate ==============-Children High Activity Dermal (All Routes) Human Characteristics (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics 5. 5.2.4/5-23 EXPOSURE ROUTE Ingestion Inhalation (All Routes) Human Characteristics (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics Figure 1-2. Road Map to Exposure Factor Recommendations EXPOSUREFACTOR ' *Adults *Children POPULATION VOLUME 6. 6-8/6-25 6. 6-8/6-27 Figure 1-2. Road Map to Exposure Factor RecommentJations RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION/ RA TINGS TABLE Ingestion Inhalation Dermal (All Routes) <Body Weight Human Characteristics Lifetime (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics Figure 1-2. Road Map to Exposure Factor Recommendations RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION/ RA TINGS TABLE Ingestion Inhalation Dermal Adults (All Routes) <Body Weight Human Characteristics Lifetime (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics 7 7.3f/-12 Figure 1-2. Road Map to Exposure Factor Recommendations ' RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION /RATINGS TABLE Ingestion Inhalation Dermal (All Routes) < Body Weight Human Characteristics Adults Lifetime (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics Children 8 8.2/8-3 Figure 1-2. Road Map to Exposure Factor Recommendations RE COMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION I RATINGS TABLE Ingestion Inhalation Dermal (All Routes) Human Characteristics (All Routes) Activity Factors Activity Patterns Children Mobility Adults (All Routes) Consumer Product Use (All Routes) Residential Building Characteristics Adults Population Mobility -======c= Children Ill Ill Ill 15 15 15 15.4.1/15-172 15.4.2/15-173 15.4.3/15-175 Figure 1-2. Road Map to Exposure Factor Recommendations RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION/ RA TINGS TABLE Ingestion Inhalation Dermal (All Routes) Human Characteristics (All Routes) Activity Factors (All Routes) ___ ..-----Frequency of Use Consumer Product Use Amount Used--(All Routes) Residential Building Characteristics -----'---Adults *--Adults Ill 16 16.4 Figure 1-2. Road Map to Exposure Factor Recommendations RECOMMENDATIONS EXPOSURE ROUTE EXPOSURE FACTOR POPULATION VOLUME CHAPTER SECTION I RATINGS TABLE Ingestion Inhalation Dermal (All Routes) Human Characteristics (All Routes) Activity Factors (All Routes) Consumer Product Use (All Routes) ------Water Use -Residential Air Exchange Rates -General Population Building Characteristics :---.. House Volumes -Building Characteristics Ill 17 17.6/17-32, 17-33 REFERENCES FOR CHAPTER 1 AIHC. (1994) Exposure factors sourcebook. Washington, DC: American Industrial Health Council. Calabrese, E.J.; Pastides, H.; Barnes, R.; Edwards, C.; Kostecki, P.T.; et al. (1989) How much soil do young children ingest: an epidemiologic study. In: Petroleum Contaminated Soils, Lewis Publishers, Chelsea, Ml. pp. 363-397. Gilbert, R.O. (1987) Statistica.1 methods for environmental pollution monitoring. New York: Van Nostrand Reinhold. U.S. EPA. (1983-1989) Methods for assessing exposure to chemical substances. Volumes 1-13. Washington, DC: Office of Toxic Substances, Exposure Evaluation Division. U.S. EPA. (1984) Pesticide assessment guidelines subdivision K, exposure: reentry protection. Office of Pesticide Programs, Washington, DC. EPA/540/9-48/001. Available from NTIS, Springfield, VA; PB-85-120962. U.S. EPA. (1986a) Standard scenarios for estimating exposure to chemical substances during use of consumer products. Volumes I and II. Washington, DC: Office of Toxic Substance, Exposure Evaluation Division. U.S. EPA. (1986b) Pesticide assessment guidelines subdivision U, applicator exposure monitoring. Office of Pesticide Programs, Washington, DC. EPA/540/9-87/127. Available from NTIS, Springfield, VA; PB-85-133286. U.S. EPA. ( 1987) Selection criteria for mathematical models used in exposure assessments: surface water models. Exposure Assessment Group, Office of Health and Environmental Assessment, Washington, DC. WPA/600/8-87/042. Available from NTIS, Springfield, VA; PB-88-139928/AS. U.S. EPA. (1988a) Superfund exposure assessment manual. Office of Emergency and Remedial Response, Washington, DC. EPA/540/1-88/001. Available from NTIS, Springfield, VA; PB-89-135859. U.S. EPA. ( 1988b) Selection criteria for mathematical models used in exposure assessments: groundwater models. Exposure Assessment Group, Office of Health and Environmental Assessment, Washington, DC. EPA/600/8-88/075. Available from NTIS, Springfield, VA; PB-88-248752/AS. U.S. EPA. (1989) Risk assessment guidance for Superfund. Human health evaluation manual: part A. Interim Final. Office of Solid Waste and Emergency Response, Washington, DC. Available from NTIS, Springfield, VA; PB-90-155581.

U.S. EPA. (1990) Methodology for assessing health risks associated with indirect exposure to combustor emissions. EPA 600/6-90/003. Available from NTIS, Springfield, VA; PB-90-187055/AS. U.S. EPA. (1992a) Guidelines for exposure assessment. Washington, DC: Office of Research and Development, Office of Health and Environmental Assessment. EP A/600/Z-92/001 . U.S. EPA. (1992b) Dermal exposure assessment: principles and applications. Washington, DC: Office of Health and Environmental Assessments. EPA/600/8-9/011 F. U.S. EPA. (1994) Estimating exposures to dioxin-like compounds. (Draft Report). Office of Research and Development, Washington, DC. EPA/600/6-88/005Cb. U.S. EPA. (1996) Daily average per capita fish consumption estimates based on the combined 1989, 1990, and 1999 continuing survey of food intakes by individuals (CSFll) 1989-91 data. Volumes I and II. Preliminary Draft Report. Washington, DC: Office of Water. Volume I -General Factors Chapter 2 -Variability and Uncertainty 2. VARIABILITY AND UNCERTAINTY 2.1. VARIABILITY VERSUS UNCERTAINTY 2.2. TYPES OF VARIABILITY .2.3. CONFRONTING VARIABILITY 2.4. CONCERN ABOUT UNCERTAINTY 2.5. TYPES OF UNCERTAINTY AND REDUCING UNCERTAINTY 2.6. ANALYZING VARIABILITY AND UNCERTAINTY 2.7. PRESENTING RESULTS OF VARIABILITY AND UNCERTAINTY ANALYSIS REFERENCESFORCHAPTER2 Table 2-1. Table 2-2. Table 2-3. Four Strategies for Confronting Variability Three Types of Uncertainty and Associated Sources* and Examples Approaches to Quantitative Analysis of Uncertainty Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 2 -Variability and Uncertainty 2. VARIABILITY AND UNCERTAINTY The chapters that follow will discuss exposure factors and algorithms for estimating exposure. Exposure factor values can be used to obtain a range of exposure estimates such as average, high-end and bounding estimates. It is instructive here to return to the general equation for potential Average Daily Dose (ADDP01) that was introduced in the opening chapter of this handbook: Contaminant Concentration x Intake Rate x Exposure Duration ADDpot ' Body Weight x Averaging Time ' (Eqn. 2-1) With the exception of the contaminant concentration, all parameters in the above equation are considered exposure factors and, thus, are treated in fair detail in other chapters of this handbook. Each of the exposure factors involves humans, either in terms of their characteristics (e.g., body weight) or behaviors (e.g., amount of time spent in a specific location, which affects exposure duration). While the topics of variability and uncertainty apply equally to contaminant concentrations and the rest of the exposure factors in equation 2-1, the focus of this chapter is on variability and uncertainty as they relate to exposure factors. Consequently, examples provided .in this chapter relate primarily to exposure factors, although contaminant concentrations may be used when they better illustrate the point under discussion. This chapter also is intended to acquaint the exposure assessor with some of the fundamental concepts and precepts related to variability and uncertainty, together with methods and considerations for evaluating and presenting the uncertainty associated with exposure estimates. Subsequent sections in this chapter are devoted to the following topics:

Distinction between variability and uncertainty;
Types of variability; *D Methods of confronting variability;
Types of uncertainty and reducing uncertainty;
Analysis of variability and uncertainty; and
Presenting results of variability/uncertainty analysis. Fairly extensive treatises on the topic of uncertainty have been provided, for example, by Morgan and Henrion (1990), the National Research Council (NRG, 1994) and, to a lesser extent, the U.S. EPA (1992; 1995). The topic commonly has been treated as it relates to the overall process of conducting risk assessments; because exposure Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 2 -*Variability and Uncertainty assessment is a component of risk-assessment process, the general concepts apply equally to the exposure-assessment component. 2.1. VARIABILITY VERSUS UNCERTAINTY* While some authors have treated variability as a specific type or component of uncertainty, the U.S. EPA (1995) has advised the risk assessor (and, by analogy, the exposure assessor) to distinguish between variability and uncertainty. Uncertainty represents a lack of knowledge about factors affecting exposure or risk, whereas variability arises from true heterogeneity across people, places or time. lri other words, uncertainty can lead to inaccurate or biased estimates, whereas variability can affect the precision of the estimates and the degree to which they can be generalized. Most of the data presented in this handbook concerns variability. Variability and uncertainty can complement or confound one another. An instructive analogy has been drawn by the National Research Council (NRG, 1994: Chapter 10), based on the objective of estimating the distance between the earth and the moon. Prior to fairly recent technology developments, it was difficult to make accurate measurements of this distance, resulting in measurement uncertainty. Because the moon's orbit is elliptical, the distance is a variable quantity. If only a few measurements were to be taken without knowledge of the elliptical pattern, then either of the following incorrect conclusions might be reached:
That the measurements were faulty,_ thereby ascribing to uncertainty what was actually caused by variability; or
That the moon's orbit was random, thereby not allowing uncertainty to shed light on seemingly unexplainable differences that are in fact variable and predictable. A more fundamental error in the above situation would be to incorrectly estimate the true distance, by assuming that a few observations were sufficient. This .latter pitfall treating a highly variable quantity as if it were invariant or only uncertain --is probably the most relevant to the exposure or risk assessor. Now consider a situation that relates to exposure, such as estimating the average daily dose by one exposure route --ingestion of contaminated drinking water. Suppose that it is possible to measure an individual's daily water consumption (and concentration of the contaminant) exactly, thereby eliminating uncertainty in the measured daily dose. The daily dose still has an inherent day-to-day variability, however, due to changes in the individual's daily water intake or the contaminant .concentration in water. It is impractical to measure the individual's dose every day. For this reason, the exposure assessor may estimate the average daily dose (ADD) based on a finite number Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 2 -Variability and Uncertainty of measurements, in an attempt to "average out" the day-to-day variability. The individual has a true (but unknown) ADD, which has now been estimated based on a sample of measurenients. Because the individual's true average is unknown, it is uncertain how close the estimate is to the true value. Thus, the variability across daily doses has been translated into uncertainty in the ADD. Although the individual's true ADD has no variability, the estimate of the ADD has some uncertainty. The above discussion pertains to the ADD for one person. Now consider a distribution of ADDs across individuals in a defined population (e.g., the general U.S. population). In this case, variability refers to the range and distribution of ADDs across individuals in the population. By comparison, uncertainty refers to the exposure assessor's state of knowledge about that distribution, or about parameters describing the distribution (e.g., mean, standard deviation, general shape, various percentiles). As noted by the National Research Council (NRG, 1994), the realms of variability and uncertainty have fundamentally different ramifications for science and judgment. For example, uncertainty may force decision-makers to judge how probable it is that exposures have been overestimated or underestimated for every member of the exposed population, whereas variability forces them to cope with the certainty that different individuals are subject to exposures both above and below any of the exposure levels chosen as a reference point.. 2.2. TYPES OF VARIABILITY Variability in exposure is related to an individual's location, activity, and behavior or preferences at a particular point in time, as well as pollutant emission rates and physical/chemical processes that affect concentrations in various media (e.g., air, soil, food and water). The variations in pollutant-specific emissions or processes, and in individual locations, activities or behaviors, are not necessarily independent of one another. For example; both personal activities and pollutant concentrations at a specific location might vary in response to weather conditions, or between weekdays and weekends. At a more fundamental level, three types of variability can be distinguished: Variability across locations (Spatial Variability); Variability over time (Temporal Variability); and Variability among individuals (Inter-individual Variability). Spatial variability can occur both at regional (macroscale) and local (microscale) levels. For example, fish intake rates can vary depending on the region of the country. Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 2 -Variability and Uncertainty Higher consumption may occur among populations located near large bodies of water such as the Great Lakes or coastal areas. As another example, outdoor pollutant levels
can be affected at the regional level by industrial activities and at the local level by activities of individuals. In general, higher exposures tend to be associated with closer proximity to the pollutant source, whether it be an industrial plant or related to a personal activity such as showering or gardening. In the context of exposure to airborne pollutants, the concept of a "microenvironment" has been introduced* (Duan, 1982) to denote a specific locality (e:g., a residential lot or a room in a specific building) where the airborne concentration can be treated as homogeneous (i.e., invariant) at a particular point in time. Temporal variability refers to variations over time, whether long-or short-term. Seasonal fluctuations in weather, pesticide applications, use of woodburning appliances and fraction of time spent outdoors are examples of longer-term variability. Examples of shorter-term variability are differences in industrial or personal activities on weekdays versus weekends or at different times_ of the day. Inter-individual variability can be either of two types: (1) human characteristics such as age or body weight, and (2) human behaviors such as location and activity patterns. Each of these variabilities, in turn, may be related to several underlying phenomena that vary. For example, the natural variability in human weight is due to a combination of genetic, nutritional, and other lifestyle or environmental factors. Variability arising from independent factors that combine multiplicatively generally will lead to an approximately lognormal distribution across the population, or across spatial/temporal dimensions. 2.3. CONFRONTING VARIABILITY According to the National Research Council (NRC 1994), variability can be confronted in four basic ways (Table 2-1) when dealing with science-policy questions surrounding issues such as exposure or risk assessment. The first is to ignore the variability and hope for the best. This strategy tends to work best when the variability is relatively small. For example, the assumption that all adults weigh 70 kg is likely to be correct within +/-25% for most adults. The second strategy involves disaggregating the variability in some explicit way, in order to better understand it or reduce it. Mathematical models are appropriate in some cases, as in fitting a sine wave to the annual *outdoor concentration cycle for a particular pollutant and location. In other cases, particularly those involving human characteristics or behaviors, it is easier to disaggregate the data by considering all the relevant subgroups or subpopulations. For example, distributions of body weight could be developed separately for adults, adolescents and children, and for males and females within Exposure Factors Handbook August 1997

---Volume I -General Factors Chapter 2 -Variability and Uncertainty each of these subgroups. Temporal and spatial analogies for this concept involve measurements on appropriate time scales and choosing appropriate subregions or microenvironments. The third strategy is to use the average value of a quantity that varies. Although this strategy might appear as tantamount to ignoring variability, it needs to be based on a decision that the average yalue can be estimated reliably in light of the variability (e.g., when the variability is known to be relatively small, as* in the case of adult body weight). The fourth strategy involves using the maximum or minimum value for an *exposure factor. 1.n this case, the variability is characterized by the range between the extreme values and a measure of central tendency. Thi$ is perhaps the most common method of dealing with variability in exposure or risk assessment --to focus on *one time period (e.g., the period of peak exposure), one spatial region (e.g., in close proximity to the pollutant source of concern), or one subpopulation (e.g., exercising asthmatics). As noted by the U.S. EPA (1992), when an exposure assessor develops estimates of high-end individual exposure and dose, care must be taken not to set all fact9rs to values that maximize exposure or dose --such an. approach will almost always lead to an overestimate. 2A. CONCERN ABOUT UNCERTAINTY Why should exposure assessor be concerned with uncertainty? As noted by the U.S. EPA (1992), exposure assessment can involve a broad array of information sources and analysis techniques. Even in situations where actual exposure-related measurements exist, assumptions or inferences will still be required because data are not likely to be available for all aspects of the exposure assessment. Moreover, the data that are available may be of questionable or unknown quality. Thus, exposure assessors have a responsibility to present not just numbers, but also a clear and explicit explanation of the implications and limitations of their' analyses. Morgan and Henrion (1990) provide an argument by analogy. When scientists report quantities that they have measured, they are expected to routinely report an estimate of the probable error associated with such measurements. Because uncertainties inherent in policy analysis (of which exposure assessment is a part) tend to be even greater than those in the natural sciences, exposure assessors also should be expected to report or comment on the uncertainties associated with their estimates. Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 2 -Variability and Uncertainty Addit!onal reasons for addressing uncertainty in exposure or risk assessments (U.S. EPA, 1992, Morgan and Henrion, 1990) include the following: *

Uncertain information from different sources of different quality often must be combined for the assessment;
Decisions need to be made about whether or how to expend resources to acquire additional information,;
Biases may result in so-called "best estimates" that in actuality are not very accurate; and Important factors and potential sources of disagreement in a problem can be identified. Addressing uncertainty will increase the likelihood that results of an assessment or analysis will be used in an appropriate manner. Problems rarely are solved to everyone's satisfaction, and decisions rarely are reached on the basis of a single piece of evidence. Results of prior analyses can shed light on current assessments, particularly if they are couched in the context of prevailing uncertainty at the time of analysis. Exposure assessment tends to be an iterative process, beginning with a screening-level assessment that may identify the need for more in-depth assessment. One of the primary goals of the more detailed assessment is to reduce uncertainty in estimated exposures. This objective can be achieved more efficiently if guided by presentation and discussion of factors thought to be primarily responsible for uncertainty in .prior estimates.
2.5. TYPES OF UNCERTAINTY AND REDUCING UNCERTAINTY The problem of uncertainty in exposure or risk assessment is relatively large, and can quickly become too complex for facile treatment unless it is divided into smaller and more manageable topics. One method of division (Bogen, 1990) involves classifying sources of uncertainty according to the step in the risk assessment process (hazard identification, dose-response assessment, exposure assessment or risk characterization) at which they can occur. A more abstract and generalized approach preferred by some scientists is to partition all uncertainties among the three categories of bias, randomness and true variability. These ideas are discussed later in some examples. The U.S. EPA (1992) has classified uncertainty in exposure assessment into three broad categories: 1. Uncertainty regarding missing or incomplete information needed to fully define exposure and dose (Scenario Uncertainty). . 2. Uncertainty regarding some parameter (Parameter Uncertainty). 3. Uncertainty regarding gaps in scientific theo"ry required to make predictions on the basis of causal inferences (Model Uncertainty). Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 2 -Variability and Uncertainty Identification of the sources of uncertainty in an exposure assessment is the first step in determining how to reduce that uncertainty. The types of uncertainty listed above can be further defined by examining their principal causes. Sources and examples for each type of uncertainty are summarized in Table 2-2. Because uncertainty in exposure assessments is fundamentally tied to a lack of knowledge concerning important exposure factors, strategies for reducing uncertainty necessarily involve reduction or elimination of knowledge gaps. Example strategies to reduce uncertainty include (1) collection of new data using a larger sample size, an unbiased sample design, a more direct measurement method or a more appropriate target population, and (2) use of more sophisticated modeling and analysis tools. 2.6. ANALYZING VARIABILITY AND UNCERTAINTY Exposure assessments often are developed in.a phased approach. The initial phase usually screens out the exposure scenarios or pathways that are not expected to pose much risk, to eliminate them from more detailed, resource-intensive review. level assessments typically examine exposures that would fall on or beyond the high end of the expected exposure distribution. Because screening-level analyses usually are included in the final exposure assessment, the final document may contain scenarios that differ quite markedly in sophistication, data qual.ity, and amenability to quantitative expressions of variability or uncertainty. According to the U.S. EPA (1992), uncertainty characterization and uncertainty assessment are two ways of describing uncertainty at different degrees of sophistication. Uncertainty characterization usually involves a qualitative discussion of the thought processes used to select or reject specific data, estimates, scenarios; etc. Uncertainty assessment is a more quantitative process that may range from simpler measures (e.g., ranges) and simpler analytical techniques (e.g., sensitivity analysis) to more complex measures and techniques. Its goal is to provide decision makers with information concerning the quality of an assessment, including the potential variability in the estimated exposures, major data gaps, and the effect that these data gaps have on the exposure estimates developed. A distinction between variability and uncertainty was made in Section 2.1. Although the quantitative process mentioned above applies more directly to variability and the qualitative approach more so to uncertainty, there is some degree of overlap. In general, either method provides the assessor or decision-maker with insights to better evaluate the assessment in the context of available data and assumptions. The following paragraphs describe some of the more common procedures for analyzing variability and uncertainty in exposure assessments. Principles that pertain to presenting the resl!lts of variability/uncertainty analysis are discussed in the next section. Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 2 -Variability and Uncertainty Several approaches can be used to characterize uncertainty in parameter values. When uncertainty is high, the assessor may use order-of-magnitude bounding estimates of parameter ranges (e.g., from 0.1 to 10 liters for daily water intake). Another method describes the range for each parameter including the lower and upper bounds as well as . a "best estimate" (e.g., 1.4 liters per day) determined by available data or professional judgement. When sensitivity analysis indicates that a parameter profoundly influences exposure estimates, the assessor should develop a probabilistic description of its range. If there are . enough data to support their use, standard statistical methods are preferred. If the data are inadequate, expert judgment can. be used to generate a subjective probabilistic representation. Such judgments should be developed in a consistent, well-documented manner. Morgan and Henrion (1990) and Rish (1988) describe techniques to solicit expert judgment. Most approaches to quantitative analysis examine how variability and uncertainty in values of specific parameters translate into the overall uncertainty of the assessment. Details may be found in reviews such as Cox and Baybutt (1981 ), Whitmore (1985), Inman and Helton (1988), Seller (1987), and Rish and Marnicio (1988). These approaches can generally be described (in order of increasing complexity and data needs) as: (1) sensitivity analysis; (2) analytical uncertainty propagation; (3) probabilistic uncertainty analysis; or (4) classical statistical methods (U.S. EPA 1992). The four approaches are summarized iri Table 2-3. 2.7. PRESENTING RESULTS OF VARIABILITY AND UNCERTAINTY ANALYSIS Comprehensive qualitative analysis and rigorous quantitative analysis are of little value for use in the decision-making process, if their results are not clearly presented. In this chapter, variability (the receipt of different levels of exposure by different individuals) has been distinguished from uncertainty (the lack of knowledge about the correct value for a specific exposure measure or estimate). Most of the data that are presented in this handbook deal with variability directly, through inclusion of statistics that pertain to the distributions for various exposure factors. Not all approaches historically used to construct measures or estimates of exposure have attempted to distinguish between variability and uncertainty. The assessor is advised to use a variety of exposure descriptors, and where possible, the full population distribution, when presenting the results. This information will provide risk managers with a better understanding of how exposures are distributed over the population and how variability in population activities influences this distribution. Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 2 -Variability and Uncertainty Although incomplete analysis is essentially unquantifiable as a source of uncertainty, it should not be ignored. At a minimum, the assessor should describe the rationale for excluding particular exposure scenarios; characterize the uncertainty in these decisions as high, medium, or low; and state whether they were based on data, analogy, or professional judgment. Where u.ncertainty is high, a sensitivity analysis can be used to credible upper limits on exposure by way of a series of "what if' questions. Although assessors have always used descriptors to communicate the kind of scenario being addressed, the 1992 Exposure Guidelines establish clear quantitative definitions for these risk descriptors. These definitions were established to ensure that consistent terminology is used throughout the Agency. The risk descriptors defined in the Guidelines include descriptors of individual risk and population risk. Individual risk descriptors are intended to address questions dealing with risks borne by individuals within a population, including not only measures of central tendency (e.g., average or median), but also those risks at the high end of the distribution. Population risk descriptors refer to an assessment of the extent of harm to the population being addressed. It can be either an estimate of the number of cases of a particular effect that might occur in a population (or population segment), or a description of what fraction of the population receives exposures, doses, or risks greater than a specified value. The data presented in the Exposure Factors Handbook is one of the tools available to exposure assessors to construct the various risk descriptors. However, it is not sufficient to merely present the results using different exposure descriptors. Risk managers should also be presented with an analysis of the uncertainties surrounding these descriptors. Uncertainty may be presented using simple or very* sophisticated techniques, depending on the requirements of the assessment and the amount of data available. It is beyond the scope of this handbook to discuss the mechanics of uncertainty analysis in detail. At a minimum, the assessor should address uncertaintY qualitatively by answering questions such as: What is the basis or rationale for selecting these assumptions/parameters, such as data, modeling, scientific judgment, Agency policy, "what if' considerations, etc.? What is the range or variability of the key parameters? How were the parameter* values selected for use in the assessment? Were average, median, or percentile values chosen? If other choices had been made, how would the results have differed?
What is the assessor's confidence (including qualitative confidence aspects) in the key parameters and the overall assessment? What are the quality and the extent of the data base(s) supporting the selection of the chosen values? Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 2 -Variability and Uncertainty Any exposure estimate developed by an assessor will have associated assumptions about the setting, chemical, population characteristics, and how contact with the chemical occurs through various exposure routes and pathways. The exposure assessor will need to examine many sources of information that bear either directly or indirectly on these components of the exposure assessment. In addition, the assessor will be required to make many decisions regarding the use of existing information in constructing scenarios and setting up the exposure equations. In presenting the scenario results, the assessor should strive for a balanced and impartial treatment of the evidence bearing on the conclusions with the key assumptions highlighted. For these key assumptions, one should cite data sources and explain any adjustments of the data. The exposure assessor also should qualitatively describe the rationale for selection of any conceptual or mathematical models that may have been used. This discussion should address their verification and validation status, how well they represent the situation being assessed (e.g., average versus high-end estimates), and any plausible alternatives in terms of their acceptance by the scientific community. *Table 2-2 summarizes the three types of uncertainty, associated sources,* and. examples. Table 2-3 summarizes four approaches to analyze .uncertainty quantitatively.
These are describedfurther in the 1992 Exposure Guidelines. Exposure Factors Handbook August 1997 Table 2-1. Four Strategies for Confronting Variability Strategy Example Comment Ignore variability Assume that all adults Works best when variability is small weigh 70 kg Disaggregate the Develop distributions of Variability will be smaller in each group variabilitY body weight for age/gender groups Use the average Use average body weight Can the average be estimated reliably given what value for adults is known about the variability? Use a maximum or Use a lower-end value Conservative approach --can lead to minimum value from the weight distribution unrealistically high exposure estimate if taken for all factors Table 2-2. Three Types of Uncertainty and Associated Sources and Examples Type of Uncertaintv Sources Examples Scenario Uncertainty Descriptive errors Incorrect or insufficient information Aggregation errors Spatial or temporal approximations Judgment errors Selection of an incorrect model Incomplete analysis Overlooking an important pathway Parameter Uncertainty Measurement errors Imprecise or biased measurements Sampling errors Small or unrepresentative samples Variability In time, space or activities Surrogate data Structurally-related chemicals Model Uncertainty Relationship errors Incorrect inference on the basis for correlations Modeling errors Excluding relevant variables Table 2-3. Approaches to Quantitative Analysis of Uncertainiy Approach Description Example Sensitivity Analysis Changing one input variable at a time while Fix each input at lower (then upper) bound leaving others constant, to examine effect on while holding others at nominal values (e.g., output medians) Analytical Uncertainty Propagation Examining how uncertainty in individual Analytically or numerically obtain a partial parameters affects the overall uncertainty of derivative of the exposure equation with the exposure assessment respect to each input parameter Probabilistic Uncertainty Analysis Varying each of the input variables over Assign probability density function to each various values of their respective probability parameter; randomly sample values from distributions each distribution and insert them in the exposure equation (Monte Carlo) Classical Statistical Methods Estimating the population exposure Compute confidence interval estimates for distribution directly, based on measured various percentiles of the exposure values from a representative sample distribution REFERENCES FOR CHAPTER 2 Bogen, K.T. (1990) Uncertainty in environmental health risk assessment. Garland Publishing, New York, NY. Cox, D.C.; Baybutt, P.C. (1981) Methods for uncertainty analysis. A comparative survey. Risk Anal. 1 (4):251 Duan, N. (1982) Microenvironment types: A model for human exposure to air pollution. Environ. Intl. 8:305-309. Inman, R.L.; Helton, J.C. (1988) An investigation of uncertainty and sensitivity analysis techniques for computer models. Risk Anal. 8(1 ):71-91. Morgan, M.G.; Henrion, M. (1990) Uncertainty: A guide to dealing with uncertainty in
qua.ntitative risk and policy analysis. Cambridge University Press, New York; NY. National Research Council (NRC). (1994) Science and judgment in risk assessment. National Academy Press, Washington, DC. Rish, W.R. (1988) Approach to uncertainty in risk analysis. Oak Ridge National Laboratory.* ORNL/TM-10746. Rish, W.R.; Marnicio, R.J. (1988) Review of studies related to uncertainty in risk analysis. Oak Ridge National Laboratory. ORNL/TM-10776, \. Seller, F.A. (1987) Error propagation for large errors. Risk Anal. 7(4):509-518. U.S. EPA (1992) Guidelines for exposure assessment. Washington, DC: Office of Research and Development, Office of Health and Environmental Assessment. EPA/600/2-92/001. U.S. EPA (1995) Guidance for risk characterization. Science Policy Council, Washington, DC. Whitmore, R.W. (1985) Methodology for characterization of uncertainty in exposure assessments. EP A/600/8-86/009.

Volume 1-General Factors Chapter 3 -Drinking Water Intake 3. DRINKING WATER INTAKE 3.1. BACKGROUND 3.2. KEY GENERAL POPULATION STUDIES ON DRINKING WATER INTAKE 3.3. RELEVANT GENERAL POPULATION STUDIES ON DRINKING WATER INTAKE

3.4. PREGNANT AND LACTATING WOMEN 3.5. HIGH ACTIVITY LEVELS/HOT CLIMATES 3.6. RECOMMENDATIONS REFERENCES FOR CHAPTER 3' Table 3-1. Table 3-2. Table 3-3. Table Table 3-5. Table 3-6. Table 3-7. Table 3-8. Table 3-9. Table 3-10. Table 3-11. Table 3-12. Table 3-13. Table 3-14. Table 3-15. Table 3-16. Table 3-17. Table 3-18. Table 3-19. Table 3-20. Daily Total Tapwater Intake Distribution for Canadians, by Age Group (approx. 0.20 L increments, both sexes, combined seasons) Average Daily Tapwater Intake of Canadians (expressed as milliliters per kilogram body weight) Average Daily Total Tapwater Intake of Canadians, by Age and Season (L/day)
Average Daily Total Tapwater Intake of Canadians as a Function of Level of Physical Activity at Work and in Spare Time (16 years and older, combined seasons, L/day) Average Daily Tapwater Intake by Canadians, Apportioned Among Various Beverages (both sexes, by age, combined seasons, L/day) Total Tapwater Intake (ml/day) for Both Sexes Combined Total Tapwater Intake (ml/kg-day) for Both Sexes Combined Summary of Tapwater Intake by Age Total Tapwater Intake (as percent of total water intake) by Broad Age Category General Dietary Sources of Tapwater for Both Sexes Summary Statistics for Best-Fit Lognormal Distributions for Water Intake Rates EstimatE!d Quantiles and Means for Total Tapwater Intake Rates (ml/day) Assumed Tapwater Content of Beverages Intake of Total Liquid, Total_ Tapwater, and Various Beverages (L/day)
Summary of Total Liquid and Total Tapwater Intake for Males and Fe.males (L/day) Measured Fluid Intakes (ml/day) Intake Rates of Total Fluids and Total Tapwater by Age Group Mean and Standard Error for the Daily Intake of Beverages and Tapwater by Age Average Total Tapwater Intake Rate by Sex, Age, and Geographic Area Frequency Distribution of Total Tapwater Intake Rates Exposure Factors Handbook August 1997 Table 3-21. Table 3-22. Table 3-23. Table 3-24. Table 3-25. Table 3-26. Table 3-27. Table 3-28. Table 3-29. Table 3-30. Table 3-31. Table 3-32. Table 3-33. Table 3-34. Table 3-35. Volume I -General Factors Chapter 3 -Drinking Water Intake Mean Per Capita Drinking Water Intake Based on USDA, CSFll Data From 1989-91 (ml/day) Number of Respondents that Consumed Tapwater at a Specified Daily Frequency Number of Respondents that Consumed Juice Reconstituted with Tapwater at a Specified Daily Frequency Total Fluid. Intake of Women 15-49 Years Old Total Tapwater Intake of Women 15-49 Years Old Total Fluid (ml/Day) Derived from Various Dietary Sources by Women Aged 15-49 Years Water Intake at Various Activity Levels (L/hr) Planning *Factors for Individual Tapwater Consumption Drinking Water Intake Surveys Summary of Recommended Drinking Water Intake Rates Total Tapwater Consumption Rates From Key Studies Daily Tapwater Intake Rates From Relevant Studies Key Study Tapwater Intake Rates for Children Summary of Intake Rates for Children in Relevant Studies Confidence in Tapwater Intake Recommendations Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 3 -Drinking Water Intake 3. DRINKING WATER INTAKE 3.1. BACKGROUND 'Z" .... , ,, Drinking water is a potential source -of human exposure to toxic substances. Contamination of drinking water may occur by, for example, percolation of toxics through the soil to ground water that is used as a source of drinking water; runoff or discharge to surface water that is used as a source of drinking water; intentional or unintentional addition of substances to treat water (e.g., chlorination); and leaching of materials from plumbing systems (e.g., lead). Estimating the magnitude of the potential dose of toxics from drinking water requires information on the quantity of water consumed. The purpose of this section is to describe key published studies that provide information on drinking water consumption (Section 3.2) and to provide recommendations of consumption rate values that should be used in exposure assessments (Section 3.6). Currently, the U.S .. EPA uses the quantity of 2 L per day for adults and 1 L per day for infants (individuals of 10 kg body mass or less) as default drinking water intake rates (U.S. EPA, 1980; 1991).* These rates include drinking water consumed in the form of juices and other beverages containing tapwater (e.g., coffee). The National Academy of Sciences (NAS, 1977) estimated that daily consumption of water may vary with levels of physical activity and fluctuations in temperature and humidity. It is reasonable to assume that some individuals in physically-demanding occupations or living in warmer regions may have high levels of water intake. Numerous studies cited in this chapter have generated data on drinking water intake rates. In general, these sources support EPA's use of 2 L/day for adults and 1 L/day for children as upper-percentile intake rates. Many of the studies have reported fluid intake rates for both total fluids and tapwater. Total fluid intake is defined as consumption of all types of fluids including tapwater, milk, soft drinks, alcoholic beverages, and water intrinsic to purchased foods. Total tapwater is defined as water consumed directly from the tap as a beverage or used in the preparation of foods and beverages (i.e., coffee, tea, frozen juices, soups, etc.). Data for both consumption categories are presented in the
sections that follow. However, for the purposes of exposure assessments involving source-specific contaminated drinking water, intake rates based on total tapwater are more representative of source-specific tapwater intake. . Given the assumption that purchased foods and beverages are widely distributed and less likely to contain specific water, the use of total fluid intake rates may overestimate the potential exposure to toxic substances present only in local water supplies; therefore tapwater intake, rather than total fluid intake, is emphasized in this section. Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 3 -Drinking Water Intake All studies on drinking water intake that are currently available are based on term survey data. Although short-term data may be suitable for obtaining mean intake values that are representative of both short-and long-term consumption patterns, percentile values may be different for short-term and long-term data because more variability generally occurs in short-term surveys. It should also be noted that most drinking water surveys currently available are based on recall. This may be a source of uncertainty in the estimated intake rates because of the subjective nature of this type of survey technique. The distribution of water intakes is usually, but not always, lognormal. Instead of presenting only the lognormal parameters, the actual percentile distributions are presented in this handbook, usually with a comment on whether or not it is lognormal. T_o facilitate comparisons between studies, the mean and the 90th percentiles are given for all studies where the distribution data are available. With these two parameters, along with information about which distribution is being followed, one can calculate, using standard formulas, the geometric mean and geometric standard deviation and hence any desired percentile of the distribution. Before doing such a calculation one must be sure that one of these distributions adequately fits the data. The available studies on drinking water consumption are summarized in the following sections. They have been classified as either key studies or relevant studies based on the applicability of their survey designs to exposure assessment of the entire United States population. Recommended intake rates are based on the results of key studies, but relevant studies are also presented to provide the reader with added perspective on the current state-of-knowledge pertaining to drinking water intake. 3.2. KEY GENERAL POPULATION STUDIES ON DRINKING WATER INTAKE Canada Department of Health and Welfare {1981) -Tapwater Consumption in Canada -In a study conducted by the Canadian Department of Health and Welfare, 970 individuals from 295 households were surveyed to determine the per capita total tapwater intake rates for various age/sex groups during winter and summer seasons (Canadian Ministry of National Health and Welfare, 1981 ). Intake rate was also evaluated as a function of physical activity. The population that was surveyed matched the Canadian 1976 census with respect to the proportion in different age, regional, community size and dwelling type groups. Participants monitored water intake for a 2-day period (1 weekday, and 1 weekend day) in both late summer of 1977 and winter of 1978. All 970 individuals participated in both the summer and winter surveys. The amount of tapwater consumed was estimated based on the respondents' _identification of the type and size of beverage container used, compared to standard sized vessels. The survey questionnaires included
a pictorial guide to help participants in classifying the sizes of the vessels. For example, Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 3 --Drinking Water Intake '::I:' .... ,
a small glass of water was assumed to be equivalent to 4.0 ounces of water, and a large glass was assumed to contain 9.0 ounces of water. The study also accounted for water derived from ice cubes and popsicles, and water in soups, infant formula, and juices. The survey did not attempt to differentiate between tapwater consumed at home and tapwater consumed away from home. The survey also did not attempt to estimate intake rates for fluids other than tapwater. Consequently, no intake rates for total fluids were reported. Daily consumption distribution patterns for various age groups are presented in Table 3-1. For adults (over 18 years of age) only, the average total tapwater intake rate was 1.38 L/day, and the 90th percentile rate was 2.41 L/day as determined by graphical interpolation. These data follow a lognormal distribution. The intake data for males, females, and both sexes combined as a function of age and expressed in the units of milliliters (grams) per kilogram body weight are presented in Table 3-2. The tapwater survey did not include body weights of the participants, but the body weight information was taken from a Canadian health survey dated 1981; it averaged 65.1 kg for males and 55.6 kg for females. Intake rates for specific age groups and seasons are presented in Table 3-3. The average daily total tapwater intake rates for all ages and seasons combined was 1.34 L/day, and the 90th percentile rate was 2.36 L/day. The summer intake rates are nearly the same as the winter intake rates. The authors speculate that the reason for the small seasonal variation here is that in Canada, even in the summer, the ambient temperature seldom exceeded 20 degrees C and marked increase in water consumption with high activity levels has been observed in other studies only when the ambient temperature has been higher than 20 degrees. Average daily total tapwater intake rates as a function of the level of physical activity, as estimated subjectively, are presented in Table 3-4. The amounts of tapwater consumed that are derived from various foods and beverages are presented in Table 3-5. Note that the consumption of direct "raw" tapwater is almost constant across all age groups from school-age children through the oldest ages. The increase in total tapwater consumption beyond school age is due to coffee and tea consumption. Data concerning the source of tapwater (municipal, well, or lake) was presented in one table of the study. This categorization is not appropriate for making conclusions about consumption of ground versus surface water. This survey may be more representative of total consumption than some other less comprehensive surveys because it included data for some tapwater-containing items not covered by other studies (i.e., ice cubes, popsicles, and infant formula). One potential source of error in the study is that estimated intake rates were based on identification of standard vessel sizes; the accuracy of this type of survey data is not known. The cooler climate of Canada may have reduced the importance of large tapwater intakes resulting from high activity levels, therefore making the study less applicable to the Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 3 "' Drinking Water Intake United States. The authors were not able to explain the surprisingly large variations between regional tapwater intakes; the largest regional difference was between Ontario ( 1.18 liters/day) and Quebec ( 1.55 liters/day). Ershow and Cantor {1989) -Total Water and Tapwater Intake in the United States: Population-Based Estimates of Quantities and Sources -Ershow and Cantor (1989) estimated water intake rates based on data collected by the USDA 1977-1978 Nationwide Food Consumption Survey (NFCS). Daily intake rates for tapwater and total water were calculated for various age groups for males, females, and both sexes combined. Tapwater was defined as "all water from the household tap consumed directly as a beverage or used to prepare foods and beverages." Total water was defined as tapwater plus "water intrinsic to foods and beverages" (i.e., water contained in purchased food and beverages). The authors showed that the age, sex, and racial distribution of the surveyed population closely matched the estimated 1977 U.S. population .. Daily total tapwater intake rates, expressed as ml (grams) per day by age group are presented in Table 3-6. These data follow a lognormal distribution. The same data, expressed as ml (grams) per kg body weight per day are presented in Table 3-7. A summary of these tables, showing the mean, the 10th and 90th percentile intakes, expressed as both mUday and mUkg-day as a function of age, is presented in Table 3-8. This shows that the mean and 90th percentile intake rates for adults (ages 20 to 65+) are a*pproximately 1,410 ml/day. and 2,280 ml/day and for all ages the mean and 90th percentile intake rates are 1, 190 ml/day and 2,090 ml/day. Note that older adults have greater intakes than do adults between age 20 and 65, an observation bearing on the interpretation of the Cantor, et al. (1987) study which surveyed a population that was older than the national average (see Section 3.3). Ershow and Cantor (1989) also measured total water intake for the same age groups and concluded that it averaged 2,070 ml/day for all groups combined and that tapwater intake (1, 190 mUday) is 55 percent of the total water intake. (The detailed intake data for various age groups are presented in Table 3-9). Ershow and Cantor (1989) also concluded that, for all age groups combined, the proportion of tapwater. consumed as drinking water., foods, and beverages is 54 percent, 10 percent and 36 percent, respectively. (The detailed data on proportion of tapwater consumed for various age groups are presented in Table 3-10). Ershow and Cantor (1989) also observed that males of all age groups had higher total water and tapwater consumption rates than females; the variation of each from the combined-sexes mean was about 8 percent. . ' Ershow and Cantor (1989) also presented data on total water intake and tapwater intake for children of various ages. They found, for infants and children between the ages of 6 months and 15 years, that the total water intake per unit body weight increased Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 3 -Drinking Water Intake
smoothly and sharply from 30 ml/kg-day above age 15 years to 190 ml/kg-day for ages less than 6 months. This probably represents metabolic requirements for water as a . . dietary constituent. However, they found that the intake of tapwater alone went up only slightly with decreasing age (from 20 to 45 ml/kg-day as age decreases from 11 years to less than 6 months). Ershow and Cantor (1989) attributed this small effect of age on tapwater intake to the large number of alternative water sources (besides tapwater) used for.the younger age groups. With respect to region of the country, the northeast states had slightly lower average tapwater intake (1,200 ml/day) than the three other regions (which were approximately equal at 1,400 ml/day). This survey has an adequately large (26,446 individuals) and it is a representative sample of the United States population with respect to age distribution, sex, racial composition, and residential location. It is therefore suitable as a description of national tapwater consumption. The chief limitation of the study is that the data were . collected in 1978 and do not reflect the expected increase in the consumption of soft drinks and bottled water or changes in the diet within the last two decades. Since the data were collected for only a three-day period, the extrapolation to chronic intake is uncertain. Roseberry and Burmaster (1992) -Lognormal Distributions for Water Intake -Roseberry and Burmaster (1992) fit lognormal distributions to the water intake data reported by Ershow and Cantor (1989) and estimated populatjon-wide distributions for total fluid and total tapwater intake based on proportions of the population in each age group. Their publication shows the data and the fitted log-normal distributions graphically. The mean was estimated as the zero intercept, and the standard deviation was estimated as the slope of the best fit line for the natural logarithm of the intake plotted against their corresponding z-scores (Roseberry and Burmaster, 1992). Least squares techniques were used to estimate the best fit straight lines for the transformed data. Summary statistics for the best-fit"lognormal distribution are presented in Table 3.,.11. In this table, the simulated balanced population represents an adjustment to account for the different age distribution of the United States populatio*n in 1988 from the age distribution in 1978 when Ershow and Cantor (1989) collected their data. Table 3-12 summarizes the quantiles and means of tapwater intake as estimated from the best-fit distributions. The mean total tapwater intake rates for the two adult populations (age 20 to 65 years, and 65+ years) were estimated to be 1.27 and 1.34 L/day. These intake rates were based on the data originally presented by Ershow and Cantor (1989). Consequently, the same advantages and disadvantages associated .with the Ershow and Cantor (1989) study apply to this data set. Exposure Factors Handbook August 1997

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Volume I -General Factors Chapter 3 -Drinking Water Intake 3.3. RELEVANT GENERAL POPULATION STUDIES ON DRINKING WATER INTAKE National Academy of Sciences {1977) -Drinking Water and Health -NAS (1977) calculated the average per capita water (liquid) consumption per day to be 1.63 L. This figure was based on a survey of the following literature sources: Evans ( 1941 ); Bourne and Kidder (1953); Walker et al. (1957); Wolf (1958); Guyton (1968); McNall and Schlegel (1968); Randall (1973); NAS (1974); and Pike and Brown (1975). Although the calculated average intake rate was 1.63 L per day, NAS (1977) adopted a larger rate (2 L per day) 'to represent the intake of the majority of water consumers. This value is relatively consistent with the total tapwafor intakes rate estimated from the key studies presented previously. However, the use of the term "liquid" was not clearly defined in this study, and it is not known whether the populations surveyed are representative of the adult u.s.* population. Consequently, the results of this study are of limited use in recommending total tapwater intake rates and this study is not considered a key study. Hopkins and Ellis {1980) -Drinking Water Consumption in Great Britain A study conducted in Great Britain over a 6-week period during September and October 1978, estimated the drinking water consumption rates of 3,564 individuals from 1,320 households in England, Scotland, and Wales (Hopkins and Ellis, 1980). The participants were selected randomly and were asked to complete a questionnaire and a diary indicating the type and quantity of beverages consumed over a 1-week period. Total liquid intake included total tapwater taken at home and. away from home; purchased alcoholic beverages; and non-tapwater-based drinks. Total tapwater included water content of tea, coffee, and other hot water drinks; . homemade alcoholic beverages; and tapwater consumed directly as a beverage. The assumed tapwater contents for these beverages are presented in Table 3-13. Based on responses from 3,564 participants, the mean intake rates and *frequency distribution data for various beverage categories were estimated by Hopkins and Ellis (1980). These data are listed in Table 3-14. The mean per capita total liquid intake rate for all individuals surveyed was 1.59 L/day, and the mean per capita total tapwater intake rate was 0.95 L/day, with a 90th percentile value of about 1.3 L/day (which is the value of the percentile for the home tapwater alone iri Table 3-14 ). Liquid intake rates were also estimated for males and females in various age groups. Table 3-15 summarizes the total liquid and total tapwater intake rates for 1,758 males and 1,800 females grouped into six age categories (Hopkins and Ellis, 1980). The mean and 90th percentile total tapwater intake values for adults over age 18 years.are, respectively, 1.07 L/day and 1.87 L/day, as determined by pooling data for males and females for the three adult age ranges in Table 3-15. This calculation assumes, as does Table 3-14 and 3-15, that the underlying distribution is normal and not lognormal. The advantage of using these data is that the responses were not generated on a recall basis, but by recording daily intake in diaries. The latter approach may result in Exposure Factors Handbook August1997 Volume 1-General Factors "Z" .... ,
Chapter 3 -Drinking Water Intake more accurate responses being generated. Also, the use of total liquid and total tapwater was well defined in this study. However, the relatively short-term nature of the survey make extrapolation to long-term consumption patterns difficult. Also, these data were based on the population of Great Britain and not the United States. Drinking patterns may differ among these populations as a result of varying weather conditions and economic factors. For these reasons this study is* not considered a key study in this document. International Commission on Radiological Protection (JCRP) (1981) -Report to the Task Group on Reference Man -Data on fluid intake levels have also been summarized by the International Commission on Radiological Protection (ICRP) in the Report of the Task Group on Reference Man (ICRP, 1981). These intake levels for adults and children are summarized in Table 3-16. The amount of drinking water (tapwater and water-based drinks) consumed by adults ranged from about 0.37 L/day to about 2.18 L/day under "normal" conditions. The levels for children ranged from 0.54 to 0.79 L/day. Because the populations, survey' design, and intake categories are not clearly defined, this study has limited usefulness in developing recommended intake rates for use in exposure assessment. It is reported here as a relevant study because the findings, although poorly defined, are consistent with the results of other studies. Gillies and Paulin (1983) -Variability of Mineral Intakes from Drinking Water -Gillies and Paulin (1983) conducted a study to evaluate variability of mineral intake from drinking water .. A study population of 109 adults (75females; 34 males) ranging in age from 16.to 80 years (mean age= 44 years) in New Zealand was asked to collect duplicate samples of water consumed directly from the tap or used in beverage preparation during a 24-hour period. Participants were asked to collect the samples on a day when all of the water consumed would be from their own home. Individuals were selected based on their will.ingness to participate and their ability to comprehend the collection procedures. The . mean total tapwater intake rate for this population was 1.25 (+/-0.39) L/daY., and the 90th percentile rate was 1.90 L/day. The median total tapwater intake rate (1.26 L/day) was very similar to the mean intake rate (Gillies and Paulin, 1983). The reported range was 0.26 to 2.80 L/day. The advantage of these data are that they were generated using duplicate sampling techniques. Because this approach is more objective than recall methods, it may result in more accurate response. .However, these data are based on a short-term survey that may not be representative of long-term behavior, the population surveyec;I is small and the procedures for selecting the survey population were not designed to be representative of the New Zealand population, and the results may not be applicable to the United States. For these reasons the study is not regarded as a key study in this document. Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 3 -Drinking Water Intake Pennington {1983) -Revision of the Total Diet Study Food List and Diets-Based on data from the U.S. Food and Drug Administration's (FDA's) Total Diet Study, Pennington (1983) reported average intake rates for various foods and beverages. for five age groups of the population. The Total Diet Study is conducted annually to monitor the nutrient and contaminant content of the U.S. food supply and to evaluate trends in consumption. Representative diets were developed based on 24-hour recall and 2-qay diary data from the 1977-1978 U.S. 'Department of Agriculture (USDA) Nationwide Food Consumption Survey (NFCS) and 24-hour recall data from the Second National Health and Nutrition Examination Survey (NHANES II). The number of participants in NFCS and NHANES II was approximately 30,000 and 20,000, respectively. The diets were developed to "approximate 90 percent or more of the weight of the foods usually consumed" (Pennington, 1983} The source of water (bottled water as distinguished from tapwater) was not stated in the Pennington study. For the purposes of this report, the *consumption rates for the food categories defined by Pennington (1983) were used to calculate total fluid and total water intake rates for five age groups. Total water includes water, tea, coffee;, soft. drinks, and soups and frozen juices that are reconstituted with water. Reconstituted soups were assumed to be comp<?sed of 50 percent water, and juices were assumed to contain 75 percent water. Total fluids include total water in addition to milk, _ ready-to-use infant formula, milk-based soups, carbonated soft drinks, alcoholic beverages, and canned fruit juices. These intake rates are presented in Table 3-17. Based on the average intake rates for total water for the two adult age groups, 1.04 and . 1.26 L/day, the average adult-intake rate is about 1.15 L/day. These rates should be more representative of the amount of source-specific water consumed than are total fluid intake rates. Because this study was designed to measure food intake, and it used both USDA 1978 data and NHANES II data, there was not necessarily a systematic attempt to define tapwater intake per se, as distinguished from bottled water. For this reason, it is not considered a key tapwater study in this document. U.S. EPA (1984) -An Estimation of the Daily Average Food Intake by Age and Sex for Use in Assessing the Radionuclide Intake of the General Population -Using data collected by USDA in the 1977-78 NFCS, U.S. EPA (1984) determined daily food and beverage intake levels by age to be used in assessing radionuclide intake through food consumption. Tapwater, water-based drinks, and soups were identified subcategories of the total beverage category. Daily intake rates for tapwater, water-based drinks, soup, and total beverage are presented in Table 3-18. As seen in Table 3-18, mean tapwater intake for different adult age groups (age 20 years and older) ranged from -0.62 to 0.76 L/day, . . water-based drinks intake ranged from 0.34 to 0.69 L/day, soup intake ranged from 0.03 to 0.06 L/day, and mean total beverage intake levels ranged from 1.48 to 1.73 L/day. Total tapwater intake rates were estimated by combining the average daily intakes of tapwater, water-based drinks, and soups for each age group. For adults (ages 20 years and older), mean total tapwater intake rates range from 1.04 to 1.47 L/day, and for children (ages <1 Exposure Factors Handbook August 1997

Volume I -General Factors Chapter 3 -Drinking Water Intake to 19 years), mean intake rates range from 0.19 to 0.90 L/day. These intake rates do not include reconstituted infant formula. The*total tapwater intake rates, derived by combining data on *tapwater, water-based drinks, and soup should be more representative of specific drinking water intake than the total beverage intake rates reported in this study. These intake rates are based on the same USDA NFCS data used in Ershow and Cantor (1989). Therefore, the data limitations discussed previously also apply to this study. Cantor et al. (1987) -Bladder Cancer, Drinknig Water Source, and Tapwater Consumption -The National Cancer Institute (NCI), in a population-based, case control study investigating the possible relationship between bladder cancer and drinking water, interviewed approximately 8,000 adult white individuals, 21 to 84 years of age (2,805 cases and 5,258 controls) in their homes, using a standardized questionnaire (Cantor et al., 1987). The cases and controls resided in one of five metropolitan areas (Atlanta, Detroit, New Orleans, San Francisco, and Seattle) and five States (Connecticut, Iowa, New Jersey, New Mexico, and Utah). The individuals interviewed were asked to recall the level of intake of tapwater and other beverages in a typical week during the winter prior to the

interview. Total beverage intake was divided into the following two components: 1) beverages derived from tapwater; and 2) beverages from other sources. Tapwater used in cooking foods and in ice cubes was apparently not considered. Participants also supplied information on the primary source of the water c;;onsumed (i.e., private well, community supply, bottled water, etc.). The control population was randomly selected from the general population and frequency matched to the bladder cancer case population in terms of age, sex, and geographic location of residence. The case population consisted
of Whites only, had no people under the age of 21 years and 57 percent were over the age of 65 years. The fluid intake rates for the bladder cancer cases were not used because their participation in the study was based on selection factors that could bias the intake estimates for the general population. Based on responses from 5,258 White controls (3,892 males; 1,366 females), average tapwater intake rates for a "typical" week were compiled by sex, age group, and geographic region. These rates are listed in Table 3-19. The average total fluid intake rate was 2.01 L/day for men of which 70 percent (1.4 L/day) was derived from tapwater, and 1.72 L/day for women of which 79 percent (1.35 L/day) was.derived from tapwater. Frequency distribution data for the 5,081 controls, for which the authors had information on both tapwater consumption and cigarette smoking habits, are presented in Table 3-20. These data follow a lognormal distribution having an average value of 1.30 L/day and* an upper 90th percentile value of approximately 2.40 L/day. These values were determined by graphically interpolating the data of Table 3-20 after plotting it on log probability graph paper. These values represent the usual level of intake for this population of adults in the winter. A limitation associated with. this data set is that the population surveyed was older than the general population and consisted exclusively of Whites. Also, the intake data are Exposure Factors Handbook August 1997 I I ____J Volume I -General Factors Chapter 3 -Drinking Water Intake based on recall of behavior from the winter previous to the interview. Extrapolation to other seasons and intake durations is difficult. The authors presented data on person-years of residence various types of water supply sources (municipal versus private, chlorinated versus nonchlorinated, and surface versus well water). Unfortunately, these data can not be used to draw conclusions about the National average apportionment of surface versus groundwater since a large fraction (24 percent) of municipal water intake in this survey could not be specifically attributed to either ground or surface water. AIHC (1994) -Exposure Factors Handbook -The Exposure Factors Sourcebook (AIHC, 1994) presented drinking water intake rate recommendations for adults. Although AIHC (1994) provided little information on the studies used to derive mean and UP.per percentile recom-mendations, the references indicate that several of the studies used were the same as ones categorized as relevant studies in this handbook. The mean adult drinking water recommendations in AIHC (1994) and this handbook are in agreement. However, the upper percentile value recommended by AIHC (1994) (2.0 L/day) is slightly lower than that recommended by this handbook (2.4 L/day). Based on data provided by Ershow and Cantor (1989), 2.0 L/day corresponds to only approximately the 84th percentile of the drinking water intake rate distribution. Thus, a slightly higher value is appropriate for representing the upper percentile (i.e., 90 to 95th percentile) of the* distribution. AIHC (1994) also presents simulated distributions of drinking water intake based on Roseberry and Burmaster (1992). These distributions are also described in detail in Section 3.2 of this handbook. AIHC (1994) has been classified as a relevant rather than a key study because it is not the primary source for the data used to make recommendations for this document. USDA (1995) -Food and Nutrient Intakes by Individuals in the United States, 1 Day, 1989-91. -USDA (1995) collected data on the quantity of "plain drinking water" and various other beverages consumed by individuals in 1 day during 1989 through 1991. The data were collected as part of USDA's Continuing Survey of Food Intakes by Individuals (CSFll). The data used to estimate mean per capita rates combined one-day. dietary recall data from 3 survey years: 1989, 1990, and 1991 during which 15, 128 individuals supplied one-day intake data. Individuals from all incoryie levels in the 48 conterminous states 8:nd Washington D.C. were included in the sample. A complex stage sampling design was employed and the overall response rate for the study was 58 percent. To minimize the biasing effects of the low response rate and adjust for the seasonality, a series of weighting factors was incorporated into the data analysis. The intake rates based on this study are presented in Table 3-21 .. Table 3:.21 includes data for: a) "plain drinking water", which might be assumed to mean tapwater directly consumed rather than bottled water; b) coffee and tea, which might be assumed to be Exposure Factors Handbook August 1997

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constituted from tapwater; and 3) fruit drinks and ades, which might be assumed to be reconstituted from tapwater rather than canned products; and 4) the total of the three sources. With these assumptions, the mean per capita total intake of water is estimated to be 1,416 ml/day for adult males (i.e., 20 years of age and older), 1,288 ml/day for adult females (i.e., 20 years of age and older) and 1, 150 ml/day for all ages and both sexes combined. Although these assumptions appear reasonable, a close reading of the definitions used by USDA reveals that the word "tapwater" does not occur, and this uncertainty prevents the use of this study as a key study of tapwater intake. The advantages of using. these data are that; 1) the survey had a large sample size; 2) the authors attempted to represent the general United States population by oversampling low-income groups and by weighting the data to compensate for low response rates; and 3) it reflects more recent intake data than the key studies. The disadvantages are that: 1) the response rate was low; 2) the word "tapwater was not defined and the assumptions that must be used in order to compare the data with the other tapwater studies might not be valid; 3) the data collection period reflects only a day intake period, and may not reflect long-term drinking water intake patterns; and 4)*data on the percentiles of the distribution of intakes were not given. Tsang and Klepeis {1996) -National Human Activity Pattern Survey (NHAPS) -The U.S. EPA collected information on the number of glasses of drinking water and juice reconstituted with tapwater consumed by the general population as part of the National Human Activity Pattern Survey (Tsang and Klepeis, 1996).
NHAPS was conducted between October 1992 September 1994. Over 9,000 individuals in the 48 contiguous United States provided data on the duration*_ and frequency of selected activities and the time spent in selected microenvironments via 24-hour diaries. Over 4,000 NHAPS respondents also provided information of the number of 8-ounce glasses of water and the
number of 8-ounce glasses of juice reconstituted with water than they drank during the 24-hour survey period (Tables 3-22 and 3-23). The median number of glasses of tapwater consumed was 1-2 and the median number of glasses of juice with tapwater consumed was 1-2.
For both individuals who drank tapwater and individuals who drank juices reconstituted with tapwater, the number of glasses ranged from 1 to 20. The highest percentage of the population (37.1 percent) who drank tapwater consumed 3-5 glasses and the highest percentage of the population (51.5 percent) who. consumed juice reconstituted with tapwater drank 1-2 glasses. Based on the assumption that each glass contained 8 ounces of water (226.4 ml), the total volume of tapwater and juice with tapwater consumed would range from 0.23 L/day (1 glass) to 4.5 L/day (20 glasses) for respondents who drank tapwater. Using the same assumption, the volume of tapwater consumed for the population who consumed 3-5 glasses would be 0.68 L/day to 1.13 L/day and the volume Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 3 -Drinking Water Intake
of juice with tapwater consumed for the population who consumed 1-2 glasses would be 0.23 L/day to 0.46 L/day. Assuming that the average individual consumes 3-5 glasses of tapwater plus 1-2 glasses of juice with tapwater, the range of total tapwater intake for this individual w0.uld range from 0.9 L/day to 1.64 L/day. These values are consistent with the average intake rates observed in other studies. The advantages of NHAPS is that the data were collected for a large number of individuals and that the data are representative of the U.S. population. However, evaluation of drinking water intake rates was not the primary purpose of the study and the data do not reflect the total volume of tapwater consumed. However, using the assumptions described above, the estimated drinking water intake rates from this study are within the same ranges observed for other drinking water studies. 3.4. PREGNANT AND LACTATING WOMEN Ershowet al. (1991) -Intake of Tapwater and Total Water by Pregnant and Lactating Women-Ershowetal. (1991) used data from the 1977-78 USDA NFCS to estimate total fluid and total tapwater intake among pregnant and lactating women (ages 15-49 years). Data for 188 pregnant women, 77 lactating women, and 6,201 non-pregnant, non-lactating control women were evaluated. The participants were interviewed based on 24 hour recall, and then asked to record a food diary for the next 2 days. "Tapwater" included tapwater consumed directly as a beverage and tapwater used to prepare food. and tapwater-based beverages. Total water" was defined as all water from tapwater and tapwater sources, including water contained in food. Estimated total fluid and total tapwater intake rates for the three groups are presented in Tables 3-24 and 3-25, respectively. Lactating women had the highest mean total fluid intake rate (2.24 L/day) compared with both pregnant women (2.08 L/day) and control women (1.94 L/day). Lactating women also had a higher mean total tapwater intake rate (1.31 L/day) than pregnant women (1.19 L/day) and control women (1.16 L/day). The tapwater distributions are neither normal nor lognormal, but lactating women had a higher mean tapwater intake than controls and pregnant women. Ershow et al. (1991) also reported that rural women (n=1,885) consumed more total water (1.99 L/day) and tapwater (1.24 L/day) than urban/suburban women (n=4,581, 1.93 and 1 :13 L/day, respectively). Total water and tapwater intake rates were lowest in the northeastern region of the United States (1.82 and 1.03 L/day) and highest in the western region of the United States (2.06 L/day and 1.21 L/day). Mean intake per unit body weight was highest among lactating women for both total fluid and total tapwater intake. Total tapwater intake accounted for over 50 percent of mean total fluid in all three groups of women (Table 3-25). Drinking water accounted for the largest single proportion of the total fluid intake for control (30 percent), pregnant . (34 percent), and lactating women (30 percent) (Table 3-26). All other beverages combined accounted for approximately 46 percent, 43 percent, and 45 percent of the total Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 3 -Drinking Water Intake water intake for control, pregnant, and lactating women, respectively. Food accounted for . the remaining portion of total water intake. The same advantages and limitations assoeiated with the Ershow and Cantor ( 1989) data also apply to these data sets (Section 3.2). A further advantage of this study. is that it provides information on estimates of total waterand tapwater intake rates for pregnant and lactating women. This topic has rarely been addressed in the literature. 3.5. HIGH ACTIVITY LEVELS/HOT CLIMATES McNall and Schlegel {1968) -Practical Thermal Environmental Limits for Young Adult Males Working in Hot, Humid Environments -McNall and Schlegel (1968) conducted a study that evaluated the physiological tolerance of adult males working under varying degrees of physical activity. Subjects were required to pedal pedal-driven propeller fans for 8-hour work cycles under varying environmental conditions. The activity pattern for each individual was: cycled at 15 minute pedalling and 15 miute rest for each 8-hour period. Two groups of eight subjects each were used. Work rates were divided into three categories as follows: high activity level [0.15 horsepower (hp) per person], medium activity level (0.1 hp per person), and low activity level (0.05 hp per person). Evidence of physical stress (i.e., increased body temperature, blood pressure, etc.) was recorded, and individuals were eliminated from further testing if certain stress criteria were met. The amount of water consumed by the test subjects during the work cycles was also recorded. Water was provided to the individuals on request. The water intake rates obtained .at the three different activity levels and the various environmental temperatures are presented in Table 3-27. The data presented are for test subjects with continuous data only (i.e., those test subjects who were not eliminated at any stage of the study as a result of stress conditions). Water intake was the highest at all activity levels when environmental temperatures were increased. The highest intake rate was observed at the low activity level at 100°F (0.65 L/hour) however, there were no data for higher activity levels at 100 ° F. It should be noted that this study estimated intake on an hourly basis during various levels of physical activity. These hourly intake rates cannot be converted to daily intake rates by multiplying by 24 hours/day because they are only representative of intake during the specified activity levels and the intake rates for the rest of the day are .not known. Therefore, comparison of intake rate values from this study cannot be made with values from the previously described studies on drinking water intake: United States Army {1983) -Water Consumption Planning Factors Study-The U.S. Army has developed water consumption planning factors to enable them to transport an adequate amount of water to soldiers in the field under various conditions (U.S. Army; 1983). Both climate and activity levels were use9 to determine the appropriate water consumption needs. Consumption factors have been established for the following uses: Exposure Factors Handbook August 1997 I Volume I -General Factors Chapter 3 -Drinking Water Intake 1) drinking, 2) heat treatment, 3) personal hygiene, 4) centralized hygiene, 5) food preparation, 6) laundry, 7) medical treatment, 8) vehicle and aircraft maintenance, 9) graves registration, and 10) construction. Only personal drinking water consumption factc;>rs are described here. Drinking water consumption planning factors are based on the estimated amount of water needed to replace fluids lost by urination, perspiration, and respiration. It assumes that water lost to urinary output averages one quart/day (0.9 L/day) and perspiration losses range from almost nothing in a controlled environment to 1.5 quarts/day (1.4 L/day) in a very hot climate where individuals are performing strenuous work. Water losses to respiration are typically very low except in extreme cold where water losses can range from 1 to 3 quarts/day (0.9 to 2.8 L/day). This occurs when the humidity of inhaled air is near zero, but expired air is 98 percent saturated at body temperature (U.S. Army, 1983). Drinking water is defined by the U.S. Army (1983) as "all fluids consumed by individuals to satisfy body needs for internal water." This includes soups, hot and cold drinks, and tapwater. Planning factors have been established for hot, temperate, and cold climates based on the following mixture of activities among the work force: 15 percent of the force performing light work, 65 percent of the force performing medium work, and 20 percent of the force performing heavy work. Hot climates are defined as tropical and arid areas where the temperature is greater than 80°F. Temperate climates are defined as where the mean daily temperature ranges from 32°F to 80°F. Cold regions are areas where the mean daily temperature is less than 32 ° F.. Drinking water* consumption factors for these three climates are presented in Table 3-28. These factors are based on research on individuals and small unit training exercises. The estimates are assumed to be conservative because they are rounded up to account for the subjective nature of the activity mix and minor water losses that are not considered (U.S. Army, 1983). The advantage of using these data is that they provide a conservative estimate of drinking water intake among individuals performing at various levels of physical activity in hot, temperate, and cold climates. However, the planning factors described here are based on assumptions about water loss from urination, perspiration, and respiration, and are not based on survey data or actual measurements. 3.6. RECOMMENDATIONS The key studies described in this section were used in selecting recommended drinking water (tapwater) consumption rates for adults and children. The studies on other subpopulations were not classified* as key versus relevant. Although different survey designs and populations were utilized by key and relevant studies described in this report, the mean and upper-percentile estimates reported in these studies are reasonably similar. The general design of both key and relevant studies and their limitations are summarized in Table 3-29. It should be noted that studies that surveyed large representative samples Exposure Factors Handbook August 1997 Volume I-General Factors Chapter 3 -Drinking Water Intake of the population provide more reliable estimates of intake rates for the general population. Most of the surveys described here are based on short-term recall which may be biased toward excess intake rates. However, Cantor et al. (1987) noted that refrospective dietary. assessments generally produce moderate correlations with "reference data from the past."
A summary of the recommended values for drinking water intake rates is preserited in Table 3-30. Adults -The total tapwater consumption rates for adults (older than 18 *or 20 years) that have been reported in the key surveys can be* summarized in Table 3-31. For comparison, values for daily tapwater intake for the relevant studies are shown in Table 3-32. Note that both Ershow and Cantor ( 1989) and Pennington ( 1983) found that adults above 60 years of age had larger intakes than younger adults. This is difficult to reconcile with the Cantor et al. (1987) study because the latter, older population had a smaller average intake. Because of these results, combined with the fact that the Cantor et al. (1987) study was not intended to be representative of the U. S. population, it is not included here in the determination of the recommended value. The USDA ( 1995) data are not included because tapwater was not defined in the survey and because the response rate was low, although the results (showing lower intakes than the studies based on older data) may be accurately reflecting an expected lower use of tapwater (compared to 1978) because of increasing use of bottled water and soft drinks in recent years. A value of 1.41 L/day, which is the population-weighted mean of the two national studies (Ershow and Cantor, 1989 and Canadian Ministry of Health and Welfare, 1981) is the recommended average tapwater intake rate. The average of the 90th percentile values from the same two studies (2.35 L/day) is recommended as the appropriate upper limit.* (The commonly-used 2.0 L/day intake rate corresponds to the 84th percentile of the intake rate distribution among the adults in the Ershow and Cantor (1989) study). In keeping with the desire to incorporate body weight . into exposure assessments without introducing extraneous errors, the values from the Ershow and Cantor (1989) study (Tables 3-7 arid 3-8) expressed as ml/kg-day are recommended in preference to the liters/day u.nits. For adults, the mean and 90th percentile values are 21 and 34.2 ml/kg/day, respectively. In the absence of actual data on chronic intake, the values in the previous paragraph are recommended as chronic values, although the chronic 90th upper percentile may. very well be larger than 2.35 L/day. If a mathematical description of the intake distribution is needed, the parameters of lognormal fit tq the Ershow and Cantor (1989) data (Tables 3-11 and 3-12). generated by Roseberry and Burmaster (1992) may be used. The Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 3 -Drinking Water Intake simulated balanced population distribution of intakes generated by Roseberry and Burmaster is not recommended for use in th.e post-1997 time frame, since it corrects the 1978 data only for the differences in the age structure of the U.'S. population between 1978 and 1988. These recommended values are different than the 2 liters/day commonly assumed in EPA risk assessments. Assessors are encouraged to use values which most accurately reflect the exposed population. When using values other than 2 liters/day, however, the assessors should consider if the dose estimate will be used to
estimate risk by combining with a dose-response relationship which was derived assuming a tap water intake of 2 liters/day. If such an inconsistency exists, the assessor should adjust the dose-response relationship as described in Appendix 1 of Chapter 1-. IRIS does not use a tap water intake assumption in the derivation of RfCs and RfDs, but does make the 2 liter/day assumption in the derivation of cancer slope factors and unit risks. Children -The tapwater intake rates for children reported in the key studies are summarized in Table 3-33. The intake rates, as expressed as liters per*day, generally increase with age, and the data are consistent across ages for the two key studies except for the Canadian Ministry of Health and Welfare (1981) data for ages 6 to 17 years; it is recommended that any of the liters/day values that match the age range of interest except the Canada data for ages 6 to 17 years be used. The ml/kg-day intake values show a consistent downward trend with increasing ages; using the Ershow and Cantor ( 1989) data in preference to the Canadian Ministry of National Health and Welfare (1981) data is recommended where the age ranges overlap .. The intakes for children as reported in the relevant studies are shown in Table 3-34. Disregarding the Roseberry and Burmaster study, which is a recalculation of the Ershow and Cantor (1989) study, the non-key studies generally have lower mean intake values than the Ershow and Cantor (1899) study. The reason is not known, but the results are not persuasive enough to discount the recommendations based on the latter study. Intake rates for specific percentiles of the distribution may be selected using the lognormal distribution data generated by Roseberry and Burmaster (1992) (Tables 3-11 and 3-12). Pregnant and Lactating Women -The data on tapwater intakes for control, pregnant, and lactating women are presented in Table 3-25. The recommended intake values are presented in Table 3-30. High Activity/Hot Climates -Data on intake rates for individuals performing strenuous activities under various environmental conditions are limited*. None of these is classed as a key study because the populations in these studies are not representative of the general . U.S. population. However, the data presented by McNall and Schlegel (1968) and U.S. Army*(1983) provide bounding intake values for these individuals. According to McNall Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 3 -Drinking Water Intake and Schlegel (1968), hourly intake can range from 0.21 to 0.65 L/hour depending on the temperature and activity level. Intake among physically active individuals can range from 6 L/day in temperate climates to 11 L/day_ in hot climates (U.S. Army, 1983). A characterization of the overall confidence in the accuracy and appropriateness of the recommendations for drinking water is presented in Table 3-35. Although the study of Ershow.and Cantor (1989) is of high quality and consistent with the other surveys, the low currency of the information (1978 data collection), in the presence of anecdotal information (not presented here) that the consumption of bottled water and beverages has increased since 1980 was the main reason for lowering the confidence score of the overall recommendations from high to medium. Exposure Factors Handbook August 1997 Table 3-1. Daily Total Tapwater Intake Distribution for Canadians, by Age Group (approx. 0.20 L increments, both sexes, combined seasons) Age Group (years) Amount Consumed" 5 and under 6-17 18 and over Uday % Number % Number % Number 0.00 -0.21 11.1 9 2.8 7 0.5 3 0.22 -0.43 17.3 14 10.0 25 1.9 12 0.44 -0.65 24.8 20 13.2 33 5.9 38 0.66 -0.86 9.9 8 13.6 34 8.5 54 0.87 -1.07 11.1 9 14.4 36 13.1 84 1.08 -1.29 11.1 9 14.8 37 14.8 94 1.30 -1.50 4.9 4 9.6 24 15.3 98 1.51 -1.71 6.2 5 6.8 17 12.1 77 1.72-1.93 1.2 1 2.4 6 6.9 44 1.94-2.14 1.2 1 1.2 3 5.6 36 2.15 -2.36 1.2 1 4.0 10 3.4 22 2.37-2.57 0 0.4 1 3.1 20 2.58 -2.79 0 2.4 6 2.7 17 2.80-3.00 0 2.4 6 1.4 9 3.01 -3.21 0 0.4 1 1.1 7 3.22 -3.43 0 0 0.9 6 3.44-3.64 0 0 0.8 5 3.65 -3.86 0 0 0 >3.86 0 1.6 4 2.0 13 TOTAL 100.0 81 100.0 250 100.0 639 Includes tapwater and foods and beverages derived from tapwater. Source: Canadian Ministry of National Health and Welfare, 1981.

Table 3-2. Average Daily Tapwater Intake of Canadians (expressed as milliliters per kilogram body weight) Average Daily Intake (ml/kg) Age Group (years) Females Males Both Sexes <3 53 35 45 3-5 49 48 48 6-17 24 27 26 18-34 23 19 21 35-54 25 19 22 55+ 24 21 22 Total Population 24 21 22 Source: Canadian Ministry of National Health and Welfare, 1981. . ' Table 3-3. Average Daily Total Tapwater Intake of Canadians, by Age and Season (Uday)" Age (years) <3 3-5 6-17 18-34 35-54 :::_55 All Ages Average Summer 0.57 0.86 1.14 1.33 1.52 1.53 1.31 Winter 0.66 0.88 1.13 1.42 1.59 1.62 1.37 Summer/Winter 0.61 0.87 1.14 1.38 1.55 1.57 1.34 90th Percentile Summer/Winter 1.50 1.50 2.21 2.57 2.57 2.29 2.36 a Includes tapwater and foods and beverages derived from tapwater. Source: Canadian Ministrv of National Health and Welfare, '1981. L Table 3-4. Average Daily Total Tapwater Intake of Canadians as a Function of Level of Physical Activity at Work and in Spare Time (16 years and older, combined seasons, Uday) Work Spare Time Activity Consumptionb Number of Respondents Consumptionb Number of Respondents Level* Uday Uday Extremely Active 1.72 99 1.57 52 Very Active 1.47 244 1.51 151 Somewhat Active 1.47 217 1.44 302 Not Very Active 1.27 67 1.52 131 Not At All Active 1.30 16 1.35 26 Did Not State 1.30 45 1.31 26 TOTAL 688 688 a The levels of physical activity listed here were not defined any further by the survey report, and categorization of activity level by survey participants is assumed to be subjective. b Includes tapwater and foods and beverages derived from tapwater. Source: Canadian Ministry of National Health and Welfare, 1981. Table 3-5. Average Daily Tapwater Intake by Canadians, Apportioned Among Various Beverages (both sexes, by age, combined seasons, Uday)" Age Groug (years} Under 3 3-5 6-17 18-34 35-54 55 and Over Total Number in Group 34 47 250 232 254 153 Water 0.14 0.31 0.42 0.39 0.38 0.38 Ice/Mix 0.01 0.01 0.02 0.04 0.03 0.02 Tea

0.01 0.05 0.21 0.31 0.42 Coffee 0.01
0.06 0.37 0.50 0.42 "Other Type of Drink" 0.21 0.34 0.34 0.20 0.14 0.11 Reconstituted Milk 0.10 0.08 0.12 0.05 0.04 0.08 Soup 0.04 0.08 0.07 0.06 0.08 0.11 Homemade Beer/Wine *
0.02 0.04 0.07 0.03 Homemade Popsicles 0.01 0.03 0.03 0.01 *
Baby Formula, etc. 0.09 * * * ..
TOTAL 0.61 0.86 1.14 1.38 1.55 1.57 a Includes tapwater and foods and beverages derived from tapwater.
Less than 0.01 Uday Source: Canadian Ministrv of National Health and Welfare, 1981.

Table 3-6. Total Tapwater Intake (ml/day) for Both Sexes Combined" Percentile Distribution Number of S.E. of Age{years) Observations Mean SD Mean 1 5 10 25 50 75 90 95 99 <0.5 182 272 247 18 . 0 *o 80 240 332 640 800 . 0.5 -0.9 221 328 265 18 . 0 0 117 268 480 688 764 . 1-3 1498 646 390 10 33 169 240 374 567 820 1162 1419 1899 4-6 1702 742 4Q6 10 68 204 303 459 660 972 1302 1520 1932 7-10 2405 787 417 9 68 241 318 484 731 1016 1338 1556 1998 11 -14 2803 925 521 10 76 244 360 561 838 1196 1621 1924 2503 15 -19 2998 999 593 11 55 239 348 587 897 1294 1763 2134 2871 20-44 7171 1255 709 8 105 337 483 766 1144 1610 2121 2559 3634 45 -64 4560 1546 723 11 335 591 745 1057 1439 1898 2451 2870 3994 65 -74 1663 1500 660 16 301 611 766 1044 1394 1873 2333 2693 3479 75+ 878 1381 600 20 279 568 728 961 1302 1706 2170 2476 3087 Infants (ages <1 )" 403 302 258 13 0 0 0 113 240 424 649 775 1102 Children (ages 1-10) 5605 736 410 5 56 192 286 442 665 960 1294 1516 1954 Teens (ages 11-19) 5801 965 562 7 67 240 353 574 867 1246 1701 2026 2748 Adults (ages 20-64) 11731 1366 728 7 148 416 559 870 1252 1737 2268 2707 3780 Adults (ages 65+) 2541 1459 643 13 299 598 751 1019 1367 1806 2287 2636 3338 All 26081 1193 702 4 80 286 423 690 1081 1561 2092 2477 3415 a Total tapwater is defined as "all water from the household tap consumed directly as a beverage or used fo prepare foods and beverages." . Value not reported due to insufficient number of observations. Source: Ershow and Cantor, 1989. Table 3-7. Total Tapwater Intake (mUkg-day) for Both Sexes Combined" Number of Observations Actual Weighted S.E. of Age (years) Count Count Mean SD Mean 1 5 10. 25 50 75 90 95 99 <0.5 182 201.2 52.4 53.2 3.9

0.0 0.0 14.8 37.8 66.1 128.3 155.6
0.5 -0.9 221 243.2 36.2 29.2 -2.0
0.0 0.0 15.3 32:2 48.1 69.4 102.9
1 -3 1498 1687.7 46.8 28.1 0.7 2.7 11.8 17.8 27.2 41.4. 60.4 82.1 101.6 -140.6 4-6 1702 1923.9 37.9 21.8 0.5 3.4 10.3 14.9 21.9 33.3 48.7 69.3 81.1 103.4 7 -10 2405 2742.4 26.9 15.3 0.3 2.2 7.4 10.3 16.0 24.0 35.5 47.3 55.2 70.5 11 -14 2803 3146.9 20.2 11.6 0.2 1.5 4.9 7.5 11.9 18.1 26.2 35.7 41.9 55.0 15 -19 2998 3677.9 16.4 9.6 0.2 1.0 3.9 5.7 9.6 14.8 21.5 29.0 35.0 46.3 20-44 7171 13444.5 18.6 10.7 0.1 1.6 4.9 7.1 11.2 16.8 23.7 _32.2 38.4 53.4 45-64 4560 8300.4 22.0 10.8 0.2 4.4 8.0 .10.3 14.7 20.2 27.2 35.5 42.1 57.8 65-74 1663 2740.2 21.9 9.9 0.2 4,6 8.7 10.9 15.1 20.2 27.2 35.2 40.6 51.6 75+ 878 1401.8 21.6 9.5 -0.3 3.8 8.8 10.7 15.0 20.5 27.1 33.9 38.6 47.2 Infants (ages <1) 403 444.3 43.5 42.5 2.1 0.0 0.0 0.0 15.3 35.3 54.7 101.8 126.5 220.5 Children (ages 1-10) 5605 6354.1 35.5 22.9 0.3 2.7 8.3 12.5 19.6 30.5 46.0 64.4 79.4 113.9 Teens (ages 11-19) 5801 6824.9 18.2 10.8 0.1 1.2 4.3 6.5 10.6 16.3 23.6 32.3 38.9 52.6 Adults (ages 20-64) 11731 21744.9 19.9 10.8 0.1 2.2 5.9 8.0 12.4 18.2 25.3 33.7 40.0 54.8 Adults (ages 65+) 2541 4142.0 21.8 9.8 0.2 4.5 8.7 10.9 15.0 20.3 27.1 34.7 40.0 51.3 All 26081 39510.2 22.6 15.4 0.1 1.7 5.8 8.2 13.0 19.4 28.0 39.8 50.0 79.8 a Total tapwater is defined as "all water from the household tap consumed directly as a beverage or used to prepare foods and beverages."
Value not reported due to insufficient number of observations. Source: Ershow and Cantor, 1989.

Table 3-8. Summarv ofTaowater Intake by Aoe Age Group Intake (mUday) Intake (mUkg-day) Mean 1 Oth-90th Percentiles Mean 1 oth-9oth Percentiles Infants (<1 year) 302 0-649 43.5 0-100 Children (1-10 years) 736 286-1,294 35.5 12.5 -64.4 Teens (11-19 years) 965 353-1,701 18.2 6.5 -32.3 Adults (20 -64 years) 1,366 559-2,268 19.9 8.0 -33.7 Adults (65+ years) 1,459 751-2,287 21.8 10.9 -34.7 All ages 1,193 423-2,092 22.6 8.2 -39.8 Source: Ershow and Cantor (1989) Table 3-9. Total Tapwater Intake (as percent of total water intake) by Broad Age Category"*b Percentile Distribution Age (years) Mean 1 5 10 25 50 75 90 95 99 <1 26 0 0 0 12 22 37 55 62 82 1-10 45 6 19 24 34 45 57 67 72 81 11-19 47 6 18 24 35 47 59 69 74 83 20-64 59 12 27 35 49 61 72 79 83 90 65+ 65 25 41 47 58 67 74 81 84 90 a Does not include pregnant women, lactating women, or breast-fed children. b Total tapwater is defined as "all water from the household tap consumed directly as a beverage or used to prepare foods and beverages." 0 = Less than 0.5 percent. Source: Ershow and Cantor, 1989. Table 3-10. General Dietary Sources of Tapwater for Both Sexes*,b % of Tapwater Age (years) Source Standard Mean Deviation 5 25 50 75 95 99 <1 Food' 11 24 0 0 0 10 70 100 Drinking Water 69 37 0 39 87 100 100 100 Other Beverages 20 33 0 0 0 22 100 100 All Sources 100 1-10 Food' 15 16 0 5 10 19 44 100 Drinking Water 65 25 0 52 70 84 96 100 Other Beverages 20 21 0 0 15 32 63 93 All Sources 100 11-19 Food' 13 15 0 3 8 17 38 100 Drinking Water 65 25 0 52 70 85 98 100 Other Beverages 22 23 0 0 16 34 68 96 All Sources 100 20-64 Food' 8 10 0 2 5 11 25 49 Drinking Water 47 26 0 29 48 67 91 100 Other Beverages 45 26 0 25 44 63 91 100 All Sources 100 65+ Food' 8 9 0 2 5 11 23 38 Drinking Water 50 23 0 36 52 66 87 99 Other Beverages 42 23 3 27 40 57 85 100 All Sources 100 All Food' 10 13 0 2 6 13 31 64 Drinking Water 54 27 0 36 56 75 95 100 Other Beverages 36 27 0 14 34* 55 87 100 All Sources 100 a Does not include pregnant women, lactating women, or breast-fed children. b Individual values may not add to totals due to rounding. c Food category includes soups. 0 = Less than 0.5 percent. Source: Ershow and Cantor, 1989. Table 3-11. Summary Statistics for Best-Fit Lognormal Distributions for Water Intake Ratesa Group In Total Fluid Intake *Rate (age in years) µD oD R2 0 <age <1 1 ,;; age <11 11 ,;; age <20 20,;; age <65 65,;; age All ages Simulated balanced population Group (age in years) 0 <age <1 1 ,;; age <11 11 ,;; age <20 20,;; age <65 65,;; age All ages Simulated balanced population 6.979 7.182 7.490 7.563 7.583 7.487 7.492 µD 5.587 6.429 6.667 7.023 7.088 6.870 6.864 0.291 0.340 0.347 0.400 0.360 0.405 0.407 In Total Tapwater Intake oD 0.615 0.498 0.535 0.489 0.476 0.530 0.575 0.996 0.953 0.966 0.977 0.988 0.984 1.000 0.970 0.984 0.986 0.956 0.978 0.978 0.995 a These value-s (mUday) were used in the following equations to estimate the quantiles and averages for total tapwater intake shown in Tables 3-12. 97.5 percentile intake rate= exp [u + (1.96 *a)] 75 percentile intake rate= exp [u + (0.6745 *a)] 50 percentile intake rate = exp [u] 25 percentile intake rate= exp [u -(0.6745

o)] 2.5 percentile intake rate= exp [u -(1.96 *a)] Mean intake rate -exp [u + 0.5
o2)] Source: Roseberry and Burmaster, 1992.

Table 3-12. Estimated Quantiles and Means for Total Tapwater Intake Rates (mUday)" Age Group Percentile Arithmetic (years) 2.5 25 50 75 97.5 Average O <age< 1 80 176 267 404 891 323 1,;age<11 233 443 620 867 1,644 701 11 ,; age< 20 275 548 786 1,128 2,243 907 20,; age< 65 430 807 1,122 1,561 2,926 1,265 65,; age 471 869 1,198 1,651 3,044 1,341 All ages 341 674 963 1,377 2,721 1,108 Simulated Balanced Population 310 649 957 1.411 2,954 1,129 a Total tapwater is defined as "all water from the household tap consumed directly as a beverage or used to prepare foods and beverages." Source: Roseberry and Burmaster, 1992 Table 3-13. Assumed Tapwater Content of Beverages Beverage Cold Water Home-made Beer/Cider/Lager Home-made Wine Other Hot Water Drinks Ground/Instant Coffee:a Black White Half Milk .All Milk Tea Hot Milk Cocoa/Other Hot Milk Drinks Water-based Fruit Drink Fizzy Drinks Fruit Juice 1b Fruit Juice 2b Milk Mineral Water0 Bought cider/beer/lager Bouaht Wine * "% Tapwater 100 100 100 100 100 80 50 0 80 0 0 75 0 0 75 0 0 0 0 a Black -coffee with all water, milk not added; White -coffee with 80% water, 20% milk; Half Milk .: coffee with 50% water, 50% milk; All Milk -coffee with all milk, water not added; b Fruit juice: individuals were asked in the questionnaire if they consumed ready-made fruit juice (type 1 above), or the variety that is diluted (type 2);

c Information on volume of mineral water consumed was obtained only as "number of bottles per week." A bottle was estimated at 500 ml, and the volume was split so that 2/7 was assumed to be consumed on weekends, and 5/7 during the week. Source: Hookins and Ellis 1980.

Table 3-14. Intake ofTotal Liquid, Total Tapwater, and Various Beverages (Uday) All Individuals Consumers Only' Beverage Approx. 95% Approx. 95% Confidence Percentage of Mean Approx. Confidence Mean Approx. Std. Interval for 10 and 90 1 and 99 Total Number Intake Std. Error Interval for Mean Intake Error of Mean Mean Percentiles Percentiles of Individuals of Mean Total Liquid 1.589 0.0203 1.547-1.6;;!9 0.77-2.57 0.34-4.50 100.0 1.589 0.0203 1.547-1.629 Total Liquid Home 1.104 0.0143 1.075-1.133 0.49-1.79 0.23-3.10 100.0 1.104 0.0143 1.075-1.133 Total Liquid Away 0.484 0.0152 0.454-0.514 0.00-1.15 0.00-2.89 89.9 0.539 0.0163 0.506-0.572 Total Tapwater 0.955 0.0129 0.929-0.981 0.39-1.57 0.10-2.60 99.8 0.958 0.0129 0.932-0.984 Total Tapwater Home 0.754 0.0116 0.731-0.777 0.26-1.31 0.02-2.30 99.4 0.759 0.0116 0.736-0.782 Total Tapwater Away 0.201 0.0056 0.190-0.212 0.00-0.49 0.00-0.96 79.6 0.253 0.0063 0.240-0.266 Tea 0.584 0.0122 0.560-0.608 . 0.01-1.19 0.00-2.03 90.9 0.643 0.0125 0.618-0.668 Coffee 0.190 0.0059 0.178-0.202 0.00-0.56 0.00-1.27 63.0 0.302 0.0105 0.281-0.323 Other Hot Water 0.011 0.0015 0.008-0.014 0.00-0.00 0.00-0.25 9.2 0.120 0.0133 0.093-0.147 Drinks Cold Water 0.103 0.0049 0.093-0.113 0.00-0.31 0.00-0.85 51.0 0.203 0.0083 0.186-0.220 Fruit Drinks 0.057 0.0027 0.052-0.062 0.00-0.19 0.00-0.49 46.2 0.123 0.0049 0.113-0.133 Non Tapwater 0.427 0.0058 0.415-0.439 0.20-0.70 0.06-1.27 99.8 0.428 0.0058. 0.416-0.440 Home-brew 0.010 0.0017 0.007-0.013 0.00-0.00 0.00-0.20 7.0 0.138 0.0209 0.096-0.180 Bought Alcoholic 0.206 0.0123 0.181-0.231 0.00-0.68 0.00-2.33 43.5 0.474 0.0250 0.424-0.524 Beveraaes a Consumers only is defined as only those individuals who reported consuming the beverage during the survey period. Source: Hopkin and Ellis, 1980. Table 3-15. Summary of Total Liquid and Total Tapwater Intake for Males and Females (Uday) Number Mean Intake Approx. Std. Error .of Approx 95% Confidence 1 O and 90 Percentiles Beverage Age Mean Interval for Mean Group (years) Male Female Male Female Male Female Male Female Male Female 1-4 88 75 0.853 0.888 0.0557 0.0660 0.742-0.964 0.756-1.020 0.38-1.51 0.39-1.48 5-11 249 201 0.986 0.902 0.0296 0.0306 0.917-1.045 0.841-0.963 0.54-1.48 0.51-1.39 Total Liquid 12-17 180 169 1.401 1.198 0.0619 0.0429 1.277-1.525 1.112-1.284 0.75-2.27 0.65-1.74 Intake 18-30 333 350 2.184 1.547 0.0691 0.0392 2.046-2.322 1.469-1.625 1.12-3.49 0.93-2.30 31-54 512 551 2.112 1.601 0.0526 0.0215 2.007-2.217 1.558-1.694 1.15-3.27 0.95-2.36 55+ 396 454 1.830 1.482 0.0498 0.0356 1.730-1.930 1.411-1.553 1.03-2.77 0.84-2.17 1-4 88 75 0.477 0.464 0.0403 0.0453 0.396-0.558 0.373-0.555 0.17-0.85 0.15-0.89 5-11 249 201 0.550 0.533 0.0223 0.0239 0.505-0.595 0.485-0.581 0.22-0.90 0.22-0.93 Total 12-17 180 169 0.805 0.725 0.0372 0.0328 0.731-0.8790 0.659-0.791 0.29-1.35 0.31-1.16 Tapwater Intake 18-30 333 350 1.006 0.991 0.0363 0.0304 0.933-1.079 0.930-1.052 0.45-1.62 0.50-1.55 31-54 512 551 1.201 1.091 0.0309 . 0.0240 1.139-1.263 1.043-1.139 0.64-1.88 0.62-1.68 55+ 396 454 1.133 1.027 0.0347 0.0273 1.064-1.202 0.972-1.082 0.62-1.72 0.54-1.57 Source: Hopkin and Ellis, 1980. Table 3-16. Measured Fluid Intakes (ml/dav) Water-Based Subject Total Fluids Milk Taowater Drinks* Adults ("normal" conditions)b 1000-2400 120-450 45-730 320-1450 Adults (high environmental 2840-3410 temperature to 32°C) 3256+/- SD= 900 Adults (moderately active) 3700 Children (5-14 yr) 1000-1200 330-500 ca.200 ca.380 1310-1670 540-650 540-790 a Includes tea, coffee, soft drinks, beer, cider, wine, etc. b "Normal" conditions refer to typical environmental temperature and activity levels. Source: ICRP, 1981. Table 3-17. Intake Rates ofTotal Fluids and Total Tapwater by Age Group Average Daily Consumption Rate (L/day) Aae Grouo Total Fluidsa Total Taowater1' 6-11 months 0.80 0.20 2 years 0.99 0.50 14-16 years 1.47 0.72 25-30 years 1.76 1.04 60-65 vears 1.63 1.26 a Includes milk, "ready-to-use" formula, milk-based soup, carbonated soda, alcoholic beverages, canned juices, water, coffee, tea, reconstituted juices, and .reconstituted soups. Does not include reconstituted infant formula. b Includes water, coffee, tea, reconstituted juices, and reconstituted soups. Source: Derived from Penninaton 1983. Table 3-18. Mean and. Standard Error for the Daily Intake of Beverages and Tapwater by Age Age (years) Tapwater Intake Water-Based Drinks Soups Total Beverage lntakeb (ml) (ml)a (ml) (ml) All ages 662.5 +/- 9.9 457.1+/-6.7 45.9 +/- 1.2 1434.0 +/- 13.7 Under 1 170.7 +/- 64.5 8.3 +/- 43.7 10.1+/-7.9 307.0 +/- 89.2 1to4 .434.6 +/- 31.4 97.9 +/- 21.5 43.8 +/- 3.9 743.0 +/- 43.5 5 to 9 521.0 +/- 26.4 116.5 +/- 18.0 36.6 +/- 3.2 861.0 +/- 36.5 10 to 14 620.2 +/- 24.7 140.0 +/- 16.9 35.4 +/- 3.0 1025.0 +/- 34.2 15 to 19 664.7 +/- 26.0 201.5+/-17.7 34.8 +/- 3.2 1241.0 +/- 35.9 20 to 24 656.4 +/- 33.9 343.1+/-23.1 38.9 +/- 4.2 1484.0 +/- 46.9 25 to 29 619.8 +/- 34.6 441.6 +/- 23.6 41.3 +/- 4.2 1531.0 +/- 48.0 30 to 39 636.5 +/- 27.2 601.0 +/- 18.6 40.6 +/- 3.3 1642.0 +/- 37.7 40 to 59 735.3 +/- 21.1 686.5 +/- 14.4 51.6 +/- 2.6 1732.0 +/- 29.3 60 and over 762.5 +/- 23.7 561.1+/-16.2 59.4 +/- 2.9 1547.0 +/- 32.8 a Includes water-based drinks such as coffee, etc. Reconstituted infant formula does not appear to be included in this group. b Includes tapwater and water-based drinks such as coffee, tea, soups, and other drinks such as soft drinks, fruitades, and alcoholic drinks. Source: U.S. EPA, 1984. Table 3-19. Average Total Tapwater Intake Rate by Sex Age, and Geographic Area Average Total Number of Tapwater lntake,a,b Group/Subgroup Respondents Uday Total group 5,258 1.39 Sex Males 3,892 1.40 Females 1,366 1.35 .Age, years 21-44 291 1.30 45-64 1,991 1.48 65-84 2,976 1.33 Geographic area Atlanta 207 1.39 Connecticut 844 1.37 Detroit 429 1.33 Iowa 743 1.61 New Jersey 1,542 1.27 New Mexico 165 1.49 New Orleans 112 1.61 San Francisco 621 1.36 Seattle 316 1.44 Utah 279 1.35 a Standard deviations not reported in Cantor et al. (1987). b Total tapwater defined as all water and beverages derived from tapwater. Source: Cantor et al. 1987. Table 3-20. Frequency Distribution of Total Tapwater Intake Rates* Consumption Rate (Uday) 0.80 0.81-1.12 1.13-1.44 1.45-1.95 L1 .96 Frequencyb (%) 20.6 21.3 2Q.5 19.5 18.1 Cumulative Frequencyh (%) 20.6 41.9 62.4 81.9 100.0

Represents consumption of tapwater and beverages derived from tapwater in a "typical" winter week. b Extracted from Table 3 in Cantor et al. (1987). Source: Cantor, et al., 1987.

Table 3-21 Mean Per Capita Drinking Water Intake Based on USDA, CSFll Data From 1989-91 (mUday) Sex and Age Plain Drinking Fruit Drinks (years) Water Coffee Tea and Ades* Total Males and Females: Under 1 194 0 <0.5 17 211.5 1-2 333 <0.5 9 85 427.5 3-5 409 2 26 100 537 5 & Under 359 1 17 86 463 Males: 6-11 537 2 44 114 697 12-19 725 12 95 104 936 20-29 842 168 136 101 1,247 30-39 793 407 136 50 1,386 40-49 745 534 149 53 1,481 50-59 755 551 168 51 1,525 60-69 946 506 115 34 1,601 70-79 824 430 115 45 1,414 80 and over 747 326 165 57 1,295 20 and over 809 408 139 60 1,416 Females: 6-11 476 1 40 86 603 12-19 604 21 87 87 799 20-29 739 154 120 61 1,074 30-39 732 317 136 59 1,244 40-49 781 412 174 36 1,403 50-59 819 438 137 37 1,431 60-69 829 429 124 36 1,418 70-79 772 324 161 34 1,291 80 and over 856 275 149 28 1,308 20 and over 774 327 141 46 1,288 All individuals 711 260 114 65 1 150 a Includes regular and low calorie fruit drinks, punches, and ades, including those made from powdered mix and frozen concentrate. Excludes fruit juices and carbonated drinks. Source: USDA 1995. Table 3-22. Number of Respondents that Consumed Tapwater at a Specified Daily Frequency Number of Glasses in a Day Population Group Total N None 1-2 3-5 6-9 10-19 20+ DK Overall 4,663 1,334 1,225 1,253 500 151 31 138 Gender tii1aie 2,163 604 582 569 216 87 25 65 Female 2,498 728 643 684 284 64 6 73 Refused 2 2 . . . . 1-4 263 114 96 40 7 1 0 5 5-11 348 90 127 86 15 7 2 20 12-17 326 86 109 88 22 7 . 11 18-64 2,972 908 751 769 334 115 26 54 > 64 670 117 127 243 112 20 2 42 Race White 3,774 1,048 1,024 1,026 416 123 25 92 Black 463 147 113 129 38 9 1 21 Asian 77 25 18 23 6 1 . 4 Some Others 96 36 18 22 6 7 2 5 Hispanic 193 63 42 40 28 10 2 7 Refused 60 15 10 13 6 ' 1 1 9 Hispanic No 4,244 1,202 1,134 1,162 451 129 26 116 Yes 347 116 80 73 41 18 4 13 DK 26 .5 6 7 4 3 . 1 Refused 46 11 5 11 4 1 1 8 Employment Full-trme 2,017 637 525 497 218 '72 18 40 Part-time 379 90 94 120 50 13 7 5 Not Employed 1,309 313 275 413 188 49 3 54 Refused 32 6 4 11 1 2 1 4 Education < High School 399 89 95 118 . 51 14 2 28 High School Graduate 1,253 364 315 330 132 52 13 37 <College 895 258 197 275 118 31 5 9 College Graduate 650 195 157 181 82 19 4 6 Post Graduate 445 127 109 113 62 16 3 12 Census Region Northeast 1,048 351 262 266 95 32 7 28 Midwest 1,036 243 285 308 127 26 9 33 South. 1,601 450 437 408 165 62 11 57 West 978 290 241 271 113 31 4 20 OW of Week eekday 3,156 864 840 862 334 96 27 106 Weekend 1,507 470 385 391 166 55 4 32 Season Winter 1,264 398 321 336 128 45 5 26 Spring 1, 181 337 282 339 127 33 10 40 Summer 1,275 352 323 344 155 41 9 40 Fall 943 247 299 234 90 32 7 32 Asthma --"NO 4,287 1,232 1,137 1,155 459 134 29 115 Yes 341 96 83 91 40 16 1 13 DK 35 6 5 7 1 1 1 10 4,500 1,308 1,195 1,206 470 143 29 123 Yes 125 18 25 40 27 6 1 6 DK 38 8 5 7 3 2 1 9 No 4,424 1,280 1, 161 1,189 474 142 29 124 Yes 203 48 55 58 24 9 1 5 DK 36 6 9 6 2 . 1 9 NOTE: "*" = Missing Data "DK" = Don't know N = sample size Refused = respondent refused to answer Source: Tsang and Kleipeis, 1996 Table 3-23. Number of Respondents that Consumed Juice Reconstituted with Tapwater at a Specified Daily Frequency Number of Glasses in a Day Population Group Total N None 1-2 3-5 6-9 10-19 20+ DK Overall 4,663 1,877 1,418 933 241 73 21 66 Gender rviaiEl 2,163 897 590 451 124 35 17 33 Female 2,498 980 826 482 117 38 4 33 Refused 2 . 2 . . . &Jg (years) 1-4 263 126 71 48 11 4 1 2 5-11 348 123 140 58 12 2 1 11 12-17 326 112 118 63 18 7 1 4 18-64 2,972 1,277 817 614 155 46 16 30 > 64 670 206 252 133 43 12 2 14 Race White 3,774 1,479 1,168 774 216 57 16 44 Black 463 200 142 83 15 9 1 7 Asian 77 33 27 15 1 0 Some Others 96 46 19 24 2 1 3 1 Hispanic 193 95 51 30 5 5 1 5 Refused 60 24 11 7 2 -1 9 Hispanic No 4,244 1,681 1,318 863 226 64 17 49 Yes 347 165 87 61 14 7 4 7 DK 26 11 6 5 . 1 . 3 Refused 46 20 7 4 1 1 . 7 Employment Full-time 2,017 871 559 412 103 32 9 20 Part-time 379 156 102 88 19 7 2 5 Not Employed 1,309 479 426 265 75 20 7 21 Refused 32 15 4 4 2 .1 .. 3 Education < High School 399 146 131 82 25 7 2 4 High School Graduate 1,253 520 355 254 68 21 7 17 <College 895 367 253 192 47 18 5 11 College Graduate 650 274 201 125 31 7 1 5 Post Graduate 445 182 130 92 26 5 3 4 Census Region Northeast 1,048 440 29.7 220 51 13 4 15 Midwest 1,036 396 337 200 63 17 4 14 South 1,601 593 516 332 84 26 10 28 West 978 448 268 181 43 17 3 9 ow of Week eekday 3,156 1,261 969 616 162 51 11 46 Weekend 1,507 616 449 307 79 22 10 20 Season Winter 1,264 529 382 245 66 23 4 10 Spring 1, 181 473 382 215 54 19 8 17 Summer 1,275 490 389 263 68 18 6 28 Fall 943 385 265 21.0 53 13 3 11 Asthma 4,287 1,734 1,313 853 216 69 20 55 Yes 341 130 102 74 25 3 1 5 DK 35 13 3 6 . 1 . 6 Angina No 4,500 1,834 1,362 900 231 67 20 59 Yes 125 31 53 25 7 5 1 1 DK 38 12 3 8 3 1 . 6 Bronchitis/Emphy_sema No 4,424 1,782 1,361 882 230 65 21 57 .Yes 203 84 53 44 10 6 . 3 DK 36 11 4 7 1 2 . 6 NOTE: :'*" = Missing Data "DK" = Don't know N = sample size Refused = Respondent refused to answer Source: Tsang and Klepeis, 1996 Table 3-24. Total Fluid Intake of Women 15-49 Years Old Percentile Distribution Reproductive Standard Status* Mean Deviation 5 10 25 50 75 90 95 mUday Control 1940 686 995 1172 1467 1835 2305 2831 3186 Pregnant 2076 743 1085 1236 1553 1928 2444 3028 3475 Lactating 2242 658 1185 1434 1833 2164 2658 3169 3353 mUkg/day Control 32.3 12.3 15.8 18.5 23.8 30.5 38.7 48.4 55.4 Pregnant 32.1 11.8 16.4 17.8 17.8 30.5 40.4 48.9 53.5 Lactating 37.0 11.6 19.6 21.8 21.8 35.1 45.0 53.7 59.2

Number of observations: nonpregnaht, non lactating controls (n = 6,201 ); pregnant (n = 188); lactating (n = 77). Source: Ershow et al., 1991.

Table 3-25. Total Tapwater Intake of Women 15-49 Years Old Percentile Distribution Reproductive Mean Standard Status" Deviation 5 10 25 50 75 90 95 mUday Control 1157 635 310 453 709 1065 1503 1983 2310 Pregnant 1189 699 274 419 713 1063 1501 2191 2424 Lactating 1310 591 430 612 855 .1330 1693 1945 2191 mUkg/day Control 19.1 10.8 5.2 7.5 11.7 17.3 24.4 33.1 39.1 Pregnant 18.3 10.4 4.9 5.9 10.7 16.4 23.8 34.5 39.6 Lactating 21.4 9.8 7.4 9.8 14.8 20.5 26.8 35.1 37.4 Fraction of daily fluid intake that is ta12water (%) Control 57.2 18.0 24.6 32.2 45.9 59.0. 70.7 79.0 83.2 Pregnant 54.1 18.2 21.2 27.9 42.9 54.8 67.6 76.6 83.2 Lactating 57.0 15.8 27.4 38.0 49.5 58.1 65.9 76.4 80.5 a Number of observations: nonpregnant, nonlactating controls (n = 6,201 ); pregnant (n = 188); lactating (n = 77). Source: Ershow et al., 1991. Table 3-26. Total Fluid (mUDay) Derived from Various Dietary Sources by Women Aged 15 Control Women Percentile Mean' Sources 50 95 Drinking Water 583 480 1440 Milk and Milk Drinks 162 107 523 Other Dairy Products 23 8 93 Meats, Poultry, Fish, Eggs 126 114 263 Legumes, Nuts, and Seeds 13 0 77 Grains and Grain Products 90 65 257 Citrus and Noncitrus Fruit Juices 57 0 234 Fruits, Potatoes, Vegetables, Tomatoes 198 171 459 Fats, Oils, Dressings, Sugars, Sweets 9 3 41 Tea. 148 0 630 Coffee and Coffee Substitutes 291 159 1045 Carbonated Soft Drinks' 174 110 590 Noncarbonated Soft Drinks' 38 0 222 Beer 17 0 110 Wine Spirits, Liqueurs, Mixed Drinks 10 0 66 All Sources 1940 NA NA Mean' 695 308 24 121 18 98 69 212 9 132 197 130 48 7 5 2076 Pre nan! Women Percentile 50 640 273 9 104 0 69 0 185 3 0 0 73 0 0 0 NA 95 1760 749 93 252 88 246 280 486 40 617 955 464 257 0 '25 NA -49 Years' Mean' 677 306 36 133 15 119 64 245 10 253 205 117 38 17 6 2242 Number of observations: nonpregnant, nonlactating controls (n = 6,201 ); pregnant (n = 188); lactating (n = 77 ). Individual.means may not add to all-sources total due to rounding. Includes regular, low-calorie, and noncalorie soft drinks. NA: Not appropriate to sum the columns for the 50th and 95th percentiles of intake. Source: Ershow et al., 1991. Lactatina Women Percentile 50 95 560 1600 285 820 27 113 117 256 0 72 82 387 0 219 197 582 6 50 77 848 80 955 57 440 0 222 0 147 0 59 NA NA Table 3-27. Water Intake at Various Activity Levels (Uhr)* Room Activity Level Temperatureb ('Fl High (0.15 h11/man)° Medium (0.1 O h11/manl° Low (0.05 h11/man)' No.d Intake No. Intake No. Intake 100 -------15 0.653 (0.75) 95 18 0.540 12 0.345 6 0.50 (0.31) (0.59) (0.31) 90 7 0.286 7 0.385 16 0.23 (0.26) (0.26) (0.20) 85 7 0.218 16 0.213 ----(0.36) (0.20) 80 16 0.222 -------(0.14) a Data expressed as mean intake with standard deviation in parentheses. b Humidity= 80 percent; air velocity = 60 ft/min. c The symbol "hp" refers to horsepower. d Number of subjects with continuous data. Source: McNall and Schlegel, 1968. Table 3-28. Plannino Factors for Individual Taowater Consumption Environmental Condition Recommended Planning Factor (gal/day)" Recommended Planning Factor (Uday)"'b Hot 3.0' 11.4 Temperate 1.5d 5.7 Cold 2.0' 7.6

Based on a mix of activities among the work force as follows: 15% light work; 65% medium work; 20% heavy work. These factors apply to the conventional battlefield where no nuclear, biological, or chemical weapons are used. b Converted from gal/day to Uday. ' This assumes 1 quart/12-hour rest period/man for perspiration losses and 1 quart/day/man for urination plus 6 quarts/12-hours light work/man, 9 quarts/12-hours moderate work/man, and 12 quarts/12-hours heavy work/man. d This assumes 1 quart/12-howr rest period/man for perspiration losses and 1 quart/day/man for urination plus 1 quart/12-hours light work/man, 3 quarts/12-hours moderate work/man, and 6 quarts/12-hours heavy work/man. ' This assumes 1 quart/12-hour rest period/man for perspiration losses, 1 quart/day/man for urination, and 2 quarts/day/man for respiration losses plus 1 quart/12-hours light work/man, 3 quarts/12-hours moderate work/man, and 6 quarts/6-hours heavy work/man. Source: U.S. Army, 1983. I L_

Table 3-29. Drinking Water Intake Surveys Number of Individuals Type of Water Time Period/ Survey Studv Consumed Type Population Surveyed Comments KEY Canadian Ministry of 970 Total tapwater Weekday and weekend All ages; Canada Seasonal data; includes many tapwater-National Health and consumption day in both summer and containing items not commonly surveyed; Welfare, 1981 winter; estimation based possible bias because identification of on sizes and types of vessel size used as survey techniques; containers used short-term study Ershow and Cantor, Based on data from Total tapwater; total 3-day recall *. diaries All ages; large sample Short-term recall data; seasonally 1989 NFCS; approximately fluid consumption representative of U.S: balanced data 30,000 individuals population Rosenberry and Based on data from Total tapwater; total 3-day recall, diaries All ages; large sample Short-term recall data; seasonally Burmaster, 1992 Ershow and Cantor, fluid consumption representative of US balanced; suitable for Monte Carlo . 1989 population simulations RELEVANT Cantor et al., 1987 5,258 Total tapwater; total 1 week/usual intake in Adults only; weighted Based on recall of behavior from previous fluid consumption winter based on recall toward older adults; U.S. winter; short-term data; population not population representative of general U.S. population Gillies and Paulin, 109 Total tapwater 24 hours; duplicate water Adults only; New Zealand Based on short-term data 1983 consumption samples collected Hopkin and Ellis, 3,564 Total tapwater, total 1 week period, diaries All ages; Great Britain Short-term diary data 1980 liquid consumption ICRP, 1981 Based on data from Water and water-based NA' NA' Survey design and intake categories not several sources drinks; milk; total fluids clearly defined NAS, 1977 Calculated average Average per capita NA" NA' Total tapwater not reported; population and based on several "liquid" consumption survey design not reported sources Table 3-29. Drinking Water Intake Surveys (continued) Number of Individuals Type of Water Consumed Time Period/ Survey Studv Type Population Surveyed Comments Pennington, 1983 Based on NFCS and Total tapwater; total fluid NFCS:24-hour recall NFCS:1 month to 97 years; Based on short-term recall data NHANES II; approximately consumption on 2-day dairy; NHANES 11:6 months to 74 30,000 and 20,000 NHANES 11:24-hour years; representative participants, respectively recall samples of U.S. population USDA, 1995 Based on 89-91 CSF11; Plain drinking water, 1-day recall All ages, large sample Short-term recall data; seasonally approximately 15,000 coffee, tea, fruit drinks representative of U.S. adjusted individuals and ades population U.S. EPA, 1984 Based on NFCS; Tapwater; water based 3-da*y recall, diaries All ages; large sample Short-term recall data; seasonally approximately 30,000 foods and beverages; representative of U.S. balanced individuals soups; beverage population consumption U.S. EPA, 1995 Over 4,000 participants of Number of glasses of 24-hour diaries All ages, large Does not provide data on the volume NHAPS drinking water and juice representative sample of of tapwater consumed with tapwater U.S. population McNall and Based on 2 groups of 8 Tapwater 8-hour work cycle Males between 17-25 years Based on short-term data Schlegel, 1968 subjects each of age; small sample; high activity lev.els/hot climates U.S. Army, 1983 NA All fluids consumed to NA High activity levels/hot Study designed to provide water satisfy body needs for climates consumption planning factors for internal water; includes various activities and field conditions; soups, hot and cold based on estimated amount of water drinks arid tapwater required to account for losses from urination, perspiration, and respiration ' Not applicable. Table 3-30. Summarv of Recommended Drinkinq Water Intake Rates Percentiles Age Group/ Fitted Population Mean 50th 9oth 95th Multiple Distributions <:1 year' 0.30 Uday 0.24 Uday 0.65 Uday 0.76 Uday Tables 3-6, Table 3-11b 44 mUkg-day 35 mUkg-day 102 mUkg-day 12! mUkg-day 3-7, and 3-8 <3 years' 0.61 Uday --1.5 Uday --Table3-3 3-5 years' 0.87 Uday --1.5 Uday --Table3-3 1-10years* 0.74 Uday 0.66 Uday 1.3 Uday 1.5 Uday Tables 3-6, Table 3-11b 35 mUkg-day 31 mUkg-day 64 mUkg-day 79.4 mUkg-3-7, and 3-day 8 11-19 years* 0.97 Uday 0.87 Uday 1.7 Uday 2.0 Uday Tables 3-6, Table 3-11b 18 mUkg-day 16 mUkg-day 32 mUkg-day . 40 mUkg-day 3-7, and 3-8 Adults* 1.4 Uday 1.3 Uday 2.3 Uday Tables 3-6, Table 3-11b 21 mUkg-day 19 mUkg-day 34 mUkg-day 3-7, and 3-8 Pregnant Womend 1.2 Uday 1.1 Uday 2.2 Uday 2.4 Uday Table 3-25 18.3 mUkg-day 16 mUkg-day 35 mUkg-day 40 mUkg-day Lactating Women*d Uday 1.3 Uday 1.9 Uday 2.2 Uday Table 3-25 21.4 mUkg-day 21 mUkg-day 35 mUkg-day 37 mUkg-day Adults in High 0.21 to 0.65 Uhour, depending on ambient temperature and activity level; see Table 3-27. Activity/Hot Climate Conditions' Active Adultsr 6 Uday (temperate climate) to 11 Uday (hot climate); see Table 3-28. a Source: Ershow and Cantor, 1989 b Source: Roseberry and Burmaster, 1992 c Source: Canadian Ministry of Health and Welfare, 1981 d Ershow et al. (1991) presented data for pregnant women, lactating women, and control women. e Source: McNall and Schlegal, 1968 f Source* U.S. Armv 1983 Table 3-31. Total Tapwater Consumption Rates From Key Studies 90th Mean (L/day) Percentile Number in Reference (L/dav) Survev 1.38 2.41 639 Canadian Ministry of Health and Welfare, 1981 1.41 2.28 11,731 Ershow and Cantor, 1989 Table 3-32. Daily Tapwater Intake Rates From Relevant Studies Mean (L/day) 90th Percentile Reference 1.30" 2.40 Cantor et al., 1987 1.63 (calculated) --NAS, 1977 1.25 1.90 Gillies and Paulin, 1983 1.04 (25 to 30 yrs) --* Pennington, 1983 1.26 (60 to 65 yrs) --Pennington, 1983 1.04-1.47 (ages 20+) --U.S. EPA, 1984 1.37 (20 to 64 yrs) 2.27 Ershow and Cantor, 1989 1.46 (65+ yrs) 2.29 Ershow and Cantor, 1989 1.15 --USDA, 1995 1.07 1.87 Hookins and Ellis 1980 *Age of the Cantor et al. ( 1987) population was higher than the U.S. average. Table 3-33. Key Study Tapwater Intake Rates for Children Age Mean 90th Percentile (years) (L/day) (L/day) Reference <1 0.30 0.65 Ershow and Cantor, 1989 <3 0.61 1.50 Canadian Ministry of National Health and Welfare, 1981 3-5 0.87 1.50 Canadian Ministry of National Health and Welfare, 1981 1-10 0.74 1.29 Ershow and Cantor, 1989 6-17 1.14 2.21 Canadian Ministry of National Health and Welfare, 1981 11-19 0.97 1.70 Ershow and Cantor, 1989 Table 3-34. Summary of Intake Rates for Children in Relevant Studies Mean Age (Uday) Reference 6-11 months 0.20 Pennington, 1983 <1 yr 0.19 U.S. EPA, 1984 <1 yr 0.32 Roseberry and Burmaster, 1992 2 yrs 0.50 Pennington, 1983 1-4 yrs 0.58 U.S. EPA, 1984 5-9 yrs 0.67 U.S. EPA, 1984 1-10 yrs 0.70 Roseberry and Burmaster, 1992 10-14 yrs 0.80 U.S. EPA, 1984 14-16 yrs 0.72 Pennington, 1983 15-19 yrs 0.90 U.S. EPA, 1984 11-19yrs 0.91 Roseberry and Burmaster, 1992

Considerations Study Elements

Level of peer review Accessibility
Reproducibility
Focus on factor of interest
Data pertinent to U.S.
Primary data
Currency
Adequacy of data collection period Validity of approach
Study size
Representativeness of the population
Characterization of variability
Lack of bias in study design (high rating is desirable)
Measurement error Other Elements
Number of studies
Agreement between researchers Overall Ratina Table 3-35. Confidence in Tapwater Intake Recommendations Rationale The study of Ershow and Cantor ( 1989) had a thorough expert panel review. Review procedures were not reported in the Canadian study; it was a government report. Other reports presented are published in scientific journals. The two monographs are available from the sponsoring agencies; the others are library-accessible. Methods are well-described. The studies are directly relevant to tapwater. See "representativeness" below. The two monographs used recent primary data (less than one week) on recall of intake. Data were all collected in the 1978 era. Tapwater use may have changed since that time period. These are one-to three-day intake data. However, long term variability may be small. Their use as a chronic intake measure can be assumed. High High High High NA High Low Medium Rating The approach was competently executed. High This study was the largest monograph that had data for 11,000 H!gh individuals. The Ershow and Cantor (1989) and Canadian surveys were validated as demographically representative. The full distributions were given in the main studies. Bias was not apparent. No physical measurements were taken. The method relied on recent recall of standardized volumes of drinking water containers, and was not validated. There were two key studies for the adult and child recommendations. There were six other studies for adults, one study for pregnant and lactating women, and two studies for high activity/hot climates. This agreement was good. The data are excellent, but are not current. High High High Medium High for adult and clhildren. Low for the other recommended subpopulation values. High Medium REFERENCES FOR CHAPTER 3 American Industrial Health Council (Al HC). ( 1994) Exposure factors sourcebook. AIHC, Washington, DC. Bourne, G.H.; Kidder, G.W., eds. (1953) Biochemistry and physiology of nutrition. Vol. 1. New York, NY: Academic Press. Canadian Ministry of National Health and Welfare (1981) Tapwater consumption in Canada. Document number 82-EHD-80. Public Affairs Directorate, Department of National Health and Welfare, Ottawa, Canada. Cantor, K.P.; Hoover, R.; Hartge, P.; Mason, T.J.; Silverman, D.T.; et al. (1987) Bladder cancer, drinking water source, and tapwater consumption: A case-control study. J. Natl. Cancer Inst. 79(6):1269-1279.
Ershow, A.G.; Brown, L.M.; Cantor, K.P. (1991) Intake of tapwater and total water by pregnant and lactating women. American Journal of Public Health. 81 :328-334. Ershow, A.G.; Cantor, K.P. (1989) Total water and tapwater intake in the United States: population-based estimates of quantities and sources. Life Sciences Research Office, Federation of American Societies for Experimental Biology. Evans, C.L., ed. (1941) Starling's principles of human physiology, 8th ed. Philadelphia, PA: Lea and Febiger.
Gillies, M.E.; Paulin, H.V. (1983) Variability of mineral intakes from drinking water: A possible explanation for the controversy over the relationship of water quality to cardiovascular disease. Int. J. Epid. 12(1 ):45-50. Guyton, A.C. (1968) Textbook of medical physiology, 3rd ed. Philadelphia, PA: W.B. Saunders Co. Hopkins, S.M.; Ellis, J.C. (1980) Drinking water consumption in Great Britain: a survey of drinking habits with special reference to tap-water-based beverages. Technical Report 137, Water Research Centre, Wiltshire Great Britain. ICRP. (1981) International Commission on Radiological Protection. Report of the task group on reference man. New York: Pergammon Press. McNall, P.E.; Schlegel, J.C. (1968) Practical thermal environmental limits for young adult males working in hot, humid environments. American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) Transactions 74:225-235.

National Academy of Sciences (NAS). (1974) Recommended dietary allowances, 8th ed. Washington, DC: National Academy of Sciences-National Research Council. National Academy of Sciences (NAS). (1977) Drinking water and health. Vol. 1. Washington, DC: National Academy of Sciences-National Research Council. Pennington, J.A.T. (1983) Revision of the total diet study food list and diets .. J. Am. Diet. Assoc. 82:166-173. Pike, R.L.; Brown, M. (1975) Minerals and water in nutrition--an integrated approach, 2nd ed. New York, NY: John Wiley. Randall, H.T. (1973) Water, electrolytes and acid base balance. In: Goodhart RS, Shils ME, eds. Modern nutrition in health and disease. Philadelphia, PA: Lea and Febiger. Roseberry, A.M.; Burmaster, D.E. (1992) Lognormal distribution for water intake by children and adults. Risk Analysis 12:99-104. Tsang, A.M.; Klepeis, N.E. (1996) Results tables from a detailed analysis of the National Human Activity Pattern Survey (NHAPS) responses. Draft Report prepared for the U.S. Environmental Protection Agency by Lockheed Martin, Contract No. 68-W6-001, Delivery Order No. 13. U.S. Army. (1983) Water Consumption Planning Factors Study. Directorate of Combat Developments, United States Army Quartermaster School, Fort Lee, Virginia. USDA. (1995) Food and nutrient intakes by individuals in the United States, 1 day, 1989-91. United States Department of Agriculture, Agricultural Research Service. NFS Report No. 91-2. U.S. EPA. (1980) U.S. Environmental Protection Agency. Water quality criteria documents; availability. Federal Register, (November 28) 45(231 ):79318-79379.

U.S. EPA. ( 1984) An estimation of the daily average food intake by age and sex for use in assessing the radionuclide intake of individuals in the general population. EPA-520/1-84-021. U.S. EPA. (1991) U.S. Environmental Protection Agency. National Primary Drinking Water Regulation; Final Rule. Federal Register 56(20):3526-3597. January 30, 1991. Walker, B.S.; Boyd, W.C.; Asimov, I. (1957) Biochemistry and human metabolism, 2nd ed. Baltimore, MD: Williams & Wilkins Co. Wolf, A.V. (1958) Body water. Sci. Am. 99:125.

DOWNLOADABLE TABLES FOR CHAPTER 3 The following selected tables are available for download as Lotus 1-2-3 worksheets. Table 3-1. Daily Total Tapwater Intake Distribution for Canadians, by Age Group (approx. 0.20 L increments, both sexes, combined seasons) [WK1, 3 kb] Table 3-6. Total Tapwater Intake (ml/day) for Both Sexes Combined [WK1, 3 kb] Table 3-7. Total Tapwater Intake (ml/kg-day) for Both Sexes Combined [WK1, 5 kb] Table 3-9. Total Tapwater Intake (as percent of total water intake) by Broad Age Category [WK1, 1 kb] Table 3-10. General Dietary Sources of Tapwater for Both Sexes [WK1, 3 kb] Table 3-12. Estimated Quantiles and Means for Total Tapwater Intake Rates (ml/day) [WK1, 1 kb] Volume I -General Factors Chapter 4 -Soil Ingestion and Pica 4. SOIL INGESTION AND PICA 4.1 . BACKGROUND 4.2. KEY STUDIES ON SOIL INTAKE AMONG CHILDREN 4.3. RELEVANT STUDIES ON SOIL INTAKE AMONG CHILDREN 4.4. SOIL INTAKE AMONG ADULTS 4.5. PREVALENCE OF PICA 4.6. DELIBERATE SOIL INGESTION AMONG CHILDREN 4.7. RECOMMENDATIONS REFERENCES FOR CHAPTER 4 Table 4-1. Table 4-2. Table 4-3. Table4-4. Table 4-5. Table 4-6. Table 4-7. Table 4-8. Table 4-9.

Table 4-10. Table 4-11. Table 4-12. Table 4-13. Table 4-14. Table 4-15. Table 4-16. Table 4*-17. Estimated Daily Soil Ingestion Based on Aluminum, Silicon, and Titanium Concentrations Calculated Soil Ingestion by Nursery School Children Calculated Soil Ingestion by Hospitalized, Bedridden Children Mean and Standard Deviation Percentage Recovery of Eight Tracer Elements Soil and Dust Ingestion Estimates for Children Aged 1-4 Years Average Daily Soil Ingestion Values Based on Aluminum, Silicon, and Titanium as Tracer Elements .
Geometric Mean (GM) and Standard Deviation (GSD) L TM Values for Children at Daycare Centers and Campgrounds Estimated Geometric Mean. LTM Values of Children Attending Daycare* Centers According to Age, Weather Category, and Sampling Period Distribution of Average (Mean) Daily Soil Ingestion Estimates Per Child for 64 Children (mg/day) v Estimated Distribution of Individual Mean Daily Soil Ingestion Based on Data for 64 Subjects Projected *over 365 Days Estimates of Soil Ingestion for Children Estimated Soil Ingestion Rate Summary Statistics and Parameters for
Distributions Using Binder et al. (1986) Data with Actual Fecal Weights Tukey's Multiple Comparison of Mean Log Tracer Recovery in Adults Ingesting Known O.uantities of Soil Positive/Negative Error (bias) in Soil Ingestion Estimates in the Calabrese et al. (1989) Mass-balance Study: Effect on Mean Soil Ingestion Estimate (mg/day)
Soil Ingestion Rates for Assessment Purposes Estimates of Soil Ingestion for Adults* Adult Daily Soil Ingestion by Week and Tracer Element After Subtracting Food and Capsule Ingestion, Based on Median. Amherst Soil Concentrations: Means.and Medians Over Subjects (mg)

Table 4-18. Table 4-19. Table 4-20. Table 4-21. Table 4-22. Table 4-23. Volume I -General Factors Chapter 4 -Soil Ingestion and Pica Daily Soil Ingestion Estimation in a Soil-Pica Child by Tracer and by Week (mg/day) Ratios of Soil, Dust, and Residual Fecal Samples in the Pica Child Soil Intake Studies Confidence in Soil Intake Recommendation Summary of Estimates of Soil Ingestion By Children Summary of Recommended Values for Soil Ingestion Exposure Factors Handbook August 1997 Volume I-General Factors Chapter 4 -Soil Ingestion and Pica 4. SOIL INGESTION AND PICA 4.1. BACKGROUND The ingestion of soil is a potential source of human exposure to toxicants. The potential for exposure to contaminants via this source is greater for children because they are more likely to ingest more soil than adults as a result of behavioral patterns present during childhood. Inadvertent soil ingestion among children may* occur through the mouthing of objects or hands. Mouthing behavior is considered to be a normal phase of childhood development. Adults may also ingest soil or dust particles that to food, cigarettes, or their hands. Deliberate soil ingestion is defined as pica and is considered to be relatively uncommon. Because normal, inadvertent soil ingestion is more prevalent and data for individuals with pica behavior are limited, this.section focuses primarily on normal *soil ingestion that occurs as a result of mouthing or unintentional hand-to-mouth activity. Several studies have been conducted to estimate the amount of soil ingested by children. Most of the early studies attempted to estimate the amount of soil ingested by measuring the amount of dirt present on children's hands and making generalizations based on behavior. More recently, soil intake studies have been conducted using a methodology that measures trace elements in feces and soil that are believed to be poorly absorbed in the gut. . These measurements are used to estimate the amount of soil ingested over a specified time period. The available studies on soil intake are summarized in the following sections. Studies on soil intake among children have been classified as either key studies or relevant studies based on their applicability to exposure assessment needs. Recommended intake rates are based on the results of key studies, but relevant studies are also presented to provide the reader with added perspective on the current state-of-knowledge pertaining to soil intake. Information on soil ingestion among adults is presented based on available data from a limited number of studies. This is an area where more data and more research are needed. Relevant information on the prevalence of pica and intake among individuals exhibiting pica behavior is also presented. 4.2. KEY STUDIES ON SOIL INTAKE AMONG CHILDREN Binder et al. (1986) -Estimating Soil Ingestion: Use of Tracer Elements in Estimating the Amount of Soil Ingested by Young Children -Binder et al. (1986) studied the ingestion of soil among children 1 to 3 years of age who wore diapers using a tracer technique modified from a method previously used to measure soil ingestion among grazing animals. The children were studied during the summer of 1984 as part of a larger study of residents living near a lead smelter in East Helena, Montana. Soiled diapers were collected over a 3-day period from 65 children (42 males and 23 females), and composited samples of Exposure Factors Handbook August 1997 Volume I -General Factors . Chapter 4 -Soil Ingestion and Pica soil were obtained from the children's yards. Both excreta and soil samples were analyzed for aluminum, silicon, and titanium. These elements were found in* soil, but were thought to be poorly absorbed in the gut and to have been present in the diet only in limited quantities. This made them tracers* for estimating soil intake. Excreta measurements were obtained for 59 of the children. Soil ingestion by each child was estimated based on each of the three tracer elements using a standard assumed fecal dry weight of 15 g/day, and the following equation: T;,e ' where: Ti,e fi,e Fi si,e = = = = estimated soil ingestion for child i based on element e (g/day); concentration of element e in fecal sample of child i (mg/g); fecal dry weight (g/day}; and concentration of element e in child i's yard soil (mg/g). (Eqn. 4-1) The analysis conducted by Binder et al. (1986) assumed that: (1) the tracer elements were neither lost nor introduced during sample processing; (2) the soil ingested by children originates primarily from their own yards; and (3) that absorption of the tracer elements by children occurred in only small amounts. The study did not distinguish between ingestion of soil and housedust nor did it account for the presence of the tracer elements in ingested foods or medicines. The arithmetic mean quantity of soil ingested by the children in the Binder et al. (1986) study was estimated to be 181 mg/day (range 25 to 1,324) based on the aluminum tracer; 184 mg/day (range 31 to 799) based on the silicon tracer; and 1,834 mg/day (range 4 to 17 ,076) based on the titanium tracer (Table 4-1 ). The overall mean soil ingestion estimate based on the minimum of the three individual tracer estimates for each child was 108 mg/day (range 4 to 708). The 95th percentile values for aluminum, silicon, and titanium were 584 mg/day, 578 mg/day, and 9,590 mg/day, respectively. The 95th percentile value based on the minimum of the three individual tracer estimates for each. child was 386 mg/day. The authors were not able to explain the difference between the results for titanium and for the other two elements, but speculated that unrecognized sources of titanium in the diet or in the laboratory processing of stool samples may have accounted for the increased levels. The frequency distribution graph of soil ingestion estimates based on titanium shows that a group of 21 children had particularly high titanium values (i.e., Exposure Factors Handbook . August 1997 Volume I -General Factors Chapter 4 -Soil Ingestion and Pica >1,000 mg/day). The remainder of the children showed titanium ingestion estimates at lower levels, with a distribution more comparable to that of the other elements. The advantages of this study are that a relatively large number of children were studied and tracer elements were used to estimate soil ingestion. However, the children studied may not be representative of the U.S. population and the study did not account for tracers ingested via foods or medicines. Also, the use of an assumed fecal weight instead of actual fecal weights may have biased the results of this study. Finally, because of the short-term nature of the survey, soil intake estimates may not be entirely representative of long-term behavior, especially at the upper-end of the distribution of intake. Clausing et al. (1987) -A Method for Estimating Soil Ingestion by Children -Clausing et al. (1987) conducted a soil ingestion study with Dutch children using a tracer element methodology similar to that of Binder et al. (1986). Aluminum, titanium, and acid-insoluble residue (AIR) contents were determined for fecal samples from children, aged 2 to 4 years, attending a nursery school, and for samples of playground dirt at that school. seven daily fecal samples were obtained over a 5-day period for the 18 children examined. Using the average soil concentrations present at the school, and assuming a standard fecal dry weight of 10 g/day, Clausing et al. (1987) estimated soil ingestion for each tracer. Clausing et al. (1987) also collected eight daily fecal samples from six hospitalized; bedridden children. These children served as a control group, representing children who had very limited access to soiL The average quantity of soil ingested by the school children in this study was as follows: 230 mg/day (range 23 to 979 mg/day) for aluminum; 129 mg/day (range 48 to 362 mg/day) for AIR; and 1,430 mg/day (range 64 to 1.1,620 mg/day) for titanium (Table 4-2). As in the Binder et al. (1986) study, a fraction of the children (6/19) showed titanium values well above 1,000 mg/day, with most of the remaining children showing substantially lower values. Based on the Limiting Tracer Method (L TM), mean soil intake was estimated to be 105 mg/day with a population standard deviation of 67 mg/day (range 23 to 362 mg/day). Use of the L TM assumed that "the maximum amount of soil ingested corresponded with the lowest estimate from the three tracers" (Clausing et al., 1987). Geometric mean soil intake was estimated to be 90 mg/day: This assumes that the maximum a.mount of soil ingested Gannot be higher than the lowest estimate for the individu.al tracers. Mean soil intake for the hospitalized children was estimated to be 56 mg/day based on aluminum (Table 4-3). For titanium, three of the children had estimates well in excess of 1,000 mg/day, with the remaining three children in the range of 28 to 58 mg/day. Using the L TM method, the mean soil ingestion rate was estimated to be 49 mg/day with a population standard deviation of 22 mg/day (range 26 to 84 mg/day). The geometric mean Exposure Factors Handbook August 1997 Volume I-General Factors Chapter 4 -Soil Ingestion and Pica soil intake rate was 45 mg/day. The data on hospitalized children suggest a major nonsoil source of titanium for.some children, and may suggest a background.nonsoil source of aluminum. However, conditions specific to hospitalization (e.g., medications) were not considered. AIR measurements were not reported for the hospitalized children. Assuming that the tracer-based soil ingestion rates observed in hospitalized children actually represent background tracer intake from dietary and other nonsoil sources, mean soil ingestion by nursery school children was estimated to be 56 mg/day, based on the L TM (i.e., 105 mg/day for nursery school children minus 49 mg/day for hospitalized children) (Clausing et al. 1987). The advantages of this study are that Clausin,g et al. ( 1987) evaluated soil ingestion among two populations of children that had differences in access to soil; and corrected soil intake rates based on backgro.und estimates derived from the hospitalized group. However, a smaller number of children were used in this study than in the Binder et al. (1986) study and these children may not be representative of the U.S. population. Tracer elements in foods or medicines were not evaluated. Also, intake rates derived from this study may not be representative of soil intake over the long-term because of the short-term nature of the study. In addition, one of the factors that could affect soil intake rates is hygiene (e.g., hand washing frequency). Hygienic practices can vary across countries and

cultures and may be more stringently emphasized in a more structured environment such as child care centers in The Netherlands and other European countries than in child care centers in the United States. Calabrese et al. (1989) -How Much Soil do Young Children Ingest: An Epidemiologic Study-Calabrese et al. (1989) studied soil ingestion among children using the basic tracer design developed by Binder et al. (1986). However, in contrast to the Binder et al. (1986) study, eight tra"cer elements (i.e., aluminum, barium, manganese, silicon, titanium, vanadium, yttrium, and zirconium) were analyzed instead of only three (i.e., aluminum, silicon, and titanium). A tOtal of 64 children between the ages of 1 and 4 years old were included in the study. These children were all selected from the greater Amherst, Massachusetts area and were predominantly from two-parent households where the parents were highly educated. The Calabrese et al. (1989) study was conducted over eight days during a two week period and included the use of a mass-balance methodology in which duplicate samples of food, medicines, vitamins, and others were collected and analyzed on a daily basis, in addition to soil and dust samples collected from the child's home and play area. Fecal and urine samples were also collected and analyzed for tracer elements. Toothpaste, low in tracer content, was provided to all participants. In order to validate the mass-balance methodology used to estimate soil ingestion rates among children and to determine which tracer elements provided the most reliable data on soil ingestion, known amounts of soil (i.e., 300 mg over three days and 1,500 mg Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 4 -Soil Ingestion and Pica over three days) containing eight tracers were* administered to six adult volunteers (i.e., three males and three females). Soil samples and feces samples from these adults and duplicate food samples were analyzed for tracer elements to ca.lculate recovery rates of tracer elements in soil. Based on the adult validation study, Calabrese et al. (1989) confirmed that the tracer methodology could adequately detect tracer elements in feces at levels expected to correspond with soil intake rates in children. Calabrese et al. (1989). also found that aluminum, silicon, and yttrium were the most reliable of the eight tracer elements analyzed. The standard deviation of recovery of these three tracers was the lowest and the percentage of recovery was closest to 100 percent (Calabrese, et al., 1989). The recovery of these three tracers ranged from 120 to 153 percent when 300 mg of soil had been ingested over a three-day period and from 88 to 94 percent when 1,500 mg soil had been ingested over a three-day period (Table 4-4 ). Using the three most reliable tracer elements, the mean soil intake rate for children, adjusted to account for the amount of tracer found in food and medicines, was estimated to be 153 mg/day based on aluminum, 154 mg/day based on silicon, and 85 mg/day based on yttrium (Table 4-5). Median intake rates were somewhat lower (29 mg/day for aluminum, 40 mg/day for silicon, and 9 mg/day for yttrium). Upper-percentile (i.e., 95th) values were 223 mg/day for aluminum, 276 mg/day for silicon, and 106 mg/day for yttrium. Similar results were observed when soil and dust ingestion was combined (Table 4-5). , Intake of soil and dust was estimated using a weighted average of tracer concentration in dust composite samples and in soil composite samples based on the timechildren spent at home and away from home, and indoors and outdoors. Calabrese et al. (1989) suggested that the use of titanium as a tracer in earlier studies that lacked food ingestion data may have significantly overestirnated soil intake because of tlie high levels of titanium in food. Using the median values of aluminum and silicon, Calabrese et al. (1989) estimated the quantity of soil ingested daily to be 29 mg/day and 40 mg/day, respectively. It should be noted that soil ingestion for one child in the study ranged from approximately
10 to 14 grams/day during the second week of observation. Average soil ingestion for this child was 5 to 7 mg/day, based on the entire study period. The advantages of this study* are that intake rates were corrected for tracer concentrations in foods and medicines and that the methodology was validated using adults. Also, intake was observed over a longer time period in this study than in earlier studies and the number of tracers used was larger than for other studies. A relatively large population was studied, but they may not be entirely representative of the U.S. population because they were selected from a single location. Davis et al. (1990) -Quantitative Estimates of Soil Ingestion in Normal Children Between the ages of 2 and 7 years: Population-Based Estimates Using Aluminum, Silicon, and Titanium as Soil Tracer Elements -Davis et al. (1990) also used a mass-Exposure Factors Handbook August 1997 t.* Volume I-General Factors Chapter 4 -Soil Ingestion and Pica balance/tracer technique to estimate soil ingestion among children. In this study, 104 children between the ages of 2 and 7 years were randomly selected from a three-city area in south.eastern Washington State. The study was conducted over a seven day period, primarily during the summer. Daily soil ingestion was evaluated by collecting and analyzing soil and house dust samples, feces, urine, and duplicate food samples for aluminum, silicon, and titanium. In addition, information on dietary habits and demographics was collected in an attempt to identify behavioral and demographic characteristics that influence soil intake rates among children. The amount of soil ingested on a daily basis was estimated using the following equation: (DW1 % DWP) X (E1 % 2Eu) & (DW1d X E1d) Si,e ' soil where: Si,e = soil ingested for child i based on tracer e (g); DWf = feces dry weight (g); DWP = feces dry weight on toilet paper (g); Ef = tracer amount in feces (µgig); Eu = tracer amount in urine (µgig); DWtd = food dry weight (g); Efd = tracer amount in food (µgig); and Esoil * = tracer concentration in soil (µgig). (Eqn. 4-2) The soil intake rates were corrected by adding the amount of tracer in vitamins and medications to the amount of tracer in food, and adjusting the food quantities, feces dry weights, and tracer concentrations in urine to account for missing samples. Soil ingestion rates were highly variable, especially those based on titanium. Mean daily soil ingestion estimates were 38.9 mg/day for aluminum, 82.4 mg/day for silicon and 245.5 mg/day for titanium (Table 4-6). Median values were 25 mg/day for aluminum, 59 mg/day for silicon, and 81 mg/day for titanium .. Davis et al. (1990) also evaluated the extent to which differences in tracer concentrations in house dust and yard soil impacted estimated soil ingestion rates. The value used in the denominator of the mass balance equation was recalculated to represent a weighted average of the tracer concentration in yard soil and house dust based on the proportion oftime the child spent indoors and outdoors. The adjusted mean soil/dust intake rates were 64:5 mg/day for aluminum, 160.0 mg/day for silicon, and 268.4 mg/day for titanium. Adjusted median soil/dust intake rates were: 51.8 mg/day for aluminum, 112.4 mg/day for silicon, and 116.6 _mg/day for titanium. Davis et al. (1990) also observed that the following demographic characteristics were associated with high soil intake rates: male sex, non-white racial group, low income, Exposure Factors Handbook August 1997 Volume I-General Factors Chapter 4 -Soil Ingestion and Pica operator/laborer as the principal occupation of the parent, and city of residence. However, none of these factors were predictive of soil intake rates when tested using multiple linear regression. The advantages of the Davis et al. (1990) study are that soil intake rates were corrected based on the tracer content of foods and medicines and that a relatively large number of children were sampled. Also, demographic and behavioral information was collected for the survey group. However, although a relatively large sample population was surveyed, these children were all from a single area of the U.S. and may not be representative of the U.S. population as a whole. The study was conducted over a week period during the summer and may not be representative of long-term (i.e., annual) patterns of intake. Van Wtjnen et al. (1990) -Estimated Soil Ingestion by Children -In a study by Van W1]nen et al. (1990), soil ingestion among Dutch children ranging in age from 1 to 5 years was evaluated using a tracer element methodology similar to that used by Clausing et al. (1987). Van W1]nen et al. (1990) measured three tracers (i.e., titanium, aluminum, and AIR) in soil and feces and estimated soil ingestion based on the L TM. An average daily feces weight of 15 g dry weight was assumed. A total of 292 children attending daycare centers were sampled during the first of two sampling periods and 187 children were sampled in the second sampling period; 162 of these children were sampled during both periods (i.e., at the beginning and near the end of the summer of 1986). A total of 78 .children were sampled at campgrounds, and 15 hospitalized children were sampled. The mean values for these groups were: 162 mg/day for children in daycare centers, 213 mg/day for campers and 93 mg/day for hospitalized children. Van W1]nen et al. (1990) also repprted geometric mean L TM values because soil inta.ke rates were found to be skewed and the log transformed data were approximately normally distributed. Geometric mean L TM values were estimated to be 111 mg/day for children in daycare centers, 17 4 mg/day for children vacationing at campgrounds (Table 4-7) and 74. mg/day for
hospitalized children (70-120 mg/day based on the 95 percent confidence limits of the mean).* AIR was the limiting tracer in about 80 percent of the samples. Among children attending daycare centers, soil was also found to be higher when the weather was good (i.e., <2 days/week precipitation) than when the weather was bad (i.e., >4 days/week precipitation (Table 4-8). Van W1]nen et al. (1990) suggest that the mean L TM value for hospitalized infants represents background intake of tracers and should be used to correct the soil intake rates based on L TM values for other sampling groups. Using mean values, corrected soil intake rates were 69 mg/day (162 mg/day minus 93 mg/day) for daycare children and 120 mg/day (213 mg/day minus 93 mg/day) for campers. Corrected geometric mean soil intake was estimated to range from 0 to 90 mg/day with a 90th percentile value of 190 mg/day.for the various age categories within the daycare group and Exposure Factors Handbook August 1997 Volume I-General Factors Chapter 4 -Soil Ingestion and Pica 30 to 200 mg/day with a 90th percentile value of 300 mg/day for the various age categories Within the camping group. The advantage of this study is that soil intake was estimated for three different populations of children; one expected to have high intake, one expected to have "typical" intake, and one expected to have low or background-level intake. Van W1jnen et al. (1990) used the background tracer measurements to correct soil intake rates for the other two populations .. Tracer concentrations in food and medicine were not evaluated. Also, the population of children studied was relativ.ely large, but may not be representative of the* U.S. population. This study was conducted over a relatively short time period. Thus, estimated intake rates may not reflect long-term patterns, especially at the high-end of the distribution. Another limitation of this study is that values were not reported element which would be the preferred way of reporting. In addition, one of the factors that could affect soil intake rates is hygiene (e.g., hand washing frequency). Hygienic practices can vary across countries and cultures and may be more stringently emphasized in a more structured environment such as child care centers in The Netherlands and other European* countries than in child care centers in the United States.*
Stanek and Calabrese (1995a) -Daily Estimates of Soil Ingestion in Children -Stanek and Calabrese (1995a) presented a methodology which links the physical passage of food and fecal samples to construct daily soil ingestion estimates from daily food and fecal trace-element concentrations. Soil ingestion data for children obtained from the Amherst study (Calabrese et al., 1989) were reanalyzed by Stanek and Calabrese (1995a). In the Amherst study, soil ingestion measurements were made over a period of 2 weeks for a non-random sample of sixty-four children (ages of 1-4 years old) living adjacent to an academic area in western Massachusetts. During each week, duplicate food samples were collected for 3 consecutive days and fecal samples* were collected for 4 consecutive days for each subject. The total amount of each of eight trace elements present in the food and fecal were measured. The eight trace elements are aluminum, barium, manganese, silicon, titanium, vanadium, yttrium, and zirconium. The authors expressed the amount of trace element in food input or fecal output as a "soil equivalent," which was defined as the amount of the element in average daily food intake (or average daily fecal output) divided by the concentration of the element in soil. A lag period of 28 hours between food intake and fecal output was assumed for all respondents. Day 1 for the food sample corresponded to the 24 hour period from midnight on Sunday to midnight on Monday of a study week; day 1 of the fecal sample corresponded to the 24 hour period from noon on Monday to noon on Tuesday (Stanek and Calabrese, 1995a). Based on these definitions, the food soil equivalent was subtracted from the fecal soil equivalent to obtain an estimate of soil ingestion for a trace element. A daily "overall" ingestion estimate was constructed for each child as the median of trace element values remaining after tracers falling outside of a defined range around the overall median were excluded. Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 4 -Soil Ingestion and Pica Additionally, estimates of the distribution of soil ingestion projected over a period of 365 days were derived by fitting log-normal distributions to the "overall" daily soil ingestion estimates. Table 4-9 presents the estimates of mean daily soil ingestion intake per child (mg/day) for the 64 study participants. (The authors also presented estimates of the median values of daily intake for each child. For most risk assessment purposes the child mean values, which are proportional to the cumulative soil intake by the child, are needed instead of the median values.) The approach adopted in this paper led to changes in ingestion estim9tes from those presented in Calabrese et al. (1989). Specifically, among elements that may be more useful for estimation of ingestion, the mean estimates decreased for Al ( 153 mg/d to 122 mg/d) and Si ( 154 mg/d to 139 mg/d); but increased for Ti (218 mg/d to 271 mg/d) and Y (85 mg/d to 165 mg/d). The "overall" mean estimate from this reanalysis was 179 mg/d. Table 4-9 presents the empirical distribution of the the "overall" mean daily soil ingestion estimates for the 8-day study period (not based on lognormal modeling). The estimated intake based on the "overall" estimates is 45 mg/day or less for 50 percent of the children and 208 mg/day or less for 95 percent of the children. The upper percentile values for most. of the individual trace elements are somewhat higher. Next, estimates of the respondents soil intake averaged over a period of 365 days were presented based upon the lognormal models fit to the daily ingestion estimates (Table 4-10). The estimated median value of the 64 respondents' daily soil ingestion averaged over a year is 75 mg/day, while the 95th percentile is 1,751 mg/day. A strength of this study is that it attempts to make full use of the collected data thro'ugh estimation of daily ingestion rates for children. The data are then screened to remove less consistent tracer estimates and the remaining values are aggregated. Individual daily estimates of ingestion will be subject to larger errors than are weekly average values, particularly since the assumption of a constant lag time between food intake and fecal output may be not be correct for many subject days. The aggregation approach used to arrive at the "overall" ingestion estimates rests on the assumption that the mean ingestion estimates across acceptable tracers provides the most reliable estimates. The validity of this assumption depends on the particular set of tracers used in the study, and is not fully assessed. In developing the 365 day soil ingestion estimates, data that were obtained over a short period of time (as is the case with all available soil* ingestion studies) were extrapolated over a year. The 2-week study period may not reflect variability in tracer element ingestion over a year. While Stanek and Calabrese (1995a) attempt to address this through lognormal modeling of the long term intake, new uncertainties are introduced through the parametric modeling of the limited subject day data. Also, the sample population size of the original study was small and site limited, and, therefore, is not Exposure Factors Handbook August 1997 Volume I-General Factors Chapter 4 -Soil Ingestion and Pica representative of the U.S. population. Study mean estimates of soil ingestion, such as the study mean estimates presented in Table 4-9, are substantially more reliable than any available distributional estimates. Stanek and Calabrese (1995b) -Soil Ingestion Estimates for Use in Site Evaluations* Based on the Best Tracer Method -Stanek and Calabrese ( 1995b) recalculated ingestion rates that were estimated in three previous studies (Calabrese et al., 1989 and Davis et al., 1990 for children's soil ingestion, and Calabrese et al., 1990 for adult soil ingestion) using the Best Tracer Method (BTM). This method allows for the selection of the most recoverable tracer for a particular subject or group of subjects. The s*e1ection process involves ordering trace elements for each subject based on food/soil (F/S) ratios. These ratios are estimated by dividing the total amount of the tracer in food by the tracer concentration in soil. The F/S ratio is small when the tracer concentration in food is almost . zero when compared to the tracer concentration in soil. A small F/S ratio is desirable because it lessens the impact of transit time error (the error that occurs when fecal output does not reflect food ingestion, due to fluctuation in gastrointestinal transit time) in the soil ingestion calculation. Because the recoverability of tracers can vary within any group of individuals, the BTM uses a ranking scheme of F/S ratios to determine the best tracers for use in the ingestion rate calculation. To reduce biases that may occur as a result of sources of fecal tracers other than food or soil, the median* of soil ingestion estimates based on the four lowest F/S ratios was used to represent soil ingestion among individuals. For adults, Stanek and Calabrese ( 1995b) used data for 8 tracers from the Calabrese et al. (1990) study to estimate soil ingestion by the BTM. The lowest F/S ratios were Zr and Al and the element with the highest F/S ratio was Mn. For soil ingestion estimates based on the median of the lowest four F/S ratios, the tracers contributing most often to the soil ingestion estimates were Al, Si, Ti, Y, V, and Zr. Using the median of the soil ingestion rates based on the best four tracer elements, the average adult soil ingestion rate was estimated to be 64 mg/day with a median of 87 mg/day. The 90th percentile soil ingestion estimate was 142 mg/day. These estimates are based on 18 subject weeks for the six adult volunteers described in Calabrese et al. (1990). For children, Stanek and Calabrese (1995b) used data on 8 tracers from Calabrese et al., 1989 and data on 3 tracers from Davis et al. (1990) to estimate soil ingestion rates. The median-of the soil ingestion estimates from the lowest four F/S ratios from the Calabrese et al. (1989) study most often included Al, Si, Ti, Y, and Zr. Based on the median of soil ingestion estimates from the best four tracers, the mean soil ingestion rate was 132 mg/day and the median was 33 mg/day. The 95th percentile value was 154 mg/day. These estimates are based on data for 128 subject weeks for the 64 children in the Calabrese et al. (1989) study. For the 101 children in the Davis et al. (1990) study, the mean soil ingestion rate was 69 mg/day and the median soil ingestion rate was 44 mg/day. Exposure Factors Handbook August 1997 Volume I-General Factors Chapter 4 -Soil Ingestion and Pica The 95th percentile estimate was 246 mg/day. These data are based on the three tracers (i.e., Al, Si, and Ti) from the Davis et al. (1990) study. When the Calabrese et al. (1989) and Davis et al. (1990) studies were combined, soil ingestion was estimated to be 113 mg/day (mean); 37 mg/day (median); and 217 mg/day (95th percentile), using the BTM. This study provides a reevaluation of previous studies. Its advantages are that it combines data from 2 studies for children, one from California and one from Massachusetts, which increa*ses the number of observations. It also corrects for biases associated with the differences in tracer metabolism. The limitations associated with the data used in this study are the same as the limitations described in the su.mmaries of the Calabrese et al. (1989), Davis et al. (1990) and Calabrese et al. (1990) studies. ' 4.3. RELEVANT STUDIES ON SOIL INTAKE AMONG CHILDREN Lepow et al. (1975) -Investigations Into Sources of Lead in the Environment of Urban Children -Lepow et al. ( 1975) used data from a previous study (Lepow et al., 197 4) to estimate daily soil ingestion rates of children. Lepow et al. (1974) estimated ingestion of airborne lead fallout among urban children by: ( 1) analyzing surface dirt and dust samples from locations where children played; (2) measuring hand dirt by applying preweighed adhesive labels to the hands and weighing the amount of dirt that was removed; and (3) observing "mouthing" behavior over 3 to 6 hours of normal play. Twenty-two children from an urban area of Con*necticut were included in the study. Lepow et al. (1975) used data from 197 4 study and found that the mean weight of soil/dust on the hands was 11 mg. Assuming that a child would put fingers or other "dirty" objects into his mouth about 10 times a day ingesting 11 mg of dirt each time, Lepow et al. ( 1975) estimated that the daily soil ingestion rate would be about 100 mg/day. According to Lepow et al. (1975), the amount of hand dirt measured with this technique is probably an underestimate because dirt trapped in skin folds and creases was probably not removed by the adhesive label. Consequently, mean soil ingestion rates may be somewhat higher than the values estimated in this study. Day et al .. (1975) -Lead in Urban Street Dust -Day et al. (1975) evaluated the of incidental ingestion of lead-contaminated street dust and soil to children's total daily intake of lead by measuring the amount of lead in street dust and soil and estimating the amount of dirt ingested by children. The amount of soil that might be ingested was estimated by measuring the amount of dirt that was transferred to a "sticky sweet" during 30 minutes of play and assuming that a child might eat from 2 to 20 such sweets per day. Based on "a small number of direct measurements," Day et al. (1975) found that 5 to 50 mg of dirt from a. child's hands may be transferred to a "sticky sweet" during 30 minutes of "normal playground activity. Assuming that all of the dirt is ingested Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 4 -Soil Ingestion and Pica with the 2 to 20 "sticky sweets," Day et al. (1975) estimated that intake of soil among ch!ldren could range from 10 to 1000 mg/day. Duggan and Williams (1977) -Lead in Dust in City Streets -Duggan and Williams (1977) assessed the risks associated with lead in street dust by analyzing street dust from areas in and around London for lead, and estimating the amount of hand dirt that a child might ingest. Duggan and Williams (1977) estimated the amount of dust that would be retained on the forefinger and thumb by removing a small amount of dust from a weighed amount, rubbing the forefinger and thumb together, and reweighing to determine the amount retained on the finger and thumb. The results of "a number of tests with several different people" indicated that the mean, amount of dust retained on the finger and thumb* was approximately* 4 mg with a range of 2 to 7 mg (Duggan and Williams, 1977). Assuming that a child would suck his/her finger or thumb 10 tim.es a day and that all of the dirt is removed each time and replaced with new dirt prior to subsequent mouthing behavior, Du_ggan and Williams (1977) estimated that 20 mg of dust would be ingested per day. Hawley et al. (1985) -Assessment of Health Risk from Exposure to Contaminated Soil -Using existing literature, Hawley (1985) developed scenarios for estimating exposure of young children, older children, and adults to contaminated soil. Annual soil ingestion rates were estimated based on assumed intake rates of soil and housedust for indoor and outdoor activities and assumptions about the duration and frequency of the activities. These soil ingestion rates were based ori the assumption that the contaminated area is in a region having a winter season. Housedust was assumed to be comprised of 80 percent soil. Outdoor exposure to contaminated soil among young children (i.e., 2.5 years old) was assumed to occur 5 days per week during only 6 months of the year (i.e., mid-April through mid-October). Children were assumed to ingest 250 mg soil/day while playing outdoors based on data presented in Lepow et al. (1974; 1975) and Roels et al. (1980). Indoor exposures among this population were based on t_he assumption that young children ingest : 100 mg of housedust per day while spending all of their time indoors during the winter months, and 50 mg of housedust per day during the warmer months when only a portion of their time is spent indoors. Based on these assumptions, Hawley ( 1985) estimated that the annual average soil intake rate for young children is 150 mg/day (Table 4-11 ). Older children (i.e:, 6 year olds) were assumed to ingest 50 mg of soil per day from an are.a equal to the area of the fingers on one hand while playing outdoors. This assumption was based on data from Lepow et al. (1975). Outdoor activities were assumed to occur each day over 5 months of the year (i.e., during May through October). These children were also assumed to ingest 3 mg/day of housedust from the indoor surfaces of the hands during Exposure Factors Handbook August 1997

Volume I-General Factors Chapter 4 -Soil Ingestion and Pica indoor activities occurring over the entire year. Using these data, Hawley (1985) estimated the annual average soil intake rate for older children to be 23.4 mg/day (Table 4-11 ). Thompson and Burmaster (1991) -Parametric Distributions for Soi/Ingestion by Children -Thompson and Burmaster ( 1991) developed .parameterized distributions of soil ingestion rates for children based on a reanalysis of the data collected by Binder et al. (1986). In the original Binder et al. (1986) study, an assumed fecal weight of 15 g/day was used. Thompson and Burmaster reestimated the soil ingestion rates from the Binder et al. (1986) study using the actual stool weights of the study participants instead of the assumed stool weights. Because the actual stool weights averaged only 7.5 g/day, the soil ingestion estimates presented by Thompson and Burmaster (1991) are approximately half of those reported by Binder et al. (1986). Table 4-12 presents the distribution of estimated soil ingestion rates calculated by Thompson and Burmaster ( 1991) based on the three tracers elements (i.e., aluminum, silicon, and titanium), and on the arithmetic average of soil ingestion based on aluminum and silicon. The mean soil intake rates were 97 mg/day for aluminum, 85 mg/day for silicon, and 1,004 mg/day for titanium. The 90th percentile estimates were 197 mg/day for aluminum, 166 mg/day for silicon, and 2, 105 mg/day for titanium. Based on the arithmetic average of aluminum and silicon for each child, mean soil intake was estimated to be 91 mg/day and 90th percentile intake was estimated to be 143 mg/day. Thompson and Burmaster (1991) tested the hypothesis that soil ingestion rates based on the adjusted Hinder et al. (1986) data for aluminum, silicon and the average of these two tracers were lognormally distributed. The distribution of soil intake based on titanium was not tested for lognormality because titanium may be present in food in high . concentrations and the Binder et al. (1986) study did not correct for food sources of titanium (Thompson and Burmaster, 1991 ). Although visual inspection of the distributions for aluminum, silicon, and the average of these tracers all indicated that they may be lognormally distributed, statistical tests indicated that only silicon and the average of the silicon and aluminum tracers were lognormally distributed. Soil intake rates based on / aluminum were not lognormally distributed. Table 4-12 also presents* the lognormal distribution parameters and underlying normal distribution parameters (i.e., the natural logarithms of the data) for aluminum, silicon, and the average of these two tracers. According to the authors, "the parameters estimated from the underlying normal distribution are much more reliable and robust" (Thompson and Burmaster, 1991 ). The advantages of this study are that it provides percentile data and defines the shape of soil intake distributions. However, the number of data points used to fit the distribution was limited. In addition, the study did not generate "new" data. Instead, it provided a reanalysis of previously-reported data using actual fecal weights. No corrections were made for tracer intake from food or medicine and the results may not be Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 4 -Soil Ingestion and Pica representative of long-term intake rates because the data were derived from a short-term study. Sedman and Mahmood (1994) -Soil Ingestion by Children and Adults Reconsidered Using *the Results of Recent Tracer Studies -Sedman and Mahmood (1994) used the results of two recent children's (Calabrese et al. 1989;. Davis et al. 1990) tracer studies to determine estimates of average daily soil ingestion in young children and for over a lifetime. In the two studies, the intake and excretion of a variety of tracers were monitored, and concentrations of tracers in soil adjacent to the children's dwellings were determined (Sedman and Mahmood, 1994). From a mass balance approach, estimates of soil ingestion in these children were determined by dividing the excess tracer intake (i.e., quantity of tracer recovered in the feces in excess of the measured intake) by the average concentration of tracer in soil samples from each child's dwelling. Sedman and Mahmood ( 1994) adjusted the mean estimates of soil ingestion in children for each tracer (Y) from both studies to reflect that of a 2-year old child using the following equation: where: y ' x e (&o.112(yr) I Y; = adjusted mean soil ingestion (mg/day) x = a constant yr= average age (2 years) (Eqn. 4-3) In addition to the study in young children, a study (Calabrese et al., 1989) in adults was conducted to evaluate the tracer methodology. In the adult studies, percent recoveries of tracers were determined in six adults who ingested known quantities of tracers in 1.5 or 0.3 grams of soil. The distribution of tracer recoveries from adults was evaluated using data analysis techniques involving visualization and exploratory data analysis (Sedman and Mahmood, 1994). From the results obtained in these studies, the distribution of tracer . recoveries from adults were determined. In addition, an analysis of variance (AN OVA) and Tukey's multiple comparison methodologies were employed to identify differences in the . recoveries of the various tracers (Sedman and Mahmood, 1994). Frc:im the adult studies, the ANOVA of the natural logarithm of the recoveries of tracers from 0.3 or 1.5 g of ingested soil showed a significant difference (ex =0.05) among the estimates of recovery of the tracers regardless of whether the recoveries were combined or analyzed separately (Sedman and Mahmood, 1994 ). Sedman and Mahmood (1994) also reported that barium, manganese, and zirconium yielded significantly different estimates of soil ingestion than the other tracers (aluminum, silicon, yttrium, titanium, and Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 4 -Soil Ingestion and Pica. vanadium). Table 4-13 presents the Tukey's multiple comparison of mean log tracer recovery in adults ingesting known quantities of soil. The average ages of children in the two recent studies were 2.4 years .in Calabrese, et al. (1989) and 4.7 years in Davis et al. (1990). The mean of the adjusted levels of soil ingestion for a two year old child was 220 mg/kg for the Calabrese*et al. (1989) study and 170 mg/kg for the Davis et al. (1990) study (Sedman and Mahmood, 1994). From the adjusted soil ingestion estimates, based on a normal distribution of means, the mean

estimate for a 2-year old child was 195 mg/day and the overall mean of soil ingestion .and the standard error of the mean was 53 mg/day (Sedman and Mahmood, 1994). Based on uncertainties associated with the method employed, Sedman and Mahmood (1994) recommended a conservative estimate of soil ingestion in young chil.dren of 250 mg/day. Based on the 250 mg/day ingestion rate in a 2-year old child, an average daily soil ingestion over a lifetime was estimated to be 70 mg/day. The lifetime estimates were derived using the equation presented above that describes changes in soil ingestion with age (Sedman and Mahmood, 1994). A/HG Exposure Factors Sourcebook (1994) -The Exposure Factors Sourcebook (AIHC, 1994) uses data from the Calabrese et al. (1990) study to derive soil ingestion rates using zirconium as the tracer. More recent papers indicate that zirconium is not a good tracer. Therefore, the values recommended in the AIHC Sourcebook are not appropriate. Furthermore, because individuals were only studied for_a *short period of time, deriving a distribution of usual intake is not possible and is inappropriate. Calabrese and Stanek (1995) -Resolving Jntertracer Inconsistencies in Soil Ingestion Estimation -Calabrese and Stanek ( 1995) explored sources and magnitude of positive and negative errors in soil ingestion estimates for children on a subject-week and trace element basis. Calabrese and Stanek (1995) identified possible sources of positive errors to be the following:
Ingestion of high levels of tracers before the study starts and low ingestion d.uring study period may result in over estimation of soil ingestion; and
Ingestion of element tracers from a non-food or non-soil source during the study period. Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 4 -Soil Ingestion and Pica Possible sources of negative bias identified by Calabrese and Stanek (1995) are the following: -* Ingestion of tracers in food, but the tracers are not captured in the fecal sample either due to slow lag time or not having a fecal sample available on the final study day; and
Sample* measurement errors which result in diminished detection of fecal tracers, but not in soil tracer levels. The authors rjeveloped an approach which attempted to reduce the magnitude of error in the individual trace element ingestion estimates. Results from a previous study conducted by Calabrese et al. (1989) were used to quantify these errors based on the following criteria: ( 1) a lag period of 28 hours was assumed for the passage of tracers ingested in food to the feces (this value was applied to all subject-day estimates); (2) daily soil ingestion rate was estimated for each tracer for each 24-hr day a fecal sample was obtained; (3) the median tracer-based soil ingestion rate for each subject-day was determined. Also, upper and lower bound estimates were determined based on criteria formed using an assumption of the magnitude of the relative standard deviation (RSD) presented in another study conducted by Stanek and Calabrese (1995a). Daily soil ingestion rates for tracers that fell beyond the upper and lower ranges were excluded from subsequent calculations, and the median soil ingestion rates of the remaining tracer elements were considered the best estimate for that particular day. The magnitude of positive or negative error for a specific tracer per day was derived by determining the difference between the value for the tracer and the median value; (4) negative errors due to missing fecal samples at the end of the study period were also determined (Calabrese and Stanek, 1995). Table 4-14 presents the estimated magnitude of positive and negative error for six tracer elements in the children's study (i.e., conducted by Calabrese et al., 1989). The original. mean soil ingestion rates ranged from a low of 21 mg/day based on zirconium to a high of 459 mg/day based on titanium (Table 4-14). The adjusted mean soil ingestion rate after correcting for negative and positive errors ranged from 97 mg/day based on yttrium to 208 mg/day based on titanium (Table 4-14). Calabrese and Stanek (1995) concluded that correcting for errors at the individual level for each tracer element provides more reliable estimates of soil ingestion. This report is valuable in providing additional understanding of the nature of potential errors in trace element specific estirpates of soil ingestion. However, the operational definition used for estimating the error in a trace element estimate was the observed difference of that tracer from a median tracer value. Specific identification of sources of Exposure Factors Handbook
August 1997 Volume 1-General Factors Chapter 4 -Soil Ingestion and Pica error, or direct evidence that individual tracers were indeed in error was not developed. Corrections to individual tracer means were then made according to how different values for that tracer were from the median values. This approach is based .on the hypothesis that the median tracer value is the most accurate estimate of soil ingestion, and the validity of this assumption depends on the specific set of tracers used in the study and need not be correct. The approach used for the estimation of daily tracer intake is the same as in Stanek and Calabrese (1995a), and some limitations of that approach are mentioned in the review of that study. Sheppard (1995) -Parameter Values to Model the Soil Ingestion Pathway-Sheppard (1995) summarized the available literature on soil ingestion to estimate the amount of soil ingestion in humans for the purposes of risk assessment. Sheppard (1995) categorized the available soil ingestiqn studies into two general approaches: (1) those that measured the soil intake rate with the use of tracers in the soil, and (2) those that estimated soil ingestion based on activity (e.g., hand-to-mouth) and exposure duration. Sheppard (1995) provided estimates of soil intake based on previously published tracer studies. The data from these studies were assumed to be lognormally distributed due to the broad range, the concept that soil ingestion is never zero, and the possibility of very high values. In order to account for skewness in the data, geometric means rather than arithmetic means, were calculated by age, excluding pica and geophagy values. The geometric mean for soil ingestion rate for children under six was estimated to be 100 mg/day. For children over six and adults, the geometric mean intake rate was estimated to be 20 mg/day. Sheppard (1995) also provided soil ingestion estimates for indoor and .outdoor activities based on data from Hawley (1985) and assumptions regarding duration of exposure (Table 4-15). Sheppard's (1995) estimates, based on activity and exposure duration, are quite similar to the mean values from intake rate estimates described in previous sections. The advantages of this study are that the model can be used to calculate the ingestion rate from non-food sources with variability in exposure ingestion rates and exposure durations. The limitation of this study is that it does not introduce new data; previous data are evaluated. In addition, because the model is based on previous data, the same . advantages and limitations of those studies apply. 4.4. SOIL INTAKE AMONG ADULTS Hawley 1985 -Assessment of Health Risk from Exposure to Contaminated Soil -Information on soil ingestion among adults is very limited. Hawley (1985) estimated soil ingestion among adults based on assumptions regarding activity patterns and corresponding ingestion amounts. Hawley (1985) assumed that adults ingest outdoor soil at a rate of 480 mg/day while engaged in yardwork or other physical activity. These outdoor exposures were assumed to occur 2 days/week during 5 months of the year (i.e., Exposure Factors Handbook August 1997 Volume I-General Factors Chapter 4 -Soil Ingestion and Pica May through October). The ingestion estimate was based on the assumption that a 50 µm/thick layer of soil is ingested from the inside surfaces of the thumb and fingers of one hand. Ingestion of indoor housedust was assumed to occur from typical living space activities such as eating and smoking, and work in attics or other uncleaned areas of the house. Hawley (1985) assumed that adults ingest an average of 0.56 mg housedust/day during typical living space activities and 110 mg housedust/day while working in attics. Attic work was assumed to occur 12 days/year. Hawley ( 1985) also assumed that soil comprises 80 percent of household dust. Based on these assumptions about soil intake and the frequency of indoor and outdoor activities, Hawley (1985) estimated the annual average soil intake rate for adults to be 60.5 mg/day (Table 4-16). The soil intake value estimated by Hawley (1985) is consistent with adult soil intake rates suggested by other researchers. Calabrese et al. (1987) suggested that soil intake among adults ranges from 1to100 mg/day. According to Calabrese et al. (1987), these values "are conjectural and based on fractional estimates" of e*arlier Center for Disease Control (CDC) estimates. In an evaluation of the scientific literature concerning soil ingestion rates for children and adults (Krabliri, 1989), Arco Coal Company suggested that 10 mg/day may be an appropriate value for adult soil ingestion. This value is based on "extrapolation from urine arsenic epidemiological studies and information on mouthing behavior and time activity patterns" (Krablin, 1989). Calabrese et al. (1990) -Preliminary Adult Soil Ingestion Estimates: Results.of a Pilot Study-Calabrese et al. (1990) studied six adults to evaluate the extent to which they ingest* soil. This adult study was originally part of the children soil ingestion study conducted by Calabrese and was used to validate part of the analytical methodology used in the children study. The participants were six healthy adults, three males and three females, 25-41 years old. Each volunteer ingested one empty gelatin capsule at breakfast and one at dinner Monday, Tuesday, and Wednesday during the first week of the study. During the second week, they ingested 50 mg of soil within a gelatin capsule at breakfast and at dinner (a total of 100 mg of sterilized soil per day) for 3 days. For the third week, the participants ingested 250 mg of sterilized soil in a gelatin capsule at breakfast and at dinner (a total of 500 mg of soil per day) during the three days. Duplicate meal samples (food and beverage) were collected from the six adults .. The sample included all foods ingested from breakfast Monday, through the evening meal Wednesday during each of the 3 weeks. In addition, all medications and vitamins ingested by the adults were collected. Total excretory output were collected from Monday noon through Friday midnight over 3 consecutive weeks. Table 4-17 provides the mean and median values of soil ingestion for each element by week. Data obtained from the first week, when empty gelatin capsules were ingested, may be used to derive an estimate of soil intake by adults. The mean
intake rates for the eight tracers are: Al, 110 mg; Ba, -232 mg; Mn, 330 mg; Si, 30 mg; Ti, 71 mg; V, 1,288 mg; Y, 63 mg; and Zr, 134 mg. Exposure Factors Handbook August 1997 Volume I-General Factors Chapter 4 -Soil Ingestion and Pica The advantage of this study is that it provides quantitative estimates of soil ingestion for adults. The study also corrected for tracer concentrations in foods and medicines. However, a limitation of this study is that a limited number of subjects were studied. In addition, the subjects were only studied for one week before soil capsules were ingested. 4.5. PREVALENCE OF PICA Th_e scientific literature define pica as "the repeated eating of non-nutritive substances" (Feldman, 1986). For the purposes of this handbook, pica is defined as an deliberately high soil ingestion rate. Numerous articles have been published that report on the incidence of pica among various populations. However, most of these papers describe pica for substances other than soil including sand, clay, paint, plaster, hair, string, cloth, glass, matches, paper, feces, and various other items. These papers indicate* that the pica occurs in approximately half of all children between the ages of 1 and 3 years (Sayetta, 1986). The incidence of deliberate ingestion behavior in children has been shown to differ for different subpopulations. The incidence rate appears to be higher for black children than for white children. Approximately 30 percent of black children aged 1 to. 6 years are reported to have deliberate ingestion behavior, compared with 10 to 18 percent of white children in the same age group (Danford, 1982). There does not appear to be any sex differences in the incidence rates for males or females (Kaplan and Sadock, 1985). Lourie et al. (1963) states that the incidence of pica is higher among children in lower socioeconomic groups (i.e., 50 to 60 percent).thah in higher income families (i.e., . about 30 percent). Deliberate soil ingestion behavior appears to be more common in rural areas (Vermeer and Frate,
1979). A higher rate of pica has also been reported for pregnant women and individuals with poor nutritional status (Danford, 1982). In general, deliberate ingestion behavior is more frequent and more severe in mentally retarded children than in children in the general population (Behrman and Vaughan 1983, Danford 1982, Forfar and Arneil 1984, Illingworth 1983, Sayetta 1986). It should be noted that the pica statistics cited above apply to the incidence of general pica and not soil pica. Information on the incidence of soil pica is limited, but it appears that soil pica is less common. A study by Vermeer and Frate (1979) showed that the incidence of geophagia (i.e., earth-eating) was about 16 percent among children from a rural black community in Mississippi. However, geophagia was described as a cultural practice among the community. surveyed and may not be representative of the general population. Average daily consumption of soil was estimated to be 50 g/day. Bruhn and Pangborn (1971) reported the incidence of pica for "dirt" to be 19 percent in children, 14 percent in pregn.ant women, and 3 percent in nonpregnant women. However, "dirt" was not clearly defined. The Bruhn and Pangborn (1971) study was conducted among 91 black, low income families of migrant agricultural workers in California. Based on the data from the five key tracer studies (Binder et al., 1986; Clausing et al., 1987; Van W1]nen et Exposure Factors Handbook August 1997 Volume I-General Factors Chapter 4 -Soil Ingestion and Pica al., 1990; Davis et al., 1990; and Calabrese et al., 1989) only one child out of the more .* than 600 children involved in all of these studies ingested an amount of soil significantly greater than the range for other children. Although these studies did not include data for all populations and were representative of short-term ingestions only, it can be assumed that the incidence rate of deliberate soil ingestion behavior in the general population is low. However, it is incumbent upon the user to use the appropriate value for their specific study population.
4.6. DELIBERATE SOIL INGESTION AMONG CHILDREN Information on the amount of soil ingested by children with abnormal soil ingestion behavior is limited. However, some evidence suggests that a rate on the order of 10 g/day may not be unreasonable.
Calabrese et al. (1991) -Evidence of Soi/ Pica Behavior and Quantification of Soil Ingestion -Calabrese et al. (1991) estimated that upper range soil ingestion values may
range from 5-7 grams/day. This estimate was based on observations of one pica child among.the 64 children who participated in the study. In the study, a 3.5-year old female exhibited extremely high soil ingestion behavior during one of the two weeks of observation. Intake ranged from 74 mg/day to 2.2 g/day during the first week of observation and. 10.1 to 13.6 g/day during the second week of observation (Table 4-18). These results are based on mass-balance analyses for seven (i.e., aluminum, barium, manganese, silicon, titanium, vanadium, and yttrium) of the eight tracer elements used. Intake rates based on zirconium was significantly lower but Calabrese et al. (1991) indicated that this may have "resulted from a limitation in the analytical protocol." Calabrese and Stanek (1992) -Distinguishing Outdoor Soil Ingestion from Indoor Dust Ingestion in-a Soil Pica Child-Calabrese and Stanek (1992) quantitatively distinguished the amount of outdoor soil ingestion from indoor dust ingestion in a soil pica child. This study was based on a previous mass-balance study (conducted in 1991) in which a 3-1/2 year old child ingested 10-13 grams of soil per day over the second week of a .2-week soil ingestion study. Also, the previous study utilized a soil tracer methodology with eight different tracers (Al, Ba, Mn, Si, Ti, V, Y, Zr). The reader is referred to Calabrese et al. (1989) for a detailed description and results of the soil ingestion study. Calabrese and Stanek (1992) distinguished indoor dust from outdoor soil in ingested soil based on a methodology which compared differential element ratios. Table 4-19 presents tracer ratios of soil, dust, and residual fecal samples in the soil pica child. Calabrese and Stanek (1992) reported that there was a maximum total of 28 pairs of tracer ratios based on eight tracers. However, only 19 pairs of tracer ratios were available for quantitative evaluation as shown in Table 4-19. Of these 19 pairs, 9 fecal Exposure Factors Handbook August 1997 _i Volume I-General Factors Chapter 4 -Soil Ingestion and Pica tracer ratios fell within the boundaries for soil and dust (Table 4-19). For these 9 tracer soils, an interpolation was performed to estimate the relative contribution of soil and dust to the residual fecal tracer ratio. The other 10 fecal tracer ratios that fell outside the soil and dust boundaries were concluded to be 100 percent of the fecar tracer ratios from soil origin (Calabrese and Stanek, 1992). Also, the 9 residual fecal samples within the boundaries revealed that a high percentage (71-99 percent) of the residual fecal tracers were estimated to be of soil origin. Therefore, Calabrese and Stanek (1992) concluded. that the predominant proportion of the fecal tracers was from outdoor soil and not from *indoor dust origin. In conducting a risk assessment for TCDD, U.S. EPA (1984) used 5 g/day to represent the soil intake rate for pica children. The Centers for Disease Control (CDC) also investigated the potential for exposure to TCDD through the soil ingestion route. CDC used a value of 10 g/day to represent the amount of soil that a child with deliberate soil ingestion behavior might ingest (Kimbrough et al., 1984). These values are consistent with those observed by Calabrese et al. (1991 ). 4. 7. RECOMMENDATIONS The key studies described in this section were used to recommend values for soil intake among children. The key and relevant studies used different survey designs and . study populations. These studies are summarized in Table 4-20. For example, some of the studies considered food and nonfood sources of trace elements, while others did not. In other studies, soil ingestion estimates were adjusted to account for the contribution of house dust to this estimate. Despite these differences, the mean and upper-percentile estimates reported for these studies are relatively consistent. The confidence rating for soil intake recommendations is presented in Table 4-21. It is important, however, to understand the various uncertainties associated with these values. First, individuals were not studied for sufficient periods of time to get a good estimate of the usual intake. Therefore, the values presented in this section may not be representative of long term exposures. Second, the experimental error in measuring soil ingestion values for individual children is also a source of uncertainty. For example, incomplete sample collection of both input (i.e., food and nonfood sources) and output (i.e., urine and feces) is a limitation for some of the studies conducted. In addition, an individual's soil ingestion value may be artificially high* or low depending on the extent to which a mismatch between input and output occurs due to individual variation in the gastrointestinal transit time. Third, the degree to which the tracer elements used in these studies are absorbed in the human body is uncertain. Accuracy of the soil ingestion estimates depends on how good this assumption is. Fourth, there is uncertainty with regard to the homogeneity of soil samples and the accuracy of parent's knowledge about Exposure Factors Handbook August 1997 Volume I -General.Factors Chapter 4 -Soil Ingestion and Pica their child's playing areas. Fifth, all the soil ingestion studies presented in this section with the exception of Calabrese et al. (1989) were conducted during the summer wheri soil contact is more likely. Although the recommendations presented below are derived from studies which were mostly conducted in the summer, exposure during the winter months when the ground is frozen or snow covered should not be considered as zero. Exposure during these months, although lower than in the summer months, would not be zero because some portion of the house dust comes from outdoor soil.
Soi/ Ingestion Among Children -Estimates of the amount of soil ingested by children are summarized in Table 4-22. The mean values ranged from 39 mg/day to 271 mg/day with an average of 146 mg/day for soil ingestion and 191 mg/day for soil and dust ingestion. Results obtained using titanium as a tracer in the Binder et al. (1986) and Clausing et al. (1987) studies were not considered in the derivation of. this recommendation because these studies did not take into consideration other sources of the element in the diet which for titanium seems to be significant. Therefore, these values may overestimate the soil intake. One can note that this group of mean values is consistent with the 200 mg/day value that EPA programs have used as a conservative mean estimate. Taking into consideration that the highes.t values were seen with titanium, which may exhibit greater variability than the other tracers, and the fact that the Calabrese et al. (1989) study included .a pica child, 100 mg/day is the best estimate of the mean for children under 6 years of age. However, since the children were studied for short periods oftime and the prevalence of pica behavior is not known; excluding the pica child from the calculations may underestimate soil intake rates. It is plausible that many children may exhibit some pica behavior if studied for longer periods of time. Over the period of study, upper percentile values ranged from 106 mg/day to 1 ,4;32 mg/day with an average of 383 mg/day for soil ingestion and 587 mg/day for soil and dust ingestion. Rounding to one significant figure, the recommended upper percentile soil ingestion rate for children is 400 mg/day. However, since the period of study was short,. these values are not estimates of usual intake. The recommended values for soil ingestion among children and adults are summarized in Table 4-23. Data on soil ingestion rates for children who deliberately ingest soil are also limited. An ingestion rate of 10 g/day is a reasonable value for use in acute exposure assessments, based on the available information. It should be noted, however, that this value is based on only one pica child observed in the Calabrese et al. (1989) study. Soil Ingestion Among Adults-Only three studies have attempted to estimate adult soil ingestion. Hawley (1985) suggested a value of 480 mg/day for adults engaged in outdoor activities and a range of 0.56 to 110 mg/day of house dust during indoor activities. These Exposure Factors Handbook August 1997

.Volume I -General Factors Chapter 4 -Soil Ingestion and Pica estimates were derived from assumptions about soil/dust levels on .hands and mouthing behavior; no supporting measurements were made. Making further assumptions about frequencies of indoor and outdoor activities, Hawley (1985) derived an annual average of 60.5 Given the lack of supporting measurements, these estimates must be

considered conjectural. Krablin (1989) used arsenic levels in urine (n=26) combined with information on mouthing behavior and activity patterns to suggest an* estimate for adult soil ingestion of 10 mg/day. The study protocols are not well described and has not been formally published. Finally, Calabrese et al. (1990) conducted a tracer study on 6 adults and found a range of 30 to 100 mg/day. This study is probably the most reliable of the
three, but still has two significant uncertainties: (1) representativeness of the general population is unknown due to the small study size (n=6); and (2) representativeness of long-term behavior is unknown since the study was conducted over only 2 weeks. In the past, many EPA risk assessments have assumed an adult soil ingestion rate of 50 mg/day for industrial settings and 100 mg/day for residential and agricultural scenarios. These values are within the range of estimates from the studies discussed above. Thus, 50 mg/day still represents a reasonable central estimate of adult soil ingestion and is the recommended value in this handbook. This recommendation is clearly highly uncertain; however, and as indicated in Table 4-21, is given a low confidence rating. Considering the uncertainties in the central estimate, a recommendation for an upper percentile value would be inappropriate. Table 4-23 summarizes soil ingestion recommendations for adults. Exposure Factors Handbook August 1997 Table 4-1. Estimated Daily Soil Ingestion Based on Aluminum, Silicon, and Titanium Concentrations Standard Geometric Estimation Mean Median -Deviation Range 95th Percentile Mean Method (mo/davl (mo/davl (mo/davl (mo/davl (mo/davl (mo/davl Aluminum 181 121 203 25-1,324 584 128 Silicon 184 136 175 31-799 5,78 130 Titanium 1,834 618 3,091 4-17,076 9,590 401 Minimum 108 88 121 4-708 386 65 Source: Binder et al., 1986.

Table 4-2. Calculated Soil Ingestion by Nursery School Children Soil Ingestion as Soil Ingestion as Soil Ingestion as Sample Calculated from Ti Calculated from Al Calculated from AIR Limiting Tracer Child Number lmo/davl lmo/davl lmo/davl lmo/dav\ 1 L3 103 300 107 103 L14 154 211 172 154 L25 130 23 -23 2 L5 131 -71 71 L13 184 103 82 82 L27 142 81 84 81 3 L2 124 42 84 42 L17 670 566 174 174 4 L4 246 62 145 62 L11 2,990 65 139 65 5 LS 293 -108 108 L21 313 -152 152 6 L12 1,110 693 362 362 L16 176 -145 145 7 L18 11,620 -120 120 L22 11,320 77 -77 8 L1 3,060 82 96 82 9 L6 624 979 111 111 10 L7 600 200 124 124 11 L9 133 -95 95 12 L10 354 195 106 106 13 L15 2,400 -48 48 14 L19 124 71 93 71 15 L20 269 212 274 212 16 L23 1,130 51 84 51 17 L24 64 566 -64 18 L26 184 56 -56 Arithmetic Mean 1 431 232 129 105 Source: Adanted from Clausino et al. 1987.

Table 4-3. Calculated Soil lnaestion bv Hosoitalized, Bedridden Children Soil Ingestion as Soil Ingestion as Calculated from Ti Calculated from Al Limiting Tracer *Child Samele lma/dav) lma/dav) lma/dav) 1 .G5 3,290 57 57 G6 4,790 71 71 2 G1 28 26 26 3 G2 6,570 94 84 GB 2,480 57 57 4 G3 28 77 28 5 G4 1,100 30 30 6 G7 58 38 38 Arithmetic Mean 2,293 56 49 Source: Adaoted from Clausina et al. 1987. Table 4-4. Mean and Standard Deviation Percentage Recovery of Eight Tracer Elements 300 mg Soil Ingested 1500 mg Soil Ingested Tracer Element Mean SD Mean SD Al 152.8 107.5 93.5 15.5 Ba 2304.3 4533.0 149.8 69.5 Mn 1177.2 1341.0 248.3 183.6 Si 139.3 149.6 91.8 16.6 Ti 251.5 316.0 286.3 380.0 v 345.0 247.0 147.6 66.8 y 120.5 42.4 87.5 12.6 Zr 80.6 43.7 54.6 33.4 Source: Adaoted from Calabrese et al., 1989. Table 4-5. 'Soil and Dust lnoestion Estimates for Children Aoed 1-4 Years Intake (mg/day)* Tracer Element N Mean Median SD 95th Maximum Percentile Aluminum soil 64 153 29 852 223 6,837 dust 64 317 31 1,272 506 8,462 soil/dust combined 64 154 30 629 478 4,929 Silicon soil 64 154 40 693 276 5,549 dust 64 964 49 6,848 692 54,870 soil/dust combined 64 483 49 3,105 653 24,900 Yttrium soil 62 85 9 890 106 6,736 dust 64 62 15 687 169 5,096 soil/dust combined 62 65 11 717 159 5,269 Titanium soil 64 218 55 1,150 1,432 6,707 dust 64 163 28 659 1,266 3,354 soil/dust combined 64 170 30 691 1 059 3597 a Corrected for Tracer Concentrations in Foods Source: Adaoted from Calabrese et al. 1989. Table 4-6. Average Daily Soil Ingestion Values Based on Aluminum, Silicon, and Titanium as Tracer Elements* Standard Error of the Element Mean Median Mean Range (maid) (maid) !maid) lmald)b Aluminum 38.9 25.3 14.4 279.0 to 904.5 Silicon 82.4 59.4 12.2 -404.0 to 534.6 Titanium 245.5 81.3 119.7 -5,820.8 to 6, 182.2 Minimum 38.9 25.3 12.2 -5,820.8 Maximum 245.5 81.3 119.7 6, 182.2 a Excludes three children who did not provide any samples (N=101 ). b Negative values occurred as a result of correction for nonsoil sources of the tracer elements. Source: Adaoted from Davis et al., 1990. Table 4-7. Geometric Mean (GM) and Standard Deviation (GSD) LTM Values for Children at Daycare Centers and Campi:irounds Daycare Centers Campi:irounds Age (yrs) Sex n GMLTM GSD LTM n GMLTM GSD LTM (mi:i/day) (mi:i/day) (mi:i/day) (mi:i/day) <1 Girls 3 81 1.09 ---Boys 1 75 ----1-<2 Girls 20 124 1.87 3 207 1.99 Boys 17 114 1.47 5 312 *2.58 2-<3 Girls 34 118 1.74 4 367 2.44 Boys 17 96 1.53 8 232 2.15 3-4 Girls 26 111 1.57 6 164 1.27 Boys 29 110 1.32 8 148 1.42 4-<5 Girls 1 180 -19 164 1.48 Boys 4 99 1.62 18 136 1.30 All girls \. 86 117 1.70 36 179 1.67 All boys 72 104 1.46 42 169 1.79 Total 162' 111 1.60 78b 174 1.73 ' Age and/or sex not registered for eight children. b Age not registered for seven children. Source: Adapted from Van Wijnen et al., 1990. Table 4-8. Estimated Geometric Mean L TM Values of Children Attending Daycare Centers According to Acie, Weather Category, and Samplinq Period First Sampling Period Second Sampling Period Weather Category Age (years) Estimated Geometric Mean Estimated Geometric Mean LTM Value LTM Value n lma/davl

n lmo/davl Bad <1 3 94 3 67 (>4 days/week precipitation) 1-<2 18 103 33 80 2-<3 33 109 48 91 4-<5 5 124 6 109 Reasonable <1 1 61 (2-3 days/week precipitation) 1-<2 10 96 2-<3 13 99 3-<4 19 94 4-<5 1 61 Good <1 4 102 (<2 days/week precipitation) 1-<2 42 229 2-<3 65 166 3-<4 67 138 4-<5 10 132 Source: Van Wiinen et al. 1990.

Table 4-9. Distribution of Average (Mean) Daily Soil Ingestion Estimates Per Child for 64 Children* (mg/day) Type of Estimate Overall A1 Ba Mn Si Ti v y Zr Number of Samples (64) (64) (33) (19) (63) (56) (52) (61) (62\ Mean 179 122 655 1,053 139 271 112 165 23 25th Percentile 10 10 28 35 5 8 8 0 0 50th Percentile 45 19 65 121 32 31 "47 15 15 75th Percentile 88 73 260 319 94 93 177 47 41 90th Percentile 186 131 470 478 206 154 340 105 87 95th Percentile 208 254 518 17,374 224 279 398 144 117 Maximum 7,703 4,692 17,991 17,374 4,975 12,055 845 8,976 208 a For each child, estimates of soil ingestion were formed on days 4-8 and the mean of these estimates was then evaluated for each child. The values in the column "overall" correspond to percentiles of the distribution of these means over the 64 children. When specific trace elements were not excluded via the relative standard deviation criteria, estimates of soil ingestion based on the specific trace element were formed for 108 days for each subject. The mean soil ingestion estimate was again evaluated. The distribution of these means for specific trace elements is shown. Source: Stanek and Calabrese, 1995a. Table 4-10. Estimated Distribution of Individual Mean Daily Soil Ingestion Based on Data for 64 Subjects Projected Over 365 Days" Range 1 -2,268 mg/db 50th Percentile (median) 75 mg/d 90th Percentile 1, 190 mg/d 95th Percentile 1 751 maid " Based on fitting a log-normal distribution to model daily soil ingestion values. b Subject with pica excluded. Source: Stanek and Calabrese 1995a. Table 4-11. Estimates of Soil Ingestion for Children Annual Average Exposure -Days/Year Fraction Soil Soil Intake Scenarios Media lma/dav) Activitv Content Cma/dav\ Young Child (2.5 Years Old) Outdoor Activities (Summer) Soil 250 130 1 90 Indoor Activities (Summer) Dust 50 182 0.8 20 Indoor Activities (Winter Dust 100 182 0.8 40 TOTAL SOIL INTAKE 150 Older Child (6 Years Old) Outdoor Activities (Summer) Soil 50 152 1 21 Indoor Activities (Year-Round) Dust 3 365 0.8 2.4 TOTAL SOIL INTAKE 23.4 Source: Hawley, 1985. Table 4-12. Estimated Soil Ingestion Rate Summary Statistics and Parameters for Distributions Using Binder et al. (1986) Data with Actual Fecal Weights Soil Intake (ma/day) Trace Element Basis A1 Si Ti MEAN" Mean 97 85 1,004 91 Min 11 10 1 13 10th 21 19 3 22 20th 33 23 22 34 30th 39 36 47 43 40th 43 52 172 49 Med 45 60 293 59 60th 55 65 475 69 70th 73 79 724 92 80th 104 106 1,071 100 90th 197 166 2,105 143 Max 1,201 642 14,061 921 Lognormal Distribution Parameters Median 45 60 --59 Standard Deviation 169 95 --126 Arithmetic Mean 97 85 --91 Underlying Normal Distribution Parameters Mean 4.06 4.07 --4.13 Standard Deviation 0.88 0.85 --0.80

MEAN = arithmetic average af sail ingesiion based on aluminum and silicon. Source: Thomoson and Burmaster, 1991.

Table 4-13. Tukey's Multiple Comparison of Mean Log Tracer Recovery in Adults Ingesting Known Quantities of Soil Tracer Reported Mean Age Adjusted Mean lma/davl . lma/davl Calabrese et al., 1989 Study Aluminum 153 160 Silicon 154 161 Titanium 218 228 Vanadium 459 480 Yttrium 85 89 Davis et al., 1990 Study Aluminum 39 53 Silicon 81 111 Titanium 246 333 a Age adjusted mean estimates of soil ingestion in young children. Mean estimates of soil ingestion for each tracer in each study were adjusted using the following equation: Y = x e(*0*112""'i, where Y =adjusted mean soil ingestion (mg/day), x =a constant, and yr= age in years. Source: Sedman and Mahmood 1994. Table 4-14. Positive/Negative Error (bias) in Soil Ingestion Estimates in the Calabrese et al. (1989) Mass-balance Study: Effect on Mean Soil lnQestion Estimate (mQ/day)' Neaative Error Lack of Fecal Sample on Final Other Total Negative Total Positive Original Adjusted Study Dav Causesb Error Error Net Error Mean Mean Aluminum

14 11 25 43 +18 153 . 136 Silicon 15 6 21 41 +20 154 133 Titanium 82 187 269 282 +13 218 208 Vanadium 66 55 121 432 +311 459 148 Yttrium 8 26 34 22 -12 85 97 Zirconium 6 91 97 5 -92 21 113 ' How to read table: for example, aluminum as a soil tracer displayed both negative and positive error. The cumulative total negative error is estimated to bias the mean estimate by 25 mg/day downward. However, aluminum has positive error biasing the original mean upward by 43 mg/day. The net bias in the original mean was 18 mg/day positive bias. Thus, the original 156 mg/day mean for aluminum should be corrected downward to 136 mg/day. b Values indicate impact on mean of 128-subject-weeks in milligrams of soil ingested per day. Source: Calabrese and Stanek 1995.

Table 4-15. Soil Ingestion Rates for Assessment Purposes Soil Load on Soil Exposure Suggested Average Daily Soil Receptor Age Setting Hands Ingestion Rate Exposure Ingestion (mg/cm2) (mg/hr) Durations (mg/day) (hr/yr) Pica Child ---1,000 200 500 2.5 yrs Outdoor 0.5 20 . 1,000 50 Indoor 0.4 3 Remaining* 60 6 yrs Outdoor 0.5 10 700 20 Indoor 0.04 0.15 5,000 2 Adult Gardening 1.0 20 300 20 Indoor 0.04 0.03 5,000 0.4 a Hawley (1985) assumed the child spent all the time at home, so that the indoor time was 8,760 hours/year minus the outdoor time. Source: Sheppard, 1995 Table 4-16. Estimates of Soil Ingestion for Adults Annual Average Soil Exposure Days/Year Fraction Soil Intake Scenarios Media lma/davl Activitv Content lma/davl Adult Work in attic (year-round) Dust 110 12 0.8 3 Living Space (year-round) Dust 0.56 365 0.8 0.5 Outdoor Work (summer) Soil 480 43 1 57 TOTAL SOIL INTAKE 60.5 Source: Hawley, 1985. Table 4-17. Adult Daily Soil Ingestion Estimates by Week and Tracer Element After Subtracting Food and Capsule Ingestion, Based on Median Amherst Soil Concentrations: Means and Medians Over Subjects (mg)" Week Al Ba Mn Si Ti v y Zr Means 1 110 -232 330 30 71 1,288 63 134 2 98 12,265 1,306 14 25 43 21 58 3 28 201 790 -23 896 532 67 -74 Medians 1 60 -71 388 31 102 1,192 44 124 2 85 597 1,368 15 112 150 35 65 3 66 386 831 -27 156 047 60 -144 a Data were converted to milligrams b Negative values occur because of correction for food and capsule ingestion. Source: Calabrese et al. 1990 Table 4-18. Daily Soil Ingestion Estimation in a Soil-Pica Child by Tracer and by Week (mg/day) Week 1 Week2 Tracer Estimated Soil Estimated Soil lnaestion lnaestion Al 74 13,600 Ba 458 12,088 Mn 2,221 12,341 Si 142 10,955 Ti 1,543 11,870 v 1,269 10,071 y 147 13,325 Zr 86 2 695 Source: Calabrese et al. 1991 Table 4-19. Ratios of Soil, Dust, and Residual Fecal Samples in the Soil Pica Child Estimated % of Residual Fecal Tracers of Tracer Ratio Pairs Soil Fecal Dust Soil Origin as Predicted by Specific Tracer Ratios 1. Mn/Ti 208.368 215.241 260.126 87 2. Ba/Ti 187.448 206.191 115.837 100 3. Si/Ti 148.117 136.662 7.490 92 4. V/Ti 14.603 10.261 17.887 100 5. Ai/Ti 18.410 21.087 13.326 100 6. Y/Ti 8.577 9.621 5.669 100 7. Mn/Y 24.293 22.373 45.882 100 8. Ba/Y 21.854 21.432 20.432 71 9. Si/Y 17.268 14.205 1.321 81 10. V/Y 1.702 1.067 3.155 100 11. Al/Y 2.146 2.192 2.351 88 12. Mn/Al 11.318 10.207 19.520 100 13. Ba/Al 10.182 9.778 8.692 73 14. Si/Al 8.045 6.481 0.562 81 15. VIAi 0.793 0.487 1.342 100 16. SiN 10.143 13.318 0.419 100 17. Mn/Si 1.407 1.575 34.732 . 99 18. Ba/Si 1.266 1.509 15.466 83 19. Mn/Ba 1.112 1.044 2.246 100 Source: Calabrese and Stanek, 1992. Table 4-20. Soil Intake Studies Number of Population Studied Studv Studv Tvoe Observations Aae Comments CHILDREN KEY STUDIES: Binder et al., 1986 Tracer study using aluminum, silicon, 59 children 1-3 years Children living near lead Did not account for tracer in food and titanium smelter in Montana and medicine; used assumed fecal weight of 15 g/day; short-term study conducted over 3 days Calabrese et al., 1989 Tracer -mass balance study using 64 Children 1-4 years Children from greater Corrected for tracer in food and aluminum, barium, manganese, silicon, Amherst area of medicine; study conducted over titanium, vanadium, ytrium, and Massachusetts; highly-two-week period; used adults to zirconium educated parents validate methods; one pica child in study group. Clausing et al., 1987 Tracer study using aluminum, acid 18 nursery school 2-4 years Dutch children Did not account for tracer in food insoluble residue, and titanium children; 6 and medicines; used tracer-based hospitalized intake rates for hospitalized children children as background values; short-term study conducted over 5 days Davis et al., 1990 Tracer -mass balance study using 104 children 2-7 years Children from 3-city area Corrected for tracer in food and aluminum silicon and titanium in Washington State medicine; short-term study conducted over seven-day period;

collected information on demographic characteristics affecting soil intake. Stanek and Calabrese, Adjusted soil intake estimates B4 children 1-4 years Same children as in Based on data from Calabrese et 1995a Calabrese et al., 1989 al., 1989 Stanek and Calabrese, Recalculated intake rates based on three 164 children 1-7 years Children from three Based on studies of Calabrese et 1995b previous mass-balance studies using the 6 adults 25-41 years mass-balance studies al., 1989; Davis et al., 1990; and Best Tracer Method Calabrese et al., 1990. Van Wijnen et al., 1990 Tracer study using aluminum, acid 292 daycare 1-5 years Dutch children Did not account for tracer in food insoluble residue, and titanium children; 78 and medicines; used tracer-based campers; 15 intake for hospitalized children as hospitalized background values; evaluated children population (campers) with greater access to soil; evaluated differences in soil intake due to weather conditions. CHILDREN RELEVANT STUDIES: AIHC, 1994 Reanalysis of data from Calabrese et al., 6 adults 21-41 years Health adults Used data from Calabrese et al. 1990 (1990) study to derive soil ingestion rates using zirconium as a tracer; recent studies indicate that zirconium is not a good tracer Calabrese and Stanek, Evaluated errors in soil ingestion 64 children 1-4 years Study population of Based on Calabrese et al., 1989 1995 estimates Calabrese et al. 1989 data.

Table 4-20. Soil Intake Studies (continued) Number of Population Studied Studv Studv Tvne Observations Ane Comments CHILDREN RELEVANT STUDIES (continued): Day et al., 1977 Measured dirt on sticky sweets Not specified Not specified Not specified Based on observations and crude and assumed number of sweets measurements. eaten per day Duggan and Williams, 1977 Measured soil on fingers and Not specified Not specified Areas around London Based on observations and crude observed mouthing behavior measurements. Hawley, 1985 Assumed soil intake rates based Not specified Young children, Not specified No data on soil intake collected; on nature and duration of activities older children, estimates based on assumptions adults regarding data from previous studies. Lepow et al., 1974; 1975 Measured soil on hands and 22 children 2-6 years Urban children from Based on observations over 3-6 observed mouthing behavior Connecticut hours of play and crude measurement techniques. Sedman and Mahmood, 1994 Adjusted data from earlier tracer-64 children from Adjusted to 2-Same children as in Based on data from Calabrese et al., mass balance studies to generate Calabrese et al., year old child Calabrese et al., 1989 1989 and Davis et al., 1990. mean soil intake rates for a 2-year 1989 study and 104 and Davis et al., 1990 old child children from Davis et study al., 1990 study Sheppard, 1995 Provides estimates based on the Not specified 1 year-adults Various Presents mean estimates for current literature on soil ingestion (age not children and adults; provides from tracer methods and specified) ingestion estimates for indoor and recommends values for use in outdoor activities based on Hawley, assessments 1985. Thompson and Burmaster, Re-evaluation of Binder et al., 59 children 1-3 years Children living near Re-calculated soil intake rates from 1991 1986 data lead smelter in

Binder et al., 1986 data using actual Montana fecal weights instead of assumed weights. ADULT SOIL INTAKE STUDIES: Hawley, 1985 Assumed soil intake raies based Not specified Young children, Not specified ' No data on soil intake collected; on nature and duration of activities older children, estimates based on assumptions adults regarding data from previous studies. Calabrese et al., 1990 Measured excretory output after 6 adults 21-41 years Healthy adult Data used to validate the analytical ingestion of capsules with volunteers methodology used in the children's sterilized s.oil study (Calabrese, 1989). PICA STUDIES: Calabrese et al., 1991 Tracer-mass balance 1 pica child 3.5 years 1 pica child from Child was observed as part of the greater Amherst area Calabrese et al., 1989 study. of Massachusetts Calabrese and Stane.k, 1992 Reanalysis of data from Calabrese 1 pica child 3.5 years 1 pica child from Distinguished between outdoor soil etal., 1991 greater Amherst area ingestion and indoor dust ingestion of Massachusetts in a soil oica child.

Table 4-21. Confidence in Soil Intake Recommendation Considerations Rationale Ralina Study Elements *D Level of peer review , All key studies are from peer review literature. High *D Accessibility Papers are widely available from peer review journals. High *D Reproducibility Methodology used was presented, but results are difficult to Medium reproduce. *D Focus on factor of interest The focus of the studies was on estimating soil intake rate by High (for children) children; studies did not focus on intake rate by adults. Low (for adults) *D Data pertinent to U.S. Two of the key studies focused on Dutch children; other Medium studies used children from specific areas of the U.S. *D Primary data All the studies. were based on primary data. High *D Currency Studies were conducted after 1980. High *D Adequacy of data collection Children were not studied long enough to fully characterize day Medium period to day variability. *D Validity of approach The basic approach is the only practical way to study soil Medium intake, but refinements are needed in tracer selection and matching input with outputs. The more recent studies corrected the data for sources of the tracers in food. There are, however, some concerns about absorption of the tracers into the body and lag time between input and output. *D Study size The sample sizes used in the key studies were adequate for Medium (for children) children. However, only few adults have been studied. Low (for adults) *D Representativeness of the The study population may not be representative of the U.S. in Low population terms of race, socio-economics, and geographical location; Studies focused on specific areas; two of the studies used Dutch children. *D Characterization of variability Day-to-day variability was not very well characterized. Low *D Lack of bias in study design The selection of the population studied may introduce some Medium (high rating is desirable) bias in the results (i.e., children near a smelter site, volunteers in nursery school, Dutch children). *D Measurement error Errors may result due to problems with absorption of the Medium tracers in the body and mismatching inputs and outputs. Other Elements *D Number of studies There are 7 key studies. High *D Agreement between researchers Despite the variability, there is general agreement among Medium researchers on central estimates of daily intake for children. Overall Rating Studies were well designed; results were fairly consistent; Medium (for children sample size was adequate for children and very small for -long-term central adults; accuracy of methodology is uncertain; variability cannot estimate) be characterized due to limitations in data collection period. Low (for adults) Insufficient data to recommend upper percentile estimates for Low (for upper both children and adults. oercentile\ Table 4-22. Summary of Estimates of Soil lnaestion by Children Mean lmn/dav\ Unner Percentile lma/dav\ References Al Si AIR' Ti y Al Si Ti y 181 184 584 578 Binder et al. 1986 230 129 Clausing et al. 1987 39 82 245.5 Davis et al. 1990 64.5b 160b 268.4b 153 154 218 85 223 276 1,432 106 Calabrese et al. 1989 154b 483b 170b 65b 478b 653b 1,059b 159b 122 139 --271 165 254 224 279 144 Stanek and Calabrese, 1995a 133' 217' Stanek and Calabrese, 1995b 69-120' Van W1}nen et al. 1990 Average = 146 mg/day soil 383 mg/day soil 191 mg/day soil and dust 587 mg/day soil and dust combined combined a AIR = Acid Insoluble Residue b Soil and dust combined ' BTM d L TM* corrected value Table 4-23. Summary of Recommended Values for Soil Ingestion Population Mean Upoer Percentile Children 100 mg/day a 400 mg/day b Adults 50 mg/dw --Pica child 10 a/dav ---a 200 mg/day may be used as a conservative estimate of the mean (see text). b Study period was short; therefore, these values are not estimates of usual intake. c To be used in acute exoosure assessments. Based on onlv one oica child <Calabrese et al. 1989). REFERENCES FOR CHAPTER 4 American Industrial Health Council (AIHC). (1994) Exposure factors sourcebook. AIHC, Washington, DC. Binder, S.; Sokal, D.; Maughan, D. (1986) Estimating soil ingestion: the use of tracer elements in estimating the amount of soil ingested by young children. Arch. Environ. Health. 41(6):341-345. Behrman, L.E.; Vaughan, V.C.,.111. (1983) Textbook of Pediatrics. Philadelphia, PA: W.B. Saunders Company. Bruhn, C.M.; Pangborn, R.M. (1971) Reported incidence of pica among migrant families. J. of the Am. Diet. Assoc. 58:417-420 . . Calabrese, E.J.; Kostecki, P.T.; Gilbert, C.E. (1987) How much soil do children eat? An emerging consideration for environmental health risk assessment. In press (Comments in Toxicology). Calabrese, E.J.; Pastides, H.; Barnes, R.; Edwards, C.; Kostecki, P.T.; et al. (1989) How much soil do young children ingest: an epidemiologic study. In: Petroleum Contaminated Soils, Lewis Publishers, Chelsea, Ml. pp. 363-397. Calabrese, E.J.; Stanek, E.J.; Gilbert, C.E.; Barnes, R.M. (1990) Preliminary adult soil ingestion estimates; results of a pilot study. Regul. Toxicol. Pharmacol. 12:88-95. Calabrese, E.J.; Stanek, E.J.; Gilbert, C.E. (1991) Evidence of soil-pica behavior and quantification of soil ingested. Hum. Exp. Toxicol. 10:245-249. Calabrese, E.J.; Stanek, E.J. (1992) Distinguishing outdoor soil ingestion from indoor dust ingestion in a soil pica child. Regul. Toxicol. Pharmacol. 15:83-85. Calabrese, E.J.; Stanek, E.J. (1995) Resolving intertracer inconsistencies in soil ingestion estimation. Environ. Health Perspect. 103(5):454-456. Clausing, P.; Brunekreef, B.; Van Wijnen, J.H, (1987) A method for. estimating soil ingestion by children. Int. Arch. Occup. Environ. Health (W. Germany) 59(1 ):73-82. Danford, D.C. (1982) Pica and nutrition. Annual Review of Nutrition. 2:303-322. Davis, S.; Waller, P.; Buschbon, R.; Ballou, J.; White, P. (1990) Quantitative estimates of soil ingestion in normal children between the ages of 2 and 7 years: population based estimates using aluminum, silicon, and titanium as soil tracer elements. Arch .. Environ. Hlth. 45:112-122. Day, J.P.; Hart, M.; Robinson, M.S. (1975) Lead in urban street dust. Nature 253:343-.345. Duggan, M.J.; Williams, S . .(1977) Lead in dust in city streets. Sci. Total Environ. 7:91-97. . . Feldman, M.D. (1986) Pica: current perspectives. Psychosomatics (USA) 27(7):519-523. Forfar, J.O.; Arneil, G.C., eds. (1984) Textbook of Paediatrics. 3rd ed. London: Churchill

Livingstone. Hawley, (1985) Assessment of health risk exposure to contariina\ed soil. Risk Anal. 5.289-302. Illingworth, R.S. (1983) The normal child. New York: Churchill Livingstone. Kaplan, H.I.; Sadock, B.J. (1985) Comprehensive textbook of psychiatry/IV. Baltimore, MD: Williams and Wilkins. Kimbrough, R.; Falk, H.; P.; Fries, G. (1984) Health implications of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) contamination of residential soil. J. Toxicol. Environ. Health 14:47-93. Krablin, R. (1989) [Letterto Jonathan Z. Cannon concerning soil ingestion rates.] Denver, CO: Arco Coal Co.; October 13, 1989. Lepow, M.L.; Bruckman, L.; Robina, R.A.; Markowitz, S.; Gillette, M.; et al. (1974) Role of airborne lead in increased body burden of lead in Hartford children. Environ. Health Perspect. 6:99:..101. Lepow, M.L.; Bruckman, L.; Gillette, M.; Markowitz, S.; Robina, R.; et al. (1975) Investigations into sources of lead in the environment of urban children. Environ. Res. 10:415-426. !-ourie, R.S.; Layman, E.M.; Millican, F.K. (1963) Why children eat things that are not food. Children 10:143-146.
Roels, H.; Buchet, J.P.; l.auwerys, R.R. (1980) Exposure to lead by the oral and pulmonary route of children living in the vicinity of a primary lead smelter. Environ. Res. 22:81-94. Sayetta, R.B. (1986) Pica: An overview. American Family Physician 33(5):181-185.

Sedman, R.; Mahmood, R.S. (1994) Soil ingestion by children and adults reconsidered using the results of recent tracer studies. Air and Waste, 44:141-144. Sheppard, S.C._(1995) Parameter values to model the soil ingestion pathway. Environmental Monitoring and Assessment 34:27-44. Stanek, E.J.; Calabrese, E.J. (1995a) Daily estimates of soil ingestion in children. Environ. Health Perspect. 103(3):276-285. Stanek, E.J.; Calabrese, E.J. (1995b) Soil ingestion estimates for use in site evaluations based on the best tracer method. Human and Ecological Risk Assessment. 1 :133-156. Thompson, K.M.; Burmaster, D.E. (1991) Parametric distributions for soil ingestion by children. Risk Analysis. 11 :339-342. U.S. EPA. (1984) Risk analysis of TCDD contaminated soil. Washington, DC: U.S. Envirorimental Protection Agency, Office of Health and Environmental Assessment. EPA 600/8-84-031. Van Wijnen, J.H.; Clausing, P.; Brunekreff, B. (1990) Estimated soil ingestionby children. Environ. Res. 51 :147-162. Vermeer, D.E.; Frate, D.A. (1979) Geophagia in rural Mississippi: environmental and cultural contexts and nutritional implications. Am. J. Clin. Nutr. 32:2129.,2135. DOWNLOADABLE TABLES FOR CHAPTER 4 The following selected tables are available for download as Lotus 1-2-3 worksheets. Table 4-9. Distribution of Average (Mean) Daily Soil Ingestion Estimates Per Child for 64 Children (mg/day) [WK1, 3 kb] Table 4-10. Estimated Distribution of Individual Mean Daily Soil Ingestion Based on* Data for 64 Subjects Projected Over .365 Days [WK1, 1 kb] Volume I -General Factors Chapter 5 -Inhalation 5. INHALATION ROUTE 5.1. EXPOSURE EQUATION FOR INHALATION 5.2. INHALATION RATE 5.2.1. Background 5.2.2. Key Inhalation Rate Studies 5.2.3. Relevant Inhalation Rate Studies 5.2.4. Recommendations REFERENCES FOR CHAPTER 5 APPENDIX 5A Table 5-1. Calibration and Field Protocols for Self-Monitoring of Activities Grouped by Subject Panels Table 5-2. Subject Panel Inhalation Rates by Mean VR, Upper Percentiles, and Self-Estimated Breathing Rates Table 5-3. Distribution of Predicted IR by Location and Activity Levels for Elementary and High School Students Table 5-4. Average Hours Spent Per Day in a Given Location and Activity Level for Elementary (EL) and High School (HS) Students Table 5-5. Distribution Patterns of Daily Inhalation Rates for Elementary (EL) and High School (HS) Students Grouped by Activity Level Table 5-6. Summary of Average Inhalation Rates (m3/hr) by Age Group and Activity Levels for Laboratory Protocols Table 5-7. Summary of Average Inhalation Rates (m3/hr) by Age Group and Activity Levels in Field Protocols Table 5-8. Distributions of Individual and Group lnhalationNentilation Rate for Outdoor Workers Table 5-9. Individual Mean Inhalation Rate (m3/hr) by Self-Estimated Breathing Rate or Job Activity Category for .Outdoor Workers Table 5-10. Comparisons of Estimated Basal Metabolic Rates (BMR) with Average Food-Energy Intakes for Individuals Sampled in the 1977-78 NFCS

Table 5-11. Daily Inhalation Rates Calculated from Food-Energy Intakes Table 5-12. Daily Inhalation Rates Obtained from the Ratios of Total Energy Expenditure to Basal Metabolic Rate (BMR) Table 5-13. Daily Inhalation Rates Based on Time-Activity Survey Table 5-14. Inhalation Rates for Short-Term Exposures Table 5-15. Daily Inhalation Rates Estimated From Daily Activities Table 5-16. Summary of Human Inhalation Rates for Men, Women, and Children by Activity Level (m3/hour) Table 5-17. Activity Pattern Data Aggregated for Three Microenvironments by Activity Level for all Age Groups Exposure Factors Handbook August 1997 Table 5-18. Table 5-19. Table 5-20. Table 5-21. Table 5-22. Table 5-23. Table 5-24. Table 5-25. Table 5-26. Table 5-21. Table 5A-1. Table 5A-2. Table 5A-3. Table 5A-4. Table 5A-5. Table 5A-6. Volume I -General Factors Chapter 5 -Inhalation Summary of Daily Inhalation Rates Grouped by Age and Activity Level Distribution Pattern of Predicted VR and EVR (equivalent ventilation rate) for 20 Outdoor Workers Distribution Pattern of Inhalation Rate by Location and Activity Type for 20 Outdoor Workers Actual Inhalation Rates Measured at Four Ventilation Levels Confidence in Inhalation Rate Recommendations Summary of Recommended Values for Inhalation Summary of Inhalation Rate Studies Summary of Adult Inhalation Rates for Short-Term Exposure Studies Summary of Children's (18 years old or less) Inhalation Rates for Long-Term Exposure Studies Summary of Children's Inhalation Rates for Short-Term Exposure Studies Mean Minute Ventilation (VE, L/min).by Group and Activity for Laboratory Protocols Mean Minute Ventilation (VE, Umin) by Group Activity for Field Protocols Characteristics of Individual Subjects: Anthropometric Data, Job Categories, Calibration* Results Statistics of the Age/Gender Cohorts Used to Develop Regression Equations for Predicting Basal Metabolic Rates (BMR) Selected Ventilation Vall,les During Different Activity Levels Obtained FromVarious Literature Sources Estimated Minute Ventilation Associated with Activity Level for Average Male Adult Table 5A-7. Minute Ventilation Ranges by Age, Sex, and Activity Level Figure 5-1. Schematic of Dose and Exposure: Respiratory Route Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 5 -Inhalation 5. INHALATION ROUTE This chapter presents data and recommendations for inhalation rates that can be used to assess exposure to contaminants in air. The studies discussed in this chapter have been classified as key or relevant. Key studies are used as the basis for deriving recommendations and the relevant studies are included to provide additional background and perspective. The recommended inhalation rates are summarized in Se_ction 5.2.4 and cover adults, children, and outdoor workers/athletes. Inclusion of this chapter in the Exposure Factors Handbook does not imply that assessors will always need to select and use inhalation rates when-evaluating exposure to air contaminants. In fact, it is unnecessary to calculate inhaled dose when using response factors from Integrated Risk Information System (IRIS) (U.S. EPA, 1994). This is due to the fact that IRIS methodology accounts for inhalation rates in the development pf "dose-response" relationships. When using IRIS for inhalation risk assessments, response" relationships require only an average air concentration to evaluate health concerns:
For non-carcinogens, IRIS uses Reference Concentrations (RfC) which are expressed in concentration units. Hazard is evaluated by comparing the inspired air concentration to the RfC.
For carcinogens, IRIS uses unit risk values which are expressed in inverse concentration units. Risk is evaluated by multiplying the unit risk by the inspired air concentration. Detailed descriptions of the IRIS methodology for derivation of inhalation reference. concentrations can be found in two methods manuals produced by the Agency (U.S. EPA, 1992; 1994). . . IRIS employs a default inhalation rate of 20 m3/day. This is greater than the recommendated value in this chapter. When using IRIS, adjustments of dose-response relationships using inhalation rates other than the default, 20 m3/day, are not c*urrently recommended. There are instances where the inhalation rate data presented in this chapter may be used for estimating. average daily dose. For example, the inhalation average daily dose is often estimated in cases where a compative pathway analysis is desired or to determine a total dose by adding across pathways in cases where RfCs and unit risk factors are not available. Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 5 -Inhalation 5.1. EXPOSURE EQUATION FOR INHALATION For those cases where the average daily.dose (ADD) needs to be estimated, the general equation is: ADD= [[C x IR x ED] I [BW x AT]] (Eqn. 5-1) where: ADD = average daily dose (mg/kg-day); C = contaminant concentration in inhaled air (µg/m3); IR = inhalation rate (m3/day); ED = exposure duration (days); *sw = body weight (kg); and . AT = averaging time (days), for non-carcinogenic effects AT= ED, for carcinogenic or chronic effects AT= 70 years or 25,550 days (lifetime) . . The average daily dose is the dose rate averaged over a pathway-specific period of exposure expressed as a daily dose on a per-unit-body-weight basis. The ADD is used for exposure to chemicals with non-carcinogenic non-chronic effects. For compounds with carcinogenic or chronic effects, the lifetime average daily dose (LADD) is used. The LADD is the dose rate averaged over a lifetime. The contaminant concentration refers to the concentration of the contaminant in inhaled air. Exposure duration refers to the total time an individual is exposed to an air pollutant. 5.2. INHAl-ATION RATE 5.2.1. Background The* Agency defines exposure as the chemical concentration at the boundary of the body (U.S. EPA, 1992). In the case of inhalation, the situation is complicated by the fact that oxygen exchange with carbon dioxide takes place in the distal portion of the lung. The anatomy and physiology of the respiratory system diminishes the pollutant concentration in inspired air (potential dose) such that the amount of a pollutant that actually enters the body through the lung (internal dose) is less than that measured at the boundary of the body (Figure 5-1 ). When constructing risk assessments that concern the inhalation route of exposure, one must be aware if any adjustments have been employed in the estimation of the pollutant concentration to account for this reduction in potential dose. The respiratory system is comprised of three regions: nasopharyngeal, tracheobronchial, and pulmonary. The _nasopharyngeal region extends from the nose to the larynx. The tracheobronchial region forms the conducting airways between Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 5 -Inhalation nasopharynx and alveoli where gas exchange occurs. It consists of the trachea, bronchi, . and bronchioles. The pulmonary regions consists of the acinus which is the site where gas exchange occurs; it is comprised of respiratory bronchioles, alveolar ducts and sacs, and alveoli. A detailed discussion of pulmonary anatomy and physiology can be found in: Benjamin (1988) and U.S. EPA (1989 and 1994). Each region in the respiratory system can be involved with removing pollutants from inspired air. The nasopharyngeal region filters out large inhaled particles, moderates the femperature, and increases the humidity of the air. The surface of the tracheobronchial region is covered with .ciliated mucous secreting cells which forms a mucociliary escalator that moves particles from deep regions of the lung to the oral cavity where they may be -swallowed and then excreted. The branching pattern and physical dimensions of the these airways determine the pattern of deposition of airborne particles and absorption of gases by the respiratory tract. They decrease in diameter as they divide into a bifurcated branching network dilutes gases by axial diffusion of gases along the streamline of airways and radial diffusion of gases due to an increase in cross sectional area of the lungs. The velocity of the airstream .in this decreasing branching network creates a turbulent force such that airborne particles can be deposited along the walls of these airways by impaction, interception, sedimentation, or diffusion depending on their size. The pulmonary region contains macrophages which engulf particles and pathogens that enter this portion of the lung. Notwithstanding these removal mechanisms, both gaseous and particulate pollutants can deposit in various regions of the lung. Both*the physiology of the lung and the chemistry of the pollutant influences where the pollutant tends to deposit. Gaseous pollutants are evenly dispersed in the air stream. They come into contact with a large portion of the lung. Generally, their solubility and reactivity determines where they deposit in the lung. Water soluble and chemically reactive gases tend to deposit in the upper respiratory tract. Lipid soluble or non-reactive gases usually are not removed in the upper airways and tend to deposit in the distal portions of the lung. Gases can be absorbed into the blood stream or react with lung tissue. Gases can be removed from the lung by reaction with tissues or by expiration. The amount of gas retained in the lung or other parts of the body is mainly due to their solubility in blood. Chemically, particles are quite heterogenous. They range from aqueous soluble particles to solid insoluble particles. Their size, chemical composition, and the physical forces of breathing dictate where they tend to deposit in the lung. Large particles, those with a diameter of greater than 0.5 micrometers (um), not filtered out in the nasopharynx, tend to deposit in the upper respiratory tract at airway branching points due to impaction. The momentum of these particles in the air stream is such that they tend to collide with the Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 5 -Inhalation airway wall at branching points in the tracheobronchial region of the lung. Those particles not removed from the airstream by impaction will likely be deposited in small bronchi and bronchioles by sedimentation, a process where by particles settle out of the airstream due to the decrease in airstream velocity and the gravitational force on the particles. Small particles, less than 0.2 um, acquire a random motion due to bombardment by air molecules. This movement can cause particles to be deposited on the wall of an air way throughout the lungs. A special case exists for fibers. Fibers can deposit along. the wall of an airway by a process known as interception. This occurs when a fiber makes contact with an airway wall. The likelihood of interception increases as airway diminish in diameter. Fiber shape influences deposition too. Long, thin, straight fibers tend to deposit in the deep region of the lung compared to thick or curved fibers. The health risk associated with human exposure to airborne toxics is a function of concentration of air pollutants, chemical species, duration of exposure, and inhalation rate. The dose delivered to target organs (including the lungs), the biologically effective dose, is dependent on the poteritail dose, the applied dose and the internal dose (Figure 5-1) A detailed discussion of this concept can be found in Guidelines for Exposure Assessment (U.S. EPA, 1992). The estimation of applied dose for a given air pollutant is dependent on inhalation rate, commonly described as ventilation rate (VR) or breathing rate. VR is usually measured as minute volume, the volume in liters of air exhaled per minute(VE). VE is the product of the number of respiratory cycles in a minute and the volume of air respired during each respiratory cycle, the tidal volume( Vr)-When interested in calculating internal dose, assessors must consider the alveolar ventilation rate. This is the amount of air available for exchange with alveoli per unit time. It is equivalent to the tidal volume( Vr) minus the anatomic dead space of the lungs (the space containing air that does not come into contact with the alveoli). Alveolar ventilation is approximately 70 percent of total ventilation; tidal volume is approximately 500 milliliters (ml) and the amount of anatomic dead space in the lungs is approximately 150 ml, approximately 30% of the amount of air inhaled (Menzel and. Amdur, 1986). Breathing rates are affected by numerous individual characteristics, including age, gender, weight, health status, and levels of activity (running, walking, jogging, etc.). VRs are either measured directly using a spirometer and a collection system or indirectly from heart rate (HR) measurements. In many of the studies described in the following sections, HR measurements are usually correlated with VR in simple and multiple regression analysis.
Exposure Factors Handbook *August 1997 Volume I -General Factors Chapter 5 -Inhalation The available studies on inhalation rates are summarized in the following sections. Inhalation rates are reported for adults and children (including infants) performing various activities and outdoor workers/ athletes. The activity levels have been categorized as resting, sedentary, light, moderate, and heavy. In most studies, the sample population kept diaries to record their physical activities, locations, and breathing rates. Ventilation rates were either measured, self-estimated or predicted from equations derived using HR calibration relationships. 5.2.2. Key Inhalation Rate Studies Linn et al. (1992).-Documentation of Activity Patterns in "High*Risk" Groups Exposed
to Ozone in the Los Angeles Area -Linn efal. (1992) conducted a study that estimated the inhalation rates for "high-risk" subpopulation groups exposed to ozone (03) in their daily activities in the Los Angeles area. The population surveyed consisted of seven subject panels: Panel 7: 20 healthy outdoor workers (15 males, 5 females, ages 19-50 years); Panel 2: 17 healthy elementary school students ( 5 males, 12 females, ages 10-12 years); Panel 3: 19 healthy high school students (7 males, 12 females, ages 13-17 years); Panel 4: 49 asthmatic adults (clinically mild, moderate, and severe, 15 males, 34 females, ages 18-50 years); Panel 5: 24 asthmatic adults from 2 neighborhoods of contrasting 03 air quality ( 10 males, 14 females, ages 19-46 years); Panel 6: 13 young asthmatics (7 males, 6 females, ages 11-16 years); Panel 7: construction workers (7 males, ages 26-34 years). Initially, a calibration test was conducted, followed by a training session. Finally, a field study was conducted which involved subjects' collecting their own heart rate and diary data. During the calibration tests, VR and HR were measured simultaneously at each exercise level. From the* calibration data an equation was developed using linear regression analysis to predict VR from measured HR (Linn et al., 1992). In the field study, each subject (except construction workers) recorded in diaries: their daily activities, change in locations (indoors, outdoors, or in a vehicle), self-estimated breathing rates during each activity/location, and time spent at each activity/location. Healthy subjects recorded their HR once every 60 seconds, Asthmatic subjects recorded their diary information once every hour using a Heart Watch. Construction workers dictated their diary information to a technician accompanying them on the job. Subjective breathing rates were defined as slow (walking at their normal pace); medium (faster than normal walking); and fast (running or similarly strenuous exercise). Table 5-1 presents the calibration and field protocols for self-monitoring of activities for each subject panel. Table 5-2 presents the mean VR, the 99th percentile VR, and the mean VR at each subjective activity level (slow, medium, fast). The mean VR and 99th percentile VR were Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 5 -Inhalation derived from all HR recordings (that appeared to be valid) without considering the diary . data. Each of the three activity levels was determined from both the concurrent diary data and HR recordings by direct calculation or regression (Linn et al., 1992). The mean VR for healthy adults was 0.78 m3/hr while the mean VR for asthmatic adults was 1.02 m3/hr (Table 5-2). The preliminary data for construction workers indicated that during a 10-hr work shift, their mean VR (1.50 m3/hr) exceeded the VRs of all other subject panels (Table 5-2). Linn et al. ( 1992) reported that the diary data showed that mo_st individuals except construction workers spent most of their time (in a typical day) indoors at slow activity level. During slow activity, asthmatic subjects had higher VRs than healthy subjects, except construction workers (Table 5-2). Also, Linn et al. (1992) reported that in every panel, the predicted VR correlated significantly with the subjective estimates of activity levels. A limitation of this study is that calibration data may overestimate the predictive power of HR during actual field monitoring. The wide variety of exercis13s in everyday activities may re.suit in greater variation of the VR-HR relationship than calibrated. Another limitation of. this study is the small sample size of each subpopulation surveyed. An
advantage of this study is that diary data can provide rough estimates of ventilation patterns which are useful in exposure assessments. Another advantage is that inhalation rates were presented for various subpopulations (i.e., healthy outdoor adult workers, *healthy children, asthmatics, and construction workers). Spier et al .. (1992) -Activity Patterns in Elementary and High School Students Exposed To Oxidant Pollution -et al. (1992) investigated activity patterns of 17 elementary school students (10-12 years old) and 19 high school students (13-17 years old) in suburban Los Angeles from late September to October (oxidant pollution season). Calibration tests were conducted in supervised outdoor exercise sessions. The exercise sessions consisted of 5 minutes for each: rest, slow walking, jogging, and fast HR and VR were measured during the last 2 minutes of each exercise. Individual VR and HR relationships for each individual were determined by fitting a regression line to HR values and log VR values. Each subject recorded their daily activities, change in location, and breathing rates in diaries for 3 consecutive days. Self-estimated breathing rates were recorded as slow (slow walking), medium (walking faster than normal), and fast (running). HR was recorded during the 3 days once per minute by wearing a Heart -Watch. VR values for each self-estimated breathing rate and activity type were estimated from the HR recordings by employing the VR and HR equation obtained from the calibration tests. The data presented in Table 5-3 represent HR distribution patterns and corresporn;:ling pre.dieted VR for each age group during hours spent awake. At the same self-reported activity levels for both age groups, inhalation rates were higher for outdoor activities than for indoor activities. The total hours spent indoors by high school students Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 5 -Inhalation (21.2 hours) were higher than for elementary school students (19.6 hours). The converse was true for outdoor activities; 2.7 hours for high school students, and 4.4 hours for elementary school students (Table 5-4 ). Based on the data presented in Tables 5-3 and 5-4, the average activity-specific inhalation rates for elementary (10-12 years) and high school (13-17 years) students were calculated in Table 5-5. For elementary school students, the average daily inhalation rates (based on indoor and outdoor locations) are 15.8 m3/day for light activities, 4.62 m for moderate activities, and 0.98 m Jday for heavy activities. For high school students the daily inhalati.on rates for light, moderate, and heavy activities are estimated to be 16.4 m3/day, 3.1 m3/day, *and 0.54 m3/day, respectively (Table 5-5). A limitation of this study is the small sample The results may not be representative of all children in these age groups. limitation is that the accuracy of the self-estimated breathing rates reported by younger age groups is uncertain. This may affect the validity of the data set generated. An advantage of this study is that inhalation rates were determined for children and adolescents. These data are useful in estimating exposure for the younger population. Adams (1993}-Measurement of Breathing Rate and Volume in Routinely Performed Daily Activities -Adams (1993) conducted research to accomplish two main objectives: (1) identification of mean and ranges of inhalation rates for various age/gender cohorts and specific activities;. and (2) derivation of simple linear and multiple regression equations used to predict inhalation rates through other variables: heart rate (HR), breathing frequency (f 8), and oxygen consumption (V * )02 A total of 160 subjects participated.in the primary study. There were four age dependent groups: (1) .children 6 to 12.9 years old, (2) adolescents between 13 and 18.9 years old, (3) adults between 19 and 59:9 years old, and (4) seniors >60 years old (Adams, 1993). An additional 40 *children* from 6 to 12 yea.rs old and 12 young children from 3 to 5 years old were identified as subjects for pilot testing purposes in this age group (Adams, 1993). Resting protocols conducted in the laboratory for all age groups consisted of three phases (25 minutes each) of lying, sitting, and standing. They were categorized as resting and sedentary activities. Two*active protocols, moderate (walking) and heavy Uogging/ running) phases, were performed on a treadmill over a progressive continuum of intensities made up of 6 minute intervals, at 3 speeds, ranging from slow to moderately fast. All protocols involved measuring VR, HR, f8 (breathing frequency), and V02 (oxygen consumption). Measurements were taken in the last 5 minutes of each phase of the resting protocol, and the last 3 minutes of the 6 minute intervals at each speed designated in the active protocols. * ' Exposure Factors Handbook . August 1997 Volume 1-General Factors Chapter 5 -Inhalation In the field, all children completed spontaneous play protocols, while the older adolescent population (16-18 years) completed car driving and riding, car maintenance (males), and housework (females) protocols. All adult females (19-60 years) and most of the senior (60-77 years) females completed*housework, yardwork, and car driving and riding protocols. Adult and senior males completed car driving and riding, yardwork, and mowing protocols. HR, VR, and f8 were measured *during each protocol. Most protocols were conducted for 30 minutes. All the active field protocols were conducted twice.
Dur"ing all activities in either the laboratory or field protocols, IR for the children's group revealed no significant gender differences, but those for the adult groups
demonstrated gender differences. Therefore, IR data presented in Appendix Tables 5A-1 and 5A-2 were categorized as young children, children (no gender),and for adult female, and adult male by activity levels (resting, sedentary, light, moderate, and heavy). These categorized data from the Appendix tables are summarized as IR in m3/hr in Tables 5-6. and 5-7. The laboratory protocols are shown in Table 5-6. Table 5-7 presents the mean inhalation rates by group and activity levels (light, sedentary, and moderate) in field protocols. A comparison of the data shown in Tables 5-6 and 5-7 suggest that during light and sedentary activities in laboratory and field protocols, similar inhalation rates were obtained for adult females and adult Accurate predictions of IR across all population groups and activity types were obtained by including body surface area (BSA), HR, and f8 in multiple regression analysis (Adams, 1993). Adams (1993) calculated BSA from measured height and weight using the equation: BSA = Height(0*125l x Weight(0.425l x 71.84. (Eqn. 5-2) A limitation associated with this study is that the population does not represent the general U.S. population. Also, the classification of activity types (i.e., laboratory and field protocols) into activity levels may bias the inhalation rates obtained for various age/gender cohorts. The estimated rates were based on short-term data and may not reflect long-term patterns. An advantage of this study is that it provides inhalation data for all age groups. Linn et al. (1993) -Activity patterns in Ozone Exposed Construction Workers -Linn et al. ( 1993) estimated the inhalation rates of 19 construction workers who perform heavy outdoor labor before and during a typical work shift. The workers (laborers, iron workers, and carpenters) were employed at a site on a hospital campus in suburban Los Angeles. The construction site induded a new hospital building and a separate medical office complex. The study was conducted between mid-July and early November, 1991. During this period, ozone (03) levels were typically high. Initially, each subject was calibrated with a 25-minute exercise test that included walking, fast walking, jogging', lifting, and . Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 5 -Inhalation carrying. All calibration tests were conducted in the mornings. VR and HR were measured simultaneously during the test. The data were analyzed using least squares regression to derive an equation for predicting VR at a given HR. Following the calibration tests, each subject recorded the type of activities to be performed during their work shift (i.e., sitting/standing, walking, lifting/carrying, and "working at trade" -defined as tasks specific to the individual's job classification). Location, and self-estimated breathing rates ("slow" similar to slow walking, "medium" similar to fast walking, and "fast" similar to running) were also recorded in the diary. During work, an investigator recorded the diary information by the subjects. HR was recorded minute by minute* for each subject before work and during the entire work shift. Thus, VR ranges for each breathing rate and activity category were estimated from the HR recordings by employing the relationship between VR and HR obtained from the calibration tests. A total of 182 hours of HR recordings were obtained during the survey from the 19 volunteers; 144 hours reflected actual working time according to the diary records. The lowest actual working hours recorded was 6.6 hours and the highest recorded for a complete work shift was 11.6 hours (Linn et al., 1993). Summary statistics for predicted VR distributions for all subjects, and for job or site defined subgroups are presented in Table 5-8. The data reflect all recordings before and during work, and at break times. For all subjects, the mean IR was 1.68 m3/hr with a standard deviation of +/-0.72 (Table 5-8). Also, for most subjects, the 1st and 99th percentiles of HR were outside of the _calibration range . (calibration. ranges are presented in Appendix Table 5A-3). Therefore, corresponding IR per9entiles were extrapolated using the calibration data (Linn et al., 1993). The data presented in Table 5-9 represent distribution patterns of IR for each subject, total subjects, and job or site defined subgroups by self-estimated breathing rates (slow, medium, fast) or by type of job activity. All data include working and non-working hours. The mean inhalation rates for most individuals showed statistically significant increases with higher self-estimated breathing rates or with increasingly strenuous job* activity (Linn et al., 1993). Inhalation rates were higher in hospital site workers when compared with office site workers (Table 5-9). In spite of their higher predicted VR workers at the hospital site reported a higher percentage of slow breathing time (31 percent) than workers at the office site (20 percent), and a lower percentage of fast breathing time, 3 percent and 5 percent, respectively (Linn et al., 1993). Therefore,* individuals whose work was objectively heavier than average (from VR predictions) tended to describe their work as lighter than average (Linn et al., 1993). Linn et al. (1993) also concluded that during an 03 pollution episode, construction workers should experience similar microenvironmental 03 exposure concentrations as other healthy outdoor workers, but with approximately twice as high a VR. Therefore, the inhaled dose of 03 should be almost two times higher for typical heavy-Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 5 -Inhalation construction workers than for typical healthy adults performing less strenuous outdoor jobs. A limitation associated with this study is the small sample size. Another limitation of this study is that calibration data were not obtained at extreme conditions. Therefore, it was necessary to predict IR values that were outside the calibration range. This may introduce an unknown amount of uncertainty to the data set. Subjective self-estimated breathing rates may be another source of uncertainty in the inhalation rates estimated. An advantage is that this study provides empirical data useful in exposure assessments for
a subpopulation thought to be the most highly exposed common occupational group I (outdoor workers). Layton {1993) -*Metabolically Consistent Breathing Rates for Use in Dose Assessments -Layton (1993) presented a new method for estimating metabolically consistent inhalation rates for use in quantitative dose assessments of airborne radionuclides. Generally, the approach for estimating the breathing rate for a specified time frame was to calculate a time-weighted-average of ventilation rates associated with physical activities of varying durations (Layton, 1993). However, in this study, breathing rates were calculated based on oxygen consumption associated with energy expenditures for short (hours) and long (weeks and months) periods of time, using the following general equation to calculate energy-dependent inhalation rates: VE= ExHxVQ (Eqn. 5-3) where: VE = ventilation rate (Umin or m3/hr); E = energy expenditure rate; [kilojoules/minute (KJ/min) or megajoules/hour (MJ/hr)]; H = volume of oxygen [at standard temperature and pressure, dry air (STPD) consumed. in the production of 1 kilojoule (KJ) of energy expended (L/KJ or m3/MJ)]; and VQ = ventilatory equivalent (ratio of minute volume (Umin) to oxygen uptake (L/min)) unitless. Three alternative approaches were used to estimate daily chronic (long term) inhalation rates for different age/gender cohorts of .the U.S. population using this methodology. First Approach Inhalation rates were estimated by multiplying average daily food energy intakes for different age/gender cohorts, volume of oxygen (H), and ventilatory equivalent (VQ), as shown in the equation above. The average food energy intake data (Table 5-10) are based on approximately 30,000 individuals and were obtained from the USDA 1977-78. Nationwide Food Consumption Survey (USDA-NFCS). The food energy intakes were Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 5 -Inhalation adjusted upwards by a constant factor of 1.2 for all individuals 9 years and older (Layton, 1993). This factor compensated for a consistent bias in USDA-N FCS attributed to under reporting of the foods consumed or the methods used to ascertain dietary intakes. Layton (1993) used a weighted average oxygen uptake of 0.05 L OzfKJ which was determined from data reported in the 1977-78 USDA-NFCS and the second National Health and Nutrition Examination Survey (NHANES II). The survey sample for NHANES II was approximately 20,000 participants. The ventilatory equivalent (VQ) of 27 used was calculated as the geometric mean of VQ data that were obtained from several studies by -. Layton (1993). The inhalation rate estimation techniques are shown in footnote (a) of Table 5-11. Table 5-11 presents the daily inhalation rate for each age/gender cohort. The highest daily inhalation rates were reported for children between the ages of 6-8 years ( 10 m3/day), for males between 15-18 years (17 m3/day), and females between 9-11 years (13 m3/day). Estimated average lifetime inhalation rates for males and females are 14 m3/day and_ 1 O m3/day, respectively (Table 5-11 ). Inhalation rates were also calculated for active a'nd inactive periods for the various age/gender cohorts. _ The inhalation rate for inactive periods was estimated by multiplying the basal metabolic rate (BMR) times the oxygen uptake (H) times the VQ. BMR was defined as "the minimum amount of energy required to support basic cellular respiration while at rest and not actively digesting food"(Layton, 1993). The inhalation rate for active periods was calculated by multiplying the inactive inhalation rate by the ratio of the rate of energy expenditure during active hours to the estimated BMR. This ratio is presented as F in Table 5-11. These data for active and inactive inhalation rates are also presented in Table 5-11. For children, inactive and active inhalation rates ranged between 2.35 and 5.95 m3/day and 6.35 to -13.09 m3/day, respectively. For adult males (19-64 years old), the average Inactive and active inhalation rates were approximately 1 O and 19 m3/day, respectively. Also, the average inactive and active inhalation rates for adult females (19-64 years old) were approximately 8 and 12 m3/day, respectively. Second Approach Inhalation rates were calculated by multiplying the BMR of the population cohorts times A (ratio of total daily energy expenditure to daily BMR) times H times VQ. The BMR data obtained from literature were statistically analyzed and regression equations were developed to predict BMR from body weights of various age/gender cohorts (Layton, 1993). The statistical data used to develop the regression equations are presented in Appendix Table 5A-4. The data obtained from the second approach are presented in Table 5-12. Inhalation rates for children (6 months -10 years) ranged from 7 .3-9.3 m3/day for male and 5.6 to 8.6 m3/day for female children and ( 10-18 years) was 15 m3/day for Exposure Factors Handboofc August 1997 Volume I -General Factors Chapter 5 -Inhalation males and 12 m3/dayforfemales. Adult females (18 years and older) ranged from 9.9-11 m3/day and adult males (18 years and older) ranged from 13-17 m3/day. These rates are
similar to the daily inhalation rates obtained using the first approach. Also, the inactive inhalation rates obtained from the first approach are lower than the inhalation rates obtained using the second approach. This may be attributed to the BMR multiplier employed in the equation of the second approach to calculate inhalation rates. Third Approach Inhalation rates were calculated by multiplying estimated energy associated with different levels of physical activity engaged in over the course of an average day by VQ and H for each age/gender cohort. The energy expenditure associated with each level of activity was estimated by multiplying BMRs of each activity level by the metabolic equivalent (MET) and by the time spent per day performing each activity for each age/gender population. The time-activity data used in this approach were obtained from a survey conducted by Sallis et al. (1985) (Layton, 1993). In that survey, the . physical-activity categories and associated MET values used were sleep, MET=1; activity, MET=1.5; moderate activity, MET=4; hard activity, MET=6; and very hard activity, MET=10. The physical activities were based on recall by the te.st subject (Layton, 1993). The survey sample was 2,126 individuals (1, 120 women and 1,006 men) ages 20-7 4 years that were randomly selected from four communities in California. The BMRs were estimated using the metabolic equations presented in Appendix Table 5A-4. The body weights were obtained from a study conducted by Najjar and Rowland (1987) which randomly sampled individuals from the U.S. population (Layton, 1993). Table 5-13 presents the inhalation rates (VE) in m3/day and m3/hr for adult males and females aged 20-7 4 years at five physical activity levels. The total daily inhalation rates ranged from 13-17 m3/day for adult males and 11-15 m3/day for adult females.
The rates for adult females were higher when compared with the other two approaches. Layton (1993) reported that the estimated inhalation rates obtained from the third approach were particularly sensitive to the MET value that represented the energy expenditures for light activities. Layton (1993) stated further that in the original activity survey (i.e., conducted by Sallis et al., 1985), time spent performing light activities was not presented. Therefore, the time spent at light activities was estimated by subtracting the total time spent at sleep, moderate, heavy, and very heavy activities from 24 hours (Layton, 1993). The range of inhalation rates for adult females were 9.6 to 11 * ' m3/day, 9.9 to 11 m3/day, and 11 to 15 m3/day, for the first, second, and third. approach, respectively. The inhalation rates for adult males ranged from 13 to 16 m3/day for the first approach, and 13 to 17 m3/day for the second and third approaches. Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 5 -Inhalation Inhalation rates were also obtained for short-term exposures for various age/gender cohorts and five energy-expenditure categories (rest, sedentary, light, moderate, and heavy). BMRs were multiplied by the product of MET, H, and VQ. The data obtained for short term exposures are presented in Table 5-14. The major strengths of the Layton (1993) study are that it obtains similar results using three different approaches to estimate inhalation rates in different age groups and that the populations are large, consisting of men, women, and children. Explanations for differences in results due to metabolic measurements, reported diet, or activity patterns are supported by observations reported by other investigators in other studies .. Major limitations of this study are that activity pattern levels estimated in this study are somewhat subjective, the explanation that activity pattern differences is responsible for the lower level obtained with the* metabolic approach (25 percent) compared to the activity pattern approach is not well supported by the data, and different populations were used in each approach which may introduce error. 5.2.3. Relevant Inhalation Rate Studies International Commission on Radiological Protection {ICRP) {1981) -Report of the Task Group on Reference Man -The International Commission of Radiological Protection (ICRP) estimated daily inhalation rates for reference adult males, adult females, children (10 years old), infant (1 year old), and newborn babies by using a time-activity-ventilation approach. This approach for estimating inhalation rate over a specified period of time was based on calculating a time weighted average of inhalation rates associated with physical activities of varying durations. ICRP (1981) compiled reference values (Appendix Table 5A-5) of minute volume/inhalation rates from various literature* sources. ICRP (1981) *assumed that the daily activities of a reference man and woman, and child (10 yrs) consisted of 8 hours of rest and 16 hours of light activities. It was also assumed that 16 hours were divided evenly between occupational and nonoccupational activities. It was assumed that a day consisted of 14 hours resting and 10 hours light activity for an infant (1 yr). A newborn's daily activities consisted of 23 hours resting and 1 hour light activity. Table 5-15 presents the daily inhalation rates obtained for all ages/genders. The estimated inhalation rates were 22.8 m3/day for adult males, 21.1 m3/day for adult females, 14.8 m3/day for children (age 10 years), 3.76 m3/day for infants (age 1 year), and 0.78 m3/day for newborns. A limitation associated with this study is that the validity and accuracy of the inhalation rates data used in the compilation were not specified. This may introduce some degree of uncertainty in the results obtafned. Also, the approach used involved assuming hours spent by various age/gender cohorts in specific activities. These assumptions may over/under-estimate the inhalation rates obtained. Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 5 -Inhalation U.S. EPA (7985) -Development of Statistica(Distributions or Ranges of Standard Factors Used in Exposure Assessments -Due to a paucity of information in the literature regarding equations used to develop statistical distributions of minute ventilation/ventilation rate at all activity levels for male and female children and adults, the U.S. EPA (1985) compiled measured values of minute ventilation for various age/gender cohorts from early studies. In more recent investigations, minute ventilations have been measured more as background information than as research objective itself and the available studies have been for specific subpopulations such as obese, asthmatics, or marathon runners. The data compiled by the U.S. EPA (1985) for each age/gender cohorts were obtained at various activity levels. These levels were categorized as light, moderate, or heavy according to the criteria developed by the EPA Office of Environmental Criteria and Assessment for the Ozone Criteria Document. These criteria were developed for a reference male adult with a body weight of 70 kg (U.S. EPA, 1985). The minute ventilation rates for adult males based on these activity level categories are detailed in Appendix Table 5A-6. Table 5-16 presents a summary of inhalation rates by age, gender, and activity level (detailed data are presented in Appendix Table 5A-7). A description of activities included in each activity level is also presented in Table 5-16. Table 5-16 indicates that at rest, the average adult inhalation rate is 0.5 m3/hr. The mean inhalation rate for children at rest,
ages 6 and 10 years, is 0.4 m3/hr. Table 5-17 presents activity pattern data aggregated for three microenvironments by activity level for all age groups. The total average hours spent indoors was 20.4, outdoors was 1. 77, and in transportation vehicle was 1. 77. Based on the data presented in Tables 5-16 and 5-17, a daily inhalation rate was calculated for adults and children by using a time-activity-ventilation approach. These data are presented in Table 5-18._ The calculated average daily inhalation rate is 16 m3/day for adults. The average daily inhalation rate for children (6 and 10 yrs) is 18.9 m3/day ([16.74 '+ 21.02]/2). A limitation associated with this study is that many of the values used in the data -compilation were from early studies. The accuracy and/or validity of the values used and data collection method were not presented in U.S. EPA (1985). This introduces uncertainty in the results obtained. An advantage of this study is that the data are actual measurement data for a large number of subjects and the data are presented for both adults and children. Shamoo et al. (1990} -Improved Quantitation of Air Pollution Dose Rates by Improved Estimation of Ventilation Rate-Shamoo et al. (1990) conducted this study to develop and validate new methods to accurately estimate ventilation rates for typical individuals during their normal activities. Two practical approaches were tested for estimating ventilation rates indirectly: (1) volunteers were trained to estimate their own VR Exposure Factors Handbook August 1997 Volume I -General Factors . Chapter 5 -Inhalation at various controlled levels of exercise; and (2) individual VR and HR relationships were determined in another set of volunteers during supervised exercise sessions (Shamoo et al., 1990). In the first approach, the training session involved 9 volunteers (3 females and 6 males) from 21 to 37 years old. Initially the subjects were trained on a treadmill with regularly increasing speeds. VR measurements were recorded during the last minute of the 3-minute interval at each speed. VR was reported to the subjects as low (1.4 m3/hr), medium (1.5-2.3 m3/hr), heavy (2.4-3.8 m3/hr), and very heavy (3.8 m3/hr or higher) (Shamoo et al., 1990). Following the initial test, treadmill training sessions were conducted on a different day in which 7 different speeds were presented, each for 3 minutes in arbitrary order. VR was measured and the subjects were given feedback with the four ventilation ranges provided previously. After resting, a treadmill testing session was conducted in which seven speeds were presented in different arbitrary order from the training session. VR was measured and each subject estimated their own ventilation level at each speed. The correct level was then revealed to each subject after his/her own estimate. Subsequently, two 3-hour outdoor supervised exercise sessions were conducted in the summer on two consecutive days. Each hour consisted of 15 minutes each of rest, slow walking, jogging, and fast walking. The subjects' ventilation level and VR were recorded; however, no feedback was given to .the subjects. Electrocardiograms were recorded via direct connection or telemetry and HR was measured concurrently with ventilation measurement for all . treadmill sessions. The second approach consisted of two protocol phases (indoor/outdoor exercise sessions and field testing). Twenty outdoor adult workers between 19-50 years old were recruited. Indoor and outdoor supervised exercises similar to the protocols in the first approach were conducted; however, there were no feedbacks. Also, in this approach, electrocardiograms were recorded and HR was measured concurrently with VR. During the field testing phase, subjects were trained to record their activities during three different 24-hour periods during one week. These periods included their most active working and non-working days. HR was measured quasi-continuously during the 24-hour periods that activities were recorded. The subjects recorded in a diary all changes in physical activity, location, and exercise levels during waking hours. Self-estimated activities in supervised exercises and field studies were categorized as slow (resting, slow walking or equivalent), medium (fast walking or equivalent), and fast Uogging or equivalent). Inhalation rates were not presented in this study. In the first approach, about 68 percent of all self-estimates were correct for the 9 subjects sampled (Shamoo et al., 1990). Inaccurate self-estimates occurred in the younger male population who were highly physically fit and were competitive aerobic trainers. This subset of sample population tende'd to underestimate their own physical activity levels at higher VR ranges. Shamoo Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 5 -Inhalation et al. ( 1990) attributed this* to a "macho effect." In the second approach, a regression analysis was conducted that related the logarithm of VR to HR. The logarithm of VR correlated better with HR than VR itself (Shamoo et al., 1990). A limitation associated with this study is that the *population sampled is not representative of the general U.S. population. Also, ventilation rates were not presented. Training individuals to estimate their VR may contribute to uncertainty in the results because the estimates are subjective. Another limitation is that calibration data were not obtained at extreme conditions; therefore, the VR/HR relationship obtained may be biased. An additional limitation is that training subjects may be too labor-intensive for widespread use in exposure assessment ,studies. An advantage of this study is that HR recordings are useful in predicting ventilation rates which in turn are useful in estimating exposure. Shamoo et al. (7997) -Activity Patterns in a Panel of Outdoor Workers Exposed to Oxidant Pollution -Shamoo et al. (1991) investigated summer activity patterns in 20 adult volunteers with potentially high exposure to ambient oxidant pollution. The selected volunteer subjects were 15 men and 5 women ages 19-50 years from the Los Angeles area. All volunteers worked outdoors at least 10 hours per week. The experimental approach involved two stages: (1) indirect objective estimation* of VR from HR measurements; and (2) self estimation of inhalation/ventilation r13tes recorded by subjects in diaries during their normal activities. The approach consisted of calibrating the relationship between VR and HR for each test subject in controlled exercise; monitoring by subjects of their own normal activities with diaries and electronic HR recorders; and then relating VR with the activities described in the diaries (Shamoo et al., 1991 ). Calibration tests were conducted for indoor and outdoor supervised exercises to determine individual relationships between VR and HR. Indoors: each subject was tested on a treadrnill at rest and at increasing speeds. HR and VR were measured at the third minute at each 3-minute interval speed. In addition, subjects were tested while walking a 90-meter course in a corridor at 3 self-selected speeds (normal, slower than normal, and faster than normal) for 3 minutes. Two outdoor testing sessions (one hour each) were conducted for each subject, 7 days apart. Subjects exercised on a 260-meter asphalt course. A session involved 15 minutes each of rest, slow walking, jogging, and fast walking during the first hour. The sequence was also repeated during the second hour. HR and VR measurements were recorded starting at the 8th minute of each 15-minute segment. Following the calibration tests, a field study was conducted in which subject's self-monitored their activities by filling out activity diary booklets, self-estimated their breathing rates, and their HR. Breathing . rates were defined as sleep, slow (slow or normal walking); medium (fast walking); and fast * (running) (Shamoo et al., 1991 ). Changes in location, activity, or breathing rates during Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 5 -Inhalation three 24-hr periods within a week were recorded. These periods included their most active working and non-working days. Each subject wore Heart Watches which recorded their HR once per minute during the field study. Ventilation rates were estimated for the following categories: sleep, slow, medium, and fast. Calibration data were fit to the equation log (VR) =intercept+ (slope x HR), each individual's intercept and slope were determined separately to provide a specific equation that predicts each subject's VR from measured HR (Shamoo et al., 1991). The average measured VRs were 0.48, 0.9, 1.68, and 4.02 m3/hr for rest, slow walking or normal walking, fast walking and jogging, respectively (Shamoo et al., 1991 ). Collectively, the diary recordings showed that sleep occupied about 33 percent of the subject's time; slow activity 59 percent; medium activity 7 percent; and fast activity 1 percent. The diary data covered an average of 69 hours per subject (Shamoo et al., 1991 ). Table 5-19 presents. the distribution pattern of predicted ventilation rates and equivalent ventilation rates (EVR)
obtained at the four activity levels. EVR was defined as the VR per square meter of body surface area, and also as a percentage of the subjects average VR over the entire field monitoring period (Shamoo et al., 1991 ). The overall mean predicted VR was 0.42 m3/hr for sleep; 0,71 m3/hr for slow activity; 0.84 m3/hr for medium activity; and 2.63 m3/hr for fast activity. The mean predicted VR and standard deviation, and the percentage of time spent in each combination of VR, activity type (essential and non-essential), and location (indoor and outdoor) are presented in Table 5-20. Essential activities include income-related work, household chores, child care, study and other school activities, personal care and destination-oriented travel. *Non-essential activities include sports and active leisure, passive leisure, some travel, and social or civic activities (Shamoo et al., 1991 ). Table 5-20 shows that inhalation rates were higher outdoors than indoors at slow, medium, and fast activity levels .. Also, inhalation rates were higher for outdoor non-essential activities than for indoor non-essential activity levels at slow, medium, and fast self-reported breathing rates (Table* 5-20). An advantage of this study is that subjective activity diary data can provide exposure modelers with useful rough estimates of VR for groups of generally healthy people. A limitation of this study is that the results obtained show high within-person and person variability in VR at each diary-recorded level, indicating that VR estimates from diary reports could potentially be substantially misleading in individual cases. Another limitation of this study is that elevated HR data of slow activity at the second hour of the exercise session reflect persistent effects of exercise and/or heat stress. Therefore,
predictions of VR from the VRIHR relationship may be biased. Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 5 -Inhalation Shamoo et al. (1992) -Effectiveness of Training Subjects to Estimate Their Level of Ventilation -Shamoo et al. (1992) conducted a study where nine non-sedentary subjects in good health were trained on a treadmill to estimate their own ventilation rates at four activity levels: low, medium, heavy, and very heavy. The purpose of the study was to train the subjects self-estimation of ventilation in the field and assess the effectiveness of the training (Shamoo et al., 1992). The subjects included 3 females and 6 males between 21 to 37 years of age. The tests were conducted in four stages. First, an initial treadmill pretest was indoors at various speeds until the four ventilation levels were experienced by each subject; VR was measured and feedback was given to the subjects. Second, two treadmill training sessions which involved seven 3-minute segments of varying speeds based on initial tests were conducted; VR was measured and feedback was given to the subjects. Another similar session was conducted; however, the subjects estimated their own ventilation level during the last 20 seconds of each segment and VR was measured during the last minute of each segment. Immediate feedback was given to the subject's estimate; and the third and fourth stages involved 2 outdoor sessions of 3 hours each. Each hour comprised 15 minutes each of rest, slow walking, jogging, and fast walking. The subjects estimated their own ventilation level at the middle of each segment. The subject's estimate was verified by a respirometer which measured VR in the middle of each 15-minute activity. No feedback was given to the subject. The overall percent correct score obtained for all ventilation levels was 68 percent (Shamoo et al., 1992) . .Therefore, Shamoo et al. (1992) concluded that this training protocol was effective in training subjects to correctly estimate their minute ventilation levels. For this handbook, inhalation rates were analyzed from the raw data provided by Shamoo et al. (1992). Table 5-21 presents the mean inhalation rates obtained from this analysis at four ventilation levels in two microenvironments (i.e., indoors and outdoors) for all subjects. The mean inhalation rates for all subjects were 0.93, 1.92, 3.01, 4.80 m3/hr for low, medium, heavy, and very heavy activities, respectively. The population sample size used in this study was small and was not selected to represent the general U.S. population. The training approach employed may not be cost effective because it was labor intensive; therefore, this approach may not be viable in field studies especi!=IllY for field studies within large sample sizes. AIHC (1994) -The Exposure Factors Sourcebook -AIHC (1994) recommends an average adult inhalation rate of 18 m3/day and pr.esents values for children of various ages. These recommendations were derived from data presented in U.S. EPA (1989). The newer study by Layton (1993) was not considered. In addition, the Sourcebook presents probability distributions derived* by Brorby and Finley (1993). For each distribution, the @Risk formula is provided for direct use in the @Risk simulation software (Palisade, 1992). The organization of this document makes it very convenient to use in Exposure Fa.ctors Handbook August 1997 Volume I -General Factors Chapter 5 -Inhalation . support of Monte Carlo analysis. The reviews of the supporting studies are very brief with little of their strengths and weaknesses. The Sourcebook has. been classified as a relevant rather than key study because it is not the primary source for the data used to make recommendations in this document. The Sourcebook is very similar to this document in the sense that it summarizes exposure factor data and recommends values. As such, it is clearly relevant as an alternative information source on inhalation rates as well as other. exposure factors. 5;2.4. Recommendations In the Ozone Criteria Document prepared by the U.S. EPA Office of Environmental Criteria and Assessment, the EPA identified the collapsed range of activities and its corresponding VR as follows: light exercise (VE < 23 Umin or 1.4 m3/hr); moderate/ medium exercise (VE= 24-43 Umin or 1.4-2.6 m3/hr); heavy exercise (VE= 43-63 Umin or 2.6-3.8 m3/hr); and very heavy exercise (VE>. 64 Umin or 3.8 m3/hr), (Adams, 1993). Recent peer reviewed scientific papers and an EPA report comprise the studies that were evaluated in this Chapter. These studies were conducted in the United States among both men and women of different age groups. All are widely available. The confidence ratings in the inhalation rate 'recommendations are shown in Table 5-22 . . Each study focused.on ventilation rates and factors that may affect them. Studies were conducted among randomly selected volunteers. Efforts were made to .include men, women, different age groups, and different kinds of activities. Measurement methods are indirect, but reproducible. Methods are well described (except for questionnaires) and experimental error is well documented. There is general agreement with these estimates, among researchers. The recommended inhalation rates for adults, children, and outdoor workers/athletes are based on the key studies described in this chapter (Table 5-23)., Different survey designs and populations were utilized in the studies described in this Chapter. A summary of these designs, data generated, and their limitations/advantages are presented in Table 5-24. Excluding the study by Layton (1993), the population surveyed in all of the key studies described in this report were limited. to the Los Angeles area. This regional population may not represent the general U.S. population and may result in biases. However, based on other aspects of the study design, these studies were selected as the basis for recommended inhalation rates. . . The selection of inhalation rates to be used for exposure assessments depends on the age of the exposed population and the specific activity levels of this population during various exposure scenarios. The recommended values for adults, children (including Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 5 -Inhalation infants), and outdoor workers/athletes for use in various exposure scenarios are discussed below. These rates were calculated by averaging the inhalation rates for each activity level from the various key studies (see Table 5-25). Adults (19-65+ yrs) -Adults in this recommendation include young to middle age
adults (19-64 yrs), and older adults (65+ yrs). The daily average inhalation rates for long term exposure for adults are: 11.3 m3/day for women and 15.2 m3/day for men. These values are averages of the inhalation rates provided for males and females in each of the three approaches of Layton (1993) (Tables 5-11 through 5-14 ). An upper percentile is not recommended. Additional research and analysis of activity pattern data and dietary data *in the future is necessary to attempt to calculate upper percentiles . . The recommended value for the general population average inhalation rate, 11.3 m3/day for women and 15.2 m3/day for men, is different than the 20 m lday which has commonly been assumed in past EPA risk assessments. 'In addition, recommendations are presented for various ages and special populations (athletes, outdoor workers) which also differ from 20 m3/day. Assessors are encouraged to use values which most accurately reflect the exposed population. For exposure *scenarios where the distribution of activity patterns is known, the following results, calculated from the studies referenced are shown in Table 5-25. Based on these key studies, the following recommendations are made: for short term exposures in which distribution of activity patterns are specified, the recommended average rates are 0.4 3/hr during rest; 0.5 m3/hr for sedentary activities; 1.0 m 7hr for light activities; 1.6 m3/hr for moderate activities; and 3.2 m3/hr for heavy activities. Children {18 yrs old or less including infants) -* For the purpose of this recommendation, children are defined as males and females between the ages of 1-18 years old, while infants are individuals less than 1 year old. The inhalation rates for children are presented below according to different exposure scenarios.* The daily inhalation rates for long-term dose assessments, are based on the first approach of Layton (1993) (Table 5-11) and are summarized in Table 5-26. Based on the key study results (i.e., Layton, 1993), the recommended daily inhalation . rate for infants (children less than 1 yr), during long-term dose assessments is 4.5 m3/day. For children 1-2 years old, 3-5 years old, and 6-8 years old, the recommended daily inhalation rates are 6.8 m3/day, 8.3 m3/day, and 10 m3/day, respectively. Recommended values for children aged 9-11 years are 14 m3/day for males and 13 m3/day for females. For children aged 12-14 years and 15-18 years, the recommended values are shown in Table 5-23. Exposure Factors Handbook August 1997 I I Volume I -General Factors Chapter 5 -Inhalation For short-term exposures for children aged 18 years and under, in which activity patterns are known, the data are summarized in Table 5-27. For short term exposures, the recommended average hourly inhalation rates are based on these key studies. They are averaged over each activity held as follows: 0.3 m3/hr during rest; 0.4 m3/hr for sedentary activities; 1.0 m3/hr for light activities; 1.2 m3/hr for moderate activities; and 1.9 m3/hr for heavy activities. The recommended short-term exposure data also include infants (less than 1 yr). These values represent averages of the activity level data from key studies (Table 5-27). Outdoor Worker -Inhalation rate data for outdoor workers/athlete are limited. However, based on the key studies (Linn et al., 1992 and 1993), the recommended average hourly inhalation rate for outdoor workers is 1.3 m3/hr and the upper-percentile rate is 3.3 m3/hr (see Tables 5-5 and 5-8). This is calculated as the weighted mean of the 99th percentile values reported for the individuals on Panels 1 and 7 in Tables 5-5 and the 19 subjects in Table 5-8. The recommended average *inhalation rates for outdoor workers based on the activity levels categorized as slow (light activities), medium (moderate activities), and fast (heavy activities) are 1.1 m3/hr, 1.5 m3/hr, and 2.5 m3/hr, respectively. These values are based on the data from Linn et al. (1992 and 1993) and are the weighted mean of the values for the individuals on Panels 1 and 7 in Table 5-5 and the 19 outdoor workers in Table 5-9. Inhalation rates may be higher among outdoor workers/athletes because levels of activity outdoors may be higher. Therefore, this subpopulation group .may be more susceptible to air pollutants and are considered a subgroup (Shambo et al., 1991; Linn et al., 1992). \_* Exposure Factors Handbook August 1997 Table 5-1. Calibration and Field Protocols for Self-Monitoring of Activities Grouped by Subiect Panels Panel Calibration Protocol Field Protocol Panel 1 -Healthy Outdoor Workers -Laboratory treadmill exercise tests, indoor 3 days in 1 typical summer week (included 15 female, 5 male, age 19-50 hallway walking tests at different self-most active workday and most active day off); chosen speeds, 2 outdoor tests consisted HR recordings.and activity diary during of 1-hour cycles each of rest, walking, and waking hours. jogging. Panel 2 -Healthy Elementary School Outdoor exercises each consisted of 20 Saturday, Sunday and Monday (school day) in Students -5 male, 12 female, age minute rest, slow walking, jogging and fast early autumn; HR recordings and activity diary 10-12 walking during waking hours and during sleep. Panel 3 -Healthy High School Outdoor exercises each consisted of 20 Same as Panel 2, however, no HR recordings Students -7 male, 12 female, age minute rest, slow walking, jogging and fast during sleep for most subjects. 13-17 walking Panel 4 -Adult Asthmatics, clinically Treadmill and hallway exercise tests 1 typical summer week, 1 typical winter week; mild, moderate, and severe -15 hourly activity/health diary during waking male, 34 female, age 18-50 hours; lung function tests 3 limes daily; HR recordings during waking hours on at least 3 days (including most active work day and day off). Panel 5 -Adult Asthmatics from 2 Treadmill and hallway exercise tests Similar to Panel 4, personal N02 and acid neighborhoods of contrasting 03 air exposure monitoring included. (Panels 4 and quality -1 O male, 14 female, age 19-5 were studied in different years, and had 10 46 subjects in common). Panel 6 -Young Asthmatics -7 male, Laboratory exercise tests on bicycles and Similar to Panel 4, summer monitoring for 2 6 female, age 11-16 treadmills successive weeks, including 2 controlled exposure studies with few or no observable respiratory effects. Panel 7 -Construction Workers -7 Performed similar exercises as Panel 2 HR recordings and diary information during 1 male, age 26-34 and 3, and also performed job-related tests includina liftina and carrvina a 9-kq oioe. typical summer work day. Source: Linn et al. 1992 Table 5-2. Subject Panel Inhalation Rates bv Mean VR, Upper Percentiles, and Self-Estimated Breathing Rates Inhalation Rates (m3/hrl Panel N* Mean VR 99th Percentile Mean VR at Activity Levels tm3/hr\ VR im3/hr\b Slow Medium0 Fast° Healthy 1 -Adults 20 0.78 2.46 0.72 1.02 3.06 2 -Elementary School Students 17 0.90 1.98. 0.84 0.96 1.14 3 -High School Students 19 0.84 2.22 0.78 1.14 1.62 7. -Construction Workers0 7 1.50 4.26 1.26 1.50 1.68 Asthmatics 4-Adults 49 1.02 1.92 1.02 1.68 2.46 5-Adultsd 24 1.20 2.40 1.20 2.04 4.02 6 -Elementary and High School 13 1.20 2.40 1.20 1.20 1.50 Students a Number of individuals in each survey panel. b Some subjects did riot report medium and/or fast activity. Group means were calculated from individual means (i.e., give equal weight to each individual who recorded any time at the indicated activity level). c Construction workers recorded only on 1 day, mostly during work, while others recorded on 1 work or school day and 1 day off. d Excluding subjects also in Panel 4. Source: Linn et al. 1992.

Table 5-3. Distribution of Predicted IR bv Location and Activitv Levels for Elementarv and Hiqh School Students Inhalation Rates (m3/hr) Age % Recorded Percentile Rankings" (yrs) Student Location Activity Level Time' Mean+ SD 1st 50th 99.9th 10-12 EL' Indoors slow 49.6 0.84 +/- 0.36 0.18 0.78 2.34 (nd=17) medium 23.6 0.96 +/- 0.42 0.24 0.84 2.58 fast 2.4 1.02 +/- 0.60 0.24 0.84 3.42 Outdoors slow 8.9 0.96 +/- 0.54 0.36 0.78 4.32 medium 11.2 1.08 +/- 0.48 0.24 0.96 3.36 fast 4.3 1.14+/- 0.60 0.48 0.96 3.60 13-17 HS' Indoors slow 70.7 0.78 +/- 0.36 0.30 0.72 3.24 (nd=19) medium 10.9 0.96 +/- 0.42 0.42 0.84 4.02 fast 1.4 1.26 +/- 0.66 0.54 1.08 6.84' Outdoors slow 8.2 0.96 +/- 0.48 0.42 . 0.90 5.28 medium 7.4 1.26 +/- 0.78 0.48 1.08 5.70 fast 1.4 1.44 + 1.08 0.48 1.02 5.94 . Recorded time averaged about 23 hr per elementary school student and 33 hr. per high school student, over 72-hr. periods . b Geometric means closely approximated 50th percentiles; geometric standard deviations were 1.2-1.3 for HR, 1.5-1.8 for VR. ' EL = elementary school student; HS = high school student. d N = number of students that participated in survey. e Highest single value. Source: Soier et al. 1992. Table 5-4. Average Hours Spent Per Day in a Given Location and Activity Level for Elementary (EL) and High School (HS) Students Activity Level Student Total Time Spent IELa n'=17* HSb N'=19l Location Slow Medium Fast lhrs/davl EL Indoor 16.3 2.9 0.4 19.6 EL Outdoor 2.2 1.7 0.5 4.4 HS Indoor 19.5 1.5 0.2 21.2 HS Outdoor 1.2 1.3 0.2 2.7 a Elementary school (EL) students were between 10-12 years old. b High school (HS) students were between 13-17 years old. c N corresponds to number of school students. Source: Soier et al., 1992. Table 5-5. Distribution Patterns of Daily Inhalation Rates for Elementary (EL) and High School (HS) Students Grouped by Activity Level Age Mean IRb Percentile Rankings Students (yrs) Location Activity type' (m'/day) 1st 50th 99.9th EL (n'=17) 10-12 Indoor Light 13.7 2.93 12.71 38.14 Moderate 2.8 0.70 2.44 7.48 Heavy 0.4 0.096 0.34 1.37 EL Outdoor Light 2.1 0.79 1.72 9.50 Moderate 1.84 0.41 1.63 5.71 Heavy 0.57 0.24 0.48 1.80 HS (n=19) 13-17 Indoor Light 15.2 5.85 14.04 63.18 Moderate 1.4 0.63 1.26 6.03 Heavy 0.25 0.11 0.22 1.37 HS Outdoor Light 1.15 0.50 1.08 6.34 Moderate 1.64 0.62 1.40 7.41 Heaw 0.29 0.096 0.20 1.19 ' For this report, activity type presented in Table 5-2 was redefined as light activity for slow, moderate activity for medium, and heavy activity for fast. b Daily inhalation rate was calculated by multiplying the hours spent at each activity level (Table 5-4) by the corresponding inhalation rate (Table 5-3). ' Number of elementary (EL) and high school students (HS). Source: Adaoted from Soier et al. 1992 !Generated usina data from Tables 5-3 and 5-4). Table 5-6. Summarv of Average Inhalation Rates (m3/hr) by Age Group and Activity Levels for Laboratorv Protocols Acie Group Restinq" Sedentarvb Liq hf Moderated He aw* Young Children1 0.37 0.40 0.65 DNP9 DNP Childrenh 0.45 0.47 0.95 1.74 2.23 Adult Females; 0.43 0.48 1.33 2.76 2.96i Adult Malesk 0.54 0.60 1.45 1.93 3.63 a Resting defined as lying (see Appendix Table 5A-1 for original data). b Sedentary defined as sitting and standing (see Appendix Table 5A-1 for original data). c Light defined as walking at speed level 1.5 -3.0 mph (see Appendix Table 5A-1 for original data). d Moderate defined as fast walking (3.3 -4.0 mph) and slow running (3.5 -4.0 mph) (see Appendix Table 5A-1 for original data). e Heavy defined as fast running (4.5 -6.0 mph) (see Appendix Table 5A-1 for original data). f Young children (both genders) 3 -5.9 yrs old. g DNP. Group did not perform this protocol or N was too small for appropriate mean comparisons. All young children did not run. h Children (both genders) 6 -12.9 yrs old. i Adult females defined as adolescent, young to middle aged,.and older adult females. j Older adults not included in mean value since they did not perform running protocols at particular speeds. k Adult males defined as adolescent, young to middle aged, and older adult males. Source: Adapted from Adams, 1993. Table 5-7. Summary of Average Inhalation Rates (m3/hr) by Age Group and Activity Levels in Field Protocols AQe Group Light8 Sedentarl Moderatec Young Childrend DNP0 DNP 0.68 Child rent DNP DNP 1.07 Adult Females9 1.10h 0.51 DNP Adult Malesi 1.40 0.62 1.78j a Light activity was defined as car maintenance (males), housework (females), and yard work (females) (see Appendix Table 5A-2 for original data). b Sedentary activity was defined as car driving and riding (both genders) (see Appendix Table 5A-2 for original data). c Moderate activity was defined as mowing (males); wood working (males); yard work (males); and play (children) (see Appendix Table 5A-2 for original data). d Young children (both genders)= 3 -5.9 yrs old.

DNP. Group did not perform this protocol or N was too small for appropriate mean comparisons. 1 Children (both genders)= 6 -12.9 yrs old. 9 Adult females defined as adolescent, young to middle aged, and older adult females. h Older adults not included in mean value since they did not perform this activity. ; Adult males defined as adolescent, young to middle aged, and older adult males. i Adolescents not included in n:iean value since they did not perform this activity. Source: Adams, 1993.

Table 5-8. Distributions of Individual and Grouo lnhalationNentilation Rate for Outdoor Workers Ventilation Rate IVR\ lm3/hr\ Percentile Pooulation Grouo and Subcirouo' Mean+/- SD 1 50 99 All Subjects (nb = 19) 1.68 +/- 0.72 0.66 1.62 3.90 Job GCW'/Laborers (n=5) 1.44 +/- 0.66 0.48 1.32 3.66 Iron Workers (n=3) 1.62 +/- 0.66 0.60 1.56 3.24 Carpenters ( n= 11) 1.86 +/- 0.78 0.78 1.74 4.14 Site Medical Office Site (n=7) 1.38 +/- 0.66 0.60 1.20 3.72 Hosoital Site (n=12) 1.86 +/- 0.78 0.72 1.80 3.96 a Each group or subgroup mean was calculated from individual means, not from pooled data. b n = number of individuals performing specific jobs or number of individuals at survey sites. c GCW -general construction worker. Source: Linn et al., 1993. Table 5-9. Individual Mean Inhalation Rate (m3/hr) bv Self-Estimated Breathino Rate or Job Activitv Cateoorv for Outdoor Workers Self-Estimated Job Activity Category (m3/hr) Breathing Rate {m3/hr) Population Group and Subgroup Slow Med Fast Sit/Std Walk Carry Trade" All Subjects {n=19) 1.44 1.86 2.04 1.56 1.80 2.10 1.92 Job GCW'/Laborers {n=5) 1.20 1.56 1.68 1.26 1.44 1.74 1.56 Iron Workers {n=3) 1.38 1.86 2.10 1.62 1.74 1.98 1.92 Carpenters {n=11) 1.62 2.04 2.28 1.62 1.92 2.28 2.04 Site Office Site {n=7) 1.14 1.44 1.62 1.14 1.38 1.68 1.44 Hospital Site {n=12) 1.62 2.16 2.40 1.80 2.04 2.34 2.16 ' GCW -general construction worker b Trade -"Working at Trade" (i.e., tasks specific to the individual's job classification) Source: Linn et al., 1993 Table 5-!0. Comparisons of Estimated Basal Metabolic Rates (BMR) with Average Food-Energy Intakes for Individuals Samoled in the 1977-78 NFCS Cohort/Age Body Weight BMR" Energy Intake (EFD) Ratio (years) kQ MJ d-1b kcal d-1c MJ d-1 kcal d"1 EFD/BMR Children Under1 7.6. 1.74 416 3.32 793 1.90 1to2 13 3.08 734 5.07 1209 1.65 3 to 5 18 3.69 881 6.14 1466 1.66 6 to 8 26 4.41 1053 7.43 1774 1.68 Males 9 to 11 36 5.42 1293 8.55 2040 1.58 12 to 14 50 6.45 1540 9.54 2276 1.48 15 to 18 66 7.64 1823 10.8 2568 1.41 19 lei 22 74 7.56 1804 10.0 2395 1.33 23 to 34 79 7.87 1879 10.1 2418 1.29 35 to 50 82 7.59 1811 9.51 2270 1.25 51to64 80 7.49 1788 9.04 2158 1.21 65to 74 76 6.18 1476 8.02 1913 1.30 75+ 71 5.94 1417 7.82 1866 1.32 Females 9 to 11 36 4.91 1173 7.75 1849 .1.58 12 to 14 49 5.64 1347 7.72 1842 1.37 15 to 18 56 6.03 1440 7.32 1748 1.21 19 to 22 59 5.69 1359 6.71 1601 1.18 23 to 34 62 5.88 1403 6.72 1603 1.14 35 to 50 66 5.78 1380 6.34 1514 1.10 51to64 67 5.82. 1388 6.40 1528 1.10 65 to 74 66 5.26 1256 5.99 1430 1.14 75 + 62 5.11 1220 5.94 1417 1 :16 a Calculated from the appropriate age and gender-based BMR equations given in Appendix Table 5A-4. b MJ d*1 -mega joules/day C' kcal d*1 -kilo calories/day Source: Layton, 1993. Table 5-11. Dailv Inhalation Rates Calculated from Food-Enerav Intakes Daily Inhalation Inhalation Rates Rate* Sleeo METbValue Inactive' Active' Cohort/Aae lvearsl Ld lm'/dav1 lh\ A* Ft lm3/dav1 lm3/dav\ Children <1 1 4.5 11 1.9 2.7 2.35 6.35 1 -2 2 6.8 11 1.6 2.2 4.16 9.15 3-5 3 8.3 10 1.7 2.2 4.98 10.96 6-8 3 10 10 1.7 2.2 5.95 13.09 Males 9 -11 3 14 9 1.9 2.5 7.32 18.3 12 -14 3 15 9 1.8 2.2 8.71 19.16 15-18 4 17 8 1.7 2.1 10.31 21.65 19 -22 4 16 8 1.6 1.9 10.21 19.4 23-34 11 16 8 1.5 1.8 10.62 19.12 35-50 16 15 8 1.5 1.8 10.25 18.45 51 -64 14 15 8 1.4 1.7 10.11 17.19 65-74 10 13 8 1.6 1.8 8.34 15.01 75+ 1 11 8 1.6 1.9 8.02 15.24 Lifetime average 9 14 Females 9 -11 3 13 9 1.9 2.5 6.63 16.58 12-14 3 12 9 1.6 2.0 7.61 15.20 15 -18 4 12 8 1.5 1.7 8.14 13.84 19 -22 4 11 8 1.4 1.6 7.68 12.29 23 -34 11 11 8 1.4 1.6 7.94 12.7 35-50 16 10 8 1.3 1.5 7.80 11.7 51 -64 14 10 8 1.3 1.5 7.86 11.8 65 -74 10 9.7 8 1.4 1.5 7.10 10.65 75+ 1 9.6 8 1.4 1.6 6.90 11.04 Lifetime averaae 9 10 a Daily inhalation rate was calculated by multiplying the EFD values (see Table 5-10) by H x VQ x (m' 1,000 L"1} for subjects under 9 years of age and by 1.2 x H x VQ x (m' 1,000 L-1) (for subjects 9 years of age and older (see text for explanation}. Where: EFD = Food energy intake (Kcal/day} or (MJ/day} H = Oxygen uptake= 0.05 LO,tKJ or 0.21 LO/Kcal VQ = Ventilation equivalent= 27 =geometric mean ofVQs (unitless} b MET = Metabolic equivalent ' Inhalation rate for inactive periods was calculated as BMR x H x VQ x (d 1,440 min-1) and for active periods by multiplying inactive inhalation rate by F (See footnote f}; BMR values are from Table 5-10. Where: BMR = Basal metabolic rate (MJ/day} or (kg/hr} d L is the number of years for each age cohort . . For individuals 9 years of age and old.er, A was calculated by multiplying the ratio for EFD/BMR (unitless} (Table 5-10) by the factor 1.2 (see text for explanation}. f F = (24A-S)/(24 -S} (unitless}, ratio of the rate of energy expenditure during active hours to the estimated BMR (unitless} Where: s = Number of hours spent sleeping each day (hrs} g Lifetime average was calculated by multiplying individual inhalation rate by corresponding L values summing the products across cohorts and dividing the result by 75, the total of the cohort age spans. Source: Lavton 1993. Table 5-12. Daily Inhalation Rates Obtained from the Ratios of Total Energy Expenditure to Basal Metabolic Rate (BMR) Gender/Age Body Weight' BMRb H Inhalation Rate, VE (yrs) (kg) (MJ/day) VQ Ac (m30,IMJ) (m3/day)' Male 0.5 -<3 14 3.4 27 1.6 0.05 7.3 3 -<10 23 4.3 27 1.6 0.05 9.3 10 -<18 53 6.7 27 1.7 0.05 15 *18 -<30 76 7.7 27 1.59 0.05 17 30 -<60 80 7.5 27 1.59 0.05 16 60+ 75 6.1 27 1.59 0.05 13 Female 0.5 -<3 11 2.6 27 1.6 0.05 5.6 3-<10 23 4.0 27 1.6 0.05 8.6 10 -<18 50 5.7 27 1.5 0.05 12 18-<30 62 5.9 27 1.38 0.05 11 30-<60 68 5.8 27 1.38 0.05 11 60+ 67 5.3 27 1.38 0.05 9.9 ' Body weight was based on the average weights for age/gender cohorts in the U.S. population. b The BMRs (basal metabolic rate) are calculated using the respective body weights and BMR equations (see Appendix Table 5A-4). 0 The values of the BMR multiplier (EFD/BMR) for those 18 years and older were derived from the Basiotis et al. (1989) study: Male = 1.59, Female = 1.38. For males and females under 10 years old, the mean BMR multiplier used was 1.6. For males and females aged 10 to< 18 years, the mean values for A given in Table 5-11 for 12-14 years and 15-18 years, age brackets for males and females were used: male= 1.7 and female= 1.5. ' Inhalation rate= BMR x Ax H x VQ; VQ = ventilation equivalent and H = oxygen uptake. Source: Lavton, 1993. Table 5-13. Daily Inhalation Rates Based on Time-Activity Survey Males Females Age (yrs) and Activity MET Body Body v.r v* vr Weight BMRb Duration° Ed v* (m,/Elay) (m3'hr) E a (KJ/hr) (hr/day) (MJ/day) (m3/day) (m3/hr) (kg) 20-34 Sleep 1 76 320 7.2 2.3 3.1 0.4 62 283 7.2 2.0 2.8 0.4 Light 1.5 76 320 14.5 7.0 9.4 0.7 62 283 14.5 6.2 8.3 0.6 Moderate 4 76 320 1.2 1.5 2.1 1.7 62 283 1.2 1.4 1.8 1.5 Hard 6 76 320 0.64 1.2 1.7 2.6 62 283 0.64 1.1 1.5 2.3 Very Hard 10 76 320 0.23 0.74 1.0 4.3 62 283 0.23 0.65 0.88 3.8 Totals 24 17 17 24 11 15 35-49 Sleep 1 81 314 7.1 2.2 3.0 0.4 67 242 7.1 1.7 2.3 0.3 Light 1.5 81 314 14.6 6.9 9.3 0.6 67 242 14.6 5.3 7.2 0.5 Moderate 4 81 314 1.4 1.8 2.4 1.7 67 242 1.4 1.4 1.8 1.3 Hard 6 81 314 0.59 1.1 1.5 2.5 67 242 0.59 0.9 1.2 2.0 Very Hard 10 81 314 0.29 0.91 1.2 4.2 67 242 0.29 0.70 0.95 3.2 Totals 24 13 17 24 9.9 13 50-64 Sleep 1 80 312 7.3 2.3 3.1 0.4 68 244 7.3 1.8 2.4 0.3 Light 1.5 80 312 14.9 7.0 9.4 0.6 68 244 14.9 5.4 7.4 0.5 Moderate 4 80 312 1.1 1.4 1.9 1.7 68 244 1.1 1.1 1.4 1.3 Hard 6 80 312 0.50 0.94 1.3 2.5 68 244 0.5 0.7 1.0 2.0 Very Hard 10 80 312 0.14 0.44 0.6 4.2 68 244 0.14 0.34 0.46 3.3 Totals 24 12 16 24 9.4 13 65-74 Sleep 1 75 256 7.3 1.9 2.5 0.3 67 221 7.3 1.6 2.2 . 0.3 Light 1.5 75 256 14.9 5.7 7.7 0.5 67 221 14.9 4.9 6.7 0.4 Moderate 4 75 256 1.1 1.1 1.5 1.4 67 221 1.1 1.0 1.3 1.2 Hard 6 75 256 0.5 0.8 1.0 2.1 67 221 0.5 0.7 0.9 1.8 Very Hard 10 75 256 0.14 0.36 0.48 3.5 67 221 0.14 0.31 0.42 3.0 Totals 24 9.8 13 24 8.5 11 a Body weights were obtained from Nallar and Rowland (1987) b The basal metabolic rates (BMRs) for the age/gender cohorts were calculated using the respective body weights and the BMR equations (Appendix Table 5A-4) c Duration of activities were obtained*from Sallis et al. (1985) d Energy expenditure rate (E) was calculated by multiplying BMR (KJ/hr) x (MJ/1000 KJ) x duration (hr/day) x MET e v. (inhalation rate) was calculated by multiplying E (MJ/day) by H(0.05 m' oxygen/MJ) by VQ (27) f v. (m3/hr) was calculated by multiplying BMR (KJ/hr) x (MJ/1000 KJ) x MET x H (0.05 m' oxygen/MJ) x VQ (27) Source: Layton, 1993. Table 5-14. Inhalation Rates for Short-Term Exoosures Activity Type Rest Sedentary Light Moderate Heavy Gender/Age (yrs) Weight BM Rb MET (BMR Multiplier) (kg)" (MJ/day) 1 1.2 2c 4* 10° Inhalation Rate rm'ihrl'*g Male 0.5 -<3 14 3.40 0.19 0.23 0.38 0.78 1.92 3-<10 23 4.30 0.24 0.29 0.49 0.96 2.40 10 -<18 53 6.70 0.38 0.45 0.78 1.50 3.78 18 -<30 76 7.70 0.43 0.52 0.84 1.74 4.32 30 -<60 80 7.50 0.42 0.50 0.84 1.68 4.20 60+ 75 6.10 0.34 0.41 0.66 1.38 3.42 Female 0.5-<3 11 2.60 0.14 0.17 0.29 0.60 1.44 3 -<10 23 4.00 0.23 0.27 0.45 0.90 2.28 10 -<18 50 5.70 0.32 0.38 0.66 1.26 3.18 18 -<30 62 5.90 0.33 0.40 0.66 1.32 3.30 30 -<60 68 5.80 0.32 0.39 0.66 1.32 3.24 60+ 67 5.30 0.30 0.36 0.59 1.20 3.00 a Body weights were based on average weights for age/gender cohorts of the U.S. population

The BMRs for the age/gender cohorts were calculated using the respective body weights and the BMR equations (Appendix Table 5A-4). 0 Range of 1.5 -2.5. d Range of3-5.
Range of >5 -20. 1 The inhalation rate was calculated by multiplying BMR (MJ/day) x H (0.05 L/KJ) x MET x VQ (27) x (d/1,440 min) 9 Original data were presented in Umin. Conversion to m'/hr was obtained as follows: 60 min m' L _h_r_ x --x IOOOL min Source: Lavton 1993.

Table*5-15. Daily Inhalation Rates Estimated From Daily Activities" Inhalation Rate (IR) Subject Resting Light Activity Daily Inhalation (m3/hr) (m3/hr) Rate (DIR)b (m3/day) Adult Man 0.45 1.2 22.8 Adult Woman 0.36 1.14 21.1 Child (10 yrs) .. 0.29 0.78 14.8 Infant ( 1 yr) 0.09 0.25 3.76 Newborn 0.03 0.09 0.78 a Assumptions made were based on 8 hours resting and 16 hours light activity for adults and children ( 10 yrs); 14 hours resting and 10 hours light activity for infants (1 yr); 23 hours resting and 1 hour light activity for newborns. b K DIR ' ..!_ j IR.t T II 11 IR; = Corresponding inhalation rate at i1h activity t; = Hours spent during the i1h activity k = Number of activity periods T =Total time of the exposure period (i.e., a day) Source: ICRP, 1981 Table 5-16. Summary of Human Inhalation Rates for Men, Women, and Children by Activity Level (m'/hour)' n' Restinq' n Liq ht' n 'Moderate' n Heavv' Adult male 454 0.7 102 0.8 102 2.5 267 4.8 Adult female 595 0.3 786 0.5 106 1.6 211 2.9 Average adult' 0.5 0.6 2.1 3.9 Child, age 6 years 8 0.4 16 0.8 4 2.0 5 2.3 Child, aqe 10 years 10 0.4 40 1.0 29 3.2 43 3.9 . Values of inhalation rates for males, females, and children (male and female) presented in this table represent the mean of values reported for b each activity level in 1985. (See Appendix Table 5A-7 fqr a detailed listing of the data from U.S. EPA, 1985.) n = number of observations at each activity level. ' Includes watching television, reading, and sleeping. d Includes most domestic work, attending to personal needs and care, hobbies, and conducting minor indoor repairs and home improvements . . \ Includes heavy indoor cleanup, performance of major indoor repairs and alterations, and climbing stairs. f Includes vigorous physical exercise and climbing stairs* carrying a load. g Derived by taking the mean of the adult male and adult female values for each activity level. Source: Adaoted from U.S. EPA, 1985. Table 5-17. Activity Pattern Data Aggregated for Three Microenvironments by Activity Level for all Age Groups Average Hours Per Day in Each Microenvironment Adivity Level Microenvironment at Each Activity Level Indoors Resting 9.82 Light 9.82 Moderate 0.71 Heavy 0.098 TOTAL 20.4 Outdoors Resting 0.505 Light 0.505 Moderate 0.65 Heavy 0.12 TOTAL 1.77 In Transportation Vehicle Resting 0.86 Light 0.86 Moderate 0.05 Heavy 0.0012 TOTAL 1.77 Source: Adaoted from U.S. EPA 1985. Table 5-18. Summary of Daily Inhalation Rates Grouped by Age and Activity level Daily Inhalation Rate (m3/day)a Total Daily IRb Resting Light Moderate Heavy (m3/day) Subiect Adult Male 7.83 8.95 3.53 1.05 21.4 Adult Female 3.35 5.59 2.26 0.64 11.8 Adult Averagec 5.60 6.71 2.96 0.85 16 Child 4.47 8.95 2.82 0.50 16.74 (age 6) Child 4.47 11.19 4.51 0.85 21.02 (aae 1 Q) a Daily inhalation rate was calculated using the following equation: ' 1 K JR -j. IRt. T II 11 IR; = inhalation rate at i1h activity (Table 5-18) t; = hours spent per day during ith activity (Table 5-19) k = number of activity periods T = total time ofthe exposure period (e.g., a day) b Total daily inhalation rate was calculated by summing the specific activity (resting, light, moderate, heavy) daily inhalation rate. Source: Generated using the data from U.S. EPA (1985) as shown in Tables 5-16 and 5-17.

Table 5-19. Distribution Pattern of Predicted VR and EVR (equivalent ventilation rate) for 20 Outdoor Workers VR (m3/hr)' EVRb (m3/hr/m2 body surface) Self-Reported Arithmetic Geometric Arithmetic Geometric Activity Level N' Mean+/- SD Mean+/- SD Mean+/- SD Mean+/- SD Sleep 18,597 0.42+/-0.16 0.39 +/- 0.08 0.23 +/- 0.08 0.22 +/- 0.08 Slow 41,745 0.71 +/- 0.4 0.65+/- 0.09 0.38 +/- 0.20 0.35 +/- 0.09 Medium 3,898 0.84 +/- 0.47 0.76 +/- 0.09 0.48 +/- 0.24 0.44 +/- 0.09 Fast 572 2.63 +/- 2.16 1.87 +/- 0.14 1.42 +/- 1.20 1.00+/-0.14 Percentile Rankings, VR 1 5 10 50 90 95 99 99.9 Sleep 0.18 0.18 0.24 0.36 0.66 0.72 0.90 1.20 Slow 0.30 0.36 0.36 0.66 1.08 1.32 1.98 4.38 Medium 0.36 0.42 0.48 . 0.72 1.32 1.68 2.64 3.84 Fast 0.42 0.54 0.60 1.74 5.70 6.84 9.18 10.26 Percentile Rankinqs, EVR 1 5 10 50 90 95 99 99.9 Sleep 0.12 0.12 0.12 0.24 0.36 0.36 0.48 0.60. Slow 0.18 0.18 0.24 0.36 0.54 0.66 1.08 2.40 Medium 0.18 0.24 0.30 0.42 0.72 0.90 1.38 2.28 Fast 0.24 0.30 0.36 0.90 3.24 3.72 4.86 5.52 ' Data presented by Shamoo et al. (1991) in liters/minute were converted to m3/hr. b EVR = VR per square meter of body surface area. ' Number of minutes with valid appearing heart rate records and corresponding daily records of breathing rate. Source: Shamoo et al. 1991 Table 5-20. Distribution Pattern of Inhalation Rate by Location and Activity Type for 20 Outdoor Workers Self-reported Inhalation rate (m3/hr)* Location Activity Type" Activity Level % of Time +/-SD % of Indoor Essential Sleep 28.7 0.42+/-0.12 69+/- 15 Slow 29.5 0.72 +/- 0.36 106 +/- 43 Medium 2.4 0.72 +/- 0.30 129 +/- 38 Fast 0 0 0 Indoor Non-essential Slow 20.4 0.66 +/- 0.36 98+/- 36 Medium 0.9 0.78 +/- 0.30 120 +/- 50 Fast 0.2 1.86 +/- 0.96 278 +/- 124 Outdoor Essential Slow 11.3 0.78 +/- 0.36 117 +/- 42 Medium 1.8 0.84 +/- 0.54 130 +/- 56 Fast 0 0 0 Outdoor Non-essential Slow 3.2 0.90 +/- 0.66 136 +/- 90 Medium 0.8 1.26 +/- 0.60 213 +/- 91 Fast 0.7 2.82 + 2.28 362 + 275 a Essential activities include income-related, work, household chores, child care, study and other school activities, personal care, and destination-oriented travel; Non-essential activities include sports and active leisure, passive leisure, some travel, and social or civic activities. b Data presente9 by Shamoo et al. (1991) in liters/mintue were converted to m'/hr. c Statistic was calculated by converting each VR for a given subject to a percentage of her/his overall average. Source: Adaoted from Shamoo et al. 11991\.

Table 5-21. Actual Inhalation Rates Measured at Four Ventilation Levels Mean Inhalation Rate" (m3/hr)" Subject Location Low Medium Heavy Very Heavy All subjects Indoor 1.23 1.83 3.13 4.13 (Treadmill 1.96 2.93 4.90 Out oor 0.88 Total 0.93 1.92 3.01 4.80 a Original data were presented in Umin. Conversion to m3/hr was obtained as follows: *

60 min x x _L_ hr 1000L min Source: Adapted from Shamoo et al., 1992 Table 5-22. Confidence in Inhalation Rate Recommendations Considerations Rationale Ra ti no Elements
Peer Review Studies are from peer reviewed journal articles and an EPA peer High reviewed report. *D Accessibility Studies in have wide circulation. . High EPA repo s are available from the National Technical Information Service. * *D Reproducibility Information on questionnaires and interviews were not provided. Medium *D Focus on factor of interest Studies focused on ventilation rates and factors influencing them. High *D Data pertinent to U.S. Studies conducted in the U.S. High *D Primary data Both data collection and re-analysis of existing data occurred. Medium *D Currency Recent studies were evaluated. High *D Adequacy of data collection period Effort was made to collect data over time. High *D . Validity of approach Measurements were made by indirect methods. Medium *D Representativeness of the population An effort has been made to consider age and gender, but not systematically. Medium *D Characterization of variability An effort has been made to address age and gender, but not High systematically. *D Lack of bias in study design Subjects were selected randomly from volunteers and measured in the High same way. *D Measurement error Measurement error is well documented by statistics, but procedures Medium measure factor indirectly. Other Elements *D Number of studies Five key studies and six relevant studies were evaluated: *D Agreement between researchers . There is general agreement among researchers using different High experimental methods. Overall Rating Several studies exist that attempt to estimate inhalation rates according to age, gender and activity. High Table 5-23. Summary of Recommended Values for Inhalation Pooulation Mean Unner Percentile Long-term Exgosures Infants <1 year 4.5 m3/day ---Children 1-2 years 6.8 m3/day ---. 3-5 years 8.3 m3/day ---6-8 years 10 m3/day ---9-11 years males 14 m3/day ---females 13 m3/day ---12-14 years males 15 m3/day ---females 12 m3/day --15-18 years males 17 m3/day ---females 12 m3/day ---Adults (19-65+ yrs) females 11.3 m3/day ---males 15.2 m3/day ---Short-term Exgosures Adults Rest 0.4 m3/hr ---Sedentary Activities 0.5 m3/hr ---Light Activities 1.0 m3/hr ---Moderate Activities 1.6 m3/hr ---Heavy Activities 3.2 m3/hr ---Children Rest 0.3 m3/hr ---Sedentary Activities 0.4 m3/hr ---Light Activities 1.0 m3/hr ---Moderate Activities 1.2 m3/hr ---Heavy Activities 1.9 m3/hr ---Outdoor Workers Hourly Average 1.3 m3/hr 3.3 m3/hr Slow Activities 1.1 m3/hr Moderate Activities 1.5 m3/hr Heavv Activities 2.5 m3/hr Note: See Tables 5-25 5-26 and 5-27 for reference studies.

Table 5-24. Summarv of Inhalation Rate Studies Studv Ponulation Surveved Survev Time Period Data Generated Limitations/Advantaaes KEY INHALATION RATE STUDIES: Adams, 1993 n=160, ages 6-77; n = 40, ages 3-12. Three 25 min phases of resting Mean values of IR for adult HR correlated poorly with IR. protocol in the lab 6 mins of active males and females and children protocols in the lab. 30 min by their activity.levels. phases of field protocols repeated once. Layton, 1993 NFCS survey: nz30,000; NHANES survey: Daily I Rs; !Rs at 5 activity levels; Reported food biases in the dietary nz20,000 and IR for short-term exposures surveys employed; time activity Time Activity survey: nz2, 126 at 5 activity levels. survey was based on recall. Linn et al., 1992 Panel 1 -20 healthy outdoor workers, ages Late spring and early autumn. 3 Mean and upper estimates of JR; Small sample size; Calibration data 19-50; Panel 2 -17 healthy elementary diary days. Construction workers' Mean IR at 3 activity levels. not obtained over full HR range; school students, ages 10-12; Panel 3 -19 diary day. activities based on short-term diary healthy high school students, ages 13-17; data. Panel 4 -49 adult asthmatics, ages 18-50; Panel 5 -24 adult asthmatics, ages 19-46; Panel 6 -13 young asthmatics, ages 11-16; Panel 7 -7 construction workers, ages 26-34. Linn et al., 1993 n=19 construction workers. (Mid-July-early November, 1991) Distribution patterns of hourly IR Small sample population size; Diary.recordings before work, by activity level. breathing rates subjective in nature; during work and break times activities based on short-term diary data. Spier et al., 1992 n=36 students, ages 10-17. (Late September -October) Distribution patterns of hourly IR Activities based on short-term diary Involved 3 consecutive days of by activity levels and location data; self-estimated breathing rate diary recording by younger population was biased; small sample population size. RELEVANT INHALATION RATE STUDIES: ICRP, 1974 Based on data from other references -Reference daily IR for adult Validity and accuracy of data set females, adult males, children employed not defined; JR was (1 O yrs), and infant (1 yr) estimated not measured. Shamoo etal., n=9 volunteer workers ages 21-37, n=20 Involved 3-min indoor session/two No IR data presented. No useful data were presented for 1990 outdoor workers, 19-50 years old. 3-hr outdoor session at 4 activity dose assessments studies. levels Shamoo etal., n=20 outdoor workers, ages 19-50 Diary recordings of three 24-hr. Distribution patterns of IR and Small sample size; short-term diary 1991 periods within a week. EVR by activity levels and data. location. Shamoo etal., n=9 non-sedentary subjects, ages 21-37. 3-min. intervals of indoor Actual measured ventilation Small sample size; training 1992 exercises/two 3-hr outdoor rates presented. approach may not be cost-effective; exercise sessions at 4 activity VR obtained for outdoor workers levels. which are sensitive subpopulation. U.S. EPA, 1985 Based on data from several literature -Estimated IR for adult males, Validity and accuracy of data set sources adult females and children (ages employed not defined; JR was 6 and 10) by various activity estimated not measured. levels. Note: IR= inhalation rate* HR= heart rate* EVR = eauivalent ventilation rate. Table 5-25. Summary of Adult Inhalation Rates for Short-Term Exposure Stu.dies Arithmetic Mean (m3/hr) Activity Level Rest Sedentary Light Moderate High Reference 0.5 0.5 1.4 2.4 3.3 Adams, 1993 (Lab protocols) --0.6 1.2 1.8 --Adams, 1993 (Field protocols) 0.4 0.4 0.7 1.4 3.6 Layton, 1993 (Short-term exposure) 0.4 --0.6 1.5 3.0 Layton, 1993 (3rd approach) ----1.0 1.6 3.0 Linn et al., 1992 Table 5-26. Summary of Children's (18 years old or less) Inhalation Rates for Long-Term Exposure Studies* Arithmetic Mean (m3/day) Males and Age Males Females Females Reference less than 1 yr ----4.5 Layton, 1993 1-2 years ----6.8 Layton, 1993 3-5 years ----8.3 Layton, 1993 6-8 years ----10 Layton, 1993 9-11 years 14 13 --Layton, 1993 12-14 years 15 12 --Layton, 1993 15-18 years 17 12 --Layton, 1993

Layton, 1993 1st approach.

Table 5-27. Summary of Children's Inhalation Rates for Short-Term Exposure Studies Arithmetic Mean (m3/hr) Activity Level Rest Sedentary Light Moderate High Reference 0.4 0.4 0.8 ----Adams, 1993 (Lab protocols) ------0.9 --Adams, 1993 (Field protocols) 0.2 0.3 0.5 1.0 2.5 Layton, 1993 (Short-term data) --. --1.8 2.0 2.2 Spieretal., 1992(10-12yrs) ----0.8 1.0 11 Linn et al., 1992 (10-12 yrs) Table 5A-1. Mean Minute Ventilation L/min) by Group and Activity for Laboratory Protocols Activity Younq Childrena Children Adult Females Adult Males Lying 6.19 7.51 7.12 8.93 Sitting 6.48 7.28 7.72 9.30 Standing 6.76 8.49 8.36 10.65 Walking 1.5 mph 10.25 DNP DNP DNP 1.875 mph 10.53 DNP DNP DNP 2.0 mph DNP 14.13 DNP DNP 2.25 mph 11.68 DNP DNP DNP 2.5 mph DNP 15.58 20.32 24.13 3.0 mph DNP 17.79 24.20 DNP 3.3 mph DNP DNP *oNP 27.90 4.0 mph DNP DNP DNP 36.53 Running 3.5 mph DNP 26.77 DNP DNP 4.0 mph DNP 31.35 46.03b DNP 4.5 mph DNP 37.22 47.86b 57.30 5.0 mph DNP DNP 50.78b 58.45 6.0 moh DNP DNP DNP 65.66b a Young Children, male and female 3-5.9 yr olds; Children, male and female 6-12.9 yr olds; Adult Females, adolescent, young to middle-aged, and older adult females; Adult Males, adolescent, young to middle-aged, and older adult males; DNP, group did not perform this protocol or N was too small for appropriate mean b comparisons Older adults not included in the mean value since they did not perform running protocol at particular speeds. Source: Adams 1993.

* Table 5A-2. Mean Minute Ventilation Umin) bv Grouo and Activitv for Field Protocols Activity Young Children Adult Females Adult Males Children" Play 11.31 17.89 DNP DNP Car Driving DNP DNP 8.95 10.79 Car Riding DNP DNP 8.19 9.83 Yardwork DNP DNP 19.23e 26.07b/31.89c Housework DNP DNP 17.38 DNP Car Maintenance DNP DNP DNP 23.21d Mowing DNP DNP DNP 36.55e Woodworkina DNP DNP DNP 24.42e a Young Children, male and female 3-5.9 yr olds; Children, male and female 6-12.9 yr olds; Adult Females, adolescent, young to middle-aged, and older adult females; Adult Males, adolescent, young to middle-aged, and older adult males; DNP, group did not perform this protocol or N was too small for appropriate mean b comparisons; Mean value for young to middle-aged adults only c Mean value for older adults only d Older adults not included in the mean value since they did not perform this activity. e Adolescents not included in mean value since they did not perform this activity Source: Adams 1993.

Table 5A-3. Characteristics of Individual Subjects: Anthropometric Data, Job Cateqories, Calibration Results Calibration Subj.# Age (years) Ht. (in.) Wt.(lb.) Ethnic Group* Jebb Site' HR r* Range' 1761 26 71 180 Wht GCW Ofc 69-108 .91 1763 29 63 135 Asn GCW Ofc 80-112 .95 1764 32 71 165 Blk Car Ofc 56-87 .95 1765 30 73 145 Wht GCW Ofc 66-126 .97 1766 31 67 170 His Car Ofc 75-112 .89 1767 34 74 220 Wht Car Ofc 59-114 .98 1768 32 69 155 Blk GCW Ofc 62-152 .95 1769 32 77 230 Wht Car Hosp 69-132 .99 1770 26 70 180 Wht Car Hosp 63-106 .89 1771 39 66 150 Wht Car Hosp 88-118 .91 1772 32 71 260 Wht Car Hosp 83-130 .97 1773 39 69 170 Wht lrn Hosp 77-128 .95 1774 23 68 150 His Car Hosp 68-139 .98 1775 42 67 150 Wht lrn Hosp 76-118 .88 1776 29 70 180 His Car Hosp 68-152 .99 1778 35 76 220 Ind Car Hosp 70-129 .94 1779 40 70 175 Wht Car Hosp 72-140 .99 1780 37 75 242 His lrn Hosp 68-120 .98 1781 38 65 165 His Lab Hosp 66-121 .89 Mean 33 70 181 70-123 .94 SD 5 4 36 8-16 .04 a Abbreviations are interpreted as follows. Ethnic Group: Asn = Asian-Pacific, Blk = Black, His = Hispanic, Ind =American Indian, Wht =White b Job: Car= carpenter, GCW = general construction worker, lrn = ironworker, Lab = laborer ' Site:. Hosp = hospital buidling, Ofc = medical office complex. Calibration data d HR range = range of heart rates in calibration study e r2 = coefficient of determination (proportion of ventilation rate variability explainable by heart rate variability under calibration-study conditions, using quadratic prediction equation). Source: Linn et al. 1993. Table 5A-4. Statistics of the Age/Gender Cohorts Used to Develop Regression Equations for Predicting Basal Metabolic Rates <BMRl Gender/Age BMR Body Weight (y) MJ d-1 +/-SD cv* (kq) Nb BMR Equationc rd Males Under 3 1.51 0.918 0.61 6.6 162 0.249 bw-0.127 0.95 3 to< 10 4.14 0.498 0.12 21 338 0.095 bw + 2.110 0.83 10to<18 5.86 1.171 0.20 42 734 0.074 bw + 2.754 0.93 18 to< 30 6.87 0.843 0.12 63 2879 0.063 bw + 2.896 0.65 30 to< 60 6.75 0.872 0.13 64 646 0.048 bw + 3.653 0.6 60 + 5.59 0.928 0.17 62 50 0.049 bw + 2.459 0.71 Females Under 3 1.54 0.915 0.59 6.9 137 0.244 bw -0.130 0.96 3 to< 10 3.85 0.493 0.13 21 413 0.085 bw + 2.033 0.81 10to<18 5.04 0.780 0.15 38 575 0.056 bw + 2.898 0.8 18 to< 30 5.33 0.721 0.14 53 829 0.062 bw + 2.036 0.73 30 to< 60 5.62 0.630 0.11 61 372 0.034 bw + 3.538 0.68 60 + 4.85 0.605 0.12 56 38' 0.038 bw + 2.755 0.68 a Coefficient of variation (SD/mean) b N = number of subjects c Body weight (bw) in kg d coefficient of correlation Source: Lavton 1993. Table 5A-5. Selected Ventilation Values Durinq Different Activitv Levels Obtained From Various Literature Sources Col. 1 2 3 4 5 6 Resting Light Activity Heavy Work Maximal Work During Line Subject W(kg) Exercise f VT V* f VT V* f VT V* f VT V* Adult 1 Man 68.5 12 750 7.4 17 1670 29 21 2030 43 2 1.7 m2 SA 12 500 6 3 30y; 170 cm L 15 500 7.5 16 1250 20 4 20-33 y 70.4 40 3050 111 5 Woman 54 12 340 4.5 19 860 16 30 880 25 6 30y; 160 cm L 15 400 6 20 940 19 7 20-25 y; 165.8 cm L 60.3 46 2100 90 8 Pregnant (8th mo) 16 650 10 Adolescent 9 male, 14-16 y 16 330 5.2 53 2520 1'13 10 male, 14-15 y 59.4 11 female, 14-16 y 15 300 4.5 12 female, 14-15 y; 164.9 cm L 56 52 1870 88 Childreri

13 10y;140cml 16 300 4.8 24 600 14 14 males, 10-11 y 36.5 58 1330 71 15 males, 10-11y;140.6 cm L 32.5 61 1050 61 16 females, 4-6 y 20.8 70 600 40 17 females, 4-6 y; 111.6 cm L 18.4 66 520 34 18 Infant, 1 y 30 48 1.4. 19 Newborn 2.5 34 15 0.5 20 20 hrs-13 wk 2.5-5.3 68b 51*,b 3.5b 21 9.6 hrs 3.6 25 21 0.5 22 6.6 days 3.7 29 21 0.6 W = body weights referable to the dimension quoted in column 1; f = frequency (breaths/min); VT= tidal volume (ml); V* = minute volume (I/min); SA = surface area; cm L = length/height; y = years of age; wk = week. -' a Calculated from V* = f x VT. b Crying. Source: ICRP 1981.

Table 5A-6. Estimated Minute Ventilation Associated with Activity Level for Average Male Adulta Level of work L/min Representative activities Light 13 Level walking at 2 mph; washing clothes Light 19 Level walking at 3 mph; bowling; scrubbing floors Light 25 Dancing; pushing wheelbarrow with 15-kg load; simple construction; stacking firewood Moderate 30 Easy cycling; pushing wheelbarrow with 75-kg load; using sledgehammer Moderate 35 Climbing stairs; playing tennis; digging with spade Moderate 40 Cycling at 13 mph; walking on snow; digging trenches Heavy 55 Cross-country skiing; rock climbing; stair climbing Heavy 63 with load; playing squash or handball; chopping Very heavy 72 with axe Very heavy 85 Level running at 10 mph; competitive cycling Severe 100+ Competitive long distance running; cross-country skiing a Average adult assumed to weigh 70 kg. Source: Adapted from U.S. EPA, 1985 Table 5A-7. Minute Ventilation Ranges by Age, Sex, and Activity Level Ventilation ranges liters/minute Age Sex Resting Light Moderate Heavy (years) n Range Mean n Range Mean ri Range Mean n Range Mean Infants M/F 316 0.25 -2.09 0.84 2 F M 3 F M 4 F 2 32.0 -32.5 32.3 M 4 39.3 -43.3 41.2 5 F 3 31.0-35.0 32.8 M 3 30.9 -42.6 37.5 6 F 2 35.9 -38.9 37.4 M 8 5.0 -7.0 6.5 16 5.0 -32.0 13.9 4 28.0 -43.0 33.3 3 35.5 -43.5 40.3 7 F 3 48.2 -51.4 49.6 M 2 44.1 -55.8 50.0 8 F 4 51.2 -67.6 57.6 M 3 59,3 -62.2 60.7 9 F 27 55.8 -63.4 50.9 M 7 59.5 -75.2 65.7 10 F 21 46.2 -71.1 60.4 M 10 5.z'-8.3 7.1 20 5.2 -35.0 17.2 9 41.0 -68.0 53.4 6 63.9 -74.6 70.5 F 7 49.7 -80.9 63.5 M 20 20.3 20 33.1 9 47.6 -77.5 65.5 12 F 54 4.1 -16.1 15.4 4 19.6 -46.3 26.5 31 65.5 -79.9 71.8 M 56 7.2 -16.3 15.4 6 18.5 -46.3 34.1 9* 58.1 -84.7 67.7 13 F 5 7.2 -15.4 9.9 5 18.5 -46.3 30.3 7 67.6 -102.6 87.7 M 16 3.1-15.4 8.9 30 3.1 -24.9 16.4 29 14.4 -48.4 32.8 38 27.8 -105.0 57.9 14 F 53 3.1 -15.6 14.9 3 21.6 -37.1 28.1 5 80.7-100.7 88.9 M 77 3.1 -27.8 14.2 24 24.7 -55.0 39.7 16 42.2 -121.0 86.9 15 F 1 6.2 1 26.8 6 68.4 -97.1 87.1 M 8 3.1 -26.8 11.1 7 27.8 -46.3 39.3 6 48.4 -140.3 110.5 16 F 50 15.2 8 73.6-119.1 93.9 M 50 15.6 3 79.6 -'132.2 102.5 17 F 2 91.9 -95.3 93.6 M 12 5.8 -9.0 7.3 12 40.0 -63.0 48.6 3 89.4 -139,3 107.7 18 F M 9 99.7 -143.0 120.9 Adults F 595 4.2-11.66 5.7 786 4.2 -29.4 8.1 106 20.7 -34.2 26.5 211 23.4 -114.8 47.9 Adults M 454 2.3 -18.8 12.2 . 102 2.3 -27.6 13.8 102 14.4 -78.0 40.9 267 34.6 -183.4 80.0 n = number of observations Note: Values in liters/minute can be converted to units of m' /hour by multiplying by the conversion factor, 60 minutes/hour 1000 liters/m3 Source: Adapted from U.S. EPA, 1985. Potential Dose Mouth/ Nose Intake Applied Dose . Lung Uptake Internal Dose Metabolism I I Biologically Effective Dose Organ Figure 5-1. Schematic of Dose and Exposure: Respiratory Route Source: U.S. EPA, 1992. Effect REFERENCES FOR CHAPTERS Adams, W.C. (1993) Measurement of breathing rate and volume in routinely performed daily activities, Final Report. California Air Resources Board (GARB) Contract No. A033-205. June 1993. 185 pgs. American Industrial Health Council (AIHC). (1994) Exposure factors sourcebook. AIHC, Washington, DC. Basiotis, P.P.; Thomas, R.G.; Kelsay, J.L.; Mertz, W. (1989) Sources of variation in energy intake by men and women as determined from one year's daily dietary records. Am. J. Clin. Nutr. 50:448-453.

Benjamin, G.S. (1988) "The lungs." In: Fundamentals of Industrial Hygiene, Third Edition, Plog, B.A., ed. Chicago, iL: National Safety Council, p. 31-45. Brorby, G.; Ffnley, B. (1993) Standard probability density functions for routine use in environmental health risk assessment. Presented at the Society of Risk Analysis Meeting, December 1993, Savannah, GA. ICRP. ( 1981) International Commission on Radiological Protection. Report of the task group on reference man. New York: Pergammon Press. Layton, D.W. (1993) Metabolically consistent breathing rates for use in dose . assessments. Health Physics 64(1 ):23-36. Linn, W.S.; Shamoo, D.A; Hackney, J.D. (1992) Documentation of activity patterns in "high-risk" groups exposed to ozone in the Los Angeles area. In: Proceedings of the . Second EPA/AWMA Conference on Tropospheric Ozone, Atlanta, Nov. 1991. pp. 701-712. Air and Waste Management Assoc;, Pittsburgh, PA. Linn, W.S.; Spier, C.E.; Hackney, J.D. (1993) Activity patterns in ozone-exposed construction workers. J. Occ. Med. Tox. 2(1 ):1-14. Menzel, D.B.; Amdur, M.O. (1986) Toxic responses of the respiratory system. In: Klaassen, C.; Amdur, M.O.; Doull, J., eds. Toxicology, The Basic Science of Poisons. 3rd edition. New York: MacMillan Publishing Company. Najjar, M.F.; Rowland, M. (1987) Anthropometric reference data and prevalence of overweight: United States. 1976-80. Hyattsville, MD: National Center for Health Statistics. U.S. Department of Health and Human Services: DHHS Publication No. (PHS) 87-1688. Palisade. (1992) @Risk User Guide. Newfield, NY: Palisade Corporation.

Sallis, J.F.; Haskell, W.L.; Wood, P.O.; Fortmann, S.P.; Rogers, T.; Blair, S.N.; Pafferibarger, Jr., R.S. (1985) Physical activity assessment methodology in the City project. Am. J. Epidemiol. 121:91-106. Shamoo, D.A.; Trim, S.C.; Little, D.E.; Linn, W.S.; Hackney, J.D. (1990) Improved quantitation of air pollution dose rates by improved estimation of vei:itilation rate. In: Total Exposure Assessment Methodology: A New Horizon, pp. 553-564. Air and Waste Management Assoc., Pittsburgh, PA. Shamoo, D.A.; Johnson, T.R.; Trim, S.C.; Little, D.E.; Linn, W.S.;*Hackney, J.D. (1991) Activity patterns in a panel of outdoor workers exposed to oxidant pollution. J. Expos. Anal. Environ. Epidem. 1(4):423-438. Shamoo, D.A.; Trim, S.C.; Little, D.E.; Whynot, J.D.; Linn, W.S. (1992) Effectiveness of training subjects to estimate their level of ventilation. J. Occ. Med. Tox. 1 (1 ):55-62. Spier, C.E.; Little, D.E.; Trim, S.C.; Johnson, T.R.; Linn, W.S.; Hackney, J.D. (1992) Activity patterns in elementary and high school students exposed to oxidant . pollution. J. Exp. Anal. Environ. Epid. 2(3):277-293. U.S. EPA. (1985) Development of statistical distributions or ranges of standard factors used in exposure assessments. Washington, DC: Office of Health and Environmental Assessment; EPA report No. EPA 600/8-85-010. Available from: NTIS, Springfield, VA; PB85-242667. U.S. EPA. (1989) Exposure factors handbook. Washington, DC: Office of Research and Development, Office of Health and Environmental Assessment. EPA/600/18-89/043. U.S. EPA. (1992) Guidelines for exposure assessment. Washington, DC: Office of Research and Development, Office of Health and Environmental Assessments. EPA/600/Z-92/001. U.S. EPA. (1994) Methods for derivation of inhalation reference concentrations and application of inhalation dosimetry. Washington, DC: Office of Health and Environmental Assessment. EPA/600/8-90/066F. -) I I __J DOWNLOADABLE TABLES FOR CHAPTER 5 The following selected tables are available for download as Lotus 1-2-3 worksheets. Table 5-3. Distribution of Predicted IR by Location and Activity Levels for Elementary and High School Students *[WK1, 2 kb] Table 5-5. Distribution Patterns of Dqily Inhalation Rates for Elementary (EL) and High School (HS) Students Grouped by Activity Level [WK1, 2 kb] Table 5-11. Daily Inhalation Rates Calculated from Food-Energy Intakes [WK1, 5 kb] Table 5-12. Daily Inhalation Rates Obtained from the Ratios of Total Energy Expenditure to Basal Metabolic Rate (BMR) [WK1, 2 kb] Table 5-14. Inhalation Rates for Short-Term Exposures . [WK1, 3 kb] Table 5-19. Distribution Pattern of Predicted VR and EVR (equivalent ventilation rate) for 20 Outdoor Workers [WK 1, 3 kb] Table 5A-3. Characteristics of Individual Subjects: Anthropometric Data, Job Categories, Calibration Results [WK1, 4 kb] Table 5A-7. Minute Ventilation Ranges by Age, Sex, and Activity Level [WK1, 9 kb] Volume I -General Fa_ctors Chapter 6 -Dermal 6. DERMAL ROUTE 6.1. EQUATION FOR DERMAL DOSE 6.2. SURFACE AREA 6.2.1. Background 6.2.2. Measurement Techniques 6.2.3. Key Body Surface Area Studies 6.2.4. Relevant Surface Area Studies 6.2.5. Application of Body Surface Area Data 6.3. SOIL ADHERENCE TO SKIN 6.3.1. Background 6.3.2. Key Soil Adherence to Skin Studies 6.3.3. Relevant Soil Adherence to Skin Studies 6.4. RECOMMENDATIONS 6.4.1. Body S.urface Area 6.4.2. Soil Adherence to Skin REFERENCES FOR CHAPTER 6 APPENDIX6A Table 6-1. Table 6-2. Table 6-3. Table 5,.4_ Table 6-5. Table 6-6. Table 6-7. Table 6-8. Table 6-9. Table 6-10. Table 6-11. Table 6-12. Summary of Equation Parameters for Calculating Adult Body Surface Area Surface Area of Adult Males in Square Meters Table 6-13. Table 6-14.

Table 6-15. Table 6-16. Table 6-17. Table 6-18. Surface Area of Adult Females in Square Meters Surface Area of Body Part for Adults (m2) Percentage of Total Body Surface Area by Part for Adults Total Body Surface Area of Male Children in Square Meters Total Body Surface Area of Female Children in Square Meters Percentage of Total Body Area by Body Part for Children Descriptive Statistics for Surface Area/BodyWeight (SA/WB) Ratios (m2/kg) Statistical Results for Total Body Surface Area Distributions (m2) Summary of Field Studies Geometric Mean and Geometric Standard Deviations of Soil Adherence by Activity and Body Region
Summary of Surface Area Studies Summary of Recommended Values for Skin Surface Area Confidence in Body Surface Area Measurement Recommendations Recommendations for Adult Body Surface Area Summary of Soil Adherence Stud!es Confidence in Soil Adherence to Skin Recommendations Table 6-A1. Estimated Parameter Values for Different Age Intervals Table 6-A2. Summary of Surface Area Parameter Values for the DuBois and DuBois
Model Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 6 -Dennal Figure 6-1. Schematic of Dose and Exposure: Dermal Route Figure 6-2. SA/BW Distributions for Infants, Adults, and All Ages Combined Figure 6-3. Surface Area Frequency Distribution: Men and Women Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 6 -Dermal 6. DERMAL ROUTE Dermal exposure can occur during a variety of activities in different environmental media and microenvironments (U.S. EPA, 1992). These include:
Water (e.g., bathing, washing, swimming);
Soil (e.g., outdoor recreation, gardening, construction);
Sediment (e.g., wading, fishing);
Liquids (e.g., use of commercial products);
Vapors/fumes (e.g., use of commercial products); and *
Indoors (e.g., carpets, floors, countertops). The major factors that must be considered when estimating dermal exposure are: the ch.emical concentration in contact with the skin, the potential dose, the extent of skin surface area exposed, the duration of exposure, the absorption of the chemical through the skin, the internal dose, and the amount of chemical that can be delivered to a target organ (i.e., biologically effective dose) (see Figure 6-1 ). A discussion of these factors can be found in Guidelines for Exposure Assessment (U.S. EPA, 1992a). This chapter focuses on measurements of body surface areas and various factors needed to estimate dermal exposure to chemicals in water and soil. Information concerning dermal exposure to pollutants in indoor environments is limited. Useful . information concerning estimates of body surface area can be found in "Development of_ Statistical Distributions or Ranges of Standard Factors Used in Exposure Assessments" (U.S. EPA, 1985). "Dermal Exposure Assessment: Principles and Applications (U.S. EPA, 1992b), provides detailed information concerning dermal exposure using a stepwise guid_e in the exposure assessment process. .
The available studies have been classified as either key or relevant based on their applicability to exposure assessment needs and are summarized in this chapter. Recommended values are based on the results of the key studies. Relevant studies are presented to provide an added perspective on the state-of-knowledge pertaining to dermal exposure factors. All tables and figures presenting data from these studies are shown at the end of this chapter.
6.1. EQUATION FOR DERMAL DOSE The average daily dose (ADD) is the dose rate averaged over a pathway-specific period of exposure expressed as a daily dose on a per-unit-body-weight basis. The ADD is used for exposure to chemicals with non-carcinogenic non-chronic effects. For Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 6 -Dennal compounds with carcinogenic or chronic effects, the lifetime average daily dose (LADD) is used. The LADD is the dose rate averaged over a lifetime. For dermal contact with chemicals in soil or water, dernially absorbed average daily dose can be estimated by (U.S. EPA, 1992b): ADD ' x EV x ED x EF x SA BW xAT where: average daily dose (mg/kg-day); absorbed dose per event (mg/cm2-event); event frequency (events/day); exposure duration (years); exposure frequency (days/year); skin surface area available for contact (cm2); body weight (kg); and (Eqn. 6-1) ADD DA,,,.,, EV ED EF SA BW AT averaging time (days) for noncarcinogenic effects, AT= ED and for carcinogenic effects, AT= 70 years or 25,550 days. This method is to be used to calculate the absorbed dose of a chemical. Total body surface area (SA) is assumed to be exposed for a period of time (ED). For dermal contact with water, the is estimated with consideration for the permeability coefficient from water, the chemical concentration in Water, and the event duration. The approach to estimate DAevent is different for inorganic and organic compounds. The nonsteady-state approach to estimate the dermally absorbed dose from water is recommended as the preferred approach for organics which exhibit octanol-water partitioning (U.S. EPA, 1992b). First, this approach more.accurately reflects normal human exposure conditions since the short contact times associated with bathing and swimming generally mean that steady state will not occur. Second, the approach accounts for uptake that can occur after the actual exposure event due to absorption of residual chemical trapped in skin tissue. Use of the nonsteady-state model for organics has implications for selecting permeability coefficient (Kp) values (U.S. EPA, 1992b). It is recommended that the traditional steady-state approach be applied to inorganics (U.S. EPA, 1992b). Detailed information concerning how to estimate absorbed dose per event (DAevent) and KP values can be found in Section 5.3.1 of "Dermal Exposure Assessment: Principles and Applications" (U.S. EPA, 1992b). For dermal contact with contaminated soil, estimation of the DAevent is different from the estimation for dermai contact with chemicals in water. It is based on the concentration of the chemical in soil, the adherence factor of soil to skin, and the absorption fraction. Information for DAevent estimation from soil contact can be found in U.S. EPA (1992b), Section 6.4. Exposure Factors Handbook August 1997

Volume I -General Factors Chapter 6 -Dermal The* apparent simplicity of the absorption fraction (percent absorbed) makes this approach appealing. However, it is not practical to apply it to water contact scenarios, such as swimming, because of the difficulty in estimating the total material contacted (U.S. EPA, 1992b). It is assumed that there is essentially an infinite amount of material available, and that the chemical will be replaced GOntinuously, thereby increasing the amount.of material (containing the chemical) available by some large unknown amount. Therefore, the permeability coefficient-based approach is recommended over the absorption fraction approach for determining the dermally absorbed dose of chemicals in aqueous media. Before the absorption fraction approach can be used in soil co.ntact scenarios, the contaminant concentration in soil must be established. Not all of the chemical in a layer of dirt applied to skin may be bioavailable, nor is it assumed to be an internal dose. Because of the lack of KP data for compounds bound to soil, i;md reduced uncertainty in defining an applied dose, the absorption fraction-based approach is suggested for determining the internal dose* of chemicals in soil. More detailed explanation of the equations, assumptions, and approaches can be found in "Dermal Exposure Assessment: Principles and Applications" (U.S. EPA. 1992b). 6.2. SURFACE AREA 6.2.1. Background The total surface area of skin exposed to a contaminant must be determined using measurement or estimation techniques before conducting a dermal exposure assessment. Depending on the exposure scenario, estimation of the surface area for the total body or a specific body part can be used to calculate the contact rate for the pollutant. This section presents estimates for total body surface area and for body parts and presents information on the application of body surface area data. 6.2.2. Measurement Techniques Coating, triangulation, and surface.integration are direct measurement techniques that have been used to measure total body surface area and the surface area of specific body parts. Consideration has been given for differences due to age, gender, and race. The results of the various techniques have been summarized in "Development of Statistical Distributions or Ranges of Standard Factors Used in Exposure Assessments" (U.S. EPA, 1985). The coating method consists of coating either the whole body or specific body regions with a substance of known or measured area. Triangulation consists of marking the area of the body into geometric figures, then calculating the figure areas from their . Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 6 -Dermal linear dimensions. Surface integration is performed by using a planimeter and adding the areas. The triangulation measurement technique developed by Boyd (1935) has been found to be highly reliable. It estimates the surface area of the body using geometric approximations that assume parts of the body resemble geometric solids (Boyd, 1935). More recently, Popendorf and Leffingwell (1976), and Haycock et al. (1978) have developed similar geometric methods tliat assume body parts correspond to geometric solids, such as the sphere and cylinder. A linear method proposed by DuBois and DuBois (1916) is based on the principle that the surface areas of the parts of the body are proportional, rather than equal to the surface area of the solids they resemble. In addition to direct measurement techniques, several formulae have been proposed to estimate body surface area from measurements of other major body dimensions (i.e., height and weight) (U.S. EPA, 1985). Generally, the formulae are based on the principles that body density and shape are roughly the same and that the* relationship of surface area to any dimension may be represented by the curve of central tendency of their plotted values or by the algebraic expression for the curve. A discussion and comparison of formulae to determine total body surface area are presented in Appendix 6A. 6.2.3. Key Body Surface Area Studies U.S. EPA (1985) -Development of Statistical Distributions or Ranges of Standard Factors Used in Exposure Assessments -U.S. EPA (1985) analyzed the direct surface area measurement data of Gehan and George (1970) using the Statistical Processing System (SPS) software package of Buhyoff et al. (1982). Gehan and George (1970) selected 401 measurements made by Boyd (1935) that were complete for surface area, height, weight, and age for their analysis. Boyd (1935) had reported surface area estimates for 1,114 individuals using coating, triangulation, or surface integration methods (U.S. EPA, 1985). U.S.,EPA (1985) used SPS to generate equations to calculate surface area as a function of height and weight. These equations were then used to calculate body surface area distributions of the U.S. population u*sing the height and weight data obtained from the National Health and Nutrition Examination Survey (NHANES) II and the computer program QNTLS of Rochon and Kalsbeek (1983). The equation proposed by Gehan and George (1970) was determined by U.S. EPA (1985) to be the best choice for estimating tqtal body surface area. However, the paper by Gehan and George (1970) gave insufficient information to estimate the standard error about the regression. Therefore, U.S. EPA (1985) used the 401 direct measurements of Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 6 -Dennal children and adults and reanalyzed the data using the formula of Dubois and Dubois (1916) and SPS to obtain the standard error (U.S. EPA, 1985r Regression equations were developed for specific body parts using the Dubois and Dubois (1916) formula and using the surface area of various body parts provided by Boyd (1935) and Van Graan (1969) in conjunction with SPS. Regression equations for adults were developed for the head, trunk (including the neck), upper extremities (arms and hands, upper arms, and forearms) and lower extremities (legs and feet, thighs, and lower legs) (U.S. EPA, 1985). Table 6-1 presents a summary of the equation parameters developed by U.S. EPA (1985) for calculating surface area of adult body parts. Equations to estimate the body part surface area of children were not developed because of insufficient data. Percentile estimates of total surface area and surface area of body parts developed by U.S. EPA (1985) using the regression equations and NHANES II height and weight data are presented in Tables 6-2 and 6-3 for adult males and adult females, respectively. The calculated mean surface areas of body parts for men and women are presented in Table 6-4. The standard deviation, the minimum value, and the maximum value for each body part are included. The meqian total body surface area for men and women and the corresponding standard errors about the regressions are also given. It has been assumed that errors associated with height and weight are negligible (U.S. EPA, 1985). The data in Table 6-5 present the percentage of total body surface by body part for men and women. Percentile estimates for total surface area of male and female children presented in Tables 6-6 and 6-7 were calculated using the total surface area regression equation, NHANES II height and weight data, and using QNTLS. Estimates are not included for children younger than 2 years old because NHANES height data are not available for this age group. For children, the error associated with height and weight cannot be assumed to be zero because of their relatively sr:nall sizes. Therefore, the standard errors of the percentile estimates cannot be estimated, since it cannot be assumed that the errors associated with the exogenous variables (neight and weight) are independent of that associated with the model; there are insufficient data to determine the relationship between these errors.

Measurements of the surface area of children's body parts are summarized as a percentage of total surface area in Table 6-8. Because of the small sample size; the data cannot be assumed to represent the average percentage of surface area by body part for all children. Note that the percent of total body surface area contributed by the head decreases from childhood to adult, while the percent contributed by the leg Exposure Factors Handbook August 1997 I' Volume I -General Factors Chapter 6 -Dermal *Phillips et al. (1993} -Distributions of Total Skin Surface Area to Body Weight Ratios -Phillips et al. (1993) observed a strong correlation (0.986) between body surface area and body weight and studied the effect of using these factors as independent variables in the LADD equation. Phillips et al. (1993) concluded that, because of the correlation between these two variables, the use of body surface area to bodyweight (SA/BW) ratios in human exposure assessments is more appropriate than treating these factors as independent variables. Direct measurement (coating, triangulation, and surface integration) data from the scientific literature were used to calculate body surface area to body weight (SA/BW) ratios for three age groups (infants aged 0 to 2 years, children aged 2.1 to 17 .9 years, and adults 18 years and older). These ratios were calculated by dividing body surface areas by corresponding body weights for the 401 individuals analyzed by Gehan and George (1970) and summarized by U.S. EPA (1985). Distributions of SA/BW ratios were developed and summary statistics were calculated for each of the three age groups and the combined data set. Summary statistics for these populations are presented in Table 6-9. The shapes of these SA/BW distributions were determined using D'Agostino's test. The results indicate that the SA/BW ratios for infants are lognormally distributed and the SA/BW ratios for adults and all ages combined are normally distributed (Figure 6-2). SA/BW ratios for children were neither normally nor lognormally distributed. According to Phillips et al. (1993), SA/BW ratios should be used to calculate LADDs by replacing the body surface area factor in the numerator of the LADD equation with the SA/BW ratio and eliminating the body weight factor in the denominator of the LADD equation. The effect of gender and age on SA/BW distribution was also analyzed by classifying the 401 observations by gender and age. Statistical analyses indicated no significant differences between SA/BW ratios for males and females. SA/BW ratios were found to decrease with increasing age. 6.2.4. Relevant Surface Area Studies Murray and Burmaster (i992} -Estimated Distributions for Total Body Surface Area of Men and Women in the United States -In this study, distributions of total body surface area for men and women ages 18 to 7 4 years were estimated using Monte Carlo simulations based on height and weight distribution data. Four different formulae for estimating body surface area as a function of height and weight were employed: Dubois and Dubois (1916); Boyd (1935); U.S. EPA (1985); and Costeff (1966). The formulae of Dubois and Dubois (1916); Boyd (1935); and U.S. EPA (1985) are based on height and weight. They are discussed in Appendix 6A. The formula developed by Costeff (1966) is based on 220 observations that estimate body surface area based on weight only. Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 6 -Dennal This formula is: SA= 4W+7/W+90 where: SA = Surface Area (m2); and W =Weight (kg). (Eqn. 6-2) Formulae were compared and the effect of the correlation between height and weight o.n the body surface area distribution was analyzed. Monte Carlo simulations were conducted to estimate body surface area distributions. They were based on the bivariate distributions estimated by Brainard and Burmaster (1992) for height and natural logarithm of weight and the formulae described above. A total of 5,000 rapdom samples each for men and women were selected from the two correlated bivariate distributions. Body surface area calculations were made for each -sample, and for each formula, resulting in body surface area distributions. Murray and Burmaster (1992), found that the body surface area frequency distributions were similar for the four models (Table 6-10). Using the U.S. EPA (1985) formula, the median surface area values were calculated to be 1.96 m2 for men and 1.69 m2 for women. The median value for women is identical to that generated by U.S. EPA (1985) but differs for men by approximately 1 percent. Body surface area was found to have lognormal distributions for both men and women (Figure 6-3). It was also found that assuming correlation between height and weight influences the final distribution by less than 1 percent. ** AIHC (1994) -Exposure Factors Sourcebook -The Exposure Facfors Sourcebook (AIHC, 1994) provides similar body surface area data as presented here. Consistent with this document, average and percentile values are presented on the basis of age and gender. In addition, the Sourcebook presents point estimates of exposed skin surface*
areas for various scenarios on the basis of several published studies. Finally, the Sourcebook presents probability distributions based on U.S. EPA (1989) and as derived by Thompson and Burmaster (1991); Versar (1991); and Brorby and Finley (1993). For each distribution, the @Risk formula is provided for direct use in the @Risk simulation software (Palisade, 1992). The organization of this document, makes it very convenient to use in support of Monte Carlo analysis. The reviews of the supporting studies are very brief with little analysis of their strengths and weaknesses. The Sourcebook has been classified as a relevant rather than key study because it is not the primary source for the data used to make recommendations in this document. The Sourcebook is very similar to this document in the sense that it summarizes exposure factor data and recommends Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 6 -Dennal values. As sucti, it is clearly relevant as an alternative information source on body surface area as well as other exposure factors. 6.2.5. Application of Body Surface Area Data In many settings, it is likely that only certain parts of the body are exposed. All body parts that come in contact with a chemical must be c;;onsidered to estimate the total surface area of the body exposed. The data in Table 6-4 may be used to estimate the total surface area of the particular body part(s). For example, to assess exposure to a chemical in a cleaning product for which only the hands are exposed, surface area values for hands from Table 6-4 can be used. For exposure to both hands and arms, mean surface areas for these parts from Table 6-4 may be summed to estimate the total surface area exposed. The mean surface area of these body parts for men and women is as follows: Arms (includes upper arms and forearms) Hands Total area Surface Area (m2) Men Women 0.228 0.084 0.312 0.210 0.075. *0.285 Therefore, the total body part surface area that may be in contact with the chemical in the cleaning product in this example is 0.312 m2 for men and 0.285 m2 for women. A common assumption is that clothing prevents dermal contact and subsequent absorption of contaminants. This assumption may be false in cases where the chemical may be able to penetrate clothing, such as in a fine dust or liquid suspension. Studies using personal patch monitors placed beneath clothing of pesticide workers exposed to fine mists and vapors show that a significant proportion of dermal exposure may occur at anatomical sites covered by clothing (U.S. EPA, 1992b). In addition, it has been demonstrated that a "pumping" effect can occur which causes material to move under loose clothing (U.S. EPA, 1992b). Furthermore, studies have demonstrated that hands cannot be considered to be protected from exposure even if waterproof gloves are worn (U.S. EPA, 1992b). This may be due to contamination to the interior surface of the gloves when donning or removing them during work activities (U.S. EPA, 1992b). Depending on the task, pesticide workers have been shown to experience 12 percent to 43 percent of their total exposure through their hands, approximately 20 percent to 23 percent through their heads and necks, and 36 percent to 64 percent through their torsos and arms, despite the use of protective gloves and clothing (U.S. EPA, 1992b). Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 6 -Dermal* For swimming and bathing scenarios, past exposure assessments have assumed that 75 percent to 100 percent of the skin surface is exposed (U.S. EPA, 1992b). As shown in Table 6-4, total adult body surface areas can vary from about 17,000 ch12 to 23,000 cm2. The mean is reported as approximately 20,000 cm2* For default purposes, adult body surface areas of 20,000 cm2 (central estimate) to 23,000 cm2 (upper percentile) are recommended in U.S. EPA (1992b). Tables 6-2 and6-3 can also be used when the default values are not preferred. Central and upper-percentile values for children should be derived from Table 6-6 or 6-7. Unlike exposure to liquids, clothing may or may not be effective in limiting the extent of exposure to soil. The 1989 Exposure Factors Handbook presented two adult clothing scenarios for outdoor activities (U.S. EPA, 1989): Central tendency mid range: Individual wears long sleeve shirt, pants, and shoes. The exposed skin surface is limited to the head and hands (2;000 *cm2). Upper percentile: Individual wears a short sleeve shirt, shorts, and shoes. The exposed skin surface is limited to the head, hands, forearms, and lower legs (5,300 cm2). The clothing scenarios presented above, suggest that roughly 10 percent to 25 percent . of the skin area may be exposed to soil. Since some studies have suggested that exposure can occur under clothing, the upper end of this range was selected in Dermal Exposure Assessment: Principles and Applications (U.S. EPA, 1992b) for deriving defaults. Thus, taking 25 percent of the total body surface area results in defaults for adults of 5,000 cm2 to 5,800 cm2* These values were obtained from the body surface areas in Table 6-2 after rounding to 20,000 cm2 and 23,000 cm2, respectively. The range of defaults for children can be derived by multiplying the 50th and 95th percentiles by 0.25 for the ages of interest. When addressing soil contact exposures, assessors may want to refine estimates of surface area exposed on the basis of seasonal conditions. For example,*in moderate *climates, it may be reasonable to assume that 5 percent of the skin is exposed during the winter, 10 percent during the spring and fall, and 25 percent during the summer. The previous dis_cussion, has presented information about the area of skin exposed to soil. These estimates of exposed skin area should be useful to assessors using the
traditional approach of multiplying the soil adherence factor by exposed skin area to estimate the total amount of soil on skin. The next section presents soil adherence data specific to activity and body part and is designed to be combined with the total surface area of that body part; No reduction of body part area is made for clothing coverage using Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 6 -Dennal this approach. Thus, assessors who adopt this approach, should not use the defaults presented above for soil exposed skin area. Rather, they should use Table 6-4 to obtain total surface areas of specific body parts. See detailed discussion below. 6.3. SOIL ADHERENCE TO SKIN 6.3.1. Background Soil adherence to the surface of the skin is a required parameter to calculate dermal dose when the exposure scenario involves dermal contact with a chemical in soil. A number of studies have attempted to determine the magnitude of dermal soil adherence. These studies are described in detail in U.S. EPA (1992b). This section summarizes recent studies that estimate soil adherence to skin for use as exposure facto.rs. 6.3.2. Key Soil Adherence to Skin Studies Kissel et al. {1996a) -Factors Affecting Soil Adherence to Skin in Hand-Press Trials: Investigation of Soil Contact and Skin Coverage -Kissel et al. (1996a) conducted soil adherence experiments using five soil types (descriptor) obtained locally in the Seattle, Washington, area: sand (211 ), loamy sand (CP), loamy sand (85), sandy loam (228), and silt loam (72). All soils were analyzed by hydrometer (settling velocity) to determine composition.* Clay contents ranged from 0.5 to 7.0 percent. Organic carbon content, determined by combustion, ranged from 0.7 to 4.6 percent. Soils were dry sieved to obtain particle size ranges of <150, 150-250, and >250 µm. For each soil type, the amount of soil adhering to an adult female hand, using both sieved and unsieved soils, was determined by measuring the difference in.soil sample weight before and after the hand was pressed 'into a pan containing the test soil. Loadings were estimated by dividing the recovered soil mass by total hand area, although loading occurred primarily on only one side of the hand. Results showed that generally, soil adherence to hands could be directly correlated with moisture content, inversely correlated with particle size, and independent of clay content or organic carbon content. Kissel et *al. {1996b) -Field Measurement of Dermal Soil Loading Attributable to Various Activities: Implications for Exposure Assessment -Further experiments were conducted by Kissel et al. ( 1996b) to estimate soil adherence associated with various indoor and outdoor activities: greenhouse gardening, tae kwon do karate, soccer, rugby, reed gathering, irrigation installation, truck farming, and playing in mud. A summary of field studies by activity, gender, age, field conditions, and clothing worn is presented in Table 6-11. Subjects' body surfaces (forearms, hands, lower legs in all cases, faces, and/or feet; pairs in some cases) were washed before and after monitored activities. Paired samples were pooled into single ones. Mass recovered was converted to loading Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 6 -Dennal using allometric models of surface area. These data are presented in Table 6-12. Results presented are based on direct measurement of soil loading on the surfaces of skin before and after occupational and recreational activities that may be expected to have soil contact (Kissel et al., 1996b). 6.3.3. Relevant Soil Adherence to Skin Studies Lepow et al. (1975) -Investigations into Sources of Lead in the Environment of Urban Children -This study was conducted to identify the behavioral and environmental factors contributing to elevated lead levels in ten preschool children. The study was performed over 6 to 25 months. Samples of dirt from the hands of subjects were collected during the course of play around the areas where they lived. Preweighed self-adhesive labels were used to sample a standard area on the palm of the hands of 16 male and female children. The labels were* pressed on a single area, often pressed several times, to obtain an adequate sample. In the laboratory, labels were equilibrated in a desiccant cabinet for 24 hours (comparable to the preweighed desiccation), then the total weight was recorded. The mean weight of dirt from the 22 hand sample labels was 11 mg. This corresponds to 0.51 mg/cm2* Lepow et al. (1975) reported that this amount (11 mg) represented only a small fraction (percent not specified) of the total amount of surface dirt present on the hands, because much of the dirt may be trapped in skin folds and. creases or there may be a patchy distribution of dirt on hands. Roets et al. (1980} -Exposure to Lead by the Oral and the Pulmonary Routes of Children Living in the Vicinity of a Primary Lead Smelter -Roels et al. (1980) examined blood lead levels among 661 children, 9 to 14 years old, who lived in the vicinity of a large lead smelter in Brussels, Belgium. During five different study periods, levels were assessed by rinsing the childrens' hands in 500 ml dilute nitric acid.* The amount of lead on the hands was divided by the concentration of lead in soil to estimate the amount of soil adhering to the hands. The mean soil amount adhering to the hands was 0.159 grams. Que Hee et al. (1985) -Evolution of. Efficient Methods to Sample Lead Sources, Such as House Oust and Hand Oust, in the Homes of Children -Que Hee et al. (1985) used soil having particle sizes ranging from :<> 44 to 833 µm diameters, fractionated into six size ranges, to estimate the amount that adhered to the palm of the hand that are assumed to be approximately 160 cm2 (test subject with an average total body surface area of 16,000 cm2 and a total hand surface area of 400 cm2). The amount of soil that adhered to skin was determined by applying approximately 5 g of soil for each size fraction, removing excess soil by shaking the hands, and then measuring the difference iri weight before and after application. Several assumptions were made to apply these results to other soil types and exposure scenarios: (a) the soil is composed of particles of the indicated diameters; (b) all soil types and particle sizes adhere to the skin to the degree observed . Exposure Factors Handbook August 1997 Volume I -General Fai:tors Chapter 6 -Dennal in this study; and an equivalent weight of particles of any diameter adhere to the same surface area of skin. On average, 31.2 mg of soil adhered to the palm of the hand. Driver et al. (1989} -Soil Adherence to Human Skin -Driver et al. ( 1989) conducted soil adherence experiments using various soil types collected from sites in Virginia. A total of five soil types were collected: Hyde, Chapanoke, Panorama, Jackland, and Montalto. Both top soils and subsoils were collected for each soil type. The soils were also characterized by cation exchange capacity, organic content, clay mineralogy, and particle size distribution. The soils were dry sieved to obtain particle sizes of s:250 µm and s: 150 µm. For each soil type, the amount of soil adhering to adult male hands, using both sieved and unsieved soils, was determined gravimetrically (i.e., measuring the difference in soil sample weight before and after.soil application to the hands). An attempt was made to measure only the minima.I or "monolayer" of soil adhering to the hands. This was done by mixing a pre-weighed amount of soil over the entire surface area of the hands for a period of approximate1y*30 seconds, followed by removal of excess soil by gently rubbing the hands together after contact with the soil. Excess soil that was removed from the hands was collected, weighed,. and compared to the original soil sample* weight. The authors measured average adherence of 1.40 mg/cm2 for particle sizes less than 150 µm, 0.95 mg/cm2 for particle sizes less than 250 µm, and 0.58 mg/cm2 for unsieved soils. Analysis of variance statistics showed that the most important factor affecting adherence variability was particle size (p < 0.001 ). The next mo.st important factor is soil type and subtype (p < 0.001 ). The interaction of soil type and particle size was also significant, but at a lower significance level (p < 0.01 ). Driver et al. ( 1989) found statistically significant increases in soil adherence with
decreasing particle size; whereas, Que Hee et al. (1985) found relatively small changes with changes in particle size. The amount of soil adherence found by Driver et al. (1989) was greater than that reported by Que Hee et al. (1985). Sedman (1989) -The Development of Applied Action Levels for Soil Contact: A Scenario for the Exposure of Humans to Soil in a Residential Setting -Sedman (1989) used the estimate from Roels et al. (1980), 0.159 g, and the average surface area of the hand of an 11 year old, 307 cm2 to estimate the amount of soil adhering per unit area of skin to be 0.9 mg/cm2* This assumed that approximately 60 percent ( 185 cm2) of the lead on the hands was recovered by the method employed by Roels et al. (1980). Sedman (1989) used estimates from Lepow et al. (1975), Roels et al. (1980), and Que Hee et al. (1985) to develop a maximum soil load that could occur on the skin. A rounded arithmetic mean of 0.5 mg/cm2 was calculated from these three. studies. According to Sedman (1989), this was near the maximum load of soil that could occur on Exposure Factors Handbook August 1997

Volume I -General Factors Chapter 6 -Dennal the skin but it is unlikely that most skin surfaces would be covered with this amount of soil (Sedman, 1989). Yang et al. (1989) -In vitro and In vivo Percutaneous Absorption of Benzo[a]pyrene from Petroleum Crude -Fortified Soil in the Rat -Yang et al. (1989) evaluated the percutaneous absorption of benzo[a]pyrene (BAP) in petroleum crude oil sorbed on soil using a modified in vitro technique. This method was used in preliminary experiments to determine the minimum amount of soil adhering to the skin of rats. Based on these results, percutaneous absorption experiments with the crude-sorbed soil were conducted with soil particles of <150 µm only. This particle size was intended to represent the composition of the soil adhering to the skin surface. Approximately 9 mg/cm2 of soil was found to be the minimum amount required for a "monolayer" coverage of the skin surface in both in vitro and in vivo experiments. This value is larger than reports for human skin in the studies of Kissel et al., 1996a,b; Lepow et al., 1975; Roels et al., 1980; and Que Hee et al., 1985. Differences between the rat and human soil adhesion findings may be the result of differences in.rat and human skin texture, the types of soils used, soil moisture content or possibly the methods of measuring soil adhesion (Yang et al., 1989). 6A. RECOMMENDATIONS 6.4.1. Body Surface Area Body surface area estimates are based on direct measurements. Re-analysis of data collected by Boyd (1935) by several investigators (Gehan and George, 1970; U.S. EPA, 1985; Murray and Burmaster, 1992; Phillips et al., 1993} constitutes much of this literature. Methods are highly reproducible and the results* are widely accepted. The representativeness of these data to the general population is somewhat limited since variability due to race or gender have not been systematically addressed: Individual body surface area studies are summarized in Table 6-13 and the recommendations for body surface area are summarized in Table 6-14. Table 6-15 presents the confidence ratings for various aspects of the for body surface area. The U.S. EPA (1985) study is based on generally accepted measurements that enjoy widespread usage, summarizes and compares previous reports in the literature, provides statistical distributions for adults, and provides data for total body surface area and body parts by gender foradults and children. However, the results are based on 401 selected measurements from the original 1, 114 made by Boyd (1935). More than half of the measurements are from children. Therefore, these estimates may be subject to selection bias. and may not be representative of the general population nor specific ethnic groups. Phillips et al. (1993) analyses are based on direct measurement data that provide distributions of body surface area to calculate LADD. The results are consistent with Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 6 -Dennal previous efforts to estimate body surface area. Analyses are based on 401 measurements selected from the original 1, 114 measurements made by Boyd ( 1935) and data were not analyzed for specific body parts. The study by Murray and Burmaster (1992) provides frequency distributions for body surface area for men and women and produces results that are similar to those obtained by the U.S. EPA (1985), but do not provide data for body parts nor can results be applied to children. For most dermal exposure scenarios concerning adults, it is recommended that the body surface areas presented in Table 6-4 be used after determining which body parts will be exposed. Table 6-4 was selected because these data are straightf9rward determinations for most scenarios. However, for _others,* additional considerations may need to be addressed. For example, (1) the type of clothing worn could have a significant effect on the surface area exposed, and (2) climatic conditions will also affect the type of clothing worn and, thus, the skin surface area exposed. Frequency, event, and exposure duration for water activities and soil contact are presented in Activity Patterns, Volume 111,* Chapter 15 of this report. For each parameter, recommended values were derived for average and upper percentile values. Each of these considerations are also discussed in more detail in U.S. EPA (1992b). Data in Tables 6-2 and 6-3 can be used when surface area distributions are preferred. A range of recommended values for estimates of the skin surface area of children may be taken from Tables 6-6 and using the 50th and 95th percentile values for age(s) of concern.

The recommended 50th and 95th percentile values for adult skin surface area provided in U.S. EPA (1992b) are presented in Table 6-16.
6.4.2. Soil Adherence to-skin Table 6-17 summarizes the relevant and key studies addressing soil adherence to skin. Both Lepow et al. (1975) and Roels et al. (1980) monitored typical exposures in children. They attempted to estimate typical exposure by recovery of accumulated soil from hands at specific time intervals. The efficiency of their sample collection methods is not known and may be subject to error. Only children were studied which may limit generalizing these results to adults. Later studies (Que Hee et al., 1985 and Driver et al., 1989) attempted to character_ize both soil properties and sample collection efficiency to estimate adherence of soil to skin. However, the experimental conditions used to expose skin to soil may not reflect typical dermal exposure situations. This provides useful information about the influence of soil characteristics on skin adherence, but the intimate -contact of skin with soil required under the controlled experimental conditions in the studies by Driver et al. (1989) and Que Hee et al. (1985) may have exaggerated the amount of adherence over what typically occurs. Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 6 -Dennal More recently, Kissel et al. (1996a; 1996b) have related dermal adherence to soil characteristics and to specific activities. In all cases, experimental design and measurement methods are straightforward and reproducible, but application of results is limited. Both controlled experiments and field studies are based on a limited number of measurements. Specific situations have been selected to assess soil adherence to skin. Consequently, variation due to individuals, protective clothing, temporal, or s.easonal factors remain to be studied in more.detail. Therefore, caution is required in interpretation and application of these results for exposure assessments. These studies are based on limited data, but suggest:
Soil properties influence adherence. Adherence increases with moisture content, decreases with particle size, but is relatively unaffected by clay or organic carbon content.
Adherence levels vary considerably across different parts of the body. The highest levels were found on common contact points such as hands, knees, and elbows; the
least was detected on the face ..
Adherence levels vary with activity. In general, the highest levels of soil adherence were seen in outdoor workers such as farmers and irrigation system installers, followed by outdoor recreation, and gardening activities. Very high adherence levels were seen in individuals contacting wet soils such as might occur during wading or other shore area recreational activities. In consideration, of these general observations and the recent data from Kissel et al. (1996a, 1996b), changes are needed from past EPA recommendations which used one adherence value to represent all soils, body parts, and activities. One approach would be to select the activity from Table 6-11 which best represents the exposure scenario of co*ncern and use the corresponding adherence value from Table 6-12. Although this approach represents an improvement, it still has shortcomings. For example, it is difficult to decide which activity in Table 6-12 is most representative of a typical residential setting involving a variety of activities. It may be useful to combine these activities into general classes of low, moderate, .and high contact. In the future, it may be possible to combine activity-specific soil adherence estimates with survey-specific soil adherence estimates with* survey-derived data on activity frequency and duration to develop overall average soil contact rates. EPA is sponsoring research to develop such an approach. As this information becomes availble, updated recommendations will be issued: Table 6-12 provides the best estimates available on activity-specific adherence values, but are based on limited data. Therefore, they have a high *degree of uncertainty Exposure Factors Handbook August 1997 Volume I -General Factors. Chapter 6 -Dermal such that considerable judgment must be used when selecting them for an assessment. The confidence ratings for various aspects of this recommendation are summarized in Table 6-18. Insufficient data are available to develop a distribution or a probability function for soil loadings. Past EPA guidance has recommended assuming that soil exposure occurs primarily to exposed body surfaces and used typical clothing scenarios to derive estimates of exposed skin area. The approach recommended above for estimating soil adherence addresses this issue in a different manner. This change was motivated by two developments. First, increased acceptance that soil and dust particles can get under clothing and be deposited on skin. Second, recent studies of soil adherence have measured soil on entire body parts (whether or not they were covered by clothing) and averaged the amount of soil adhering to skin over the area of entire body part. The soil adherence levels resulting from these new studies must be combined with the surface area of the entire body part (not merely unclothed surface area) to estimate the amount of contaminant on skin. An important caveat, however, is that this approach assumes that clothing in the exposure scenario of interest matches the clothing in the studies used to derive these adherence levels such that the same degree of protection provided by clothing can be assumed in both cases. If clothing differs significantly between the studies reported here and the exposure scenarios under investigation, considerable judgment is needed to adjust either the adherence level or surface area assumption: The dermal adherence value represents the amount of soil on the skin at the. time of . measurement. Assuming that the amount measured on the skin represents its accumulation *between washings and that people wash at least once per day, these adherence values can be interpreted as daily contact rates (U.S. EPA, 1992b). However, this is not recommended because the residence time of soils on skin has not been studied. Instead, it is recommended that these adherence values be interpreted on an event basis (U.S. EPA, 1992b). Exposure Factors Handbook August 1997 Volume I -General Factors Appendix 6A APPENDIX GA FORMULAEFORTOTALBODVSURFACEAREA Exposure Factors Handbook August 1997 Volume I -General Factors Appendix 6A APPENDIX GA FORMULAE FOR TOTAL BODY SURFACE AREA Most formulae for estimating surface area (SA), relate height to weight to surface area. The following formula was proposed by Gehan and George (1970): SA= KW213 where: SA = surface area in square meters; W = weight in kg; and K = constant. (Eq*n. 6A-1) While the above equation has been criticized because human bodies have different specific gravities and because the surface area per unit volume differs for individuals with different body builds, it gives a reasonably good estimate of surface area. A formula published in 1916 that still finds wide acceptance and use is that of DuBois and DuBois. Their model can be written:
SA ' a H 81 W 82 . 0 where: SA = surface area in square meters; H = height in centimeters; and W = weight in kg. (Eqn. 6A-2) . The values of a0 (0.007182), a1 (0.725), and a2 (0.425) were estimated from a sample of only nine individuals for whom surface area was directly measured. Boyd (f935) stated that the Dubois formula was considered a reasonably adequate substitute for measuring surface area. Nomograms for determining surface area from height and mass presented in Volume I of the Geigy Scientific Tables (1981) are based on the DuBois and DuBois formula. In addition, a computerized literature search Exposure Factors Handbook August 1997 Volume I -General Factors Appendix 6A conducted for this report identified several articles written in the last 10 years in which the DuBois and DuBois formula was used to estimate body surface area. Boyd (1935) developed new constants for the DuBois and DuBois model based on 231 direct measurements of body surface area found in the literature. These data were limited to measurements of surface area by coating methods (122 cases), surface integration (93 cases), and triangulation (16 cases). The subjects were Caucasians of normal body build for whom data on weight, height, and age (except for exact age of adults) were complete. Resulting values for the constants in the DuBois and DuBois model were a0 = 0.01787, a1 = 0.500, and a2 = 0.4838. Boyd also developed a formula based exclusively on weight, which was inferior to the DuBois and DuBois formula based on height and weight. Gehan and George (1970) proposed another set of constants for the DuBois and DuBois model. The constants were based on a total of 401 direct measurements of surface height, and weight of all postnatal subjects listed in Boyd (1935). The methods used to measure these subjects were coating ( 163 cases), surface integraUon. (222 cases), and triangulation (16 cases). Gehan and George (1970) used a least-squares method to identify the values of the constants. The values of the constants chosen are those that minimize the sum of the squared percentage errors of the predicted values of surface area. This approach was used because the importance of an error of 0.1 square meter depends on the surface area of the individual. Gehan and George (1970) used the 401 observations summarized in Boyd (1935) in the least-squares method. The following estimates of the constants were obtained: a0 = 0.02350, a1 = 0.42246,. and a2 = 0.51456. Hence, their equation for predicting surface area (SA) is: SA = 0.02350 Ho.42246 wo.s1456 or in logarithmic form: In SA= -3.75080 + 0.42246 In H + 0.51456 In W where: SA = surface area in square meters; H = height in centimeters; and W = weight in kg. (Eqn. 6A-3) (Eqn. This prediction explains more than 99 percent1 of the variations in surface area among the 401 individuals measured (Gehan and George, 1970). Exposure Factors Handbook August 1997 Volume 1-Generai'Fai:tors Appendix 6A The equation proposed by Gehan and George (1970) was determined by the U.S. EPA (1985) as the best choice for estimating total body surface area. However, _.the paper by Gehan and George gave insufficient information to estimate the standard error about the regression. Therefore, the 401 direct measurements of children and adults (i.e., Boyd, 1935) were reanalyzed in U.S. EPA (1985) using the formula of Dubois and Dubois (1916) and the Statistical Processing System (SPS) software package to obtai.n the standard error. The Dubois and Dubois (1916) formula uses weight and height as independent variables to predict total body surface area (SA), and can be written as: SA = a0 Ha1 w.a2 e. I I I I (Eqn. 6A-5) or in logarithmic form: (Eqn. 6A-6) where: Sai = surface area of the i-th individual (m2); Hi = height of the i-th individual (cm); Wi = weight of the i-th individual (kg); a0, a1, and a2 = parameters to be estimated; and ei = a random error term with mean zero and constant variance. Using the least squares procedure for the 401 observations, the following parameter estimates and their standard errors were obtained: a0 = -3. 73 (0.18), a1 = 0.417 (0.054 ), a2 = 0.517 (0.022) The model is then: SA= 0.0239 H0.417 W0*517 (Eqn. 6A-7) or in logarithmic form: In SA= -3.73 + 0.417 In H + 0.517 In W (Eqn. 6A-:8) with a standard error about the regression of 0.0037 4. This model explains more than 99 percent of the total variation in surface area among the observations,* and is identical to two significant figures with the model developed by Gehan and George (1970). Exposure Factors Handbook August 1997 Volume I -General Factors Appendix 6A When natural logarithms of the measured surface areas are plotted against natural logarithms of the surface predicted by the equation, the observed surface areas are symmetrically distributed around a line of perfect fit, with only a few large percentage deviations. Only five subjects differed from the measured value by 25 percent or more. Because each of the five subjects weighed less than 13 pounds, the amount of difference was small. Eighteen estimates differed from measurements by 15 to 24 percent. Of these, 12 weighed less than 15 pounds each, 1 was overweight (5 feet 7 inches, 172 pounds), 1 was very thin ( 4 feet 11 inches, 78 pounds), and 4 were of average build. Since the same observer measured surface area for these 4 subjects, the possibility of some bias in measured values cannot be discounted (Gehan and George 1970).
Gehan and George (1970) also considered separate constants for different age groups: less than 5 years old, 5 years old to less than 20 years old, and greater than 20 years old. The different values for the constants are presented below: Table 6A-1. Estimated Parameter Values for Different Age Intervals Age Number aa a1 az group of persons . All ages 401 0.02350 0.42246 0.51456 <5 years old 229 0.02667 0.38217 0.53937 2 5 -<20 years old 42 0.03050 0.35129 0.54375 2 20 years old 1 30 0.01545 0.54468 0.46336' The surface areas estimated using the parameter values for all ages were compared to surface areas estimated by the values for each age group for subjects at the 3rd, 50th, and 97th percentiles of weight and height. Nearly all differences in "surface area estimates were less than 0.01 square meter, and the largest difference was 0.03 m2 for an 18-year-old at the 97th percentile. The authors concluded that there is no advantage in using separate values of a0, a1, and a2 by age interval. Haycock et al. (1978) without knowledge of the work by Gehan and George (1970), developed values for the parameters a0, a1, and a2 for the DuBois and DuBois model. Their interest in making the DuBois and DuBois model more accurate resulted Exposure Factors Handbook August 1997 Volume I -General Factors Appendix 6A from their work in pediatrics and the fact that DuBois and DuBois (1916) included only one child in their study group, a severely undernourished girl who weighed only 13.8 pounds at age 21 months. Haycock et al. (1978) used their own geometric method for estimating surface area from 34 body measurements for 81 subjects.* Their study included newborn infants ( 10 cases), infants ( 12 cases); children ( 40 cases), and adult members of the medical and secretarial staffs of 2 hospitals (19 cases). The subjects all had grossly normal body structure, but the sample included subjects of widely varying physique ranging from thin to obese. Black, Hispanic, and white children were included in their sample. The values of the model parameters were solved for the relationship between surface area and height and weight by multiple regression analysis. The least squares best fit for this equation yielded the following values for the three coefficients: a0 = 0.024265, a1 = 0.3964, and a2 = 0.5378. The result was the following equation for estimating surface area: SA= 0.024265 Ho.3964 wo.s31s (Eqn. 6A-9) expressed logarithmically as: In SA= In 0.024265 + 0.3964 In H + 0.5378 In W (Eqn. 6A-10) The coefficients for this equation agree remarkably with those obtained by Gehan and George (1970) for 401 measurements. George et al. (1979) agree that a model more complex than the model of DuBois and DuBois for estimating surface area is unnecessary. Based on samples of direct measurements by Boyd (1935) and Gehan and George (1970), and samples of geometric estimates by Haycock et al. (1978), these authors have obtained parameters for the DuBois and DuBois model that are different than those originally postulated in 1916. The DuBois and DuBois model can be written logarithmically as: In SA = In a0 + a1 In H + a2 In W (Eqn. 6A-11) Exposure Factors Handbook August 1997 Volume I -General Factors Appendix 6A The values for a0, a1, and a2 obtained by the various authors discussed in this section are presented to follow:
Table 6A-2. Summary of Surface Area Parameter Values for the DuBois and DuBois Model Author Number ao a1 a2 (year) of persons DuBois and DuBois (1916) 9 0.007184 0.725 0.425 . Boyd (1935) 231 0.01787 0.500 0.4838 Gehan and George (1970) 401 0.02350 0.42246 0.51456 Haycock et al. (1978} 81 0.024265 0.3964 0.5378 The agreement between the model parameters estimated by Gehan and George (1970) and Haycock et al. (1978) is remarkable in view of the fact that Haycock et al. (1978) were unaware of the previous work. Haycock *et al. (1978) used an entirely different set of subjects, and used geometric estimates of surface area rather than direct measurements. It has been determined that the Gehan and George model is the formula of choice for estimating total surface area of the body since it is based on the largest number of direct measurements. Nomograms
Sendroy and Cecchini ( 1954) proposed a graphical* method whereby surface area could be read from a diagram relating height and weight to surface area. However, they do not give an explicit model for calculating surface area. The graph was developed empirically based on 252 cases, 127 of which were from the 401 direct measurements reported by Boyd ( 1935). In the other 125 cases the surface area was estimated using the linear method of DuBois and DuBois (1916). Because the Sendroy and Cecchini method is graphical, it is inherently less precise and less accurate than
the formulae of other authors discussed above. Exposure Factors Handbook August 1997 Table 6-1. Summary of Equation Parameters for Calculating Adult Body Surface Area Equation for surface areas (m') Bodv Part N ao W"' H"' p R' S.E. Head Female 57 0.0256 0.124 0.189 0.01 0.302 0.00678 Male 32 0.0492 0.339 -0.0950 0.01 0.222 0.0202 Trunk Female 57 0.188 0.647 -0.304 0.001 0.877 0.00567 Male 32 0.0240 0.808 -0.0131 0.001 0.894 0.0118 Extremities emale 57 0.0288 0.341 0.175 0.001 0.526 0.00833 Male 48 0.00329 0.466 0.524 0.001 0.821 0.0101 Arms Female 13 0.00223 0.201 0.748 0.01 0.731 0.00996 Male 32 0.00111 0.616 0.561 0.001 0.892 0.0177 Upper Arms Male 6 8.70 0.741 -1.40 0.25 0.576 0.0387 Forearms Male 6 0.326 0.858 -0.895 0.05 0.897 0.0207 Hands Female 12b 0.0131 0.412 0.0274 0.1 0.447 0.0172 Male 32 0.0257 0.573 -0.218 0.001 0.575 0.0187 Lower Extremities' 105 0.00286 0.458 0.696 0.001 0.802 0.00633 Legs 45 0.00240 0.542 0.626 0.001 0.780 0.0130 Thighs 45 0.00352 0.629 0.379 0.001 0.739 0.0149 Lower legs 45 0.000276 0.416 0.973 0.001 0.727 0.0149 Feet 45 0.000618 0.372 0.725 0.001 0.651 0.0147 a SA = a0 W81 H82 w = Weight in kilograms; H = Height in centimeters; P = Level of significance; R2 =Coefficient of determination; SA = Surface Area; S.E. = Standard error; N = Number of observations b One observation for a female whose body weight exceeded the 95 percentile was not used. c Although two separate regressions were marginally indicated by the F test, pooling was done for consistency with individual components of lower extremities. Source: U.S. EPA, 1985.

Table 6-2. Surface Area of Adult Males in Square Meters Percentile Bod art 5 10 15 25 50 75 85 90 95 S.E.8 Total 1.66 1.72 1.76 1.82 1.94 2.07 2.14 2.20 2.28 0.00374 Head 0.119 0.121 0.123 0.124 0.130 0.135 0.138 0.140 0.143 0.0202 Trunkb 0.591 0.622 0.643 0.674 0.739 0.807 0.851 0.883 0.935' 0.0118 Upper extremities 0.321 0.332 0.340 0.350 0.372 0.395 0.408 0.418 0.432' 0.00101 Arms 0.241 0.252 0.259 0.270 0.291 0.314' 0.328' 0.339' 0.354' 0.00387 Forearms 0.106 0.111 0.115 0.121 0.131 0.144' 0.151' 0.157' 0.166' 0.0207 Hands 0.085 0.088 0.090 0.093 0.099 0.105 0.109 0.112 0.117 0.0187 Lower extremities 0.653 0.676 0.692 0.715 0.761 0.810 0.838 0.858 0.888' 0.00633 Legs 0.539 0.561 0.576 0.597 0.640 0.686' 0.714' 0.734' 0.762' 0.0130 Thighs 0.318 0.331 0.341 0.354 0.382 0.411' 0.429' 0.443' 0.463' 0.0149 Lower legs 0.218 0.226 0.232 0.240 0.256 0.272 0.282 0.288 0.299 0.0149 Feet 0.114 0.118 0.120 0.124 0.131 0.138 0.142 0.145 0.149 0.0147 Standard error for the 5-95 percentile of each body part. Trunk includes neck. Percentile estimates exceed the maximum measured values upon which the equations are based. Source: U.S. EPA 1985. Table 6-3. Surface Area of Adult Females in Square Meters Percentile Body part 5 10 15 25 50 75 85 90 95 S.E.* Total 1.45 1.49 1.53 1.58 1.69' 1.82 1.91 1.98 2.09 0.00374 Head 0.106 0.107 0.108 0.109 0.111 0.113 0.114 0.115 0.117 0.00678 Trunkb 0.490 0.507 0.518 0.538 0.579 0.636 0.677 0.704 0.752 0.00567 Upper extremities 0.260 0.265 0.269 0.274 0.287 0.301 0.311 0.318 0.329 0.00833 Arms 0.210 0.214 0.217 0.221 0.230 0.238' 0.243' 0.247' 0.253' 0.00996 Hands 0.0730 0.0746 0.0757 0.0777 0.0817 Q.0868 Q.0903 p.0927 0.0966' 0.0172 Lower extremities 0.564 0.582 0.595 0.615 0.657 0.796 0.00633 Legs 0.460 0.477 0.488 0.507 0.546 0.704 0.736 0.757 0.683' 0.0130 Thighs 0.271 0.281 0.289 0.300 0.326 0.592 0.623 0.645 0.421' 0.0149 Lower legs 0.186 0.192 0.197 0.204 0.218 0.357 0.379 0.394 0.261 0.0149 Feet 0.100 0.103 0.105 0.108 0.114 0.233 0.243 0.249 0.134 0.0147 0.121 0.126 0.129 a Standard error forthe 5-95 percentile of each body part. b Trunk includes neck. ' Percentile estimates exceed the maximum measured values upon which the equations are based. Source: U.S. EPA, 1985. Table 6-4. Surface Area bv Body Part for Adults (m2l Men Women Body part (sd)b (sd) N* Mean Min. -Max. N Mean Min. -Max. Head 32 0.118 (0.0160) 0.090 -0.161 57 0.110 (0.00625) 0.0953 -0.127 Trunk 32 0.569 0.306 -0.893 57 0.542 (0.0712) 0.437 -0.867 {Incl. Neck) Upper extremities 48 0.319 (0.0461) 0.169 -0.429 57 0.276 (0.0241) 0.215 -0.333 Arms 32 0.228 (0.0374)" 0.109 -0.292 13 0.210 (0.0129) 0.193 -0.235 Upper arms 6 0.143 (0.0143) 0.122 -0.156 ------Forearms 6 0.114 (0.0127) 0.0945 -136 -----Hands 32 0.084 (0:0127) 0.0596 -0.113 12 0.0746 (0.00510) 0.0639 0.0824 Lower extremities 48 0.636 (0.0994) 0.283 -0.868 57 0.626 (0.0675) 0.492 -0.809 Legs 32 0.505 (0.0885) 0.221 -0.656. 13 0.488 (0.0515) 0.423 -0.585 Thighs 32 0.198 (0.1470) 0.128 -0.403 13 0.258 (0.0333) 0.258 -0.360 Lower legs 32 0.207 (0.0379) 0.093 -0.296 13 0.194 (0.0240) 0.165 -0.229 Feet

32 0.112 (0.0177) 0.0611 -0.156 13 0.0975 (0.00903) 0.0834 -0.115 TOTAL 1.94' (0.00374)' 1.66 -2.28' 1.69' (0.00374)' 1.45 -2.09'
number of observations. b standard deviation. ' median (see Table 6-2). ' standard error. 'percentiles (5th -95th). Source: Adapted from U.S. EPA, 1985.

Table 6-5. PercentaQe of Total Body Surface Area by Part for Adults Men Women Body part N" Mean (s.d.)b Min. -Max. N Mean (s.d.) Min. -Max. Head 32 7.8 (1.0) 6.1 -10.6 57 7.1 (0.6) 5.6 -8.1 Trunk 32 35.9 (2.1) 30.5 -41.4 57 34.8 (1.9) 32.8 -41.7 Upper extremities 48 18.8 (1.1) 16.4 -21.0 57 17.9 (0.9) 15.6 -19.9 Arms 32 14.1 (0.9) 12.5 -15.5 13 14.0 (0.6) 12.4 -14.8 Upper arms 6 7.4 (0.5) 6.7 -8.1 ------Forearms 6 5.9 (0.3) 5.4 -6.3 -----Hands 32 5.2 (0.5) 4.6 -7.0 12 5.1 (0.3) 4.4 5.4 Lower extremities 48 37.5 (1.9) 33.3 -41.2 57 40.3 (1.6) 36.0 -43.2 Legs 32 31.2 (1.6) 26.1 -33.4 13 32.4 (1.6) 29.8 -35.3 Thighs 32 18.4 (1.2) 15.2 -20.2 13 19.5 (1.1) 18.0 -21.7 Lower legs 32 12.8 (1.0) 11.0 -15.8 13 12.8 (1.0) 11.4 -14.9 Feet 32 7.0 (0.5) 6.0 -7.9 13 6.5 (0.3) 6.0 -7.0 a Number of observations. b Standard deviation. Source: Adapted from U.S. EPA, 1985. Table 6-6. Total Bodv Surface Area of Male Children in Square Meters" Percentile Age (yr)b 5 10 15 25 50 75 85 90 95 2<3. 0.527. 0.544 0.552 0.569 0.603 0.629 0.643 0.661 0.682 3<4 0.585 0.606 0.620 0.636 0,664 0.700 0.719 0.729 0.764 4<5 0.633 0.658 0.673 0.689 0.731 0.771 0,796 0.809 0.845 5<6 0.692 0.721 0.732 0.746 0.793 0.840 0.864 0.895 0.918 6<7 0.757 0.788 0.809 0.821 0.866 0.915 0.957 1.01 1.06 7<8 0.794 0.832 0.848 0.877 0.936 0.993 1.01 1.06 1.11 8<9 0.836 0.897 0.914 0.932 1.00 1.06 1.12 1.17 1.24 9 < 10 0.932 0.966 0.988 1.00 1.07 1.13 1.16 1.25 1.29 10 < 11 1.01 1.04 1.06 1.10 1.18 1.28 1.35 1.40 1.48 11<12 1.00 1.06 1.12 1.16 1.23 1.40 1.47 1.53 1.60 12 < 13 1.11 1.13 1.20 1.25 1.34 1.47 1.52 1.62 1.76 13 < 14 1.20 1.24 1.27 1.30 1.47 1.62 1.67 1.75 1.81 14 < 15 1.33 1.39 1.45 1.51 1.61 1.73 1.78 1.84 1.91 15 < 16 1.45 1.49 1.52 1.60 1.70 1.79 1.84 1.90 2.02 16 < 17 1.55 1.59 1.61 1.66 1.76 1.87 1.98 2.03 2.16 17 < 18 1.54 1.56 1.62 1.69 1.80 1.91 1.96 2.03 2.09 3<6 0.616 0.636 0.649 0.673 0.728 0.785 0.817 0.842 0.876 6<9 0.787 0.814 0.834 0.866 0.931 1.01 1.05 1.09 1.14 9 < 12 0.972 1.00 1.02 1.07 1.16 1.28 1.36 1.42 1.52 12 < 15 1.19 1.24 1.27 1.32 1.49 1.64 1.73 1.77 1.85 15 < 18 1.50 1.55 1.59 1.65 1.75 1.86 1.94 2.01 2.11 a Lack of height measurements for children <2 years in NHANES II precluded calculation of surface areas for this age group. b Estimated values calculated using NHANES II data. Source: U.S. EPA 1985. Table 6-7. Total Bodv Surface Area of Female Children in Square Meters" Percentile Aqe(vd 5 10 15 25 50 75 85 90 95 2<3 0.516 0.532 0.544 0.557 0.579 0.610 0.623 0.637 0.653 3<4 0.555 0.570 0.589 0.607 0.649 0.688 0.707 0.721 0.737 4<5 0.627 0.639 0.649 0.666 0.706 0.758 0.777 0.794 0.820 5<6 0.675 0.700 0.714 0.735 0.779 0.830 0.870 0.902 0.952. 6<7 0.723 0.748 0.770 0.791 0.843 0.914 0.961 0.989 1.03 7<8 0.792 0.808 0.819 0.854 0.917 0.977 1.02 1.06 1.13 8<9 0.863 0.888 0.913 0.932 1.00 1.05 1.08 1.11 1.18 9 < 10 0.897 0.948 0.969 1.01 1.06 1.14 1.22 1.31 1.41 10 < 11 0.981 1.01 1.05 1.10 1.17 1.29 1.34 1.37 1.43 11<12 1.06 1.09 1.12 1.16 1.30 1.40 1.50 1.56 1.62 12 < 13 1.13 1.19 1.24 1.27 1.40 1.51 1.62 1.64 1.70 13 < 14 1.21 1.28 1.32 1.38 1.48 1.59 1.67 1.75 1.86 14 < 15 1.31 1.34 1.39 1.45 1.55 1.66 1.74 1.76 1.88 15 < 16 1.38 1.49 1.43 1.47 1.57 1.67 1.72 1.76 1.83 16 < 17 1.40 1.46 1.48 1.53 1.60 1.69 1.79 1.84 1.91 17 < 18 1.42 1.49 1.51 1.56 1.63 1.73 1.80 1.84 1.94 3<6 0.585 0.610 0.630 0.654 0.711 0.770 0.808 0.831 0.879 6<9 0.754 0.790 0.804 0.845 0.919 1.00 1.04 1.07 1.13 9 < 12 0.957 0.990 1.03 1.06 1.16 1.31 1.38 1.43 1.56 12 < 15 1.21 1.27 1.30 1.37 1.48 1.61 1.68 1.74 1.82 15 < 18 1.40 1.44 1.47 1.51 1.60 1.70 1.76 1.82 1.92 a Lack of height measurements for children <2 years in NHANES II precluded calculation of surface areas for this age. group. b Estimated values calculated using NHANES II data. Source: U.S. EPA 1985. Table 6-8. Percentaoe of Total Bodv Surface Area bv Bodv Part for Children Percent of Total Head Trunk Arms Hands Legs Feet N Aoe lvr\ M:F Mean Min-Max Mean Min-Max Mean Min-Max Mean Min-Max Mean Min-Max Mean Min-Max <1 2:0 18.2 18.2-18.3 35.7 34.8-36.6 13.7 12.4-15.1 5.3 5.21-5.39 20.6 18.2-22.9 6.54 6.49-6.59 1<2 1 :1 16.5 16.5-16.5 35.5 34.5-36.6 13.0 12.8-13.1 5.68 5.57-5.78 23.1 22.1-24.0 6.27 5.84-6.70 2<3 1 :0 14.2 38.5 11.8 5.30 23.2 7.07 3<4 0:5 13.6 13.3-14.0 31.9 29.9-32.8 14.4 14.2-14.7 6.07 5.83-6.32 26.8 26.0-28.6 7.21 6.80-7.88 4<5 1 :3 13.8 "12.1-15.3 31.5 30.5-32.4 14.0 13.0-15.5 5.70 5.15-6.62 27.8 26.0-29.3 7.29 6.91-8.10 5<6 6<7 1 :O 13.1 35.1 13.1 4.71 27.1 6.90 7<8 8<9 9<10 0:2 12.0 11.6-12.5 34.2 33.4-34.9 12.3 11.7-12.8 5.30 5.15-5.44 28.7 28.5-28.8 7.58 7.38-7.77 10 < 11 11 < 12 12 < 13 1:0 8.74 34.7 13.7 5.39 30.5 7.03 13<14 1:0 9.97 32.7 12.1 5.11 32.0 8.02 14<15 15<16 16<17 1:0 7.96 32.7 13.1 5.68 33.6 6.93 17 < 18 1:0 7.58 31.7 17.5 5.13 30.8 7.28 N: Number of subjects, male to female ratios. Source: U.S. EPA 1985. Table 6-9. Descriotive Statistics for Surface Area/BodvWeiaht CSA/BWl Ratios (m2/k!J) Percentiles Range 5 10 25 50 75 90 95 Ane lvrs.\ Mean Min-Max SD' SE' 0-2 0.0641 0.0421-0.1142 0.0114 7.84e-4 0.0470 0.0507 0.0563 0.0617 0.0719 0.0784 0.0846 2.1 -17.9 0.0423 0.0268-0.0670 0.0076 1.05e-3 0.0291 0.0328 0.0376 0.0422 0.0454 0.0501 0.0594 > 18 0.0284 0.0200-0.0351 0.0028 7.68e-6 0.0238 0.0244 0.0270 0.0286 0.0302 0.0316 0.0329 All aaes 0.0489 0.0200-0.1142 0.0187 9.33e-4 0.0253 0.0272 0.0299 0.0495 0.0631 0.0740 0.0788 ' Standard deviation. b Standard error of the mean. Source: Phillios et al. 1993. Table 6-10. Statistical Results for Total Body Surface Area Distributions (m2) Men U.S. EPA . Bovd DuBois and DuBois Costeff

Mean 1.97 1.95 1.94 1.89 Median 1.96 1.94 1.94 -1.89 Mode 1.96 1.91 1.90 1.90 Standard Deviation 0.19 0.18 0.17 0.16 Skewness 0.27 0.26 0.23 0.04 Kurtosis 3.08 3.06 3.02 2.92 Women U.S. EPA Bovd DuBois and DuBois Costeff Mean 1.73 1.71 1.69 1.71 Median 1.69 1.68 1.67 1.68 Mode 1.68 1.62 1.60 1.66 Standard Deviation 0.21 020 0.18 0.21 Skewness 0.92 0.88 0.77 0.69 Kurtosis 4.30 4.21 4.01 3.52 Source: Murrav and Burmaster 1992 Table 6-11. Summarv of Field Studies Event" Activity Mo.nth (hrs) Nb M F Age Conditions Clothing Indoor ITae Kwon Do Feb. 1.5 7 6 1 8-42 Carpeted floor All in longsleeve-long pants martial arts uniform, sleeves rolled back, barefoot Greenhouse Workers Mar. 5.25 2 1 1 31-39 Plant watering.spraying, soil Long pants, elbow length short blending, sterilization
sleeve shirt, no gloves Indoor Kids No. 1 Jan. 2 4 3 1 6-13 Playing on carpeted floor 3 of 4 short pants, 2 of 4 short sleeves, socks, no shoes Indoor Kids No. 2 Feb. 2 6 4 2 3-13 Playing on carpeted floor 5of 6 long pants, 5 of 6 long sleeves, socks, no shoes Indoor Totals 19 14 5 Outdoor Daycare Kids No. 1a Aug. 3.5 6 5 1 1-6.5 Indoors: linoleum surface; 4 of 6 in long pants, 4 of 6 short outdoors: grass, bare earth, sleeves, shoes barked area Daycare Kids No. 1 b Aug. 4 6 5 1 1-6.5 Indoors: linoleum surface; 4 of 6 in long pants, 4 of 6 short outdoors: grass, bare earth, sleeves, no shoes barked area Daycare Kids No.2c Sept. 8 5 4 1 1-4 Indoors, low napped carpeting, 4 of 5 long pants, 3of 5 long linoleum surfaces sleeves, all barefoot for part of the day Daycare Kids No. 3 Nov. 8 4 3 1 1-4.5 Indoors: linoleum surface, All long pants, 3 of 4 long sleeves, outside: grass, bare earth, socks and shoes barked area Soccer No. 1. Nov. 0.67 8 8 0 13-15 Half grass-half bare earth 6 of 8 long sleeves, 4 of 8 long pants, 3 of 4 short pants and shin guards Soccer No. 2 Mar. 1.5 8 0 8 24-34 All-weather field (sand-ground All in short sleeve shirts, shorts, tires) knee socks, shin guards Soccer.No. 3 Nov. 1.5 7 0 7 24-34 All-weather field (sand-ground All in short sleeve shirts, shorts, tires) knee socks, shin guards Groundskeepers No. 1 Mar. 1.5 2 1 1 29-52 Campus grounds, urban* All in long pants, intermittent use of horticulture center, arboretum gloves Groundskeepers No. 2 Mar. 4.25 5 3 2 22-37 Campus grounds.urban All in long pants, intermittent use of horticulture center, arboretum gloves Groun.dskeepers No. 3 Mar. 8 7 5 2 30-62 Campus grounds.urban All in long pants, intermittent use of horticulture center, arboretum gloves Groundskeepers No. 4 Aug. 4.25 7 4 3 22-38 Campus grounds.urban 5 of 7 in short sleeve shirts, horticulture center, arboretum intermittent use of gloves Groundskeepers No. 5 Aug. 8 8 6 2 19-64 Campus grounds.urban 5 of 8 in short sleeve shirts, horticulture center, arboretum intermittent use of gloves Landscape/Rockery June 9 4 3 1 27-43 Digging (manual All long pants, 2 long sleeves, all andmechanical), rock moving socks and boots Irrigation Installers Oct. 3 6 6 0 23-41 Landscaping.surface restoration All in long pants, 3 0(6 short sleeve or sleeveless shirts Gardeners No. 1 Aug. 4 8 1 7 16-35 Weeding, pruning.digging a 6 of 8 long pants, 7 of 8 short trench sleeves, 1 sleeveless, socks, shoes intermittent use of aloves Activity Gardeners No. 2 Rugby No.1 Rugby No. 2 Rugby No. 3 Archeologists Construction Workers Utility Workers No.1 Utility Workers No.2 Equip. Operators No.1 Equip. Operators No.2 Farmers No. 1 Farmers No. 2 Reed Gatherers Kids-in-mud No. 1 Kids-in-mud No. 2 a Event duration b Number of subject Table 6-11. Summarv of Field Studies (continued) Event' Month (hrs) Nb M F Age Conditions Aug. 4 7 2 5 26-52 Weeding, pruning, digging a trench, picking fruit, cleaning Mar. 1.75 8 8 o 20-22 Mixed grass-barewet field Clothing 3 of 7 long pants, 5of 7 shprt sleeves, 1 sleeveless, socks, shoes, no gloves All in short sleeve shirts, shorts, variable sock lengths July 8 8 0 23-33 Grass field (80% oftime) and all-All in shorts, 7 of 8 in short sleeve weather field (mix of gravel, shirts, 6 of 8 in low socks 2 Sept. 2.75 July 11.5 Sept. 8 July 9.5 Aug. 9.5 Aug. 8 Aug. 8 May 2 July 2 Aug. 2 Sept. . 0.17 Sept. 0.33 7 7 7 3 8 8 5 5 sand, and clay) (20% oftime) O 24-30 Compacted mixedgrass and bare earth field 4 16-35 Digging withtrowel, screening dirt, sorting O 21-30 Mixed bare earth and concrete surfaces, dust and debris O 24-45. Cleaning, fixing mains, excavation (backhoe and shovel) 6 6 O 23-44 Cleaning, fixing mains, excavation (backhoe and shovel) 4 4 O 21-54 Earth scraping withheavy machinery, dusty conditions 4 4 O 21-54 Earth scraping withheavy machinery, dusty conditions 4 2 2 39-44 Manual weeding,mechanical cultivation 6 4 2 18-43 Manual weeding,mechanical cultivation 4 0 4 42-67 Tidal flats 6 5 1 9-14 Lake shoreline 6 5 1 9-14 Lake shoreline Outdoor Totals 181 125 56 All short pants, 7 of 8 short or rolled up sleeves, socks, shoes 6 of 7 short pants, all short sleeves, 3 no shoes or socks, 2 sandals 5 of 8 pants,7 of 8 short sleeves, all socks and shoes All long pants,short sleeves, socks, boots, gloves sometimes All long pants, 5 of 6 short sleeves, socks, boots, gloves sometimes All long pants, 3 of 4 short sleeves, socks, boots, 2 of 4 gloves All long pants, 3 of 4 short sleeves, socks, boots, 1 gloves All in long pants, heavy shoes, short sleeve shirts, no gloves 2 of 6 short, 4 of 61ong pants, 1 of 6 long sleeve shirt, no gloves 2 of 4 shortsleeve shirts/knee length pants, all wore shoes All in short sleeve T-shirts, shorts, barefoot All in short sleeveT-shirts, shorts, barefoot c Activities were confined to the house Sources: Kissel et al., 1996b; Holmes et al., 1996 (submitted for publication).

Table 6-12. Geometric Mean and Geometric Standard Deviations of Soil Adherence by Activity and Body ReQion Post-activity Dermal Soil Loadings (mg/cm2) Activity N* Hands Arms Legs Faces Feet Indoor [Tae Kwon Do 7 0.0063 0.0019 0.0020 0.0022 1.9 4.1 2.0 2.1 GreenhouseWorkers 2 0.043 0.0064 0.0015 0.0050 --------Indoor Kids No. 1 4 0.0073 0.0042 0.0041 0.012 1.9 1.9 2.3 1.4 Indoor Kids No. 2 6 0.014 0.0041 0.0031 0.0091 1.5 2.0 1.5 1.7 Daycare Kids No. 1 a 6 0.11 0.026 0.030 0.079 1.9 1.9 1.7 2.4 Daycare Kids No. 1 b 6 0.15 0.031 0.023 0.13 2.1 1.8 1.2 1.4 Daycare Kids No. 2 5 0.073 0.023 0.011 0.044 1.6 1.4 1.4 1.3 Daycare Kids No. 3 4 0.036 0.012 0.014 0.0053 1.3 1.2 3.0 5.1 Outdoor Soccer No. 1 8 0.11 0.011 0.031 0.012 1.8 2.0 3.8 1.5 Soccer No. 2 8 0.035 0.0043 0.014 0.016 3.9 2.2 5.3 1.5 Soccer No. 3 7 0.019 0.0029 0.0081 0.012 1.5 2.2 1.6 1.6 Groundskeepers No. 1 2 0.15 0.005 0.0021 0.018 --------Groundskeepers No. 2 5 0.098 . 0.0021 0.0010 0.010 2.1 2.6 1.5 2.0 Groundskeepers No. 3 7 0.030* 0.0022 0.0009 0.0044 0.0040 2.3 1.9 1.8 2.6 Groundskeepers No. 4 7 0.045 0.014 0.0008 0.0026 0.018 1.9 1.8 1.9 1.6 --Groundskeepers No. 5 8 0.032 0.022 0.0010 0.0039 1.7 2.8 1.4 2.1 Landscape/Rockery 4 0.072 0.030 0.0057 2.1 2.1 1.9 Irrigation Installers 6 0.19 0.018 0.0054 0.0063 1.6 3.2 1.8 1.3 Gardeners No. 1 8 0.20 0.050 0.072 0.058 0.17 1.9 2.1 --1.6 -- Table 6-12. Geometric Mean and Geometric Standard Deviations of Soil Adherence by Activity and Body Region (continued) Post-activity Dermal Soil Loadings (mg/cm2) Activity N" Hands* Arms Legs Faces Feet Gardeners No. 2 7 0.18 0.054 0.022 0.047 0.26 3.4 2.9 2.0 1.6 --Rugby No. 1 8 0.40 0.27 0.36 0.059 1.7 1.6 1.7 2.7 Rugby No. 2 8 0.14 0.11 0.15 0.046. 1.4 1.6 1.6 1.4 Rugby No. 3 7 0.049 0.031 0.057 0.020 1.7 1.3 1.2 1.5 Archeologists 7 0.14 0.041 0.028 0.050 0.24 1.3 1.9 4.1 1.8 1.4 Construction .Workers 8 0.24 0.098 0.066 0.029 1.5 1.5 1.4 1.6 Utility Workers No.1 5 0.32 0.20 0.10 1.7 2.7 1.5 Utility Workers No. 2 6 0.27 0.30 0.10 2.1 1.8 1.5 Equip. Operators No. 1 4 0.26 0.089 0.10 2.5 1.6 1.4 Equip. Operators No. 2 4 0.32 0.27 0.23 1.6 1.4 1.7 Farmers No. 1 4 0.41 0.059 0.0058 0.018 1.6 3.2 2.7 1.4 Farmers No. 2 6 0.47 0.13 0.037 0.041 1.4 2.2 3.9 3.0 Reed Gatherers 4 0.66 0.036 0.16 0.63 1.8 2.1 9.2 7.1 Kids-in-mud No. 1 6 35 11 36 24 2.3 6.1 2.0 3.6 Kids-in-mud No. 2 *6 58 11 9.5 6.7 2.3 3.8 2.3 12.4

Number of subjects. Sources: Kissel et al. 1996b* Holmes et al. 1996 fsubmitted for nublicationt Table 6-13. Summary of Surface Area Studies Surface Area Study Type of Surface Area Recommended Population No. of Individuals Measurement Formulae Used Surveyed Comments KEY STUDIES Phillips et al, (1993) Based on data from NA calculated surface area to Children Developed distributions of *U.S. EPA (1985): 401 body weight ra!ios Adults SA/BW and cali:ulated individuals summary statistics for 3 age I groups and the combined data set U:S. EPA (1985) 401 individuals Based on Gehan and Children Provides statistical distribution George (1970) Adults data for total SA and SA of body parts RELEVANT STUDIES AICH (1994) Based on data from @Risk simulation Various Adults Distribution data for: adult U.S. EPA (1989); software Children men and women and both Brainard et al. (1991 ); sexes combined; total skin Brorby and Finley area, children 8-18 years; (1993) exposed skin area (hands and forearms); head; upper body Murray and Burmaster Based on data from Calculated based on Various Children Analysis of and comparision . (1992) U.S. EPA (1985): N = regression equation using Adults of four models developed* by. 401; the data of U.S. EPA Dubois & Dubois (1916), Dubois and Dubois (1985) Boyd (1935), U.S. EPA (1976):N= 9; (1985), and Costeff (1966). Boyd (1935): N = 231; Presents frequency Costeff (1966): N = distribtions 220 Table 6-14. Summary of Recommended Values for Skin Surface Area Surface Area *Central Tendency Upper Percentile Multiple Percentiles Adults Whole body and body see Tables 6-4 and 6-5 see Tables 6-2 and 6-3 see Tables 6-2 and 6-3 parts Bathing/swimming 20,000 cm2 23,000 cm2 ---Outdoor soil contact 5,000 cm2 5,800 cm2 ---Children Whole body ---see Tables 6-6 and 6-7 see Tables 6-6 and 6-7 Body parts ---see Table 6-8 see Table 6-8 Table 6-15. Confidence in Body Surface Area Measurement Recommendations Considerations Study Elements
Level of Peer Review
Accessibility
Reproducibility
Focus on factor of interest
Data pertinent to U.S.
Primary data
Currency
Adequacy of data collection period
Validity of approach
Representativeness of the population
Characterization of variability
Lack of bias in study design
Measurement error Other Elements
Number of studies
Agreement among researchers Overall Rating Rationale Studies were from peer reviewed journal articles. EPA report was peer reviewed before distribution. The journals used have wide circulation. EPA report available from National Technical Information Service. Experimental methods are well-described. Experiments measured skin area directly. Experiments conducted in the U.S. Re-analysis of primary data in more detail by two different investigators . Neither rapidly changing nor controversial area; estimates made in 1935 deemed to be accurate and subsequently used by others. Not relevant to exposure factor; parameter not time dependent. Approach us.ed by other investigators; not challenged 1n other studies. Not statistically representative of U.S. population. Individual variability due to age, race, or gender not studied. Objective subject selection and measurement methods used; results reproduced by others with different methods. Measurement variations are low; adequately described by normal statistics. 1 experiment; two independent re-analyses of this data set. Consistent results obtained with different analyses; but from a single set of measurements. This factor can be directly measured. It is not subject to dispute. Influence of age, race, or gender have not been detailed adequately 1n these studies. Rating High High High High High Low Low NA High Medium Low High Low/Medium Medium Medium High Bathing and Swimming Outdoor Activities Source: U.S. EPA, 1992. Table 6-16. Recommendations for Adult Body Surface Area Water Contact 50th 20,000 cm2 Soil Contact 50th 5,000 cm2 95th 23,000 cm2 95th 5,800 cm2 Table 6-17. Summarv of Soil Adherence Studies Size Soil Population Study . Fraction Adherence Surveyed Comments (µm) (mg/cm2) KEY STUDIES Kissel et al., 1996a <150, 150-Various 28 adults Data presented for soil loadings by 200,>250 24 children body part. See Table 6-11. Kissell et al., 1996b --Various 12 children Data presented by activity and body 89 adults part. RELEVANT STUDIES Driver et al., 1989 <150 1.40 Adults Used 5 soil types and 2-3 soil <250 0.95 Adults horizons (top soils and subsoils); unsieved 0.58 Adults placed soil over entire hand of test subject, excess removed by shaking the hands. Lepow et al., 1975 --0.5 10 children Dirt from hands collected during play. Represents only fraction of total present, some dirt may be trapped in skin folds. Que Hee et al., 1985 --1.5 1 adult Assumed exposed area= 20 cm2. Test subject was 14 years old. Roels et al., 1980 --0.9-1.5 661 children Subjects lived near smelter in Brussels, Belgium. Mean amount adhering to soil was 0.159 g. Sedman, 1989 --0.9; 0.5 Children Used estimate of Roels et al. ( 1980) and average surface of hand of an 11 year old; used estimates of Lepow et al. (1975), Roels et al. (1980), and Que Hee et al. (1985) to develop mean of 0.5 mg/cm2* Yang et al., 1989 <150 9 Rats Rat skin "monolayer" (i.e., minimal amount of soil covering the skin); in vitro and in vivo experiments.

Table 6-18. Confidence in Soil Adherence to Skin Recommendations Considerations Rationale Rating Study Elements

Level of Peer Review Studies were from peer reviewed journal articles. High
Accessibility Articles were published in widely circulated journals. High
Reproducibility Reports clearly describe experimental method. High . Focus on factor of interest The goal of the studies was to determine soil High adherence to skin. . Data pertinent to U.S . Experiments were conducted in the U.S. High
Primary data Experiments were directly measure soil adherence to _High skin; exposure and dose of chemicals in soil were measured indirectly or estimated from soil contact.
Currency New studies were presented. High
Adequacy of data collection Seasonal factors may be important, but have not been Medium period studied adequately.
Validity of approach Skin rinsing technique is a widely employed procedure. High
Representativeness of the Studies were limited to the State of Washington and Low population may not be representative of other locales.
Characterization of variability Variability in soil adherence is affected by many factors Low including soil properties, activity and individual behavior patterns.
Lack of bias in study design The studies attempted to measure soil adherence in High selected activities and conditions to identify important activities and groups.
Measurement error The experimental error is low and well controlled, but Low/High application of results to other similar activities may be subject to variation. Other Elements
Number of studies The experiments were controlled as they were Medium conducted by a few laboratories; activity patterns were studied by only one laboratory.
Agreement among researchers Results from key study were consistent with earlier Medium estimates from relevant studies and assumptions, but are limited to hand data. Overall Rating Data are limited, therefore it is difficult to extrapolate Low from experiments and field observations to general conditions .

Potential Exposure Dose ______. Chemical Applied Dose Skin Uptake Internal Dose Metabolism I I Biologically Effective Dose Organ Figure 6-1. Schematic of Dose and Exposure: Dermal Route Source: U.S. EPA, 1992a. Effect 0.25 1 I 0.2 f p I R D.15 1 . I o 0, r B . 0.05 l Infant SA/BW Ratios: Lognormf0.0641.0.01141 Eliip11cted Value .. 6.410E*D2 o*.__1 ___ _ 0.25 f 0.2 { p l R 0.15 1 0.0& J s 7 9 tt 13 16 Valuu in 10"*2 All Ages SA/BW Ratios: NormalC0.04S9,0.0187) Expect*d Value"' 4.890E-02 0.251 p 0.21 R o.ts , 0 l B 0.1 t 0.05 12 *1 4 9 In 10"*2 Adult SA/BW Ratios: NormalC0.0284.0.0028) Valuuln 10*.3 ExpllCfed Value"' 2.B40E*D2 37 14 17 Figure 6-2. SA/BW Distributions for Infants, Adults, and All Ages Combined Source: Phillips et al., 1993.

J) .06 -.g .04 ,Q Q i... a.. ... 02 -i--------1.00 Surface Area: Women Frequency Distribution ,09. ::::fJ .07 ---.05 -t------.c Q L.. c.. -+------1.00 1.50 2.00. 2.50 3.00 Area in m2, n=5,000, LHS 465 349. .,, ., Q) ,Q 232 c: (I) :J n u: 116 0 Figure 6-3. Frequency Distributions for the Surface Area of Men and Women Source: Murray and Burmaster, 1992.

REFERENCES FOR CHAPTER 6 American Industrial Health Council (AIHC). (1994) Exposure factors sourcebook. Washington, DC: AIHC. Boyd, E. ( 1935) The growth of the surface area of the human body. Minneapolis, Minnesota: University of Minnesota Press. Brainard, J.B.; Burmaster, D.E. (1992) Bivariate distributions for height and weight, men and women in the United States. Risk Anal. 12(2):267-275. Brorby, G.; Finley B. (1993) Standard probability density functions for routine use in environmental health risk assessment. Presented at the Society of Risk Analysis Annual Meeting, December 1993, Savannah, GA. Buhyoff, G.J.; Rauscher, H.M.; Hull, R.B.; Killeen, K.; Kirk, R.C. (1982) User's Manual for Statistical Processing System (version 3C.1 ). Southeast Technical Associates, Inc. Costeff, H. (1966) A simple empirical formula for calculating approximate surface area in children. Arch. Dis. Childh. 41:681-683. Driver, J.H.; Konz, J.J.; Whitmyre, G.K. (1989) Soil adherence to human skin. Bull. Environ. Contarri. Toxicol. 43:814-820. Dubois, D.; Dubois, E.F. (1916) A formula to estimate the approximate surface area if height and weight be known. Arch. of Intern. Med. 17:863-871. Gehan, E.; George, G.L. (1970) Estimation of human body surface area from height and weight. Cancer Chemother. Rep. 54( 4 ):225-235.

Geigy Scientific Tables (1981) Nomograms for determination of body surface area from height and mass. Lentner, C. (ed.). CIBA-Geigy Corporation, West Caldwell, NJ. pp. 226-227. George, S.L.; Gehan, E.A.; Haycock, G.B.; Schwartz, G.J. (1979) Letters to the editor. J. Ped. 94(2):342. Haycock, G.B.; Schwartz, G.J.; Wisotsky, D.H. (1978) Geometric method for measuring body surface area: A height-weight formula validated in infants, children, and adults. J. Ped. 93(1 ):62-66. Holmes, K.K.; Kissel, J.C.; Richter, K.Y. (1996) Investigation of the influence of oil on soil adherence to skin. J. Soil Contam. 5(4):301-308.

Kissel, J.; Richter, K.; Duff, R.; Fenske, R. (1996a) Factors Affecting Soil Adherence to Skin in Hand-Press Trials. Bull. Environ. Contamin. Toxicol. 56:722-728. Kissel, J.; Richter, K.; Fenske, R. (1996b) Field measurements of dermal soil loading attributable to various activities: Implications for exposure assessment. Risk Anal. 16(1 ):116-125 . . Lepow, M.L.; Bruckman, L.; Gillette, M.; Markowitz, S.; Rubino, R.; Kapish, J. (1975) Investigations into sources of lead in the environment of urban children. Environ. Res. 10:415-426. Murray, D.M.; Burmaster, D.E. (1992) Estimated distributions for total surface area of men and women in the United States. J. Expos. Anal. Environ. Epideiniol. 3(4):451-462. Palisade. (1992) @Risk users guide. Corporation, Newfield, NY. Phillips, L.J.; Fares, R.J.; Schweer, L.G. (1993) Distributions of total skin surface area to body weight ratios for use in dermal exposure assessments. J. Expos. Anal. Environ. Epidemiol. 3(3): 331-338. Popendorf, W.J.; Leffingwell, J.T. (1976) Regulating OP pesticide residues for farmworker protection. In: Residue Review 82. New York, NY: Springer-Verlag New York, Inc., 1982. pp. 125-201, Que Hee, S.S.; Peace, B.; Clark, C.S.; Boyle, J.R.; Bornschein, R.L.; Hammond, P.B. (1985) Evolution of efficient methods to sample lead sources, such as house dust and hand dust, in the homes of children. Environ. Res. 38: 77-95. Rochon, J.; Kalsbeek, W.D. (1983) Variance estimation from multi-stage sample survey data: the jackknife repeated replicate approach. Presented at 1983 SAS Users Group Conference, New Orleans, .Louisiana, January 1983. Roels, H.A.; Buchet, J.P.; Lauwenys, R.R.; Branx, P.; Claeys-Thoreau, F.; Lafontaine, A.; Verduyn, G. (1980) Exposure to lead by oral and pulmonary routes of children

living in the vicinity of a primary lead smelter. Environ. Res. 22:81-94. Sedman, R.M. (1989) The development of applied action levels for soil contact: a scenario for the exposure of humans to soil in a residential setting. Environ. Health Perspect. 79:291-313. Sendroy, J.; Cecchini, L.P. (1954) Determination of human body surface area from height and weight. J. Appl. Physiol. 7(1):3-12.

Thompson, K.M.; Burmaster, D.E. (1991) Parametric distributions for soil ingestion by children. Risk . Anal. 11 (2):339-342. U.S. EPA. (1985) Development of statistical distributions or ranges of standard factors used in assessments. Washington, DC: Office of Research and Development, Office of Health and Environmental Assessment. EPA 600/8-85-010. Available from: NTIS, Springfield, VA. PB85-242667. U.S. EPA. (1989) Exposure factors handbook. Washington, DC: Office of Research and Development, Office of Health and Environmental Assessment. EPA/600/18-89/043. U.S. EPA. (1992a) Guidelines for exposure assessment. Federal Register. FR 57:104:22888-22938. May 29, 1992. U.S. EPA. (1992b) Dermal exposure assessment: principles and applications. Washington, DC: Office of Research and Development, Office of Health and Environmental Assessment/GHEA. U.S. EPA/600/8-9-91. Van Graan, C.H. (1969) The determination of body surface area. Supplement to the South African J. of Lab. and Clin. Med. 8-2-69. Inc. (1991) Analysis of the impact of exposure assumptions on risk assessment of chemicals in the environment, phase II: uncertainty analyses of existing exposure assessment methods. Draft Report. Prepared for Exposure Assessment Task Group, Chemical.Manufacturers Association, Washington, DC. Yang, J.J.; Roy, T.A.; Krueger, A.J.; Neil, W.; Mackerer, C.R. (1989) In vitro and in vivo percutaneous absorption of benzo[a]pyrene from petroleum crude-fortified soil in the rat. Bull. Environ. Contam. Toxicol. 43: 207-214. __J DOWNLOADABLE TABLES FOR CHAPTER 6 The following selected tables are available for download as Lotus 1-2-3 worksheets. Table 6-2. Surface Area of Adult Males in Square Meters [WK1, 3 kb] Table 6-3. Surface Area of Adult Females in Square Meters [WK1, 3 kb] . Table 6-6. Total Body Surface Area of Male Children in Square Meters [WK1, 4 kb] Table 6-7. Total Body Surface Area of Female Children in Square Meters [WK1, 4 kb] Table 6-9. Descriptive Statistics for Surface Area/BodyWeight (SA/WB) Ratios (m /kg) [WK1, 1 kb] Volume I -General Factors Chapter 7 -Body Weight Studies 7. BODY WEIGHT STUDIES 7 .1. KEY BODY WEIGHT STUDY 7.2. RELEVANT BODY WEIGHT STUDIES 7.3. RECOMMENDATIONS REFERENCES FOR CHAPTER 7 Table 7-1. Table 7-2. Table 7-3. Table 7-4.

Table 7-5. Table 7-6. Table 7-7. Table 7-8. Table 7-9. Table 7-10. Table 7-11. Table 7-12. Smoothed Percentiles of Weight (in kg) by Sex and Age: Statistics from NCHS and Data from Fels Research Institute, Birth to 36 Months Body Weights of Adults (kilograms) Body Weigllts of Children (kilograms) Weight in Kilograms for Males 18-74 Years of Age--Number Examined, Mean, Standard Deviation, and Selected Percentiles, by Race and Age: United States, 1976-1980 Weight in Kilograms for Females 18-74 Years of Age--Number Examined, Mean, Standard Deviation, and Selected Percentiles, by Race and Age: United States, 1976-1980 Weight in Kilograms for Males 6 Months-19 Years of Age--Number Examined, Mean, Standard Deviation, and Selected Percentiles, by Sex and Age: United States, 1976-1980 Weight in Kilograms for Females 6 Months-19 Years of Age--Number Examined, Mean, Standard Deviation, and Selected Percentiles, by Sex and Age: United States, 1976-1980 Statistics for Probability Plot Regression Analyses Female's Body Weights 6 Months to 20 Years of Age Statistics for Probability Plot Regression Analyses Male's Body Weights 6 Months to 20 Years of Age Summary of Body Weight Studies Summary of Recommended Values for Body Weight Confidence in Body Weight Recommendations Figure 7-1. Weight by Age Percentiles for Boys Aged Birth-36 Months Figure 7-2. Weight by Age Percentiles for Girls Aged Birth-36 Months Exposure Factors Handbook *August 1997 Volume I -General Factors Chapter 7 -Body Weight Studies 7. BODY WEIGHT STUDIES There are several factors needed to calculate potential exposures. These include skin surface area (see Volume I, Section 6), inhalation rate (see Volume I, Section 5) life expectancy (see Volume I, Section 8), and body weight. The average daily dose is typically normalized to the average body weight of the exposed population. If exposure occurs only during childhood years, the average child body weight during the exposure period should be used to estimate risk (U.S. EPA, 1989). Conversely, if adult exposures are being evaluated, an adult body weight value should be used. The purpose of this section is to describe published studies on body weight for the general U.S. population. The studies have been classified as either key or relevant studies, based on the criteria described in Volume I, Section 1.3.1. Recommended values are based on the results of key studies, but relevant studies are also presented to provide the reader with added perspective on the current state of knowledge pertaining to body weight. 7 .1. KEV BODY WEIGHT STUDY Hamill et al. {1979) -Physical Growth: . National Center for Health Statistics Percentiles -A National Center for Health Statistics (NCHS) Task Force that included academic investigators and representatives from CDC Nutrition Surveillance Program selected, collated, integrated, and defined appropriate data sets to generate growth curves for the age interval:* birth to 36 months developed (Hamill et al., 1979). The percentile curves were for assessing the physical growth of children in the U.S. They are based on accurate measurements made on large nationally representative samples of children (Hamill et al., 1979). Smoothed percentile curves were derived for body weight by age (Hamill et al., 1979). Curves were developed for boys and for girls. The data used to construct the curves were provided by the Fels Research Institute, Yellow Springs, Ohio. These data were from an ongoing longitudinal study where anthromopetric data from direct *measurements are collected regularly from participants (-1,000) in various areas of the U.S. The NCHS used advanced statistical and computer technology to generate the growth curves. Table 7-1 presents the percentiles of weight by sex and age. Figures 7-1 and 7-2 present weight by age percentiles for boys and for girls aged birth to 36 months, respectively. Limitations of this study are that mean body weight values were not reported and the data are more than 15 years old. However, this study does provide body weight data for infants less than 6 months old. NCHS (1987) -Anthropometric Reference Data and Prevalence of Overweight, United States, 1976-80 -Statistics on anthropometric measurements, including body weight, for the U.S. population were collected by NCHS through the second National Health and Nutrition Examination Survey (NHANES II). NHANES II was conducted on a nationwide Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 7 -Body Weight Studies probability sample of approximately 28,000 persons, aged 6 months to 7 4 years, from the civilian, non-institutionalized population of the United States. Of the 28,000 persons, 20,322 were interviewed and examined, resulting in a response rate of 73.1 percent. The survey began in February 1976 and was completed in February 1980. The sample was selected so that certain subgroups thought to be at high risk of malnutrition (persons with low incomes, preschool children, and the elderly) were oversampled. The estimates were weighted to reflect national population estimates. The weighting was accomplished by inflati.ng examination results for each subject by the reciprocal of selection probabilities adjusted to account for those who were not examined, and post stratifying by race, age, and sex (NCHS, 1987). The NHANES II collected standard body measurements of sample subjects, including height and weight, that were made at various times of the day and in different seasons of the year. This technique was used because one's weight may vary between winter and summer and may fluctuate with recency of food and water intake and other daily activities (NCHS, 1987). Mean body weights of adults, by age, and their standard deviations are presented in Table 7-2 for men, women, and both sexes combined. Mean body weights and standard deviations for children, ages 6 months to 19 years, are presented in Table 7-3 for boys, girls, and boys and girls combined. Percentile distributions of the body weights of adults by age and race for males are presented in Table 7-4, and for females in Table 7-5. Data for children by age are presented in Table 7-6 for males, and for females in Table 7-7.
Results shown in Tables 7-4 and 7-5 indicate that the mean weight for adult males is 78.1 kg and for adult females, 65.4 kg. It also shows that the mean weight for White males (78.5 kg) is greaterthan for Black males (77.9 kg). Additionally, mean weights are greater for Black females (71.2 kg) than for White females (64.8 kg). From Table 7-3, the mean body weights for girls and boys are approximately the same from ages 6 months to 14 years. Starting at years 15-19, the difference in mean body weight ranges from 6 to 11 kg. 7.2. RELEVANT BODY WEIGHT STUDIES Brainard and Burmaster (1992) -Bivariate Distributions for Height and Weight of Men and Women in the United States -Brainard and Burmaster (1992) examined data on the height and weight of adults published by the U.S. Public Health Service and fit bivariate distributions to the.tabulated values for men and women, separately. Height and weight of 5,916 men and 6,588 women in the age range of 18 to 7 4 years were taken from the NHANES II study and statistically adjusted to represent the U.S. population aged 18 to 74 years with regard to age structure, sex, and race. Estimation techniques were used to fit normal distributions to the cumulative marginal data and Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 7 -Body Weight Studies goodness-of-fit tests were used to test the hypothesis that height and lognormal weight *follow a normal distribution for each sex. It was found that the marginal distributions of height and lognormal weight for both men and women are Gaussian (normal) in form. This conclusion was reached by visual observation and the high R2 values for best-fit lines obtained using linear regression. The R2 values for men's height and log normal weight are reported to be 0.999. The R2 values for women's height and lognormal weight are 0.999 and 0.985, respectively. Brainard and Burmaster (1992) fit bivariate distributions to estimated numbers of men and women aged 18 to 7 4 years in cells representing 1 inch height intervals and 10 pound weight intervals. Adjusted height and lognormal weight data for men were fit to a single bivariate normal distribution with an estimated mean height of 1.75 meters (69.2 inches) and an estimated mean weight of 78.6 kg (173.2 pounds). For women, height and lognormal weight data were fit to a pair of superimposed bivariate normal distributions (Brainard and Burmaster, 1992). The average height and weight for women were estimated from the combined bivariate analyses. Mean height for women was estimated to be 1.62 meters (63.8 inches) and mean weightwas estimated to be 65.8 kg (145.0 pounds). For women, a calculation using a single bivarite normal distribution gave poor results (Brainard and Burmaster, 1992). According to Brainard and Burmaster, the distributions are suitable for use in Monte Carlo simulation. Burmaster et al. (1994) (Submitted 2119194 to Risk Analysis for Publication) -Lognormal Distributions of Body Weight as a Function of Age for Female and Male Children in the United States -Burmaster et al. ( 1994 ), performed data analysis to fit normal and lognormal distributions to the body weights bf female and male children at age 6 months to 20 years (Burmaster et al., 1994 ). Data used in this analysis were from the second survey of the National Center for Health Statistics, NHANES II, which included responses from 4,079 females and 4,379 males 6 months to 20 years of age in the U.S. (Burmaster et al., 1994). The NHANES II data had been statistically adjusted for non-response and probability of selection, and stratified by age, sex, and race to reflect the entire U.S. population prior to reporting (Burmaster et al., 1994 ). Burmaster et al. ( 1994) conducted exploratory and quantitative data analyses, and fit normal and lognormal distributions to percentiles of body weight for children. Cumulative distribution functions (CDFs) were plotted for female and male body
weights on both linear and logarithmic scales. Two models were used to assess the probability density functions (PDFs) of children's body weight. Linear and quadratic regression lines were fitted to the data. A number of goodness-of-fit measures were conducted on data generated by the two models. Burmaster et al. ( 1994) found that log normal distributions give strong fits to the body weights of children, ages 6 months to 20 years. Statistics for the lognormal Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 7 -Body Weight Studies probability plots are presented in Tables 7-8 and 7-9. These data can be used for further analyses of body weight distribution (i.e., *application of Monte Carlo analysis). AIHC -Exposure Factors Sourcebook-The Exposure Factors Sourcebook (AIHC, 1994) provides similar body weight data as presented here. Consistent with this document, an average adult body weight of 72 kg is recommended on the basis of the NHANES II data (NCHS, 1987). These data are also used to derive probability distributions for adults and children. In addition, the Sourcebook presents probability distributions derived by Brainard and Burmaster (1992), Versar (1991) and Brorby and Finley (1993). For each distribution, the @Risk formula is provided for direct use in the @Risk simulation software (Palisade, 1992). The organization of this document, makes it very convenient to use in support of Monte Carlo analysis. The reviews of the supporting studies are very brief with little analysis of their strengths and weaknesses. The . Sourcebook has been classified as a relevant rather than key study because it is not the primary source for the data used to make recommendations in this document. The Spurcebook is very similar to this document in the sense that it summarizes exposure factor data and recommends values. As such, it is clearly relevant as an alternative information source on body weights as well as other exposure factors. 7 .3. RECOMMENDATIONS The key studies described in this section was u_sed in selecting recommended values for body weight. The general description of both the key and relevant studies are summarized in Table 7-10. The recommendations for body weight are summarized in Table 7-11. *Table 7-12 presents the confidence ratings for body weight recommendations. The mean body weight for all adults (male and female, all age groups) combined is 71.8 kg as shown in Table 7-2. The mean values for each age group in Table 7-2 were derived by adding the body weights for men and women and dividing. by 2. If age and sex distribution of the exposed population is known, the mean body weight values in Table 7-2 can be used. If percentile data are needed or if race is a factor, Tables 7-4 and 7-5 can be used to select the appropriate data for percentiles or mean values. For infants (birth to 6 months), appropriate values for body weight may be selected from Table 7-1. These data (percentile only) are presented for male and female infants. For children, appropriate mean values for .weights may be selected from Table 7-3. If percentile values are needed, these data are presented in Table 7-6 for male children and in Table 7-7 for female children. Body weight is a function of age, gender, and race and populations of many geographic regions may vary from the general population across geographic regions. Therefore, the Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 7 -Body Weight Studies user should make appropriate adjustments when applying the percentiles to other geographic regions. The mean recommended value for adults (71.8 kg) is different than the 70 kg commonly *assumed in EPA risk assessments. Assessors are encouraged to use values which most accurately reflect the exposed population. When using values other than 70 kg, however, the assessors should consider if the dose estimate will be used to estimate risk by combining with a dose-response relationship which was derived assuming a body weight of 70 kg. If such an inconsistency exists, the assessor should adjust the dose-response relationship as described in the appendix to Chapter 1. The Integrated Risk Information System (IRIS) does not use a 70 kg body weight assumption in the derivation of RfCs and RfDs, but does make this assumption in the derivation of cancer slope factors and unit risks. Exposure Factors Handbook August 1997 Table 7-1. Smoothed Percentiles of Weight (in kg) by Sex and Age: Statistics from NCHS and Data from Fels Research Institute, Birth to 36 Months Smoothed' Percentile 5th 10th 25th 50th 75th 90th 95th Sex and Age Weight in Kilograms Male Birth 2.54 2.78 3.00 3.27 3.64 3.82 4.15 1 Month 3.16 3.43 3.82 4.29 4.75 5.14 5.38 3 Months 4.43 4.78 5.32 5.98 6.56 7.14 7.37 6 Months 6.20 6.61 7.20 7.85 8.49 9.10 9.46 9 Months 7.52 7.95 8.56 9.18 9.88 10.49 10.93 12 Months 8.43 8.84 9.49 10.15 10.91 11.54 11.99 18 Months 9.59 9.92 10.67 11.47 12.31 13.05 13.44 24 Months 10.54 10.85 11.65 12.59 13.44 14.29 14.70 30 Months 11.44 11.80 12.63 13.67 14.51 15.47 15.97 36 Months 12.26 12.69 13.58 14.69 15.59 16.66 17.28 Female Birth 2.36 2.58 2.93 3.23 3.52 3.64 3.81 1 Month 2.97 3.22 3.59 3.98 4.36 4.65 4.92 3 Months 4.18 4.47 4.88 5.40 5.90 6.39 6.74 6 Months 5.79 6.12 6.60 7.21 7.83 8.38 8.73 9 Months 7.00 7.34 7.89 8.56 9.24 9.83 10.17 12 Months 7.84 8.19 8.81 9.53 10.23 10.87 11.24 18 Months 8.92 9.30 10.04 10.82 11.55 12.30 12.76 24 Months 9.87 10.26 11.10 11.90 12.74 13.57 14.08 30 Months 1.0.78 11.21 12.11 12.93 13.93 14.81 15.35 36 Months 11.60 12.07 12.99 13.93 15.03 15.97 16.54 ' Smoothed by cubic-spline approximation. Source: Hamill et al., 1979.

Table 7-2. Body Weights of Adults* (kilograms) Men and Women Men Women Age (years) Mean Std. Dev. Mean (kg) Std. Dev. Mean (kg) (kg) 18 < 25 73.8 12.7 60.6 11.9 67.2 25 < 35 78.7 13.7 64.2 15.0 71.5 35 < 45 80.9 13.4 67.1 15.2 74.0 45 < 55 80.9 13.6 68.0 15.3 74.5 55 < 65 78.8 12.8 67.9 14.7 73.4 65 < 75 74.8 12.8 66.6 13.8 70.7 18 < 75 78.1 13.5 65.4 14.6 71.8 Note: 1 kg = 2.2046 pounds. a Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram. Source: Adapted from National Center for Health Statistics (NCHS), 1987. Table 7-3. Body Weights of Children8 (kilograms) Boys Girls Boys and Girls Mean Age Mean Std. Dev. Mean (kg) Std. Dev. (kg) (kg) 6-11 months 9.4 1.3 8.8 1.2 9.1 1 year 11.8 1.9 10.8 1.4 11.3 2 years 13.6 1.7 13.0 1.5 13.3 3 years 15.7 2.0 14.9 2.1 15.3 4 years 17.8 2.5 17.0 2.4 17.4 5 years 19.8 3.0 19.6 3.3 19.7 6 years 23.0 4.0 22.1 4.0 22.6 7 years 25.1 3.9 24.7 5.0 24.9 8 years 28.2 6.2 27.9 5.7 28.1 9 years 31.1 6.3 31.9 8.4 31.5 10 years 36.4 7.7 36.1 8.0 36.3 11 years 40.3 10.1 41.8 10.9 41.1 12 years '44.2 10.1 46.4 10.1 45.3 13 years 49.9 12.3 50.9 11.8 50.4 14 years 57.1 11.0 54.8 11.1 56.0 15 years 61.0 11.0 55.1 9.8 58.1 16 years 67.1 12.4 58.I 10.1 62.6 17 years 66.7 11.5 59.6 11.4 63.2 18 years 71.1 12.7 59.0 11.1 65.1 19 years 71.7 11.6 60.2 11.0 66.0 Note: 1 kg = 2.2046 pounds. a Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram. Source: Adaoted from National Center for Health Statistics (NCHSt 1987. Table 7-4. Weight in Kilograms for Males 18-74 Years of Age-Number Examined, Mean, Standard Deviation, and Selected Percentiles, by Race and Age: United States, 1976-1980* Percentile Number of Persons Mean Standard Race and Age Examined (k9) Deviation 5th 1 Oth 15th 25th 5oth ?5th 85th 9oth 95th All racesb 18-74 years ..... 5,916 78.1 13.5 58.6 62.3 64.9 68.7 76.9 85.6 91.3 95.7 102.7 18-24 years . . . . . . . 988 73.8 12.7 56.8 60.4 61.9 64.8 72.0 80.3 85.1 90.4 99.5 25-34 years . . . . . 1,067 78.7 13.7 59.5 62.9 65.4 69.3 77.5 85.6 91.1 95.1 102.7 35-44 years . . . . . . . 7 45 80.9 13.4 59.7 65.1 67.7 72.1 79.9 88.1 94.8 98.8 104.3 45-54 years . . . . . . . 690 80.9 13.6 50.8 65.2 67.2 71.7 79.0 89.4 94.5 99.5 105.3 55-64 years . . . . . 1,227 78.8 12.8 59.9 63.8 66.4 70.2 77.7 85.6 90.5 94.7 102.3 65-7 4 years . . . . . 1 , 199 74.8 12.8 54.4 58.5 61.2 66.1 74.2 82.7 87.9 91.2 96.6 White 18-74 years ..... 5,148 78.5 13.1 59.3 62.8 65.5 69.4 77.3 85.6 91.4 95.5 102.3 18-24 years . . . . . . . 846 74.2 12.8 56.8 60.5 62.0 65.0 72.4 80.6 85.5 91.0 100.0 25-34 years . . . . . . . 901 79.0 13.1 59.9 63.7 65.9 69.8 78.0 85.6 91.3 . 95.3 102.7 35-44 years . . . . . . . 653 81.4 12.8 62.3 66.6 68.8 72.9 80.1 88.2 94.6 98.7 104.1 45-54 years ....... 617 81.0 13.4 62.0 66.1 67.3 71.9 79.0 89.4 94.2 99.0 104.5 55-64 years . . . . . 1 , 086 78.9 12.4 60.5 64.5 66.6 70.6 78.2 85.6 90.4 94.5 101.7 65-74 years . . . . . 1,045 75.4 12.4 55.5 59.5 62.5 67.0 74.7 83.0 87.9 91.2 96.0 Black 18-74 years ....... 649 .77.9 15.2 58.0 61 ;1 63.6 67.2 75.3 85.4 92.9 98.3 105.4 18-24 years ....... 121 72.2 12.0 58.3 60.9 62.3 64.9 70.8 77.1 81.8 83.7 93.6 25-34 years . . . . . . . 139 78.2 16.3 58.7 63.4 64.9 68.4 75.3 84.4 90.6 92.2 106.3 35-44 years ........ 70 82.5 15.4 *' 61.7 65.2 69.7 83.1 94.8 100.4 104.2 45-54 years ........ 62 82.4 14.5

64.7 67.0 73.2 81.8 93.0 100.0 102.5 55-64 years . . . . . . . 129 78.6 14.7 56.8 61.4 64.3 68.0 77.0 86.5 93.8 98.6 104.7 65-74 ;tears ....... 128 73.3 15.3 52.5 56.7 58.0 61.0 71.2 81.1 90.8 97.3 105.1 Note: 1 kg = 2.2046 pounds.
Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram. b Includes all other races not shown as separate categories. ' Data not available. Source: National Center for Health Statistics, 1987.

1 Table 7-5. Weight in Kilograms for Females 18-74 Years of Age-Number Examined, Mean, Standard Deviation, and Selected Percentiles, by Race and Age: United States, 1976-1980" Percentile Number of Persons Mean Standard Race and Age Examined (kg) Deviation 5th 10th 15th 25th 50th ?5th 85th 90th 95th All racesb 18-74years .... 6,588 65.4 14.6 47.7 50.3 52.2 55.4 62.4 72.1 79.2 84.4 93.1 18-24 years . . . . 1, 066 60.6 11.9 46.6 49.1 50.6 53.2 58.0 65.0 70.4 75.3 82.9 25-34 years . . . . 1, 170 64.2 15.0 47A 49.6 51.4 54.3 60.9 69.6 78.4 84.1 93.5 35-44 years . . . . . . 844 67.1 15.2 49.2 52.0 53.3 56.9 63.4 73.9 81.7 87.5 98.9 45-54 years ...... 763 68.0 15.3 48.5 51.3 53.3 57.:? 65.5 75.7 82.1 87.6 96.0 55-64 years .... 1,329 67.9 14.7 48.6 51.3 54.1 57.3 65.2 75.3 82.3 87.5 95.1 65-74 years .... 1,416 66.6 13.8 47.1 50.8 53.2 57.4 64.8 73.8 79.8 84.4 91.3 White 18-74 years .... 5,686 64.8 14.1 47.7 50.3 52.2 , 55.2 62.1 71.1 77.9 83.3 91.5 18-24 years ...... 892 60.4 11.6 47.3 49.5 50.8 53.3 . 57.9 64.8 69.7 74.3 82.4 25-34 years .... 1,000 63.6 14.5 47.3 49.5 51.3 54.0 60.6 68.9 76.3 81.5 89.7 35-44 years ...... 726 66.1 14.5 49.3 51.8 52.9 56.3 62.4 71.9 79.7 85.8 94.9 45-54 years ...... 64 7 67.3 14.4 48.6 51.3 53.4 57.0 65.0 74.8 81.1 85.6 94.5 55-64 years . . . . 1 , 176 67.2 14.4 48.5 50.7 53.7 57.1-64.7 74.5 81.8 86.2 92.8 65-74 years .... 1,245 66.2 13.7 47.2 50.7 52.9 57.2 64.3 72.9 79.2 84.3 91.2 Black 18-74 years ...... 782 71.2 17.3 48.8 51.6 55.1 59.1 67.8 80.6 87.4 94.9 105.1 18-24 years ...... 147 63.1 13.9 46.2 49.0 50.6 53.8 60.4 70.0 75.8 79.1 89.3 25-34 years ...... 145 69.3 16.7 48.3 50.8 53.1 57.8 65.3 80.2 87.1 91.5 102.7 35-44 years ...... 103 75.3 18.4 50.7 55.2 57.2 63.0 70.2 85.2 95.3 103.5 113.1 45-54 years ...... 100 77.7 18.8 55.1 60.3 60.8 64.5 74.3 83.6 94.5 98.2 117.5 55-64 years ...... 135 75.8 16.4 54.2 55.2 57.6 65.4 74.6 83.4 91.9 95.5 108.5 65-74 years ...... 152 72.4 13.6 52.9 56.4 60.3 64.0 70.0 82.2 84.4 86.5 98.1 Note: 1 kg = 2.2046 pounds. *Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram. b Includes all other races not shown as separate categories. Source: National Center for Health Statistics, 1987. Table 7-6. Weight in Kilograms for Males 6 Months"19 Years of Age--Number Examined, Mean, Standard Deviation, and Selected Percentiles, by Sex and Age: United States, 1976-1980a Percentile Number of Persons Mean Standard Age Examined (kg) Deviation 5th 10th 15th 25th 50th ?5th 85th 90th 95th 6-11 months ...... 179 9.4 1.3 7.5 7.6 8.2 8.6 9.4 10.1 10.7 10.9 11.4 1 years .......... 370 11.8 1.9 9.6 10.0 10.3 10.8 11.7 12.6 13.1 13.6 14.4 2 years .......... 375 13.6 1.7 11.1 11.6 11.8 12.6 13.5 14.5 15.2 15.8 16.5 3 years .......... 418 15.7 2.0 12.9 i3.5 13.9 14.4 15.4 16.8 17.4 17.9 19.1 4 years .......... 404 17.8 2.5 14.1 15.0 15.3 16.0 17.6 19.0 19.9. 20.9 22.2 5 years .......... 397 19.8 3.0 16.0 16.8 17.1 17.7 19.4 21.3 22.9 23.7 25.4 6years .......... 133 23.0 4.0 18.6 19.2 19.8 20.3 22.0 24.1 26.4 28.3 30.1 7 years .......... 148 25.1 3.9 19.7 20.8 21.2 22.2 24.8 26.9 28.2 29.6 33.9 8 years .......... 147 28.2 6.2 20.4 22.7 23.6 24.6 27.5 29.9 33.0 35.5 39.1 9 years .......... 145 31.1 6.3 24.0 25.6 26.0 27.1 30.2 33.0 35.4 38.6 43.1 10 years . . . . . . . . . 157 36.4 7.7 27.2 28.2 29.6 31.4 34.8 39.2 43.5 46.3 53.4 11 years . . . . . . . . . 155 40.3 10.1 26.8 28.8 31.8 33.5 37.3 46.4 52.0 57.0 61.0 12 years ......... 145 44.2 10.1 30.7 32.5 35.4 37.8 42.5 48.8 52.6 58.9 67.5 13 years ......... 173 49.9 12.3 35.4 37.0 38.3 40.1 48.4 56.3 59.8 64.2 69.9 14 years ......... 186 57.1 11.0 41.0 44.5 46.4 49.8 56.4 63.3 66.1 68.9 77.0 15 years . . . . . . . . . 184 61.0 11.0 46.2 49.1 50.6 54.2 60.1 64.9 68.7 72.8 81.3 16 years ......... 178 67.1 12.4 51.4 54.3 56.1 57.6 64.4 73.6 78.1 82.2 91.2 17 years ......... 173 66.7 11.5 50.7 53.4 54.8 58.8 65.8 72.0 76.8 82.3 88.9 18 years . . . . . . . . . 164 71.1 12.7 54.1 56.6 60.3 61.9 70.4 76.6 80.0 83.5 95.3 19 years ......... 148 71.7 11.6 55.9 57.9 60.5 63.8 69.5 77.9 84.3 86.8 92.1 Note: 1 kg = 2.2046 pounds. a Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram. Source: National Center for Health Statistics, 1987. Table 7-7. Weight in Kilograms for Females 6 Months-19 Years of Age--Number Examined, Mean, Standard Deviation, and Selected Percentiles, by Sex and Age: United States, 1976-1980a Percentile Number of Persons Mean Standard Age Examined (kg) Deviation 5th 10th 15th 25th 50th 75th 85th 90th 95th 6-11 months ...... 177 8.8 1.2 6.6 7.3 7.5 7.9 8.9 9.4 10.1 *10.4 10.9 1 years .......... 336 10.8 1.4 8.8 9.1 9.4 9.9 10.7 11.7 12.4 12.7 13.4 2 years .......... 336 13.0 1.5 10.8 11.2 11.6 12.0 12.7 13.8 14.5 14.9 15.9 3 years .......... 366 14.9 2.1 11.7 12.3 12.9 13.4 14.7 16.1 17.0 17.4 18.4 4 years .......... 396 17.0 2.4 13.7 14.3 14.5 15.2 16.7 18.4 19.3 20.2 21.1 5 years .......... 364 19.6 3.3 15.3 16.1 16.7 17.2 19.0 21.2 22.8 24.7 26.6 6 years .......... 135 22.1 4.0 17.0 17.8 18.6 19.3 21.3 23.8 26.6 28.9 29.6 7years .......... 157 24.7 5.0 19.2 19.5 19.8 21.4 23.8 27.1 28.7 30.3 34.0 8 years .......... 123 27.9 5.7 21.4 22.3 23.3 24.4 27.5 30.2 31.3 33.2 36.5 9 years .......... 149 31.9 8.4 22.9 25.0 25.8 27.0 29.7 33.6 39.3 43.3 48.4 10 years ......... 136 36.1 8.0 25.7 27.5 29.0 31.0 34.5 39.5 44.2 45.8 49.6 11 yeara ......... 140 41.8 10.9 29.8 30.3 31.3 33.9 40.3 45.8 51.0 56.6 60.0 12 years ......... 147 46.4 10.1 32.3 35.0 36.7 39.1 45.4 52.6 58.0 60.5 64.3 13 years ......... 162 50.9 .11.8 35.4 39.0 40.3 44.1 49.0 55.2 60.9 66.4 76.3 14years ......... 178 54.8 11.1 40.3 42.8 43.7 47.4 53.1 60.3 65.7 67.6 75.2 15 years ......... 145 55.1 9.8 44.0 45.1 46.5 48.2 53.3 59.6. 62.2 65.5 76.6 16 years ......... 170 58.1 10.1 44.1 47.3 48.9 51.3 55.6 62.5 68.9 73.3 76.8 17 years ......... 134 59.6 11.4 44.5 48.9 50.5 52.2 58.4 63.4 68.4 71.6 81.8 18 years ......... 170 59.0 11.1 45.3 49.5 50.8 52.8. 56.4 63.0 66.0 70.1 78.0 19 years ......... 158 60.2 11.0 48.5 49.7 51.7 53.9 57.1 64.4 70.7 74.8 78.1 Note: 1 kg = 2.2046 pounds. a Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram. Source: National Center for Health Statistics, 1987. Table 7-8. Statistics for Probability Plot Regression Analyses Female's Body Weights 6 Months to 20 Years of Age Lognormal Probability Plots Age Linear Curve a?a 6 months to 1 year 2.16 0.145 1 to 2 years 2.38 0.128 2 to 3 years 2.56 0.112 3 to 4 years 2.69 0.137 4 to 5 years .2.83 0.133 5 to 6 years 2.98 0.163 6 to 7 years 3.10 0.174 7 to 8 years 3.19 0.174 8 to 9 years 3.31 0.156 9 to 10 years 3.46 0.214 10 to 11 years 3.57 0.199 11 to 12 years 3.71 0.226 12 to 13 years 3.82 0.213 13 to 14 years 3.92 0.216 14 to 15 years 3.99 0.187 1 5 to 16 years 4.00 0.156 16 to 17 years 4.06 0.167 17 to 18 years 4.08 0.165 18 to 19 years 4.07 0.147 19 to 20 years 4.10 0.149 a µQ 02 -correspond to the mean and standard deviation, respectively, of the lognormal distribution of body weight (kg). Source: Burmaster et al. 1994 .. Table 7-9. Statistics for Probability Plot Regression Analyses Male's Body Weights 6 Months to 20 Years of Age Lognormal Probability Plots Age Linear Curve µ," a," 6 months to 1 year 2.23 0.132 1 to 2 years 2.46 0.119 2 to 3 years 2.60 0.120. 3 to 4 years 2.75 0.114 4 to 5 years 2.87 0.133 5 to 6 years 2.99 0.138 6 to 7 years 3.13 0.145 7 to 8 years 3.21 0.151 8 to 9 years 3.33 0.181 9 to 10 years 3.43 0.165 10 to 11 years 3.59 0.195 11 to 12 years 3.69 0.252 12 to 13 years 3.78 0.224 13 to 14 years 3.88 0.215 14 to 15 years 4.02 0.181 15 to 16 years 4.09 0.159 16 to 17 years 4.20 0.168 17 to 18 years 4.19 0.167 18 to 19 years 4.25 0.159 19 to 20 years 4.26 0.154 a µQ 02 -correspond to the mean and standard deviation, respectively, of the lognormal distribution of body weight (kg). Source: Burmaster et al. 1994. Table 7-10. Summary of Body Weight Studies Study Number of Subjects Population Comments KEY STUDIES Hamilletal. (1979) -1,000 U.S. general Authors noted that data are accurate measurements population from a large nationally representative sample of children. NCHS, 1987 20,322 U.S. general Based on civilian non-institutionalized population aged (NHf>.NES II) population 6 months to 74 years .. Response rate was 73.1 percent. RELEVANT STUDIES Brainard and Burmaster, 12,501 (5,916 men and U.S. general Used data from NHANES II to fit bivarite distributions 1992 6,588 women) population to women and men age 18 to 7 4 years. Burmaster et al., 1994 8,458 (4,079 females and U.S. general Used data from NHANES II to develop fitted 4,379 males) population distributions for children aged 6 to 20 years old. Adjusted for non-response by age, gender, and race. _____________ T.;..a;;;;b;;.;l..;;.e..:..7_-1;..;1..:.. . ....;S:;.;u;;..m;.:;m.:..:.:;;ary'"'-'o;;....f Recommended Values for Bod Weight Ponulation Adults Children Infants Mean 71.8 kg (See Table 7-2) See Table 7-3 Not Available U er Percentile See Tables 7-4 and 7-5 See Tables 7-6 and 7-7 See able -1 Multi le Percentiles See Tables 7-4 and 7-5 See Tables 7-6 and 7-7 ee Table 7-1 Table 7-12. Confidence in Body Weight Recommendations Considerations Rationale Ratinq Study Elements * . Level of peer review NHANES II was the major source of data for NCHS (1987). This is a High published study which received a high level c;>f peer review. The Hamill et al. (1979) is a peer reviewed journal publication. Accessibility Both studies are available to the public. High Reproducibility Results can be reproduced by analyzing NHANES II data and the High Fels Research Institute data. . Focus on factor of interest The studies focused on body weight, the exposure factor of interest. High . Data pertinent to US The data represent the U.S. population. High Primary data The primary data were generated from NHANES II data and Fels Medium studies, thus these data are secondary.

Currency The data were collected between 1976-1980. Low
Adequacy of data collection The NHANES II study included data collected over a period of 4 High period years. Body weight measurements were taken at various times.of the day and at different seasons of the year.
Validity of approach Direct body weights were measured for both studies. For NHANES II, High subgroups-at risk for malnutrition were over-sampled. Weighting was accomplished by inflating examination results for those not examined and were stratified by race, age, and sex. The Fels data are from an ongoing longitudinal study where the data are collected regularly. . Study size . The sample size consisted of 28,000 persons for NHANES II. Author High noted in Hamill et al. (1979) that the data set was large.
Representativeness of the Data collected focused on the U.S. population for both studies. High population
Characterization of Both studies characterized variability regarding age and sex. High variability Additionally NHANES II characterized race (for Blacks, Whites and total populations) and sampled persons with low income.
Lack of bias in study design There are no apparent biases in the study designs for NHANES II. Medium-(high rating is desirable) The study design for collecting the Fels data was not provided. High
Measurement error For NHANES II, measurement error should be low since body weights High were performed in a mobile examination center using standardized procedures and equipment. Also, measurements were taken at various times of the day to account for weight fluctuations as a result of recent food or water intake. The authors of Hamill et al. ( 1979) report that study data are based on accurate direct measurements from an ongoing longitudinal study. Other Eiements . Number of studies There are two studies. Low Agreement between researchers There is consistency among the two studies. High Overall Ratinq Hiqh

$.* .. *.:..\. *J:.*. (.ti . I.I:)' . . . . :-;t .. .:;:. *25il4 :lo ** "':f":": ... ;;.,j 0:i I -.J **a. . *;:(.t. ... . ... .. ti-' .. ""' *. :::b ... -.:I" * . "ro .... 00 * ""r-1r:-1-_;;.1-1--t,__-ts--+.;__--:t--4-..,,,+--t+--i--L--:*. r*** ::. J:*g'.: tjjJ r 1 .. 1

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1 r 1
1.: l *t *:ci:'. *3*. s* 9 ia is **2i a4* .. 27: :;?O. *:;t6 *Pr.3J?-.N.MQ'llTf:!S .* Figure 7-1. Weight by Age Percentiles for Boys Aged Birth-36 Months Source: Hamill et al., 1979.

... .. . ... Figure 7-2. Weight by Age Percentiles for Girls Aged Birth-36 Months Source: Hamill et al., 1979 REFERENCES FOR CHAPTER 7 American Industrial Health Council (AIHC). (1994) Exposure factors sourcebook. AIHC, Washington, DC. Brainard, J.; Burmaster, D. (1992) Bivariate distributions for height and weight of men and women in the United States. Risk Arial. 12(2):267-275. Brorby, G.; Finley, G. (1993) Standard probability density functions*for routine use in environmental health risk assessment. Presented at the Society of Risk Analysis Annual Meeting, December 1993, Savannah, GA. Burmaster, D.E.; Lloyd, K.J.; Crouch, E.A.C. (1994) Lognormal distributions of body weight as a function of age for female and male children in the United States. Submitted 2/19/94 to Risk Analysis for publication. Hamill, P.V.V.; Drizd, T.A.; Johnson, C.L.; Reed, R.B.; Roche, A.F.; Moore, W.M. (1979) Physical growth: National Center for Health Statistics Percentiles. American J. Clin. Nutr. 32:607,.609. National Center for Health Statistics (NCHS) ( 1987) Anthropometric reference data and prevalence of overweight, United States, 1976-80. Data from the National Health . and Nutrition Examination Survey, Series 11, No: 238. Hyattsville, MD: U.S. Department of Health and Human Services, Public Health Service, National Center for Health Statistics. DHHS Publication No. (PHS) 87-1688. Palisade. (1.g92) @Risk Users Guide. Palisade Corporation, Newfield, NY. U.S. EPA (1989) Risk assessment guidance for Superfund, Volume I: Human health evaluation manual. Washington, DC: U.S. Environmental Protection .Agency, Office of Emergency and Remedial Response. EPA/540/1-89/002*. Versar, Inc. (1991) Analysis of the impact of exposure assumptions on risk assessment of chemicals in the environment, phase II: uncertainty analyses of existing exposure assessment methods. Draft Report. Prepared for Exposure Assessment Task Group, Chemical Manufacturers Association, Washington, DC. DOWNLOADABLE TABLES FOR CHAPTER 7 The following selected tables are available for download as Lotus 1-2-3 worksheets. Table 7-4. Weight in Kilograms for Males 18-74 Years of Age--Number Examined, Mean, Standard Deviation, and Selected Percentiles, by Race and Age: United States, 1976-1980 [WK1, 5 kb] Table 7-5. Weight in Kilograms for Females 18-74 Years of Age--Number Examined, Mean, Standard Deviation, and Selected Percentiles, by Race and Age: United States, 1976-1980 [WK1, 5 kb] Table 7-6. Weight in Kilograms for 6 Months-19 Years of Age--Number Examined, Mean, Standard Deviation, and Selected Percentiles, by Sex and Age: United States, 1976-1980 [WK1, 5 kb] Table 7-7. Weight in Kilograms for Females 6 Months-19 Years of Age--Number Examined, Mean, Standard Deviation, and Selected Percentiles, by Sex and Age: United States, 1976-1980 [WK1, 5 kb] Volume I -General Factors Chapter 8 -Lifetime 8. LIFETIME 8.1. KEY STUDY ON LIFETIME 8.2. RECOMMENDATIONS REFERENC_ES FOR CHAPTER 8 Table 8-1. Table 8-2. Table 8-3 . Expectation of Life at Birth, 1970 to 1993, and Projections, 1995 to 2010 Expectation of Life by Race, Sex, and Age: 1992 Confidence in Lifetime Expectancy Recommendations . Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 8 -Lifetime 8. LIFETIME The length of an individual's life is an important factor to consider when evaluating cancer risk because the dose estimate is averaged over an individual's lifetime. Since the averaging time is found in the denominator of the dose equation, a shorter lifetime would result in a higher potential risk estimate, and conversely, a _longer life expectancy would produce a lower potential risk estimate. 8.1. KEY STUDY ON LIFETIME Statistical data on life expectancy are published annually by the U.S. Department of Commerce in the publication: "Statistical Abstract of the United States." The latest year for which statistics are available is 1993. Available data on life expectancies for various subpopulations born in the years 1970 to 1993 are presented in Table 8-1. Data for 1993 show that the life expectancy for an average person born in the United States in 1993 is 75.5.years (U.S. Bureau of the Census, 1995). The table shows that the overall life expectancy has averaged approximately 75 years since 1982. The average life expectancy for males in 1993 was 72.1 years, and 78.9 years for females. The data consistently show an approximate 7 years difference in life expectancy for males and females from 1970 to present. Table 8-1 also indicates that life expectancy for white males (73.0 years) is consistently longer than for Black males (64.7 years). Additionally, it indicates that life expectancy for White females. (79.5 years) is longer than for Black females (73.7), a difference of almost 6 years. Table 8-2 presents data for expectation of life for persons who were at a specific age in year 1990. These data are a_vailable by age, gender, and race and may be useful for deriving exposure estimates based on the age of a specific subpopulation. The data show that expectation of life is longer for females and for Whites. 8.2. RECOMMENDATIONS Current data suggest that 75 years would be an appropriate value to reflect the average life expectancy of the general population and is the recommended value. If gender is a factor considered in the assessment, note _thatthe average life expectancy value for females is higher than for males. It is recommended that the assessor use the appropriate value of 72.1 years for males or 78.9 years for females. If race is a consideration in assessing exposure for male individuals, note that the life expectancy is about 8 years longer for Whites than for Blacks. It is recommended that the assessor use the values of 73 years and 64.7 years for White males and Black males, respectively. Table 8-3 presents the confidence rating for life expectancy recommendations. Exposure Factors Handbook August 1997 Volume I -General Factors Chapter 8 -Lifetime This recommended value is different than the 70 years commonly assumed for the general population in EPA risk assessments. Assessors are encouraged to u.se values which most accurately reflect the exposed population. When using values other than 70 years, however, the assessors should consider if the dose estimate will be used to estimate risk by combining with a dose-response relationship which was derived assuming a lifetime of 70 years. If such an inconsistency exists, the assessor should adjust the dose-response relationship by multiplying by (lifetime/70). The Integrated Risk Information System (IRIS) does not use a 70 year lifetime assumption in the derivation of RfCs and RfDs, but does make this assumption in the derivation of some cancer slope factors or unit risks.

Exposure Factors Handbook August 1997 I I Table 8-1. Expectation of Life at Birth, 1970 to 1993, and Projections, 1995 to 2010 (years)8 TOTAL WHITE BLACK AND OTHERb BLACK YEAR Total Male Female Total Male Female Total Male Female Total Male Femal e 1970 70.8 67.1 74.7 71.7 68.0 75.6 65.3 61.3 69.4 64.1 60.0 68.3 1975 72.6 68.8 76.6 73.4 69.5 77.3 68.0 63.7 72.4 66.8 62.4 71.3 1980 73.7 70.0 77.4 74.4 70.7 78.1 69.5 65.3 73.6 68.1 63.8 72.5 1981 74.1 70.4 77.8 74.8 71.1 78.4 70.3 66.2 74.4 68.9 64.5 73.2 1982 74.5 70.8 78.1 75.1 71.5 78.7 70.9 66.8 74.9 69.4 65.1 73.6 1983 74.6 71.0 78.1 75.2 71.6 78.7 70.9 67.0 74.7 69.4 65.2 73.5 1984 74.7 71.1 78.2 75.3 71.8 78.7 71.1 67.2 74.9 69.5 65.3 73.6 1985 74.7 71.1 78.2 75.3 71.8 78.7 71.0 67.0 74.8 69.3 65.0 73.4 1986 74.7 71.2 78.2 75.4 71.9 78.8 70.9 66.8 74.9 69.1 64.8 73.4 1987 74.9 71.4 78.3 75.6 72.1 78.9 71.0 66.9 75.0 69.1 64.7 73.4 1988 74.9 71.4 78.3 75.6 72.2 78.9 70.8 66.7 74.8 68.9 64.4 73.2 1989 75.1 71.7 78.5 75.9 72.5 79.2 70.9 66.7 74.9 68.8 64.3 73.3 1990 75.4 71.8 78.8 76.1 72.7 79.4 71.2 67.0 69.1 64.5 73.6 1991 75.5 71.0 78.9 76.3 72.9 79.6 71.5 67.3 75.5 69.3 64.6 73.8 1992 75.8 72.3 79.1 76.5 73.2 79.8 71.8 67.7 75.7 69.6 65.0 73.9 1!;)93 75.5 72.1 78.9 76.3 73.0 79.5 71.5 67.4 69.3 64.7 73.7 Projections0 1995 76.3 72.8 79.7 77.0 73.7 80.3 72.5 68.2 76.8 70.3 65.8 74.8 2000 76.7 73.2 80.2 77.6 74.3 80.9 72.9 68.3 77.5 70.2 65.3 75.1 2005 .77.3 73.? 80.7 78.2 74.9 81.4 73.6 69.1 78.1 70.7 65.9 75.5 . 2010 77.9 74.5 81.3 78.8 75.6 81.0 74.3 69.9 78.7 71.3 66.5 76.0 a Excludes deaths of nonresidents of the United States. b Racial descriptions were not provided in the data source. c Based on middle mortality assumptions; for details, see U.S. Bureau of the Census, Current Population Reports, Series P-25, No. 1104. Source: Bureau of the Census, 1995.

Table 8-2. Expectation of Life by Race, Sex, and Age: 1992 Expectation of Life in Years White Black Age in 1990 (years) Total Male Female Male Female At birth 75.8 73.2 79.8 65.0 73.9 1 75.4 72.8 79.3 65.2 74.1 2 74.5 71.8 78.3 64.3 73.1 3 73.5 70.9 77.3 63.4 72.2 4 72.5 69.9 76.3 62.4 71.2 5 71.6 68.9 75.4 61.4 70.3 6 70.6 67.9 Y.4.4 60.5 69.3 7 69.6 66.9 73.4 59.5 68.3 8 68.6 65.9 72.4 58.5 67.3 9 67.6 65.0 71.4 57.5 66.3 10 66.6 64.0 70.4 56.5 65.4 11 65.6 63.0 69.4 55.5 64.4 12 64.6 62.0 68.4 54.6 63.4 13 63.7 61.0 67.4 53.6 62.4 14 62.7 60.0 66.5 52.6 61.4 15 61.7 59.1 65.5 51.7 60.4 16 60.7 58.1 64.5 50.7 59.5 17 59.8 57.2 63.5 49.8 58.5 18 58.8 56.2 62.5 48.9 57.5 19 57.9 55.3 61.6 48.1 56.6 20 56.9 54.3 60.6 47.2 55.6 21 56.0 53.4 59.6 46.3 54.6 22 55.1 52.5 58.7 45.5 53.7 23 54.1 51.6 57.7 44.6 52.7 24 53.2 50.6 56.7 43.8 51.8 25 52.2 49.7 55.7 42.9 50.8 26 51.3 48 .. 8 54.8 42.1 49.9 27 50.4 . 47.8 53.8 41.2 48.9 28 49.4 46.9 52.8 40.4 48.0 29 48.5 46.0 51.8 39.5 47.1 30 47.5 45.1 50.9 38.7 46.1 31 46.6 44.1 49.9 37.8 45.2 32 45.7 43.2 48.9 37.0 44.3 33 44.7 42.3 48.0 36.2 43.4 34 43.8 41.4 47.0 35.3 42.4 35 42.9 40.5 46.0 34.5 41.5 36 42.0 39.6 45.1 33.7 40.6 37 41.0 38.7 44.1 32.9 39.7 38 40.1 37.8. 43.2 32.1 38.8 39 39.2 36.9 42.2 31.3 37.9 40 38.3 36.0 41.2 30.5 37.1 41 37.4 35.1 40.3 29.7 36.2 42 36.5 34.2 39.3 28.9 35.3 43 35.6 33.3 38.4 28.2 34.4 44 34.7 32.4 37.5 . 27.4 33.6 45 33.8 31.5 36.5 26.7 32.7 46 32.9 30.6 35.6 25.9 31.9 47 32.0 29.7 34.7 25.2 31.0 48 31.1 28.8 ' 33.7 24.4 30.2 49 30.2 28.0 32.8 23.7 29.3 Table 8-2. Expectation of Life by Race, Sex, and Age: 1992 (continued) Expectation of Life in Years White Black Age in 1990 Male Female Male Female (years) Total 50 29.3 27.1 / 31.9 23.0 28.5 51 28.5 28.3 31.0 22.3 27.7 52 27.6 25.4 30.1 21.5 26.8 53 26.8 24.6 29.2 20.8 26.0 54 25.9 23.7 28.3 20.1 25.3 55 25.1 22.9 27.5 19.5 24.5 56 24.3 22.1 26.6 18.8 23.7 57 23.5 21.3 25.7 18.2 23.0 58 22.7 20.6 24.9 17.6 22.2 59 21.9 19.8 24.1 16.9 21.5 60 21.1 19.1 23.2 . 15:3 20.8 61 20.4 18.3 22.4 15.8 20.1 62 19.7 17.6 21.6 15.2 .19.4 63 18.9 16.9 20.8 14.6 18.7 64 18.2 16.2 20.0 14.1 18.0 65 17.5 15.5 ,. 19.3 13.5 17.4 70 1.4.2 12.4 15.6 11.0 14.3 75 11.2 9.6 12.2 8.9 11.4 80 8.5 7.2 9.2 6.8 8.6 85 and over 6.2 5.3 6.6 5.1 6.3 Source: U.S. Bureau of Census, 1995. Table 8-3. Confidence in Lifetime Expectancy Recommendations Considerations Rationale Rating Study Elements . Level of peer review Data are published and have received extensive peer review . High . Accessibility The study was widely available to the public (Census data). High Reproducibility Results can be reproduced by analyzing Census data. High Focus on factor of interest Statistical data on life expectancy were published in this study. High Data pertinent to US The study focused on the U.S. population. High . Primary data Primary data were analyzed. High . Currency The study was published in 1995 and discusses life expectancy High trends from 1970 to 1993. The study has also made projections for 1995 until the year 2010. . Adequacy of data collection period The data analyzed were collected over a period of years. High . Validity of approach Census data is collected and analyzed over a period of years. High . Study size This study was based on U.S. Census data, thus the population High study size is expected to be greater than 100. . Representativeness of the population The data are representative of the U.S. population . High . Characterization of variability Data were averaged by gender and race but only for Blacks and Medium Whites; no other nationalities were represented within the section. Lack of bias in .study design (High There are no apparent biases. High rating is desirable) . Measurement error Measurement error may be attributed to portions of the population that Medium avoid or provide misleading information on census surveys. Other Elements . Number of studies Data presented in the section are from the U.S. Bureau of the Low Census publication. Agreement between researchers Recommendation was based on only one study, but it is widely High accepted. Overall Rating HIGH REFERENCES FOR CHAPTER 8 U.S. Bureau of the Census. (1995) Statistical abstracts of the United States. DOWNLOADABLE TABLES FOR CHAPTER 8 The following selected table is available for download as a Lotus 1-2-3 worksheet. Table 8-1. Expectation of Life at Birth, 1970 to 1993, .and Projections, 1995 to 2010 [WK1, 5 kb] Volume II -Food Ingestion Factors Chapter 9 -Intake of Fruits and Veaetables 9. INTAKE OF FRUITS AND VEGETABLES 9.1. BACKGROUND 9.2. INTAKE STUDIES 9.2.1. U.S. Department of Agriculture Nationwide Food Consumption Survey and Continuing Survey of Food Intake by Individuals 9.2.2. Key Fruits and Vegetables Intake.Study Based on the USDA CSFll 9.2.3. Relevant Fruits and Vegetables Intake Studies 9.2.4. Relevant Fruits and Vegetables Serving Size Study Based on the USDA NFCS 9.2.5. Conversion Between As Consumed and Dry Weight Intake Rates 9.3. RECOMMENDATIONS REFERENCES FOR CHAPTER 9 APPENDIX9A APPENDIX 9B Table 9-1. Table 9-2. Table 9-3. Table 9-4. Table 9-5. Table 9-6. Table 9-7. Table 9-8. Table 9-9. Table 9-10. Table 9-11. Table 9-12. Table 9-13. Table 9-14. Table 9-15. Table 9-16. Table 9-17. Table 9-18. Sub-category Codes and Definitions Used in the CSFll 1989-91 Analysis Weighted and Unweighted Number of Observations for 1989-91 CSFll Data Used in Analysis of Food Intake Per Capita Intake of Total Fruits (g/kg-day as consumed) Per Capita Intake of Total Vegetables (g/kg-day as consumed) Per Capita Intake of Individual Fruits and Vegetables (g/kg-day as consumed) Per Capita Intake of USDA Categories of Fruits and Vegetables (g/kg-day as consumed) *

Per Capita Intake of Exposed Fruits (g/kg-day as consumed) Per Capita Intake of Protected Fruits (g/kg-day as consumed) Per Capita Intake of Exposed Vegetables (g/kg-day as consumed) Per Capita Intake of Protected Vegetables (g/kg-day as consumed) Per Capita Intake of Root Vegetables (g/kg-qay as consumed)
Mean Daily Intake of Fruits and Vegetables Per Individual in a Day for USDA 1977-78, 87-88, 89-91, 94, and 95 Surveys Mean Per Capita Intake Rates (as consumed) for Fruits and Vegetables Based on All Sex/Age/Demographic Subgroups Mean Total Fruit Intake (as consumed) in a Day by Sex and Age (1977-1978) .Mean Total Fruit Intake (as consumed) in a Day by Sex an Age (1987-1988) Mean Total Vegetable Intake (as consumed) in a Day by Sex and Age (1977-1978) Mean Total Vegetable Intake (as consumed) in a Day by Sex and Age (1987-1988) Mean Total Fruit Intake (as consumed) in a Day by Sex and Age (1994 and 1995) Exposure Factors Handbook August 1997 Table 9-19. Volume II -Food Ingestion Factors Chapter 9 -Intake of Fruits and Vegetables . Mean Total Vegetable Intake (as consumed) in a Day by Sex and Age (1994 and 1995) Table 9-20.
Mean Per Capita lntak.e of Fats and Oils (g/day as consumed) in a Day by Table 9-21. Table 9-22. Table 9-23. Table 9-24. Table 9-25. Table 9-26. Table 9-27. Table 9-28. Table 9-29. Table 9-30. Table 9A-1. Table 9 B.' Sex and Age ( 1994 and 1995) Mean and Standard Error for the Per Capita Daily Intake of Food.Class and Subclass .by Region (g/day as consumed) Mean and Standard Error for the Daily Intake of Food Subclasses Per Capita by Age (g/day as consumed) Consumption of Foods (g dry weight/day) for Different Age Groups and Estimated Lifetime Average Daily Food Intakes for a US Citizen (averaged across sex) Calculated from the FDA Diet Data Mean Daily Intake of Foods (grams) Based on the,Nutrition Canada Dietary Survey Per Capita Consumption of Fresh Fruits and Vegetables in 1991 Quantity (as consumed) of Fruits and Vegetables Consumed Per Eating Occasion and the Percentage of Individuals Using These Foods in Three Days Mean Moisture Content of Selected Fruits and Vegetables Expressed as Percentages of Edible Portions Summary of Fruit and Vegetable Intake Studies Summary of Recommended Values for Per Capita Intake of Fruits and Vegetables Confidence *in Fruit and Vegetable Intake, Recommendations Fraction of Grain and Meat Mixture Intake Represented by Various Food Items/Groups Food Codes and Definitions Used in Analysis of the 1989-91 USDA CSFll Data Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 9-Intake of Fruits and Vegetables 9. INTAKE OF FRUITS AND VEGETABLES 9.1. BACKGROUND -Ingestion of contaminated fruits and vegetables is a potential pathway of human exposure to toxic chemicals. Fruits and vegetables may become contaminated with toxic chemicals by several different pathways. Ambient pollutants from the air may be deposited on or absorbed by the plants, or dissolved in rainfall or irrigation waters that contact the plants. Pollutants may also be absorbed through plant roots from contaminated soil and ground water. The addition* of pesticides, soil additives, and fertilizers may also result in food contamination. The primary source of information on consumption rates of fruits and vegetables among the United States population is the U.S. Department of Agriculture's (USDA) Nationwide Food Consumption Survey (NFCS) and the USDA Continuing Survey of Food Intakes by Individuals (CSFll). Data from the NFCS have been used in various studies to generate consumer-only and per capita intake rates for both individual fruits and vegetables and total fruits and total vegetables. CSFll data fromthe 1989-1991 survey have been analyzed by EPA to generate per capita intake rates for various food items and food groups. Consumer-only intake is defined as the quantity of fruits and vegetables consumed by individuals who ate these food items during the survey period. Per capita intake rates are generated by averaging consumer-only intakes over the entire population of users and non-users. In general, per capita intake rates are appropriate for use in exposure assessment for which average dose estimates for the general population are of interest because they represent both individuals who ate the foods during the survey period individuals who may eat the food items at some time, but did not consume them during the suryey period. Total fruit intake refers to the sum of all fruits consumed in a day including canned, dried, frozen, and fresh fruits. Likewise, total vegetable intake refers to the sum of all vegetables consumed in a day including canned, dried, frozen, and fresh vegetables. For the purposes of. this handbook, the distinctions between fruits and vegetables are those commonly used, not the botanical definitions. For example, in this report, tomatoes are considered vegetables, although technically they are fruits. Intake rates may be presented on either an as consumed or dry weight basis. As consumed intake rates (g/day) are based on the weight of the food in the form that it is consumed. In contrast, dry weight intake rates are based on the weight of the food consumed after the moisture content has been removed. In calculating exposures based on ingestion, the unit of weight used to measure intake should be consistent with those used in measuring the contaminant concentration in the produce. Intake data from the individual component of the NFCS and CSFll are based on "as eaten" (i.e., cooked or Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 9 -Intake of Fruits and Vegetables prepared) forms of the food items/groups. Thus, corrections to account for changes in portion sizes from cooking losses are not required. Estimating source-specific exposures to toxic chemicals in fruits and vegetables may also require information on the amount of fruits and vegetables that are exposed to or protected from contamination as a result of cultivation practices or the physical nature of the food product itself (i.e., those having protective coverings that are removed before eating would be considered protected), or the amount grown beneath the soil (i.e., most root crops such as potatoes). The percentages of foods grown above and below ground will be useful when the concentrations of contaminants in foods are estimated from concentrations in soil, water, and air. For example, vegetables grown below ground may be more likely to be contaminated by soil pollutants, but leafy above ground vegetables may be more likely to be contaminated by deposition of air pollutants on plant surfaces. The purpose of this section is to provide: (1) intake data for individual fruits and vegetables, and total fruits and total vegetables; (2) guidance for converting between as consumed and dry weight intake rates; and (3) intake data for exposed and protected fruits * *and vegetables and those grown below ground. Recommendations are based on average and upper-percentile intake among the general population of the U.S. Available data have been classified as being either a key or a relevant study based on the considerations 'i discussed in Volume I, Section 1.3.1 of the Introduction. Recommendations are based on 1 data from the CSFH 1989-1991 survey, which was considered the only key intake study for fruits and vegetables. Other relevant studies are also presented to provide the reader with added perspective on this topic. It should be noted that many of the relevant studies are based on data from USDA's NFCS and CSFll. The USDA NFCS and CSFll are described below. 9.2. INTAKE STUDIES 9.2.1. U.S. Department of Agriculture Nationwide Food Consumption Survey and Continuing Survey of Food Intake by Individuals I USDA conducts the NFCS approximately every 10 years. The three most recent NFCSs were conducted in 1965-66, 1977-78, and 1987-88. The purpose of these surveys was to "analyze the food consumption behavior and dietary status* of Americans" (USDA, 1992a). The survey uses a statistical sampling technique designed to ensure that all seasons, geographic regions of the U.S., and demographic and socioeconomic_ groups are represented. There are two components of the NFCS. The household component collects information on the socioeconomic and demographic characteristics of households, and the types, value, and sources of foods consumed over a 7-day period. The individual Exposure Factors Handbook August 1997 I I Volume II -Food Ingestion Factors Chapter 9 -Intake of Fruits and Vegetables component collects information on food intakes of individuals within each household over a 3-day period (USDA, 1992b ). The same basic survey design was used for the three most recent NFCSs, but the sample sizes and statistical classifications used were somewhat different (USDA, 1992a). In 1965-66, 10,000 households were surveyed (USDA, 1972). The sample size increased to 15,000 households (over 36,000 individuals) in 1977-78, but decreased to 4,500 households in 1987-88 because of budgetary constraints and a low response rate (37 percent). Data from the 1977-78 NFCS are presented in this handbook because the data have been published by USDA in various publications and reanalyzed by various EPA offices according to the food items/groups commonly used to assess exposure. Published 1-day data from the 1987-88 NFCS data are also presented. USDA also conducts the Continuing Survey of Food Intake by Individuals. The purpose of the survey is to "assess food consumption behavior and nutritional content of diets for policy implications relating to food production and marketing, food safety, food assistance, and nutrition education" (USDA, 1995). An EPA analysis of the 1989-91" CSFll data set is presented in this handbook. During 1989 through 1991, over 15,000 individuals participated in the CSFll (USDA, 1995). Using a stratified sampling technique, individuals of ail ages living in *selected households in the 48 conterminous states and Washington, D.C. were surveyed. Individuals provided 3 consecutive days of data, including a personal interview on the first day followed by 2-day dietary records. The 3-:day response rate for the 1989-91 CSFI I was approximately 45 percent. Published 1-day data from the 1994 and 1995 CSFll are also presented. The 1994 and 1995 CSFI I included data for 2 consecutive survey days (although 2 days of data have been collected, only data for the first survey day have been analyzed and published by USDA). Over 5,500 individuals participated in these s*urveys (USDA, 1996a; 1996b ). Individual average daily intake rates calculated from NFCS and CSFll data are based on averages of reported individual intakes over one day or three consecutive days. Such short term data are suitable for estimating mean average daily intake rates representative of both short-term and long-term consumption. However, the distribution of average daily intake rates generated using short term data (e.g., 3 day) do not necessarily reflect the distribution of average daily intake rates. The distributions generated from short term and long term data will differ to the extent that each individual's intake varies from day to day; the distributions will be similar to the extent that individuals' intakes are constant from day to day. Day to day variation in intake among individuals will be great for food item/groups that are highly seasonal and for items/groups that are eaten year around but that are not typically eaten every day. For these foods, the intake distribution generated from short term data will not be a good reflection of the long term distribution. On the other hand, for Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 9 -Intake of Fruits and Vegetables broad categories of foods (e.g., vegetables) which are eaten on a daily basis throughout the year with minimal seasonality, the short term distribution may be a reasonable approximation of the true long term distribution, although it will show somewhat more variability. In this and the following section, distributions are shown only for the following broad categories of foods: fruits, vegetables, meats and dairy. Because of the increased variability of the short-term distribution, the short-term upper percentiles shown here will overestimate somewhat the corresponding percentiles of the long-term distribution. 9.2.2. Key Fruits and Vegetables Intake Study Based on the USDA CSFll U.S. EPA Analysis of USDA 1989-91 CSFll Data -EPA analyzed three years of data from USDA's CSFll to generate distributions of intake rates for various fruit and vegetable items/groups. Data from the 1989, 1990, and 1991 CFSll were combined into* a single data set to increase the number of observations available for analysis. Approximately 15,000 individuals provided intake data over the three survey years. The fruit and vegetable items/groups selected for this analysis included total fruits and total vegetables; individual fruits such as: apples, peaches, pears, strawberries, and other berries; individual vegetables such as: asparagus, beets, broccoli, cabbage, carro"ts, corn, cucumbers, lettuce, lima beans, okra*, onions, peas, peppers, pumpkin, snap beans, tomatoes, and white potatoes; fruits and vegetables categorized as exposed, protected and roots; and various USDA categories (i.e., citrus* and other fruits, and dark green, deep yellow, and other vegetables). These fruit and vegetable categories were selected to be consistent . with those evaluated in the homegrown food analysis presented in Chapter 13. Intake rates of total vegetables, tomatoes, and white potatoes were adjusted to account for the amount of these food eaten as meat and grain mixtures as described in Appendix 9A. Food items/groups were identified in the CSFll data base according to USDA-defined food codes. Appendix 98 presents the codes used to determine the various food groups. Intake rates for these food items/groups represent intake of all forms of the product (i.e., *home produced and commercially produced). Individual identifiers in the database were used throughout the analysis to categorize populations according to demographics. These identifiers included identification number, region_, urbanization, age, sex, race, body weight, weighting factor, season, and number of days that data were reported. Distributions of intake were determined for individuals who provided data for all three days of the survey. Individuals who did not provide information on body weight, or for which identifying information was unavailable, were excluded from the analysis. Three-day average intake rates were calculated for all individuals in the database for each of the food items/groups. These average daily intake rates were divided by each individual's reported body weight to generate intake rates in units of g/kg-day. The data were also weighted according to the three-day weights provided in the 1.991 CSFll. USDA sample weights are calculated to account for inherent biases in the sample selection process, and to adjust the sample population to reflect the Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors . Chapter 9 -Intake of Fruits and Vegetables national population. Summary statistics for individual intake rates were generated on a per capita basis. That is, both users and non-users of the food item were included in the analysis. Mean cons_umer only intake rates may be calculated by dividing the mean per capita intake rate by the percent of the population consuming the food item of interest. Summary statistics included are: number of weighted and unweighted observations, percentage of the population using the food item/group being analyzed, mean intake rate, standard error, and percentiles of the intake rate distribution (i.e., 0, 1, 5, 10, 25, 50, 75,
90, 95, 99, and 1 OOth percentile). Data were provided for the total population using the food item being evaluated and for several demographic groups including: various age groups (i.e., <1, 1-2, 3-5, 12-19, 20-39, 40-69, and 70+ years); regions (i.e., Midwest, Northeast, South, and West); urbanizations (i.e., Central City, Nonmetropolitan, and Suburban; seasons (i.e., winter, spring, summer, and fall); and races (i.e., White, Black, Asian, Native American, and othe.r). Table 9-1 provides the codes, definitions, and a description of the data in these categories. The total numbers of individuals in the data set, by demographic group are presented in Table 9-2. The food analysis was accomplished using the SAS statistical programming system (SAS, 1990). The res1,..1lts of this analysis are presented in Tables 9-3 and 9-4 for total fruits and total vegetables, Table 9-5 for individual fruits and vegetables, and Table 9-6 for the various USDA categories. The data for exposed/protected and root food items are presented in Tables 9-7 through 9-11. These tables are presented at the end of this Chapter. The results are presented in units of g/kg-day. Thus, use of these* data in calculating potential dose does not require the body weight factor to be included in the denominator of the average daily dose (ADD) equation. It should be noted that converting these intake rates into units of g/day by multiplying by a single average body weight is inappropriate, because individual intake rates were indexed to the reported body weights
of the s_urvey respondents. However, if there is a need to compare the intake data presented here to intake data in units of g/day, a body weight less than 70 kg (i.e., approximately 60 kg; calculated based on the number of respondents in each age category and the average body weights for these age groups, as presented Jn Chapter 7 of Volume I) should be used because the total survey population included children as well as adults. The advantages of using the 1989-91 CSFll data set are that the data are expected to be generally representative of the U.S. population and that it includes data on a wide variety of food types. However, it should be noted that the survey covers only the 48 coterminous U.S. States; Hawaii, Alaska, and U.S. Territories are not included. The data set was the most recent of a series of publicly available USDA data sets (i.e., NFCS 1977-78; NFCS 1987-88; CSFll 1989-91) at the time that EPA conducted the analysis for this handbook, and should reflect recent eating patterns in the United States. The data set includes three years of intake data combined. However, the 1989-91 CSFll data are based on a three day survey period. Short-term dietary data may not accurately reflect long-term eating patterns. This is particularly true for the tails (extremes) of the distribution
Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors
Chapter 9 -Intake of Fruits and Vegetables of food intake. In addition, the adjustment for including mixtures adds uncertainty to the intake rate distributions. The calculation for including mixtures assumes that intake of any mixture includes all of the foods identified in Appendix Table 9A-1 in the proportions specified in that table. This may under-or over-estimate intake of certain foods among some individuals.
The data presented in this handbook for the USDA 1989-91 CSFI I is not the most to-date information on food intake. USDA has recently made available the data from its 1994 and 1995 CSFll. Over 5,500 people nationwide participated in both of these surveys, providing recalled food intake information for 2 separate days. Although the 2-day data analysis has not been conducted, USDA published the results for the respondents' intakes on the first day surveyed (USDA, 1996a; 1996b ). USDA 1996 survey data will be made available later in 1997. As soon as 1996 data are available, EPA will take steps to get the 3-year data ( 1994, 1995, and 1996) analyzed and the food ingestion factors updated. Meanwhile, Table 9-12 presents a comparison of the mean daily intakes per-individual in a day for fruits and vegetables from the USDA survey data from years 1977-78, 19887-88, 1989-91, 1994, and 1995. This table shows that food consumption patterns have changed for fruits when comparing 1977 and 1995 data. Consumption of fruits increased by 72 percent, but vegetable intake remained relatively constant, when comparing data from 1977 and 1995. However, only an 11 percent increase was observed when comparing fruit . intake values from 1989-91 with the most recent data from 1994 and 1995. This indicates that the 1989-91 CSFll data are probably adequate for assessing ingestion exposure for current populations. 9.2.3. Relevant Fruits and.Vegetables Intake Studies The U.S. EPA'.s Dietary Risk Evaluation System (ORES) -USEPA, Office of Pesticide Programs -The U.S. EPA, Office of Pesticide Programs (OPP) uses the Dietary Risk Evaluation System (formerly the Tolerance Assessment System) to assess the dietary risk of pesticide use as part of the pesticide registration process. OPP sets tolerances for specific pesticides on raw agricultural commodities based on estimates of dietary risk. These estimates are calculated using pesticide residue data for the food item of concern and relevant consumption data. Intake rates are based primarily on the USDA 1977-78 NFCS althou*gh intake rates for some food items are based on estimations from production volumes or other data (i.e., some items were assigned an arbitrary value of 0.000001 day) (Kariya, 1992). OPP has calculated per capita intake rates of individual fruits and vegetables for 22 subgroups (age, regional, and seasonal) of the population by determining the composition of NFCS food items and disaggregating complex food dishes into their component raw agricultu.ral commodities (RACs) (White et al., 1983). The ORES per capita, as consumed intake rates for all age/sex/demographic groups combined are presented in Table 9-13. These data are based on both consumers and non
Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 9 -Intake of Fruits and Vegetables consumers of these food items. Data for specific subgroups of the population are not presented here, but are available through OPP via direct request. The data in Table 9-13 may be *useful for estimating the risks of exposure associated with the consumption of individual fruits and vegetables. It should be noted that these data are indexed to the reported body weights of the survey respondents and are expressed in units of grams of food consumed per kg bodyweight per day. Consequently, use of these data in calculating potential dose does not require the body weight factor in the denominator of the ADD equation. It should also be noted that conversion of these intake rates into units of g/day by multiplying by a single average body weight is not appropriate because the ORES data base did not rely on a single body weight for all individuals. Instead, ORES used the body weights reported by each individual surveyed to estimate consumption in units of g/kg-day. The advantages of using these data are that complex food dishes have been disaggregated to provide intake rates for a very large number of fruits and vegetables. These data are also based on the individual body weights of the respondents. Therefore, the use of these data in calculating exposure to toxic chemicals may provide more representative estimates of potential dose per unit body weight. However, because the data are based on NFCS short-term dietary recall the same limitations discussed previously for other NFCS data sets also apply here. In addition, consumption patterns may have changed since the data were collected in 1977-78. OPP is in the process of translating consumption information from the USDA CSFll 1989-91 survey to be used in ORES. Food and Nutrient Intakes of Individuals in One Day in the U.S., USDA (1980, 1992b, 1996a, 1996bJ.-USDA calculated mean intake rates for total fruits and total vegetables using NFCS data from 1977-78 and 1987-88 (USDA, 1980; USDA, 1992b) and CSFll data from 1994 and 1995 (USDA, 1996a; 1996b ). The mean per capita total intake rates are presented in Tables 9-14 and 9-15 for fruits and Tables 9-16 and 9-17 for vegetables. These values are based on intake data for one day from the 1977-78 and 1987-88 USDA NFCSs, respectively. Data from both surveys are presented here to demonstrate that although the 1987-88 survey had fewer respondents, the mean per capita intake rates for all individuals are in good agreement with the earlier survey. Also, slightly different age classifications were u.sed in the two surveys providing a wider range of age categories from which exposure assessors may select appropriate intake rates. Tables 9-18 and 9-19 present similar data from the 1994 and 1995 CSFI I. The age groups used in this data set are the same as those in the 1987-88 NFCS. Tables 9-14 through 9-19 include both per capita intake rates and intake rates for consumers-only for various ages of individuals. Intake rates for consumers-only were calculated by dividing the per capita consumption rate by the fraction of the population using vegetables or fruits in a day. The average per capita vegetable intake rate is 201 g/day based on the 1977-78 data (USDA, 1980), 182 g/day based on the 1987-88 data (USDA, 1992b ), 186 g/day based on the 1994 data, and 188 g/day based on the 1995 data. For fruits the average per capita intake rate is 142 Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 9 -Intake of Fruits and Vegetables g/day based on the two most recent USDA NFCSs (USDA, 1980; USDA, 1992b ), and 171 g/day and 173 g/day based on the 1994 and 1995 CSFll, respectively (USDA, 1996a, 1996b). One-day per capita intake data for fats or oils from the 1994 and 1995 CSFI I surveys are presented in Table 9-20. This total fats and oils food category includes table and cooking fats, vegetable oils, salad dressings, nondairy cream substitutes, and sauces such as tartar sauce that are mainly fat or oil (USDA, 1996a). It does not include oils or fats that were ingredients in food mixtures. The advantages of using these data are that they provide intake estimates for all fruits, all vegetables, or all fats combined. Again, these estimates are based on one-day dietary data which may not reflect usual consumption patterns . . U.S. EPA -Office of Radiation Programs-The U.S. EPA Office of Radiation Programs (ORP) has also used the USDA 1977-78 NFCS to estimate daily food intake (U.S. EPA, 1984a; 1984b). ORP uses food consumption data to assess human intake of radionuclides in foods. The 1977-78 NFCS data have been reorganized by ORP, and food items have been classified according to the characteristics of radionuclide transport. Data for selected agricultural products are presented in Table 9-21 and Table 9-22. ThesE? data represent per capita, as consumed intake rates for. total, leafy, exposed, and protected produce. Exposed produce refers to products (e.g., apples, pears, berries, etc.) that can intercept atmospherically deposited materials. The term protected refers to products (e.g., citrus fruit, carrots, corn, etc.) that are protected from deposition from the atmosphere. Although the fruit and vegetable classifications used in the study are somewhat limited in number, they provide alternative food categories that may be useful to exposure assessors. Because this study was based on the USDA NFCS, the limitations discussed previously regarding short-term dietary recall data also apply to the intake rates reported here. Also, consumption patterns may have changed since the data were collected in 1977-78.
U.S. EPA -Office of Science and Technology-The U.S. EPA Office of Science and Technology (OST) within the Office of Water (formerly the Office of Water Regulations and Standards) used data from the FDA revision of the Total Diet Study Food Lists and Diets . (Pennington, 1983) to calculate food intake rates (U.S. EPA, 1989). OST uses these consumption data in its risk assessment model for land application of municipal sludge. The FDA data used are based on the combined results of the USDA 1977-78, NFCS and the second National Health and Nutrition Examination Survey (NHANES II), 1976-80 (U.S. EPA, 1989). Because food items are listed as prepared complex foods in the FDA Total Diet Study, each item was broken down into its component parts so that the amount of raw commodities consumed could be determined. Table 9-23 presents intake rates of various fruit and vegetable categories for various age groups and estimated lifetime ingestion rates that have been derived by U.S. EPA Note that these are per capita intake rates tabulated as grams dry weight/day. Therefore, these rates differ from those in the Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 9 -Intake of Fruits and Vegetables previous tables because U.S. EPA (1984a, 1984b) report intake rates on an as consumed basis. The EPA-OST analysis provides intake rates for additional food categories and estimates of lifetime average daily intake on a per capita basis. In contrast to the other analyses of USDA NFCS data, this study reports the data in terms of dry weight intake rates. Thus, conversion is not required when contaminants are to be estimated on a dry weight basis. These data, however, may not reflect current consumption patterns because they are based on data from 1977-78. Canadian Department of National Health and Welfare Nutrition Canada Survey -The Nutrition Canada Survey was conducted between 1970 and 1972 to "(a) examine the mean consumption of selected food groups and their contribution to nutrient intakes of Canadians, (b) examine patterns of food consumption and nutrient intake at various times of the day, and provide information on the changes in eating habits during pregnancy." (Canadian Department of National Health and Welfare, n.d.). The method used for collecting dietary intake data was 24-hour recall. The* recall method relied on interview techniques in which the interviewee was asked to recall all foods and . beverages consumed during the day prece9ing the interview. Intake rates were reported for various age/sex groups of the population and for pregnant women (Table 9-24 ). The report does not specify whether the values represent per capita or consumer-only rates. However, they appear to be consistent with the as consumed intake rates for only reported by USDA (1980, 1992b). It should be noted that these data are also based on short-term dietary recall and are based on the Canadian population. USDA (1993) -Food Consumption, Prices, and Expenditures, 1970-92-The USDA's Economic Research Service (ERS) calculates the amount of food available for human consumption in the United States on an annual basis (USDA; 1993). Supply and utilization balance sheets are generated, based on the flow of food items from production to end uses for the years 1970 to 1992. Total available supply is estimated as the sum of production and imports (USDA, 1993). The availability of food for human use commonly termed as "food disappearance" is determined by subtracting exported foods from the total available supply (USDA, 1993). USDA (1993) calculates the per capita food consumption by dividing the total food disappearance by the total U.S. population. USDA (1993) estimated per capita consumption data for various fruit and vegetable products from 1970-1992 (1992 data are published). In this section, the 1991 values, which are the most recent published final data, are presented. Retail weight per capita data are presented in Table 9-25. These data have been derived from the annual per values in units of pounds per year, presented by USDA (1993), by converting to units of g/day. One of the limitations of this study is that disappearance data do not account for losses from the food supply from waste or spoilage. As a result, intake rates based on Exposure Factors Handbook August 1997 r ! Volume II -Food Ingestion Factors Chapter 9 -Intake of Fruits and Vegetables these data may overestimate daily consumption because they are based on the total quantity of marketable commodity utilized. Thus, these data represent bounding estimates of intake rates only. It should also be noted that per capita estimates based on food disappearance are not a direct measure of actual consumption or quantity ingested, instead the data are used as indicators of changes in usage over time (USDA, 1993). An advantage of this study is that it provides per capita consumption rates for fruits and vegetables that are representative of long-term intake because disappearance data are generated annually. AIHC, 1994 -Exposure Factors Sourcebook-The AIHC Sourcebook (AIHC, 1994) uses the data presented in the 1989 version of the Exposure Factors Handbook which reported data from the USDA 1977-78 NFCS. Distributions are provided in the @Risk format and the @Risk formula is also provided. In this handbook, new analyses of more recent data from the USDA 1989-91 CSFll are presented. Numbers, however, cannot be directly compared with previous values since the results from the new analysis are presented on a body weight basis. The Sourcebook was classified as a relevant study because it was not the primary source for the data to make recommendations in this document. However, it can be used as an alternative source of information. The advantage of using the CSFll and USDA NFCS data sets are that they are the *largest publicly available data source on food intake patterns in the United States. Data are available for a wide variety of fruit and vegetable products and are intended to be representative of the U.S. population. 9.2.4. Relevant Fruits and Vegetables Serving Size Study Based on the USDA NFCS Pao et al. {1982) -Foods Commonly Eaten by Individuals -Using data gathered in the 1977-78 USDA NFCS, Pao et al. (1982) calculated distributions for the quantities of individual fruit and vegetables consumed per eating occasion by members of the U.S. population (i.e., serving sizes), over a 3-day period. The data were collected during NFCS home interviews of 37,874 respondents, who were asked to recall food intake for the day preceding the interview, and record food intake the day of the interview and the day after the interview. Serving size data are presented on an as consumed (g/day) basis. The data presented in Table 9-26 are for all ages of the population, combined. If age-specific intake data are needed, refer to Pao et al. (1982). Although serving size data only are presented in this handbook, percentiles for the average quantities of individual fruits and vegetables Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 9 -Intake of Fruits and Vegetables consumed by members of the U.S. population who had consumed these fruits and vegetables over a 3-day period can be found in Pao et al. (1982). The advantages of using these data are that they were derived from the USDA NFCS and are representative of the U.S. population. This data set provides serving size distributions for a number of commonly eaten fruits and vegetables, but the list of foods is limited and does not account for fruits and vegetables included in complex food dishes. Also, these data represent the quantity of fruits and vegetables consumed per eating occasion. Although these estimates are based on USDA NFCS 1977-78 data, serving size data have been collected but not published for the more recent USDA surveys. These estimates may be useful for assessing acute exposures to contaminants in specific foods, or other assessments where the amount consumed per eating occasion is necessary. However, it should be noted that serving sizes may have changed since the data were collected in 1977-78. 9.2.5. Conversion Between As Consumed and Dry Weight Intake Rates As noted previously, intake rates may be reported in terms of units as consumed or units of dry weight. It is essential that exposure assessors be aware of this difference so that they may ensure consistency between the units used for intake rates and those used for concentration data (i.e., if the unit of food consumption is grams dry weight/day, then the unit for the amount of pollutant in the food should be grams dry weight). If necessary, as consumed intake rates may be converted to dry weight intake rates using the moisture content percentages presented in Table 9-27 and the following equation: I IRdw = IRa/ [( 100-W)/100] , (Eqn. 9-1) I "Dry weight" intake rates may be converted to "as consumed" rates by using: lRac = (Eqn. 9-2) where: IRdw = dry weight intake rate; IRac = as consumed intake rate; and w = percent water content. Exposure Factors Handbook -August 1997 Volume II-Food Ingestion Factors Chapter 9 -Intake of Fruits and Vegetables 9.3. RECOMMENDATIONS The 1989-91 CSFll data described in this section were used in selecting recommended fruit and vegetable intake rates for the general population and various subgroups of the United States population. The general design of both key and relevant studies are summarized in Table 9-28. Table 9-29 presents a summary of the recommended values for fruit and vegetable intake and Table 9-30 presents the confidence ratings for the fruit and vegetable intake recommendations. Based on the CSFll 1989-91, the recommended per capita fruit intake rate for the general population is 3.4 g/kg-day and the recommended per capita vegetable intake rate for the general population is 4.3 g/kg-day. Per capita intake rates for specific food items, on a g/kg-day basis, may be obtained from Table 9-5. Percentiles of the per capita intake .rate distribution in the general population for total fruits and total vegetables are presented in Tables 9-3 and 9-4. From these tables, the 95th percentile intake rates for fruits and vegetables are 12 g/kg-day and 10 g/kg-day, respectively. It is important to note that the distributions presented in Tables 9-3 through 9-4 are.based on data collected over a 3-dqy period and may not necessarily reflect the long-term distribution of average daily intake rates. However, for these broad categories of food (i.e., total fruits and total vegetables), because they are eaten on a daily basis throughout the year with minimal seasonality, the short term distribution may be a reasonable approximation of the long-term distribution, although it will display somewhat increased variability. This implies that the upper percentiles shown here will tend to overestimate the corresponding percentiles of the true long-term distribution. Intake rates for the home-produced form of these fruit and vegetable products are presented in Volume II, Chapter 13.. It should be noted that because these recommendations are based on 1989-91 CSFll data, they may not reflect the most recent changes that may have occurred in consumption patterns. However, as indicated in Table 9-12, intake has remained fairly constant between 1989-91and1995. Thus, the 1989-91 CSFll data are believed tb be appropriate for assessing ingestion exposure for current populations. Exposure Factors Handbook August 1997 /

Volume II -Food Ingestion Factors Appendix 9A APPENDIX9A CALCULATIONS USED IN THE 1989-91 CSFll ANAL.YSIS TO CORRECT FOR MIXTURES Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors E J . Appendix 9A APPENDIX 9A Calculations Used in the 1989-91 CSFll Analysis to Correct for Mixtures Distributions of intake for various food groups were generated for the food/items groups using the USDA 1989-91 CSFll data set as described in Sections 9.2.2. and 11.1.2. However, several of the food categories used did not include meats, dairy products, and

vegetables that were eaten as mixtures with other foods. Thus, adjusted intake rates were calculated for food items that were identified by USDA ( 1995) as comprising a significant portion of grain and meat mixtures. To account for the amount of these foods consumed as mixtures, the mean fractions of total meat or grain mixtures represented by these food items were calculated (Table 9A-1) using Appendix C of USDA (1995). Mean values.for all individuals were used to calculate these fractions. These fractions were multiplied by each individual's intake rate for total meat mixtures or grain mixtures to calculate the amount of the individual's food mixture intake that can be categorized into one of the selected food groups. These* amounts were then added to the total intakes rates for meats, grains, total vegetables, tomatoes, and white potatoes to calculate an individual's total intake of these food groups, as shown in the example for meats below. IR . ' (IR . ( Fr ) % (IR . ( Fr ) % (IR ) meat&ad;usted gr mixtures meat/gr mt mixtures meat/mt . meat where: I Rmeat-adjusted I Rgr mixtures I Rmt mixtures IRmeat Fr meat/gr Fr meat/mt = = = = = = adjusted individual intake rate for total meat; individual intake rate for grain mixtures; individual intake rate for meat mixtures; individual intake rate* for meats; fraction of grain mixture that is meat; and fraction of meat mixture that is meat. Population distributions for mixture-adjusted intakes were based on adjusted intake rates for the population of interest. Exposure Factors Handbook August 1997 Table 9-1. Sub-category Codes and Definitions Used in the CSFll 1989-91 Analysis Code Definition Description Rec:iion* 1 Northeast Includes Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, and Vermont 2 Midwest Includes Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin 3 South Includes Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, and West Virginia 4. West Includes Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming Urbanization 1 Central City Cities with populations of 50,000 or more that is the main city within the metropolitan statistical area .(MSA). 2 Suburban An area that is generally within the boundaries of an MSA, but is not within the legal limit of the central 3 Non metropolitan city. An area that is not within an MSA. Season Spring -April, May, June Summe -July, August, September r -October, November, December Fall -January, February, March Winter Race 1 --White (Caucasian) 2 --Black 3 --Asian and Pacific Islander 4 --Native American, Aleuts, and Eskimos 5 8 9 Other/NA Don't know no answer some other race
Alaska and Hawaii were not included. Source: CSFll 1989-91.

Table 9-2. Weighted and Unweighted Number of Observations for 1989-91 CSFll Data Used in Analysis of Food Intake Demographic Factor Weighted Unweighted Total 242,707,000 11,912 Age <01 7,394,000 424 01-02 7,827,000 450 03-05 11,795,000 603 06-11 21,830,000 1,147 12-19 26,046,000 1,250 20-39 78,680,000 3,555 40-69 71,899,000 3,380 70+ 17,236,000 1,103 Season Fall 60,633,000 3,117 Spring 60,689,000 3,077 Summer 60,683,000 2,856 Winter 60,702,000 2,862 Urbanization Central City 73,410,000 3,607 Nonmetropolitan 53,993,000 3,119 Suburban 115,304,000 5,186 Race Asian 2,871,000 149 Black 29,721,000 1,632 Native American 2,102,000 171 Other/NA 7,556,000 350 White 200,457 ,000 9,610 Region Northeast 59,285,000 . 3,007 Midwest 50,099,000 2,180 South 83,741,000 4,203 West 49,582,000 2,522 Table 9-3. Per Caoita Intake ofTotal Fruits (g/kg-dav as consumed) Population Percent Group Cons um Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 inq Total 69.0% 3.381 0.068 0 0 0 0 1.68 4.16 7.98 12.44 26.54 210.72 Age (years) < 01 67.9% 14.898 1.285 0 0 0 0 8.80 21.90 35.98 42.77 88.42 210.72 01-02 76.7% 11.836 0.582 0 0 0 2.80 9.76 17.99 25.70 30.69 52.27 80.19 03-05 80.8% 8.422 0.364 0 0 0 2.22 6.37 12.53 19.29 22.78 32.83 52.87 06-11 79.2% 5.047 0.160 o. 0 0 1.30 3.86 7.17 11.79 14.49 21.53 30.37 12-19 62.6% 2.183 0.095 0 0 0 0 1.36 3.38 5.66 7.24 11.80 16.86 20-39 58.8% 1.875 0.056 0 0 0 0 1.06 2.82 5.08 6.43 10.26 41.58 40-69 71.0% 2.119 0.051 0 0 0 0 1.36 3.24 5.20 6.73 10.52 23.07 70 + 83.3% 2.982 0.087 0 0 0 0.89 2.42 4.28 6.77 8.31 11.89 15.00 Season Fall 68.9% 3.579 0.169 0 0 0 0 1.66 3.94 8.20 13.41 32.62 204.28 Spring 68.3% 3.249 0.116 0 0 0 0 U3 4.14 7.43 12.22 23.71 88.42 Summer 70.4% 3.381 0.131 0 0 0 0 1.80 4.29 7.87 12.26 23.11 210.72 Winter 68.4% 3.314 0.119 0 0 0 0 1.52 4.27 8.33 12.17 26.54 75.52 Urbanization Central City 68.8% 3.288 0.114 0 0 0 0 1.66 4.00 7.82 11.94 23.73 210.72 Nonr'netropolitan 67.4% 3.107 0.113 0 0 0 0 1.51 3.94 7.52 12.25 26.04 84.34 Suburban 70.1% 3.567 0.113 0 0 0 0 1.80 4.40 8.43 13.19 28.13 204.28 Race Asian 77.2% 5.839 0.632 0 0 0 1.24 4.20 6.76 17.30 20.65 29.61 38.95 Black 63.7% 3.279 0.188 0 0 0 0 1.51 4.25 7.70 12.34 26.54 210.72 Native American 61.4% 3.319 0.490 0 0 0 0 1.58 4.31 7.57 16.02 22.66 29.24 Other/NA 64.9% 4.027 0.465 0 0 0 0 1.77 5.10 10.92 14.96 47.78 53 .. 89 White 70.1% 3.337 0.075 0 0 0 0 1.66 4.06 7.87 12.21 26.48 204.28 Region Midwest 69.9% 3.236 0.120 0 0 0 0 1.58 4.07 7.87 11.30 28.64 84.34 Northeast 73.9% 3.665 0.143 0 0 0 0.07 1.84 4.70 8.37 12.75 31.67 88.42 South 62.0% 3.017 0.105 0 0 0 0 1.42 3.80 7.39 11.67 24.67 210.72 West 75.4% 3.880 0.187 0 0 0 0.17 2.08 4.45 9.18 14.61 25.49 204.28 NOTE: SE = Standard error P = Percentile of the distribution Source: Based on EPA's analvses of the 1989-91 CSFll Table 9-4. Per Capita Intake of Total Vegetables la/ka-dav as consumed) Population Percent Group Consumi Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 na Total 97.2% 4.259 0.029 0 0.75 1.29 2.26 3.60 5.37 7.93 10.00 15.65 44.99 Age (years) < 01 74.8% 6.802 0.375 0 0 0 0 5.52 10.41 15.27 19.29 29.61 44.99 01-02 95.6% 7.952 0.228 0 1.33 2.32 4.65 7.28 10.26 14.77 16.32 21.24 32.10 03-05 97.2% 7.125 0.200 0 1.11 2.15 3.79 5.83 9.64 13.87 15.43 25.09 35.56 06-11 97.6% 5.549 0.109 0 1.03 1.72 3.09 4.82 7.31 10.06 11.74 18.39 31.30 12-19 98.1% 3.807 0.070 0 0.85 1.30 2.16 3.49 4.71 6.80 8.52 12.26 27.84 20-39 98.2% 3.529 0.037 0 0.75 1.22 2.06 3.16 4.54 6.36 7.63 10.69 17.07 40-69 98.3% 3.741 0.039 0 0.85 1.34 2.19 3.43 4.94 6.56 7.78 10.91 24.51 70 + 98.3% 4.068. 0.071 0 0.96 1.47 2.47 3.67 5.35 6.89 8.17 11.96 18.92 Season Fall 97.8% 4.366 0.063 0 0.86 1.31 2.28 3.56 5.28 8.33 10.52 17.95 35.56 Spring 96.9% 4.095 0.055 0 0.72 1.20 2.19 3.45 5.19 7.67 9.85 15.33 44.99 Summer 97.0% 4.181 0.059 0 0.58 1.16 2.21 3.54 5.34 7.73 9.54 15.14 41.68 Winter 97.0% 4.394 0.056 0 0.86 1.40 2.36 3.78 5.67 8.03 9.69 15.23 29.69 Urbanization Central City 97.4% 4.059 0.053 0 0.67 1.22 2.08 3.34 5.17 7.74 9.51 16.04 44.99 Nonmetropolitan 96.3% 4.450 0.060 0 0.86 1.41 2.44 3.72 5.66 8.28 10.08 16.27 35.56 Suburban 97.6% 4.296 0.044 0 0.82 1.31 2.30 3.64 5.38 7.86 10.17 15,39 41.68 Race Asian 93.3% 4.913 0.330 0 0 1.53 2.06 3.66 7.52 10.32 14.84 15.43 16.76 Black 96.1% 4.228 0.093 0 0.36 0.85 1.99 3.19 5.46 8.80 11.35 18.39 32.10 Native American 87.1% 4.880 0.277 0 0 0.58 2.40 4.22 6.85 8.87 11.37 13.89 21.77 Other/NA 96.6% 4.762 0.183 0 0 1.11 2.46 4.24 6.20 9.33 11.93 15.02 22.14 White 97.6% 4.229 0.031 0 0.86 1.37 2.30 3.60 5.32 7.74 9.75 15.31 44.99 Region Midwest 97.0% 4.123 0.061 0 0.75 1.20 2.09 3.35 5.16 8.03 9.87 16.90 35.56 Northeast 97.2% 4.494 0.073 0 0.69 1.29 2.37 3.77 5.70 8.42 11.00 15.86 41.68 South 97.4% 4.268 0.047 0 0.86 1.39 2.31 3.66 . 5.32 7.76 9.80 15.31 44.99 West 96.9% 4.168 0.060 0 0.60 1.22 2.25 3.57 5.38 7.78 9.53 15.28 35.56 NOTE: SE = Standard error P =Percentile of the distribution Source: Based on EPA's analvses of the 1989-91 CSFll Table 9-5. Per Capita Intake of Individual Fruits and Veqetables (q/kq-dav as consumed) Apples Asparagus Bananas Beets Population Percent Percent Percent Percent Grouo Consumina Mean SE Consumina Mean SE Consumina Mean SE Consumina Mean SE Total 28.4% 0.854 0.052 1.5% 0.012 0.008 20.9% 0.27 0.02 1.8% 0.009 0.010 Age (years) < 01 41.7% 5.042 0.823 0.0% 0 0 24.3% 1.33 0.27 1.2% 0.045 0.296 01-02 42.9% 4.085 0.508 0.2% 0.003 0.041 23.3% 0.86 0.17 0.7% 0.006 0.055 03-05 44.1% 3.004 0.312 0.2% 0.001 0.038 20.1% 0.46 0.09 0.5% 0.006 0.056 06-11 41.6% 1.501 0.123 0.3% 0.001 0.019 16.2% 0.29 0.05 0.9% 0.008 0.040 12-19 23.0% 0.394 0.062 0.3% 0.003 0.033 13.3% 0.16 0.03 0.6% 0.001 0.010 20-39 21.3% 0.337 0.033 1.1% 0.008 0.012 14.4% 0.13 0.02 1.3% 0.004 0.007 40-69 26.0% 0.356 0.027 2.5% 0.025 0.016 26.0% 0.22 0.02 2.4% 0.009 0.009 70 + 30.8% 0.435 0.052 3.5% 0.026 0.028 37.4% 0.36 0.03 . 5.2% 0.029 0.022 Season Fall 33.7% 1.094 0.116 0.8% 0.005 0.013 19.3% 0.25 0.03 1.2% 0.009 0.040 Spring 25.9% 0.667 0.078 2.7%* 0.023 0.017 21.3% 0.27 0.03 2.0% 0.009 0.012 Summer 23.2% 0.751 0.122 1.1% 0.006 0.014 20.5% 0.23 0.03 1.7% 0.005 0.008 Winter 30.4% 0.905 0.095 1.3% 0.015 0.018 22.6% 0.31 0.03 2.3% 0.011 0.013 Urbanization Central City 27.4% 0.749 0.081 1.1% 0.013 0.018 19.6% 0.25 0.03 1.3% 0.008 0.031 Non metropolitan 26.8% 0.759 0.104 1.3% 0.011 0.015 20.5% 0.24 0.03 1.8% 0.010 0.013 Suburban 29.9% 0.965 0.083 1.8%' 0.013 0.012 21.9% 0.29 0.03 2.0% 0.008 0.009 Race Asian 38.3% 0.871 0.327 2.7% 0.067 0.123 33.6% 0.54 0.20 o .. 7% 0.040 0.320 Black 22.7% 0.688 0.159 0.3% 0.003 0.019 14.4% 0.19 0.04 1.1% 0.007 0.024 Native American 20.5% 0.407 0.273 0.0% 0 0 17.5% 0.36 0.16 1.2% 0.003 0.028 Other/NA 24.9% 0.964 0.256 0.6% 0.001 0.009 20.6% 0.33 0.15 0.9% 0.015 0.101 White 29.4% 0.879 0.057 1.7% 0.013 0.009 21.8% 0.27 0.02 1.9% 0.008 0.010 Region Midwest 29.1% 0.782 0.082 1.8% 0.015 0.016 18.8% 0.25 0.03 0.8% 0.010 0.049 Northeast 31.5% 0.953 0.116 1.6% 0.015 0.022 23.0% 0.26 0.04 2.3% 0.008 0.012 South 23.6% 0.828 0.099 1.0% 0.010 0.014 19.3% 0.28 0.03 1.8% 0.009 0.011 West 32.7% 0.885 0.121 1.8% 0.012 0.015 24.0% 0.27 0.03 2.4% 0.008 0.009 *------------------- Table 9-5. Per Capita Intake of Individual Fruits and Vegetables (g/kg-day as consumed) (continued) Broccoli Cabbage Carrots Corn Population Percent Percent Percent Percent Group Consuminq Mean SE Consuminq Mean SE Consuminq Mean SE Consuminq Mean SE Total 10.9% 0.107 0.012 12.2% 0.088 0.009 16.9% 0.115 0.010 24.1% 0.206 0.010 Age (years) < 01 4.2% 0.142 0.224 2.4% 0.023 0.078 13.4% 0.379 0.165 17.5% 0.356 0.128 01-02 7.6% 0.234 0.134 5.1% 0.086 0.089 13.3% 0.214 0.085 32.9% 0.587 0.091 03-05 10.1% 0.307 0.118 7.5% 0.107 0.081 15.1% 0.148 0.052 31.5% 0.490 0.070 . 06-11 6.8% 0.098 0.052 7.5% 0.049 0.027 17.1% 0.154 0.037 35.8% 0.367 0.032 12-19 8.2% 0.065 0.028 8.5% 0.065 0.028 11.8% 0.056 0.018 24.0% 0.173 0.024 20-39 11.4% 0.081 0.015 10.6% 0.070 0.015 15.2% 0.076 0.013 23.8% 0.154 0.013 40-69 13.8% 0.102 0.016 17.1% 0.115 0.015 20.1% 0.120 0.016 20.4% 0.138 0.013 70 + 11.8% 0.115 0.028 21.1% 0.151 0.025 21.3% 0.132 0.022 19.0% 0.140 0.027 Season Fall 10.8% 0.089 0.024 12.3% 0.092 0.019 17.7% 0.100 0.017 23.6% 0.171 0.018 Spring 11.7% 0.122 0.022 12.4% 0.086 0.018 16.5% 0.117 0.022 24.7% 0.204 0.019 Summer 8.8% 0.120 0.032 12.3% 0.097 0.018 13.9% 0.083 0.017 24.8% 0.244 0.022 Winter 12.3% 0.098 0.020 11.9% 0.076 0.014 19.2% 0.160 0.022 23.2% 0.205 0.020 Urbanization Central City 10.6% 0.119 0.024 10.8%. 0.073 0.015 15.5% 0.111 0.019 22.4% 0.182 0.017 Nonmetropolitan 9.0% 0.067 0.017 13.7% 0.102 0.016 14.4% 0.095 0.017 27.6% 0.255 0.020 Suburban 12.2% 0.119 0.019 12.4% 0.091 0.014 19.2% 0.127 0.015. 23.1% 0.198 0.015 Race Asian 15.4% 0.209 0.166 27.5% 0.400 0.100 28.2% 0.177 0.101 14.1% 0.134 0.080 Black 8.3% 0.154 0.047 13.9% 0.129 0.029 7.0% 0.066 0.036 24.6% 0.226 0.028 Native American 5.3% 0.021 0.045 4.7% 0.037 0.068 11.1% 0.097 0.075 30.4% 0.373 0.099 Other/NA 10.3% 0.180 0.100 6.0% 0.041 0.044 12.9% 0.104 0.063 16.9% 0.160 0.065 White 11.4% 0.097 0.012 12.1% 0.080 0.009 18.6% 0.122 0.011 24.3% 0.204 0.011 Region Midwest 8.43 0.077 0.025 10.1% 0.065 0.016 16.2% 0.100 0.018 26.8% 0.242 0.020 Northeast 13.5% 0.113 0.026 11.6% 0.083 0.022 19.0% 0.15.1 0.027 23.3% 0.208 0.026 South 9.8% 0.109 0.022 14.4% 0.106 0.015 12.4% 0.074 0.015 24.9% 0.219 0.016 West 13.4% 0.135 0.025 11.8% 0.088 0.016 23.3% 0.166 0.021 20.1% 0.138 0.018 Table 9-5. Per Capita Intake of Individual Fruits and Veoetables la/ka-dav as consumed) (continued) Cucumbers Lettuce Lima Beans Okra Population Percent Percent Percent Percent Group Consumina Mean SE Consumina Mean SE .consumina Mean SE Consumina Mean SE Total 15.8% 0.063 0.006 41.3% 0.224 0.006 0.9% 0.006 0.007 1.3% 0.009 0.007 Age (years) < 01 2.4% 0.021 0.107 6.8% 0.025 0.026 0.5% 0.005 0.055 0.5% 0.003 0.040 01-02 7.3% 0.062 0.069 18.2% 0.116 0.039 0.4% 0.006 0.069 0.2% 0.004 0.068 03-05 12.1% 0.083 0.046 29.4% 0.191 0.031 0.0% 0 0 0.7% 0.013 0.046 06-11 14.9% 0.086 0.032 36.3% 0.247 0.027 0.3% 0.002 0.017 0.3% 0.005 0.028 12-19 12.6% 0.050 0.017 40.4% 0.187 0.014 0.5% 0.003 0.019 1.4% 0.011 0,027 20-39 17.0% 0.057 0.009 44.4% 0.231 0.010 0.7% 0.005 0.012 1.0% 0.008 0.016 40-69 19.8% 0.070 0.008 51.0% 0.264 0.010 1.5% 0.010 0.013 1.8% 0.008 0.010 70 + 14.8% 0.055 0.016 37.4% 0.203 0.017 1.9% 0.008 0.019 2.7% 0.015 0.021 Season Fall 14.3% 0.056 0.014 38.1% 0.175 0.010 0.8% 0.004 0.010 0.9% 0.004 0.009 Spring 15.8% 0.060 0.009 43.5% 0.259 0.011 1.0% 0.008 0.015 0.8% 0.009 0.020 Summer 19.0% 0.092 0.014 42.3% 0.218 0.012 0.9% 0.006 0.014 2.2% 0.016 0.015 Winter 14.3% 0.044 0.010 41.5% 0.243 0.013 1.0% 0.007 0.013 1.3% 0.006 0.012 Urbanization Central City 15.1% 0.061 0.011 37.9% 0.196 0.009 0.5% 0.004 0.011 1.0% 0.004 0.008 Nonmetropolitan 15.1% 0.071 0.013 39.9% 0.221 0.012 1.5% 0.015 0.018 1.8% 0.013 0.015 Suburban 16.7% 0.060 0.008 44.6% 0.242 0.009 0.9% 0.004 0.007 1.2% 0.010 0.012 Race Asian 16.1% 0.065 0.036 40.3% 0.231 0.050 0.0% 0 0 4.7% 0.084 0.074 Black 7.8% 0.040 0.021 . 27.1% 0.134 0.014 0.9%. 0.006 0.021 2.1% 0.024 0.029 Native American 6.4% 0.037 0.042 42.7% 0.146 0.034 0:0% 0 0 0.0% 0 0 Other/NA 10.9% 0.038 0.029 41.1% 0.186 0.027 0.0% 0 0 1.7% 0.004 0.023 White 17.5% 0.067 0.007 43.7% 0.239 0.007 1.0% 0.006 0.007 1.1% 0.006 0.007 Region Midwest 15.1% 0.074 0.014 36.1% 0.191 0.012 0.4% 0.005 0.019 0.2% 0 0.004 Northeast 18.9% 0.097 0.018 43.9% 0.246 0.014 0.5% 0.003 0.013 0.6% 0.009 0.031 South 13.8% 0.042 0.007 39.3% 0.210 Q.009 1.8% 0.011 0.011 3.2% 0.016 0.010 West 17.2% 0.050 0.011 48.7% 0.263 0.013 0.5% 0.002 0.009 0.2% 0.005 0.022 Table 9-5. Per Capita Intake of Fruits and Veaetables (a/ka-dav as consumed) (continued) Onions Other Berries Peaches Pears Population Percent Percent Percent Percent Group Consumina Mean SE Consumina Mean SE Consumina Mean SE Consumina Mean SE Total 17.4% 0.040 0.003 2.5% 0.029 0.017 8.6% 0.131 0.019 4.8% 0.098 0.036 Age (years) < 01 1.9% 0.004 0.022 0.9% 0.092 0.369 14.2% 0.855 0.268 *12.3% 1.286 0.598 01-02 6.4% 0.012 0.017 1.3% 0.053 0.248 8.9% 0.286 0.158 2.7% 0.105 0.243 03-05 8.0% 0.023 0.016 2.2%. 0.039 0.073 10.0% 0.283 0.121 4.5% 0.144 0.141 06-11 9.7% 0.033 0.015 1.4% 0.014 0.056 13.8% 0.250 0.063 7.8% 0.147 0.057 12-19 12.2% 0.030 0.010 0.8% 0.011 0.029 6.9% 0.084 0.037 3.4% 0.025 0.027 20-39 20.5% 0.040 0.005 2.3% 0.024 0.030 4.2% 0.037 0.019 2.4% 0.026 0.019 40-69 24.0% 0.054 0.005 3.2% 0.031 0.023 8.7% 0.090 0.021 5.2% 0.062 0.022 70 + 16.5% 0.043 0.012 5.1% 0.049 O.D40 16.1% 0.161 0.033 7.8% 0.087 0.037 Season Fall 16.3% 0.045 0.007 i6% 0.024 0.023 6.4% 0.113 0.043 5.5% 0.159 0.107 Spring 19.7% 0.040 0.005 1.9% 0.019 0.024 8.4% 0.107 0.037 4.3% 0.071 0.041 Summer 18.7% 0.040 0.005 3.4% 0.032 0.027 12.5% 0.166 0.033 4.2% 0.076 . 0.066 Winter

14.8% 0.033 0.006 2.0% 0.042 0.058 7.4% 0.136 0.041 5.1% 0.088 0.039 Urbanization Central City 16.4% 0.043 0.006 2.9% 0.033 0.030 7.3% 0.121 0.035 4.5% 0.120 0.091 Non metropolitan 15.7% 0.033 0.005 1.6% 0.016 0.019 9.8% 0.156 0.034 5.4% 0.083 0.033 Suburban 19.1% 0.041 0.004 2.7% 0.033 0.028 8.8% 0.125 0.029 4.6% 0.092 0.050 Race Asian 20.8% 0.090 0.042 2.7% 0.014 0.057 6.7% 0.202 0.235 2.7% 0.053 0.151 Black 9.6% 0.034 0.014 0.9% 0.008 0.034 5.6% 0.111 0.053 2.9% 0.066 0.056 Native American 5.3% 0.018 0.022 2.3% 0.072 0.165 9.9% 0.192 0.158 1.2% 0.003 0.053 Other/NA 15.1% 0.057 0.022 0.9% 0.015 0.069 4.3% 0.118 0.145 5.1% 0.063 0.089 White 19.0% 0.039 0.003 2.8% 0.033 0.019 9.3% 0.132 0.021 5.2% 0.106 0.042 Region Midwest 13.8% 0.033 0.006 2.3% 0.022 0.020 9.6% 0.155 0.040 6.0% 0.121 0.054 Northeast 20.6% 0.057 0.009 3.2% 0.023 0.024 9.0% 0.132 0.048 5.7% 0.108 0.064 South 17.2% 0.034 0.004 1.7% 0.030 0.037 7.9% 0.113 0.027 3.6% 0.051 0.023 West 19.2% 0.039 0.006 3.3% 0.043 0.045 8.3% 0.131 0.042 4.5% 0.142 0.142 Table 9-5. Per Capita Intake of Individual Fruits and VeQetables (Q/kQ-day as consumed) (continued) Peas Peppers Pumpkins Snap Beans Population Percent Percent Percent Percent Group ConsuminQ Mean SE ConsuminQ Mean SE ConsuminQ Mean SE ConsuminQ Mean SE Total 12.8% 0.095 0.009 6.5% 0.022 0.005 1.0% 0.026 0.032 21.5% 0.146 0.008 Age (years) < 01 13.7% 0.294 0.142 0.7% 0.0Q3 0.025 5.2% 0.497 0.363 16.7% 0.439 0.154 01-02 13.6% 0.174 0.083 204% 0.011 0.031 0.4% 0.030 0.253 24.9% 0.383 0.070 03-05 12.9% 0.199 0.077 3.0% 0.014 0.032 0.7% 0.018 0.148 25.0% 0.274 0.048 06-11 13.2% 0.120 0.029 4.7% 0.019 0.016 0.4% 0.012 0.118 25.6% 0.183 0.024 12-19 8.4% 0.053 0.021 5.3% 0.017 0.014 0.2% 0 0.007 18.3% 0,112 0.018 20-39 10.9% 0.067 0.013 7.9% 0 .. 026 0.009 0.6% 0.007 0.026 19.0% 0.096 0.010 40-69 14.8% 0.084 0.011 8.6% 0.027 0.008 1.2% 0.011 0.018 22.3% 0.124 0.011 70 + 16.4% 0.117 0.024 4.7% 0.010 0.008 1.7% 0.034 0.053 25.5% 0.149 0.019 Season Fall 13.2%. 0.120 0.023 6.0% 0.023 0.009 1.9% 0.043 0.056 21.5% 0.164 0.018. Spring 12.6% 0.077 0.015 7.3% 0.021 0.009 0.6% 0.034 0.105 18.9% 0.109 0.013 Summer 11.2% 0.074 0.019 7.9% 0.023 0.009 0.4% O.Q12 0.064 22.3% 0.147 0.016 Winter 14.1% 0.111 0.017 4.7% 0.019 0.010 1.0% 0.015 0.037 23.7% 0.163 0.017 Urbanization Central City 11.7% 0.085 0.018 6.5% 0.023 0.009 1.1% 0.035 0.068 20.2% 0.133 0.015 Nonmetropolitan 14.5% 0.113 0.020 6.0% 0.017 0.006 0.5% 0.015 0.068 22.3% 0.141 0.013 Suburban 12.5% 0.094 0.014 6.8% 0.023 0.007 1.3% 0.025 0.041 22.0% 0.156 0.013 Race Asian 8.1% 0.047 0.071 8.1% 0.102 0.112 0.7% 0.005 0.057 13.4% 0.059 0.050 Black 17.0% 0.143 0.032 3.6% 0.005 0.007 0.3% 0.037 0.238 24.1% 0.188 0.022 Native American 2.9% 0.007 0.035 5.3% 0.015 0.031 0.0% 0 0 21.1% 0.119 0.048 Other/NA 6.9% 0.037 0.058 11.1% 0.037 0.024 0.9% 0.024 0.208 15.1% 0.168 0.073 White 12.5% 0.092 0.010 6.8% 0.022 0.005 1.2% 0.025 0.030 21.5% 0.140 . 0.009 Region Midwest 10.9% 0.071 0.014 4.7% 0.016 0.011 1.2% 0.027 0.050 22.4% 0.146 0.014 Northeast 12.5% 0.101 0.026 9.0% 0.036 0.012 1.4% 0.061 0.106 19.7% 0.131 0.020 South 16.2% 0.126 0.017 5.8% 0.015 0.006 0.5% 0.002 0.026 24.3% 0.177 0.014 West 9.5% 0.067 0.018 7.6% 0.025 0.010 1.3% 0.030 0.060 17.5% 0.107 0.019 Table 9-5. Per Capita Intake of Individual Frui!S and Vegetables (g/kg-day as consumed) (continued) Strawberries Tomatoes White Potatoes Population Percent Percent Percent Grouo Consuminq Mean SE Consumina Mean SE Consumina Mean SE Total 3.4% 0.039 0.019 91.8% 0.876 0.010 87.6% 1.093 0.013 Age (years) < 01 0.7% 0.018 0.154 64.2% 1.116 0.094 59.9% 1.102 0.128 01-02 1.6% 0.155 0.598 93.8% 1.838 0.103 84.2% 2.228 0.113 03-05 3.2% 0.045 0.080 94.9% 1.700 0.072 88.1% 1.817 0.086 06-11 3.3% 0.052 0.058 95.2% 1.160 0.032 90.5% 1.702 0.058 12-19 2.3% 0.016 0:028 95.5% 0.852 0.022 90.1% 1.238 0.042 20-39 2.7% 0.028 0.020 94.7% 0.791 0.013 88.6% 0.897 0.018 40-69 4.5% 0.042 0.020 90.6% 0.673 0.013 88.1% 0.882 0.018 70 + 5.8% 0.050 0.040 87.2% 0.689 0.027 88.9% 0.865 0.031 Season Fall 1.3% 0.008 0.017 92.5% 0.907 0.021 88.9% 1.169 0.027 Spring 7.7% 0.105 0.045 90.6% 0.808 0.018 86.3% 1.036 0.024 Summer 2.2% 0.030 0.032 92.4% 0.946 0.019 86.5% 1.001 0.029 Winter 2.5% 0.013 0.015 91.9% 0.844 0.018 88.7% 1.167 0.024 Urbanization Central City 2.8% 0.028 0.020 91.5% 0.827 0.017 84.7% 1.017 0.025 Nonmetropolitan 3.8%. 0.052 0.029 90.7% 0.827 0.018 89.4% 1.211 0.027 Suburban 3.6% 0.040 0.035 92.8% 0.931 0.015 88.5% 1.087 0.019 Race Asian 3.4% 0.395 1.152 90.6% 1.147 0.110 77.2% 0.446 0.062 Black 1.5% 0.031 0.056 87.4% 0.713 0.027 83.3% 1.202 0.047 Native American 1.8% 0.023 0.120 84.2% 0.890 0.073 85.4% 1.735 0.134 Other/NA 1.4% 0.007 0.042 91.4% 1.004 b.049 77.1% 1.036 0.080 White 3.9% 0.037 0.013 92.8% 0.892 0.011 88.9% 1.082 0.014 Region Midwest 4.8% 0.051 0.025 92.2% 0.814 0.019 89.2% 1.246 0.029 Northeast 3.3% 0.059 0.079 93.0% 0.988 0.024 86.6% 1.090 0.030 Sau th 2.6% 0.025 0.019 90.7% 0.831 0.016 88.5% 1.074 0.021 West 3.3% 0.028 0.025 92.3% 0.914 0.021 85.1% 0.946 0.026 NOTE: SE = Standard error P = Percentile of the distribution Source: Based on EPA's analvses of the 1989-91 CSFll Table 9-6. Per Capita Intake of USDA of Fruits and Vegetables (g/kg-dav as consumed) Dark Green Vegetables Deep Yellow Vegetables Citrus Fruits Other Fruits Other Vegetables Population Percent Percent Percent Percent Percent Group Consuminn Mean SE Consumina Mean SE Consumina Mean SE Consumina Mean SE Consumina Mean SE Total 19.1% 0.180 0.012 20.0% 0.147 0.010 38.0% 1.236 0.039 57.7% 2.141 0.063 83.1% 1.316 0.016 Age (years) < 01 7.5% 0.180 0.177 10.1% 0.178 o.'157 24.8% 1.929 0.586 61.6% 12.855 1.284 41.7% 1.346 0.200 01-02 12.4% 0.364 0.137 14.4% 0.281 0.109 43.6% 4.237 0.459 66.4% 7.599 0.498 73.6% 2.077 0.136 03-05 14.8% 0.390 0.119 16.3% 0.177 0.063 41.0% 2.596* 0.267 70.0% 5.826 0.348 78.9% 1.979 0.102 06-11 13.3% 0.150 0.044 19.1% 0.185 0.043 40.5% 1.805 0.138 70.1% 3.242 0.126 83.2% 1.534 0.062 12-19 14.3% 0.112 0.030 14.0% 0.080 0.020 37.0% 1.130 0.085 47.3% 1.053 0.070 81.0% 0.950 0.035 20-39 18.8% 0.137 0.016 17.5% 0.100 0.015 '33.4% 0.903 0.049 44.9% 0.972 0.042 84.1% 1.081 0.022 40-69 24.4% 0.187 0.016 24.8% 0.164 0.017 39.9% 0.864 0.045 60.9% 1.255 0.038 88.3% 1.374 0.026 70 + 24.6% 0.255 0.034 29.4% 0.245 0.028 46.8% 1.155 0.069 76.1% 1.827 0.067 87.7% 1.615 0.046 Season Fall 19.6% 0.169 0.023 22.7% 0.156 0.020 38.3% 1.211 0.074 57.6% 2.354 0.171 82.5% 1.276 0.032 Spring 21.0% 0.187 0.020 19.7% 0.144 0.023 38.4% 1.225 0.072 56.4% 2.024 0.102 83.3% 1.297 0.030 Summer 15.4% 0.182 0.029 15.6% 0.094 *0.017 33.8% 1.136 0.093 60.8% 2.245 0.112 83.1% 1.332 0.032 Winter 20.0% 0.180 0.024 21.9% 0.192 0.023 41.3% 1.371 . 0.073 56.0% 1.943 0.106 83.4% 1.361 0.031 Urbanization Central City 20.5% 0.197 0.021 18.6% 0.133 0.019 39.8% 1.187 0.072 55.3% 2.090 0.100 81.4% 1.245 0.027 Non metropolitan 16.0% 0.133 0,020 18.4% 0.138 0.021 34.2% 1.153 0.074 57.8% 1.954 0.100 83.2% 1.407 0.033 Suburban 19.9% 0.190 0.019 22.0% 0.160 0.016 39.1% 1.306 0.058 59.2% 2.262 0.110 84.1% 1.319 0.023 Race Asian 30.9% 0.327 0.127 29.5% 0".221 0.118 51.0% 2.479 0.453 69.8% 3.360 0.547 85.2% 2.228 0.205 Black 25.9% 0.318 0.039 12.5% 0.104 0.029 40.1% 1.474 0.135 46.2% 1.806 0.156 78.1% 1.232 0.044 Native American 9.4% 0.126 0.092 10.5% 0.081 0.060 33.3% 0.945 0.219 50.9% 2.375 0.431 75.4% 1.077 0,107 Other/NA 15.1% 0.224 0.087 13.4% 0.106 0.071 40.3% 1.439 0.229 52.0% 2.589 0.452 76.3% 1.116 0.104 White 18.1% 0.156 0.012 21.6% 0.154 0.011 37.4% 1.178 0.041 59.8% 2.154 0.071 84.2% 1.326 0.017 Region Midwest 12.6% 0.125 0.026 . 18.7% 0.128 0.020 35.5% 1.099 0.077 59.8% 2.137 0.108 81.2% 1.186 0.029 Northeast 21.1% 0.185 0.026 22.1% 0.175 0.026 45.6% 1.430 0.079 60.5% 2.235 0.132 84.5% 1.445 0.040 South 20.5% 0.206 0.021 .16.8% 0.119 0.018 33.5% 1.090 0.067 50.3% 1.927 0.095 83.2% 1.346 0.026 West 22.6% 0.195 0.022 25.2% 0.187 0.021 41.8% 1.449 0.092 65.0% 2.414 0.182 83.8% 1.293 0.033 NOTE: SE = Standard error P = Percentile of the distribution Source: Based on EPA's analvses of the 1989-91 CSFll Table 9-7. Per Canita Intake of Exnosed Fruits ln/kn-dav as consumed) Population Percent Group Consumina Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 44.1% 1.435 0.062 0 0 0 0 0 1.402 3.496 6.075 17.823 204.28 Age (years) < 01 54.7% 9.224 1.247 0 0 0 0 2.897 12.336 26.98 33.216 75.353 204.28 01-02 55.3% 5.682 0.486 0 0 0 0 2.897 8.598 15.187 19.107 33.353 80.189 03-05 56.9% 4.324 0.344 0 0 0 0 2.305 5.766 11.65 19.049 24.123 48.728 06-11 58.8% 2.316 0.12 0 0 0 0 1.379 3.32 5.879 8.585 15.318 25.367 12-19 36.4% 0.682 0.065 0 0 0 0 0 0.871 2.158 3.214 6.703 10.766 20-39 32.7% 0.596 0.038 0 0 0 0 0 0.754 1.984 2.858 5.911 28.486 40-69 44.3% 0.716 0.031 0 0 0 0 0 1.102 2.139 3.048 5.127 13.206 70 + 57.7% 1.032 0.058 0 0 0 0 0.534 1.452 2.894 4.042 6.983 10.631 Season Fall 45.5% 1.753 0.179 0 0 0 0 0 1.521 3.64 7.537 25.206 204.28 Spring 42.6% 1.184 0.078 0 0 0 0 0 1.283 3.208 5.505 14.872 84.336 Summer 45.3% 1.44 0.113 0 0 0 0 0 1.389 3.451 6.313 17.427 98.133 Winter 43.0% 1.362 0.097 0 0 0 0 0 1.441 3.54 5.703 18.752 59.848 Urbanization Central City 42.4% 1.322 0.088 0 0 0 0 0 1.328 3.481 6.075 15.927 80.189 Nonmetropolitan 44.0% 1.335 0.097 0 0 0 0 0 1.445 3.32 5.505 16.057 84.336 Suburban 45.3% 1.553 0.112 0 0 0 0 0 1.442 3.686 6.614 20.444 204.28 Race Asian 52.3% 2.118 0.541 0 0 0 0 0.654 1.674 4.299 8.678 25.206 27.337 Black 34.6% 1.132 0.149 0 0 0 0 -0 1.045 2.888 4.618 17.351 80.189 Native American 35.7% 0.939 0.316 0 0 0 0 0 0.922 2.271 4.157 15.635 17.684 Other/NA 34.0% 1.614 0.408 0 0 0 0 0 1.659 4.084 8.529 35.073 36.71 White 46.1% 1.468 0.07 0 0 0 0 0 1.441 3.593 6.104 17.427 204.28 Region Midwest 47.3% 1.422 0.091 0 0 0 0 0 1.645 3.501 6.114 16.438 84.336 Northeast 47.3% 1.518 0.118 0 0 0 0 0 1.49 3.898 6.834 19.393 75.353 South 36.9% 1.271 0.092 0 0 0 0 0 1.177 3.104 5.695 19.91 80.189 West 49.4% 1.643 0.198 0 0 0 0 0 1.443 3.774 7.009 15.947 204.28 NOTE: SE = Standard error P = Percentile of the distribution Source: Based on EPA's analyses of the 1989-91 CSFll Table 9-8. Per Canita Intake of Protected Fruits ln/kn-dav as consumed\ Population Percent Grouo Consumina Mean SE P1 . P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 52.9% 1.692 0.037 0 0 0 0 0.598 2.316 4.687 6.717 13.019 136.69 Age (years) < 01 38.9% 3.097 0.528 0 0 0 0 0 4.353 9.963 15.242 23.624 136.69 01-02 56.7% 5.518 0.455 0 0 0 0 2.618 9.049 15.677 20.912 27.432 49.904 03-05 57.0% 3.443 0.235 0 0 0 0 1.948 5.606 9.826 13.018 17.729 35.141 06-11 56.2% 2.339 0.125 0 0 0 0 1.079 3.727 6.92 8.688 12.807 27.945 12-19 47.7% 1.401 0.081 0 0 o. 0 0.598 2.234 4.341 5.761 7.894 15.503 20-39 45.4% 1.188 0.047 0 0 0 0 0.108 1.694 3.645 4.844 8.205 29.275 40-69 57.3% 1.284 0.043 0 0 0 0 0.583 2.009 3.541 4.596 7.719 21.372 70 + 67.5% 1.78 0.072 0 0 0 0 1.236 2.706 4.363 5.779 8.611 15.003 Season Fall 50.2% 1.539 0.071 0 0 0 0 0.269 2.04 4.323 6.509 13.595 26.751 Spring 53.9% 1.75 0.072 0 0 0 0 0.688 2.407 4.681 6.787 13.032 44.68 Summer 54.1% 1.754 0.082 0 0 0 0 0.672 2.471 4.732 6.571 15.503 136.69 Winter 53.7% 1.727 0.071 0 0 0 0 0.621 2.423 4.941 6.905 12.166 30.692 Urbanization Central City 53.3% 1.632 0.069 0 0 0 0 0.625 2.276 4.497 6.099 11.535 136.69 Nonmetropolitan 49.4% 1.55 0.069 0 0 0 0 0.334 2.115 4.368 6.961 12.076 29.275 Suburban 54.7% 1.797 0.056 0 0 0 0 0.667 2.472 4.897 6.826 14.399 44.68 Race Asian 69.8% 3.279 0.429 0 0 0 0 2.052 4.382 6.981 17.729 17.729 18.792 Black 49.6% 1.861 0.126 0 0 0 0 0.621 2.695 5.64 7.241 13.572 136.69 Native American 46.8% 2.019 0.33 0 0 0 0 0.851 2.701 5.995 10.354 11.554 15.244 Other/NA 51.7% 2.014 0.263 0 0 0 0 0.845 2.472 5.759 8.88 14.279 44.68 White 53.4% 1.629 0.039 0 0 0 0 0.574 2.238 4.527 6.425 12.53 49.904 Region Midwest 49.5% 1.501 0.072 0 0 0 0 0.265 2.07 4.353 6.099 12.53 49.904 Northeast 59.4% 1.887 0.08 b 0 0 0 0.838 2.675 5.371 7.268 13.018 42.347 South 47.6% 1.56 0.064 0 0 0 0 0.465 2.147 4.443 6.39 12.076 136.69 West 60.1% 1.947 0.084 0 0 0 0 2.613 4.88 7.836 16.064 44.68 NOTE: SE = Standard error P = Percentile of the distribution Source: Based on EPA's analyses of the 1989-91 CSFll Table 9-9. Per Caoita Intake of Exoosed Veaetables la/ka-dav as consumed) Population Percent Grouo Consumina Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 84.9% 1.49 0.016 0 0 0 0.367 1.043 2.067 3.403 4.515 7.727 20.492 Age (years) < 01 42.7% 1.208 0.17 0 0 0 0 0 1.55 3.834 6.451 11.524 18.592 01-02 78.0% 2.268 0.145 0 0 0 0.299 1.132 3.616 5.855 7.404 12.808 20.492 03-05 83.6% 2.245 0.119 0 0 0 0.329 1.411 3.061 5.433 7.664 12.493 17.872 06-11. 84.7% 1.606 0.059 0 0 0 0.293 1.062 2.222 3.769 5.118 9.161 15.741 12-19 83.6% 1.181 0.04 0 0 0 0.253 0.804 1.696 2.756 3.84 5.699 12.139 20-39 86.3% 1.3 0.025 0 0 0 0.331 0.923 1.87 2.968 3.692 6.327 14.837 40-69 89.9% 1.568 0.026 0 0 0.07 0.557 1.22 2.177 3.42 4.443 6.274 13.624 70 + 86.4% 1.603 0.044 0 0 0 0.672 1.326 2.214 3.344 4.206 5.928 12.814 Season Fall 82.8% 1.383 0.033 0 0 0 0.29 0.951 1.824 3.151 4.283 8.783 18.592 Spring 85.0% 1.475 0.031 0 0 0 0.383 1.028 2.075 3.406 4.562 7.403 20.492 Summer 87.1% 1.634 0.033 0 0 0 0.432 1.272 2.289 3.68 4.765 7.399 18.283 Winter 84.9% 1.468 0.033 0 0 0 0.367 0.999 2.09 3.109 4.464 7.664 16.152 Urbanization Central City 83.6% 1.413 0,029 0 0 0 0.392 0.957 1.952 3.278 4.331 8.17 20.492 Nonmetropolitan 85.8% 1.55 0.031 0 0 0 0.471 1.185 2.146 3.499 4.59 7.283 17.872 Suburban 85.2% 1.511 0.025 0 0 0 0.356 1.055 2.098 3.464 4.683 7.664 16.152 Race Asian 83.2% 2.133 0.195 0 0 0 0.606 1.537 . 3.135 4.746 6.883 10.325 11.841 Black 81.8% 1.472 0.051 0 0 0 0.308 0.908 1.88 3.217 4.989 9.219 16.141 Native American 75.4% 1.501 0.141 0 0 0 0.168 1.018 2.423 3.445 4.155 6.424 8.189 Other/NA 85.4% 1.682 0.092 0 0 0 0.338 1.287 2.748 3.644 4.697 6.933 8.368 White 85.6% 1.476 0.017 0 0 0 0.371 1.045 2.067 3.376 4.464 7.359 20.492 Region Midwest 80.9% 1.215 0.029 0 0 0 0.239 0.824 1.683 2.843 3.834 6.35 20.492 Northeast 84.7% 1.561 0.041 0 0 0 0.378 1.051 2.126 3.564 4.994 8.243 18.283 South 86.7% 1.609 0.027 0 0 0 0.434 1.208 2.254 3.575 4.562 7.404 14.568 West 86.6% 1.546 0.035 0 0 0 0.424 1.127 2.158 3.524 4.7 7.664 16.152 NOTE: SE = Standard error P = Percentile of the distribution Source: Based on EPA's analyses of the 1989-91 CSFll Table 9-10. Per Caoita Intake of Protected Veaetables la/ka-dav as consumed\ Population Percent Grouo Consumina Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 34.0% 0.332 0.012 0 0 0 0 0 0.414 1.038 1.637 3.394 14.4 Age (years) < 01 30.9% 1.144 0.192 0 0 0 0 0 1.435 4.584 6.25 8.752 14.4 01-02 41.6% 0.794 0.104 0 0 0 0 0 1.201 2.232 3.766 6.488 9.74 03-05 39.8% 0.703 0.081 0 0 0 0 0 1.205 2.443 3.053 4.811 11.3 06-11 44.3% 0.5 0.035 0 0 0 0 0 0.848 1.439 2.058 3.32 8.6 12-19 30.1% 0.229 **0.025 0 0 0 0 0 0.332 0.824 1.339 2.138 4.94 20-39 31.6% 0.233 0.015 0 0 0 0 0 0.323 0.78 1.161 2.427 5.6 40-69 32.4% 0.239 0.014 0 0 0 0 0 0.362 0.772 1.164 2.033 6.25 70 + 34.6% 0.303 0.028 0 0 0 0 0 0.427 1.015 1.491 2.291 5.34 Season Fall 34.1% 0.336 0.025 0 0 0 0 0 0.394 1.064 1.725 3.674 11.3 Spring 34.8% 0.32 0.024 0 0 0 0 0 0.421 0.96 1.435 3.493 14.4 Summer 32.5% 0.334 0.024 0 0 0 0 0 0.411 1.116 1.7 3.492 10.4 Winter 34.4% 0.337 0.022 0 0 0 0 0 0.42 1.109 1.724 2.945 8.68 Urbanization Central City 31.7% 0.303 0.022 0 0 0 0 *o 0.354 0.971 1.619 3.098 14.4 Nonmetropolitan 37.9% 0.396 0.024 0 0 0 0 0 0.514 1.22 1.725 3.826 11.3 Suburban 33.1% 0.32 0.018 0 0 0 0 0 0.39 1.029 1.591 3.32 14.1 Race Asian 16.1% 0.166 0.081 0 0 0 0 0 0 0.636 1.201 1.506 3.17 Black 37.3% 0.411 0.038 0 0 0 0 0 0.502 1.29 2.014 4.579 9.07 Native American 32.7% 0.38 0.095 0 0 0 0 0 0.446 1.062 1.826 2.85 4.64 Other/NA 22.9% 0.221 0.074 0 0 0 0 0 0 0.644 1.369 2.767 5.6 White 34.1% 0.326 0.013 0 0 0 0 0 0.413 1.014 1.587 3.317 14.4 Region Midwest 35.8% 0.344 0.022 0 0 0 0 0 0.46 1.127 1.674 3.013 11.3 Northeast 32.4% 0.369 0.036 0 0 0 0 0 0.376 1.102. 1.835 5.022 14.1 South 36.8% 0.358 0.019 0 0 0 0 0 0.48 1.093 1.726 3.484 14.4 West 28.4% 0.236 0.022 0 0 0 0 0 0.178 0.791 1.257 2.688 6.25 NOTE: SE = Standard error P = Percentile of the distribution Source: Based on EPA's analvses of the 1989-91 CSFll Table 9-11. Per Canita Intake of Root Veaetables ln/kn-dav as consumed\ Population Percent Groun Consumina Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 80.7% 1.245 0.015 0 0 0 0.226 0.832 1.675 2.974 4.029 7.074 30.609 Age (years) < 01 52.4% 1.857 0.204 0 0 0 0 0.184 2.66 5.337 8.233 12.5 30.609 01-02 76.2% 2.398 0.129 0 0 0 0.52 1.879 3.542 5.695 7.084 10.449 16.27 03-05 77.9% 1.914 0.096 0 0 0 0.203 1.344 2.998 4.596 6.14 7.505 17.416 06-11 84.4% 1.85 0.065 0 0 0 0.381 1.23 2.638 4.449 6.018 8.165 17.107 12-19 81.4% 1.29 0.045 0 0 0 0.279 0.909 1.739 3.051 4.177 5.74 24.949 20-39 81.6% 0.988 0.02 0 0 0 0.182 0.717 1.37 2.385 3.096 5.025 8.002 40-69 82.8% 1.059 0.021 0 0 0 0.244 0.807 1.488 2.454 3.087 4.983 9.043 70 + 80.6% 1.109 0.04 0 0 0 0.312 0.821 1.549 2.535 3.203 5.636 10.723 Season Fall 80.6% 1.324 0.032 0 0 0 0.213 0.893 1.756 3.238 4.402 7.484 15.625 Spring 80.5% 1.204 0.029 0 0 0 0.228 0.858 1.557 2.752 3.889 6.644 30.609 Summer 80.3% 1.102 0.031 0 0 0 0.152 0.655 1.452 2.669 3.858 7.751 24.949 Winter 81.5% 1.348 0.029 0 0 0 0.339 0.97 1.953 3.1 4.137 5.989 17.416 Urbanization Central City 77.6% 1.167 0.029 0 0 0 0.176 . 0.755 1.545 2.826 3.903 7.505 30.609 Nonmetropolitan 82.3% 1.33 0.03 0 0 0 0.311 0.893 1.795 3.256 4.422 6.946 19.449 Suburban 81.9% 1.254 0.023 0 0 0 0.21 0.861 1.708 2.972 4.017 7.079 17.416 Race Asian 55.0% 0.743 0.146 0 0 0 0 0.274 0.814 1.764 3.546 7.269 10.702 Black 73.8% 1.309 0.052 0 0 0 0.134 0.761 1.627 3.337 5.358 7.968 17.534 Native American 78.9% 1.791 0.137 0 0 0 0.655 1.47 2.762 3.858 4.705 7.067 13.578 Other/NA 65.4% 1.239 0.11 0 0 0 0 0.635 1.75 3.38 4.861 8.253 10.415 White 82.9% 1.237 0.016 0 0 0 0.25 0.858 1.673 2.887 3.942 6.651 30.609 Region Midwest 82.2% 1.361 0.033 0 0 0 0.29 0.889 1.844 3.238 4.386 7.968 19.449 Northeast 80.2% 1.304 0.037 0 0 0 0.21 0.912 1.781 3.212 4.246 7.022 24.949 South 81.2% 1.183 0.024 0 0 0 0.25 0.796 1.591 2.82 3.906 6.926 30.609 West 78.5% 1.15 0.032 0 0 0 0.146 0.786 1.56 2.673 3.683 7.269 13.578 NOTE: SE = Standard error P = Percentile of the distribution Source: Based on EPA's.analvses of the 1989-91 CSFll Table 9-12. Mean Daily Intake of Fruits and Vegetables Per Individual in a Day for USDA 1977-78, 87-88, 89-91, 94, and 95 Surveys Food Produci 77-78 Data 87-88 Data* 89-91 Data 94 Data 95 Data (g/day) (g/day) (g/day) (g/day) (g/day) Fruits 142 142 156 171 173 Vegetables 201 182 179 186 188 Source: USDA, 1980; 1992; 1996a; 1996b.

Table 9-13. Mean Per Capita Intake Rates (as consumed) for Fruits and Vegetables Based on All Sex/Age/Demographic Subgroups Average Consumption Raw Agricultural Commodity" (Grams/ka Bodv Weiaht-Davl Standard Error Alfalfa Sprouts 0.0001393 0.0000319 Apples-Dried 0.0002064 0.0000566 Apples-Fresh 0.4567290 0.0142203 Apples-Juice 0.2216490 0.0142069 Apricots-Dried 0.0004040 0.0001457 Apricots-Fresh 0.0336893 0.0022029 Artichokes-Globe 0.0032120 0.0007696 Artichokes-Jerusalem 0.0000010

Asparagus 0.0131098 0.0010290 Avocados 0.0125370 0.0020182 Bamboo Shoots 0.0001464 0.0000505 Bananas-Dried 0.0004489 0.0001232 Bananas-Fresh 0.2240382 0:0088206 Bananas-Unspecified 0.0032970 0.0004938 Beans-Dry-Blackeye Peas (cowpeas) 0.0024735 0.0005469 Beans-Dry-Broad Beans (Mature 0.0000000
Seed) Beans-Dry-Garbanzo (Chick Pea) 0.0005258 0.0001590 Beans-Dry-Great Northern 0.0000010
Beans-Dry-Hyacinth (Mature Seeds) 0.0000000
Beans-Dry-Kidney 0.0136313 0.0045628 Beans-Dry-Lima 0.0079892 0.0016493 Beans-Dry-Navy (Pea) 0.0374073 0.0023595 Beans-Dry-Other 0.0398251 0.0023773 Beans-Dry-Pigeon Beans 0.0000357 0.0000357 Beans-Dry-Pinto 0.0363498 0.0048479 Beans-Succulent-Broad Beans 0.0000000 * (Immature Seed) Beans-Succulent-Green 0.2000500 0.0062554 Beans-Succulent-Hyacinth (Young 0.0000000
Pods) Beans-Succulent-Lima 0.0256648 0.0021327 Beans-Succulent-Other 0.0263838 0.0042782 Beans-Succulent-Yellow, Wax 0.0054634 0.0009518. Beans-Unsoecified 0.0052345 0.0012082 Table 9-13. Mean Per Capita Intake Rates (as consumed) for Fruits and Vegetables Based on All Sex/Age/Demographic Subgroups (continued) Average Consumption Raw Agricultural Commodity" (Grams/k!l Body Weight-Day) Standard Error Beets-Roots 0.0216142 0.0014187 Beets-Tops (Greens) 0.0008287 0.0003755 Bitter Melon 0.0000232 0.0000233 Blackberries 0.0064268 0.0007316 Blueberries 0.0090474 0.0008951 Boysenberries 0.0007313 0.0006284 Bread Nuts 0.0000010
Bread Fruit 0.0000737 0.0000590 Broccoli 0.0491295 0.0032966 Brussel Sprouts 0.0068480 0.0009061 Cabbage-Chinese/Celery, Inc. Bok 0.0045632 0.0020966 Choy Cabbage-Green and Red 0.0936402 0.0039046 Cactus Pads 0.0000010
Cantaloupes 0.0444220 0.0029515 Caram bola 0.0000010
Carob 0.0000913 0.0000474 Carrots 0.1734794 0.0041640 Casabas 0.0007703 0.0003057 Cassava (Yuca Blanca) 0.0002095 0.00001574 Cauliflower 0.0158368 0.0011522 -Celery 0.0609611 0.0014495 Cherimoya 0.0000010
Cherries-Dried . 0.0000010
Cherries-Fresh 0.0321754 0.0024966 Cherries-Juice 0.0034080 0.0009078 Chicory (French or Belgian Endive) 0.0006707 0.0001465 Chili Peppers 0.0000000
Chives 0.0000193 0.0000070 Citrus Citron 0.0001573 0.0000324 Coconut-Copra 0.0012860 0.0000927 Coconut-Fresh 0.0001927 0.0000684 Coconut-Water 0.0000005 0.0000005 Table 9-13. Mean Per Capita Intake Rates (as consumed) for Fruits and Vegetables Based on All Sex/Ag.e/Demographic Subgroups (continued) Average Consumption Raw Agricultural Commodity' (Grams/ka Bodv Weiaht-Davl Standard Error Collards 0.0188966 0.0032628 Corn, Pop 0.0067714 0.000334.8 Com, Sweet 0.2367071 0.0062226 Crabapples 0.0003740 . Cranberries 0.0150137 0.0006153 Cranberries-Juice 0.0170794 0.0022223 Crenshaws 0.0000010 . Cress, Upland 0.0000010 . Cress, Garden, Field 0.0000000 . Cucumbers 0.0720821 0.0034389 Currants 0.0005462 0.0000892 Dandelion 0.0005039 0.0002225 Dates 0.0006662 0.0001498 Dewberries 0.0023430 . Eggplant 0.0061858 0.0007645 ( Elderberries 0.0001364 0.0001365 Endive, Curley and Escarole 0.0011851 0.0001929 Fennel 0.0000000 . Figs 0.0027847 0.0005254 Garlic 0.0007621 0.0000230 Genip (Spanish Lime) 0.0000010 . Ginkgo Nuts 0.0000010 . Gooseberries 0.0003953 0.0001341 Grapefruit-Juice 0.0773585 0.0053846 Grapefruit-Pulp 0.0684644 0.0032321 Grapes-Fresh 0.0437931 0.0023071 Grapes-Juice 0.0900960 0.0058627 Grapes-Leaves 0.0000119 0.0000887 Grapes-Raisins 0.0169730 0.0009221 Groundcherries (Poha or Cape-0.0000000 . Gooseberries) Guava 0.0000945 0.0000558 Honevdew Melons 0.0183628 0.0042879 Table 9-13. Mean Per Capita Intake Rates (as consumed) for Fruits and Vegetables Ba_sed on All Sex/Age/Demographic Subgroups (continued) Average Consumption Raw Agricultural Commodity" (Grams/kg Body Weight-Day) Standard Error Huckleberries (Gaylussacia) 0.0000010 .. Juneberry 0.0000010 . Kale 0.0015036 0.0006070 Kiwi 0.0000191 0.0000191 Kohlrabi 0.0002357 0.0001028 Kumquats 0.0000798 0.0000574 Lambsquarter 0.0000481 0.0000481 Leafy Oriental Vegetables 0.0000010 . Leeks 0.0000388 0.0000221 Lemons-Juice 0.0189564 0.0009004 Lemons-Peel 0.0002570 0.0001082 Lemons-Pulp 0.0002149 0.0000378 Lemons-Unspecified 0.0020695 0.0003048 Lentiles-Split 0.0000079 . 0.0000064 Len tiles-Whole 0.0012022 0.0002351 Lettuce-Head Varieties 0.2122803 0.0059226 Lettuce-Leafy Varieties 0.0044328 0.0003840 Lettuce-Unspecified 0.0092008 0.0004328 Limes-Juice 0.0032895 0.0005473 Limes-Pulp 0.0000941 0.0000344 Limes-Unspecified 0.0000010 . Loganberries 0.0002040 . Logan Fruit 0.0000010 . Loquats 0.0000000 . Lychee-Dried 0.0000010 . Lychees (Litchi) 0.0000010 . Maney (Mammee Apple) 0.0000010 . Mangoes 0.0005539 0.0002121 Mulberries 0.0000010 . Mung Beans (Sprouts) 0.0066521 0.0006462 Mushrooms 0.0213881 0.0009651 Mustard Greens 0.0145284 0.0024053 Table 9-13. Mean Per Capita Intake Rates (as consumed) for Fruits and Vegetables Based on All Sex/Age/Demographic Subgroups (continued) Average Consumption Raw Agricultural Commoditv' (Grams/kg Body Weight-Dav) Standard Error Nectarines 0.0129663 0.0013460 Okra 0.0146352 0.0017782 Olives 0.0031757 0.0002457 Onions-Dehydrated or Dried 0.0001192 0.0000456 Onions-Dry-Bulb (Cipollini) 0.1060612 0.0021564 Onions-Green 0.0019556 0.0001848 Oranges-Juice 1.0947265 0.0283937 Oranges-Peel 0.0001358 0.0000085 Oranges-Pulp 0.1503524 0.0092049 Papayas-Dried 0.0009598 0.0000520 Papayas-Fresh 0.0013389 0.0005055 Papayas-Juice 0.0030536 0.0012795 Parsley Roots 0.0000010
Parsley 0.0036679 0.0001459 Parsnips 0.0006974 0.0001746 Passion Fruit (Granadilla) 0.0000010
Pawpaws 0.0000010
Peaches-Dried 0.0000496 0.0000152 Peaches-Fresh 0.2153916 0.0078691 Pears-Dried 0.0000475 0.0000279 Pears-Fresh 0.1224735 0.0050442 Peas (Garden)-Green Immature 0.1719997 0.0067868 Peas (Garden)-Mature Seeds, Dry 0.0017502 0.0002004 Peppers, Sweet, Garden 0.0215525 0.0010091 Peppers-Other 0.0043594 0.0004748 Persimmons 0.0004008 0.0002236 Persian Melons 0.0000010
Pimentos 0.0019485 0.0001482 Pineapple-Dried 0.0000248 0.0000195 Pineapple-Fresh, Pulp 0.0308283 0.0017136 Pineapple-Fresh, Juice 0.0371824 0.0026438 Pitanoa !Surinam Cherrv) 0.0000010
Table 9-13. Mean Per Capita Intake Rates (as consumed) for Fruits and Vegetables Based on All Sex/Age/Demographic Subgroups (continued) Average Consumption Raw AQricultural Commodity" (Grams/kg Body WeiQht-Day) Standard Error Plantains 0.0016370 0.0007074 Plums, Prune-Juice 0.0137548 0.0017904 Plums (Damsons)-Fresh 0.0248626 0.0020953 Plums-Prunes (Dried) 0.0058071 0.0005890 Poke Greens 0.0002957 0.0001475 Pomegranates 0.0000820 0.0000478 Potatoes (White)-Whole 0.3400582 0.0102200 Potatoes (White )-Unspecified 0.0000822 0.0000093* Potatoes (White)-Peeled 0.7842573 0.0184579 Potatoes (White)-Dry 0.0012994 0.0001896 Potatoes (White)-Peel Only 0.0000217 0.0000133 Pumpkin 0.0044182 0.0004354 Quinces 0.0001870 . Radishes-Roots 0.0015558 0.0001505 Radishes-Tops 0.0000000 . Raspberries 0.0028661 0.0005845 Rhubarb 0.0037685 0.0006588 Rutabagas-Roots 0.0027949 0.0009720 Rutabagas-Tops 0.0000000 . Salsify (Oyster Plant) 0.0000028 0.0000028 Shallots 0.0000000 . Soursop (Annona Muricata) 0.0000010 . Soybeans-Sprouted Seeds 0.0000000 . Spinach .0.0435310 0.0030656 Squash-Summer 0.0316479 0.0022956 : Squash-Winter 0.0324417 0.0026580 Strawberries 0.0347089, 0.0020514 Sugar Apples (Sweetsop) 0.0000010 . Sweetpotatoes (including Yams) 0.0388326 0.0035926 Swiss Chard 0.0016915 0.0004642 Tangelos 0.0025555 0.0006668 Tanaerine-Juice 0.0000839 0.0000567 Table 9-13. Mean Per Capita Intake Rates (as consumed) for Fruits and Vegetables Based on All Sex/Age/Demographic Subgroups (continued) Average Consumption Raw Aciricultural Commoditv" (Grams/kq Body Weight-Dav) Standard Error Tangerines 0.0088441 0.0010948 Tapioca 0.0012199 0.0000951 Taro-Greens 0.0000010 . Taro-Root 0.0000010 . Tomatoes-Catsup 0.0420320 0.0015878 Tomatoes-Juice 0.0551351 0.0029515 Tomatoes-Paste 0.0394767 0.0012512 Tomatoes-Puree 0.17012311 0.0054679 Tomatoes-Whole 0.4920164 0.0080927 Towelgourd 0.0000010 . Turnips-Roots 0.0082392 0.0014045 Turnips-Tops 0.0147111 0.0025845 Water Chestnuts 0.0004060 0.0000682 Watercress 0.0003553 0.0001564 Watermelon 0.0765054 0.0068930 Yambean, Tuber 0.0000422 0.0000402 Yautia, Tannier 0.0000856 0.0000571 Younqberries 0.0003570 .
Not reported
Consumed in any raw or prepared form Source: ORES data base (based on 1977-78 NFCS data).

Table 9-14. Mean Total Fruit Intake (as consumed) in a Day by Sex and AQe (1977-1978)' Age (yr) Per Capita Intake Percent of Population Using Intake (g/day) for Users Onlyb lo/davl Fruit in a Dav Males and Females 1 and under 169 86.8 196 1-2 146 62.9 231 3-5 134 56.1 239 6-8 152 60.1 253 Males . 9-11 133 50.5 263 12-14 120 51.2 236 15-18 147 47.0 313 19-22 107 39.4 271 23-34 141 46.4 305 35-50 115 44.0 262 51-64 171 62.4 275 65-74 174 62.2 281 75 and over 186 62.6 197 Females 9-11 148 59.7 247 12-14 120 48.7 247 15-18 126 49.9 251 19-22 133 48.0 278 23-34 122 47.7 255 35-50 133 52.8 252 51-64 171. 66.7 256 65-74 179 69.3 259 75 and over 189 64.7 292 Males and Females All aaes 142 54.2 263 ' Based on USDA Nationwide Food Consumption Survey (1977-1978) data for one day. b Intake for users only was calculated by dividing the per capita intake rate by the fraction of the population using fruit in a day. Source: USDA 1980. Table 9-15. Mean Total Fruit Intake (as consumed) in a Dav bv Sex and Ac:ie (1987-1988)* Percent of Population Using Intake (g/day) for Users Only" Aae lvrl Per Canita Intake ln/dav\ Fruit in 1 Dav Males and Females 5 and under 157 59.2 265 Males 6-11 182 63.8 285 12-19 158 49.4 320 20 and over 133 46.5 286 Females 6-11 154 58.3 264 12-19 131 47.1 278 20 and over 140 52.7 266 Males and Females All Aaes 142 51.4 276 a Based on USDA Nationwide Food Consumption Survey (1987-1988) data for one day. b Intake for users only was calculated by dividing the per capita intake rate by the fraction of the population using fruits in a day. Source: USDA 1992b. ' Table 9-16. Mean Total Vegetable Intake (as consumed) in a Day by Sex and Age (1977-1978)* Age (yr) Per Capita Intake Percent of Population Using Intake (g/day) for Users (g/day) Vegetables in a Day Onlv" Males and Females 1 and under 76 62.7 121 1-2 91 78.0 116 3-5 100 79.3 126 6-8 136 84.3 161 Males 9-11 138 83.5 165 12-14 184 84.5 217 15-18 216 85.9 251 19-22 226 84.7 267 23-34 248 88.5 280 50 261 86.8 300 51-64 285 90.3 316 65-74 265 88.5 300 75 and over 264 93.6 281 Females 9-11 139 83.7 166 12-14 154 84.6 183 15-18 178 83.8 212 19-22 184 81.1 227 23-34 187 84.7 221 35-50 187 84.6 221 51-64 229 89.8 255 65-74 221 87.2 253 75 & over 198 88.1 226 Males and Females All Aaes 201 85.6 235 a Based on USDA Nationwide Food Consumption Survey (1977-1978) data for one day. b Intake for users only was calculated by dividing the per capita intake rate by the fraction of the population using vegetables in a day. Source: USDA 1980. Table 9-17. Mean Total Veqetable Intake (as consumed) in a Dav by Sex and Aqe (1987-1988)* Percent of Population Using Aae (vr\ Per Caaita Intake (a/dav\ Veaetables in a Dav Intake (o/dav\ for Users Onlv" Males and Females 5 and under 81 74.0 109 Males 6-11 129 86.8 149 12-19 173 85.2 203 20 and over 232 85.0 273 Females 6-11 129 80.6 160 12-19 129 75.8 170 20 and over 183 82.9 221 Males and Females AllAaes 182 82.6 220 a Based on USDA Nationwide Food Consumption Survey (1987-1988) data for one day. b Intake for users only was calculated by dividing the per capita intake rate by the fraction of the population using vegetables in a day. Source: USDA 1992b. Table 9-18. Mean Total Fruit Intake {as consumed) in a Dav bv Sex and Aae (1994 and 1995)' Percent of Population Using Aoe fvrl Per Canita Intake la/davl Fruit in 1 Dav Intake (a/davl for Users Onlvb 1994 1995 1994 1995 1994 1995 Males and Females 5 and under 230 221 70.6 72.6 326 304 Males 6-11 176 219 59.8 62.2 294 352 12-19 169 210 44.0 47.1 384 446 20 and over 175 170 50.2 49.6 349 342 Females 6-11 174 172 59.3 63.6 293 270 12-19 148 167 47.1 44.4 314 376 20 and over 157 155 55.1 54.4 285 285 Males and Females All Aaes 171 173 54.1 54.2" 316 319 a Based on USDA CSFll (1994 and 1995) data for one day. b Intake for users only was calculated by dividing the per capita intake rate by the fraction of the population using fruits in a day. Source: USDA 1996a* 1996b. Table 9-19. Mean Total VeQetable Intake las consumed\ in a Dav bv Sex and Aae 11994 and 19951* Percent of Population Using Aae lvr\ Per Caoita Intake (a/dav\ Veaetables in 1 Da" Intake ln/da*i\ for Users Onlvb 1994 1995 1994 1995 1994 1995 Males and Females 5 and under 80 83 75.2 75.0 106 111 Males 6-11 118 111 82.4 80.6 143 138 12-19 154 202 74.9 79.0 206 256 20 and over 242 241 85.9 86.4 282 278 Females 6-11 115 108 82.9 79.1 139 137 12-19 132 144 78.5 76.0 168 189 20 and over 190 189 84.7 83.2 224 227 Males and Females All Aaes 186 188 83.2 82.6 223 228 a Based on USDA CSFll (1994 and 1995) data for one day. b Intake for users only was calculated by dividing the per capita intake rate by the fraction of the population using vegetables in a day. Source: USDA 1996a* 1996b. Table 9-20. Mean Per Capita Intake of Fats and Oils (g/day as consumed) in a Day by Sex and Age (1994 and 1995)" Total Fats and Oilsb Table Fats0 Salad Dressingsd 1994 1995 1994 1995 1994 1995 Males and Females 5 and 4 3 2 2 2 1 under Males 6-11 8 7 3 3 5 4 12-19 11 14 2 5 8 10 20 and 19 18 5 5 11 10 over Females 6-11 7 8 3 3 4 4 12-19 9 9 2 3 6 6 20 and 16 14 4 5 10 7 over Males and Females AllAqes 14 14. 4 4 9 8 a Based on USDA CSFll 1994 and 1995 data for one day. b Table fats, cooking fats, vegetable oils, salad dressings, nondairy cream substitutes, sauces that are mainly fat and oil. c Butter, margarines, blends of butter with margarines or vegetable oils, and butter replacements. d Regular and reduced-and low-calorie dressings and mayonnaise. Source: USDA 1996a-1996b. Table 9-21. Mean and Standard Error for the Per Capita Dailv Intake of Food Class and Subclass bv Region (g/dav as consumed) US population Northeast North Central South West Total Produce 282.6 +/- 3.5 270.6 +/- 6.9 282.4 +/- 6.7 280.7 +/- 5.6 303.1 +/- 8.2 Leafy" 39.2 +/- 0.8 38.1 +/- 1.5 37.1 +/- 1.5 38.4 +/- 1.2 45.3 +/- 1.8 Exposedb 86.0 +/- 1.5 88.5 +/- 3.0 87.8 +/- 2.9 76.9 +/- 2.4 95.5 +/- 3.6 Protected' 150.4 +/- 2.3 137.2 +/- 4.5 150.1+/-4.3 160.1 +/- 3.6 . 152.5 +/- 5.3 Other 7.0 +/- 0.3 6.9 +/- 0.6 7.3 +/- 0.5 5.4 +/- 0.4 9.8 +/- 0.7 a Produce belonging to this category include: cabbage, cauliflower, broccoli, celery, lettuce, and spinach. b Produce belonging to this category include: apples, pears, berries, cucumber, squash, grapes, peaches, apricots, plums, prunes, string beans, pea pods, and tomatoes. ' Produce belonging to this category include: carrots, beets, turnips, parsnips, citrus fruits, sweet corn, legumes (peas, beans, etc.), melons, onion, and potatoes. NOTE: Northeast= Maine, New Hampshire, Vermont, Massachusetts, Connecticut, Rhode Island, New York, New Jersey, and Pennsylvania. North Central = Ohio, Illinois, Indiana, Wisconsin, Michigan, Minnesota, Iowa, Missouri, North Dakota, South Dakota, Nebraska, and Kansas. South = Maryland, Delaware, District of Columbia, Virginia, West Virginia, North Carolina, South Carolina, Georgia, Florida, Kentucky, Tennessee, Alabama, Mississippi, Arkansas, Louisiana, Texas, and Oklahoma. West= Montana, Idaho, Wyoming, Utah, Colorado, New Mexico, Arizona, Nevada, Washington, Oregon, and California. Source: U.S. EPA, 1984b (based on 1977-78 NFCS data). Table 9-22.Mean and Standard Error for the Daily Intake of Food Subclasses Per Capita by Age (g/day as consumed) Age (years) Leafy produce* Exposed produceb Protected produce' Other produce All Ages 39.2 +/- 0.8 86.0 +/- 1.5 150.4 +/- 2.3 7.0 +/- 0.3 <1 3.2 +/- 4.9 75.5 +/- 9.8 50.8 +/- 14.7 25.5 +/- 1.8 1-4 9.1+/-2.4 55.6 +/- 4.8 94.5 +/- 7.2 5.1+/-0.9 5-9 20.1+/-2.0 69.2 +/- 4.8 128.9 +/- 6.1 4.3 +/- 0.8 10-14 26.1 +/- 1.9 76.8 +/- 3.8 151.7+/-5.7 8.1 +/- 0.7 15-19 31.4 +/- 2.0 71.9 +/- 4.0 156.6 +/- 6.0 6.2 +/- 0.7 20-24 35.3 +/- 2.6 65.6 +/- 5.2 144.5 +/- 7.8 5.0 +/- 1.0 25-29 41.4+/-2.7° 73.4 +/- 5.3 149.8 +/- 8.0 7.0 +/- 1.0 30-39 44.4 +/- 2.1 77.1 +/- 4.2 150.5 +/- 6.3 6.1 +/- 0.8 40-59 51.3+/-1.6 94.7 +/- 3.3 162.9.+/- 4.9 6.9 +/- 0.6 ;, 60 45.4 +/- 1.8 114.2 +/- 3.6 163.9 +/- 5.5 7.6 +/- 0.7 a Produce belonging to this category include: cabbage, cauliflower, broccoli, celery, lettuce, and spinach. b Produce belonging to this category include: apples, pears, berries, cucumber, squash, grapes, peaches, apricots, plums, prunes, string beans, pea pods, and tomatoes. ' Produce belonging to this category include: carrots, beets, turnips, parsnips, citrus fruits, sweet corn, legumes (peas, beans, etc.), melons, onion, and potatoes. Source: U.S. EPA, 1984a (based on 1977-78 NFCS data). Table 9-23. Consumption of Foods (g dry weight/day) for Different Age Groups and Estimated Lifetime Average Daily Food Intakes for a US Citizen (averaged across sex) Calculated from the FDA Diet Data Age (in years) Estimated Lifetime (0-1) (1-5) (6-13) (14-19) (20-44) (45-70) Intake* Potatoes 5.67 10.03 14.72 19.40 17.28 14.79 15.60 Leafy Veg. 0.84 0.49 0.85 1.22 2.16 2.65 1.97 Legume Veg. 3.81 4.56 6.51 8.45 9.81 9.50 8.75 Root Veg. 3.04 0.67 1.20 1.73 1.77 1.64 1.60 Garden fruits 0.66 1.67 2.57 3.47 4.75 4.86 4.15 Peanuts 0.34 2.21 2.56 2.91 2.43 1.91 2.25 Mushrooms 0.00 0.01 0.03 0.04 0.14 0.06 0.08 Veg. Oils 27.62. 17.69 27.54 37.04 37.20 27.84 31.24

The estimated lifetime dietary intakes were estimated by: Estimated lifetime= IR(0-1) + 5yrs *IR (1-5) + 8 yrs* IR (6-13) + 6 yrs* IR (14-19) + 25 yrs* IR (20-44) + 25 yrs* IR (45-70) 70 years where IR= the intake rate for a specific age group. Source: U.S. EPA, 1989 (based on 1977-78 NFCS and NHANES II data).

Table 9-24. Mean Daily Intake of Foods (grams) Based on the Nutrition Canada Dietary Survey" Fruit and Vegetables Not Nuts and Ane lvrs\ SamoleSize Fruit Products lncludina Potatoes Potatoes Leaumes Males and Females 1-4 1031 258 56 75 6 5-11 1995 312 83 110 13 Males 12-19 1070 237 94 185 20 20-39 999 244 155 189 15 40-64 1222 194 134 131 15 65+ 881 165 118 124 8 Females 12-19 1162 237 97 115 15 20-39 1347 204 134 99 8 40-64 1500 239 136 79 10 65+ 818 208 103 80 5 Pregnant Females ---769 301 156' 114 15 a Report does not specify whether means were calculated per capita or for consumers only. The reported values are consistent with the as consumed intake rates for consumers only reported by USDA (1980). Source: Canadian Department of National Health and Welfare n.d. Table 9-25. Per Caoita Consumotion of Fresh Fruits and Veoetables in 1991" Fresh Fruits Fresh Venetables Per Capita Per Capita Food Item Consumption Food Item Consumption (a/dav)b ln/dav\b Citrus Artichokes 0.62 Oranges (includes Temple 10.2 Asparagus 0.75 oranges) 1.6 Snap Beans 1.4 Tangerines and Tangelos 3.1 Broccoli 3.5 Lemons 0.9 Brussel Sprouts 0.4 Limes 7.1 Cabbage 9.5 Grapefruit 22.9 Carrots 9.0 Total Fresh Citrus Cauliflower 2.2 Celery 7.8 Non citrus 21.8 Sweet Corn 6.6 Apples 0.1 Cucumber 5.2 Apricots 1.7 Eggplant 0.5 Avocados 31.2 Escarole/Endive 0.3 Bananas 0.5 Garlic 1.6 Cherries 0.4 Head Lettuce 30.2 Cranberries 8.2 Onions 18.4 Grapes 0.5 Bell Peppers 5.8 Kiwi Fruit 1.0 Radishes 0.6 Mangoes 7.6 Spinach 0.9 Peaches & Nectarines 3.7 Tomatoes 16.3 Pears 2.2 Total Fresh Vegetables 126.1 Pineapple 0.3 Papayas 1.7 Plums and Prunes 4.1 Strawberries 85.0 Total Fresh Noncitrus 107.7 Total Fresh Fruits

Based on retail-weight equivalent. Includes imports; excludes exports and foods grown in home gardens. Data for 1991 used. b Original data were presented in lbs/yr; data were converted to g/day by multiplying by a factor of 454 g/lb and dividing by 365 days/yr. Source: USDA 1993.

Table 9-26. Quantity (as consumed) of Fruits and Vegetables Consumed Per Eating Occasion and the Percentage of Individuals Using These Foods in Three Days Consumers-only Food category % lndiv. using Quantity consumed per eating Quantity consumed per eatinq occasion at specified percentiles (g)' food in 3 days occasion (g) 5 25 50 75 90 95 99 Average Standard Deviation Raw vegetables White potatoes 74.4 125 90 29 63 105 170 235 280 426 Cabbage and coleslaw 9.7 68 45 15 40 60 90 120 120 240 Carrots 5 43 40 4 13 31 55 100 122 183 Cucumbers 5.6 80 76 8 24 70 110 158 220 316 Lettuce and tossed salad 50.7 65 59 10 20 55 93 140 186 270 Mature onions 8.5 31 33 3 17 18 36 57 72 180 Tomatoes 27.8 81 55 30 45 62 113 123 182 246 Cooked vegetables Broccoli 6.2 112 68 30 78 90 155 185 190 350 Cabbage 4.7 128 83 28 75 145 150 225 300 450 Carrots 9.8 70 59 19 46 75 92 150 155" 276 Com, whole kernel 23.9 95 56 21 65 83 123 170 170 330 Lima beans 2.8 110 75 21 67 88 170 175 219 350 Mixed vegetables 3.4 117 69 28 91 94 182 187 187 374 Cowpeas, field peas, black-2.9 131 88 22 88 88 175 196 350 350 eyed peas , Green peas 18.3 90 57 20 43 85 85 170 170 330 Spinach 4.5 121 70 24 78 103 185 205 205 380 String beans 27.3 86 54 18 67 70 135 140 140 280 Summer squash 2.8 145 98 27 105 108 215 215 352 430 Sweet potatoes 4.1 136 87 38 86 114 185 225 238 450 Tomato juice 3.9 91 122 91 122 182 243 243 363 486 Cucumber pickles 9.2 45 45 7 16 30 65 90 130 222 Fruits Grapefruit 4.7 159 58 106 134 134 165 268 268 330 Grapefruit juice 3.6 202 99 95 125 186 247 250 375 500 Oranges 9 146 57 73 145 145 145 180 228 360 Orange juice 35.5 190 84 95 125 187 249 249 311 498 Apples 18.2 . 141 49 69 138 138 138 212 212 276 Applesauce, cooked apples 9.8 134 86 28 64 128 130 255 155 488 Apple juice 3.8 191 101 63 124 186 248 248 372 496 Cantaloupe 3.3 171 91 61 136 136 272 272 272 529 Raw peaches 4.5 160 75 76 152 152 152 304 304 456 Raw pears 3.1 163 69 82 164 164 164 164 328 328 Raw strawberries 2.1 100 58 37 75 75 149 149 180 298 ' Percentiles are cumulative; for example, 50 percent of people eat 105 g white potatoes per day or less. Source: Pao et al. 1982 (based on 1977-78 NFCS datal. Table 9-27. Mean Moisture Content of Selected Fruits and Vegetables Expressed as Percentages of Edible Portions Food Moisture Content (Percent) Comments Fruit Apples -dried Apples-Apples -juice Applesauce Apricots Apricots -.dried Bananas Blackberries Blueberries Boysenberries Cantaloupes -unspecified Casabas Cherries -sweet Crabapples Cranberries Cranberries -juice cocktail Currants (red and white) Elderberries Grapefruit Grapefruit -juice Grapefruit -unspecified Grapes -fresh Grapes -juice Grapes -raisins Honeydew melons Kiwi fruit Kumquats Lemons -juice Lemons -peel Lemons -pulp Limes -juice Limes -unspecified Loganberries Mulberries Nectarines Oranges -unspecified Peaches Pears -dried Pears -fresh Pineapple Pineapple -juice Plums Quinces. Raspberries Strawberries Tangerine -juice Tangerines Watermelon Vegetables Alfalfa sprouts Artichokes -globe & French Artichokes -Jerusalem Raw Cooked 31.76 83.93* 86.35 31.09 74.26 85.64 84.61 85.90 89.78 91.00 80.76 78.94 86.54 85.00 83.95 79.80 90.89 90.00 90.89 81.30 84.12 15.42 89.66 83.05 81.70 90.73 81.60 88.98 90.21 88.26 84.61 87.68" 86.28 86.75 87.66 26.69 83.81 86.50 83.80 86.57 91.57 88.90 87.60 91.51 91.14 84.38 78.01 84.13* 84.46** 87.93 88.35* 86.62* 85.56* 86.59* 84.95* 90.1 O* 92.46* 92.52* 87.49* 64.44* 86.47* 83.51* 85.53 85.20 89.97* 87.00* 89.51* 86.50 sulfured; *without added sugar *with skin; **without skin canned or bottled *unsweetened *canned juice pack with skin sulfured; *without added sugar *frozen unsweetened frozen unsweetened *canned, juice pack bottled *canned unsweetened pink, red, white American type (slip skin) canned or bottled seedless *canned or bottled *canned or bottled all varieties *canned juice pack sulfured; *without added sugar *canned juice pack *canned juice pack canned *frozen unsweetened *canned sweetened *canned juice pack boiled, drained Table 9-27. Mean Moisture Content of Selected Fruits and Vegetables Expressed as Percentages of Edible Portions (continued) Food Moisture Content (Percent) Comments Raw Cooked Asparagus 92.25 92.04 boiled, drained Bamboo shoots 91.00 95.92 boiled, drained Beans -dry Beans -dry-blackeye peas (cowpeas) 66.80 71.80 boiled, drained Beans -dry-hyacinth (mature seeds) 87.87 86.90 boiled, drained Beans -dry -navy (pea) 79.15 76.02 boiled, drained Beans -dry -pinto 81.30 93.39 boiled, drained Beans -Hrna 70.24 67.17 , boiled, drained Beans -snap -Italian -green -yellow 90.27 89.22 boiled, drained Beets 87.32 90.90 boiled, drained Beets -tops (greens) 92.15 89.13 boiled, drained Broccoli 90.69 90.20 boiled, drained Brussel sprouts 86.00 87.32 boiled, drained Cabbage -Chinese/celery, including bok choy . 95.32 95.55 boiled, drained Cabbage -red 91.55 93.60 boiled, drained Cabbage -savoy 91.00 92.00 boiled, drained Carrots 87.79 87.38 boiled, drained Cassava (yucca blanca) 68.51 Cauliflower 92.26 92.50 boiled, drained 9eleriac 88.00 92.30 boiled, drained Celery 94.70 95.00 boiled, drained Chili peppers 87.74 92.50* *canned solids & liquid Chives 92.00 Cole slaw 81.50 Collards 93.90 95.72 boiled, drained Com -sweet 75.96 69.57 boiled, drained Cress -garden -field 89.40 92.50 boiled, drained Cress -garden 89.40 92.50 boiled, drained Cucumbers 96.05 Dandelion -greens 85.60 89.80 boiled, drained Eggplant 91.93 91.77 boiled, drained Endive 93.79 Garlic 58.58 Kale 84.46 91.20 boiled, drained Kohlrabi 91.00 90.30 boiled, drained Lambsquarter 84.30 88.90 boiled, drained Leeks 83.00 90.80 boiled, drained Lentils -whole 67.34 68.70 stir-fried Lettuce -iceberg 95.89 Lettuce -romaine 94.9'1 Mung beans (sprouts) 90.40 93.39 boiled, drained Mushrooms 91.81 91.08 boiled, drained Mu.stard greens 90.80 94.46 boiled, drained Okra 89.58 89.91 boiled, drained Onions 90.82 92.24 boiled, drained Onions -dehydrated qr dried 3.93 Parsley 88.31 Parsley roots 88.31 Parsnips 79.53 77.72 boiled, drained Peas (garden) -mature seeds -dry 88.89 88.91 boiled, drained Peppers -sweet , garden 92.77 94.70 boiled, drained Potatoes (white)-peeled 78.96 75.42 baked Table 9-27. Mean Moisture Content of Selected Fruits and Vegetables Expressed as Percentages of Edible Portions (continued) Food Moisture Content (Percent) Comments Raw Cooked Potatoes (white) -whole 83.29 71.20 baked Pumpkin 91.60 93.69 boiled, drained Radishes -roots 94.84 Rhubarb 93.61 67.79 frozen, cooked with added sugar Rutabagas -unspecified 89.66 90.10 boiled, drained Salsify (oyster plant) 77.00 81.00 boiled, drained Shallots 79.80 Soybeans -sprouted seeds 69.05 79.45 steamed Spinach 91.58 91.21 boiled, drained Squash -summer 93.68 93.70 all varieties; boiled, drained Squash -winter 88.71 89.01 all varieties; baked Sweetpotatoes (including yams) 72.84 71.85 baked in skin Swiss chard 92.66 92.65 boiled, drained Tapioca -pearl 10.99 dry Taro -greens 85.66 92.15 steamed Taro -root 70.64 63.80 Tomatoes -juice 93.90 canned Tomatoes -paste 74.06 canned Tomatoes -puree 87.26 canned Tomatoes -raw 93.95 Tomatoes -whole 93.95 92.40 boiled, drained Towelgourd 93.85 84.29 boiled, drained Turnips -roots 91.87 93.60 boiled, drained Turnips -tops 91.07 93.20 boiled, drained Water chestnuts 73.46 Yambean -tuber 89.15 87.93 boiled, drained Source: USDA, 1979-1986. Table 9-28. Summary of Fruit and Vegetable Intake Studies Survey Population Used Study in Calculating Intake Tvoes of Data Used Units Food Items KEY STUDIES EPA Analysis of 1989-Per capita data; 1989-91 CSFll data; g/kg-day; as consumed Major food groups; individual food 91 USDA CSFll data consumer only data can Based on 3-day average individual items; exposed and protected fruits be calculated intake rate and vegetables; USDA food categories RELEVANT STUDIES AIHC, 1994 Per Capita Based on the 1977-78 USDA NFCS glday Distributions for vegetables using data provided in the 1989 version of @Risk software. the Exposure Factors Handbook. Canadian Department Not known if per capita or 1970-72 survey based on 24-hour glday; not known if as Fruit and fruit products, vegetables of National Health and consumers only dietary recall consumed not including potatoes and nuts Welfare, n.d. and legumes EPA's ORES Per capita (i.e., 1977-78 NFCS glkg-day; as consumed Intake for a wide variety of fruits consumers and 3-day individual intake data and vegetables presented; complex nonconsumers) food groups were disaggregated Pao et al., 1982 Consumers only serving 1977-78 NFCS g; as consumed Serving sizes for only a limited size data provided 3-day individual intake data number of products USDA, 1980; 1992b; Per capita and consumer 1977-78 and 1987-88 NFCS, and glday; as consumed Total fruits and total vegetables 1996a; 1996b only 1994 and 1995 CSFll 1-day individual intake data USDA, 1!:)93 Per capita consumption Based on food supply and utilization glday; as consumed Various food groups based on "food data provided by the National disappearance" Agricultural Statistics Service (NASS), Customs Service Reports, and trade associations U.S. EPAIORP, 1984a; Per capita 1977-78 NFCS glday; as consumed . Exposed, protected, and leafy 1984b Individual intake data produce U.S. EPAIOST, 1989 Estimated lifetime dietary Based on FDA Total Diet Study Food glday; dry weight Various food groups; complex intake . List which used 1977-78 NFCS data, foods disaggregated and NHANES 11 data Table 9-29. Summary of Recommended Values for Per Capita Intake of Fruits and Vegetables Mean 95th Percentile Multiple Percentiles Study Total Fruit Intake 3.4 g/kg-day 12 g/kg-day see Table 9-3 EPA Analysis of CSFll 1989-91 Data Total Vegetable Intake 4.3 g/kg-day 10 g/kg-day see Table 9-4 EPA Analysis of CSFll 1989-91 Data Individual Fruit and Vegetables Intake -see Table 9-5 ------EPA Analysis of CSFll 1989-91 Data Table 9-30. Confidence in Fruit and VeQetable Intake Recommendations Considerations Rationale Ralina Study Elements

Level of peer review USDA CSFll survey receives high level of peer High review. EPA analysis of these data has been peer reviewed outside the Agency. . Accessibility CSFll data are publicly available. High . Reproducibility Enough information is included to reproduce High results .. Focus on factor of interest Analysis is specifically designed to address High food intake. . Data pertinent to U.S. Data focuses on the U.S. population . High . Primary data This is new analysis of primary data. High . Currency Were the most current data publicly available at High the time the analysis was conducted for the Handbook.
Adequacy of data collection Survey is designed to collect short-term data. Medium confidence for average period values; Low confidence for long term percentile distribution . Validity of approach Survey methodology was adequate. High Study size Study size was very large and therefore High adequate. Representativeness of the The population studied was the U.S. High population population.
Characterization of variability Survey was not designed to capture long term Medium day-to-day variability. Short term distributions are provided.
Lack of bias in study design Response rate was adequate. Medium (high rating is desirable)
Measurement error No measurements were taken. The study N/A relied on survey data. Other Elements
Number of studies 1; CSFll 1989-91 was the most recent data set Low publicly available at the time the analysis was conducted for the Handbook. Therefore, it was the only study classified as key study.
Agreement between researchers Although the CSFll was the only study High classified as key study, the results are in good agreement with earlier data. Overall Rating The survey is representative of U.S. population. High confidence in the average; Although there was only one study considered Low confidence in the long-term *key, these data are the most recent and are in upper percentiles agreement with earlier data. The approach used to analyzed the data was adequate . . However, due to the limitations of the survey design estimation of long-term percentile values (esoeciallv the unner nercentiles\ is uncertain.

Table 9A-1. Fraction of Grain and Meat Mixture Intake Represented by Various Food Items/Groups Grain Mixtures . total vegetables tomatoes white potatoes total meats beef pork poultry dairy total grains Meat Mixtures total vegetables tomatoes white potatoes total meats beef pork poultry dairy total grains 0.2360 0.1685 0.0000 0.0787 0.0449 0.0112 0.0112 0.1348 0.3146 0.2778 0.1111 0.0333 0.3556 0.2000 0.0222 0.0778 0.0556 0.1333 Appendix 9B. Food Codes and Definitions Used in Analysis of the 1989-91 USDA CSFll Data Food Food Codes Product MAJOR FOOD GROUPS Total Fruits 6-Fruits (includes baby foods) citrus fruits and juices dried fruits other fruits fruits/juices & nectar fruit/iuices babv food Total 7-Vegetables (all forms) 411-Beans/legumes Vegetables white potatoes & PR starchy 412-Beans/legumes dark green vegetables 413-Beans/legumes deep yellow vegetables (includes baby foods; mixtures, mostly vegetables; does not tomatoes and tom. mixtures include nuts and seeds) other vegetables veg. and mixtures/baby food veg. with meat mixtures Total Meats 20-Meat, type not specified (excludes meat, poultry, and fish with non-meat items; frozen 21-Beef plate meals; soups and gravies with meat, poultry and fish 22-Pork base; and gelatin-based drinks; includes baby foods) 23-Lamb, veal, game, carcass meat 24-Poultry 25-Organ meats, sausaaes, lunchmeats, meat spreads Total Dairy 1-Milk and Milk Products (includes regular fluid milk, human milk, imitation milk milk and milk drinks products, yogurt, milk-based meal replacements, and infant cream and cream substitutes formulas) milk desserts, sauces, and gravies cheeses INDIVIDUAL FOODS White 71-White Potatoes and PR Starchy Veg. (does not include vegetables soups; vegetable mixtures; or Potatoes baked, boiled, chips, sticks, creamed, scalloped, au vegetable with meat mixtures) gratin, fried, mashed, stuffed, puffs, salad, recipes, soups, Puerto Rican starchy vegetables Peppers 7512100 Pepper, hot chili, raw 7522606 Pepper, red, cooked, fat added 7512200 Pepper, raw 7522609 Pepper, hot, cooked, NS as to fat added 7512210 Pepper, sweet green, raw 7522610 Pepper, hot, cooked, fat not added 7512220 Pepper, sweet red, raw 7522611 Pepper, hot, cooked, fat added 7522600 Pepper, green, cooked, NS as to fat added 7551101 Peppers, hot, sauce 7522601 Pepper, green, cooked, fat not added 7551102 Peppers, pickled 7522602 Pepper, green, cooked, fat added 7551105 Peppers, hot pickled 7522604 Pepper, red, cooked, NS as to fat added (does not include vegetable soups; vegetable mixtures; or 7522605 Pepper, red, cooked, fat not added vegetable with meat mixtures) Onions 7510950 Chives, raw 7522102 Onions, mature cooked, fat added 7511150 Garlic, raw 7522103 Onions, pearl cooked 7511250 Leek, raw 7522104 Onions, young green cooked, NS as to fat 7511701 Onions, young green, raw 7522105 Onions, young green cooked, fat not added 7511702 Onions, mature 7522106 Onions, young green cooked, fat added 7521550 Chives, dried 7522110 Onion, dehydrated 7521740 Garlic, cooked 7541501 Onions, creamed 7521840 Leek, cooked 7541502 Onion rings 7522100 Onions, mature cooked, NS as to fat added (does not include vegetable soups; vegetable mixtures; or 7522101 Onions mature cooked fat not added veaetable with meat mixtures) Food Product Corn Apples Tomatoes Snap Beans Beef Appendix 9B, Food Codes and Definitions Used in Analysis of the 1989-91 USDA CSFll Data (continued) Food Codes 7510960 Corn, raw 7521600 Corn, cooked, NS as to color/fat added 7521601 Corn, cooked, NS as to color/fat not added 7521602 Corn, cooked, NS as to color/fat added 7521605 Corn, cooked, NS as to color/cream style 7521607 Corn,cooked,dried 7521610 Corn, cooked, yellow/NS as to fat added 7521611 Corn, cooked, yellow/fat not added 7521612 Corn, cooked, yellow/fat added 7521615 Corn, yellow, cream style 7521616 Corn, cooked, yell. & wh./NS as to fat 7521617 Corn, cooked, yell. & wh./fat not added 7521618 Corn, cooked, yell. & wh./fat added 7521619 Corn, yellow, cream style, fat added 7521620 Corn, cooked, white/NS as to fat added 6210110 Apples, dried, uncooked 6210115 Apples, dried, uncooked, low sodium 6210120 Apples, dried, cooked, NS as to sweetener 6210122 Apples, dried, cooked, unsweetened 6210123 Apples, dried, cooked, with sugar 6210130 Apple chips 6310100 Apples, raw 6310111 Applesauce, NS as to sweetener 6310112 Applesauce, unsweetened 6310113 Applesauce with sugar 6310114 Applesauce with low calorie sweetener 6310121 Apples, cooked or canned with syrup 6310131 Apple, baked NS as to sweetener 6310132 Apple, baked, unsweetened ' 6310133 Apple, baked with sugar 74-Tomatoes and Tomato Mixtures raw, cooked, juices, sauces, mixtures, soups, sandwiches 7510180 Beans, string, green, raw 7520498 Beans, string, cooked, NS color/fat added 7520499 Beans, string, cooked, NS color/no fat 7520500 Beans, string, cooked, NS color & fat 7520501 Beans, string, cooked, green/NS fat 7520502 Beans, string, cooked, green/no fat 7520503 Beans, string, cooked, green/fat 7520511 Beans, sir., canned, low sod.,green/NS fat 7520512 Beans, sir., canned, low sod.,green/no fat 7520513 Beans, sir., canned, low sod.,green/fat 7520600 Beans, string, cooked, yellow/NS fat 7520601 Beans, string, cooked, yellow/no fat 21-Beef beef, nfs beef steak beef oxtails, neckbones, ribs roasts, stew meat, corned, brisket, sandwich steaks ground beef, patties, meatballs other beef items beef babv food 7521621 Com, cooked, white/fat not added 7521622 Corn, cooked, white/fat added 7521625 Corn, white, cream style 7521630 Corn, yellow, canned, low sodium, NS fat 7521631 Corn, yell., canned, low sod., fat not add 7521632 Corn, yell., canned, low sod., fat added 7521749 Hominy, cooked 752175-Hominy, cooked 7541101 Corn scalloped or pudding 7541102 Corn fritter 7541103 Corn with cream sauce 7550101 Corn relish 76405-Corn, baby (does not include vegetable soups; vegetable mixtures; or veoetable with meat mixtures; includes baby food) 6310141 Apple rings, fried 6310142 Apple, pickled 6310150 Apple, fried 6340101 Apple, salad 6340106 Apple, candied 6410101 Apple cider 6410401 Apple juice 6410405 Apple juice with vitamin C 6410409 Apple juice with calcium 6710200 Applesauce baby fd., NS as to str. or jr. 6710201 Applesauce baby food, strained 6710202 Applesauce baby food, junior 6720200 Apple juice, baby food (includes baby food; except mixtures) 7520602 Beans, string, cooked, yellow/fat 7540301 Beans, string, green, creamed 7540302 Beans, string, green, w/mushroom sauce 7540401 Beans, string, yellow, creamed 7550011 Beans, string, green, pickled 7640100 Beans, green, string, baby 7640101 Beans, green, string, baby, sir. 7640102 Beans, green, string, baby, junior 7640103 Beans, green, string, baby, creamed (does not include vegetable soups; vegetable mixtures; or vegetable with meat mixtures; includes baby foods) (excludes meat, poultry, and fish with non-meat items; frozen plate meals; soups and gravies with meat, poultry and fish base; and gelatin-based drinks; includes baby food} Appendix 9B. Food Codes and Definitions Used in Analysis of the 1989-91 USDA CSFll Data (continued) Food Food Codes Product Pork 22-Pork (excludes meat, poultry, and fish with non-meat items; frozen pork, nfs; ground dehydrated plate meals; soups and gravies with meat, poultry and fish chops base; and gelatin-based drinks; includes baby food) steaks, cutlets ham roasts Canadian bacon bacon, salt pork other pork items pork baby food Game 233-Game (excludes meat, poultry, and fish with non-meat items; frozen plate meals; soups and gravies with meat, poultry and fish base; and qelatin-based drinks) Poultry 24-Poultry (excludes meat, poultry, and fish with non-meat items; frozen chicken plate meals; soups and gravies with meat, poultry and fish turkey base; and gelatin-based drjnks; includes baby food) duck other poultry poultry baby food Eggs 3-Eggs (includes baby foods) eggs egg mixtures egg substitutes eggs baby food froz. meals with eqg as main ingred. Broccoli 722-Broccoli (all forms) (does not include vegetable soups; vegetable mixtures; or vegetable with meat mixtures) Carrots 7310-Carrots (all forms) (does not include vegetable soups; vegetable mixtures; or 7311140 Carrots in Sauce vegetable with meat mixtures; includes baby foods except 7311200 Carrot Chips mixtures) 76201-Carrots, babv Pumpkin 732-Pumpkin (all forms) (does not include vegetable soups; vegetables mixtures; or 733-Winter squash (all forms) vegetable with meat mixtures; includes baby foods) 76205-Squash, baby Asparagus 7510080 Asparagus, raw (does not include vegetable soups; vegetables mixtures, or 75202-Asparagus, cooked vegetable with meat mixtures) 7540101 Asparaqus, creamed or with cheese Lima Beans 7510200 Lima Beans, raw (does not include vegetable soups; vegetable mixtures; or 752040-Lima Beans, cooked vegetable with meat mixtures; does not include succotash) 752041-Lima Beans, canned 75402-Lima Beans with sauce Cabbage 7510300 Cabbage, raw 75212-Red Cabbage, cooked 7510400 Cabbage, Chinese, raw 752130-Savoy Cabbage, cooked 7510500 Cabbage, red, raw 75230-Sauerkraut, cooked 7514100 Cabbage salad or coleslaw 7540701 Cabbage, creamed 7514130 Cabbage, Chinese, salad 755025-Cabbage, pickled or in relish 75210-Chinese Cabbage, cooked (does not include vegetable soups; vegetable mixtures; or 75211-Green Cabbaae cooked veaetable with meat mixtures) I Appendix 98. Food Codes and Definitions Used in Analysis of the 1989-91 USDA CSFll Data (continued) Food Food Codes Product Lettuce 75113-Lettuce, raw (does not include vegetable soups; vegetable mixtures; or 75143-Lettuce salad with other veg. vegetable with meat mixtures) 7514410 Lettuce, wilted, with bacon dressing 7522005 Lettuce, cooked Okra 7522000 Okra, cooked, NS as to fat 7541450 Okra, fried 7522001 Okra, cooked, fat not added 7550700 Okra, pickled 7522002 Okra, cooked, fat added (does not include vegetable soups; vegetable mixtures; or 7522010 Lufta, cooked (Chinese Okra) vegetable with meat mixtures) Peas 7512000 Peas, green, raw 7541660 Pea salad with cheese 7512775 Snowpeas, raw 75417-Peas, with sauce or creamed 75223-Peas, cowpeas, field or blackeye, cooked 76409-Peas, baby 75224-Peas, green, cooked 76411-Peas, creamed, baby 75225-Peas, pigeon, cooked (does not include vegetable soups; vegetable mixtures; or 75231-Snowpeas, cooked vegetable with meat mixtures; includes baby foods except 7541650 Pea salad mixtures) Cucumbers 7511100 Cucumbers, raw 7550305 Cucumber pickles, fresh 75142-Cucumber salads 7550307 Cucumber, Kim Chee 752167-Cucumbers, cooked 7550311 Cucumber pickles, dill, reduced salt 7550301 Cucumber pickles, dill 7550314 Cucumber pickles, sweet, reduced salt 7550302 Cucumber pickles, relish (does not include vegetable soups; vegetable mixtures; or 7550303 Cucumber pickles, sour vegetable with meat mixtures) 7550304 Cucumber pickles, sweet Beets 7510250 Beets, raw 7550021 Beets, pickled 752080-Beets, cooked 76403-Beets, baby 752081-Beets, canned (does not include vegetable soups; vegetable mixtures; or 7540501 Beets, harvard vegetable with meat mixtures; includes baby foods except mixtures) Strawberrie 6322-Strawberries (includes baby food; except mixtures) s 6413250 Strawberry Juice Other 6320-Other Berries 6410460 Blackberry Juice Berries 6321-Other Berries 64105-Cranberry Juice 6341101 Cranberry salad (includes baby food; except mixtures) Peaches 62116-Dried Peaches 67108-Peaches.baby 63135-Peaches 6711450 Peaches, dry, baby 6412203 Peach Juice (includes baby food; except mixtures) 6420501 Peach Nectar Pears 62119-Dried Pears 67109-Pears, baby ' 63137-Pears 6711455 Pears, dry, baby 6341201 Pear salad 6721200 Pear juice, baby 6421501 Pear Nectar (includes baby food; except mixtures) Appendix 98. Food Codes and Definitions Used in Analysis of the 1989-91 USDA CSFll Data (continued) Food Food Codes Product EXPOSED/PROTECTED FRUITSNEGETABLES, ROOT VEGETABLES Exposed 621011-Apple, dried 63143-Plum Fruits 621012-Apple, dried 63146-Quince 6210130 Apple chips 63147-Rhubarb/Sapodillo 62104-Apricot, dried 632-Berries 62108-Currants, dried 64101-Apple Cider 62110-Date, dried 64104-Apple Juice 62116-Peaches, dried 6410409 Apple juice with calcium 62119-Pears, dried 64105-Cranberry Juice 62121* Plum, dried 64116-Grape Juice 62122-Prune, dried 64122-Peach Juice 62125-Raisins 64132-. Prune/Strawberry Juice 63101-Apples/applesauce 6420101 Apricot Nectar 63102-Wi-apple 64205-Peach Nectar 63103-Apricots 64215-Pear Nectar 63111-Cherries, maraschino 67102-Applesauce, baby 63112-Acero la 67108-Peaches, baby 63113-Cherries, sour 67109-* Pears, baby 63115-Cherries, sweet 6711450 Peaches, baby, dry 63117-Currants, raw 6711455 Pears, baby, dry 63123-Grapes 67202-Apple Juice, baby 6312601 Juneberry 6720380 White Grape Juice, baby 63131-Nectarine 67212-Pear Juice, baby 63135-Peach (includes baby except mixtures; excludes 63137-Pear fruit mixtures) 63139-Persimmons Protected 61-Citrus Fr., Juices (incl. cit. juice mixtures) 63145-Pomegranate Fruits 62107-Bananas, dried 63148-Sweetsop, Soursop, Tamarind 62113-Figs, dried 63149-Watermelon 62114-Lychees/Papayas, dried . 64120-Papaya Juice 62120-Pineapple, dried 64121-Passion Fruit Juice 62126-Tamarind, dried 64124-Pineapple Juice 63105-Avocado, raw 64125-Pineapple juice 63107-Bananas 64133-Watermelon Juice 63109-Cantaloupe, Carambola 6420150 Banana Nectar 63110-Cassaba Melon 64202-Cantaloupe Nectar 63119-Figs 64203-Guava Nectar 63121-Ge nip 64204-Mango Nectar 63125-Guava/Jackfruit, raw 64210-Papaya Nectar 6312650 Kiwi 64213-Passion Fruit Nectar 6312651 Lychee, raw 64221-Soursop Nectar 6312660 Lychee, cooked 6710503 Bananas, baby 63127-Honeydew 6711500 Bananas, baby, dry 63129-Mango 6720500 Orange Juice, baby 63133-Papaya 6721300 Pineapple Juice, baby 63134-Passion Fruit (includes baby foods/juices except mixtures; excludes fruit 63141-Pineaoole mixtures) Appendix 9B. Food Codes and Definitions Used in Analysis of the 1989-91 USDA CSFll Data (continued) Food Food Codes Product Exposed 721-Dark Green Leafy Veg. 752167-Cucumber, cooked Veg. 722-Dark Green Nonleafy Veg. 752170-Eggplant, cooked 74-Tomatoes and Tomato Mixtures 752171-Fem shoots 7510050 Alfalfa Sprouts 752172-Fem shoots 7510075 Artichoke, Jerusalem, raw 752173-Flowers of sesbania, squash or lily 7510080 Asparagus, raw 7521801 . Kohlrabi, cooked 75101-Beans, sprouts and green, raw 75219-Mushrooms, cooked 7510260 Broccoflower, raw 75220-Okra/lettuce, cooked 7510275 Brussel Sprouts, raw 7522116 Palm Hearts, cooked 7510280 Buckwheat Sprouts, raw 7522121 Parsley, cooked 7510300 Cabbage, raw 75226-Peppers, pimento, cooked 7510400 Cabbage, Chinese, raw 75230-Sauerkraut, cooked/canned 7510500 Cabbage, Red, raw 75231-Snowpeas, cooked 7510700 Cauliflower, raw 75232-Seaweed 7510900 Celery, raw 75233-Summer Squash 7510950 Chives, raw 7540050 Artichokes, stuffed 7511100 Cucumber, raw 7540101 Asparagus, creamed or with cheese 7511120 Eggplant. raw 75403-Beans, green with sauce 7511200 Kohlrabi, raw 75404-Beans, yellow with sauce 75113-Lettuce, raw 7540601 Brussel Sprouts, creamed 7511500 Mushrooms, raw 7540701 Cabbage, creamed 7511900 Parsley 75409-Cauliflower, creamed 7512100 Pepper, hot chili 75410-Celery/Chiles, creamed 75122-Peppers, raw 75412-Eggplant, fried, with sauce, etc. 7512750 Seaweed, raw 75413-Kohlrabi, creamed 7512775 Snowpeas, raw 75414-Mushrooms, Okra, fried, stuffed, creamed 75128-Summer Squash, raw 754180-Squash, baked, fried, creamed, etc. 7513210 Celery Juice 7541822 Christophine, creamed 7514100 Cabbage or cole slaw 7550011 Beans. pickled 7514130 Chinese Cabbage Salad 7550051 Celery, pickled 7514150 Celery with cheese 7550201 Cauliflower, pickled 75142-Cucumber salads 755025-Cabbage, pickled 75143-Lettuce salads 7550301 Cucumber pickles, dill 7514410 Lettuce, wilted with bacon dressing 7550302 Cucumber pickles, relish 7514600 Greek salad 7550303 Cucumber pickles, sour 7514700 Spinach salad 7550304 Cucumber pickles, sweet 7520060 Algae, dried 7550305 Cucumber pickles, fresh 75201-Artichoke, cooked 7550307 Cucumber, Kim Chee 75202-Asparagus, cooked 7550308 Eggplant, pickled 75203-Bamboo shoots, cooked 7550311 Cucumber pickles, dill, reduced salt 752049-Beans. string, cooked 7550314 Cucumber pickles, sweet, reduced salt 75205-Beans, green, cooked/canned 7550500 Mushrooms, pickled 75206-Beans, yellow, cooked/canned 7550700 Okra, pickled 75207-Bean Sprouts, cooked 75510-Olives 752085-Breadfruit 7551101 Peppers, hot 752087-Broccoflower, cooked 7551102 Peppers.pickled 752090-Brussel Sprouts, cooked 7551104 Peppers. hot pickled 75210-Cabbage, Chinese, cooked 7551301 Seaweed, pickled 75211-Cabbage,. green, cooked 7553500 Zucchini, pickled 75212-Cabbage, red, cooked 76102-Dark Green Veg., baby 752130-Cabbage, savoy, cooked 76401-Beans, baby (excL most soups & mixtures) 75214-Cauliflower 411-Beans/legumes 75215-Celery, Chives, Christophine (chayote) 412-Beans/legumes 413-Beans/leoumes Appendix 9B. Food Codes and Definitions Used in Analysis of the 1989-91 USDA CSFll Data (continued) Food Food Codes Product Protected 732-Pumpkin 752175-Hominy Veg. 733-Winter Squash 75223-Peas, cowpeas, field or blackeye, cooked 7510200 Lima Beans, raw 75224-Peas, green, cooked 7510550 Cactus, raw 75225-Peas, pigeon, cooked 7510960 Corn, raw 75301-Succotash 7512000 Peas, raw 75402-Lima Beans with sauce 7520070 Aloe vera juice 75411-Corn, scalloped, fritter, with cream 752040-Lima Beans, cooked 7541650 Pea salad 752041-Lima Beans, canned 7541660 Pea salad with cheese 7520829 Bitter Melon 75417-Peas, with sauce or creamed 752083-Bitter Melon, cooked 7550101 Corn relish 7520950 Burdock 76205-Squash, yellow, baby 752131-Cactus 76405-Corn, baby 752160-Corn, cooked 76409-Peas, baby 752161-Corn, yellow, cooked 76411-Peas, creamed, baby 752162-Corn, white, cooked (does not include vegetable soups; vegetable mixtures; or 752163-Corn, canned vegetable with meat mixtures) 7521749 Hominv Root 71-White Potatoes and Puerto Rican St. Veg. 7522110 Onions, dehydrated Vegetables 7310-Carrots 752220-Parsnips, cooked 7311140 Carrots in sauce 75227-Radishes, cooked 7311200 Carrot chips 75228-Rutabaga, cooked 734-Sweetpotatoes 75229-Salsify, cooked 7510250 Beets, raw 75234-Turnip, cooked 7511150 Garlic, raw 75235-Water Chestnut 7511180 Jicama (yambean), raw 7540501 Beets, harvard 7511250 Leeks, raw 75415-OnJons, creamed, fried 75117-Onions; raw . 7541601 Parsnips, creamed 7512500 Radish, raw 7541810 Turnips, creamed 7512700 Rutabaga, raw 7550021 Beets, pickled 7512900 Turnip, raw 7550309 Horseradish 752080-Beets, cooked 7551201 Radishes, pickled 752081-Beets, canned 7553403 Turnip, pickled 7521362 Cassava 76201-Carrots, baby 7521740 Garlic, cooked 76209-Sweetpotatoes, baby 7521771 Horseradish 76403-Beets, baby 7521840 Leek, cooked (does not include vegetable soups; vegetable mixtures; or 7521850 Lotus root vegetable with meat mixtures) 752210-Onions, cooked USDA SUBCATEGORIES Dark Green 72-Dark Green Vegetables Vegetables all forms leatv, nonleatv, dk. gr. veo. soups Deep 73-Deep Yellow Vegetables Yellow all forms Vegetables carrots, pumpkin, squash, sweetpotatoes, dp. yell. veg. soups Other 75-Other Vegetables Veoetables all forms Citrus Fruits 61-Citrus Fruits and Juices 6720700 Orange-Pineapple Juice, baby food 6720500 Orange Juice, baby food 6721100 Orange-Apple-Banana Juice, baby food 6720600 Oranae-Anricot Juice babv food r excludes dried fruits) Food Product Other Fruits Meat Mixtures Grain Mixtures Appendix 98. Food Codes and Definitions Us 62-63-Dried Fruits Other Fruits -ed in Analysis of the 1989-91 USDA CSFll Data (continued) Food Codes 67204-Baby Juices 67212-Baby Juices 64-671-67202-67203-Fruit Juices and Nectars Excluding Fruits, baby Citrus 67213-Baby Juices Apple Juice, baby Bab Juices 27-Meat Mixtures 28-58-Grain Mixtures MIXTURES 6725-Baby Juice 673-Baby Fruits 674-Babv Fruits (includes frozen plate meals and soups) (includes frozen plate meals and soups) v -----------.. REFERENCES FOR CHAPTER 9 American Industrial Health Council (AIHC). (1994) Exposure factors sourcebook. AIHC, Washington, DC. Canadian Department of National Health and Welfa.re, Bureau of National Sciences, Health Protection Branch (n.d.). Food Consumption, Patterns Report: A report from Nutrition Canada. Kariya, J. (1992) Written communication to L. Phillips, Versar, Inc., March 4, 1992. Pao, E.M.; Fleming, K.H.; Guenther, P.M.; Mickle, S.J. (1982) Foods commonly eaten by individuals: amount per day and per eating occasion. U.S. Department of Agriculture. Home Economics Report No. 44. Pennington, J.A.T. (1983) Revision of the total diet study food list and diets. J. Am. Diet. Assoc. 82:166-173. SAS Institute, Inc. (1990) SAS Procedures Guide, Version 6, Third Edition, Cary, NC: SAS Institute, Inc., 1990, 705 pp. USDA. (1972) Food consumption: households in the United States, Seasons and year 1965-1966. U.S. Department of Agriculture..

USDA. (1979-1986) Agricultural Handbook No. 8. United States Department of Agriculture. USDA. (1980) Food and nutrient intakes of individuals in one day in the United States, Spring 1977. Nationwide Food Consumption Survey 1977-1978. U.S. Department of * ,Agriculture. Preliminary Report No. 2 .. USDA. (1992a) Changes in food consumption and expenditures in American households during the 1980s. U.S. Department of Agriculture. Washington, D.C. Statistical Bulletin No. 849. *
USDA. (1992b) Food and nutrient intakes by individuals in the United States, 1 day, 1987-88: U.S. Department of Agriculture, Human Nutrition Information Service. Nationwide Food Consumption Survey 1987-88, NFCS Rpt. No. 87-1-1. USDA. (1993) Food consumption prices and expenditures (1970-1992) U.S. Department of Agriculture, Economic Research Service. Statistical Bulletin, No. 867. USDA. (1995) Food and nutrient intakes by individuals in the United States, 1 day, 1989-91. U.S. Department of Agriculture, Agricultural Research Service. NFS Report No. 91-2.

USDA. (1996a) Data tables: results from USDA's 1994 Continuing Survey of Food Intakes by Individuals and 1994 Diet and Health Knowledge Survey. U.S. Department of Agriculture, Agricultural Research Service, Riverdale, MD. USDA. (1996b) Data tables: results from USDA's 1995 Continuing Survey of Food Intakes by Individuals and 1995 Diet and Health Knowledge Survey. U.S.

Department of Agriculture, Agricultural Research Service, Riverdale, MD. U.S. EPA. (1984a) An estimation of the daily average food intake by age and sex for use in assessing the radionuclide intake of individuals in the general population. EPA-520/1-84-021. U.S. EPA. (1984b) An estimation of the daily food intake based on data from the 1977-1978 USDA Nationwide Food Consumption Survey. Washington, DC: Office of Radiation Programs. EPA-520/1-84-015. U.S. EPA. (1989) Development of risk assessment methodologies for land application and distribution and marketing of municipal sludge. Washington, DC: Office of Science and Technology. EPA 600/-89/001. White, S.B.; Peterson, B.; Clayton, C.A.; Duncan, D.P. (1983) lnte-rim Report Number 1: The construction of a raw agricultural commodity consumption data base. Prepared by Research Triangle Institute for EPA Office of Pestici.de Programs.

DOWNLOADABLE TABLES FOR CHAPTER 9 The following selected tables are available for download as Lotus 1-2-3 worksheets. Table 9-3. Per Capita Intake of Total Fruits (g/kg-day as consumed) [WK1, 6 kb] Table 9-4. Per Capita Intake of Total Vegetables (g/kg-day as consumed) [WK1, 6 kb] Table 9-5. Per Capita Intake of Individual Fruits and Vegetables (g/kg-day as consumed) [WK1, 31 kb] Table 9-6. Per Capita Intake of USDA Categories of Fruits and Vegetables (g/kg-day as consumed) [WK1, 9 kb] Table 9-7. Per Capita Intake of Exposed Fruits (g/kg-day as consumed) [WK1, 7 kb] Table 9-8. Per Capita Intake of Protected Fruits (g/kg-day as consumed) [WK1, 7 kb] Table 9-9. Per Capita Intake of Exposed Vegetables (g/kg-day as consumed) . [WK1, 7 kb] Table 9-10. Per Capita Intake of Protected Vegetables (g/kg-day as consumed) [WK1, 7 kb] Table 9-11. Per Capita Intake of Root Vegetables (g/kg-day as consumed) [WK1, 7 kb] Table 9-26. Quantity (as consumed) of Fruits and Vegetables Consumed Per Eating Occasion and the Percentage of Individuals Using These Foods in Three Days [WK1, 6 kb] Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellflsh 10. INTAKE OF FISH AND SHELLFISH 10.1. BACKGROUND 10.2. KEY GENERAL POPULATION STUDIES 10.3. RELEVANT GENERAL POPULATION STUDIES 10.4. KEY RECREATIONAL (MARINE FISH STUDIES) 10.5. RELEVANT RECREATIONAL MARINE STUDIES 10.6. KEY FRESHWATER RECREATIONAL STUDIES 10.7. RELEVANT FRESHWATER RECREATIONAL STUDIES 10.8. NATIVE AMERICAN FRESHWATER STUDIES 10.9. OTHER FACTORS 10.10. RECOMMENDATIONS 10.10.1. Recommendations -General Population 10.10.2. Recommendations -Recreational Marine Anglers 10.10.3. Recommendations -Recreational Freshwater Anglers 10.10.4. Recommendations -Native American Subsistence Populations REFERENCES FOR CHAPTER 10 APPENDIX 1 OA APPENDIX 1 OB APPENDIX 10C Table 10-1. Total Fish Consumption by Demographic Variables Table 10-2. Mean and 95th Percentile of Fish Consumption (g/day) by Sex and Age Table 10-3. Percent Distribution of Total Fish Consumption for Females by Age Table 10-4. Percent Distribution of Total Fish Consumption for Males by Age Table 10-5. Mean Total Fish Consumption by Species Table 10-6. Best Fits of Log normal Distributions Using the Nonlinear Optimization (NLO) Method . Table 10-7. Per Capita Distribution of Fish Intake (g/day) by Habitat and Fish Type for the U.S. Population (Uncooked Fish Weight) Table 10-8. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) by Habitat for Consumers Only (Uncooked Fish Weight) Table 10-9. Per Capita Distribution of Fish Intake (mg/kg-day) by Habitat and Fish Type for U.S. Population (Uncooked Fish Weight) Table 10-10. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) by Habitat for Consumers Only (Uncooked Fish Weight) Table 10-11. Per Capita Distribution of Fish Intake (g/day) by Habitat and Fish Type for the U.S. Population (Cooked Fish Weight -As Consumed)) Table 10-12. Per Capita Distribution of Fish Intake (g/day) by Habitat for Consumers Only (Cooked Fish Weight -As Consumed)) Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish Table 10-13. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the U.S. Population by Age and Gender -As Consumed (Freshwater and Estuarine)

Table 10-14. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the U.S. Population by Age and Gender -As Consumed (Marine) Table 10-15. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the U.S. Population by Age and Gender-As Consumed (All Fish) Table 10-16. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (grams/day) for the U.S. Population Aged 18 Years and Older by Habitat-As*Consumed Table 10-17. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the u:s. Population by Age and Gender -As Consumed (Freshwater and Estuarine) Table 10-18. Per Capita Distribution *of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the U.S. Population by Age and Gender -As Consumed (Marine) Table 10-19. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the U.S. Population by Age and Gender -As Consumed (All Fish) Table 10-20. Per Capita Distribution of Fish (Finfish and *shellfish) Intake (mg/kg-day) for the U.S. Population Aged 18 Years and Older by Habitat-As Consumed Table 10-21. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for Consumers Only by Age and Gender -As Consumed (Freshwater and . Estuarine) Table 10-22. Per Capita Distribution of Fish (Finfish and Shellfish) Intake. (g/day) for Consumers Only by Age and Gender -As Consumed (Marine) Table 10-23. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for Consumers Only by Age and Gender -As Consumed (All Fish) Table 10-24. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for *consumers Only Aged 18 Years and Older by Habitat-As Co.nsumed Table 10-25. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for Consumers Only by Age and Gender -As Consumed (Freshwater and Estuarine) Table 10-26. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for Consumers Only by Age and Gender-As Consumed (Marine) Table 10-27. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for Consumers Only by Age and Gender -As Consumed (All Fish) Table 10-28. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for Consumers Only Aged 18 Years and Older by Habitat -As Consumed Table 10-29. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the U.S. Population by Age and Gender -Uncooked Fish Weight (Freshwater and Estuarine)
Table 10-30. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the *U.S. Population by Age and Gender-Uncooked Fish Weight (Marine) Exposure Factors Handbook . August 1997 Volume II-Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish Table 10-31. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the U.S. Population by Age and Gender-Uncooked* Fish Weight (All Fish) Table 10-32. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the U.S. Population Aged 18 Years and Older by Habitat -Uncooked Fish . Weight Table 10-33. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the U.S. Population by Age and Gender -Uncooked Fish Weight . (Freshwater and Estuarine)
Table 10-34. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the U.S. Population by Age and Gender -Uncooked Fish Weight (Marine) Table 10-35. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the U.S. Population by Age and Gender -Uncooked Fish Weight (All Fish) Table 10-36. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the U.S. Population Aged 18 Years and Older by Habitat -Uncooked Fish Weight Table 10-37. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for Consumers Only by Age and Gender -Uncooked Fish Weight (Freshwater and Estuarine)
Table 10-38. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for Consumers\Only by Age and Gender -Uncooked Fish Weight ,(Marine) Table 10-39. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for Consumers Only by Age and Gender -Uncooked Fish Weight (All Fish). Table 10-40. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for
Consumers Only Aged 18 Years and Older by Habitat -.Uncooked Fish Weight Table 10-41 . Per Capita Distribution of Fish ( Finfish and Shellfish)* Intake (mg/kg-day) for Consumers Only by Age and -Uncooked Fish Weight (Freshwater and Estuarine) Table 10-42. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for Consumers Only by Age and Gender -Uncooked Fish Weight (Marine) Table 10-43. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for Consumers Only by Age and Gender -Uncooked Fish Weight (All Fish) Table 10-44. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for Consumers Only Aged 18 Years and Older by Habitat -Uncooked Fish Weight Table 10-45. Distribution of Quantity of Fish Consumed (in grams) Per Eating Occasion, by Age and Sex Table 10-46. Mean Fish Intake in a Day, by Sex and Age *Table 10-47. Percent of Respondents That Responded Yes, No, or Don't Know to Eating Seafood in 1 Month (including shellfish, eels, or squid) Table 10-48. Number of Respondents Reporting Consumption of a Specified Number of Servings of Seafood in 1 Month
Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish Table 10-49. Number of Respondents Reporting Monthly Consumption of Seafood That Was Purchased or Caught by Someone They Knew Table 10-50. Estimated Number of Participants in Marine Recreational Fishing by State and Subregion Table 10-51. Estimated Weight of Fish Caught (Catch Type A and B1) by Marine. Recreational Fishermen, by Wave and Subregion Table 10-52. Average Daily Intake (g/day) of Marine Finfish, by Region and Coastal Status Table 10-53. Estimated Weight of Fish Caught (Catch Type A and B1) by Marine Recreational Fishermen by, Species Group and Subregion, Atlantic and Gulf Table 10-54. Estimated Weight of Fish Caught (Catch Type A and B1) by Marine . Recreational Fishermen by Species Group and Subregion, Pacific Table 10:-55. Median Intake Rates Based on .Demographic Data of Sport Fishermen and Their, Family/Living Group Table 10-56. Cumulative Distribution of Total Fish/Shellfish Consumption by Surveyed Sport Fishermen in the Metropolitan Los Angeles Area Table 10-57. Catch Information for Primary Fish Species Kept by Sport Fishermen (n=1059) Table 10-58. Percent of Fishing Frequency During the Summer and Fall Seasons in Commencement Bay, Washington Table 10-59. Selected Percentile Consumption Estimates (g/day) for the Survey and Total Angler Populations Based on the Reanalysis of the Puffer et al. (1981) and Pierce et al. ( 1981) Data Table 10-60. Means
and Standard Deviations of Selected Characteristics by Subpopulation Groups in Everglades, Florida Table 10-61. Mean Fish Intake Among Individuals Who Eat Fish and Reside in Househol,ds With Recreational Fish Consumption Table 10-62. Comparison of Seven-Day Recall and Estimated Seasonal Frequency for Fish Consumption Table 10-63. Distribution of Usual Fish *Intake Among Survey Main Respondents Who . Fished and Consumed Recreationally Caught Fish Table 10-64. Estimates of Fish Intake Rates of Licensed Sport Anglers in Maine During the 1989-1990 Ice Fishing or 1990 Open-Water Seasons Table 10-65. Analysis of Fish Consumption by Ethnic Groups for "All Waters" (g/day) Table 10-66. Total Consumption of Freshwater Fish Caught by All Survey Respondents During the 1990 Season Table 10-67. Mean Sport-Fish Consumption by Demographic Variables, Michigan Sport Anglers Fish Consumption Study, 1991-1992 Table 10-68. Distribution of Fish Intake Rates (from all sources and from sp9rt-caught sources) For 1992 Lake Ontario Anglers Table 10-69. Mean Annual Fish Consumption (g/day) for Lake Ontario Anglers, 1992, by Sociodemographic Characteristics Exposure Factors Handbook August 1997 I I I Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellf1sh Table 10-70. Percentile and Mean Intake Rates for Wisconsin Sport Anglers Table 10-71. Sociodemographic Characteristics of Respondents Table 10-72. Number of Grams Per Day of Fish Consumed by All Adult Respondents (Consumers and Non-consumers Combined)-Throughout the Year Table 10-73. Fish Intake Throughout the Year by Sex, Age, and Location by All Adult Respondents Table 10-74. Children's Fish Consumption Rates-Throughout Year Table 10-75. Sociodemographic Factors and Recent Fish Consumption Table 10-76. Number of Local Fish Meals Consumed Per Year by Time Period for All Respondents Table 10-77. Mean Number of Local Fish Meals Consumed Per Year' by Time Period for All Respondents and Consumers Only
Table 10-7.8. Mean Number of Local Fish Meals Consumed Per Year by Time Period and Selected Characteristics for All Respondents (Mohawk, N=97; Control, N=154) . . Table 10-79. Percentage of Individuals Using Various Cooking Methods at Specified
Frequencies
Table 10-80. Percent Moisture and Fat Content for Selected Species Table 10-81. Recommendations -General Population Table 10-82. Recommendations -General Population -Fish Serving Size Table :10-83. Recommendations -Recreational Marine Anglers Table 10-84. Recommendations -Freshwater Anglers Table 10-85. Recommendations -Native American Subsistence Populations Table 10-86. Summary of Fish Intake Studies Table 10-87. Confidence in Fish Intake Recommendations for General Population Table 10-88. Confidence in Fish Intake Recommendations for Recreational Marine Anglers Table 10-89. Confidence in Recommendations for Fish Consumption -Recreational Freshwater Table 10-90. Confidence in Recommendations for Native American Subsistence Fish Consumption Table 108-1. Percent of Fish Meals Prepared Using Various Cooking Methods by Residence Size Table 108-2. Percent of Fish Meals Prepared Using Various Cooking Methods by Age Table 108-3. Percent of Fish Meals Prepared Using Various Cooking Methods* by Ethnicity Table 108-4. Percent of Fish Meals Prepared Using Various Cooking Methods by Education Table 108-5. Percent of Fish Meals-Prepared Using Various Cooking Methods by Income Table 108-6. Percent of Fish Meals Where Fat was Trimmed or Skin was Removed, by Demographic Variables Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish Table 108-7. Method of Cooking of Most Common Species Kept by Sportfishermen Table 1 OB-8. Adult Consumption of Fish Parts Table -1 OC-1. Daily Average Per Capita Estimates of Fish Consumption U.S. Population -* Mean Consumption by Species Within Habitat -As Consumed Fish Table 10C-2. Daily Average Per Capita Estimates of Fish Consumption U.S. Population -Mean Consumption by Species Within Habitat -Uncooked Fish Table 1 OC-3. Daily Average Per Capita Estimates of Fish Consumption As Consumed Fish -Mean Consumption by Species Within Habitat -U.S. Population Table 1 OC-4. Daily Average Per Capita Estimates of Fish Consumption Uncooked Fish -Mean Consumption by Species Within Habitat-U.S. Population Figure 10-1. Seasonal Fish Consumption: Wisconsin Chippewa, 1990 Figure 10-2. Peak Fish Consumption: Wisconsin Chippewa, 1990 Exposure Factors Handbook August 1997 I Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellflsh 10. INTAKE OF FISH AND SHELLFISH 10.1. BACKGROUND Contaminated finfish and shellfish are potential sources of human exposure to toxic chemicals. Pollutants are carried in the surface waters, but also may be stored and accumulated in the sediments as a result of complex physical and chemical processes. Consequently, finfish and shellfish are exposed to these pollutants and may become sources of contaminated food. Accurately estimating exposure to a toxic chemical among a population that consumes fish from a polluted water body requires an estimation of intake rates of the caught fish by both fishermen and their families. Commercially caught fish are marketed widely, making the prediction of an individual's consumption from a particular commercial source difficult. Since the catch of recreational and subsistence fishermen is not "diluted" in this way, these individuals and their families represent the population that is most vulnerable to exposure by intake of contaminated fish from a specific location. This *section focuses on intake rates of fish. Note that in this section the term fish refers to both finfish and shellfish. The following subsections address intake rates for the general population, and recreational and subsistence fishermen. Data are presented for intake rates for both marine and freshwater fish, when available. The available studies have been classified as either key or relevant based on the guidelines given in Volume I, Section 1.3. Recommended intake rates are based on the results of key studies, but other relevant studies are also presented to provide the reader with added perspective on the current state-of-knowledge pertaining to fish intake. Survey data on fish consumption have been collected using a number of different approaches which need to be considered in interpreting the survey results. Generally, surveys are either "creel'! studies in which fishermen are interviewed while fishing, or broader population surveys using either mailed questionnaires or phone interviews. Both types of data can be useful for exposure assessment purposes, but somewhat different applications and interpretations are needed. In fact, results from creel studies have often been misinterpreted, due to inadequate knowledge of survey principles. Below, some basic facts about survey design are presented, followed by an analysis of* the differences between creel and population based studies. The typical survey seeks to draw inferences about a larger population from a smaller sample of that population. This larger population, from which the survey sample is to be taken and to which the results of the survey are to generalized, is denoted the target population of the survey. In order to generalize from the sample to the target population, the probability of being sampled must be known for each member of the target population. Exposure Factors Handbook August 1997
f Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellflsh This probability is reflected in weights assigned to each survey respondent, with weights being inversely proportional to sampling probability. When all members of the target population have the same probability of being sampled, all weights can be set to one and essentially ignored. In a mail or phone study of licensed anglers, the target population is generally all licensed anglers in a particular area, and in the studies presented, the sampling probability is essentially equal for all target population members. In a creel study, the target population is anyone who fishes at the locations being studied; generally, in a creel study, the probability of being sampled is not the same for all members of the target population. For instance, if the survey is conducted for one day at a site, then it will include all persons who fish there daily but only about 1 /7 of the people who fish there weekly, 1 /30th of the people who fish there monthly, etc. In this example, the probability of being sampled (or inverse weight) is seen to be proportional to the frequency of fishing. However, if the survey involves interviewers revisiting the same site on multiple days, and persons are only interviewed once for the survey, then the probability of being in the survey is not proportional to frequency; in fact, it increases less than proportionally with frequency. At the extreme of surveying the same site every day over the survey period with no interviewing, all members of the target population would have the same probability of being sampled regardless of fishing frequency, implying that the survey weights should all equal one. On the other hand, if the survey protocol calls for individuals to be interviewed each time an interviewer encounters them (i.e., without regard to whether they were previously interviewed), then the inverse weights will again be proportional to fishing frequency, no matter how many times interviewers revisit the same site. Note that when individuals can be interviewed multiple times, the results of each interview are included as separate records in the data base and the survey weights should be inversely proportional to the expected number of times that an individual's are included in the data base. In the published analyses of most creel studies, there is no mention of sampling weights; by default all weights are set to 1, implying .equal probability of sampling. However, since the sampling probabilities in a creel study, even with repeated interviewing at a site, are highly dependent on fishing frequency, the fish intake distributions reported for these surveys are not reflective of the corresponding target populations. Instead, those individuals with high fishing frequencies are given too big a weight and the distribution is skewed to the right, i.e., it overestimates the target population distribution. Price et al. ( 1994) explained this problem and set out to rectify it by adding weights to creel survey data; he used data from two creel studies (Puffer et al., 1981 and Pierce et al., 1981) as examples. Price et al. (1994) used inverse fishing frequency as survey weights and produced revised estimates of median and 95th percentile intake for the Exposure Factors Handbook August 1997
Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish above two studies. These revised estimates were dramatically lower than the original estimates. The approach of Price et al. ( 1994) is discussed in more detail in Section 10.5 where the Puffer et al. (1981) and Pierce et al. (1981) studies are summarized. When the correct weights are applied to survey data, the resulting percentiles reflect, on average, the distribution in the target population; thus, for example, an estimated 90 percent of the target population will have intake levels below the 90th percentile of the survey fish intake distribution.* There is another way, however, of characterizing distributions in addition to the standard percentile approach; this approach is reflected in statements of the form "50 percent of the income is received by, for example, the top 10 percent of the populatiori, which consists of individuals making more than $100,000", for example. Note that-the 50th percentile (median) of the income distribution is well below $100,000. Here the $100,000 level can be thought of as, not the 50th percentile of the population income distribution, but as the 50th percentile of the "resource utilization distribution" (see Appendix 10A for technical discussion of this distribution). Other percentiles of the resource utilization distribution have similar interpreta-tions; e.g., the 90th percentile of the resource utilization distribution (for income) would be that level of income such that 90 percent of total income is received by individuals with incomes below this level and 10 percent by individuals with income above this level. This alternative approach to characterizing distributions is of particular interest when a relatively small fraction of individuals consumes a relatively large fraction of a resource, which is the case with regards to recreational fish consumption. In the studies of recreational anglers, this alternative approach, based on resource utilization, will be presented, where possible, in addition to the primary approach of presenting the standard percentiles of the fish intake distribution. It has been determined* that the resource utilization approach to characterizing distributions has relevance to the interpretation of creel survey data. As mentioned above,
most published analyses of creel surveys do not employ weights reflective of sampling probability, but instead give each respondent equal weight. For mathematical reasons that are explained in Appendix 1 OA, when creel analyses are performed in this (equal weighting) manner, the calculated percentiles of the fish intake distribution do not reflect the percentiles of the target population fish intake distribution but instead reflect (approximately) the percentiles of the "resource utilization distribution". Thus, one would not expect 50 percent of the target population to be consuming above the median intake level as reported from such a creel survey, but instead would expect that 50 percent of the total recreational fish consumption would be individuals consuming above this level. As with the example above, and in accordance with the statement above that creel surveys analyzed in this manner overestimate intake distributions, the actual median level of intake in the target population will be less (probably considerably so) than this level and, accordingly, (considerably) less than 50 percent of the target population will be consuming at or above this level. These considerations are discussed when the results of individual Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish creel surveys are presented in later sections and should be kept in mind whenever estimates based on creel survey data are utilized. The U.S. EPA has prepared a review of and an evaluation of five different survey methods used for obtaining fish consumption data. They are: Recall-Telephone Survey;
Recall-Mail Survey;
Recall-Personal Interview;
Diary; and Creel Census. , The reader is referred to U.S. EPA 1992-Consumption Surveys for Fish and Shellfish for more detail on these survey methods and their advantages and limitations. 10.2. KEY GENERAL POPULATION STUDIES Tuna Research Institute Survey-The Tuna Research Institute (TRI) funded a study of fish consumption which was performed by the National Purchase Diary (NPD) during the period of September, 1973 to August, 197 4. The data tapes from this survey were obtained by the National Marine Fisheries Service (NMFS), which later, along with the FDA, USDA and TRI, conducted an intensive effort to identify and correct errors in the data base. Javitz (1980) summarized the TRI survey methodology and used the corrected tape to generate fish intake distributions for various sub-populations. The TRI survey sample included 6,980 families who were currently participating in a syndicated national purchase diary panel, 2,400 additional families where the head of household was female and under 35 years old; and 210 additional black families ( Javitz, 1980). Of the 9,590 families in. the total sample, 7,662 families (25,162 individuals) completed the questionnaire, a response rate of 80 percent. The survey was weighted to represent the U.S. population based on a number of census-defined controls (i.e., census region, household size, income, presence of children, race and age). The calculations of means, percentiles, etc. were performed on a weighted basis with each person contributing in proportion to his/her assigned survey weight. The survey population was divided into 12 different sample segments and, for each of the 12 survey months, data were collected from a different segment. Each survey household was given a diary in which they recorded, over a one month period, the date of any fish meals consumed and the following accompanying information: the species of fish consumed, whether the fish was commercially or recreationally caught, the way the fish was packaged (canned, frozen fresh, dried, smoked), the amount of fish prepared and consumed, and the number of servings consumed by household members and guests. Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellt1sh Both meals eaten at home and away fro'm home were recorded. The amount of fish prepared was determined as follows (Javitz, 1980): "For fresh fish, the weight was recorded in ounces and may have included the weight of the head and tail. For frozen fish, the weight was recorded in packaged ounces, and it was noted whether the fish was breaded or combined with other ingredients (e.g., TV dinners). For canned fish, the weight was recorded in packaged ounces and it was noted whether the fish was canned in water, oil, or with other ingredients (e.g., soups)". Javitz (1980) reported that the corrected survey tapes contained data on 24,652 individuals who consumed fish in the survey month and that tabulations performed by NPD indicated that these fish consumers represented 94 percent of the U.S. population. For this population of fish consumers", Javitz (1980) calculated means and percentiles of fish consumption by demographic variables (age, sex, race, census region and community type) and overall (Tables 10-1 through 10-4). The overall _mean fish intake rate among fish consumers was calculated at 14.3 g/day and the 95th percentile at 41. 7 g/day. As seen in Table 10-1, the mean and 95th percentile offish consumption were higher for Asian-Americans as compared to the other racial groups. Other differences in intake rates are those between gender and age groups. While males (15.6 g/d) eat slightly more fish than females (13.2 g/d), and adults eat more fish than children, the corresponding differences in body weight would probably compensate for the different intake rates in exposure calculations (Javitz, 1980). There appeared to be no large differences in. regional intake rates, although higher rates are shown in the New England and Middle Atlantic census regions. The mean and 95th percentile intake rates by age-gender groups are presented in Table 10-2. Tables 10-3 and 10-4 present the distribution of,fish consumption for females and males, respectively, by age; these tables give the percentages of females/males in a given age bracket with intake rates within various ranges. Table 10-5 presents mean total fish consumption by fish species. The TRI survey data were also utilized by Rupp et al. (1980) to generate fish intake distributions for three age groups ( < 11, 12-18, and 1'9+ years) within each of the 9 census regions and for the entire United States. Separate distributions were derived for freshwater finfish, saltwater finfish and shellfish; thus, a total of 90 (3*3*10) different distributions were derived, each corresponding to intake of a specific category of fish for a given age group within a given region. The analysis of Rupp et al. (1980) included only those respondents with known age. This* amounted to 23,213 respondents. Ruffle et al. ( 1994) used the percentiles data of Rupp et al. ( 1980) to estimate the best fitting lognormal parameters for each distribution. Three methods (non-linear optimization, first probability plot and second probability plot) were used to estimate Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish optimal parameters. Ruffle et al. ( 1994) determined that, of the three methods, the linear optimization method (NLO) generally gave the best results. For some of the distributions fitted by the NLO method, however, it was determined that the lognormal model* did not adequately fit the empirical fish intake distribution. Ruffle et al. ( 1994) used a criterion of minimum sum of squares (min SS) less than 30 to identify which distributions provided adequate fits. Of the 90 distributions studied, 77 were seen to have min SS < 30; for these, Ruffle et al. (1994) concluded that the NLO modeled lognormal distributions are "well suited for risk assessment". Of the remaining 13 distributions, 12 had min SS > 30; for these Ruffle et al. ( 1994) concluded that modeled log normal distributions "may also be appropriate for use when exercised with due care and with sensitivity analyses". One distribution, that of freshwater finfish intake for children < 11 years of age in New England, could not be modeled due to the absence of any reported consumption. . Table 10-6 presents the optimal lognormal parameters, the mean (µ), standard deviation (s), and min SS, for all 89 modeled distributions. These parameters can be used to determine
percentiles of the corresponding distri.bution of average daily fish consumption rates through the relation DFC(p)=exp[µ+ z(p)s] where DFC(p) is the pth percentile of the distribution of average daily fish consumption rates and z(p) is the z-score associated with the pth percentile (e.g., z(50)=0 ). The mean average daily fish consumption rate is given by exp[µ+ 0.5s2]. The analyses of Javitz (1980) and Ruffle et al. (1994) were based on consumers only, who are estimated to represent 94.0 percent of the U.S. population. U.S. EPA estimated the mean intake in the general population by multiplying the fraction consuming, 0.94, by the mean among consumers reported by Javitz (1980) of 14.3 g/day; the resulting estimate is 13.4 g/day. The 95th percentile estimate of Javitz (1980) of 41.7 g/day among consumers would be essentially unchanged when applied to the general population; 41. 7 g/day would represent the 95.3 percentile (i.e., 100*[0.95*0.94+0.06]) among the general population. Advantages of the TRI data survey are that it was a large, nationally representative survey with a high response rate (80 percent) and wa.s conducted over an entire year. In addition, consumption was recorded in a daily diary over a one month period; this format should be more reliable than one based on one-month recall. The upper percentiles presented are derived from one month of data, and are likely to overestimate the corresponding upper percentiles of the long-term (i.e., one year or more) average daily fish intake distribution. Similarly, the standard deviation of the fitted lognormal distribution probably overestimates the standard deviation of the long-term distribution. However, the period of this survey (one month) is considerably longer than those of many other consumption studies, including the USDA National Food Consumption Surveys, which report consumption over a 3 day to one week period. Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish Another obvious limitation of this data base is that it is now over twenty years out of date. Ruffle et al. (1994) considered this shortcoming and suggested that one may wish to shift the distribution upward to account for the recent increase in fish consumption. Adding ln(1+x/100) to the log meanµ will shift the distribution upward by x percent (e.g., adding 0.22 = ln(1.25) increases the distribution by 25 percent). Although the TRI survey distinguished between recreationally and commercially caught fish, Javitz (1980), Rupp et al. (1980), and Ruffle et al. (1994) (which was based on Rupp et al., 1980) did not present analyses by this variable. U.S. EPA {1996a) -Daily Average Per Capita Fish Consumption Estimates Based on the Combined USDA 1989, 1990, and 1991 Continuing Survey of Food Intakes by Individuals (CSF/1)-* The USDA conducts the CSFll on an ongoing basis. U.S. EPA used the 1989, 1990, and 1991 CSFll data to generate fish intake estimates. Participants in the CSFll provided 3 consecutive days of dietary data. For the first day's data, participants supplied dietary recall information to an in-home interviewer. Second and third day dietary intakes were recorded by participants. Data collection for the CSFI I started in April of the given yerar and was completed in March of the following year. The CSFll contains 469 fish-related food codes; survey respondents reported consumption across 284 of these codes. Respondents estimated the weight of each food that they consumed. The fish component (by weight) of these foods was calculated using data from the recipe file for release 7 of the USDA's Nutrient Data Base for Individual Food Intake Surveys. The amount of fish consumed by each individual was then calculated by summing, over all fish containing foods, the product of the weight of food consumed and the fish component (i.e., the percentage fish by weight) of the food. The recipe file also contains cooking loss factors associated with each food. These were utilized to convert, for each fish food, the as-eaten fish weight consumed into an uncooked equivalent weight of fish. Analyses of fish intake were performed on both an as-eaten and uncooked basis. Each (fish-related) food code was assigned by EPA a habitat type of either freshwater/estuarine or marine. Food codes were also designated as finfish or shellfish. Average daily individual consumption (g/day) for a given fish type-by-habitat category (e.g., marine finfish) was calculated by summing the amount. of fish consumed by the *individual across the three reporting days for all fish-related food codes iri the given by-habitat category and then dividing by 3. Individual consumption per day consuming fish (g/d!3Y) was calculated similarly except that total fish consumption was divided by the specific number of survey days the individual reported consuming fish; this was calculated* for fish consumers only (i.e., those consuming fish on at least one of the three survey days). The reported body-weight of the individual was used to convert consumption in g/day to consumption in g/kg-day. Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 Intake of Fish and Shellfish There were a total of 11,912 respondents in the combined data set who had three-day dietary intake data. Survey weights were assigned to this data set to make it representative of the U.S. population with respect to various demographic characteristics related to food intake. / . U.S. EPA (1996a) reported means, medians, upper percentiles, and 90-percent interval estimates for the 90th, 95th, and 99th percentiles. The 90-percent interval estimates are nonparametric estimates from bootstrap techniques. The bootstrap estimates result from the percentile method which estimates the lower and upper bounds for the interval estimate by the 1 OOa percentile and 100 (1-a) percentile estimates from the non-parametric distribution of the given point estir:nate (U.S. EPA, 1996a). Analyses of fish intake were performed on an as-eaten as well as on an uncooked equivalent basis and on a g/day and g/kg-day basis. Table 10,..7. gives the mean and various percentiles of the distribution of per-capita fish intake rates (g/day) based on uncooked equivalent weight by habitat and fish type, for the general population. The mean. per capita intake rate of finfish and shellfish from all habitats was 20.1 g/day. Per-capita consumption estimates by species are shown in Appendix 1 OC. Table 10-8 displays the mean and various percentiles of the distribution of total fish intake per day consumi11g fish, by habitat for consumers only. Also displayed is the percentage of the population consuming fish of the specified habitat during the three day survey period. Tables 10-9 and 10-10 present similar results as above but on a mg/kg-day basis; Tables 10-11 and 10-12 present results in the same format for fish intake (g/day) on an as-eaten (cooked) basis.
Tables 10-13 through 10-44 present data for daily average per capita fish consumption by age and gender. These data are presented by selected age grouping (4
and under, 15-44, 45 and older, all ages) and gender. Tables 10-13 through 10-20 present fish intake data (g/day and mg/kg-day) on an as consumed basis for the general population and Tables 10-21through10-28 for consumers only. Tables t0-29 through 10-44 provide intake data (g/day and mg/kg-day) on an uncooked equivalent basis for the same population groups described above. ,,-/ The advantages of this study are its large size, its relative currency* and its representativeness. In addition, through use of the USDA recipe files, the analysis identified all fish-related food codes and estimated ttie percent fish content of each of these codes. .By contrast, some analyses of the USDA National Food Consumption Surveys (NFCSs) which reported p*er capita fish intake rates ( e .. g., Pao et al., 1982; USDA, 1992a), excluded certain fish containing foods (e:g., fish mixtures, frozen plate meals) in their calculations. Exposure Factors Handbook. August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish Results from the 1977-1978 NFCS survey (Pao et al., 1982) showed that only a small percentage of consumers ate fish on more than one occasion per day. This implies that the distribution presented for fish intake per day consuming fish can be used as a surrogate for the distribution of fish intake per (fish) eating occasion (Table 10-8). Also, it should be noted that the 1989-91 CSFll data are not the most recent intake survey data. USDA has recently made available data from its 1994 and 1995 CSFll. Over 5,500 people nationwide participated in both of these surveys, providing recalled food intake information for two separate days. Although the 2-day data analysis has not been conducted, USDA published results for the respondents' intakes on the first day surveyed (USDA, 1996a; USDA, 1996b). USDA 1996 survey data will be made available later in 1997. As soon as 1996 data are available, EPA will take steps to get the 3-year de:tta (1994, 1995, 1996) analyzed and the food ingestion factors updated. Meanwhile, comparisons between the mean daily fish intake per individual in a day from the USDA survey data from years 1977-78, 1987-88, 1989-91, 1994, and 1995 indicate that fish intake has been relatively constant over time. The 1-day fish intake rates were 11 g/day, 11 g/day, 13 g/day, 9 g/day, and 11 g/day for survey years 1977-78, 1987-88, 1989-91, 1994, and 1995, respectively. This indicates that the 1989-91 CSFll data presented in this handbook are probably adequate for assessing fish ingestion exposure for current populations. 10.3. RELEVANT GENERAL POPULATION STUDIES Pao et al. {1982) -Foods Commonly Eaten by Individuals: Amount Per Day and Per Eating Occasion-The USDA 1977-78 Nationwide Food Consumption Survey (NFCS) was described in Chapter 9. The survey consisted of a household and individual component. For the individual component, all members of surveyed households were asked to provide 3 consecutive days of dietary data. For the first day's data, participants supplied dietary recall information to an in-home interviewer. Second and third day dietary intakes were recorded by participants. A total of 15,000 households were included in the 1977-78 NFCS and about 38,000 individuals completed the 3-day diet records. Fish intake was estimated based on consumption of fish products identified in the NFCS data base according to NFCS-defined food codes. These products included fresh, breaded, floured, canned, raw and dried fish, but not fish mixtures or frozen plate meals. Pao et al. (1982) used the 1977-78 NFCS to examine the quantity of fish consumed per eating occasion. For each individual consuming fish in the 3 day survey period, quantity of fish consumed per eating occasion was derived by dividing the total report.ed fish intake over the 3 day period by the number of occasions the individual reported eating fish. The distributions, by age and sex, for the quantity of fish consumed per eating occasion are displayed in Table 10-45 (Pao et al., 1982). For the general population, the average quantity of fish consumed per fish meal was 117 g, with a 95th percentile of 284 Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish g. Males in the age groups 19..:34, 35-64 and 65-74 years had the highest average and 95th percentile quantities among the age-sex groups presented .. Pao et al. ( 1982) also used the data from this survey set to calculate per capita fish intake rates. However, because these data are now almost 20 years out of date, this analysis is not considered key with respect to assessing per capita intake (the average quantity of fish consumed per fish meal should be less subject to change over time than is per capita intake). In addition, fish mixtures and frozen plate meals were not included in the calculation of fish intake. The per capita fish intake rate reported by Pao et al. (1982) was 11.8 g/day. The 1977-1978 NFCS was a large and well designed survey and the data are representative of the U.S. population. USDA Nationwide Food Consumption Survey 1987-88 -The USDA 1987-88 Nationwide Food Consumption Survey (NFCS) was described in Chapter 9. Briefly, the survey consisted of a household and individual component. The household component asked about household food consumption over the past one week period. For the individual component, each member of a surveyed household was interviewed (in person) and asked to recall all foods eaten the previous day; the information from this interview made up the "one day data" for the survey. In addition, members were instructed to fill out a c;letailed dietary record for the day of the interview and the following day. The data for this entire. 3-day period made up the "3-day diet records". A statistical sampling design was used to ensure that all seasons, geographic regions of the U.S., demographic, and socioeconomic groups were represented. Sampling weights were used to match the population distribution of 13 demographic characteristics related to food intake (USDA, 1992a). Total fish intake was estimated based on consumption of fish products identified in the NFCS data base according to NFCS-defined food codes. These products included fresh, breaded, floured, canned, raw and dried fish, but not fish mixtures or frozen plate
meals. A total of 4,500 households participated in the 1987-88 survey; the household response rate was 38 percent. One day data were obtained for 10, 172 (81 percent) of the 12,522 individuals in participating households; 8,468 (68 percent) individuals completed 3-day diet records. USDA (1992b) used the one day data to derive per capita fish intake rate and intake rates for consumers of total fish. rates, calculated by sex and age group, are shown in Table 10-46. Intake rates for consumers-only were calculated by dividing the per capita intake rates by the fractions of the population consuming fish in one day. Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish The 1987-1988 NFCS was also utilized to estimate consumption ofhome produced fish (as well as home produced fruits, vegetables, meats and dairy products) in the general U.S. population. The methodology for estimating home-produced intake rates was rather complex and involved combining the household and individual components of the NFCS; the methodology, as well as the estimated intake rates, are described in detail in Chapter 12. However, since much of the rest of this chapter is concerned with estimating consumption of recreationally caught, i.e., home produced fish, the methods and results of Chapter 12, as they pertain to fish consumption, are summarized briefly here. A total of 2.1 percent of the survey population reported home produced fish consumption during the survey week. Among consumers, the mean intake rate was 2.07 g/kg-day and the 95th percentile was 7.83 g/kg-day; the per-capita intake rate was 0.04 g/kg-day. Note that intake rates for home-produced foods were indexed to the weight of the survey respondent and reported in g/kg-day. It is possible to compare the estimates of home-produced fish consumption derived in this analyses with estimates derived from studies of recreational anglers (described in Sections 10.4-10.8); however, the intake rates must be put into a similar context. The. home-produced intake rates described refer to average daily intake rates among individuals consuming home-produced fish in a week; results from recreational angler studies, however, usually report average daily* rates for those eating home-produced fish (or for those who recreationally fish) at least some time during the year. 'Since many of these latter individuals eat home-produced *fish at a frequency of less than once per week, the ave_rage daily intake in this group would be expected to be less than that reported. The NFCS household component contains the question "Does anyone in 'your household fish?". For the population answering yes to this question (21 percent of households), the NFCS data show that 9 percent consumed home-produced fish in the week of the survey; the mean intake rate for these consumers from fishing households was 2.2 g/kg-day. (Note that 91 percent of individuals reporting home grown fish consumption for the week of the survey indicated that a household member fishes; the overall mean intake rate among home-produced fish consumers, regardless of fishing status, was the above reported 2.07 g/kg-day). The per capita intake rate among those living in a fishing household is then calculated as 0.2 g/kg-day (2.2
0.09). Using the estimated average weight of survey participants of 59 kg, this translates into 11.8 g/day. Among members of fishing households, home-produced fish consumption accounted for 32.5 percent of total fish consumption. As discussed in Chapter 12 of this volume, intake rates for home-produced foods, including fish, are based on the results of the household survey, and as such, reflect the weight of fish taken into the household. In most of the recreational fish surveys discussed later in this section, the weight of the fish catch (which generally corresponds to the weight . Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shelll1sh taken into the household) is multiplied by an edible fraction to convert to an uncooked equivalent of the amount consumed. This fraction may be species specific, but some studies used an average value; these average values ranged from 0.3 to 0.5. Using a factor of 0.5 would convert the above 11.8 g/day rate to 5.9 g/day. This estimate, 5:9 g/day, of the per-capita fish intake rate among members of fishing households is within the range of the per-capita intake rates among recreational anglers addressed in sections to follow. An advantage of analyses based on the 1987-1988 USDA NFCS is that the data set is a large, geographically and seasonally balanced survey of a representative sample of the U.S. population. The survey* response rate, however, was low and an expert panel concluded that.it was not possible to establish the presence or absence of non-response bias (USDA, 1992b ). Limitations of the home-produced analysis are given in Chapter 12 of this volume.
Tsang and Klepeis (1996) -National Human Activity Pattern Survey (NHAPS) -The U.S. EPA collected information for the general population on the duration and frequency of.time spent in selected activities and time spent in selected microenvironments via 24-hour diaries. Over 9,000 individuals from 48 contiguous states participated in NHAPS. Approximately 4,700 participants also provided information on seafood consumption. The sljrvey was conducted between October 1992 and September 1994. Data were collected on the (1) number.of people that ate seafood in the last month, (2) the number of servings of seafood consumed, and (3) whether the seafood consumed was caught or purchased (Tsang and Klepeis, 1996). The participant responses were weighted according to selected demographics such as age, gender, and race to ensure that results were representative of the U.S. population. Of those 4, 700 respondents, 2,980 (59.6 percent) ate seafood (including shellfish, eels, or squid) in the last month (Table 10-47). The number of servings per month were categorized in ranges of 1-2, 3-5, 6-10, 11-19, and 20+ servings per month (Table 10-48). The highest percentage (35 percent) of respondent population had an intake of 3-5 servings per month. Most (92 percent) of the respondents purchased the seafood they ate (Table 10-49). Intake data were not provided in the survey. However, intake offish can be estimated using the information on the number of servings of fish eaten from this study and serving size data from other studies. The recommended mean value in this handbook for fish serving size is 129 g/serving (Table 10-82). Using this mean value for serving size and assuming that the average individual eats 3-5 servings pe.r month, the amount of seafood eaten per month would range from 387 to 645 grams/month or 12.9 to 21.5 g/day for the highest percentage of the population. These values are within the range of mean intake values for total fish (20.1 g/day) calculated in the U.S. EPA analysis of the USDA CSFll data. It should be noted that an all inclusive description for seafood was not presented in Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish Tsang and Klepeis (1996). It is not known if processed or canned seafood and seafood mixtures are included in the seafood category. The advantages of NHAPS is that the data were collected for a large number of individuals and are representative of the U.S. general population. However, evaluation of seafood intake was not the primary purpose of the study and the data do not reflect the actual amount of seafood that was eaten. However, using the assumption described above, the estimated seafood intake from this study are comparable to those observed in the EPA CSFll analysis. 10.4. KEY RECREATIONAL (MARINE FISH STUDIES) National Marine Fisheries Service (1986a, b, c; 1993) -The National Marine Fisheries Ser\tice (NMFS) conducts systematic surveys, on a continuing basis, of marine recreational fishing. These surveys are designed to estimate the size of the recreational marine finfish catch by location, species and fishing mode. In addition, the surveys provide estimates for the total number of participants in marine recreational finfishing and the total number of fishing trips. The surveys are not designed to estimate individual consumption . offish from marine recreational sources, primarily because they do not attempt to estimate the number of individuals consuming the recreational catch. Intake rates for inarine 'recreational anglers can be estimated, however, by employing assumptions derived from other data sources about the number of consumers. The NMFS surveys involve two components, telephone surveys and direct interviewing of fishermen in the field. The telephone survey randomly samples residents of coastal regions, defined generally as counties within 25 miles of the nearest seacoast, and inquires about participation in marine recreational fishing in the resident's home state in the past year, and more specifically, in the past two months. This component of the survey is used to estimate, for each coastal state, the total number of coastal region residents who participate in marine recreational fishing (for finfish) within the state, as well as the total number of (within state) fishing trips these residents take. To estimate the total number of participants and fishing trips in the state, by coastal residents and others, a ratio approach, based on the field interview data, was used. Thus, if the field survey data found that there was a 4:1 ratio of fishing trips taken by coastal residents as compared to trips taken by non-coastal and out of state residents, then an additional 25 percent would be added to the number of trips taken by coastal residents to generate an estimate of the total number of within state trips. The field intercept survey is essentially a creel type survey. The survey utilizes a national site register which details marine fishing locations in each state. Sites for field interviews are chosen in proportion to fishing frequency at the site. Anglers fishing on shore, private boat, and charter/party boat modes who had completed their fishing were Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish interviewed. The field survey included questions about frequency of fishing, area of fishing, age, and place of residence. The fish catch was classified by the interviewer as either type A, type 81 or type 82 catch. The type A catch denoted fish that were taken whole from the fishing site and were available for inspection. The type 81 and 82 catch were not available for inspection; the former consisted of fish used as bait, filleted, or discarded dead while the latter was fish released alive. The type A catch was identified by species and weighed, with the weight reflecting total fish weight, including inedible parts. The type 81 catch-was not weighed, but weights were estimated using the average weight derived from the type A catch for the given species, state, fishing mode and season of the year. For both the A and 81 catch, the intended disposition of the catch (e.g., plan to eat, plan to throw away, etc.) was ascertained. EPA obtained the raw data tapes from NMFS in order to generate intake distributions and other specialized analyses. Fish intake distributions were generated using the field survey tapes. Weights proportional to the inverse. of the angler's reported fishing frequency were employed to correct for the unequal probabilities of sampling; this was the same approach used by NMFS in deriving their estimates. Note that in the field survey, anglers were interviewed regardless of past interviewing experience; thus, the use of . inverse fishing frequency as weights was justified (see Section 10.1 ). For each angler interviewed in the field survey, the yearly amount of fish caught that was intended to be eaten by the angler and his/her family or friends was estimated by EPA as follows: Y = [(wt of A catch)* IA+ (wt of 81 catch)* 16] *[Fishing frequency] where IA (16) are indicator variables equal to 1 if the type A (81) catch was intended to be eaten and equal to 0 otherwise. To convert Y to a daily fish intake rate by the angler, it was necessary to convert amount of fish caught to edible amount of fish, divide by the number of intended consumers, and convert from yearly to daily rate. Although theoretically possible, EPA chose not to use species specific edible fractions to convert overall weight to edible fish weight since edible fraction estimates were not readily available for many marine species. Instead, an average value of 0.5 was employed. For the number of intended consumers, EPA used an average value of 2.5 which was an average derived from the results of several studies of recreational fish consumption (Chem risk, 1991; Puffer et al., 1981; West et al., 1989). Thus, the average daily intake rate (ADI) for each angler was calculated as I ADI :::: y * (0.5)/[2.5" 365] (Eqn. 10-2) I Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish Note that ADI will be Ofor those anglers who either did r)Ot intend to eat their catch or who did not catch any fish. The distribution of ADI among anglers was calculated by region and coastal status (i.e., coastal versus non-coastal counties). A mean ADI for the overall population of a given area was calculated as follows: first the estimated number of anglers in the area was multiplied by the average number of intended fish consumers (2.5) to get a total number of recreational marine finfish consumers. This number was then multiplied by the mean ADI among anglers to get the total recreational marine finfish consumption in the area. Finally, the mean ADI in the population was calculated by dividing total fish consumption by the total population in the area. 1 The results presented below are based on the results of the 1993 survey. Samples sizes were 200,000 for the telephone survey and 120,000 for the field surveys. All coastal states in the continental U.S. were included in the survey except Texas and Washington. Table 10-50 presents the estimated number of coastal, non-coastal, and out-of-state fishing participants by state and region of fishing. Florida had the greatest number of both Atlantic and Gulf participants. The total number of coastal residents who participated in . marine finfishing in their home state was 8 million; an additional 750,000 non-coastal residents participated in marine finfishing in their home state. Table 10-51 presents the estimated total weight of the A and B 1 catch by region and time of year. For each region, the greatest catches were during the six-month period from May through October. This period accounted for about 90 percent of the North and Mid-Atlantic catch, about 80 percent of the Northern California and Oregon catch, about 70 percent of the Southern Atlantic and Southern California catch and 62 percent of the Gulf catch. Note that in the North and Mid-Atlantic regions, field surveys were not done in January and February due to very low fishing activity. For all regions, over half the catch occurred within 3 miles of the shore or in inland waterways. Table 10-52 presents the mean and 95th percentile of average daily intake of recreationally caught marine finfish among anglers by region. The mean ADI among all *anglers was 5.6, 7.2, and 2.0 g/day for the Atlantic, Gulf, and Pacific regions, respectively. Also given is the per-capita ADI in the overall population (anglers and non.:.anglers) of the region and in the overall coastal population of the region. Table 10-53 gives the distribution of the catch by species for the Atlantic and Gulf regions and Table 10-54 for Pacific regions. The NMFS surveys provide a large, up-to-date, and geographically representative sample of marine angler activity in the U.S. The major limitation of this data base in terms of estimating fish intake is the lack of information regarding the intended number of consumers of each angler's catch. In this analysis, it was assumed that every angler's catch was consumed by the same number (2.5) of people; this number was derived from Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellt1sh averaging the results of other studies. This assumption introduces a relatively low level of uncertainty in the estimated.mean intake.rates among anglers, but a somewhat higher level of uncertainty in the estimated intake distributions. It should be noted that under the above assumption, the distributions shown here pertain not only to the population of anglers, but also to the entire population of recreational fish consumers, which is 2.5 times the number of anglers. If the number of consumers was changed, to, for instance, 2.0, then the distribution would be increased by a factor of 1.25 (2.5/2.0), but the estimated population of recreational fish consumers to which the distribution would apply would decrease by a factor of 0.8 (2.0/2.5). Note that the mean intake rate of marine finfish in the overall population .is independent of the assumption of number of intended fish consumers. Another un_certainty involves the use of 0.5 as an .(average) edible fraction. This figure is somewhat conservative (i.e., the true average edible fraction is probably lower); thus, the intake rates calculated here may be biased upward somewhat. It should be noted again that the recreational fish intake distributions given refer only to marine finfish. In addition, the intake rates calculated are based only on the catch of anglers in their home state. Marine fishing performed out-of-state would not be included in these distributions. Therefore, these distributions give an estimate of consumption of locally caught fish. 10.5. RELEVANT RECREATIONAL MARINE STUDIES Puffer et al. (1981) -Intake Rates of Potentially Hazardous Marine Fish Caught in the Metropolitan Los Angeles Area -Puffer et al. (1981) conducted a creel survey with sport fishermen in the Los Angeles area in 1980. The survey was conducted at 12 sites in the harbor and coastal areas to evaluate intake rates of potentially hazardous marine fish and shellfish by local, non:..professional fishermen. It was conducted for the full 1980 calendar year, although inclement weather in January, February, and March limited the interview days. Each site was surveyed an average of three times per month, on different days, and at a different time of the day. The survey questionnaire was designed to collect information on demographic characteristics, fishing patterns, species, number of fish caught, and fish consumption patterns. Scales were used to obtain fish weights. Interviews were conducted only with anglers who had caught fish, and the anglers were interviewed only once during the entire survey period. Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish Puffer et al. (1981) estimated daily consumption rates (grams/day) for each angler using the following equation: (K x N x W x F)/[E x 365] where: K = edible fraction of fish (0.25 to 0.5 depending on species); N = number of fish in catch; W = average weight of (grams) fish in catch; F frequency of fishing/year; and E = number of fish eaters in family/living group. (Eqn. 10-3) No explicit survey weights were used in analyzing this survey; thus, each respondent's data was given equal weight. A total of 1,059 anglers were interviewed for the survey. The ethnic and age distribution of respondents is shown in Table 10-55; 88 percent of respondents were male. The median intake rate was higher for Oriental/Samoan anglers (median 70.6 g/day) than for other ethnic groups and higher for those ages over 65 years (median 113.0 g/day) than for other age groups. Puffer et al. (1981) found similar median intake rates for seasons; 36.3 g/day for November through March *and 37. 7 g/day for April through October. Puffer et aL ( 1981) also evaluated fish preparation methods; these data are presented in Appendix 1 OB. The cumulative distribution of recreational fish (finfish and shellfish) consumption by survey respondents is presented in Table 10-56; this distribution was . calculated only for those fishermen who indicated they eat the fish they catch. The median fish consumption rate was 37 g/day and the 90th percentile rate was 225 g/day (Puffer et al., 1981 ). A description of catch patterns for primary fish species kept is presented in Table 10-57.
As mentioned in the Background to this Chapter, intake distributions derived from analyses of creel surveys which did not employweights reflective of sampling probabilities will overestimate the target population intake distribution and will, in fact, be more reflective of the "resource utilization distribution". Therefore, thereported median level of 37.3 g/day does not reflect the fact that 50 percent of the target population has intake above this level; instead 50 percent of recreational fish consumption is by individuals consuming at or above 37.3 g/day. In order to generate an intake distribution reflective of that in the target population, weights inversely proportional to sampling probability need to be employed. Price et al. ( 1994) made this attempt with the Puffer et al. ( 1981) survey data, using inverse fishing frequencies as the sampling weights. Price et al. (1994) was unable to get the raw data for this survey, but using frequency tables and the average level of fish consumption per fishing trip provided in Puffer et al. (1981 ), generated an approximate revised intake distribution. This distribution was dramatically lower than that obtained by Puffer et al. ( 1981 ); the median was estimated at 2.9 g/day (compared with Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish 37.3 from Puffer et al., 1981) and the 90th percentile at35 g/day (compared to 225 g/day from Puffer et al., 1981). There are several limitations to the interpretation of the percentiles presented by both Puffer et al. (1981) and Price et al. (1994). As described in Appendix 10A, the interpretation of percentiles reported from creel surveys in terms of perGentiles of the "resource utilization distribution" is approximate and depends on several assumptions. One of these.assumptions is that sampling probability is proportional to inverse fishing frequency. In this survey, where interviewers revisited sites numerous times and anglers were not interviewed more than once, this assumption is not valid, though it is likely that the sampling probability is still highly dependant on fishing frequency so that the assumption does hold in an approximate sense. The validity of this assumption also impacts the interpretation of percentiles reported by Price et al. (1994) since inverse frequency was used as sampling weights. It is likely that the value (2.9 g/day) of Price et al. (1994) underestimates somewhat the median intake in the target population, but is much closer to the actual value than the Puffer et al. (1981) estimate of 37 .3 g/day. Similar statements would apply about the 90th percentile. Similarly, the 37.3 g/day median value, if interpreted as the 50th percentile of the "resource utilization distribution", is also somewhat of an underestimate. It should be noted again that the fish intake distribution generated by Puffer et al. (1981) (and by Price et al., 1994) was based only on fishermen who caught fish and ate the fish* they caught. If all anglers were included, intake estimates would be somewhat lower. In contrast, the survey assumed that the number of fish caught at the time of the interview was all that would be caught that day. If it were possible to interview fishermen at the conclusion of their fishing day, intake estimates could be potentially higher. An additional factor potentially affecting intake rates is that fishing quarantines were imposed in early spring due to heavy sewage overflow (Puffer et al., 1981 ) . .. Pierce et al. (1981) -Commencement Bay Seafood Consumption Study-Pierce et al. (1981) performed a local creel survey to examine seafood consumption patterns and demographics of sport fishermen in Commencement Bay, Washington. The objectives of this survey included determining (1) seafood consumption habits and demographics of non-commercial anglers catching seafood; (2) the extent to which resident fish were used as food; and (3) the method of preparation of the fish to be consumed. Salmon were excluded from the survey since it was believed that they had little potential for contamination. The first half of this survey was conducted from early July to September, 1980 and the second half from mid-September through most of November . . During the summer months, interviewers visited each of 4 sub-areas of Commencement Bay on five mornings and five evef!ings; in the fall the areas were sampled 4 complete survey days. Interviews were conducted only with persons who had caught fish. The anglers were interviewed only once during the survey period. Data were recorded for Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish species, wet weight, size of the living group (family, place of residence, fishing frequency, planned uses of the fish, age, sex, and race (Pierce et al., 1981 ). The analysis of Pierce et al. (1981) did not employ explicit sampling weights (i.e., all weights were set to 1 ). There were 304 interviews in the summer and 204 in the fall. About 60 percent of anglers were white, 20 percent black, 19 percent Oriental and the rest Hispanic or Native American. Table 10-58 gives the. distribution of fishing frequency calculated by Pierce et al. (1981 ); for both the summer and fall, more than half of the fishermen caught and consumed fish weekly. Ttie dominant (by weight) species caught were Pacific Hake and Walleye Pollock. Pierce et al. (1981) did not present a distribution of fish intake or a mean fish intake rate.
The U.S. EPA (1989a) used the Pierce et al. (1981) fishing frequency distribution and an estimate of the average amount of fish consumed per angling trip to create an . . approximate intake distribution for the Pierce et al. (1981) survey. The estimate of the amount of fish consumed per angling trip (380 g/person-trip) was based on data on mean fish catchweightand mean number of consumers reported in Pierce et. al. (1981) and on an edible fraction of 0.5. U.S. EPA (1989a) reported a median intake rate of 23. g/day. Price et al. (1994) obtained the raw data from this survey and performed a re-analysis using sampling weights proportional to inverse fishing frequency. The rationale for these weights is explained in Section 10.1 and in the discussion above of the Puffer et al. ( 1981) study. In the re-analysis, Price et al. ( 1994) found a median intake rate of 1.0 g/day and a 90th percentile rate of 13 g/day. The distribution of fishing frequency generated by Price et al. (1994) is shown in.Table 10-59. Note that when equal weights were used, Price et al. (1994) found a median rate of 19 g/day, which was close to the approximate . U.S. EPA (1989a) value reported above of 23 g/day. The same limitations apply to interpreting the results presented here to those presented above in the discussion of Puffer et al. (1981 ). The median intake rate found by Price et al. (1994) (using inverse frequency weights) is more reflective of median intake in the target population than is the value of 19 g/day (or 23 g/day); the latter value reflects more the 50th percentile of the resource utilization distribution, (i.e., that anglers with intakes above 19 g/day consume 50 percent of the recreational fish catch). Similarly, the fishing frequency distribution generated by Price et al. ( 1994) is more reflective of the fishing frequency distribution in the target population than is the distribution presented in Pierce et al. (1981 ). Note the target population. is those anglers who fished at Commencement Bay during the time period of the survey. As with the Puffer et al. (1981) data, these values (1.0 g/day and 19 g/day) are both probably underestimates since the sampling probabilities are less than proportional to fishing frequency; thus, the true target population median is probably somewhat above 1.0 Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish g/day and the true 50th percentile of the resource utilization distribution is probably somewhat higher than 19 g/day. The data from this survey provide an indication of consumption patterns for the time period around 1980 in the Commencement Bay area. However, the data may not reflect current consumption patterns because fishing advisories were instituted due to local contamination. U.S. DHHS (1995) -Health Study to Assess the Human Health Effects of Mercury Exposure to Fish Consumed from the Everglades -A health study was conducted in two phases in the Everglades, Florida for the U.S. Department of Health and Human Services (U.S. DHHS, 1995). The objectives of the first phase were to: (a) describe the human populations at risk for mercury exposure through their consumption of fish and other contaminated animals from* the Everglades and (b) evaluate the extent of mercury exposure in those persons consuming contaminated food and their compliance with the voluntary health advisory. The second phase of the study involved neurologic testing of all study participants who had total mercury levels in hair greater than 7.5 µgig. Study participants were identified by using special targeted screenings, mailings to residents, postings and multi-media advertisements of the study throughout the Everglades region, and direct discussions with people fishing along the canals and waterways in the contaminated areas. The contaminated areas Were identified by the interviewers and term Everglade residents. Of a total of 1,794 individuals sampled, 405 individuals were eligible to participate in the study because they had consumed fish or wildlife from the Everglades at least once per month in the last 3 months of the study period. The majority of the eligible participants (> 93 percent) were either sut;>sistence fishermen, Everglade residents, or both. Of the total eligible participants, 55 individuals refused to participate in the survey. Useable data were obtained from 330 respondents ranging in age from 10-81 years of age (mean age 39 years+/- 18.8) (U.S. DHHS, 1995). Respondents were administered a three page questionnaire from which demographic information, fishing and eating habits, and other variables were obtained (U.S. DHHS, '1995). Tabie 10-60 shows the ranges, means, and standard deviations of selected characteristics by subgroups _of the survey population. Sixty-two percent of the respondents were male with a slight preponderance of black individuals ( 43 percent white, 46 percent black non-Hispanic, and 11 percent Hispanic) (Table 10-60). Most of the respondents reported earning an annual income of $15,000 or less per family before taxes (U.S. DHHS, 1995) .. The mean number of years fished along the canals by the respondents was 15.8 years with a standard deviation of 15.8. The mean number of times per week fish consumers reported eating fish over the last 6 months and last month of the . . survey period was 1.8 and 1.5 per week with a standard deviation of 2.5 and 1.4, respectively (Table 10-60). Table 10-60 also indicates that 71 percent of the respondents reported knowing about the mercury health advisories. Of those who were aware, 26 percent reported that they had lowered their consumption of fish caught in the. Everglades Exposure Factors Handbook August 1997 \._

Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish while the rest (74 percent) reported no change in consumption patterns (U.S. DHHS, 1995). A limitation of this study is that fish intake rates (g/day) were not reported. Another limitation is that the survey was site limited, and, therefore, not representative of the U.S. population. An advantage of this study is that it is one of the few studies targeting subsistence fishermen.

10.6. KEY FRESHWATER RECREATIONAL STUDIES West et al. (1989) -Michigan Sport Anglers Fish Consumption Survey, 1989 -surveyed a stratified random sample of Michigan residents with fishing licences. The sample was divided into 18 cohorts, with one cohort receiving a mail questionnaire each week between January and May 1989. The survey included both a short term recall component recording respondents' fish intake over a seven day period and a usual frequency component. For the short-term component, respondents were asked to identify all household members and list all fish meals consumed by each household member during the past seven days. The source of the fish for each meal was requested caught, gift, market, or restaurant). Respondents were asked to categorize serving size by comparison with pictures of 8 oz. fish portions; serving sizes could be designated as either "about the same size", "less", or "more" than the 8 oz. picture. Data on fish species, locations of self-caught fish and methods of .preparation and cooking were also obtained. The usual frequency component of the survey asked about the frequency of fish meals during each of the four seasons and requested respondents to give the overall percentage of household fish meals that come from recreational sources. A sample of 2,600 individuals were selected from state records to receive survey questionnaires. A total of 2,334 survey questionnaires were deliverable and 1, 104 were completed and returned, giving a response rate of 47.3 percent among individuals receiving questionnaires. In the analysis of the survey data by West et. al. (1989), the authors did not attempt to generate the distribution of recreationally caught fish intake in the survey population. EPA obtained the raw data of this survey for the purpose of generating fish intake distributions and other specialized analyses. As described elsewhere in this handbook, percentiles of the distribution of average daily intake reflective of long-term consumption patterns can not in general be estimated using short-term (e.g., one week) data. Such data can be used to estimate mean average daily intake rates (reflective of short or long term consumption); in addition, short term data can serve to validate estimates of usual intake based on longer recall. Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish EPA first analyzed the short term data with the intent of estimating mean fish intake rates. In order to compare these results with those based on usual intake, only respondents with information on both short term and usual intake were included in this analysis. For the analysis of the short term data, EPA modified the serving size weights used by West et al. (1989), which were 5, 8 and 10 oz., respectively, for portions that were less, about the same, and more than the 8 oz. picture. EPA examined the percentiles of
the distribution of fish meal sizes reported in Pao et al. ( 1982) derived from the 1977-1978. USDA National Food Consumption Survey and observed that a lognormal distribution provided a good visual fit to the percentile data. Using this lognormal distribution, the mean values for serving sizes greater than 8 oz. and for serving sizes at least 10 percent greater than 8 oz. were determined. In both cases a serving size of 12 oz. was consistent with the Pao et al. (1982) distribution. The weights used in the EPA analysis then were 5, 8, and 12 oz. for fish meals described as less, about the same, and more than the 8 oz: picture, respectively. It should be noted that the mean serving size from Pao et al. (1982) was about 5 oz., well below the value of 8 oz. most commonly reported by respondents in the West et al. (1989) survey. Table 10-61 displays the mean number of total and recreational fish meals for each household member based on the seven day recall data. Also shown are mean fish intake rates derived by applying the weights described above to each fish meal. Intake was calculated on both a grams/day and grams/kg body weight/day basis. This analysis was restricted to individuals who eat fish and who reside in households reporting some recreational fish consumption during the previous year. About 75 percent of survey respondents (i.e., licensed anglers) and about 84 percent of respondents who fished in the prior year reported some household recreational fish consumption. The EPA analysis next attempted to use the short term data to validate the usual intake data. West et al. (1989) asked the main respondent in each household to provide estimates of their usual frequency of fishing and eating fish, by season, during the previous year. The survey provides a series of frequency categories for each season and the respondent was asked to check the appropriate range. The ranges used for all
questions were: almost daily, 2-4 times a week, once a week, 2-3 times a month, once a month, less often, none, and don't know. For quantitative analysis of the data it is necessary to convert this categorical information into numerical frequency values .. As some of the ranges are relatively broad, the choice of conversion values can have some effect on intake estimates. In order to obtain optimal values, the usual fish eating frequency reported by respondents for the season during which the questionnaire was completed was compared to the number of fish meals reportedly consumed by respondents over the. seven day short-term recall period. The results of these comparisons are displayed in Table 10-62; it shows that, on average, there is general agreement between estimates made using one year recall and estimates based on seven day recall. The average number of meals (1.96/week) was at the bottom of the range for Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish the most frequent consumption group with data (2-4 meals/week). In contrast, for the lower usual frequency categories, the average number of meals was at the top, or exceeded the top of category range. This suggests some tendency for relatively infrequent fish eaters to. underestimate their usual frequency of fish consumption. The last column of the table shows the estimated fish eating frequency per Week that was selected for use in making quantitative estimates of usual fish intake. These values were guided by the values in the second column, except that frequency values that were inconsistent with the ranges provided to respondents in the survey were avoided. Using the four seasonal fish eating frequencies provided by respondents and the above conversions for reported intake frequency, EPA estimated the average number of fish meals per week for each respondent. This .estimate, as well as the analysis above, pertain to the total number of fish meals eaten (in Michigan) regardless of the source of the fish. Respondents were not asked to provide a seasonal breakdown for eating . frequency of recreationally caught fish; rather, they provided an overall estimate for the past year of the percent of fish they ate that was obtained from different sources. EPA estimated the annual frequency of recreationally caught fish meals by multiplying the estimated total number of fish meals by the reported percent of fish meals obtained from recreational sources; recreational sources were defi_ned as either. self caught or a gift from family or friends. The usual intake component of the survey did not include questions about the usual portion size for fish meals. In order to estimate usual fish intake, a portion size of 8 oz. was applied (the majority of respondents reported this meal size in the 7 day recall data). Individual body weight data were used to estimate intake on a g/kg-day basis. The fish intake distribution estimated by EPA is displayed in Table 10-63. The distribution shown in Table 10-63 is based on respondents who consumed recreational caught fish. As mentioned above, these represent 75 percent of all respondents and 84 percent of respondents who reported having fished in the prior year. Among this latter population, the mean recreational fish intake rate is 14.4*0.84=12.1 g/day; the value of 38.7 g/day (95th percentile among consuriiers) corresponds to the 95.8th percentile of the fish intake distribution in this (fishing) population. The advantages of this data set and analysis are that the survey was relatively large and contained both short-term and usual intake data. The presence of short term data allowed validation of the usual intake data which was based on long term recall; thus, some of the problems associated with surveys relying on long term recall are mitigated here. The response rate of this.survey, 47 percent, was relatively low. In addition, the usual fish intake distribution generated here employed a constant fish meal size, 8 oz .. Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellf1sh Although use of this value as an average meal size was validated by the short-term recall results, the use of a constant meal size, even if correct on average, may seriously reduce the variation in the estimated fish intake distribution. This study was conducted in the winter and spring months of 1988. This period does not include the summer months when peak fishing activity can be anticipated, leading to the possibility that intake results based on the 7 day recall data may understate individuals' usual (annual average) fish consumption. A second survey by West et al. (1993) gathered diary data on fish intake for respondents spaced over a full year. However, this later survey did not include questions about usual fish intake and has not been reanalyzed here. The mean recreational fish intake rates derived from the short term and usual components were quite similar, however, 14.0 versus 14.4 g/day. Chemrisk (1992) -Consumption of Freshwater Fish by Maine Anglers -Chemrisk conducted a study to characterize the rates of freshwater fish consumption among Maine residents (Chemrisk, 1992; Ebert et al., 1993). Since the only dietary source of local freshwater fish is recreational fish, the anglers in Maine were chosen as the survey . population. The survey was designed to gather information on the consumption of fish caught by anglers from flowing (rivers and streams) and standing (lakes and ponds) water bodies. Respondents were asked to recall the frequency of fishing trips during the 1989-. . 1990 ice-fishing season and the 1990 open water season, the number of fish species caught during both seasons, and estimate the number' of fish consumed from 15 fish species. The respondents were also asked to describe the number, species, and average length of each sport-caught fish consumed that had been gifts from other members of their households or other household. The weight of fish consumed by anglers was calculated by first multiplying the estimated weight of the fish by the edible fraction, and then dividing this product by the number of intended consumers. Species specific regression equations were utilized to estimate weight from the reported fish length. The edible fractions used were 0.4 for salmon, 0-?8 for Atlantic smelt, and 0.3 for all other species (Ebert et al., 1993). . A total of 2,500 prospective survey participants were randomly selected from a list of anglers licensed in Maine. The surveys were mailed in during Odober, 1990. Since this was before the end of the open fishing season, respondents were also asked to predict how many more open water fishing trips they would undertake in 1990. Chemrisk (1992) and Ebert et al. (1993) calculated distributions of freshwater fish intake for two populations, "all anglers" and "consuming anglers". All anglers were defined as licensed anglers who fished during either the 1989-1990 ice-fishing season or the 1990 open-water season (consumers and non-consumers) and licensed anglers who did not fish but consumed freshwater fish caught in Maine durin_g these seasons. "C<?nsuming anglers" were defined as those anglers who consumed freshwater fish Exposure Factors Handbook August 1997 Volume II-Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish obtained from Maine sources during the 1989-1990 ice fishing or 1990 open water fishing season. In addition, the distribution of fish intake from rivers and streams was also calculated for two populations, those fishing on rivers and streams ("river anglers") and those consuming fish from rivers and streams ("consuming river anglers"). A total of 1,612 surveys were returned, giving a response rate of 64 percent; 1,369 (85 percent) of the 1,612 respondents were included in the "all angler" population and 1,053 (65 percent) were included in the "consuming angler" population. Freshwater fish intake distributions for these populations are presented in Table 10-64. The mean and 95th percentile was 5.0 g/day and 21.0 g/day, respectively, for" all anglers," and 6.4 g/day and 26.0 g/day, respectively, for "consuming anglers.'; Table 10-64 also presents intake distributions for fish caught from rivers and streams. Among "river anglers" the mean and 95th percentiles were 1.9 g/day and 6.2 g/day, respectively, while among "consuming river anglers" the mean was 3.7 g/day and the 95th percentile was 12.0 g/day. Table 10-65 presents fish intake distributions by ethnic group for consuming anglers. The highest mean intake rates reported are for Native Americans (10 g/day) and French Canadians (7.4 g/day). Because there was a low number of respondents for Hispanics, Asian/Pacific Islanders, and African Americans, intake rates within these subgroups were not calculated (Chemrisk, 1992). The consumption, by species, of freshwater fish caught is presented in Table 10-66. The largest specie consumption was salmon from ice fishing (-292,000 grams); white perch (380,000 grams) for lakes and ponds; and Brooktrout (420,000 grams) for rivers and streams (Chem risk, 1991 ). EPA obtained the raw data tapes from the marine anglers survey and performed some specialized analyses. One analysis involved examining the percentiles of the* "resource .utilization distribution" (this distribution was defined in Section 10.1 ). The 50th, or more generally the pth percentile of the resource utilization distribution, is defined as the consumption level such that p percent of the resource is consumed by individuals with consumptions below this level and 100-p percent by individuals with consumptions above this level. EPA found that 90 percent of recreational fish consumption was by individuals with intake rates above 3.1 g/day and 50 percent was by individuals with intakes above 20 g/day. Those above 3.1 g/day make up about 30 percent of the "all angler" population and those above 20 g/day make up about 5 percent of this population; thus, the top 5 percent . of the angler population consumed 50 percent of the recreational fish catch. EPA also performed an analysis of fish consumption among anglers and their families. This analysis was possible because the survey included questions on the number, sex, and age of each individual in the household and whether the individual consumed recreationally caught fish. The total population of licensed anglers in this survey and their household members was 4,872; the average household size for the 1,612 Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish anglers in the survey was thus 3.0-persons. Fifty-six percent of the population was male and 30 percent was 18 or under .. A total of 55 percent of this population was reported to consume freshwater recreationally caught fish in the year of the survey. The sex a.nd ethnic distribution of the consumers was similar to that of the overall population. The distribution of fish intake among the overall household population, or among consumers in the household, can be calculated under the assumption that recreationally caught fish was shared equally among all .members of the household reporting consumption of such fish (note this assumption was used above to calculate intake rates for anglers). With this assumption, the mean intake rate among consumers was 5.9 g/day with a median of 1.8 g/day and a 95th percentile of 23.t g/day; for the overall population the mean was 3.2 g/day and the 95th percentile was 14.1 g/day. The results of this survey can be put into the context of the overall Maine population. The 1,612 anglers surveyed represent about 0. 7 percent of the estimated 225,000 licensed anglers in Maine. It is reasonable to assume that licensed anglers and their families will have the highest exposure to recreationally caught freshwater fish. Thus, to estimate the number of persons in Maine with recreationally caught freshwater fish intake above, for instance, 6.5 g/day (the 80th percentile among household consumers in this survey), one can assume ,that virtually all persons came from the population of licensed anglers and their families. The number of persons above 6.5 g/day in the household survey population is calculated by taking 20 percent (i.e., 100 percent -80 percent) of the consuming* population in the survey; this number then is 0.2*(0.55*4872)=536. Dividing this number by the sampling fraction of 0.007 (0. 7 percent) gives about 77 ,000 persons above 6.5 g/day of recreational freshwater fish consumption statewide. The 1990 census showed the population of Maine to be 1.2 million people; thus the 77,000 persons above 6.5 g/day represent about 6 percent of the state's population. Chemrisk (1992) reported that the fish consumption estimates obtained from the survey were conservative because of assumptions made in the analysis. The assumptions included: a 40 percent estimate as the edible portion of landlocked and Atlantic salmon; inclusion of the intended number of future fishing trips and an assumption that the average success and consumption rates for the individual angler during the trips already taken would continue through future trips. The data collected for this study were on recall and self-reporting which may have resulted in a biased estimate. The social desirability of the sport and frequency of fishing are also bias contributing factors; successful anglers are among the highest consumers of freshwater fish (Chemrisk, 1992). Over reporting appears to be correlated with skill level and the importance of the activity to the individual; it is likely that the higher consumption rates may be substantially overstated (Chemrisk, 1992). Additionally, fish advisories are in place in these areas and may affect the rate of fish consumption among anglers. The survey results showed that in 1990, 23 percent of Factors Handbook August 1997

.Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellflsh all anglers consumed no freshwater fish, and 55 percent of the river anglers ate no freshwater fish. An advantage of this study is that it presents area-specific consumption patterns and the sample size is rather large. West et al. (1993) -Michigan Sport Anglers Fish Consumption Study, 7997-7992-This survey, financed by the Michigan Great Lakes Protection Fund, was a follow-up to the earlier 1989 Michigan survey described previously. The major purpose of 1991-1992 survey was to provide short-term recall data of recreational fish consumption over a full year period; the 1989 survey, in contrast, was conducted over only a half'year period (West et al., 1993). This survey was similar in design to the 1989 Michigan survey. A sample of 7,000 persons with Michigan fishing licenses was drawn and surveys were mailed in 2-week cohorts over period January, 1991 to January, 1992. Respondents were asked to report detailed fish consumption patterns during the preceding seven days, as well as demographic information; they were also asked if they currently eat fish. Enclosed with the survey were pictures of about a half pound of fish. Respondents were asked to indicate whether reported consumption at each meal was more, less or about the same as the picture. Based on responses to this question, respondents were assumed to have consumed 10, 5 or 8 ounces of fish, respectively. A total of 2,68.1 surveys were returned. West et al. (1993) calculated a response rate for the survey of 46.8 percent; this was derived by removing from the sample those respondents who could not be located or who did not reside in Michigan for at least six months. Of these 2,681 respondents, 2,475 (93 percent) reported that they currently eat fish; all subsequent analyses were restricted to the current fish eaters. The mean fish consumption rates were found to be 16. 7 g/day for sport fish and 26.5 g/day for total fish (West et al., 1993). Table 10-67 shows mean sport-fish consumption rates by demographic categories. Rates were higher among minorities, people with low income, and people residing in smaller communities. Consumption rates in g/day were also higher in males than .in females; however, this difference would likely disappear if rates were computed on a g/kg-day basis. West et al. (1993) estimated the 80th percentile of the s.urvey fish consumption distribution. More extensive percentile calculations were performed by U.S. EPA (1995) .using the raw data from the West et al. (1993) survey and calculated 50th, 90th, and 95th percentiles. However, since this survey only measured fish consumption over a short (one week) interval, the resulting distribution will not be indicative of the long-term fish consumption distribution and the upper percentiles reported from the EPA analysis will likely considerably overestimate the corresponding long term percentiles. The overall 95th Exposure Factors Handbook August 1997 . Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish percentile calculated by U.S. EPA (1995) was 77.9; this is about double the 95th percentile estimated using year long consumption data from the 1989 Michigan survey. The limitations of this survey are the relatively low response rate and the fact that only three categories were used to assign fish portion size. The main study strengths were . its relatively large size and its reliance on short-term recall. Connelly et al. (1996) -Sportfish Consumption Patterns of Lake Ontario Anglers and the Relationship to Health Advisories, 7 992 -The objectives of this study were to provide accurate estimates of fish consumption (overall and sport caught) among Lake Ontario anglers and to evaluate the effect of Lake Ontario health advisory recommendations (Connelly et al., 1996). To target Lake Ontario anglers, a sample of 2,500 names.was randomly drawn from 1990-1991 New York fishing license records for licenses purchased in six counties bordering Lake Ontario. Participation in the study was solicited by mail with potential participants encouraged to enroll in the study even if they fished infrequently or consumed little or no sport caught fish. The survey design involved three survey techniques including a mail questionnaire asking for 12 month recall of 1991 fishing trips

and fish consumption, self-recording information in a diary for 1992 fishing trips and fish consumption, periodic telephone interviews to gather information recorded in the diary and a final telephone interview to determine awareness of health advisories (Connelly et al., 1996). Participants were instructed to record in the diary the species of fish eaten, meal size, method by which fish was acquired (sport-caught or other), fish preparation and cooking techniques used and -the number of household members eating the meal. Fish meals were defined as finfish only. *Meal size was estimated by participants by comparing their meal size to pictures of 8 oz. fish steaks and fillets on dinner plates. An 8 oz. size was assumed unless participants noted their meal size was smaller than 8 oz., in which case a_4 oz. size . was assumed, or they noted it was larger than 8 oz., in which case a 12 oz. size was assumed. Participants were also asked to record information on fishi11g trips to Lake Ontario ahd species and length of any fish caught. From the initial sample of 2,500 license buyers, 1,993 (80 percent) were reachable by phone or mail and 1,410 of these were eligible for the study, in that they intended to fish Lake Ontario in 1992. A total of 1,202 of these 1,410, or 85 percent, agreed to participate in the study. Of the 1,202 participants, 853 either returned the diary or provided diary information by telephone. Due to changes in health advisories for Lake Ontario which resulted in less Lake Ontario frshing in 1992, only 43 percent, or 366 of these 853 persons indicated that they fished Lake Ontario* during 1992. The study analyses summarized below concerning fish consumption and Lake Ontario. fishing participation are based on these 366 persons. Exposure Factors Handbook August 1997 r Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish Anglers who fished Lake Ontario reported an average of 30.3 (S.E. = 2.3) fish meals per person. from all sources in 1992; of these meals 28 percent were sport caught (Connelly et al., 1996). Less than 1 percent ate no fish for the year and 16 percent ate no sport caught fish. The mean fish intake rate from all sources was 17 .9 g/day and from sport caught sources was 4.9 g/day. Table 10-68 gives the distribution of fish intake rates from all sources and from sport caught fish. The median. rates were 14.1 *g/day for all sources and 2.2 g/day for sport caught; the 95th percentiles were 42.3 g/day and 17 .9 g/day for all sources and sport caught, respectively. As seen in Table 10-69, statistically significant differences in intake rates were seen across age and residence groups, with residents of large cities and younger people. having fower intake rates on average. The main advantage of this study is the diary format. This format provides more accurate information on fishing participation ahd fish consumption, than studies based on 1 year recall (Ebert et al., 1993). However, a considerable portion of diary respondents participated in the study for only a portion of the year and some errors may have been generated in extrapolating these respondents' results to the entire year (Connelly et al., 1996). In addition, the response rate for this study was relatively low, 853of1,410 eligible respondents, or 60 percent, which may have engendered some non-response bias. The presence of health advisories should be taken into account when evaluating the intake rates observed in this study. Nearly all respondents (>95 percent) were aware of the Lake Ontario health advisory. This advisory counseled to eat none.of 9 fish *species from Lake Ontario and to eat no more than one meal per month of another 4 species. In addition, New York State issues a general advisory to eat no more than 52 sport caught fish meals per year. Among participants who fished Lake Ontario in 1992, 32 percent said they would eat more fish if health advisories did not exist. A significant fraction of respondents did not totally adhere to the fish advisory; however, 36 percent of respondents, and 72 percent of respondents reporting Lake Ontario fish consumption, ate at least *one species of fish over the advisory limit. Interestingly, 90 percent of those violating the advisory reported that they believed they were eating within advisory limits. 10 .. 7. RELEVANT FRESHWATER RECREATIONAL STUDIES Fiore et al. (1989) -Sport Fish Consumption and Body Burden Levels of Chlorinated Hydrocarbons: A Study of Wisconsin Anglers. This survey, reported by Fiore et al. (1989), was conducted to assess sociodemographic factors and sport fishing habits of anglers, to evaluate anglers' comprehension of and compliance with the Wisconsin Fish Consumption Advisory, to measure body levels of PCBs and DOE through analysis of blood serum samples and to examine the relationship between body burden levels and consumption of sport-caught fish. The survey targeted all Wisconsin residents who had purchased fishing or sporting licenses in 1984 in any of 10 pre-selected study counties. These counties were chosen in part based on their proximity to water bodies identified in Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish Wisconsin fish advisories. A total of 1,600 anglers were sent survey questionnaires during the summer of 1985. The survey questionnaire included questions about fishing history, locations fished, species targeted, kilograms caught for consumption, overall fish consumption (including commercially caught) and knowledge of fish advisories. The recall period was one year. A total of 801 surveys were returned (50 percent response rate). Of these, 601 (75 percent) were from males and 200 from females; the mean age was 37 years. Fiore et al. ( 1989) reported that the mean number of fish meals for 1984 for all respondents was 18 for sport-caught meals and 24 for non-sport caught meals. Fiore et al. (1989) assumed that each fish meal consisted of 8 ounces (227 grams) of fish to generate means and percentiles of fish intake. The reported per-capita intake rate of sport-caught fish was 11.2 g/day; among consumers, who comprised 91 percent of all respondents, the mean caught fish intake rate was 12.3 g/day and the 95th percentile was 37.3 g/day. The mean daily fish intake from all sources (both sport caught and commercial) was 26.1 g/day with a 95th percentile of 63.4 g/day. The 95th percentile of 37 .3 g/day of sport caught fish represents 60 fish meals per year; 63.4 g/day (the 95th percentile of total fish intake) represents 102 fish meals per year . . Fiore et al. ( 1989) assumed a (constant) meal size of 8 ounces (227 grams) of fish . which may over-estimate average meal size.. Pao et al. ( 1982), using data from the* 1977-* 78 USDA NFCS, reported an average fish meal size of slightly less than 150 grams for adult males. EPA obtained the raw data from this study and calculated the distribution of the number of sport-caught fish meals and the,distribution of fish intake rates (using 150 grams/meal); these distributions are presented in Table 10-70. With this average meal size, the per-capita estimate is 7.4 g/day. This study is limited in its ability to accurately estimate intake rates because of the absence of data on weight of fish consumed. Another limitation of this study is that the results are based on one year recall, which may tend to over-estimate the number of fishing trips (Ebert et al., 1993). In addition, the response rate was rather low (50 percent). Connelly et al. (1992) -Effects of Health Advisory and Advisory Changes on Fishing Habits and Fish Consumption in New York Sport Fisheries -Connelly et al. (1992) conducted a study to assess the awareness and knowledge of New York anglers about fishing advisories and contaminants found in fish and their fishing and fish consuming behaviors. The survey sample consisted of 2,000 anglers with New York State fishing licenses for the year beginning October 1, 1990 through September 30, 1991. A questionnaire was mailed to the survey sample in January, 1992. The questiqnnaire was pesigned to measure catch and consumption of fish, as well as methods of fish preparation and knowledge of and attitudes towards health advisories (Connelly et al., 1992). The Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish survey adjusted response rate was 52.8 perqent (1,030 questionnaires were completed and 51 were not deliverable). The average and median number of fishing days per year were 27 and 15 days . respectively (Connelly et al. 1992). The mean number of sport-caught fish meals was 11. About 25 percent of anglers reported that they did not consume sport-caught fish. Connelly et al. (1992) found that 80 percent of anglers statewide did not eat listed species or ate them within advisory limits and followed the 1 sport-caught fish meal per week recommended maximum. The other 20 percent of anglers exceeded the advisory recommendations in some way; 15 percent ate listed species above the limit and 5 percent ate more than one sport caught meal per week. Connelly et al. (1992) found that respondents eating more than one sport-caught meal per week were just as likely as those eating less than one meal per week to know the recommended level of sport-caught fish consumption, although less than 1/3 in each group knew the level.. An estimated 85 percent of anglers were aware of the health advisory. Over 50 percent of respondents said that they made changes in their fishing or fish . consumption behaviors in response to health advisories. The advisory included a section on methods that can be used to reduce contaminant exposure. Respondents were asked what methods they used for* fish cleaning and cooking. Summary results on preparation and cooking methods are presented in Section 10.9 and in Appendix 1 OB. A limitation of this study with respeCt to estimating fish intake rates is that only the number of sport-caught meals was ascertained, not the weight of fish consumed. The fish meal data can be converted to an intake rate (g/day) by assuming a value for a fish meal such as that from Pao et al. (1982) (about 150 grams as the average amount of fish consumed per eating occasion for adult males -males comprised .88 percent of respondents in the current study). Using 150 grams/meal the mean intake rate among the angler population would be 4.5 g/day; note that about 25 percent of this population reported no sport-caught fish consumption. The major focus of this study was not on consumption, per se, but on the knowledge *of and impact of fish health advisories; Connelly et al. (1992) provides important information on these issues. Hudson River Sloop Clearwater, Inc. (1993} -Hudson River Angler Survey -Hudson River Sloop Clearwater, Inc. (1993) conducted a survey of adherence to fish consumption health advisories among Hudson River anglers. All fishing has been banned on the upper Hudson . River where high levels of PCB contamination are well. documented; while Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish voluntary recreational fish consumption advisories have been issued for areas south of the Troy_ Dam (Hudson River Sloop Clearwater, Inc., 1993). The survey consisted of direct interviews with 336 shore-based anglers between the months of June and November 1991, and April and July 1992. Socio-demographic characteristics of the respondents are presented in Table 10-71. The survey sites were selected based on observations of use by anglers, and legal accessibility. The selected sites included upper, mid-, and lower Hudson River sites located in both rural and urban settings. The interviews were conducted on weekends and weekdays during morning, midday, and evening periods. The anglers were asked specific questions concerning: fishing and fish consumption habits; perceptions of presence of contaminants in fish; perceptions of risks associated with consumption of recreationally caught fish; and
awareness of, attitude toward, and response to fish consumption advisories or fishing bans. Approximately 92 percent of the survey respondents were male. ihe following statistics were provided by Hudson River Sloop Clearwater, Inc. (1993). The most common reason given for fishing was for recreation or enjoyment. Over 58 percE;lnt of those surveyed indicated that they eat their catch. Of those anglers who eat their catch, 48 percent reported being aware of advisories. Approximately 24 percent of those who said they currently do not eat their catch, have done so in the past. Anglers were more likely to eat their .catch from the lower Hudson areas where health advisories, rather than fishing bans, have been issued. Approximately 94 percent of Hispanic Americans were likely to eat their catch, while *77 percent of African Americans and 47 percent of Caucasian Americans intended to eat their catch. Of those who eat their catch, 87 percent were likely to share their meal with others (including women of childbearing age, and children under the age of fifteen). For subsistence anglers, more low-income than upper income anglers eat their catch (Hudson River Sloop Clearwater, Inc., 1993). Approximately 10 percent of the respondents stated that food was their primary reason for fishing; this group is more likely to be in the lowest per capita income group (Hudson River Sloop Clearwater, Inc., 1993). The average frequency of fish consumption reported was just under one (0.9) meal over the previous week, and three meals over the previous month. Approximately 35 percent of all anglers who eat their catch exceeded the amounts recommended by the New York State health advisories. Less than half (48 percent) of all the anglers intervi_ewed were aware of the State health advisories or fishing bans. Only 42 percent of those anglers aware of the advisories have changed their fishing habits as a result.
The advantages of this study include: in-person interviews with 95 percent of all anglers approached; field-tested questions designed to minimize interviewer bias; and Exposure Factors Handbook August 1997. -,

Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellflsh candid responses concerning consumption of fish from contaminated waters. The limitations of this study are that specific intake amounts are not indicated, and that only shore-based anglers were interviewed. 10.8. NATIVE AMERICAN FRESHWATER STUDIES Wolfe and Walker (1987) -Subsistence Economies in Alaska: Productivity, Geography, and Development Impacts -Wolfe and Walker (1987) analyzed a dataset from 98 communities for harvests of fish, land mammals, marine mammals, and other wild resources. The analysis was performed to evaluate the distribution and productivity of subsistence harvests in Alaska during the 1980s. Harvest levels were used as a measure of productivity. Wolfe and Walker (1987) defined harvest to represent a single year's production from a complete seasonal round. The harvest levels were derived primarily from a compilation of data from subsistence studies conducted between 1980 to 1985 by various researchers in the Alaska Department of Fish and Game, Division of Subsistence. Of the 98 communities studied, four were large urban population centers and 94 were small communities. The harvests for these latter 94 communities were documented through detailed retrospective interviews with harvesters from a sample of households (Wolfe and Walker, 1987). Harvesters were asked to estimate the quantities of a particular species that were harvested and used by members of that household during the previous 12-month period. Wolfe and Walker (1987) converted harvests to a common unit for comparison, pounds dressed weight per capita per year, by multiplying the harvests of households within each community by standard factors converting total pounds to dressed weight, summing across households, and then. dividing by the total number of household members in the household sample. Dressed weight varied by species and community but in general was 70 to 75 percent of total fish weight; dressed weight for fish represents that portion brought into the kitchen for use (Wolfe and Walker,* 1987). Harvests for the four urban populations were developed from a statewide data set gathered by the Alaska Department of Fish and Game Divisions of Game and Sports Fish. Urban sport fish harvest estimates were derived from a survey that was mailed to a randomly selected statewide sample of anglers (Wolfe and Walker, 1987). Sport fish harvests were disaggregated by urban residency and the dataset was analyzed by converting the harvests into pounds and dividing by the 1983 urban population. For the overall analysis, each of the 98 communities was treated as a single unit of analysis and the entire group of communities was assumed to be a sample of all communities in Alaska (Wolfe and Walker, 1987). Each community was given equal weight, regardless of population size. Annual per capha harvests were calculated for each community. For the four urban fish harvests ranged from 5 to 21 pounds per capita per year (6.2 g/day to 26.2 g/day). Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellflsh The range for the 94 small communities was 25 to 1,239 pounds per capita per year (31 g/day to 1,541 g/day). For these 94 communities, the median per capita fish harvest was 130 pounds per year (162 g/day). In most (68 percent) of the 98 communities analyzed, resource harvests for fish were greater than the harvests of the other wildlife categories (land mammal, marine mammal, and other) combined.

The communities in this study were not made up entirely of Alaska Natives. For roughly half the communities, Alaska Natives comprised 80 percent or more of the population, but for about 40 percent of the communities they comprised less than 50 percent of the population. Wolfe and Walker ( 1987) performed a regression analysis which showed that the per capita harvest of a community tended to increase as a function of the percentage of Alaska Natives in the community. Although this analysis was done for total harvest (i.e., fish, land mammal, marine mammal and others) the same result should hold for fish harvest since fish harvest is highly correlated with total harvest. A limitation of this report is that it presents (per-capita) harvest rates as opposed to individual intake rates. Wolfe and Walker (1987) compared the per capita harvest rates reported to the results for the household component of the 1977-1978 USDA National Food Consumption Survey (NFCS). The NFCS showed that about 222 pounds of meat, fish, and poultry were purchased and brought into the household kitchen for each peq:mn each year in the western region of the United States. This contrasts with a median total resource harvest of 260 lbs/yr in the 94 communities studied. This comparison, and the fact that Wolfe and Walker (1987) state that "harvests represent that portion brought into the kitchen for use," suggest that the same factors used to convert household consumption rates in the NFCS to individual intake rates can be used to convert per capita harvest rates to individual intake rates. In Section 10.3, a factor of 0.5 was used to convert fish consumption from household to individual intake rates. Applying this factor, the median per capita individual fish intake in the 94 communities would be 81 g/day and the range 15.5 to 770 g/day. A limitation of this study is that the data were based on. 1. -year recall from a mailed survey. An advantage of the study is that it is one of the few studies that present fish harvest patterns for subsistence populations. AIHC {1994) -Exposure Factors Sourcebook -The Exposure Fa.ctors Sourcebook (AIHC, 1994) provides data for non-marine fish intake consistent with this document. However, the total fish intake rate recommended in Al HC ( 1994) is approximately 40 percent lower than that in this document. The fish intake rates presented in this handbook are based on more recent data from USDA CSFll (1989-1991). AIHC (1994) presents probability distributions in grams fish per kilogram of body weight for fish consumption based on data from U.S. EPA Guidance Manual, Assessing Human Health Risks from Chemically Contaminated Fish and Shellfish (U.S. EPA, 1989b). The @Risk formula is Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish provided for direct use in the @Risk simulation software. The @Risk formula was provided for the distributions that were provided for the ingestion of freshwater finfish, saltwater finfish, and fish (unspecified) in the U.S. general population, children ages 1 to 6 years, and males ages 13 years and above. Distributions we're also provided for saltwater finfish ingestion in the general population and for females and for males 13 years of age and older. Distributions for shellfish ingestion were provided for the general population, children ages 1 to 6 years, and for males and females 13 years of age and above. Additionally, distributions for "unspecified" fish ingestion were presented for the above mentioned populations. The Sourcebook has been classified as a relevant rather than key study because it was not the primary source for the data used to make recommendations in this document. The Sourcebook is very similar to this document in the sense that it summarizes exposure factor data and recommends values. Therefore, it can be used as an alternative information source on fish intake. Columbia River Inter-Tribal Fish Commission (CRITFC) {1994) -A Fish Consumption Survey of the Umatilla, Nez Perce, Yakama, and Warm Springs Tribes Df the Columbia River Basin -CRITFC ( 1994) conducted a fish consumption survey among f0ur Columbia River Basin Indian tribes during the fall and winter of 1991-1992. The target population included all adult tribal members who lived on or near the Yakama, Warm Springs, Umatilla or Nez Perce *reservations. The. survey was based on a stratified random sampling design where respondents were selected from patient registration files at the Indian Health Service. Interviews were performed in person at a central location on the member's reservation. Information requested included annual and seasonal numbers of fish meals, average serving size per fish meal, species and part(s) of fish consumed, preparation methods, changes in patterns of consumption over the last 20 years and during ceremonies and festivals, breast feeding practices and 24 hour dietary recall (CRITFC, 1994). Foam sponge food models approximating four, eight, and twelve ounce fish fillets were provided to help respondents estimate average fish meal size. Fish intake rates were calculated by multiplying the annual frequency of fish meals by the average serving size per fish meal. The study was designed to give essentially equal sample sizes for each tribe. However, since-the population sizes of the tribes were highly unequal, it was necessary to weight the data (in proportion to tribal population size) in order that the survey results represent the overall population of the four tribes. Such weights were applied to the analysis of adults; however, because the sample size for children was considered small, only an unweighted analysis was performed for this population (CRITFC, 1994 ). Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish The survey respondents consisted of 513 tribal members, 18 years old and above. Of these, 58 percent were female and 59 percent were under 40 years old. In addition, information for 204 children 5 years old and less was provided by the participating adult respondent. The overall response rate was 69 percent. The results of the survey showed that adults consumed an average of 1.71 fish meals/week and had an average intake of 58.7 grams/day (CRITFC, 1994). Table 10-72 shows the adult fish intake distribution; the median was between 29 and 32 g/day and the 95th percentile about 170 g/day. A small percentage (7 percent) of respondents indicated that they were not fish consumers. Table 10-73 shows that mean intake was slightly higher in males than females (63 g/d versus 56 g/d) and was higher in the over 60 years age group (7 4.4 g/d) than in the 18-39 years (57 .6 g/d) or 40-59 years (55.8 g/d) age groups. Intake also tended to be higher among those living on the reservation. The mean intake for nursing mothers, 59.1 g/d, was similar to the overall mean intake. A total of 49 percent of respondents reported that they caught fish from ttie Columbia River basin and itS tributaries for personal use or for tribal ceremonies and distributions to other tribe members and 88 percent reported that they obtained fish from either harvesting, family or friends, at tribal ceremonies or from tribal distributions. Of all fish consumed, 41 percent came from self or family harvesting, 11 percent from the harvest of friends, 35 percent from tribal ceremonies or distribution, 9 percent from stores and 4 percent from other sources (CRITFC, 1994). The analysis of seasonal intake showed that May and June tended to be high consumption months and December and January low consumption months. The mean adult intake rate for May and June was 108 g/d while the mean intake rate for December and January was 30.7 g/d. , Salmon was the species eaten by the highest number of respondents (92 percent) followed by trout (70 percent), lamprey (54 percent), and smelt (52 percent). Table 10-7 4 gives the fish intake distribution for under 5 years of age. The mean intake rate was 19.6 g/d and the 95th percentile was approximately 70 g/d. The authors noted that some non-response bias may have occurred in the survey since respondents were more likely to live near the reservation and were more likely to be female than non-respondents. In addition, they hypothesized that non fish consumers may have been more likely to be non-respondents than fish consumers since non consumers may have thought their contribution to the survey would be meaningless; if such were the case, this study would overestimate the mean intake rate. It was also noted that the timing of the survey, which was conducted during low fish consumption months, may have led to underestimation of actual fish consumption; the authors conjectured that an individual may report higher annual consumption if interviewed during a relatively high consumption month and lower annual consumption if interviewed during a relatively low consumption month. Finally, with respect to children's intake, it was observed that some of the Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish respondents provided the same information for their children as for themselves, thereby the reliability of some of these data is questioned. Although the authors have noted these limitations, this study does present information on fish consumption patterns and habits for a Native American subpopulation. It should be noted that the number of surveys that address subsistence subpopulations is very limited. Peterson et al. (1994) -Fish Consumption Patterns and Blood Mercury Levels in Wisconsin Chippewa Indians -Peterson et al. (1994) investigated the extent of exposure of methylmercury to Chippewa Indians living on a Northern Wisconsin reservation who consume fish caught in northern Wisconsin lakes. The lakes in northern Wisconsin are known to be contaminated with mercury and the Chippewa have a reputation for high fish consumption (Peterson et al., 1994). The Chippewa Indians fish by the traditional method of spearfishing. Spearfishing (for walleye) occurs for about two weeks each spring after the ice breaks, and although only a small number of tribal members participate in it, the . spearfishing harvest is distributed widely within the tribe by an informal distribution network of family and friends and through traditional tribal feasts (Peterson et al., 1994 ). Potential survey participants, 465 adults, 18 years of age and older, were randomly selected from the tribal registries (Peterson et al., 1994). Participants were asked to complete a questionnaire describing their routine fish consumption and, more extensively, their fish consumption during the two previous months. They were also asked to give a blood sample that would be tested for mercury content. The survey was carried out in May 1990. A follow-up survey was conducted for a random sample of 75 non-respondents (80 percent were reachable), and their demographic and fish consumption patterns were obtained. Peterson et aL (1994) reported that the non-respondents' socioeconomic and . fish consumption were similar to the respondents. A total of 175 of the original random sample (38 percent) participated iri the study. *in addition, 152 nonrandomly selected participants were surveyed and included in the data analysis; these participants were reported by Peterson et al. ( 1994) to have fish consumption rates similar to those of the randomly selected participants. Results from the survey showed that fish consumption varied seasonally, with 50 percent of the respondents reporting April and May (spearfishing *season) as the highest fish consumption months (Peterson et al., 1994). Table 10-75 shows the number of fish meals consumed per week during the last 2 months (recent consumption) the survey was conducted and during the respondents' peak consumption months grouped by gender, age, education, and employment level. During peak consumption *months, males consumed more fish (1.9 meals per week) than females (1.5 meals per week), respondents under 35 years of age consumed more fish (1.8 meals per week) than respondents 35 years of age and over (1.6 meals per week), and the unemployed consumed more fish (1.9 Exposure Factors Handbook August 1997 I .

Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish meals per week) than the employed (1.6 meals per week). During the highest fish consumption season (April and May), 50 percent of respondents reported eating one or less fish meals per week and only 2 percent reported daily fish consumption (Figures 10-1 and 10-2). A total of 72 percent of respondents reported Walleye consumption in the previous two months. Peterson et al. ( 1994) also reported that the mean number of fish meals usually consumed per week by the respondents was 1.2. The mean fish consumption rate reported (1.2 fish meals per week, or 62.4 meals per year) in this survey was compared with the rate reported in a previous survey of Wisconsin anglers (Fiore et al., 1989) of 42 fish meals per year. These results indicate that the Chippewa Indians do not consume much more fish than the general Wisconsin angler population (Peterson et al., 1994 ). The differences in the two values may be attributed to differences in study methodology (Peterson et al., 1994). Note that this number (1.2 fish meals per week) includes fish from all *sources. Peterson et al. (1994) noted that subsistence fishing, defined as fishing as a major food source; appears rare among the Chippewa. Using the recommended rate in this handbook of 129 g/meal as the average weight of fish consumed per fish meal in the general population, the rate reported here of 1.2 fish meals per week translates into a mean fish intake rate of 22 g/day in this population. Fitzgerald et al. (1995) -Fish PCB Concentrations and Consumption Patterns Among Mohawk Women at Akwesasne -Akwesasne is a native American community of ten thousand plus persons located along the St. Lawrence River (Fitzgerald et al., 1995). The local food chain has been contaminated with PCBs and some species have levels that exceed the U.S. FDA tolerance limits for human consumption (Fitzgerald et al., 1995). Fitzgerald et al. ( 1995) conducted a recall study from 1986 to 1992 to determine the fish consumption patterns among nursing Mohawk women residing near three industrial sites. The study sample consisted of 97 Mohawk women and 154 nursing Caucasian controls. The Mohawk mothers were significantly younger (mean age 24.9) than the controls (mean age 26.4) and had significantly more years of education (mean 13.1 for Mohawks versus 12.4 for controls). A total of 97 out of 119 Mohawk nursing women responded, a response rate of 78 percent; 154 out of 287 control nursing Caucasian women responded, a response rate of 54 percent. Potential participants were identified prior to, or shortly after, delivery. The interviews were conducted at home within one month postpartum and were structured to collect information for sociodemographics, vital statistics, use of medications, occupational and residential histories, behavioral patterns (cigarette smoking and alcohol consumption), drinking water source, diet, and fish preparation methods (Fitzgerald et al., 1995). The dietary data collected were based on recall for food intake during the index pregnancy, the year before the pregnancy, and more than .one year before the pregnancy. Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellt1sh The dietary assessment involved the report by each participant on the consumption of various foods with emphasis on local species of fish a*nd game (Fitzgerald et al., 1995). This method combined food frequency and dietary histories to estimate usual intake. Food frequency was evaluated with a checklist of foods for indicating the amount of consumption of a participant per week, month or year. Information gathered for the dietary history included duration of consumption, changes in the diet, and food preparation method. Table 10-76 presents the number of local fish meals per year for both the Mohawk and control participants. The highest percentage of participants reported consuming between 1 and 9 local fish meals per year. Table 10-76 indicates that Mohawk

respondents consumed statistically significantly more local fish than did control respondents during the two time periods prior to pregnancy; for the time period during pregnancy there was no significant difference in fish consumption between the two groups. Table 10-77 presents the mean number of local fish meals consumed per year by time period for all respondents and for those ever consuming (consumers only).* A total of 82 (85 percent) Mohawk mothers and 72 (47 percent) control mothers reported ever consuming local fish. The mean number. of local fish meals consumed per year by Mohawk respondents declined over time, from 23.4 (over one year before pregnancy) to 9.2 (less than one year before pregnancy) to 3.9 (during pregnancy); a similar decline was seen among consuming Mohawks only. There was also a decreasing trend over time in consumption among controls, though it was much less pronounced. Table 10-78 presents the mean number of fish meals consumed per year for all participants by time period and selected characteristics (age, education, cigarette smoking, and alcohol consumption). Pairwise contrasts indicated that control participants over 34 years of age had the highest fish consumption of local fish meals (22.1) (Table 10-78). However, neither the overall nor pairwise differences by age among the Mohawk women over 34 years old were statistically significant, and may be dueto the small sample size (N=6) (Fitzgerald et al., 1995). The most common fish consumed by Mohawk mothers was yellow perch; for controls the most common fish consumed was .trout. An advantage of this study is that it presents data for fish consumption patterns for Native Americans as compared to a demographically similar group of Caucasians. Although the data are based on nursing mothers as participants, the study also captures consumption patterns prior to pregnancy (up to 1 year before and more than 1 year before). Fitzgerald et al. (1995) noted that dietary recall for a period more than one year before pregnancy may be inaccurate, but these data were the best available measure of the more distant past. They also noted that the decrease in fish consumption among Mohawks from the period one year before pregnancy to the period of pregnancy is due to a secular trend of declining fish consumption over time in Mohawks. This decrease, which was more pronounced than that seen in controls, may be due to health advisories promulgated by tribal, as well as state, officials. The authors note that this Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellflsh decreasing secular trend in Mohawks is consistent with a survey from 1979-1980 that found an overall mean of 40 fish meals per year among male and female Mohawk adults .. The data are presented as number of fish meals per year; the authors did not assign an average weight to fish meals. If assessors wanted to estimate the weight of fish consumed, some average value of weight per fish meal would have to be assumed. et al. (1982) reported 104 grams .as the average weight of fish consumed per eating occasion for females 19-34 years old. 10.9. OTHER FACTORS Other factors to consider when using the available survey data include location, climate, season, and ethnicity of the angler or consumer population, as well as the parts* of fish consumed and the methods of preparation. Some contaminants (for example, some dioxin compounds) have the affinity to accumulate more in certain tissues, such as the fatty tissue, as well as in certain internal organs. The effects of cooking methods for various food products on the levels of dioxin-like compounds have been addressed by evaluating a number of studies in U.S. EPA (1996b). These studies showed various results for contamination losses based on the methodology of the study and the method of food preparation. The reader is referred to U.S. EPA ( 1996b) for a detailed review of these studies. In addition, some studies suggest that there is a significant decrease of * . contaminants in cooked fish when compared with raw fish (San Diego County, 1990). Several studies cited in this section have addressed fish preparation methods and parts of fish consumed. Table 10-79 provides summary results from these studies on fish preparation methods; further details on preparation methods, as well as results from some
studies on parts of fish consumed, are presented in Appendix 1 OB. The moisture content (percent) and total fat content (percent) measured and/or calculated in various fish forms (i.e., raw, cooked, smoked, etc.) for selected fish species are presented in Table 10-80, based on data from USDA (1979-1984). The total percent .fat content is based on the sum of saturated, monounsaturated, and polyunsaturated fat. The moisture content is based on the percent of water present. In some cases, the residue levels of contaminants in fish are reported as the concentration of contaminant per gram of fat. These contaminants are lipophilic compounds. When using residue levels, the assessor should ensure consistency in the exposure assessment calculations by using consumption rates that are based on the amount of fat consumed for the fish species of interest. Alternately, residue levels for the Exposure Factors Handbook
August1997 Volume II -Food Ingestion Factors Chapter. 10 Intake of Fish and Shellfish "as consumed" portions of fish may be estimated by multiplying the levels based on fat by the fraction of fat (Table 10-80) per product as follows:. residue level/g product = ( residue level) x ( g&fat ) g&fat g&product (Eqn. 10-4) The resulting residue levels may then be used in conjunction with "as consumed" consumption rates. Additionally, intake rates may be reported in terms of units as consumed or units of dry weight. It is essential that exposur¢ assessors be aware of this difference so that they may ensure consistency between the units used for intake rates and those used for .concentration data (i.e., if the unit of food consumption is grams dry weight/day, then the unit for the amount of pollutant in the food should be grams dry weight). If necessary, as
consumed intake rates may be converted to dry weight intake rates .using the moisture content percentages of fish presented in Table 10-80 and the following equation: I IR.Jw = I Rae* [(100-W)/100] (Eqn. 10-5) I "Dry weight" intake rates may be converted to "as consumed" rates by using: I Rae= IRdw/[(100-W}/100] where: IRdw I Rae w 10.10. = dry weight intake rate; = as consumed intake rate; and = percent water content. RECOMMENDATIONS (Eqn. 10-6) Fish consumption rates are recommended based on the survey results presented in the key studies described in the preceding sections. Considerable variation exists in the mean and µpper percentile fish consumption rates obtained from these studies. This can be attributed largely to the characteristics of the survey population (i.e., general population, recreational anglers) and the type of water boc;:ly (i.e .. , marine, estuarine, freshwater), but other factors such as study design, method of data collection. and geographic location also play a role. Based on these study variations, recommendations Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellf1sh for consumption rates were classified into the following categories:
General Population;
Recreational Marine Anglers;
Recreational Freshwater Anglers; and
Native American Subsistence Fishing Populations The recommendations for each of these categories were rated according to the level of confidence the Agency has in the recommended values. These ratings were derived according to the principles outlined in Volume I, Section 1.3; the ratings and a summary of the rationale behind them are presented in tables which follow the discussion of each category. For exposure assessment purposes, the selection of the appropriate category (or categories) from above will depend on the exposure scenario being evaluated. Assessors should use the recommended values (or range of values) unless specific studies are felt to be particularly relevant to their needs, in which case results from a specific study or studies may be used. This is particularly true for the last two categories where no nationwide key studies exist. Even where national data exist, it may be advantageous to use regional estimates if the assessment targets a particular region. In addition, seasonal, age, and gender variations should be considered when appropriate. It should be noted that the recommended rates are based on mean (or median) values which represent a typical intake or central tendency for the population studied, and on upper estimates (i.e., 90th-99th percentiles) which represent the high-end fish consumption of the population studied. For the recreational angler populations, the recommended mearis and percentiles are based on all persons engaged in recreational fishing, not just those consuming recreationally caught fish. 10.10.1. Recommendations -General Population The key study for estimating mean fish intake (reflective of both short-term and term consumption) is U.S. EPA (1996a) analysis of USDA CSFll 1989-1991. The recommended values for mean intake by habitat and fish type are shown in Table 10-81. For all fish (finfish and shellfish), the recommended values are 6.0 g/day for freshwater/ estuarine fish, 14.1 g/day for marine fish, and 20.1 g/day for all fish. Note that these values are reported as uncooked fish weight. This is important because the concentration of the contaminants in fish are generally measured in the uncooked samples. Assuming that cooking results in some reductions in weight (e.g., loss of moisture), and the mass of the contaminant in the fish tissue remains constant, then the contaminant concentration in the cooked fish tissue will increase. Although actual Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish consumption may be overestimated when intake is expressed in an uncooked basis, the net effect on the dose may be canceled out since the actual concentration may be underestimated when it is based on the uncooked sample. On the other hand, if the "as consumed" intake rate and the uncooked concentration are used in the dose equation, dose may be underestimated since the concentration in the cooked fish is likely to be higher, if the mass of the contaminant remains constant after cooking. Therefore, it is more conservative and appropriate to use uncooked fish intake rates. If concentration data can be adjusted to account for changes after cooking, then the "as consumed" intake rates are appropriate. For example, concentration may be expressed on a dry weight basis and, if data are available, loss of contaminant mass after cooking may be accounted for in the However, data on the effects of cooking in contaminant concentrations are limited and assessors generally make the conservative assumption that cooking has no effect on the contaminant mass. Both "as consumed" and uncooked fish intake values have been presented in this handbook so that the assessor can choose the intake data that best matches the concentration data that is being used. CSFll data were based on a short-term survey and could not be used to estimate the distribution over the long term of the average daily fish intake. The long-term average daily fish intake distribution can be estimated using the TRI study which provided dietary data for a one month period. However, because the data from the TRI study are now over 20 years old, the value presented in Table 10-81 (56 g/day) has been adjusted by upward 25 percent based on Ruffle. et al. ( 1994) to the increase in fish consumption since the TRI survey was conducted. In addition to the arguments provided by Ruffle et al. (1994) for adjusting the data upward, recent data from CSFll 1989-91 indicate an increase of fish intake of 33 percent when compared to USDA NFCS data from 1977-78. Therefore, the adjustment recommended by Ruffle et al. (1994) of 25 percent seems appropriate. Then, as suggested by Ruffle et al. (1994) the distributions generated from TRI should be shifted upward by 25 percent to estimate the current fish intake distribution. Thus, the recommended perGentiles of long-term average daily fish intake are those of Javitz ( 1980) adjusted 25 percent upward (see Tables 10-3, 10-4). Alternatively, the log-normal distribution of Ruffle et al. (1994) (Table 10-6) may be used to approximate the long term fish. intake distribution; adjusting the log mean µby adding log(1.5)= 0.4, will shift the distribution upward by 25 percent. It is important to note that a limitation with these data is that the total amount of fish reported by respondents included fish from all sources (e.g., fresh, frozen, canned, domestic, international origin). Neither the TRI nor the CSFll surveys identified the source of the fish consumed. This type_ of information may be relevant for some assessments. It should be noted that because these recommendations are based on 1989-91 CSFll data, they may not reflect the most recent changes that may have occurred in consumption patterns. However, as indicated in Section 10.2, the 1989-91 CSFll data are believed to Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 10 -Intake of Fish and Shellfish be appropriate for assessing ingestion exposure for current populations because the rate of fish ingestion did not change dramatically between 1977-78 and 1995. The distribution of serving sizes may be useful for acute exposure assessments. The recommended values are 129 grams for mean serving size and 326 grams for the 95th percentile serving size based on the CSFll analyses (Table 10-82). 10.10.2. Recommendations -Recreational Marine Anglers The recommended values presented in Table 10-83 are based on the surveys of the National Marine Fisheries Service (NMFS, 1993). The intake values are based on finfish consumption only. 10.10.3. Recommendations -Recreational Freshwater Anglers The data presented in Table 10-84 are based on mailed questionnaire surveys (Ebert et al., 1993 and West et al., 1989; 1993) and a diary study (Connelly et al., 1992; 1996). The mean intakes ranged from 5-17 g/day. The recommended mean and 95th percentile values for recreational freshwater anglers are 8 g/day and 25 g/day, respectively; these were derived by averaging the values from the three populations surveyed in the key studies. Since the two West et al. surveys studied the same population, the average of the means from the two studies was used to represent the mean for this population. The estimate from the West et al. ( 1989) survey was used to represent the 95th percentile for this population since the long term consumption percentiles could not be estimated from the West et al. (1993) study. 10.10.4. Recommendations -Native American Subsistence Populations Fish consumption data for Native American subsistence populations are very limited. The CRITFC (1994) study gives a per-capita fish intake rate of 59 g/day and a 95th percentile of 170 g/day. The report by Wolfe and Walker (1987) presents harvest rates for 94 small communities engaged in subsistence harve$ts of natural resources. A factor of 0.5 was employed to convert the per-capita harvest rates presented in Wolfe and Walker (1987) to per capita individual consumption rates; this is the same factor used to convert from per capita household consumption rates to per capita individual consumption rates in the analysis of homegrown fish consumption from the 1987-1988 NFCS. Based on this factor, the median per-capita harvest in the 94 communities of 162 g/day (and the range of 31-1,540 g/day) is converted to the median per capita intake rate of 81 g/day (range 16-770 g/day) shown in Table 10-85. The recommended value for mean intake is 70 g/day and the recommended 95th percentile is 170 g/day. Exposure Factors Handbook August 1997 Volume II -Food Ingestion 'Factors Chapter 10 -Intake of Fish and Shellfish It should be emphasized that the above recommendations refer only to Native American subsistence fishing populations, not the Native American general population. Several studies show that intake rates of recreationally caught fish among Native Americans with state fishing licenses (West et al., 1989; Ebert et al., 1993) are somewhat higher ( 50-100 percent) than intake rates among other anglers, but far lower than the rates shown above for Native American subsistence populations. In addition, the studies of Peterson et al. (1994) and Fiore et al. (1989) show that total fish intake among a Native American population on a reservation (Chippewa in Wisconsin) is roughly comparable (50 percent higher) to total fish intake among licensed anglers in the same state. Also, the study of Fitzgerald et al. (1995) showed that pregnant women on a reservation (Mohawk in New York) have sport-caught fish intake rates comparable to those of a local white control population. The survey designs, data generated, and limitations/advantages of the studies described in this report are summarized and presented in Table 10-86. The confidence in recommendations is presented in Table 10-87. The confidence rating for recreational marine anglers is presented in Table 10-88. Confidence in fish intake recommendations for recreational freshwater fish consumption is presented in Table 10-89. The confidence in intake recommendations for Native American subsistence populations is presented in Table 10-90. Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Appendix 1 OA APPENDIX 1 OA RESOURCE UTILIZATION DISTRIBUTION Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Appendix 1 OA Appendix 1 OA. Resource Utilization Distribution The percentiles of the resource utilization distribution of Y are to be distinguished from the percentiles of the (standard) distribution of Y. The latter percentiles show what percentage of individuals in the population are consuming below a given level. Thus, the 50th percentile of the distribution of Y is that level such that 50 percent of individuals consume below it; on the other hand, the 5oth percentile of the resource utilization distribution is that level such that 50 percent of the overall consumption in the population is done. by consuming below it. The percentiles of the resource utilization distribution of Y will always be greater than or equal to the corresponding percentiles of the (standard) distribution of Y, and, in the case of recreational fish consumption, usually considerably exceed the standard percentiles. To generate the resource utilization distribution, one simplyweights each observation in the data set by the Y level for that observation and performs a standard percentile analysis of weighted data. If the data already have weights, then one multiplies the original weights by the Y level for that observation, and then performs the percentile analysis. Under certain assumptions, the resource utilization percentiles of fish consumption may be related (approximately) to the (standard) percentiles of fish consumption derived from the analysis of creel studies. In this instance, it is assumed that the creel survey data analysis did not employ sampling weights (i.e., weights were implicitly set to one); this is the case for many of the published analyses of creel survey data. In creel studies the fish consumption rate for the ith individual is usually derived by multiplying the amount of fish consumption per fishing trip (say Ci) by the frequency of fishing (say fJ_ If it is assumed that the probability of sampling of an angler.is proportional to fishing frequency, then sampling weights of inverse fishing frequency (1/ fi ) should be employed in the analysis ofthe survey data. Above it was stated that for data that are already weighted the resource utilization distribution is generated by multiplying the original weights by the individual's fish consumption level .to create new weights. Thus, to generate the resource utilization distribution from the data with weights of (1/ fi ), one multiplies (1/ fJ by the fish consumption level of fi Ci to get new weights of Ci. Now if Ci (amount of consumption per fishing trip) is constant over the population, then these new weights are constant and can be taken to be one. But weights of one is what (it is assumeq) were used in the original creel survey data analysis. Hence, the resource utilization distribution is exactly the same as the original (standard) distribution derived from the creel survey using constant weights. Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Appendix 1 OA The accuracy_ of this approximation of the resource utilization distribution of fish by the (standard) distribution of fish consumption deriveq from an unweighted analysis of creel survey data depends then on two factors, how-approximately constant the Ci 's are 'in the population and how approximately proportional the relationship between sampling probability and fishing frequency is. Sampling probability will be roughly proportional to frequency if repeated sampling at the same site is limited or if interviewing is performed independent of past interviewing status. Note: For any quantity Y that is consumed by individuals in a population, the percentiles of the "resource utilization distribution" of Y can be formally defined as follows: YP (R) is the pth percentile of the resource utilization distribution if p percent of the overall consumption of Y in the population is done by individuals with consumption below Y P (R) and 100-p percent is done by individuals with consumption above YP(R). Exposure Factors Handbook August 1997 Table 10-1. Total Fish Consumption by DemoQraphic Variables* Intake (g/Qerson/day) Demographic Category Mean 95th Percentile Race Caucasian 14.2 41.2 Black 16.0 45.2 Oriental 21.0 67.3 other 13.2 29.4 Sex Female 13.2 38.4 Male 15.6 44.8 Age (years) 0-9 6.2 16.5 10-19 10.1 26.8 20-29 14.5 38.3 30-39 15.8 42.9 40-49 17.4 48.1 50-59 20.9 53.4 60-69 21.7 55.4 70+ 13.3 39.8 Census Region New England 16.3 46.5 Middle Atlantic 16.2 47.8 East North Central 12.9 36.9 West North Central 12.0 35.2 South Atlantic 15.2 44.1 East South Central 13.0 38.4 West South Central 14.4 43.6 Mountain 12.1 32.1 Pacific 14.2 39.6 Community TyQe Rural, non-SMSA 13.0 38.3 -Central city, 2M or more 19.0 55.6 Outside central city,_2M or more 15.9 47.3 Central city, 1 M -2M 15.4 41.7 Outside central city, 1 M -2M 14.5 41.5 Central city, 500K -1 M 14.2 41.0 Outside central city, 500K -1 M 14.0 39.7 Outside central city, 250K -500K 12.2 32.1 Central city, 250K -500K 14.1 40.5 Central city, 50K -250K 13.8 43.4 Outside central city, 50K -250K 11.3 31.7 other urban 13.5 39.2 a The calculations in this table are based on respondents who consumed fish during the survey month. These respondents are estimated to represent 94 percent of the U.S. population. Source: Javitz 1980.

Table 10-2. Mean and 95th Percentile of Fish Consumption (q/day) by Sex and Aqea Total Fish Age (years) Mean 95th Percentile Female 0-9 6.1 17.3 10 -19 9.0 25.0 20 -19 13.4 34.5 30-39 14.9 41.8 40-49 16.7 49.6 50-59 19.5 50.1 60-69 19.0 46.3 70+ 10.7 31.7 Male 0-9 6.3 15.8 10 -19 11.2 29.1 20 -19 16.1 43.7 30-39 17.0. 45.6 40-49 18.2 47.7 50-59 22.8 57.5 60 -69 24.4 61.1 70+ 15.8 45.7 Overall 14.3 41.7 a The calculations in this table are based upon respondents who consumed fish in the month of the survey. These respondents are estimated to represent 94.0% of the U.S. population. Source: Javitz 1980.

Table 10-3. Percent Distribution ofTotal Fish Consumption for Females by Age* Consumption Category (g/day) 0.0-5.0 5.1-10.0 10.1-15.0 15.1-20.0 20.1-25.0 25.1-30.0 30.1-37.5 37.6-47.5 47.6-60.0 60.1-122.5 over 122.5 Age (yrs) Percentage 0-9 55.5 26.8 11.0 3.7 1.0 1.1 0.7 0.3 0.0 0.0 0.0 10-19 17.8 31.4 15.4 6.9 3.5 2.4 1.2 0.7 0.2 0.4 0.0 20-29 28.1 26.1 20.4 11.8 6.7 3.5 4.4 -Z.2 0.9 0.9 0.0 30-39 22.4 23.6 18.0 12.7 8.3 4.8 3.8 2.8 1.9 1.7 0.1 40-49 17.5 21.9 20.7 13.2 9.3 4.5 4.6 2.8 3.4 2.1 0.2 50-59 17.0 17.4 16.8 15.5 10.5 8.5 6.8 5.2 4.2 2.0 0.2 60-69 11.5 16.9 20.6 15.9 9.1 9.2 6.0 6.1 2.4 2.1 0.2 70+ 41.9 22.1 12.3 9.7 5.2 2.9 2.6 1.2 0.8 1.2 0.1 Overall 28.9 24.0 16.8 10.7 6.4 4.3 '3.5 2.4 1.6 1.2 0.1 . The percentage of females in an age bracket whose average daily fish consumption is within the specified range . The calculations in this table are based upon the respondents who consumed fish during the month of the survey. These respondents are estimated to represent 94% of the U.S. population. Source: Javitz, 1980.

Table 10-4. Percent Distribution of Total Fish Consumption for Males by Age' Consumption Category (g/day) 0.0-5.0 5.1-10.0 10.1-15.0 15.1-20.0 20.1-25.0 25.1-30.0 30.1-37.5 37.6-47.5 47.6-60.0 60.1-122.5 over 122.5 Age (yrs) Percentage 0-9 52.1 30.1 11.9 3.1 1.2 0.6 0.7 0.1 0.2 0.1 0.0 10-19 27.8 29.3 19.0 10.4 6.0 3.2 1.7 1.7 0.4 0.5 0.0 20-29 16.7 22.9 19.6 14.5 8.8 6.2 4.4 3.1 1.9 1.9 0.1 30-39 .16.6 21.2 19.2 13.2 9.5 7.3 5.2 3.2 1.3 2.2 0.0 40-49 11.9 22.3 18.6 14.7 8.4 8.5 5.3 5.2 3.3 1.7 0.1, 50-59 9.9 15.2 15.4 14.4 10.4 9.7 8.7 7.6 4.3 4.1 0.2 60-69 7.4 15.0 15.6 12.8 11.4 8.5 9.9 8.3 5.5 5.5 0.1 70+ 24.5 21.7 15.7 9.9 9.8 5.3 5.4 3.1 1.7 2.8 0.1 Overall 22.6 23.1 17.0 11.3 7.7 5.7 4.6 3.6 2.2 2.1 0.1 . The percentage of males in an age bracket whose average daily fish consumption is within the specified range . The calculations in this table are based upon respondents who consumed fish during the month of the survey. These respondents are estimated to represent 94% of the U.S. population. Source: Javitz, 1980. r Table 10-5. Mean Total Fish Consumption bv Species' Mean consumption Mean consumption Species la/dav) Species la/davl Not reported 1.173 Mullet" 0.029 Abalone 0.014 Oystersb 0.291 Anchovies 0.010 Perch (Freshwater)b 0.062 Bassb 0.258 Perch (Marine) 0.773 Bluefish 0.070 Pike (Marine)b 0.154 Bluegillsb 0.089 Pollock 0.266 Bonitob 0.035 Pompano 0.004 Buffalofish 0.022 Rockfish 0.027 Butterfish 0.010 Sablefish 0.002 Carpb 0.016 Salmonb 0.533 Catfish (Freshwater)' 0.292 Scallopsb 0.127 Catfish (Marine)b 0.014 Scupb 0.014 Clamsb 0.442 Sharks 0.001 Cod 0.407 Shrimpb 1.464 Crab, King 0.030 Smelt" 0.057 Crab, other than Kingb

0.254 Snapper 0.146 Crappieb 0.076 Snookb 0.005 Croaker' 0.028 Spotb 0.046 Dolphinb 0.012 Squid and Octopi 0.016 Drums 0.019 Sunfish 0.020 Floundersb 1.179 Swordfish 0.012 Groupers 0.026 Tilefish 0.003 Haddock 0.399 Trout (Freshwater)b 0.294 Hake 0.117 Trout (Marine)b 0.070 Halibutb 0.170 Tuna, light 3.491 Herring 0.224 Tuna, White Albacore 0.008 Kingfish 0.009 Whitefishb 0.141 Lobster (Northern )b 0.162 Other finfishb 0.403 Lobster (Spiny) 0.074 Other shellfishb 0.013 Mackerel, Jack 0.002 Mackerel, other than Jack 0.172 ' The calculations in this table are based upon respondents who consumed fish during the month of the survey. These respondents are estimated to represent 94% percent of the U.S. population. b Designated as freshwater or estuarine species by Stephan (1980). Source: Javitz 1980.

Table 10-6. Best Fits of Lognormal Distributions Using the Nonlinear Optimization (NLO) Method Adults Teenaaers Children Shellfish µ 1.370 -0.183 0.854 a 0.858 1.092 0.730 (min SS) 27.57 1.19 16.06 Finfish (freshwater) µ 0.334 0.578 -0.559 a 1.183 0.822 1.141 (min SS) 6.45 23.51 2.19 Finfish (saltwater) µ 2.311 1.691 0.881 a 0.72 0.830 0.970 lminSS\

30.13 0.33 4.31 The following equations may be used with the appropriateµ and a values to obtain an average Daily Consumption Rate (OCR), in grams, and percentiles of the OCR distribution. DCR50 =exp(µ) DCR90 = exp [µ + z(0.90)
a] DCR99 = exp [µ + z(0.99)
a] DCR,,g = exp [µ + 0.5
d'] Source: Ruffle et al. 1994.

Table 10-7. Per Capita Distribution of Fish Intake (g/day) by Habitat and Fish Type for the U.S. Population (Uncooked Fish Weight) Estimate (90% Interval) Habitat Statistic Finfish Shellfish Total Fresh/Estuarine Mean 3.6 (3.0-4.1) 2.4 (2.0 -2.8) 6.0 (5.3 -6.7) 50th% 0.0 (0.0 -0.0) 0.0 (0.0 -0.0) 0.0 (0.0 -0.0) 90th% 0.4 (0.00 -0.7) 0.0 (0.0 -0.3) 15.9 (14.4-17.8) 95th% 21.7 (14.8 -25.8) 13.3 (11.7-17.8) 40.0 (37.9 -44.8) 99th% 87.3 (80.1 -98.0) 63.6 (60.4 -68.5) 107.6 (98.3-109.1) Marine Mean 12.5 (11.5-13.5) 1.6 (1.3-1.9) 14.1 (13.1 -15.1) 50th% 0.0 (0.0 -0.0) 0.0 (0.0 -0.0) 0.0 (0.0 -0.0) 90th% 47.5 (43.6 -49.8) 0.0 (0.0 -0.0) 52.1(47.8-55.9) 95th% 74.6 (70.3 -76.3) 0.0 (0.0 -6.8) 76.5 (74.6 -80.9) 99th% 133.0 (127.8 -143.2) 50.3 (44.5 -59.0) 138.2 (133.0 -155.1) All Fish Mean 16.1 (15.0 -17.2) 4.0 (3.4 -4.6) 20.1 (18.8-21.4) 50th% 0.0 (0.0 -0.0) 0.0 (0.0 -0.0) 0.0 (0.0 -0.0) 90th% 59.1 (54.6 -62.3) 0.0 (0.0 -3.5) 70.1 (65.4 -7 4.2) 95th% 84.4 (81.3 -89.6) 22.7 (21.8 -26.6) 102.0 (99.3 -106.7) 99th% 156.7 (148.7-168.1) 99.0 (87 .8 -109.6) 173.2 (162.8-176.5) Note: Percentile confidence intervals estimated using the bootstrap method with 1,000 replications; percent consuming gives the percentage of individuals consuming the specified category of fish during the 3-day survey period. Estimates are projected from a sample of 11,912 individuals to the U.S. population. Source: U.S. EPA, 1996a. Table 10-8. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) by Habitat for Consumers Only (Uncooked Fish Weight) Habitat Statistic Estimate 90% Interval Fresh/Estuarine' Mean 86.2 78.4-94.0 50th% 48.8. 45.6-54.9 90th% 217.9 205.3 -237.3 95tho/o 290.0 267 .1 -325.6 99th% 489.3 424.9 -534.2 Percent Consuming 18.5 Marine' Mean 113.1 107 .8 -118.4 50th% 93.3 92.0-94.9 90th% 222.7 216.5 -225.6 95th% 271.7 260.6 -279.9 99th% 415.9 367.3 -440.5 Percent Consuming 30.1 All Fish0 Mean 129.0 123.7 -134.3 50th% 101.9 98.9 -103.9 90th% 249.1 241.0 -264.1 95th% 326.0 306.1 -335.6 99th% 497.5 469.2 -519.7 Percent Consuming 36.9 Note: Percentile confidence intervals estimated using the bootstrap method with 1,000 replications; percent consuming gives the percentage of individuals consuming the specified category offish during the 3-day survey period. a Sample size= 1,892; population size= 44,946,000 b Sample size = 3, 184; population size= 73, 100,000 c Sample size = 3,927; population size= 89,800,000 Source: U.S. EPA, 1996a. Table 10-9. Per Capita Distribution ofFish Intake (mg/kg-day) by Habitat and Fish Type for U.S. Population (Uncooked Fish Weight) Estimate (90% Interval) Habitat Statistic Finfish Shellfish Total Fresh/Estuarin Mean 58.1 (48.4 -67.7) 35.9 (30.2 -41.6) 94.0 (83.4 -104.6) e 5oth% 0.0 (0.0 -0.0) 0.0 (0.0 -0.0) 0.0 (0.0 -0.0) 9oth% 5.9 (O:o -12.3) 0.0 (0.0 -3.8) 251.8 (222.5-282.6) 95th% 340.5 (252.9-410.1) 190.0 (155.7 -268.3) 677.7 (631.9 -729.1) 99th% 1,401.9 (1,283.9 -1,511.8) 953.5 (871.3-1,007.4) 1,593.3 ( 1,511.8 -1,659.2) Marine Mean 215.8 (195.9-235.6) 24.3 (20.6 -28.0) 240.1 (220.1 -260.0) 5oth% 0.0 (0.0 -0.0) 0.0 (0.0 -0.0) 0.0 (0.0 -0.0) 90th% 783.4 (752.5 -842.2) 0.0 (0.0 -0.0) 855.6 (809.7 -909.8) 95th% 1,208.1 (1,149.5-1,264.9) 0.0 (0.0 -88.8 1,271.5 (1,227.2-1,371.2) 99th% 2,400.0 (2,284.2 -2,660.1) 701.3 (636.2-944.7) 2,575.3 (2,393.2 -2,708.6) All Fish Mean 273.9 (252.0 -295.7) 60.2 (52.3 -68.2) 334.1 (311.3 -356.9) 5oth% 0.0 (0.0 -0.0) 0.0 (0.0 -0.0) 0.0 (0.0 -0.0) 90th% 966.1 (893.3 -1,039.5) 0.0 (O:O -47.4) 1,123.1 (1,090.8-1,179.0) 95th% 1,434.3 (1,371.2 -1,526.8) 372.5 (324.1 -460.5) 1,684.2 (1,620.5-1,718.5) 99th% 2,857.5 (2,649.6 -3,003.6) 1,412.4 (1,296.0-1,552.1) 3,092.8 (2,973.7 -3,250.2) Note: Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Estimates are projected from a sample of 11,912 individuals to the U.S. population. Source: U.S. EPA, 1996a. Table 10-10. Per Capita Distribution of Fish (Finfish and Shellfish) Intake by Habitat for Consumers Only (Uncooked Fish Weight) Habitat Statistic Estimate 90% Interval Fresh/Estuarine' Mean 1,363.4 1,242.2 -1,484.7 5oth% 819.7 736.9 -895.7 9oth% 3,325.1 3,232.6 -3,677.0 95th% 4,408.2 4,085.6 -4,781.3 99th% 7,957.5 6,979.2 -8,921.0 Percent Consuming 18.5 Marineb Mean* 1,927.0 1,829.5 -2,024.4 50th% 1,507.7 1,470.7 -1,538.8 9oth% 3,752.9 3,632.0 -4,001.2 95th% 5,018.7 4,852.1 -5,267.3 99th% 8,448.3 7,215.7-9,136.9 Percent Consuming 30.1 All Fish' Mean 2,145.3 2,055.9 -2,234.6 5oth% 1,662.8 1,610.7-1,720.1 9oth% 4,223.9 4,085.8 -4,454.2 95th% 5,477.9 5, 163.3 -5,686.0 99th% 9,171.5 8,605.4 -9,796.6 Percent Consuming 36.9 Note: Percentile confidence intervals estimated using the bootstrap method with 1,000 replications; percent consuming gives the percentage of individuals consuming the specified category of fish during the 3-day survey period. a Sample size = 1,892; population size= 44,946,000 b Sample size = 3, 184; population size = 73, 100,000 c Sample size = 3,927; population size = 89,800,000 Source: U.S. EPA, 1996a. Table 10-11. Per Capita Distribution of Fish Intake (g/day) by Habitat and Fish Type for the U.S. Population (Cooked Fish Weight -As Consumed) Estimate (90% Interval) Habitat Statistic Finfish Shellfish Total Fresh/Estuarine Mean 2.8 (2.4 -3.3) 1.9 (1.6-2.2) 4.7 (4.2 -5.3) 50th% 0.0 (0.0 -0.0) 0.0 (0.0 -0.0) 0.0 (0.0 -0.0) 90th% o.3 (o.o -o.7) 0.0 (0.0 -0.2) 12.6 (10.9-14.0) 95th% 17.2 (12.9 -20.8) 10.1 (7.9 -13.8) 32.2 (29.8 -35.2) 99th% 70.9 (60.3 -75.7) 49.9 (45.6 -56.4) 82.5 (77.2 -86.4) Marine Mean 9.7 (9.0 -10.5) 1.2 (1.0-1.4) 10.9 (10.1 -11.7) 50th% 0.0 (0.0 -0.0) 0.0 (0.0 -0.0) 0.0 (0.0 -0.0) 90th% 37.3 (33.7 -37.4) 0.0 (0.0 -0.0) 39.5 (37.3 -42.9) 95th% 56.2 (55.6 -58.2) 0.0 (0.0 -5.3) 59.6 (57.0 -61.8) 99th% 103.1 (98.5 -112.0) 37.0 (35.4 -44.5) 106.8 (104.6-114.6) All Fish Mean 12.6 (11.7-13.4) 3.1 (2.7 -3.5) 15.7 (14.7 -16.6) 50th% 0.0 (0.0 -0.0) 0.0 (0.0 -0.0) 0.0 (0.0 -0.-0) 90th% 46.0 (43.6 -49:0) 0.0 (0.0 -2.6) 55.0 (51.4 -56.0) 95th% 67.0 (63.0 -70.7) 18.9 (16.7 -22.1) 78.3 (75.2 -80.6) 99th% 119.1 (113.9-125.9) 74.3 (68.7 -82.0) 133.5 (125.3 -140.2) Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Estimates are projected from a sample of 11,912 individuals to the U.S. population. Source: U.S. EPA, 1996a. Table 10-12. Per Capita Distribution of Fish Intake (g/day) by Habitat for Consumers Only (Cooked Fish Weight -As Consumed) Habitat Statistic Estimate 90% Interval Fresh/Estuarine' Mean 68.0 61.9-74.1 50th% 39.5 36.2 -44.7 90th% 170.8 158.7 -181.8 95th% 224.8 212.9 -246.0 99th% 374.7 336.5 -341.3 Percent Consuming 18.5 Marineb Mean 87.8 *83.7 -91 .8 50th% 71.8 69.7 -74.2 90th% 169.4 167.0 -173.7 95th% 208.5 198.1 -221.7 99th% 320.4 292.8-341.9 Percent Consuming 30.1 All Fish0 Mean 100.6 96.7-104.6 5oth% 80.8 79.3-83.9 9oth% 197.4 188.7 -205.1 95th% 253.4 231.5 -264.5 99th% 371.6 359.3 -401.6 Percent Consuming 36.9 Note: Percentile confidence intervals estimated using the bootstrap method with 1,000 replications; percent consuming gives the percentage of individuals consuming the specified category of fish during the 3-day survey period. a Sample size= 1,892; population size= 44,946,000 b Sample size = 3, 184; population size = 73, 100,000 c Sample size = 3,927; population size = 89,800,000 Source: U.S. EPA, 1996a. Table 10-13. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the U.S. Population by Age and Gender-As Consumed (Freshwater and Estuarine) AQe Sample Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) Females 14 or under 1431 1.58 (1.06-2.10) 1.44 (0.00-4.07) 12.51 (6.00-14.20) 36.09 (28.53-43.20) 15 -44 2891 4.28 (3.55-5.02) 10.90 (8.79-13.84) 28.80 (26.26-33.53) 70.87 (64. 7 4-90.56) 45 or older 2340 5.27 (4.21-6.32) 18.72 (15.19-22.12) 34.67 (29.17-39.38) 85.35 (71.71-100.50) All ages 6662 4.02 (3.43-4.61) 10.66 (8.11-13.19) 28.11 (23.14-31.27) 71.98 (60.38-86.40) Males 14 or under 1546 2.17 (1.32-3.02) 0.99 (0.21-6.67) 14.94 (11.88-22.33) 48.72 (37.48-52.29) 15 -44 2151 6.14 (5.08-7.19) 18.19 (10.21-24.20) 48.61 (35.42-54.65) 96.32 (85.60-115.75) 45 or older 1553 7.12 (5.87-8.38) 22.67 (19.28-27.83) 46.62 (41.27-58.01) 103.07 (86.41-125.11) All ages 5250 5.46 (4.81-6.11) 16.05 (12.41-19.30) 40.29 (35.92-43.73) 86.40 (78.37-103.07) Both Sexes 14 or under 2977 1.88 (1.36-2.40) 1.31 (0.00-4.33) 13.90 (9.32-15.05) 40.77 (35.15-44.82) 15 -44 5042 5.17 (4.46-5.87) 13.88 (12.05-17.21) 36.21 86.14 (74.67-96.67) 45 or older 3893 6.11 (5.20-7.02) 21.48 (16.69-23.33) 40.55 (35.80-47.31) 88.18 (85.33-103.07) All aQes 11912 4.71 (4.17-5.25) 12.62 (10.91-13.98) 32.16 (29.81-35.15) 82.45 (77.17-86.40) Percentile intervals (B.1.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Source: U.S. EPA 1996a. Table 10-14. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the U.S. Population by Age and Gender.-As Consumed (Marine) Aqe Sample Size Mean (90% C.I.) 9oth % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) Females 14 or under 1431 6.60 (5.16-8.05) 24.84 (18.67-31.20) 37.32 (32.27-42.05) 87.05 (63.26-112.06) 15-44 2891 9.97 (8.94-11.01) 36.83 (31.42-41.99) 55.53 (47.67-59.59) 105.32 (96.98-112.00) 45 or older 2340 12.59 (11.36-13.82) 42.92 (38.92-47.66) 63.85 (57.27-72.36) 103.08 (91.61-121.52) All ages 6662 10.10 (9.27-10.93) 36.97 (34.86-37.33) 55.54 (51.67-56.98) 102.01 (97.67-110.69) Males 14 or under 1546 7.25 (5.72-8.79) 24.85 (19.92-33.85) 49.89 (42.09-56.45) 92.64 (65.87-132.39) 15-44 2151 13.33 (11.89-14.77) 52.73 (48.34-55.80) 71.49 (63.99-80.00) 116.51 (106.06-143.31) 45 or older 1553 13.32 (11:73-14.92) 50.39 ( 4 7 .13-53.33) 64.51 (61.64-74.58) 116.86 (106.93-144.94) All ages 5250 11.85 (10.75-12.95) 47.13. (44.52-49.80) 64.50 (62.46-67.53) 113.94 (103.47-130.00) Both Sexes 14 or under 2977 6.93 (5.63-8.23) 24.88 (22.64-28.08) 42.07 (38.15-48.96) 91.64 (68.59-112.06) 15-44 5042 11.58 (10.55-12.60) 44.24 (39.84-46.70) 62.18 (57.88-69.72) 110.07 (103.50-120.49) 45 or older 3893 12.92 (11.86-13.98) 46.51 (38.98-50;97) 64.19 (60.67-72.00) 113.33 (104.59-119.53) All ages 11912 10.94 (10.14-11.73) 39.51 (37.29-42.91) 59.62 (57.03-61.84) 106.84 (104.59-114.55) Percentile intervals (B.1.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Source: U.S. EPA 1996a. Table 10-15. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the U.S. Population by Age and Gender -As Consumed (All Fish) Aae Sample Size Mean (90% C.I.) 9oth % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) Females 14 or under 1431 8.19 (6.53-9.84) 32.28 (26.78-37.33) 43.09 (37 .99-51.55) 95.19 (63.26-113.96) 15 -44 2891 14.25 (12.96-15.55) 47.13 (41.95-55.83) 71.58 (64.74-82.11) 120.84 (110.69-132.79) 45 or older 2340 17.86 (16.19-19.52) 56.70 (54.13-62.99) 81.94 (74.63-88.23) 130.51 (122.02-140.21) All ages 6662 14.13 (13.07-15.18) 46.44 (43.63-49.67) 70.23 (67.27-73.91) 120.22 (112.06-126.07) Males 14 or under 1?46 9.42 (7.60-11.25) 34.85 (27.77-42.09) 52.85 (49.93-62.50) 98.36 (71.74-132.39) 15 -44 2151 19.46 (17.75-21.18) 68.60 (65.74-74.70) 93.65 (85.60-96.96) 149.07 (142.73-154.41) 45 or older 1553 20.45 (18.41-22.49) 64.44 (61.33-69.27) 87.21 (85.33-100.19) 168.49 (143.78-174.55) All ages 5250 17.31 (16.04-18.59) 60.23 (56.91-62.99) 85.69 (80.61-93.32) 143.91 (135.35-154.15) Both Sexes 14 or under 2977 8.82 (7.39-10.24) 32.88 (27.97-37.11) 50.95 (44.64-53.86) 98.33 (86.40-113.96) 15 -44 5042 16.74 (15.54-17.94) 57.88 (56.00-60.85) 84.59 (79.91-90.83) 138.21 (122.84-149.15) 45 or older 3893 19.03 (17.54-20.52) 61.32 (56.00-65.74) 86.21 (77.42-94.70) 143.91 (131.12-171.37) All aaes 11912 15.65 (14.67-16.63) 55.02 (51.38-56.00) 78.34 (75.21-80.56) 133.46 (125.27-140.21) Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Source: U.S. EPA 1996a. Table 10-16. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the U.S. Population AQed 18 Years and Older by Habitat -As Consumed Grams/day 90% Interval Habitat Statistic Estimate Lower Bound Unner Bound Fresh/Estuarine Mean 5.59 4.91 6.28 50th % 0.00 0.00 0.00 90th % 17.80 14.89 20.63 95th % 39.04 36.13 42.16 99th % 86.30 81.99 96.67 Marine Mean 12.42 11.55 13.29 50th % 0.00 0.00 0.00 90th % 45.98 44.48 48.34 95th % 64.08 61.61 68.05 99th % 111.38 101.94 120.49 All Fish Mean 18.01 16.85 19.17 50th % 0.00 0.00 0.00 90th % 60.64 57.06 64.63 95th % 86.25 80.29 91.00 99th % 142.96 134.23 154.15 Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Note: Estimates are projected from a sample of 8,478 individuals of age 18 and older to the U.S. population of 177,807,000 individuals of age 18 and older using 3-year combined survey weights. Source: U.S. EPA 1996a. Table 10-17. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the U.S. Population by Age and Gender-As Consumed (Freshwater and Estuarine) AQe Sample Size Mean (90% C.I.) 90th % (90% 8.1.) 95th % (90% 8.1.) 99th % (90% 8.1.) Females 14 or under 1431 67.12 (46.16-88.09) 57.30 (0.00-128.52) 460.16 (218.56-559.86) 1356.54 (1295.24-2118.93) 15 -44 2891 66.22 (55.35-77.08) 17 4.96 ( 115.11-205.05) 451.04 (421.65-505.49) 1188.16 (977.85-1278.63) 45 or older 2340 78.29 (63.27-93.30) 273.63 (209.63-300.11) 548.66 (466.18-633.87) 1251.00 (1038.97-1324.90) All ages 6662 70.32 (60.09-80.55) 177.91 (132.69-212.30) 497.30 (442.20-558.85) 1269.76 (1093.19-1328.24) Males 14 or under 1546 73.93 (44.89-102.96) 28.10 (8.86-231.33) 723.93 (423.52-785.58) 1290.10 (1279.82-1355.11) 15-44 2151 75.35 (62.00-88.70) 230.13 (132.30-309.85) .577.84 (410.09-706.31) 1132.23 (1028.61-1416.47) 45 or older 1553 86.75 (70.91-102.58) 291.50 (230.15-364.24) 584.96 (512.66-630.77) 1231.60 (1115.58-1566.68) All ages 5250 78.36 (69.10-87.61) 231.57 (186.27-276.04) 589.22 (549.64-630.09) 1265.10 (1133.18-1355.11) Both Sexes 14 or under 2977 70.59 (53.29-87.89) 53.24 (0.00-118.48) 556.34 (417.11-683.80) 1347.67 (1279.82-1390.82) 15-44 5042 70.58 (61.27-79.89) 197.11 (154.78-229.29) 502.26 (410.09-604.29) 1167.57 (1021.96-1279.82) 45 or older 3893 82.12 (70.19-94.05) 286.93 (228.49-332.88) 566.30 (505.10-625.21) 1251.55 (1115.58-1324.90) All ages 11912 74.16 (65.74-82.57) 204.00 (177.97-225.16) 547.64 (505.10-565.37) 1274.55 (1197.29-1324.90) Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Source: U.S. EPA 1996a. Table 10-18. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the U.S. Population by Age and Gender -As Consumed (Marine) Age Sample Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) Females 14 or under 1431 256.90 (207.04-306.76) 936.94 (723.73-1055.43) 1545.15 (1260.24-1760.26) 3060.22 (2403.50-4354.46) 15-44 2891 159.79 (142.76-176.82) 573.49 (493.39-663.16) 873.73 (780.56-929.55) 1700.21 (1578.65-1815.48) 45 or older 2340 191.08 (171.33-210.83) 644.33 (608.39-725.83) 978.84 (881.06-1103.01) 1694.58 (1488.32-1791.84) All ages 6662 190.61 (172.89-208.33) 658.64 (627.61-700.33) 1024.76 (958.94-1096.14) 1979.45 (1793.40-2137.78) Males 14 or under 1546 230.25 (188.33-272.17) 846.57 (734.83-987 .18) 1504.37 (1320.60-1749.26). 2885.08 (2631.87-3430.60) 15 -44 2151 165.92 (147.73-184.12) 626.85 (593.90-680.90) 933.05 (833.43-982.30) 1472.98 (1411.97-1525.47) 45 or older 1553 164.37 (144.87-183.87) 621.00 839.06 (800.23-946.97) 1422.94 (1293.89-1791.31) All ages 5250 181.08 (163.00-199.15) 670.19 (622.62-714.53) 981.87 (934.45-1071.54) 1923.63 (1802.17-1972.86) Both Sexes 14 or under 2977 243.31 (202.43-284.18) 873.87 (741.53-1093.69) 1522.52 (1371.10-1587.20) 3059.93 (2732.63-3430.60) 15-44 5042 162.72 (148.13-177.31) 602.58 (564.88-648.54) 893.82 (856.58-940.85) 1576.09 (1503.11-1697.71) 45 or older 3893 178.99 (164.13-193.84) 628.06 (555.84-700.65) 914.67 (825.21-1040.75) 1568.85 (1483.71-1760.74) All acies 11912 186.06 (170.81-201.31) 663.00 (627.39-717.18) 991.96 (960.40-1044.69) 1942.17 (1815.48-2042.99) Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Source: U.S. EPA 1996a. Table 10-19. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the U.S. Population by Age and Gender -As Consumed (All Fish) AQe Sample Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) Females 14 or under 1431 324.02 (264.25-383.80) 1091.52 (929.29-1407.54) 1690.99 (1513.97-2072.35) 3982.60 (3219.32-4568.45) . 15-44 2891 226.01 (205.01-247.01) 755.51 (641.02-879.29) 1126.02 (975.49-1269.56) 2195.86 (1762.90-2310.54) 45 or older 2340 269.37 (243.36-295.38) 862.18 (796.63-955.82) 1296.64 (1186.00-1344.85) 2147.32 (1791.84-2354.25) All ages 6662 260.93 (239.15-282.72) 873.61 (796.63-911.89) 1323.29 (1269.56-1418.85) 2361.12 (2272.41-2598.14) Males 14 or under 1546 304.17 (251.91-356.43) 1172.17 (1085.62-1320.60) 1575.43 (1496.19-1943.82) 3393.84 (2731.95-3733.22) 15 -44 2151 241.27 (219.25-263.29) 867.70 (814.06-919.25) 1208.43 (1101.68-1266.32) 1760.48 (1611.45-1851.26) 45 or older 1553 251.12 (225.48-276.76) 797.83 (762.30-858.52) 1122.80 (1041.28-1266.18) 1922.33 (1786.53-2275.93) All ages 5250 259.43 (239.81-279.06) 894.96 (842.29-938.16) 1298.95 (1224.82-1366.86) 2346.64 (1972.86-2631.87) Both Sexes 14 or under 2977 313.90 (268.42-359.38) 1128.26 (1005.58-1320.60) 1679.91 (1546.20-1848.43) 3419.49 (3184.04-3733.22) 15-44 5042 233.30 (216.16-250.44) 828.12 (771.73-868.89) 1155.30 (1102.57-1212.19) 2003.46 (1787.65-2182.19) 45 or older 3893 261.10 (240.34-281.87) 818.10 (771.23-882.53) 1249.97 (1101.32-1323.53) 1967.01 (1796.52-2257.50) All aQes 11912 260.22 (242.60-277.83) 880.47 (844.35-918. 79) 1308.54 (1267.15-1346.71) 2356.54 (2224.54-2556.68) Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Source: U.S. EPA 1996a. Table 10-20. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the U.S. Population Aged 18 Years and Older by Habitat -As Consumed 90% Interval Habitat Statistic Estimate Lower Bound Uooer Bound Fresh/Estuarine Mean 75.56 66.37 84.75 50th % 0.00 0.00 0.00 90th % 242.49 205.05 277.26 95th % 547.61 493.47 587.37 99th % 1,171.84 1,123.52 1,252.78 Marine Mean 172.86 160.73 184.99 50th % 0.00 0.00 0.00 90th % 624.83 598.84 670.34 95th % 911.05 877.29 952.66 99th % 1,573.20 1,468.43 1,713.17 All Fish Mean 248.42 232.19 264.64 50th % 0.00 0.00 0.00 90th % 829.02 791.06 872.61 95th % 1,197.36 1, 18 1,264.74 99th % 2,014.67 1,839.55 2,180.87 Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Note: Estimates are projected from a sample of 8,478 individuals of age 18 and older to the population of 177,807,000 individuals of age 18 and older using 3-year combined survey weights. Source: U.S. EPA 1996a. Table 10-21. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day)

for Consumers Only by Age and Gender -As Consumed (Freshwater and Estuarine) Sample Aae Size Mean (90% C.l.l 90th % (90% B.l.l 95th % (90% B.l.l 99th % (90% B.I.) Females 14 or under 138 38.44 91.30 128.97 182.66 15-44 445 61.40 148.83 185.44 363.56 45 or older 453 62.49 150.67 214.91 296.69 All ages 1036 58.82 (51.57-66.06) 145.65 (130.73-152.24) 190.28 (173 .. 81!-219.03) 330.41 (259.20-526.69) Males 14 or under 157 52.44 112.05 154.44 230.74 15-44 356 81.56 224.01 275.02 371.53 45 or older . 343 82.23 192.31 255.68 449.09 All ages 856 77.50 (70.21-84.80) 197.93 (169.51-224.85) 253.48 (216.54-290.00) 404.65 (371.63-421.60) Both Sexes 14 or under 295 ' 45.73 108.36 136.24 214.62 15-44 801 71.44 180.67 230.95 371.52 45 or older 796 71.81 174.54 231.38 427.73 All ages 1892 68.00 (61.92-74.07) 170.84 (158.74-181.79) 224.78 (212.91-245.98) 374.74 (336.50-431.34) Percentile intervals (B.1.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Acute Consumers only are individuals with reported fish consumption at least once during the three day reporting period. Source: U.S. EPA 1996a.

Table 10-22. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for Consumers Only by Age and Gender -As Consumed (Marine) Sample Age Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) Females 14 or under 315 69.04 114.23 162.37 336.59 15-44 774 76.53 149.78 178.74 271.06 45 or older 715 85.24 167.11 218.35 264.8 All ages 1804 78.47 (7 4.43-82.51) 155.38 (147.00-166.64) 195.15 (179.12-212.07) 279.79 (263.48-336.17) Males 14 or under 348 78.44. 160.97 190.68 336.98 15 -44 565 104.57 191.29 227.56 316.69 45 or older 467 101.46 188.77 259.85 333.18 All ages 1380 98.59 (93.16-104.03) 184.53 (173.46-194.13) 224.89 (210.00-250.28) 328.18 (310.42-348.49) Both Sexes 14 or under 663 73.62 153.2 176.9 337.24 15 -44 1339 89.93 171.88 209.17 308.06 45 or older 1182 92.19 178.33 223.82 314.44 All acies 3184 87.77 (83.74-91.80) 169.39 (167.00-173.65) 209.50 (198.11-221.73) 320.41 (292.80-341.88) Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Acute Consumers only are individuals with reported fish consumption at least once during the three day reporting period. Source: U.S. EPA 1996a. Table 10-23. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for Consumers Only by Age and Gender -As Consumed (All Fish) Age Sample Size Mean (90% C. I.) 90th % (90% B.I.) 95th % (90% B. I.) 99th % (90% B.I.) Females 14 or under 378 69.54 126.22 165.27 338.04 15-44 952 88.8 170.01 212.56 361.04 45 or older 879 96.47 184.42 226.25 310.12 All ages 2209 88.47 (83.98-92.97) 170.10 (166.63-173.88) 220.56 (201.97"236.00) 340. 71 (289.17-368.51) Males 14 or under 429 79.72 161.62 190 308.59 15-44 702 124.78 230.77 296.66 397.7 45 or older 587 119.44 224.82 262.43 434.28 All ages 1718 114.18 (108.79-119.56) 219.96 (209.17-229.91) 272.49 (254.99-301.51) 411.68 (371.43-447.85) Both Sexes 14 or under 807 74.8 153.7 178.08 337.46 15-44 1654 106.06 203.33 271.66 372.77 45 or older 1466 106.62 209.34 254.69 407.14 All aaes 3927 100.63 (96.66-104.60) 197.44 (188.74-205.12) 253.38 (231.51-264.45) 371.59 (359.29-401.61) Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Acute Consumers only are individuals with reported fish consumption at least once during the three day reporting period. Source: U.S. EPA 1996a. Table 10-24. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for Consumers Only Aged 18 Years and Older by Habitat -As Consumed 90% Interval Habitat Statistic Estimate Lower Bound Uoper Bound Fresh/Estuarine Mean 70.91 64.16 77.65 n = 1,541 5oth % 42.45 37.24 46.91 N = 37,166,000 90th % 176.58 165.08 193.26 95th% 230.41 224.00 255.55 99th % 402.56 358.58 518.41 Marine Mean 91.49 87.35 95.64 n = 2,432 5oth % 77.56 74.89 78.52 N = 57,830,000 9oth % 172.29 168.00 182.00 95th % 215.62 201.99 225.63 99th % 313.05 292.80 324.81 All Fish Mean 106.39 102.37 110.41 n = 3,007 50th % 85.36 84.00 87.36 N = 70,949,000 90th % 206.76 197.84 213.00 95th % 258.22 241.00 266.86 99th % 399.26 336.50 423.56 Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Note: Consumers only are individuals who consumed fish at least once during the 3-day reporting period; n =sample size; N = population size. Estimates are projected from a sample of consumers only 18 years of age and older to the population of consumers only 18 years of age and older using 3-year combined survey weights. The population for this survey consisted of individuals in the 48 conterminous states. Source: U.S. EPA 1996a. Table 10-25. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for Consumers Only by Age and Gender -As Consumed (Freshwater and Estuarine) Age Sample Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) Females 0 0 0 0 0 14 or under 138 1639.20 3915.56 6271.09 10113.24 15 -44 445 961.58 2578.81 3403.75 6167.24 45 or older 453 927.85 2229.97 2894.18 4338.36 All ages 1036 1037.29 (905.50-1169.09) 2582.5 (2248.8-2734.5) 3434.16 (2927.72-3979.82) 6923.5 (4757.8-9134.9) Males 0 0 0 0 0 14 or under 157 1798.24 3759.29 3952.99 7907.38 15-44 356 1004.96 2744.61 3348.86 4569.62 45 or older 343 992.11 2448.54 3281.38 5716.41 All ages 856 1117.74 (1011.5_5-1223.94) 2789.95 (2526.87-3132.65) 3399.26 (3256.87-3907.77) 5259.97 (4834.34-6593.97) Both Sexes 0 0 0 0 0 14 or under 295 1721_.99 3760.67 4208.18 9789.49 15 -44 801 983.19 2616.63 3360.85 5089.78 45 or older 796 958.20 2394.21 3121.09 5157.95 All ages 1892 1076.80 (980.00-1173.61) 2695.81 (2546.77-2819.33) 3399.46 (3132.65-3839.47) 6526.10 (5270.61-6931.61) Percentile intervals (B.1.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Consumers only are individuals with reported fish consumption at least once during the three day reporting period. Source: U.S. EPA 1996a. Table 10-26. Per Capita Distribution of. Fish (Finfish and Shellfish) Intake *(mg/kg-day) for Consumers Only by Age and Gender -As Consumed (Marine) Sample Age Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) Females 14 or under 315 2591.57 5074.80 6504.67 9970.44 15 -44 774 1227.41 2469.67 3007.98 4800.68 45 or older 715 1293.99 2642.60 3565.34 4237.73 All ages 1804 1486.90 (1400.58-1573.23) 2992.38 (2841.13-3303.96) 3961.24 (3768.48-4192.13) 6521.73 (5792.54-7794.41) Males 14 or under 348 2471.15 4852.33 5860.72 8495.57 15-44 565 1302.62 2390.20 2882.91 3887.23 45 or older 467 1242.49 2251.43 2877.73 4016.80 All ages 1380 1505.19 (1411.84-1598.55) 2899.23 (2797.30-3199.05) 3836.02 (3563.32-4581.61) 5859.85 (5247.79-7895.62) Both Sexes 14 or under 663 2532.95 5068.69 6376.47 8749.02 15 -44 1339 1263.35 2464.80 2961.92 4251.47 45 or older 1182 1271.92 2461.37 3383.46 4220.78 All aQes 3184 1495.37 (1422.63-1568.12) 2956.38 (2838.46-3083.70) 3887.52 (3770.65-4113.22) 6510.73 (5772.57-6852.01) Percentile intervals (B.1.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Consumers only are individuals with reported fish consumption at least once during the three day reporting period. Source: U.S. EPA 1996a. Table 10-27. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for Consumer Only by Age and Gender -As Consumed (All Fish) Sample Aae Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) Females 14 or under 378 2683.51 5299.68 7160.73 12473.65 15 -44 952 1414.54 2726.46 3740.83 6703.25 45 or older 879 1449.43 2838.76 3736.61 . 4693.94 All ages 2209 1637.08 (1546.08-1728.08) 3122.82 (2992.63-3308.93) 4312.16 (3969.22-4710.75) 7163.38 (6852.67-7794.41) Males 14 or under 429 2568.93 4714.97 5818.08 9350.89 15 -44 702 1545.93 2854.49 3773.51 5254.04 45 or older 587 1451.06 2841.35 3366.84 5091.31 All ages 1718 1715.79 (1636.68-1794.90) 3399.26 (3290.97-3766.18) 4244.32"(4015.03-4581.61) 6818.35 (5792.54-7588.15) Both Sexes 14 or under 807 2624.35 5020.14 6904.83 10384.82 15-44 1654 1477.57 2798.37 3747.88 5386.43 45 or older 1466 1450.15 2839.04 3515.81 4922.99 All aaes 3927 1674.31 {1606.79-1741.83) 3299.54 {3133.69-3462.35) 4258.69 (4065.32-4483.83) 7126.90 {6644.11-7794.41) Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Consumers only are individuals with reported fish consumption at least once during the three day reporting period. Source: U.S. EPA 1996a. Table 10-28. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for Consumers Onlv Aged 18 Years and Older bv Habitat-As Consumed Milligrams/kilogram/person/day 90% Interval Habitat Statistic Estimate Lower Bound Upper Bound Fresh/Estuarine Mean 959.15 867.58 1,050.72 n=1,541 50th % 601.88 532.31 656.86 N = 37,166,000 90th % 2,442.97 2,233.16 2,606.66 95th % 3,116.28 2,839.90 3,303.96 99th % 5, 151.98 4,432.30 6,931.61 Marine Mean 1,270.78 1,214.65 1,326.90 n = 2,432 50th % 1,062.93 1,019.60 1,087.06 N = 57,830,000 90th % 2,467.68 2,331.88 2,585.09 95th% 3,116.74 2,906.16 3,264.98 99th% 4,250.22 4,037.74 4,387.96 All Fish Mean 1,461.71 1,406.34 1,517.09 n = 3,007 50th % 1,189.29 1,156.77 1,225.43 N = 70,949,000 90th % 2,802.28 2,685.81 2,868.73 95th % 3,588.11 3,308.93 3,798.54 99th % 5,355.90 5,095.58 5,766.99 Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Note: Consumers only are individuals who consumed fish at least once during the 3-day reporting period; n = sample size; N = population size Estimates are projected from a sample of consumers only 18 years of age and older to the population of consumers only 18 years of age and older using 3-year combined survey weights. The population for this survey consisted of individuals in the 48 conterminous states. Source: U.S. EPA 1996a. Table 10-29. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the U.S. Population by Age and Gender -Uncooked Fish Weight (Freshwater and Estuarine) Age Samole Size Mean (90% C.I.) 90th % (90% 8.1.) 95th % (90% 8.1.) 99th % (90% 8.1.) Females 14 or under 1431 1.99 (1.34-2.64) 1.81 (0.00-4.63) 15.88 (7.89-18.38) 46.82 (36.72-54.55) 15 -44 2891 5.50 (4.53-6.48) 13.62 (9.99-18.11) 36.68 (32.53-40.31) 94.93 (75.74-114.34) 45 or older 2340 6.65 (5.30-8.00) 24.18 (18.11-27.41) 46.91 (37.94-52.92) 108.90 (92.06-123.72) All ages 6662 5.13 (4.37-5.88) 13.31 (10.48-16.67) 35.63 (28.92-40.07) 94.61 (77. 70-109.09) Males 14 or under 1546 2.69 (1.62-3.76) 1.07 (0.33-8.67) 18.47 (14.39-25.91). 57.07 (47.32-65.37) 15 -44 2151 7.87 (6.46-9.29) 22.10 (13.43-31.80) 63.26 (50.62-70.12) 126.61 (108.54-162.80) 45 or older 1553 8.87 (7.32-10.43) 28. 7 4 (24.23-33.07) 61.15 (52.57-71.59) 125.90 (112.28-147.62) All ages. 5250 6.91 (6.07-7.75) 19.00 (14.99-23.69) 51.43 (47.32-54.82) 112.11 (108.54-127.19) Both Sexes 14 or under 2977 2.35 (1.70-3.00) 1. 72 (0.00-5.00) 17.46 (12.78-18.68) 50.14 ( 43.58-55.00) 15 -44 5042 6.64 (5.71-7.56) 18.30 (14.99-21.14) 47.31 (36.22-59.65) 109.66 (94.43-127.19) 45 or older 3893 7 .66 (6.50-8.81) 26.11 (21.95-28.85) 52.92 (45.73-61.51) 113.10 (107.18-133.74) All ages 11912 5.98(5.29-6.67) 15.89(14.39-17.76) 40.03(37.94-44. 75) 107 .63(98.25-109.09) Percentile intervals (8.1.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Source: U.S. EPA 1996a. Table 10-30. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the U.S. Population by Age and Gender -Uncooked Fish Weight (Marine) Age Samole Size Mean (90% C.U 90th % (90% 8.1.) 95th % (90% 8.1.) 99th % (90% 8.1.) Females 14 or under 1431 8.61 (6.67-10.56) 31.23 (26.85-37.29) 49.75 (41.46-57.49) 104.26 (83.35-140.07) 15 -44 2891 12.84 (11.51-14.18) 46.66 (38.35-54.30) 72.16 (63.12-77.18) 133.69 (121.33-142.82) 45 or older 2340 16.26(14.68-17.84) 56.01 (50.00-61.97) 84.71 (75.05-93.29) 131.43 (112.07-156.01) All ages 6662 13.05 (11.97-14.12) 46.70 (44.49-49.72) 72.22 (65.55-75.47) 130.73 (121.33-137.18) Males 14 or under 1546 9.40 (7.36-11.45) 31.32 (25.20-44.12) 65.37 (54.60-73.39) 118.42 (82.34-176.52) 15 -44 2151 17.11 (15.31-18.90) 66.06 (62.21-73.20) 93.32 (81.26-106.67) 155.16 (136.77-181.18) 45 or older 1553 17.22 (15.19-19.25) 62.64 (59.39-68.44) 84.96 (79.93-99.44) 146.78 (142.58-185.44)

All ages* 5250 15.27 (13.86-16.68) 61.12 (56.59-63.09) 81.89 (77.91-87.16) 147.09 (134.55-174.31) Both Sexes 14 or under 2977 9.02 (7.28-10.75) 31.52 (30.19-35.75) 56.35 (50.22-62.25) 117.75 (91.82-140.07) 15 -44 5042 14.88 (13.57-16.19) 55.99 (53.04-61.33) 80.70 (75.19-87.16) 138.23 (128.40-157.23) 45 or older 3893 16.69 (15.34-18.04) 59.12 (52.84-64.53) 84.92 (76.67-93.32) 142.92 (134.55-155.13) All ages 11912 14.'11 (13.07-15.14) 52.10(47.83-55.93) 76.51(74.58-80.89) 138.22(132.98-155.13) Percentile intervals (8.1.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Source: U.S. EPA 1996a.

Table 10-31. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the U.S. Population by Age and Gender -Uncooked Fish Weight (All Fish) Aae Sample Size Mean (90% C.I.) 9oth % (90% B.I.) 95th % (90% B.l.l 99th % (90% B.1.l Females 14 or under 1431 10.60 (8.40-12.81) 41.10 (35.80-47 .57) 56.16 (49.78-65.55) 130.78 (83.35-160.66) 15-44 2891 18.35 (16.67-20.02) 62.21 (54.47-73.56) 93.13 (82.29-108.03) 155.75 (137.18-174.31) 45 or older 2340 22.91 (20.78-25.04) 74.56 (65.37-79.67) 107.66 (97.64-111.71) 159.97 (157.17-173.74) All ages 6662 18.17 (16.82-19.53) 61.08 (56.94-63.12) 92.03 (86.94-96.11) 157.08 (147.34-168.83) Males 14 or under 1546 12.09 (9.70-14.49) 45.59 (34.69-53.11) 68.18 (64.28-79.90) 127.20 (87.29-176.52) 15 -44 2151 24.98 (22.79-27.17) 87 .15 (80.89-94.63) 122.29 (111.05-124.83) 197.15 (179.86-198.87) 45 or older 1553 26.09 (23.52-28.67) 81.76 (76.67-88.03) 112.33 (109.65-130.36) 211.20 (190.74-223.72) All ages 5250 22.18 (20.52-23.83) 76.13 (74.22-79.92) 110.88 (10_8.54-118.56) 180.90 (174.39-198.87) Both Sexes 14 or under 2977 11.36 (9.49-13.24) 43.00 (34.69-47.32) 65.34 (56.28-68.51) 130.41 (107.12-160.66) 15 -44 5042 21.51 (19.97-23.06) 75.15 (73.56-79.71) 109.57 (106.72-117.47) 175.73 (162.80-198.63) 45 or older 3893 24.35 (22.46-26.24) 77.57 (72.07-84.02) 110.13 (100.42-119.87) 18.0.74 (164.76-210.75) All ages 11912 20.08(18.82-21.35) 70.11 (65.37-74.20) 102.01 (99.26-106.67) 173.18 (162.80-176.52) Percentile intervals (B.1.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Source: U;S. EPA 1996a. Table 10-32. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the U.S. Population AQed 18 Years and Older by Habitat-Uncooked Fish Weight 90% Interval Habitat Statistic Estimate Lower Bound Uooer Bound Fresh/Estuarine Mean 7.09 6.22 7.96 5oth % 0.00 0.00 0.00 9oth % 21.72 18.52 25.82 95th % 49.89 47.32 54.67 99th % 111.13 107.18 116.38 Marine Mean. . 16.01 14.89 17.12 5oth % 0.00 0.00 0.00 9oth % 59.35 56.59 61.49 95th % 82.95 80.37 88.36 99th % 142.78 131.02 156.89 All Fish Mean 23.10 21.62 24.58 50th % 0.00 0.00 0.00 90th % 76.84 74.37 80.13 95th % 110.28 106.67 115.32 99th % 177.44 171.73 198.63 Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications. NOTE: Estimates are projected from a sample of 8,478 individuals of age 18 and older to the U.S. population of 177,807,000 individuals of age 18 and older using 3-year combined survey weights. Source: U.S. EPA 1996a. Table 10-33. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the U.S. Population by Age and Gender -Uncooked Fish Weight (Freshwater and Estuarine) Sample Age Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) Females 14 or under 1431 84.78 (58.06-111.50) 70.75 (0.00-143.13) 599.06 (266.71-722.58) 1713.06 (1511.78-2313.50) 15 -44 2891 85.15 (70.68-99.62) 202.83 (153.48-259.97) 584.79 (538.05-631.86) 1411.42 (1236.72-1659.15) 45 or older 2340 98.97 (79.89-118.04) 333.38 (269.96-379.98) 733.74 (606.36-820.68) 1561.40 (1331.46-1667.88) All.ages 6662 89.54 (76.51-102.58) 225.51 (176.38-280.11) 625.30 (552.99-713.85) 1558.08 (1394.99-1659.15) Males 14 or under 1546 91.62 (55.18-128.05) 38.98 (12.26-281.50) 868.97 ( 485.33-1063.50) 1642.60 (1599.78-1693.88) 15-44 2151 96.91 (78.91-114.90) 281.17 (165.37-387.46) 740.91 (546.79-850.52) 1589.97 (1353.43-1992.23) 45 or older 1553 107.87 (88.47-127.28) 361.99 (304.96-455.29) 702.35 (628.25-810.62) 1612.49 (1344.07-1848.39) All ages 5250 98.86 (87.19-110.52) 292.58 (217.42-342.11) 755.53 (677.47-790.85) 1596.61 (1538.89-1711.41) Both Sexes 14 or under 2977 88.26 (66.69-109.83) 66.00 (0.00-143.13) 717.37 (485.60-880.64) 1688.55 (1511.78-1824.44) 15-44 5042 90.77 (78.37-103.16) 250.26 (194.04-289.19) 631.31 (538.05-773.91) 1529.94 (1352.50-1659.15) 45 or older 3893 103.00 (87 .86-118.15) 345.69 (291.80-423.39) 719.81 (637.94-790.85) 1590.13 (1373.97-1668.93) All aqes 11912 93.99 (83.41-104.57) 251.82 (222.54-282.58) 677.66 (631.86-729.11) 1593.28 (1511.78-1659.15) Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Source: U,S. EPA 1996a. Table 10-34. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the U.S. Population by Age and Gender -Uncooked Fish Weight (Marine) Age Sample Mean (90% C.1.) 90th % (90% B.1.) 95th % (90% B.I.) 99th % (90% B.I.) Size Females 14 or under 1431 333.99 (267.25-400.72) 1132.99 (864.83-1407.24) 1959.91 (1780.61-2347 .02) 3776.60 (3173.86-5736.90) 15 -44 2891 206.03 (183.95-228.11) 762.54 (617.86-857.55) 1137.58 {1036.38-1211.86) 2174.21 (2014.41-2393.16) 45 or older 2340 246.73 (221.45-272.00) 829.52 (777.87-944.26) 1236.00 (1174.14-1413.34) 2161.65 (1952.51-2303.80) All ages 6662 246.47 (223.28-269.66) 847.60 (811.19-893.29) 1305.49 (1215.53-1385.66) 2615.85 (2365.65-2857 .62) Males 14 or under 1546 296.99 (241.85-352.13) 1089.46 (1003.46-1256.97) 1907.65 (1685.30-2186.58) 3723.81 (3274.93-4574.13) 15-44 2151 212.88 (190.31-235.44) 800.79 (741.29-859.61) 1191.75 (1096.61-1245.94) 1890.42 (1685.30-1969.63) 45 or older 1553 212.15 (187.25-237.04) 792.86 (747.56-890.31) 1100.20 (1039.02-1210.66) 1842.38 (1749.67-2219.32) All ages 5250 233.07 (209.65-256.49) 859.01 (798.27-907.76) 1255.35 (1204.46-1382.05) 2520.94 (2263.58-2733.15) Both Sexes 14 or under 2977 315.12 (260.95-369.29) .1123.28 (993.12-1371.24) 1909.37 (1785.09-2062.64) 3820.21 (3370.59-457 4.13) 15 -44 5042 209.30 (190.68-227.92) 780.16 (722.86-843.41) 1174.69 (1104.42-1215.53) 2019.59"(1918.45-2237.22) 45 or older 3893 231.06 (212.18-249.95) 813.12 (747.56-907.76) 1193.22 (1076.85-1333.72) 2029.16 (1863.17-2219.32) All aaes 11912 240.07 (220.14-260.01) 855.63 (809.67-909.76\ 1271.54 (1227.16-1371.24\ 2575.29 (2393.16-2708.59) Percentile intervals (B.1.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Source: U.S. EPA 1996a. Table 10-35. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the U.S. Population by Age and Gender -Uncooked Fish Weight (All Fish) Sample Aqe Size Mean (90% C.I.) 9oth % (90% 8.1.) 95th % (90% 8.1.) 99th % (90% 8.1.) Females 14 or under 1431 418.76 (339.58-497.95) 1389.10 (1150.77-1785.09) 2341.90 (2062.64-2860.52) 4985.96 (3971.54-5736.90) 15-44 2891 291.18 (263.86-318.50) 993.92 (854.63-1127.32) 1436.00 (1234.66-1631.25) 2726.50 (2406.11-3044.81) 45 or older 2340 345.69 (312.49-378.90) 1122.26 (1050.15-1230.68) 1669.72 (1556.83-1784.37) 2684.71 (2303.80-3064.38) All ages 6662 336.01 (307.83-364.20) 1120.91 (1054.05-1172.38) 1720.84 (1642.63-1855.69) 3093.76 (2973.66-3265.54) Males 14 or under 1546 388.61 (320.66-456.56) 1476.31 (1371.24-1632.55) 2038.58 (1909.00-2631.42) 4294.12 (3556.31-4574.13) 15 -44 2151 309.78 (281.55-338.02) 1096.57 (1044.57-1194.06) 1566.39 (1410.20-1609.35) 2275.15 (2047.18-2465.77) 45 or older 1553 320.02 (287.79-352.25) 1013.05 (955.37-1096.43) 1459.73 (1340.97-1601.79) 2392.05 (2233.16-2806.51) All ages 5250 331.93 (306.46-357.40) 1126.66 (1081.06-1225.66) 1621.80 (1599.78-1696.20) 3031.31 (2806.51-3274.93) Both Sexes 14 or under 2977 403.38 (343.65-463.12) 1442.72 (1279.82-1672.75) 2191.90 (2021.16-2536.75) 4425.27 (4000.27-4669.59) 15-44 5042 300.06 (277.94-322.19) 1040.98 (1003.55-1097.08) 1514.82 (1421.34-1572.40) 2481.23 (2383.54-2773.15) 45 or older 3893 334.07 (307.87-360.26) 1069.14 (978.95-1140.98) 1579.43 (1373.97-1696.20) 2653.45 (2292.45-2806.51) All ages 11912 334.06 (311.25-356.88) 1123.14 (1090.76-1178.95) 1684.23 (1620.48-1718.51) 3092.77 (2973.66-3250.20) Percentile intervals (8.1.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Source: U.S. EPA 1996a. Table 10-36. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the U.S. Population Aged 18 Years and Older by Habitat -Uncooked Fish Weight 90% Interval Habitat Statistic Estimate Lower Bound Upper Bound Fresh/Estuarine Mean 95.99 84.30 107.69 5oth % 0.00 0.00 0.00 9oth % 306.74 259.97 334.58 95th % 677.39 626.01 734.34 99th % 1,547.81 1,411.56 1,599.78 Marine Mean 222.86 207.34 238.37 50th % 0.00 0.00 0_.00 9oth % 810.43 778.50 859.61 95th % 1, 190.45 1,145.61 1,219.60 99th % 2,033.92 1,870:09 2,263.58 All Fish Mean 318.85 298.20 339.49 50th% 0.00 0.00 0.00 90th% 1,061.14 1,016.87 1,105.01 95th% 1,548.77 1,464.72 1,609.14 99th% 2,559.07 2,444.24 2,764.50 Percentile intervals were estimated using the percentile bootstrap method with 1,000 bootstrap replications. NOTE: Estimates are projected from a sample of 8,478 individuals of age 18 and older to the population of 177,807,000 individuals of age 18 and older using 3-year combined survey weights. Source: U.S. EPA 1996a. Table 10-37. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for Consumers Only by Age and Gender -Uncooked Fish Weight (Freshwater and Estuarine) Age Sample Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) Females ' 14 or under 138 48.3 117.27 161.44 230.63 15-44 445 78.56 191.95 242.76 472.21 45 or older 453 78.77 192.32 258.56 368.84 All ages 1036 74.67 (65.46-83.88) 181.08 (171.19-197.59) 239.59 (220.69-284.70) 409.00 (345.96-671.54) Males 14 or under 157 64.91 141.35 193.79 287.28 15 -44 356 104.86 269.96 343.66 494.38 45 or older 343 102.56 234.28 326.96 539.77 All ages 856 98.12 (88.60-107.64) 246.93 (212.93-283.90) 324.53 (283.28-381.58) 499.19 (488.41-532.32) Both Sexes 14 or under 295 56.95 134.89 166.32 262.87 15 -44 801 91.66 237.27 322.06 494.64 45 or older 796 90 220.76 295.41 523.94 All ages 1892 86.19 (78.41-93.97) 217.92 (205.28-237.27) 290.04 (267 .10-325.61) 489.29 (424.87-534.20) Percentile intervals (B.1.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Consumers only are individuals reported fish consumption at least once during the three day reporting period. Source: U.S. EPA 1996a. Table 10-38. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for Consumers Only by Age and Gender -Uncooked Fish Weight (Marine) Age Sample Size Mean (90% C.I. l 90th % (90% 8.1.) 95th % (90% B.l.l 99th % (90% B.l.l Females 14 or under 315 89.92 169.23 198.62 432.51 15-44 774 98.53 194.59 231.22 317.42 45 or older 715 110 214.73 279.67 345.37 All ages 1804 101.30 (95.90-106.69) 195.37 (186.67-213.33) 252.43 (231.53-278.16). 372.17 (314.67-428.00) Males 14 or under 348 101.5 205.49 242.28 408.68 15 -44 565 133.86 244.46 297.67 393.14 45 or older 467 131.2 243.33 327.14 428.72 All ages 1380 126.85 (119.75-133.94) 238.64 (225.57-247.01) 296.68 (279.95-316.81) 425.98 (403.66-481.95) Both Sexes 14 or under 663 95.56 189.32 231.72 442.87 15-44 1339 115.41 223.99 263.76 383.16 45 or older 1182 119.08 226.55 288.16 418.23 All aQes 3184 113.11 (107.79-118.43) 222.67 (216.50-225.56) 271.70 (260.62-279.95) 415.88 (367.26-440.45' Percentile intervals (B.1.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Consumers only are individuals with reported fish consumption at least once during the three day reporting period. Source: U.S. EPA 1996a. Table 10-39. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for Consumers Only by Age and Gender -Uncooked Fish Weight (All Fish) Age Sample Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) Females 14 or under 378 89.73 163.47 204.14 476.56 15 -44 952 114.04 220.63 277.69 461.54 45 or older 879 123.61 236.3 298.66 397.43 All ages 2209 113.58 (107.69-119.47) 220.44 (206.27-226.80) 287.08 (257.09-312.42) 448.57 (393.68-531.63) Males 14 or under 429 102.01 205.25 244.46 386.47 15 -44 702 160.06 305.61 379.38 495.51 45 or older 587 152.52 292:95 350.26 555.11 All ages 1718 146.18 (138.99-153.38) 283.46 (261.72-297.95) 350.99 (328.70-382.33) 520.51 (488.41-591.47) Both Sexes 14 or under 807 96.07 195.35 232.85 466.09 15 -44 1654 136.12 262.15 343.86 488.9 45 or older 1466 136.38 263.95 326.94 510.25 All aQes 3927 129.00 (123.74-134.27) 249.09 (240.99-264.10) 326.00 (306.02-335.58) 497 .54 ( 469.23-519.67) Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Consumers only are individuals reported fish consumption at least once during the three day reporting period. Source: U.S. EPA 1996a. Table 10-40. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for Consumers Only Aged 18 Years and Older bv Habitat-Uncooked Fish Weight 90% Interval Habitat Statistic Estimate Lower Bound Upper Bound Fresh/Estuarine Mean 89.88 81.41 98.35 n = 1,541 50th % 53.64 46.44 57.81 N = 37,166,000 90th % 223.11 206.58 237.27 95th % 296.89 283.90 325.61 99th % 502.93 448.23 654.55 Marine Mean 117.83 112.47 123.20 n = 2,432 50th % 98.79 95.69 100.76 N = 57,830,000 90th % 225.51 / 222.67 234.00 95th % 279.50 261.47 289.44 99th % 403.48 369.10 427.73 All Fish Mean 136.33 131.11 141.55 n = 3,007 50th % 111.50 108.53 112.00 N = 70,949,000 90th % 262.03 253.24 272.71 95th % 328.66 323.61 340.52 99th % 506.02 435.44 531.63 Percentile intervals (8.1.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Note: Consumers only are individuals who consumed fish at least once during the 3-day reporting period; n = sample size; and N = population size. Estimates are projected from a sample of consumers only 18 years of age and older to the population of consumers only 18 years of age and older using 3-year combined survey weights. The population for this survey consisted of individuals in the 48 conterminous states. Source: U.S. EPA 1996a. Table 10-41. Per Capita Distribution ofFish (Finfish and Shellfish) Intake (mg/kg-day) for Consumers Only by Age and Gender -Uncooked Fish Weight (Freshwater and Estuarine) Age Sample* Mean (90% C.1.) 90th % (90% B.1.) 95th % (90% B.1.) 99th % (90% B.1.) Size Females 14 or under 138 2070.41 4450.54 6915.31 13269.61 15-44 445 1229.97 3045.41 4191.25 7711.43 45 or older 453 1171.17 2886.48 3519.87 5577.34 All ages 1036 1317.18 (1150.10-1484.26) 3250.31 (2988.81-3491.38) 4240.89 (3710.16-5025.02) 8912.52 (6385.55-11533.98) Males 14 or under 157 2229.31 4638.34 5071.41 9622.15 15-44 356 1294.27 3318.89 4275.83 5974.96 45 or older 343 1235.55 2898.00 4097.24 7217.68 All ages 856 1411.35 (1278.61-1544.08) 3579.06 (3225.84-4060.30) 4615.66 (4121.91-5081.65) 6594.61 (5980.19-7944.55) Both Sexes 14 or under 295 2153.11 4634.82 5756.93 12388.27 15-44 801 1261.99 3276.06 4246.63 6625.15 45 or older 796 1201.57 2892.52 . 3981.84 6378.11 All aqes 1892 1363.4411242.24-1484.65) 3325.14 (3232.58-3676.99) 4408.18 (4085.55-4781.34) 7957.50 (6979.20-8920.99) Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Consumers only are individuals with reported fish consumption at least once during the three day reporting period. Source: U.S. EPA 1996a. Table 10-42. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for Consumers Only by Age and Gender -Uncooked Fish Weight (Marine) Age Sample Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.) 99th % (90% B.I.) Females 0 0 0 0 0 14 or under 315 3359.10 6058.97 8573.62 13050.09 15-44 774 1582.77 3129.41 3854.14 5961.80 45 or older 715 1669.73 3429.24 4397.07 5476.02 All ages 1804 1920.77 (1804.28-2037.26) 3793.20 (3618.55-4328.00) 5083.63 (4953.40-5552.65) 8576.60 (7527.83-9743.01) Males 0 0 0 0 0 14 or under 348 3180.45 6434.20 8089.26 10764.01 15 -44 565 1666.42 3102.24 3651.10 4998.14 45 or older 467 1604.71 2931.17 3725.63 5373.82 All ages 1380 1934.12 (1812.97-2055.28) 3736.16 (3548.08-4072.42) 4884.60 (4454.15-5710.83) 8066.96 (6852.67-9869.52) Both Sexes 0 0 0 0 0 14 or under 663 3272.13 6278.74 8424.77 11838.54 15-44 1339 1622.75 3120.60 3682.17 5517.95 45 or older 1182 1641.87 3320.87 4328.34 5406.76 Allacies 3184 1926.95 (1829.50-2024.39) 3752.89 (3631.98-4001.16) 5018.74 (4852.08-5267.31) 8448.28 (7215.72-9136.89) Percentile intervals (B.1.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Consumers only are individuals with reported fish consumption at least once during the three day reporting period. Source: U.S. EPA 1996a. Table 10-43. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for Consumer Only by Age and Gender -Uncooked Fish Weight (All Fish) Age Sample Mean (90% C.1.) goth % (90% B.1.) 95th % (90% B.I.) 99th % {90% B.1.) Size Females 14 or under 378 3448.73 7100.43 9012.18 15381.13 15-44 952 1818.32 3506.20 4661.96 8789.33 45 or older 879 1857.64 3520.90 4740.11 6561.13 All ages 2209* 2102.20 (1982.89-2221.51) 4092.51 (3842.15-4282.08) 5545.07 (5080.72-6007.28) 9630.23 (8166.44-9796.61) Males 14 or under 429 3273.63 5734.46 7570.83 11891.85 15 -44 702 1983.16 3720.05 4769.44 6121.56 45 or older 587 1850.69 3534.61 4311.83 6374.34 All ages 1718 2193.24 (2089.20-2297.28) 4385.06 (4121.91-4776.34) 5351.38 (5055.10-5727.01) 8596.82 (7816.70-10199.24) Both Sexes 14 or under 807 3358.33 6333.46 8611.73 12406.35 15 -44 1654 1897.40 3674.88 4709.78 7276.18 45 or older 1466 1854.57 3522.43 4615.22 6440.17 All aQes 3927 2145.26 (2055.92-2234.61) 4223.91 (4085.76-4454.15) 5477.86 (5163.33-5686.04) 9171.52 (8605.35-9796.61) Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Consumers only are individuals with reported fish consumption at least once during the three day reporting period. Source: U.S. EPA 1996a. Table 10-44. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for Consumers Only AQed 18 Years and Older by Habitat -Uncooked Fish WeiQht 90% Interval Habitat Statistic Estimate Lower Bound Upper Bound Fresh/Estuarine Mean 1,216.82 1,101.74 1,331.90 n = 1,541 50th% 740.93 639.11 822.65 N = 37,166,000 90th % 3,050.95 2,931.26 3,270.80 95th % 4,025.44 3,639.76 4,121.91 99th % 6,638.62 6,007.28 8,920.99 Marine Mean 1,637.10 1,564.27 1,709.92 n = 2,432 50th% 1,370.42 1,302.29 1,422.69 N = 57,830,000 90th % 3,169.02 3,006.55 3,328.98 95th % 3,926.74 3,632.70 4,156.98 99th % 5,452.75 5,353.12 5,596.31 All Fish Mean 1,873.84 1,801.93 1,945.75 n = 3,007 50th % 1,515.91 1,477.99 1,570.40 N = 70,949,000 90th % 3,599.04 3,443.64 3,676.99 95th % 4,665.15 4,264.03 4,812.97 99th % 7,022.47 6,459.64 7,294.80 Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications. Note: Consumers only are individuals who consumed fish at least once during the 3-day reporting period; n = sample size; and N = population size. Estimates are projected from a sample of consumers only 18 years of age and older to the population of consumers only 18 years of age and older using 3cyear combined survey weights. The population for this survey consisted of individuals in the 48 conterminous states. Source: U.S. EPA 1996a. Table 10-45. Distribution of Quantity of Fish Consumed (in grams) Per Eating Occasion, by Age and Sex Percentiles Aoe !vearsl-Sex Graue Mean SD 5th 25th 50th. 75th 90th 95th 99th 1-2 Male-Female 52 38 8 28 43 58 112 125 168 3-5 Male-Female 70 51 12 36 57 85 113 170 240 6-8 Male-Female 81 58 19 40 72 112 160 170 288 9-14 Male 101 78 28 56 84 113 170 255 425 9-14 Female 86 62 19 45 79 112 168 206 288 15-18Male 117 115 20 57 85 142 200 252 454 15-18 Female 111 102 24 56 85 130 225 270 568 19-34 Male 149 125 28 64 113 196 284 362 643 19-34 Female 104 74 20 57 85 135 184 227 394 35-64 Male 147 116 28 80 113 180 258 360 577 35-64 Female 119 98 20 57 85 152 227 280 480 65-74 Male 145 109 35 75 113 180 270 392 480 65-74 Female 123 87 24 61 103 168 227 304 448 75+ Male 124 68 36 80 106 170 227 227 336 75+ Female 112 69 20 61 112 151 196 225 360 Overall 117 98 20 57 85 152 227 284 456 Source: Pao et al. 1982. Table 10-46. Mean Fish Intake in a Day, by Sex and Age' Sex Per capita intake Percent of population Mean intake (g/day) for Age (year) (g/day) consuming fish in 1 day consumers onlY' Males or Females 5 and under 4 6.0 67 Males 6-11 3 3.7 79 12-19 3 2.2 136 20 and over 15 10.9 138 Females 6-11 7 7.1 99 12-19 9 9.0 100 20 and over 12 10.9 110 All individuals 11 9.4 117 ' Based on USDA Nationwide Food Consumption Survey 1987-88 data for one day. b Intake for users only was calculated by dividing the per capita consumption rate by the fraction of the population consuming fish in one day . . Source: USDA, 1992b. Table 10-47. Percent of Respondents That Resoonded Yes, No, or Don't Know to Eatina Seafood in 1 Month (includina shellfish, eels, or sauidl Response Population Group Total N No Yes DK N % N % N % Overall 4663 1811 38.8 2780 59.6 72 1.5 Gender . 2 1 50.0 1 50.0 . . Male 2163 821 38.0 1311 60.6 31 1.4 Female 2498 989 39.6 1468 58.8 41 1.6 (years) 84 25 29.8 42 50.0 17 20.2 1-4 263 160 60.8 102 38.8 1 0.4 5-11 348 177 50.9 166 47.7 5 1.4 12-17 326 179 54.9 137 42.0 10 3.1 18-64 2972 997 33.5 1946 65.5 29 1.0 >64 670 273 40.7 387 57.8 10 1.5 Race . 60 20 33.3 22 36.7 18 30.0 White 3774 1475 39.1 2249 59.6 50 1.3 Black 463 156 33.7 304 65.7 3 0.6 Asian 77 21 27.3 56 72.7 . . I Some Others 96 39 40.6 56 58.3 1 1.0 Hispanic 193 100 51.8 93 48.2 . . Hispanic 46 10 21.7 412 43.0 28 41.3 No 4243 1625 31.2 1366 67.7 21 1.2 Yes 348 165 35.4 236 62.3 9 . DK 26 11 40.4 766 58.5 14 . Employment 958 518 54.1 412 43.0 28 2.9 Full Time 2017 630 31.2 1366 67.7 21 1.0 Part Time 379 134 35.4 236 62.3 9 2.4 Not Employed 1309 529 40.4 766 58.5 14 1.1 Education . 1021 550 53.9 434 42.5 37 3.6 < High School 399 196 49.1 198 49.6 45 1.3 High School Graduate 1253 501 40.0 739 59.0 13 1.0 <College 895 304 34.0 584 65.3 7 0.8 College Graduate 650 159 24.5 484 74.5 7 1.1 Post Graduate 445 101 22.7 341 76.6 3 0.7 Census Region Northeast 1048 370 35.3 655 62.5 23 2.2 Midwest 1036 449 43.3 575 55.5 12 1.2 South 1601 590 36.9 989 61.8 22 1.4 West 978 402 41.1 561 57.4 15 1.5 Day of Week Weekday 3156 1254 39.7 1848 58.6 54 1.7 Weekend 1507 557 37.0 932 61.8 18 1.2 Season Winter 1264 462 36.6 780 61.7 22 1.7 Spring 1181 469 39.7 691 58.5 21 1.8 Summer 1275 506 39.7 745 58.4 24 1.9 Fall 943 374 39.7 564 59.8 5 0.5 Asthma No 4287 1674 39.0 2563 59.8 50 1.2 Yes 341 131 38.4 207 60.7 3 0.9 DK 35 6 17.7 10 28.6 19 54.3 Angina No 4500 1750 38.9 2698 60.0 52 1.2 Yes 125 56 44.8 68 54.4 1 0.8 DK 38 50 13.2 14 36.8 19 50.0 Bronchitis/Emphysema No 4424 1726 9.0 2648 59.6 50 1.1 Yes 203 80 39.4 121 59.6 2 1.0 DK 36 5 13.9 11 30.6 20 55.6 Note:*= Missing data; DK= Don't know;%= Row percentage; N =Sample size Source: Tsano and Kleoeis 1996. Table 10-48. Number of Resoondents Reoortino Consumotion of a Soecified Number of Servinas of Seafood in 1 Month Population Group Total N Number of Servinas in a Month 1-2 3-5 6-10 11-19 20+ DK Overall 2780 918 990 519 191 98 64 Gender . 1311 405 458 261 101 57 29 Male 1468 512 532 258 90 41 35 Female 1 1 . . . . . (years) 42 13 16 5 4 1 3 1-4 102 55 29 12 2 . 4 5-11 166 72 57 21 6 4 6 12-17 137 68 54 9 2 1 3 18-64 1946 603 679 408 145 79 32 >64 387 107 155 64 32 13 16 Race . 2249 731 818 428 155 76 41 White 304 105 103 56 16 10 14 Black 56 15 17 11 5 5 3 Asian 56 22 18 6 5 3 2 Some Others 93 41 25 14 9 2 2 Hispanic 22 4 9 4 1 2 2 Hispanic 2566 844 922 480 175 88 57 No 182 68 52 34 15 8 5 Yes 15 5 8 2 . . . DK 17 1 8 3 1 2 2 Employment 399 190 140 40 11 5 13 Full Time 1366 407 466 307 107 57 22 Part Time 236 70 95 46 14 8 3 Not Employed 766 249 285 124 57 26 25 Refused 13 2 4 2 2 2 1 Education . 434 205 149 47 12 7 14 < High School 198 88 62 20 6 10 12 High School Graduate 739 267 266 119 46 21 20 <College 584 161 219 122 48 26 8 College Graduate 484 115 183 121. 43 17 5 Post Graduate 341 82 111 90 36 17 5 Census Region Northeast 655 191 241 137 62 12 12 Midwest 575 199 221 102 17 22 14 South 989 336 339 175 70 41 28 West 561 192 189 105 42 23 10 Day of Week Weekday 1848 602 661 346 129 70 40 Weekend 932 316 329 173 62 28 24 Season Winter 780 262 284 131 60 28 15 Spring 691 240 244 123 45 25 14 Summer 745 220 249 160 59 31 26 Fall 564 196 213 105 27 14 9 Asthma No 2563 846 917 475 180 88 57 Yes 207 69 71 42 11 9 5 DK 10 3 2 2 . 1 2 Angina No 2698 896 960 509 183 95 55 Yes 68 19 27 8 7 1 6 DK 14 3 3 2 1 2 3 Bronchitis/Emphysema No 2648 877 940 495 185 91 60 Yes 121 37 47 23 6 . 6 2 DK 11 4 3 1 . 1 2 Note: * = Missing data; DK= Don't know; % = Row percentage; N = Sample size; Refused = Respondent refused to answer. Source: Tsana and Kleoeis, 1996. Table'10-49. Numer of Respondents Reporting Monthly Consumption of Seafood That Was Purchased or Caught by Someone They Knew Population Group Total N . Mostly Purchased Mostly Caught DK Overall 2780 3 2584 154 39 Gender . 1311 1 1206 85 19 Male 1468 2 1377 69 20 Female 1 . 1 . . (years) 42 . 39 3 . 1-4 102 . 94 8 . 5-11 166 . 153 9 4 12-17 137 . 129 6 2 18-64 1946 3 1810 106 27 >64 387 . 359 22 6 Race . 2249 1 2092 124 32 White 304 1 280 19 4 Black 56 . 50 4 2 Asian 56 . 55 . 1 Some Others 93 . 86 7 . Hispanic 22 1 21 . . Hispanic 2566 2 2387 140 37 No 182 . 169 13 . Yes 15 . 12 1 2 DK 17 1 16 . . Employment 399 . 368 25 6 Full Time 1366 2 1285 64 15 Part Time 236 1 217 15 3 Not Employed 766 . 701 50 15 Refused 13 . 13 . . Education . 434 . 401 26 7 < High School 198 . 174 20 4 High School Graduate 739 . 680 48 11 <College 584 2 547 28 7 College Graduate 484 . 460 19 5 Post Graduate 341 1 322 13 5 Census Region Northeast 655 2 627 21 5 Midwest 575 . 547 ;w 8 South 989 1 897 73 18 West 561 . 513 40 8 .Day of Week Weekday 1848 2 1724 100 22 Weekend 932 1 860 54 17 Season Winter 780 . 7:41 35 4 Spring 691 . 655 27 9 Summer 745 2 674 54 15 Fall 564 1 514 38 11 Asthma No 2563 2 2384 142 35 Yes 207 1 190 12 4 DK 10 . 10 . . Angina 37 No 2698 3 2507 151 2 Yes 68 . 63 3* . DK 14 . 14 . Bronchitis/Emphysema No 2648 3 2457 149 39 Yes 121 . 116 5 . DK 11 . 11 . . Note: * = Missing data; DK= Don't know; N = Sample size; Refused = Respondent refused to answer. Source: Tsana and Kleoeis. 1996. Table 10-50. Estimated Number of Participants in Marine Recreational Fishing by State and Subregion Subregion State Coastal Non Coastal Out of State

Toial Particioants Particioants Pacific So. California 902 8 159 910 N. California 534 99 63 633 Oregon 265 _IB 78 284 TOTAL 1,701 126 North Atlantic Connecticut 186 *b 47 186 Maine 93 9 100 102 Massachusetts 377 69 273 446 New Hampshire 34 10 32 44 Rhode Island 97
157 97 -TOTAL 787 88 Mid-Atlantic Delaware 90
1'59 90 Maryland 540 32 268 572 New Jersey 583 9 433 592 New York 539 13 70 552 Virginia 294 29 131 323 TOTAL 1,046 83 South Atlantic Florida 1,201
741 1,201 Georgia 89 61 29 150 N. Carolina 398 224 745 622 S. Carolina _ru_ 77 304 208 TOTAL 1,819 362 Gulf of Mexico Alabama 95 9 101 104 Florida 1,053
1,349 1,053 Louisiana 394 48 *63 442 Mississippi 157 42 51 200 TOTAL 1.699 99 GRAND TOTAL 8,053 760
Not additive across states. One person can be counted as "OUT OF STATE" for more than one state. b An asterisk (*) denotes no non-coastal counties in state. Source: NMFS 1993.

Table 10-51. Estimated Weight of Fish Caught (Catch Type A and 81) by Marine Recreational Fishermen, bv Wave and Subreaion Atlantic and Gulf Pacific Renion Weinht 11000 kn\ Renion Weinht 11000 ka\ Jan/Feb South Atlantic 1,060 So. California 418 Gulf 3.683 N. California 101 Oregon 165 TOTAL 4,743 TOTAL 684 Mar/Apr North Atlantic 310 So. California 590 Mid Atlantic 1,030 N. California 346 South Atlantic 1,913 Oregon -111 Gulf 3.703 TOTAL 1,080 TOTAL 6,956 So.California 1;195 May/Jun North Atlantic 3,272 N. California 563 Mid Atlantic 4,815 Oregon __§fil_ South Atlantic 4,234 TOTAL 2,339 Gulf 5.936 TOTAL 18,257 So. California 1,566 N. California 1,101 Jul/Aug North Atlantic 4,003 Oregon Mid Atlantic 9,693 TOTAL 2,706 South Atlantic 4,032 Gulf 5,964 So. California 859 TOTAL 23,692 N. California 1,032 Oregon _ll1 Sep/Oct North Atlantic 2,980 TOTAL 2,615 Mid Atlantic 7,798 South Atlantic 3,296 So.* California 447 Gulf 7.516 N. California 417 TOTAL 21,590 Oregon . 65 TOTAL 929 Nov/Dec North Atlantic 456 Mid Atlantic 1,649 GRAND TOTAL 10,353 South Atlantic 2,404 Gulf 4,278 TOTAL 8,787 GRAND TOTAL 84,025 Source: NMFS 1993. Table 10-52. Average Daily Intake (g/day) of Marine Finfish, by Region and Coastal Status Intake Among Anglers Per-Capita Per-Capita Proportion of Region' Mean 95th Percentile (Coastal)* (Coastal & Non-Coastall0 Population Coastal N.Atlantic 6.2 20.1 1.2 1.1 0.82 Mid-Atlantic 6.3 18.9 1.2 0.9 0.70 S. Atlantic 4.7 15.9 1.5 1.0 0.51 All Atlantic 5.6 18.0 1.3 0.9 0.66 Gulf 7.2 26.1 3.0 1.9 0.60 S. California 2.0 5.5 0.2 0.2 0.96 N. California 2.0 5.7 0.3 0.3 0.70 Oregon 2.2 8.9 0.5 0.5 0.87 All Pacific 2.0 6.8 0.3 0.3 0.86 . N. Atlantic -ME, NH, MA, RI, and CT; Mid-Atlantic -NY, NJ, MD, DE, and VA; S. Atlantic -NC, SC, GA, and FL (Atlantic Coast); Gulf-AL, MS, LA, and FL (Gulf Coast). b Mean intake rate among entire coastal population of region. c M!lan intake rate among entire population of region. Source: NMFS, 1993. Table 10-53. Estimated Weight of Fish Caught (Catch Type A and B1)' by Marine Recreational Fishermen by Species Group and Subreqion, Atlantic and Gulf North Atlantic Mid Atlantic South Atlantic Gulf All Regions 11 000 kal 11 000 kal 11 000 kal 11 000 kal 11 000 kn\ Cartilaginous fishes 66 1,673 162 318 2,219 Eels 14 9 .., O' 23 Herrings 118 69 1 89 177 Catfishes 0 306 138 535 979 Toadfishes 0 7 0 . 7 Cods and Hakes 2,404 988 4 0 1,396 Searobins 2 68 . . 70 Sculpins 1 . 0 0 1 Temperate Basses 837 2,166 22 4 2,229 Sea Basses 22 2,166 644 2;477 5,309 Bluefish 4,177 3,962 1,065 158 5,362 Jacks 0 138 760 2,477 3,375 Dolphins 65 809 2,435 1,599 4,908 Snappers 0 . 508 3,219 3,727 Grunts 0 9 239 816 1,064 Porgies 132 417 1,082 2,629 4,160 Drums 3 2,458 2,953 9,866 15,280 Mullets 1 43 382 658 1,084 Barracudas 0 . 356 244 600 Wrasses 783 1,953 46 113 2,895 Mackerels and Tunas 878 3,348 4,738 4,036 13,000 Flounders 512 4,259 532 377 5,680 Triggerfishes/Filefishes 0 48 109 544 701 Puffers . 16 56 4 76 Other fishes 105 72 709 915 1,801

For Catch Type A and B 1, the fish were not thrown back. b An asterisk(*) denotes data not reported. ' Zero (0) = < 1000 kg. Source: NMFS 1993.

Table 10-54. Estimated Weight of Fish Caught (Catch Type A and B1 )*by Marine Recreational Fishermen bv Species Group and Subregion, Pacific Southern California Northern California Oregon Soecies Grouo (1 000 kal r1 000 kol 11 000 kal Total Cartilaginous fish 35 162 1 198 Sturgeons o* 89 13 102 Herrings 10 15 40 65 Anchovies *" 7 0 7 Smelts 0 71 0 71 Cods and Hakes 0 0 0 0 Silversides 58 148 0 206 Striped Bass

0 51 0 51 Sea Basses 1,319 17 0 1,336 Jacks 469 17 1 487 Croakers 141 136 0 277 Sea Chubs 53 1 0 54 Surfperches 74 221 47 342 Pacific Barracuda 866 10 0 876 Wrasses 73 5 0 78 Tunas and Mackerels 1,260 36 1 1,297 Rockfishes 409 1,713 890 3,012 California Scorpionfish 86 0 0 86 Sablefishes 0 0 5 5 Greenlings 22 492 363 877 Sculpins 6 81 44 131 Flatfishes 106 251 5 362 Otherfishes. 89 36 307 432
For Catch Type A and B1, the fish were not thrown back.
Zero (0) = <1000 kg. 0 An asterisk (*) denotes data not reported. Source: NMFS 1993.

Table 10-55. Median Intake Rates Based on Demooranhic Data of Snort Fishermen and Their Familv/Livina Groun Percent of total interviewed Median intake rates lg/nerson-day\ Ethnic GrOUQ Caucasian 42 46.0 Black 24 24.2 Mexican-American 16 33.0 Oriental/Samoan 13 70.6 Other 5 --a < 17 11 27.2 18-40 52 32.5 41 -65 28 39.0 > 65 9 113.0 a Not reported. Source: Puffer et al. 1981. Table 10-56. Cumulative Distribution of Total Fish/Shellfish Consumption by Surveyed Sport Fishermen in the Metropolitan.Los Angeles Area Percentile Intake rate {g/person-day) 5 2.3 10 4.0 20 8.3 30 15.5 40 23.9 50 36.9 60 53.2 70 79.8 80 120.8 90 224.8 95 338.8 Source: Puffer et al. 11981\. Table 10-57. Catch Information for Primarv Fish Species Kept by Sport Fishermen (n = 1059) Species Averai:ie Weight (Grams) Percent of Fishermen who Caught White Croaker 153 34 Pacific Mackerel 334 25 Pacific Bonito 717 18 Queenfish 143 17 Jacksmelt 223 13 Walleye Perch 115 10 Shiner Perch 54 7 Opal eye 307 6 Black Perch 196 5 Kelp Bass 440 5 California Halibut 1752 4 Shellfish* 421 3

Crab, mussels, lobster, abalone. Source: Modified from Puffer et al. 1981.

Table 10-58. Percent of Fishim1 Frequency During the Summer and Fall Seasons in Commencement Bav, Washington Frequency Percent Frequency Percent Frequency Percent Fishing Frequency in the Summer" in the Fallb in the Fall' Daily 10.4 8.3 5.8 Weekly 50.3 52.3 51.0 Monthly 20.1 15.9 21.1 Bimonthly 6.7 3.8 4.2 Biyearly 4.4 6.1 6.3 Yearlv 8.1 13.6 11.6 a Summer-July through September, includes 5 survey days and 4 survey areas (i.e., area #1, #2, #3 and #4) b Fall -September through November, includes 4 survey days and 4 survey areas (i.e., area #1, #2, #3 and #4) c Fall -September through November, includes 4 survey days described in footnote b plus an additional survey area (5 survey areas) (i.e., area #1, #2, #3, #4 and #5) Source: Pierce et al. 1981. Table 10-59. Selected Percentile Consumption Estimates (g/day) for the Survey and Total Angler Populations Based on the Reanalysis of the Puffer et al. ( 1981 ) and Pierce et al. ( 1981) Data 50th Percentile 90th Percentile Survey Population Puffer et al. (1981) 37 225 Pierce et al. (1981) 19 155 Average 28 190 Total Angler Population Pufferetal. (1981) 2.93 35b Pierce et al. (1981) LQ 13 Averaae 2.0 24 a Estimated based on the average intake for the 0 -90th percentile anglers. b Estimated based on the average intake for the 91 st -96th percentile anglers. Source: Price et al. 1994. Table 10-60. Means and Standard Deviations of Selected Characteristics by Subpopulation Groups in Even:ilades, Florida Variables/ Mean +/- Std. Dev.b IN.=330\1 Ranae Age (years) 38.6 +/- 18.8 2-81 Sex Female 38% -Male 62% -Race/ethnicity Black 46% --White 43% --Hispanic 11% --Number of Years Fished 15.8 +/- 15.8 0-70 Number Per Week Fished in Past 6 Months of Survey Period 1.8 +/- 2.5 0-20 Number Per Week Fished in Last Month of Survey Period 1.5+/-1.4 0-12 Aware of Health Advisories 71% -a Number of respondents who reported consuming fish b Std. Dev. = standard deviation Source: U.S. DHHS 1995 Table 10-61. Mean Fish Intake Among Individuals Who Eat Fish and Reside in Households With Recreational Fish Consumption Recreational Recreational Total Fish Recreational All Fish Fish meals/week Total Fish Fish grams/ Fish grams/ Grouo meals/week n nrams/dav nrams/dav ka/dav ka/dav All household 0.686 0.332 2196 21.9 11.0 0.356 0.178 members Respondents (i.e., 0.873 0.398 748 29.4 . 14.0 0.364 0.168 licensed anglers) Age GrouQs (years) 1-5 0.463 0.223 121 11.4 5.63 0.737 0.369 6 to 10 0.49 0.278 151 13.6 7.94 0.481 0.276 1to20 0.407 0.229 349 12.3 7.27 0.219 0.123 21to40 0.651 0.291 793 22 10.2 0.306 0.139 40 to 60 0.923 0.42 547 29.3 14.2 0.387 0.186 60 to 70 0.856 0.431 160 28.2 14.5 0.377 0.193 71 to 80 1.0 0.622 45 32.3 20.1 0.441 0.271 80+ 0.8 0.6 10 26.5 20 0.437 0.345 Source: U.S. EPA analvsis usina data from West et al. 1989. Table 10-62. Comparison of Seven-Day Recall and Estimated Seasonal Frequency for Fish Consumption Usual Fish Consumption Mean Fish Meals/Week Usual frequency Value Selected Freouencv Cateoorv 7-dav Recall Data for Data Analvsis !times/week) Almost daily no data. 4 needed] 2-4 times a week 1.96 2 Once a week 1.19 1.2 2-3 times a month 0.840 (3.6 times/month) 0.7 (3 times/month) Once a month 0.459 (1.9 times/month) 0.4 (1.7 times/month) Less often 0.306 11.3 times/month) 0.2 I0.9 times/month) Source: U.S. EPA analvsis usina data from West et al. 1989. Table 10-63. Distribution of Usual Fish Intake Among Survey Main Respondents Who Fished and Consumed Recreationally Caught Fish Recreational Recreational All Fish Recreational All Fish Intake Fish Intake All Fish Intake Fish Intake Meals/Week Fish grams/day grams/day grams/ kg/day grams/kg/day Meals/Week n 738 738 738 738 726 726 mean 0.859 0.447 27.74 14.42 0.353 0.1806 10% 0.300 0.040 9.69 1.29 0.119 0.0159 25% 0.475 0.125 15.34 4.04 0.187 0.0504 50% 0.750 0.338 24.21 10.90 0.315 0.1357 75% 1.200 0.672 38.74 21.71 0.478 0.2676 90% 1.400 1.050 45.20 33.90 0.634 0.4146 95% 1.800 1.200 58.11 38.74 0.747 0.4920 Source: U.S. EPA analvsis usino data from West et al. 1989. Table 10-64. Estimates ofFish Intake Rates of Licensed Sport Anglers in Maine During the 1989-1990 Ice Fishina or 1990 Ooen-Water Seasons* Intake Rates (grams/day) Percentile Rankings All Watersb Rivers and Streams All Anglers0 Consuming Anglers' River Anglers* Consuming Anglersd IN= 1 369) IN= 1 053\ IN= 741\ IN= 464\ 50th (median) 1.1 2.0 0.19 0.99 66th 2.6 4.0 0.71 1.8 75th 4.2 5.8 1.3 2.5 9oth 11.0 13.0 3.7 6.1 95th 21.0 26.0 6.2 12.0 Arithmetic Mead 5.0 6.4 1.9 3.7 1791 r77l r821 r811 a Estimates are based on rank except for those of arithmetic mean. b All waters based on fish obtained from all lakes, ponds, streams and rivers in Maine, from other household sources and from other non-household sources. ' Licensed anglers who fished during the seasons studied and did or did not consume freshwater fish, and licensed anglers who did not fish but ate freshwater fish caught in Maine during those seasons. d Licensed anglers who consumed freshwater fish caught in Maine during the seasons studied. a Those of the "all anglers" who fished on rivers or streams (consumers and nonconsumers ). f Values in brackets [] are percentiles at the mean consumption rates. Source: Chemrisk 1991

Ebert et al. 1993.

Table 10-65. Analysis of Fish Consumption by Ethnic Groups for "All Waters" (g/day)* Consuming Anglersb French Native Other White Canadian Irish Italian American Non-Hispanic Scandinavian Heritage Heritage Heritage Heritage Heritage Heritage N of Cases 201 138 27 96 533 37 Median (50th percentile)0*d 2.3 2.4 1.8 2.3 1.9 1.3 66th percentile0*d 4.1 4.4 2.6 4.7 3.8 2.6 ?5th percentile0*d 6.2 6.0 5.0 6.2 5.7 4.9 Arithmetic Mean° 7.4 5.2 4.5 10 6.0 5.3 Percentile at the Meand 80 70 74 83 76 78 90th percentile0*d 15 12 12 16 13 9.4

95th percentile0*d 27 20 21 51 24 25 Percentile at 6.5 g/day"** 77 75 81 77 77 84 a "All Waters" based on fish obtained from all lakes, ponds, streams and rivers in Maine, from other household sources and from other non-household sources. b "Consuming Anglers" refers to only those anglers who consumed freshwater fish obtained from Maine sources during the 1989-1990 ice fishing or 1990 open water fishing season. c The average consumption per day by freshwater fish consumers in the household. d Calculated by rank without any assumption of statistical distribution. e Fish consumption rate recommended by U.S. EPA (1984) for use in establishing ambient water quality standards. Source: Chemrisk, 1991.

Table 10-66. Total Consumption ofFreshwater Fish Caught by All Survey Respondents During the 1990 Season Ice Fishing Lakes and Ponds Rivers and Streams Species Quantity Grams Quantity Grams Quantity Grams Consumed (x103) Consumed (x103) Consumed (x103) (#) Consumed (#\ Consumed (#\ Consumed Landlocked salmon 832 290 928 340 305 120 Atlantic salmon 3 1.1 33 9.9 17 11 Tague (Lake trout) 483 200 459 160 33 2.7 Brook trout 1,309 100 3,294 210 10,185 420 Brown trout *275 54 375 56 338 23 Yellow perch 235 9.1 1,649 52 188 7.4 White perch 2,544 160 6,540 380 3,013 180 Bass (smallmouth and largemouth) 474 120 73 5.9 787 130 Pickerel 1,091 180 553 91 303 45 Lake whitefish 111 20 558 13 55 2.7 Hompout (Catfish and bullheads) 47 8.2 1,291 100 180 7.8 Bottom fish (Suckers, carp and sturgeon) 50 81 62 22 100 6.7 Chub 0 0 252 35 219 130 Smelt 7,808 150 428 4.9 4,269 37 Other 201 210 90 110 54 45 TOTALS 15 463 1 583.4 16 587 1 590 20046 1168 Source: Chemrisk 1991.

Table 10-67. Mean Sport-Fish Consumption by Demographic Variables, Michigan Sport Analers Fish Consumption Studv, 1991-1992 N Mean ln/dav1 95%C.I. Income' 290 21.0 16.3 -25.8 $15,000 -$24,999 369 20.6 15.5-25.7 $25,000 -$39,999 662 17.5 15.0 -20.1 >$40,000 871 14.7 12.8 -16.7 Education Some High School 299 16.5 12.9-20.1 High School Degree 1,074 17.0 14.9-19.1 Some College-College Degree 825 17.6 14.9 -20.2 Post Graduate 231 14.5 10.5-18.6 Residence Sizeb Large City/Suburb (>100,000) 487 14.6 11.8-17.3 Small City (20,000-100,000) 464 12.9 10.7 -15.0 Town (2,000-20,000) 475 19.4 15.5 -23.3 Small Town (100-2,000) 272 22.8 16.8 -28.8 Rural, Non Farm 598 17.7 15.1 -20.3 Farm 140 15.1 10.3 -20.0 &Jg(years) 16-29 266 18.9 13.9 -23.9 30-39 583 16.6 13.5-19.7 40-49 556 16.5 13.4 -19.6 50-59 419 16.5 13.6 -19.4 60+ 596 16.2 13.8 -18.6 Sex' -Male* 299 17.5 15.8 -19.1 Female 1,074 13.7 11.2 -16.3 Race/Ethnicilt Minority 160 23.2 13.4-33.1 White 2,289 16.3 14.9-17.6 ' P < .01, F test b P < .05, Ftest Source: West et al., 1993 Table 10-68. Distribution of Fish Intake Rates (from all sources and from sport-caught sources) For 1992 Lake Ontario Anolers Percentile of Lake Ontario Anolers Fish from All Sources (a/davl Soort-Cauaht Fish (a/dav) 25% 8.8 0.6 50% 14.1 2.2 75% 23.2 6.6 90% 34.2 13.2 95% 42.3 17.9 99% 56.6 39.8 Source. Connellv et al. 1996.

Table 10-69. Mean Annual Fish Consumption (g/day) for Lake Ontario Anglers, 1992, by Sociodemoqraphic Characteristics Mean Consumption Demoqraphic Group Fish from all Sources Sport-Cauqht Fish Overall 17.9 4.9 Residence Rural 17.6 5.1 Small City 20.8 6.3 City (25-100, 000) 19.8 5.8 City(> 100,000) 13.1 2.2 Income < $20,000 20.5 4.9 $21,000-34,000 17.5 4.7 $34,000-50,000 16.5 4.8 >$50,000 20.7 6.1 fill§. (years) <30 13.0 4.1 30-39 16.6 4.3 40-49 18.6 5.1 50+ 21.9 6.4 Education < High School 17.3 7.1 High School Graduate 17.8 4.7 Some College 18.8 5.5 College Graduate 17.4 4.2 Some Post Grad. 20.5 5.9 Note -Scheffe's test showed statistically significant differences between residence types (for all sources and sport caught) and age groups (all sources). Source: Connellv et al. 1996. ' -_J Table 10-70. Percentile and Mean Intake Rates for Wisconsin Sport AnQlers Percentile Annual Number of Soort Cauaht Meals Intake Rate of Soort-Cauaht Meals (a/dav) 25th 4 1.7 50th 10 4.1 75th 25 10.2 90th 50 20.6 95th 60 24.6 98th 100 41.1 100th 365 150 Mean 18 7.4 Source: Raw data on sport-caught meals from Fiore et al., 1989. EPA calculated intake rates using a value of 150 arams oer fish meal* this value is dervied from Pao et al. 1982. Table 10-71. Sociodemographic Characteristics of Respondents Cateaorv Subcateaorv Percent of Total* Geographic Distribution Upper Hudson 18% Mid Hudson 35% Lower Hudson 48% Age Distribution (years) < 14. 3% 15 -29 26%. 30-44 35% 45-59 23% > 60 12 % Annual Household Income < $10,000 16 % $10 -29,999 41 % $30 -49,999 29% $50 -69,999 10 % $70 -89,999 2% > $90,000 3% Ethnic Ba.ckground Caucasian American 67% African American 21 % Hispanic American 10% Asian American 1 % Native American 1 %

A total of 336 shore-based anglers were interviewed Source: Hudson River Slooo Clearwater Inc. 1993 Table 10-72. Number of Grams Per Day of Fish Consumed by All Adult Respondents (Consumers and Non-consumers Combined) -Throughout the Year Number of Grams/Dav Cumulative Percent Number of Grams/Dav Cumulative Percent 0.00 8.9% 64.8 80.6% 1.6 9.0% 72.9 81.2% 3.2 10.4% 77.0 81.4% 4.0 10.8% 81.0 83.3% 4.9 10.9% 97.2 89.3% 6.5 12.8% 130 92.2% 7.3 12.9% 146 93.7% 8.1 13.7% 162 94.4% 9.7 14.4% 170 94.8% 12.2 14.9% 194 97.2% 13.0 16.3% 243 97.3% 16.2 22.8% 259 97.4% 19.4 24.0% 292 97.6% 20.2 24.1% 324 98.3% 24.3 27.9% 340 98.7% 29.2 28.1% 389 99.0% 32.4 52.5% 486 99.6% 38.9 52.9% 648 99.7% 40.5 56.5% 778 99.9% 48.6 67.6% 972 100% N = 500 Weighted Mean= 58.7 grams/day (g/d) Weighted SE = 3.64 90th Percentile: 97.2 g/d < (90th) < 130 g/d 95th Percentile = 170 g/d 99th Percentile = 389 g/d Source: CRITFC 1994 Table 10-73. Fish Intake ThrouQhout the Year by Sex, AQe, and Location by All Adult Respondents Weighted Mean N (arams/dav) Weiahted SE Sex Female 278 55.8 4.78 Male 222 62.6 5.60 Total 500 58.7 3.64 till§. (years) 18-39 287 57.6 4.87 40-59 155 55.8 4.88 60 & Older 58 74.4 15.3 Total 500 58.7 3.64 Location On Reservation 440 60.2 3.98 Off Reservation 60 47.9 8.25 Total 500 58.7 3.64 Source: CRITFC 1994.

Table 10-74. Children's Fish Consumption Rates -Throughout Year Number of Grams/Dav Unweiahted Cumulative Percent 0.0 21.1% 0.4 21.6% 0.8 22.2% . 1.6 24.7% 2.4 25.3% 3.2 28.4% 4.1 32.0% 4.9 33.5% 6.5 35.6% 8.1 47.4% . '. 9.7 48.5% 12.2 51.0% 13.0 51.5% 16.2 72.7% 19.4 73.2% 20.3 74.2% 24.3 76.3% 32.4 87.1% 48.6 91.2% 64.8 94.3% 72.9 96.4% 81.0 97.4% 97.2 98.5% 162.0 100% N = 194 Unweighted Mean = 19.6 grams/day Unweiahted SE = 1.94 Source: CRITFC 1994. Table 10-75. Sociodemoaraohic Factors and Recent Fish Consumotion Peak Consum[!tion" Recent Consumotionb Averaae0 ;,3dl%\ Walleve N. Pike Muskellunae Bass All participants (N-323) 1.7 20 4.2 0.3 0.3 0.5 Gender Male (n-148) 1.9 26 5.1 0.5" 0.5 0.7" Female (n-175) 1.5 15 3.4 0.2 0.1 0.3 Age (y) <35 (n-150) 1.8 23 5.3" 0.3 0.2 0.7 "35 (n-173) 1.6 17 3.2 0.4 0.3 0.3 High School Graduate No (n-105) 1.6 18 3.6 0.2 0.4 0.7 Yes (n-218) 1.7 21 4.4 DA 0.2 0.4 Unemployed Yes (n-78) 1.9 27 4.8 0.6 0.6 1.1 No (n-245) 1.6 18 4.0 0.3 0.2' 0.3 a Highest number of fish meals consumed/week. b Number of meals of each species in the previous 2 months. c Average peak fish consumption. d Percentage of population reporting peak fish consumption of "3 fish meals/week. Source: Peterson et al. 1994. Table 10-76. Number cif Local Fish Meals Consumed Per Year by Time Period for All Respondents Time Period Number of Local Fish During Pregnancy ,;;1 Yr. Before Pregnancy* >Yr. Before Pregnancyb Meals Consumed Per Mohawk Control Mohawk Control Mohawk Control Year NC % NC % NC % NC % NC % NC % None 63 64.9 109 70.8 42 43.3 99 64.3 20 20.6 93 60.4 1 -9 24 24.7 24 15.6 40 41.2 31 20.1 42 43.3 35 22.7 10 -19 5 5.2 7 4.5 4 4.1 6 3.9 6 6.2 8 5.2 20-29 1 1.0 5 3.3 3 3.1 3 1.9 9 9.3 5 3.3 30-39 0 0.0 2 1.3 0 0.0 3 1.9 1 1.0 1 0.6 40-49 0 0.0 1 0.6 1 1.0 1 0.6 1 1.0 1 0.6 50+ 4 4.1 6 3.9 7 7.2 11 7.1 18 18.6 11 7.1 Total 97 100.0 154 100.0 97 100.0 154 100.0 97 100.0 154 100.0 a p <0.05 for Mohawk vs. Control. b p <0.001 for Mohawk vs. Control. c N = number of respondents. Source: Fitzgerald et al., 1995.

Table 10-77. Mean Number of Local Fish Meals Consumed Per Year b_y Time Period for All Respondents and Consumers Only All Respondents Consumers Only (N=97 Mohawks and 154 Controls) (N=82 Mohawks and 72 Controls) During ,;;1 Yr. Before >1 Yr. Before During ,, 1 Yr. Before >1 Yr. Before Pregnancy Pregnancy Pregnancy Pregnancy Pregnancy Pregnancy Moh aw 3.9 (1.2) 9.2 (2.3) 23.4 (4.3)a 4.6 (1.3) 10.9 (2.7) 27.6 (4.9) k 7.3 (2.1) 10.7 (2.6) 10.9 (2.7) 15.5 (4.2)a 23.0 (5.1 )b 23.0 (5.5) Control a p <0.001 for Mohawk vs. Control. b p<0.05 for Mohawk vs. Control ( ) =standard error. Test for linear trend: p<0.001 for Mohawk (All participants and consumers only); p=0.07 for Controls (All participants and consumers only). Source: Fitzgerald et al., 1995.

Table 10-78. Mean Number of Local Fish Meals Consumed Per Year by Time Period and Selected Characteristics for All Respondents (Mohawk, N=97; Control, N=154) Time Period Durina Preanancv ,;1 Year Before Preanancv >1 Year Before Preanancv Backaround Variable Mohawk Control Mohawk Control Mohawk Control Age (Yrs) <20 7.7 0.8 13.5 13.9 27.4 10.4 20-24 1.3 5.9 5.7 14.5 20.4 15.9 25-29 3.9 9.9 15.5 6.2 25.1 5.4 30-34 12.0 7.6 9.5 2.9 12.0 5.6 >34 1.8 11.2 1.8 26.2 52.3 22.1* Education (Yrs) <12 6.3 7.9 14.8 12.4 24.7 .8.6 12 7.3 5.4 8.1 8.4 15.3 11.4 13 -15 1.7 10.1 8.0 15.4 29.2 13.3 >15 0.9 6.8 10.7 0.8 18.7 2.1 Cigarette Smoking Yes 3.8 8.8 10.4 13.0 31.6 . 10.9 No 3.9 6.4 8.4 8.3 18.1 10.8 Alcohol Consumption Yes 4.2 9.9 6.8 13.8 18.0 14.8 No 3.8 6.3b 12.1 4.7' 29.8 2.9d a F ( 4, 149) = 2.66, p=0.035 for Age Among Controls. b F (1, 152) = 3.77, p=0.054 for Alcohol Among Controls. ' F ( 1, 152) = 5.20, p=0.024 for Alcohol Among Controls. d F ( 1, 152) = 6.42, p=0.012 for Alcohol Among Controls. Source: Fitzaerald et al. 1995. Table 10-79. Percentage of Individuals Using Various Cooking Methods at Specified Frequencies Use Pan Fry Deep Broil or Stud Fre uenc Bake F Grill Poach Boil Smoke Raw Other Connelly et al., Always 24(a) 51 13 24(a) 1992 Ever 75(a) 88 59 75(a) Connelly et al., Always 13 4 4 1996 Ever 84 72 42 CRITFC, 1994 At least 79 51 14 27 11 46 31 1 34(b) monthly 29(c) 49(d) Ever 98 80 25 39 17 73 66 3 67(b) 71(c) 75(d) Fitzgerald et al., Not 94(e)(f) 71(e)(g) 1995 Specified Puffer et al., As Primary 16.3 52.5 12 0.25 19(h) 1981 Method ' 24 and 75 listed as bake, BBQ, or poach b Dried ' Roasted ' Canned ' Not specified whether deep or pan fried 1 Mohawk women

Control population *h boil, stew, sou or steam Table 10-80. Percent Moisture and Fat Content for Selected Species* Moisture Content Total Fat Content Soecies 1%) lo/o)b Comments FIN FISH Anchovy, European 73.37 4.101 Raw 50.30 8.535 Canned in oil, drained solids Bass 75.66 3.273 Freshwater, mixed species, raw Bass, Striped 79.22 1.951 Raw Bluefish 70.86 3.768 Raw Butterfish 74.13 NA Raw Carp 76.31 4.842 Raw 69.63 6.208 Cooked, dry heqt Catfish 76.39 3.597 Channel, raw 58.81 12.224 Channel, cooked, breaded and fried Cod, Atlantic 81.22 0.456 Atlantic, raw 75.61 0.582 Canned, solids and liquids 75.92 0.584 Cooked, dry heat 16.14 1.608 Dried and salted Cod, Pacific 81.28 0.407 Raw Croaker, Atlantic 78.03 2.701 Raw 59.76 11.713 Cooked, breaded and fried Dolphinfish, Mahimahi 77.55 0.474 Raw Drum, Freshwater 77.33 4.463 Raw Flatfish, Flounder and Sole 79.06 0.845 Raw 73.16 1.084 Cooked, dry heat Grouper 79.22 0.756 Raw, mixed species 73.36 0.970 Cooked, dry heat Haddock 79.92 0.489 Raw 74.25 0.627 Cooked, dry heat 71.48 0.651 Smoked Halibut, Atlantic & Pacific 77.92 1.812 Raw 71.69 2.324 Cooked, dry heat Halibut, Greenland 70.27 12.164 Raw Herring, Atlantic & Turbot, domestic species 72.05 7.909 Raw 64.16 10.140 Cooked, dry heat 59.70 10.822 Kippered 55.22 16.007 Pickled Herring, Pacific 71.52 12.552 Raw Mackerel, Atlantic 63.55 9.076 Raw 53.27 15.482 Cooked, dry heat Mackerel, Jack 69.17 4.587 Canned, drained solids Mackerel, King 75.85 1.587 Raw Mackerel, Pacific & Jack 70.15 6.816 Canned, drained solids Mackerel, Spanish 71.67 5.097 Raw 68.46 5.745 Cooked, dry heat Monkfish 83.24 NA Raw Mullet, Striped 77.01 2.909 Raw 70.52 3.730 Cooked, dry heat Ocean Perch, Atlantic 78.70 1.296 Raw* 72.69 1.661 Cooked, dry heat Perch, Mixed species 79.13 0.705 Raw 73.25 0.904 Cooked, dry heat Pike, Northern 78.92 0.477 Raw 72.97 0.611 Cooked, dry heat Pike. Walleve 79.31 0.990 Raw )

Table 10-80. Percent Moisture and Fat Content for Selected Species* (continued) Moisture Total Fat Content Content Soecies (%) (%)b Comments Pollock, Alaska & Walleye 81.56 0.701 Raw 74.06 0.929 Cooked, dry heat Pollock, Atlantic 78.18 0.730 Raw Rockfish, Pacific, mixed species 79.26 1.182 Raw (Mixed species) 73.41 1.515 Cooked, dry heat (mixed species) Roughy, Orange 75.90 3.630 Raw Salmon, Atlantic 68.50 5.625 Raw Salmon, Chinook 73.17 9.061 Raw 72.00 3.947 Smoked Salmon, Chum 75.38 3.279 Raw 70.77 4.922 Canned, drained solids with bone Salmon, Coho 72.63 4.908 Raw 65.35 6.213 Cooked, moist heat Salmon, Pink 76.35 2.845 Raw 68.81 5.391 Canned, solids with bone and liquid Salmon, Red & Sockeye 70.24 4.560 Raw 68.72 6.697 Canned, drained solids with bone 61.84 9.616 Cooked, dry heat Sardine, Atlantic 59.61 10.545 Canned in oil, drained solids with bone Sardine, Pacific 68.30 11.054 Canned in tomato sauce, drained solids with bone Sea Bass, mixed species 78.27 1.678 Cooked, dry heat 72.14 2.152 Raw Seatrout, mixed species 78.09 2.618 Raw Shad, American 68.19 NA Raw Shark, mixed species 73.58 3.941 Raw 60.09 12.841 Cooked, batter-dipped ar:id fried Snapper, mixed species 76.87 o .. 995 Raw 70.35 1.275 Cooked, dry heat Sole, Spot 75.95 3.870 Raw Sturgeon, mixed species 76.55 3.544 Raw 69.94 4.544 Cooked, dry heat 62.50 3.829 Smoked Sucker, white 79.71 1.965 Raw Sunfish, Pumpkinseed 79.50 0.502 Raw Swordfish 75.62 3.564 Raw 68.75 4.569 Cooked, dry heat Trout, mixed species 71.42 5.901 Raw Trout, Rainbow 71.48 2.883 Raw 63.43 3.696 Cooked, dry heat Tuna, light meat 59.83 7.368 Canned in oil, drained solids 74.51 0.730 Canned in water, drained solids Tuna, white meat 64.02 NA Canned in oil 69.48 2.220 Canned in water, drained solids Tuna, Bluefish, fresh 68.09 4.296 Raw. 59.09 5.509 Cooked, dry heat Turbot, European 76.95 NA Raw Whitefish, mixed species 72.77 5.051 Raw 70.83 0.799 Smoked Whiting, mixed species 80.27 0.948 Raw 74.71 1.216 Cooked, dry heat Yellowtail mixed snecies 74.52 NA Raw Table 10-80. Percent Moisture and Fat Content for Selected Species' (continued) Moisture Total Fat Content Content Species (%) 1%lb Comments SHELLFISH Crab, Alaska King 79.57 NA Raw 77.55 0.854 Cooked, moist heat Imitation, made from surimi Crab, Blue 79.02 0.801 Raw 79.16 0.910 Canned (dry pack or drained solids of wet pack) 77.43 1.188 Cooked, moist heat 71.00 6.571 Crab cakes Crab, Dungeness 79.18 0.616 Raw Crab, Queen 80.58 0.821 Raw Crayfish, mixed species 80.79 0.732 Raw 75.37 0.939 Cooked, moist heat Lobster, Northern 76.76 NA Raw 76.03 0.358 Cooked, moist heat Shrimp, mixed species 75.86 1.250 Raw 72.56 1.421 Canned (dry pack or drained solids of wet pack) 52.86 10.984 Cooked, breaded and fried 77.28 0.926 Cooked, moist heat Spiny Lobster, mixed species 74.07 1.102 Imitation made from surimi, raw Clam," mixed species 81.82 0.456 Raw 63.64 0.912 Canned, drained solids 97.70 NA Canned, liquid 61.55 10.098 Cooked, breaded and fried 63.64 0.912 Cooked, moist heat Mussel, Blue 80.58 1.538 Raw 61.15 3.076 Cooked, moist heat Octopus, common 80.25 0.628 Raw Oyster, Eastern 85.14 1.620 Raw 85.14 1.620 Canned (solids and liquid based) raw 64.72 11.212 Cooked, breaded and fried 70.28 3.240 Cooked, moist heat Oyster, Pacific 82.06 1.752 Raw Scallop, mixed species 78.57 0.377 Raw 58.44 10.023 Cooked, breaded and fried 73.82 NA Imitation, made from Surimi Squid 78.55 0.989 Raw 64.54 6.763 Cooked fried ' Data are reported as in the Handbook b Total Fat Content-saturated, monosaturated and polyunsaturated NA = Not available Source: USDA 1979-1984-U.S. Aaricultural Handbook No. 8 Table 10-81. Recommendations -General Population Mean Intake 95th Percentile of Long-term .. (g/day) Intake Distribution (g/day) Study (Reference) 53 (Value of 42 from Javitz was adjusted TRI (Javitz, 1980; Ruffle et al., 1994) upward by 25 percent to account for recent increase in fish consumption) 20.1 (Total Fish) U.S. EPA Analysis ofCSFll, 1989-91 14.1 (Marine Fish) 6.0 (Freshwater/Estuarine Fish) Table 10-82. Recommendations -General Population -Fish Serving Size Mean Intake (grams) 95th Percentile (grams) Study (Reference) 129 326 1989-1991 CSFll IU.S. EPA 1996) Table 10-83. Recommendations -Recreational Marine Anglers Mean Intake (g/day) 95th Percentile (g/day) Study Location Study 5.6 18.0 Atlantic NMFS, 1993 7.2 26.0 Gulf 2.0 6.8 Pacific Table 10-84. Recommendations -Freshwater Anglers Mean Intake (g/day) Upper Percentile (g/day) Study Location Reference 5 13 (95th percentile) Maine Ebert et al., 1992 5 18 (95th percentile) New York Connelly et al., 1996 12 39 (96th percentile) Michigan West et al, 1989 17 ---Michiaan West et al, 1993 Table 10-85. Recommendations -Native American Subsistence Populations Per-Capita (or Mean) Intake Upper Percentile (g/day) (g/day) Study Population Reference 59 170 (95th) 4 Columbia River Tribes CRITFC, 1994 16 ---94 Alaska Communities Wolfe and Walker, 1989 (Lowest of94) 81 ---94 Alaska Communities Wolfe and Walker, 1989 (Median of 94) 770 ---94 Alaska Communities Wolfe and Walker, 1989 (Hiqhest of 94) Table 10-86. Summary of Fish Intake Studies Source of Data Population Survey Time Period/Type Analyses Performed (References) Limitations/Advantages (Reference) Surveyed General Population Key Studies Javitz, 1980 -TRI 25, 162 individuals -Sept. 1973-Aug. 1974 (1 year Mean and distribution of fish High response rate (80%); population Survey general population; survey). Completed diary over 1 consumption rates grouped by race, was large and geographically and the TRI Survey month period on date of meal age, gender, census region, fish seasonally representative; sample consumption, of fish, species, community type, and religion. ccnsumption rates based on one packaging type, amount of fish Log normal distribution fit to fish intake month of diary data; survey data is over prepared, number of servings distribution by age and region by Ruffle 20 years out of date consumed, etc. et al. (1994). U.S. EPA, 1996a 11,912 individuals -Participants provided 3 Analysis of CSFll 1989-91. Fish Large, geographically representative general population consecutive days of dietary data. grouped by habitat (freshwater vs. study; relatively recent. Based on Three survey years (1989-1991) marine) and type (finfish vs. shellfish). short-term (3 day) data so long-term combined into one data set. Per capita fish intake rates calculated percentiles of fish intake distribution using cooked and uncooked equivalent could not be estimated. weight and reported in g/day and g/kg-day; also intake distribution per day eating fish. Relevant Studies AIHC, 1994 ---Distributions using @Risk simulation Limited reviews of supporting studies; software. good alternative source of information. Pao et al., 1982 37,874 individuals -Participants provided 3 Mean and distribution of average daily Population was large and general population consecutive days of dietary data. fish intake and average fish intake per geographically representative; data Survey conducted between April eating occasion; by age-sex groups and were based on short-term dietary 1977 and March 1978. overall. recall; data are almost 20 years out of date. Tsang and Klepeis, 9,386 individuals -Participants provided 24-hour diary Frequency of eating fish and number of Population large and geographically 1996 general population data. Follow-up questionnaires, servings per month provided. and seasonally balanced; data based survey conducted between on recall; intake data not provided. October 1992 and September 1994. USDA, 1992 10,000 individuals-Participants provided 3 Per capita fish intake rates and percent Population was large and general population consecutive days of dietary data. of population consuming fish in one geographically and seasonally Survey conducted between April day; by age and sex. balanced; data based on short-term 1987 and March 1988. dietary recall. Table 10-86. Summary of Fish Intake Studies (continued) Source of Data Population Surveyed Survey Time Period!Type

Analyses Performed (References) Limitations/Advantages I Reference\ Recreational-Marine Fish Key Study NMFS 1986a. b. c; 1993 Atlantic and Gulf Coasts -Telephone interviews with residents Intake rates were not calculated; Population was large geographically 41,000 field interviews and of coastal counties; information on total catch size grouped by marine and_ seasonally balanced; fish caught 58,000 telephone fishing frequency and mode of fishing species, seasons, and number of were weighed in the field. No interviews; Pacific Coast -trips. Field interviews with marine fishermen for each coastal region information on number of potential 38,000 field interviews and anglers; information on area and were presented. consumers of catch. 73,000 telephone mode fished, fishing frequency, interviews. species caught, weight of fish, and* whether fish were intended to be consumed. Relevant Studies Pierce et al., 1981 -500 anglers in July-November 1980; creel survey Distribution of fishing frequency; Local survey. Original analysis by Commencement Bay, interviews conducted consisting of 5 total weight of catch grouped by Pierce et al. (1981) did not calculate Washington summer days and 4 fall days. species. Re-analysis by Price et intake rates; analysis over-estimated al. (1994) using inverse fishing fishing frequency distribution by frequency as sample weights. oversampling frequent anglers. Re-analysis by Price et. al. (1994) involved several assumptions; thus I results are questionable. ', Puffer et al., 1981 1,067 anglers in the Los Creel survey con_ducted tor the full Distribution of sport fish intake Local survey. Original (unweighted) Angeles, California area. 1980 calendar year. rates. Median rates by age, analysis over-estimated fish intake by ethnicity and fish species. Re-oversampling frequent anglers. Re-analysis by Price et al. (1994) analysis by Price et al. (1994) involves using inverse fishing frequency as several assumptions; thus results are sample weights. questionable. U.S. DHHS, 1995 330 everglade residents/ 1992-1993; questionnaire with Provides data for fishing frequency Intake rates were not reported, study subsistence fishermen or demographic information and fishing by sex, age, and ethnicity. not representative of the U.S. both and eating habits. population; one of few studies that tarnet subsistence fishermen.

Table 10-86. Summary of Fish Intake Studies (continued) Source of Data <Reference\ Pooulation Surveved Survev Time PeriodfTvoe Analvses Performed (References\ Limitalions/Advantaaes Recreational Fresh Water Fish Key Studies Chemrisk, 1991; Ebert 1,612 licensed Maine 1989-1990 ice fishing season and Mean and distributio'n offish Data based on one year recall; high et al .. 1993 anglers 1990 open water season; mailed consumption rates by ethnic groups response rate; area-specific survey; one year recall of frequency and overall. Mean and distribution of consumption patterns. of fishing trips, number and length fish consumption rates for fish from of fish species caught. rivers and streams. EPA analysis of fish intake for household members. Connelly et al., 1996 825 anglers with NY State Survey consisted of self-recording Distribution of intake rates of sport Meal size estimated by comparison fishing licenses intending to information in a diary for 1992 caught fish. with pictures of 8 oz. fish meals. fish Lake Ontario. fishing trips and fish consumption. West et al., 1993 2,681 persons with January 1991 through January 1992; Mean consumption rate for sport Relatively low respo*nse made and Michigan fishing licenses mailed survey; 7-day recall; and total fish by demographic only three categories were used to demographics information category (West et al., 1993) and assign fish portion size. Relatively requested, and quantity offish 50th, 90th, and 95th percentile (U.S. large-scale study and reliance on eaten, any, at each meal based on EPA, 1995). short-term recall. a photograph of 1/2 lb of fish (more about same, or less). West et al., 1989 1, 171 Michigan residents January-May 1988; anglers Mean intake rates of self-caught fish Weight of fish consumed was with fishing licenses completed questionnaires based on based on 7-day recall period estimated using a picture of an 8 oz. 7-day and 1-year recall. and mean and percentiles of self-fish meal; smaller meals were caught fish intake based on one year judged to be 5 oz., larger ones 10 recall. oz. Relevant Studies Connelly et al., 1992 1,030 anglers licensed in Survey mailed out in Jan. 1992; one Knowledge and effects of fish health Response rate of 52.8%; only New York year recall of the period Oct. 1990-advisories. Mean number of sport-number of fish mealsreported. Sept. 1991 caught fish meals. Fiore et al.; 1989 801 individuals with i 985 summer; mailed survey; one Mean number of sport caught fish Constant meal size assumed. Wisconsin fish or sporting year recall of sport fish meals of Wisconsin anglers. licenses consumption. Hudson River Sloop 336 shore-based anglers Survey conducted June-November Knowledge and adherance to health Data collected from personal Clearwater, Inc. 1991; April-July 1992. Onsite advsisories interviews; intake data not provided; 11993\ interview with analers fish meal data orovided. Table 10-86. Summarv of Fish Intake Studies (continued) Source of Data IReferencel Pooulation Surveved Survev Time PeriodfTvoe Analvses Performed rReferencesl Limitations/Advantaaes Native American Ke:t Studies CRITFC, 1994 Four tribes in Washington Fall and Winter of 1991-1992; stratified Mean and distribution of fish intake Survey was done at only one time of state; total of 513 adults random sampling approach; in-person rates for adults and for children. the year and involved one year recall; and 204 children under five interviews; information requested Mean intake rates by age and fish intake rates were based on all fish included 24-hour dietary recall, gender. Frequency of cooking and sources but great majority was locally seasonal and annual number of fish preparation methods. caught; study provides consumption meals, average weight of fish meals and habits for subsistence and species consumed. subpopulation group. Fitzgerald et al. 97 Mohawk women in New 1988-1992, up to 3-year recall Mean number of sport-caught fish Survey for nursing mothers only, recall 1995 York; 154 Caucasian meals per year. for up to 3 years; small sample size; women; nursing mothers may be representative of Mohawk women; measured in fish meals. Petersen et al., 327 residents of Chippewa Self-administered questionaire Mean number of fish meals per Did not distinguish between commercial 1994 reservation, Wisconsin completed in May, 1990. year. and sport-caught meals. Wolfe and Walker, Ninety-eight communities Surveys conducted between 1980 and Distribution among communities of Data based on 1-year recall; data 1987 in Alaska surveyed by 1985; data based on 1-year recall annual per-capita harvests for provided are harvest data that must be various researchers period. Annual per capita harvest of each resource category. converted to individual intake rates; fish, land mammals, marine mammals surveyed communities are only a and other resources estimated for sample of all Alaska communities. each communitv. ' NFMS -National Marine Fisheries Services. Table 10-87. Confidence in Fish Intake Recommendations for General Population Considerations Study Elements *D Level of peer review *D Accessibility Reproducibility *D Focus on factor of interest *D Data pertinent to U.S. *D Primary data *D Currency *D Adequacy of data collection period *D Validity of approach *D Study size *D Representativeness of the population *D Characterization of variability *D Lack of bias in study design (high rating is desirable) *D Measurement error Other Elements *D Number of studies *D Agreement between researchers Overall Rating Rationale Peer reviewed by USDA and EPA. CSFll data are publicly available. Javitz is a contractor report to EPA. Enough information is available to reproduce results. The studies focused on fish ingestion. The studies were conducted for U.S. population. The studies are primary studies. Studies were conducted from 1973-197 4 to 1989-1991. Long-term distribution are.based on one month data collection period. Data are collected using diaries and one-day recall. However, data adjusted to account for changes in eating pattern. The Range of samples was 10,000 -37,000. The data are representative of overall U.S. population. Long-term distribution (generated from 1973-1974 data) was shifted upward based on recent increase in mean consumption. Response rates were fairly high; there was no obvious source of bias. Estimates of intake amounts were imprecise. There was 1 study for the mean, the results of 2 studies were utilized for long-term distribution. Rating High High (CSFll) Medium (Javitz) High High High High Medium (mean) Low (Long-Term Distribution) High (Mean) Medium (Long-term distribution) Medium High High Medium High Medium Low Medium Medium (Mean) Low (Long-term distribution) Table 10-88. Confidence in Fish Intake Recommendations for Recreational Marine Anglers Considerations Rationale Rating Study Elements *D Level of peer review Data were reviewed by N_MFS and EPA. High *D Accessibility The analysis of the NMFS data is presented in the High Handbook and NMFS data can be found in NMFS publications. *D Reproducibility Enough information is available to reproduce results. High *D Focus on factor of interest Studies focused on fish catch rather than fish consumption Medium per se. *D Data pertinent to U.S. The studies were conducted in the U.S. High *D Primary data Data are from primary studies. High *D Currency The data were based on 1993 studies. High *D Adequacy of data collection period Data were collected once for each angler. The yearly catch Medium of anglers were estimated from catch on intercepted trip and reported fishing frequency. *D Validity of approach The creel survey provided data on fishing frequency and fish Medium weight; telephone survey data provided number of anglers. An average value was used for the number of intended fish -consumers and edible fraction. *D Study size Studies encompassed a population of over 100,000. High *D Representativeness of the Data were representative of overall U.S. coastal state High population population. *D Characterization of variability Distributions were generated. High *D Lack of bias in study design (high Response rates were fairly high; There was no obvious High rating is desirable) source of bias. *D Measurement error Fish were weighed in the field. High Other Elements *D Number of studies There was 1 study. Low *D Agreement between researchers N/A Overall Rating Medium Table 10-89. Confidence in Recommendations for Fish Consumption -Recreational Freshwater Considerations Study Elements *D Level of peer review *D Accessibility *D Reproducibility *D Focus on factor of interest *D Data pertinent to U.S. *D Primary data *D Currency *D Adequacy of data collection period *D Validity of approach *D Study size *D Representativeness of the. population *D Characterization of variability *D Lack of bias in study design (high rating is desirable) *D Measurement error Other Elements *D Number of studies *D Agreement between researchers Overall Rating Rationale Rating Studies can be found in peer reviewed journals and has High been reviewed by the EPA. The original study analyses are reported in accessible High journals. Subsequent EPA analyses are detailed in Handbook. Enough information is available to reproduce results. High Studies focused on ingestion of fish by the recreational High freshwater angler.

The studies were conducted in the U.S. High Data are from primary references. High Studies were conducted between 1988-1992. High Data were collected for one year period for 3 studies; and a High one week period for one study. Data presented are as follows: one year recall of fishing trips Medium (2 studies), one week recall offish consumption (1 study), and one year diary survey ( 1 study). Weight offish consumed was estimated using approximate weight of fish catch and edible fraction or approximate weight of fish meal. Study population ranged from 800-2600. High Each study was localized to a single state or area. Low Distributions were generated. High Response rates were fairly high. One year recall of fishing Medium trips may result in overestimate. Weight offish portions were estimated in one study, fish Medium weight was estimated from reported fish length in another study. There are 4 key studies. Intake rates in different parts of country may be expected to show some variation. The main drawback is that studies are not nationally representative and not representative of long-term consumption. High Medium Medium Table 10-90. Confidence in Recommendations for Native American Subsistence Fish Consumption Considerations Study Elements *D Level of peer review *D Accessibility *D Reproducibility *D Focus on factor of interest *D Data pertinent to U.S. *D Primary data *D Currency *D Adequacy of data collection period *D Validity of approach *D Study size *D Representativeness of the population *D Characterization of variability *D Lack of bias in study design (high rating is desirable) *D Measurement error Other Elements *D Number of studies *D Agreement between researchers Overall Rating Rationale Studies are from peer reviewed journal (1 study), and technical reports (1study). Journal articles are publicly available. CRITFC is a technical report. The studies were adequately detailed. Studies focused on fish ingestion and fish harvest. All studies were specific to area in the U.S. One study used primary data, the other used secondary data. Data were from early 1980's to 1992. Data collected for one year period. .One study used fish harvest data; EPA used a factor to convert to individual intake. Other study measured individual intake directly. The sample population was 500 for the study with primary data.
Only two states were represented. Individual variation were not described in summary study. The response rate was 69% in study with primary data. Bias was hard to evaluate in summary study. The weight of the fish was estimated. There were two studies; only one study described individual variation in intake. Range of per-capita rates from summary study includes per-capita rate from study with primary data. Studies are not nationally representative. Upper percentiles are based on only one study. Rating Medium Medium High High High Medium Medium High Medium Medium Low Medium Medium Medium High Medium (per capita intake) Low (upper percentiles)

Table 1 OB-1. Percent of Fish Meals Prepared Usinq Various Cookinq Methods by Residence Size' Large Rural Non-Residence Size City/Suburb Small City Town Small Town Fami Fa mi Total Fish Cooking Method Pan Fried 32.7 31.0 36.0 32.4 38.6 51.6 Deep Fried 19.6 24.0 23.3 24.7 26.2 15.7 Boiled 6.0 3.0 3.4 3.7 3.4 3.5 Grilled/Broiled 23.6 20.8 13.8 21.4 13.7 13.1 Baked . 12.4 12.4 10.0 10.3 12.7 6.4 Combination 2.5 6.0 8.3 5.0 2.3 7.0 Other (Smoked, etc.) 3.2 2.8 5.2 1.9 2.9 1.8 Don't Know 0.0000 0.0000 0.0000 0.5 0.2 --Total (N)b 393 317 388 256 483 94 Sport Fish Pan Fried 45.8 45.7 47.6 41.4 51.2 63.3 Deep Fried 12.2 14.5 17.5 15.2 21.9 7.3 Boiled 2.8 2.3 2.9 0.5 3.6 0 Grilled/Broiled 20.2 17.6 10.6 25.3 8.2 10.4 Baked 11.8 8.8 6.3 8.7 9.7 6.9 Combination 2.7 8.5 10.4 6.7 1.9 9.3 Other (smoked, etc.) 4.5 2.7 4.9 1.5 3.5 2.8 Don't Know 0 0 0 0.7 0 0 Total IN\ 205 171 257 176 -314 62 ' Large City= over 100,000; Small City= 20,000-100,000; Town= 2,000-20,000; Small Town= 100-2,000. b N =Total number of respondents Source: West et al. 1993. Table 108-2. Percent of Fish Meals Preoared Usina Various Cookino Methods bv Aqe Age (years) 17-30 31-40 41-50 51-64 >64 Overall Total Fish Cooking Method Pan Fried 45.9 31.7 30.5 33.9 40.7 35.3 Deep Fried 23.0 24.7 26.9 23.7 14.0 23.5 Boiled 0.0000 6.0 3.6 3.9 4.3 3.9 Grilled or Boiled 15.6 15.2 24.3 16.1 18.8 17.8 Baked 10.8 13.0 8.7 12.8 11.5 11.4 Combination 3.1 5.2 2.2 6.5 6.8 4.7 Other (Smoked, etc.) 1.6 4.2 3.5 2.7 4.0 3.2 Don't Know 0.0000 0.0000 0.3 0.4 0.0000 0.2 Total (N)' 246 448 417 502 287 1946 Sport Fish Pan Fried 57.6 42.6 43.4 46.6 54.1 47.9 Deep Fried 18.2 21.0 17.3 14.8 7.7 16.5 Boiled 0.0000 4.4 0.8 3.2 3.1 2.4 Grilled/Broiled 15.0 10.1 25.9 12.2 12.2 14.8 Baked 3.6 10.4 6.4 11.7 9.9 8.9 Combination 3.8 7.2 3.0 7.5 8.2 5.9 Other (Smoked, etc.) 1.7 4.3 3.2 3.5 4.8 3.5 Don't Know 0.0000 0.0000 0.0000 0.4 0.0000 0.1 Total IN\ 174 287 246 294 163 1187 'N =Total number of respondents. Source: West et al. 1993. Table 10B-3. Percent of Fish Meals Precared Usinq Various Cookinq Methods bv Ethnicitv Ethnicitv Black Native American Hiscanic White Other Total Fish Cooking Method Pan Fried 40.5 37.5 16.1 35.8 18.5 Deep Fried 27.0 22.0 83.9 22.7 18.4 Boiled 0 1.1 0 4.3 0 Grilled/Broiled 19.4 9.8 0 17.7 57.6 Baked 1.9 16.3 0 11.7 5.4 Combination 9.5 6.2 0 4.5 0 Other (Smoked, etc.) 1.6 4.2 3.5 2.7 4.0 Don't Know 0 0 0.3 0.4 0 Total (N)' 52 84 12 1,744. 33 Sport Fish Pan Fried 44.9 47.9 52.1 48.8 22.0 Deep Fried 36.2 20.2 47.9 15.7 9.6 Boiled 0 0 0 2.7 0 Grilled/Broiled 0 1.5 0 14.7 61.9 Baked 5.3 18.2 0 8.6 6.4 Combination 13.6 8.6 0 5.6 0 Other (Smoked, etc.) 0 3.6 0 3.7 0 Total IN) 19 60 4 39 0 ' N =Total number of respondents. Source: West et al. 1993. Table 1 OB-4. Percent of Fish Meals Prepared Usinq Various Cookinq Methods by Education Post Graduate Education Throuqh Some H.S. H.S. Degree College Deqree Education Total Fish Cooking Method Pan Fried 44.7 41.8 28.8 22.9 Deep Fried 23.6 23.6 23.8 19.4 Boiled 2.2 2.8 5.1 5.8 Grilled/Broiled 8.9 10.9 23.8 34.1 Baked 8.1 12.1 11.6 12.8 Combination 10.0 5.1 3.0 3.8 Other (Smoked, etc.) 2.1 3.4 4.0 1.3 Don't Know 0.5 0.3 0 0 Total (N)8 236 775 704 211 Sport Fish Pan Fried 56.1 52.4 41.8 36.3 Deep Fried 13.6 15.8 18.6 12.9 Boiled 2.8 2.4 3.0 0 Grilled/Baked 6.3 9.4 21.7 28.3 Baked 7.4 10.6 6.1 14.9 Combination 10.1 6.3 3.9 6.5 Other (Smoked, etc.) 2.8 3.3 4.6 1.0 Don't Know 0.8 0 0 0 Total !N\ 146 524 421 91

N =Total number of respondents. Source: West et al. 1993.

Table 10B-5. Percent of Fish Meals Prepared Using Various Cookino Methods bv Income Income 0-$24,999 $25,000 -$39,999 $40,000 -or more Total Fish Cooking Method Pan Fried 44.8 39.1 26.5 Deep Fried 21.7 22.2 23.4 Boiled 2.1 3.5 5.6 Grilled/Broiled 11.3 15.8 25.0 Baked 9.1 12.3 13.3 Combination 8.7 2.9 2.5 Other (Smoked, et.c.) 2.4 4.0 3.5 Don't Know 0 0.2 0.3 Total (N)a 544 518 714 Sport Fish Pan Fried 51.5 51.4 42.0 Deep Fried 15.8 15.8 17.2 Boiled 1.8 2.1 3.7 Grilled/Broiled 12.0 12.2 19.4 Baked 7.2 10.0 10.0 ' Combination 9.1 3.8 3.5 Other (Smoked, etc.) 2.7 4.6 3.8 Don't Know 0 0 0.3 Total(N\ 387 344 369

N =Total number of respondents. Source: West et al. 1993. v /

Table 1 OB-6. Percent of Fish Meals Where Fat was Trimmed or Skin was Removed, by DemoQraphic Variables Total Fish Sport Fish Pooulation Trimmed Fat 1%) Skin Off(%) Trimmed Fat!% l Skin Off!%l Residence Size Large City/Suburb 51.7 31.6 56.7 28.9 Small City 56.9 34.1 59.3 36.2 Town 50.3 33.4 . 51.7 33.7 Small Town 52.6 45.2 55.8 51.3 Rural Non-Farm 42.4 32.4 46.2 34.6 Farm 37.3 38.1 39.4 42.1 6gg(years) 17-30 50.6 36.5 53.9 39.3 31-40 49.7 29.7 51.6 29.9 41-50 53.0 32.2 58.8 37.0 51-65 48.1 35.6 48,8 37.2 Over65 41.6 43.1 43.0 42.9 Ethnicity Black 25.8 37.1 16.0 40.1 Native American 50.0 41.4 56.3 36.7 Hispanic 59.5 7.1 50.0 23.0 White 49.3 34.0 51.8 35.6 Other 77.1 61.6 . 75.7 65.5 Education Some High School. 50.8 43.9 49.7 47.1 High School Degree 47.2 37.1 49.5 37.6 College Degree 51.9 31.9 55.9 33.8 Post-Graduate 47.6 26.6 53.4 38.7 Income <$25,000 50.5 43.8 50.6 47.3 $25-39,999 47.8 34.0 54.9 34.6 $40,000 or more 50.2 28.6 51.7 27.7 Overall 49.0 34.7 52.1 36.5 Source: Modified from West et. al. 1993. Table 1 OB-7. Method of Cooking of Most Common Species Kept by Sportfishermen *species Percent of Anglers Use as Primary Cooking Method (Percent) Catching Species Deep Fry Pan Fry Bake and Charcoal Raw Other" Broil White Croaker 34% 19% 64% 12% 0% 5% Pacific Mackerel 25% 10% 41% 28% 0% 21% Pacific Bonito 18% 5% 33% 43% 2% 17% Queenfish 17% 15% 70% 6% 1% 8% Jacks melt 13% 17% 57% 19% 0% 7% Walleye Perch 10% 12% 69% 6% 0% 13% Shiner Perch 7% 11% 72% 8% 0% 11% Opaleye 6% 16% 56%. 14% 0% 14% Black Perch 5% 18% 53% 14% 0% 15% Kelp Bass 5% 12% 55% 21% 0% 12% California Halibut 4% 13% 60% 24% 0% 3% Shellfish' 3% 0% 0% '0% 0% 100% (n = 1059) ' Crab, mussels, lobster, abalone b Boil, soup, steam, stew Source: Modified from Puffer et al., 1981. Table 1 OB-8. Adult Consumption of Fish Parts Weighted Percent Consuming Spei:ific Parts Number Species Consuming Fillet Skin Head Eggs Bones Organs Salmon 473 95.1% 55.8% 42.7% 42.8% 12.1% 3.7% Lamprey 249 86.4% 89.3% 18.1% 4.6% 5.2% 3.2% Trout 365 89.4% 68.5% 13.7% 8.7% 7.1% 2.3% Smelt 209 78.8% 88.9% 37.4% 46.4% 28.4% 27.9% Whitefish 125 93.8% 53.8% 15.4% 20.6% 6.0% 0.0% Sturgeon 121 94.6% 18.2% 6.2% 11.9% 2.6% 0.3% Walleye 46 100% 20.7% 6.2% 9.8% 2.4% 0.9% Squawfish 15 89.7% 34.1% 8.1% 11.1% 5.9% 0.0% Sucker 42 89.3% 50.0% 19.4% 30.4% 9.8% 2.1% Shad 16 93.5% 15.7% 0.0% 0.0% 3.3% 0.0% Source: CRITFC, 1994. Table 10C-1. Daily Average Per Capita Estimates of Fish Consumption U.S. Population -Mean Consumption by Species Within Habitat -As Consumed Fish Estimated Mean Estimated Mean Estimated Mean Habitat Species Grams/Person/Day Habitat Species Grams/Person/Day Habitat Species Grams/Person/Day Estuarine Shrimp 1.37241 Marine Swordfish 0.13879 All Species Flounder 0.24590 Perch 0.52580 (Cont) Squid 0.12196 (Cont) Scallop (Marine) 0.21805 Flatfish (Estuarine) 0.43485 Sardine 0.10013 Sea Bass 0.20794 Crab (Estuarine) 0.29086 Pompano 0.09131 Lobster 0.20001 Flounder 0.24590 Sole 0.07396 Oyster 0.17840 Oyster 0.17840 Mackerel 0.06379 Clam (Estuarine) 0.14605 Clam (Estuarine) 0.14605 Whiting 0.05498 Swordfish 0.13879 Mullet 0.07089 Halibut 0.02463 Squid 0.12196 Croaker 0.05021 Mussels 0.02217 Sardine 0.10313 Herring 0.02937 Shark 0.01901 Pompano 0.09131 Smelts 0.02768 Whitefish 0.00916 Sole 0.07396 Scallop (Estuarine) 0.00247 Seafood 0.00574 Mullet 0.07089 Anchovy 0.00228 Snapper 0.00539 Mackarel 0.06379 Scup 0.00050 Octopus 0.00375 Whiting 0.05498 Sturgeon 0.00040 Barracuda 0.00111 Croaker 0.05021 Abalone 0.00075 Carp 0.04846 Freshwater Catfish 1.06776 Herring 0.02937 Trout 0.43050 Unknown Fish 0.00186 Smelts 0.02768 Carp 0.04846 Halibut 0.02463 Pike 0.01978 All Tuna 4.19998 Mussels 0.02217 Salmon (Freshwater) 0.00881 Species Clam (Marine) 1.66153 Pike 0.01978 Shrimp 1.38883 Shark 0.01901 Marine Tuna 4.19998 Cod 1.22827 Whitefish 0.00916 Clam (Marine) 1.66153 Catfish 1.06776 Salmon (Freshwater) 0.00881 Cod 1.22627 Faltfish (Marine) 1.06307 Seafood 0.00574 Flatfish (Marine) 1.06307 Salmon (Marine) 0.73778 Snapper 0.00539 Salmon (Marine) 0.73778 Perch 0.52580 Octopus 0.00375 Haddock 0.51533 Haddock 0.51533 Scallop (Estuarine) 0.00247 Pollock 0.44970 Pollock 0.44970 Anchovy 0.00228 Crab (Marine) 0.33870 Flatfish (Estuarine) 0.43485 Fish 0.00166 Ocean Perch 0.31878 Trout 0.43050 Barracuda 0.00111 Porgy 0.29844 Crab (Marine) 0.33870 Abalone 0.00075 Scallop (Marine) 0.21805 Ocean Perch 0.31878 Scup 0.00050 Sea Bass 0.20794 Porgy 0.29844 Sturgeon 0.00040 Lobster 0.20001 Crab (Estuarine) 0.29088 Notes: Estimates are projected from a sample of 11,912 individuals to the U.S. population of 242,707,000 using 3-year combined survey weights. The population for this survey consisted of individuals in the 48 conteminous states. Source of individual consumption data: USDA Combined 1989, 1990, and 1991 Continuing Survey of Food Intakes by Individuals (CSFll). The fish component of foods containing fish was calculated using data from the recipe file for release 7 of the USDA's Nutrient Data Base for Individual Food Intake Surveys. Table 1 OC-2. Daily Average Per Capita Estimates of Fish Consumption U.S. Population -Mean Consumption by Species Within Habitat-Uncooked Fish Estimated Mean Estimated Mean Estimated Mean Habitat Species Grams/Person/Day Habitat Species Grams/Person/Day Habitat Species Grams/Person/Day Estuarine Shrimp 1.78619 Marine Swordfish 0.17903 All Species Flounder 0.28559 Perch 0.66494 (Cont) Squid 0.14420 (Cont) Lobster 0.27563 Flatfish (Estuarine) 0.50832 Sardine 0.13750 Sea Bass 0.26661 Crab (Estuarine) 0.40848 Pompano 0.12160 Scallop (Marine) 0.26199 Flounder 0.28559 Mackerel 0.09866 Oyster 0.18827 Oyster 0.18827 Sole 0.08339 Swordfish 0.17903 Mullet 0.08959 Whiting 0.06514 Squid 0.14420 Croaker 0.06539 Mussels 0.03718 Sardine 0.13750 Smelts 0.03470 Halibut 0.03030 Pompano 0.12160 Herring 0.03408 Shark 0.02385 Mackarel 0.09866 Clam (Estuarine) 0.03339 Whitefish 0.00916 Mullet 0.08958 Anchovy 0.00304 Snapper 0.00551 Sole 0.08339 Scallop (Estuarine) 0.00297 Octopus 0.00457 Croaker 0.06539 Scup 0.00050 Barracuda 0.00130 Whiting 0.06514 Sturgeon 0.00040 Abalone 0.00094 Carp 0.06012 Seafood 0.00043 Mussels 0.03718 Freshwater Catfish 1.38715 Smelts 0.03470 Trout 0.53777 Unknown Fish 0.00248 Herring 0.03406 Carp 0.06012 Clam (Estuarine) 0.03339 Pike 0.02244 All Tuna 5.67438 Halibut 0.03030 Salmon (Freshwater) 0.01183 Species Shrimp 1.78619 Shark 0.02385 Cod 1.47609 Pike 0.02244 Marine Tuna 5.67438 Catfish 1.38715 Salmon (Freshwater) 0.01183 Cod 1.47609 Flatfish (Marine) 1.24268 Whitefish 0.00916 Flatfish (Marine) 1.24268 Salmon (Marine) 0.99093 Snapper 0.00551 Salmon (Marine) 0.99093 Perch 0.66494 Octopus 0.00457 Haddock 0.62219 Haddock 0.62219 Anchovy 0.00304 Pollock 0.52906 Trout 0.53777 Scallop (Estuarine) 0.00297 Crab (Marine) 0.47567 Pollock 0.52906 Fish 0.00248 Porgy 0.42587 Flatfish (Estuarine) 0.50832 Barracuda 0.00130 Ocean Perch 0.39327 Crab (Marine) 0.47567 Abalone 0.00094 Clam (Marine) 0.37982 Porgy 0.42587 Scup 0.00050 Lobster 0.27583 Crab (Estuarine) 0.40848 Seafood 0.00043 Sea Bass 0.26661 Ocean Perch 0.39327 Sturgeon 0.00040 Scallop (Marine) 0.26199 Clam (Marine) 0.37982 Notes: Estimates are projected from a sample of 11,912 individuals to the U.S. population of 242,707,000 using 3-year combined survey weights. The population for this survey consisted of individuals in the 48 conteminous states. Source of individual consumption data: USDA Combined 1989, 1990, and 1991 Continuing Survey of Food Intakes by Individuals (CSFll). Amount of consumed fish recorded by survey respondents was converted to uncooked fish quantities using data from the recipe file for release 7 of USDA's Nutrient Data Base for Individual Food Intake Surveys. The fish component of foods containing fish was calculated using data from the recipe file for release 7. of the USDA's Nutrient Data Base for Individual Food Intake Surveys. Table 10C-3. Daily Average Per Capita Estimates Of Fish Consumption As Consumed Fish -Mean Consumption by Species Within Habitat U.S. Population Estimated Estimated Estimated Habitat Species Mean Habitat Species Mean Habitat Species Mean Grams/person/day Grams/oerson/dav Grams/person/day Estuarine Shrimp 1.37241 Marine (Con't.) Swordfish 0.13879 All Species Flounder 0.24590 Perch 0.52580 Squid 0.12196 (Con't.) Scallop (Marine) 0.21805 Flatfish 0.43485 Sardine 0.10313 Sea Bass 0.20794 Crab 0.29086 Pompano 0.09131 Lobster 0.20001 Flounder 0.24590 Sole 0.07396 Oyster 0.17419 Oyster 0.17419 Mackerel 0.06379 Swordfish 0.13879 Mullet 0.07089 Whiting 0.05498 Squid 0.12196 Croaker 0.05021 Halibut 0.02463 Sardine 0.10313 Herring 0.02937 Mussels 0.02217 Pompano 0.09131 Smelts 0.02768 Shark 0.01901 Sole 0.07396 Clam 0.02691 Whitefish 0.00916 Mullet 0.07089 Scallop 0.00247 Snapper 0.00539 Mackerel 0.06379 Anchovy 0.00228 Octopus 0.00375 Whiting 0.05498 Scup 0.00050 Barracuda 0.00111 Croaker 0.05021 Sturgeon 0.00040 Abalone 0.00075 Carp 0.04846 Seafood 0.00043 Herring 0.02937 Freshwater Catfish 1.06776 Smelts 0.02768 Trout 0.43050 Unknown Fish 0.00186 Clam (Estuarine) 0.02691 Carp 0.04846 Halibut 0.02463 Pike 0.01978 All Species Tuna 4.19998 Mussels 0.02217 Salmon 0.00881 Shrimp 1.37241 Pike 0.01978 Cod 1.22827 Shark 0.01901 Marine Tuna 4.19998 Catfish 1.06776 Whitefish 0.00916 Cod 1.22827 Flatfish (Marine) 1.06307 Salmon (Freshwater) 0.00881 Flatfish 1.06307 Salmon (Marine) 0.73778 Snapper 0.00539 Salmon 0.73778 Perch 0.52580 Octopus 0.00375 Haddock 0.51533 Haddock 0.51533 Scallop (Estuarine) 0.00247 Pollock 0.44970 Pollock 0.44970 Anchovy 0.00228 Crab 0.33870 Flatfish (Estuarine) 0.43485 Fish 0.00186 Ocean Perch 0.31878 Trout 0.43050 Barracuda 0.00111 Clam 0.30617 Crab (Marine) 0.33870 Abalone 0.00075 Porgy 0.29844 Ocean Perch 0.31878 Scup 0.00050 Scallop 0.21805 Clam (Marine) 0.30617 Seafood 0.00043 Sea Bass 0.20794 Porgy 0.29844 Sturgeon 0.00040 Lobster 0.20001 Crab (Estuarine) 0.29086 Estimates are projected from a sample of 11,912 individuals to the U.S. population of 242,707,000 using 3-year combined survey weights. Source: U.S. EPA 1996a. Table 1 OC-4. Daily Average Per Capita Estimates Of Fish Consumption Uncooked Fish** -Mean Consumption by Species Within Habitat U.S. Pooulation Estimated Estimated Estimated Habitat Species Mean Habitat Species Mean Habitat Species Mean Grams/oerson/day Grams/person/day Grams/person/day Estuarine Shrimp '1.78619 Marine (Con'!.) Swordfish 0.17903 All Species Flounder 0.28559 Perch 0.66494 Squid 0.14420 (Con'!.) Lobster 0.27563 Flatfish 0.50832 Sardine 0.13750 Sea Bass 0.26661 .Crab 0.40848 Pompano 0.12160 Scallop (Marine) 0.26199 Flounder 0.28559 Mackerel 0.09866 Oyster 0.18827 Oyster 0.18827 Sole 0.08339 Swordfish 0.17903 Mullet 0.08958 Whiting 0.06514 Squid 0.14420 Croaker 0.06539 Mussels 0.03718 Sardine 0.13750 Smelts 0.03470 Halibut 0.03030 Pompano 0.12160 Herring 0.03408 Shark 0.02385 Mackerel 0.09866 Clam 0.03339 Whitefish 0.00916 Mullet 0.08958 Anchovy 0.00304 Snapper 0.00551 Sole 0.08339 Scallop 0.00297 Octopus 0.00457 Croaker 0.06539 Scup 0.00050 Barracuda 0.00130 Whiting 0.06514 Sturgeon 0.00040 Abalone 0.00094 . Carp 0.06012 Seafood 0.00043 Mussels 0.03718 Freshwater Catfish 1.38715 Smelts 0.03470 Trout 0.53777 Unknown Fish 0.00248 Herring 0.03408 Carp 0.06012 Clam (Estuarine) 0.03339 Pike 0.02244 All Species Tuna 5.67438 Halibut 0.03030 Salmon 0.01183 Shrimp 1.78619 Shark 0.02385 Cod 1.47609 Pike 0.02244 Marine Tuna 5.67438 Catfish 1.38715 Salmon (Freshwater) 0.01183 Cod 1.47609 Flatfish (Marine) 1.24268 Whitefish 0.00916 Flatfish 1.24268 Salmon (Marine) 0.99093 Snapper 0.00551 Salmon 0.99093 Perch 0.66494 Octopus 0.00457 Haddock 0.62219 Haddock 0.62219 Anchovy 0.00304 Pollock 0.52906 Trout 0.53777 Scallop (Estuarine) 0.00297 Crab 0.47567 Pollock* 0.52906 Fish 0.00248 Porgy 0.42587 Flatfish (Estuarine) 0.50832 Barracuda 0.00130 Ocean Perch 0.39327 Crab (Marine) 0.47567 Abalone 0.00094 Clam 0.37982 Porgy 0.42587 Scup 0.00050 Lobster 0.27563 Crab (Estuarine) 0.40848 Seafood 0.00043 Sea Bass 0.26661 Ocean Perch 0.39327 Sturgeon 0.00040 Scallop 0.26199 Clam (Marine) 0.37982 Estimates are projected from a sample of 11,912 individuals to the U.S. population of 242, 707,000 using 3-year combined survey weights. Source: U.S. EPA 1996a. 0 Jan Feb Mar AJir May Jun Jul Aug Sep Oct Nov Dec . Month

Panlclpants ccul.d list mare than one month. Figure 10-1. Seasonal Fish Consumption: Wisconsin Chippewa, 1990 10 0 0 _During those months of the year when you nt tile most 1istl.. how many fish meals do you eat in a weelt1 . 2 3 5 6 7 Figure 10-2. Peak Fish Consumption: Wisconsin Chippewa, 1990 Source: Peterson et al., 1994.

REFERENCES FOR CHAPTER 10 American Industrial Hygiene Council (AIHC) (1994) Exposure factors sourcebook. AIHC, Washington, DC. Chem Risk (1992) Consumption of freshwater fish by Maine anglers. A Technical Report. Portland, ME: ChemRisk, A Division of Melaren I Hart. Revised July 24, 1994. Columbia River Inter-Tribal Fish Commissi.on (CRITFC). (1994) A fish consumption . survey of the Umatilla, Nez Perce, Yakama and Warm Springs tribes of the Columbia River Basin. Technical* Report 94-3. Portland, OR: CRIFTC. Connelly, N.A.; Knuth, B.A.; Bisogni, C.A. (1992) Effects of the health advisory and advisory changes on fishing habits and fish consumption in New York sport fisheries. Human Dimension Research Unit, Department of Natural Resources, New York State College of Agriculture and Life Sciences, Fernow Hall,' Cornell University, Ithaca, NY. Report for the New York Sea Grant Institute Project No. R/FHD-2-PD. September. Connelly, N.A.; Knuth, B.A.; Brown, T.L. (1996) Sportfish consumption patterns of Lake Ontario anglers and the relationship to health advisories. N. Am. J. Fisheries Management, 16:90-101. Ebert, E.; Harrington, N.; .Boyle, K.; Knight, J.; Keenan, R. (1993) Estimating consumption of freshwater fish among Maine anglers. N. Am. J. Fisheries Management 13:737-745. Fiore, B.J.; Anderson, H.A.; Hanrahan, L.P.; Olsen, L.J.; Sorizogni, W.C. (1989) Sport fish consumption and body burden levels of chlorinated hydrocarbons: A study of Wisconsin anglers. Arch. Environ. Health 44:82-88. Fitzgerald, E.; Hwang, S.A.; Briz, K.A.; Bush, B.; Cook, K.; Worswick, P. (1995) Fish PCB cbncentrations and consumption patterns among Mohawk women at Akwesasne. J. Exp. Anal. Environ. Epid. 5(1):1-19. Hudson River Sloop Clearwater, Inc. (1993) Hudson River angler survey. Hudson River Sloop Clearwater, Inc., Poughkeepsie, NY. Javitz, H. (1980) Seafood consumption data analysis. SRI International. Final report prepared for EPA Office of Water Regulations and Standards. EPA Contract 68-01-3887. National Marine Fisheries Service (NMFS). (1986a) Fisheries of the United States, 1985. Current Fisheries Statistics No. 8368. U.S. Department of Commerce. National Oceanic and Atmospheric Administration. National Marine Fisheries Service (NMFS). (1986b) National Marine Fisheries Service. Marine Recreational Fishery Statistics Survey, Atlantic and Gulf Coasts, 1985. Current Fisheries Statistics No. 8327. U.S. Department of Commerce, National Oceanic and Atmospheric Administration. National Marine Fisheries Service (NMFS). (1986c) National Marine Fisheries Service. Marine Recreational Fishery Statistics Survey, Pacific Coast. Current Fisheries Statistics No. 8328. U.S. Department of Commerce, National Oceanic and Atmospheric Administration. National Marine Fisheries Service (NMFS). (1993) Data tapes for the 1993 NMFS provided to U.S. EPA, National Center for Environmental Assessments. Pao, E.M.; Fleming, K.H.; Guenther, P.M.; Mickle, S.J. (1982) Foods commonly eaten by individuals: amount per day and per eating occasion. U.S. Department of Agriculture. Home Economics Report No. 44. Peterson, D.; Kanarek, M.; M.; Diedrich, J.; Anderson, H.; Remington, P.; Sheffy, T. (1994) Fish consumption patterns and blood mercury levels in Wisconsin Chippewa .Indians. Archives. Environ. Health, 49:53-58. Pierce, R.S.; Noviello, D*.T.; Rogers, S.H. (1981) Commencement Bay seafood consumption report. Preliminary report. Tacoma, WA: Tacoma-Pierce County Health Department. Price, P.; Su, S.; Gray, M. (1994) The effects of sampling bias on estimates of angler consumption rates in creel surveys. Portland, ME: ChemRisk. Puffer, H.W., Azen, S.P.; Duda, M.J.; Young, D.R. (1981) Consumption rates of potentially hazardous marine fish caught in the metropolitan Los Angeles area. EPA Grant #R807 120010. Ruffle, B.; Burmaster, D.; Anderson, P.; Gordon, D. (1994) Lognormal distributions for fi*sh consumption by the general U.S. population. Risk Analysis 14(4):395-404. Rupp, E.; Miler, F .L.; Ba es, C.F. 111. ( 1980) Some results of recent surveys of fish and shellfish consumption by age and region of U.S. residents. Health Physics 39:165-175. San Diego County. (1990) San Diego Bay health risk study. San Diego, CA. San Diego County Department of Health Services. Tsang, A.M.; Klepeis, N.E. (1996) Results tables from a detailed analysis of the National Human Activity Pattern Survey (NHAPS) response. Draft Report prepared for the

U.S. Environmental Protection Agency by Lockheed Martin, Contract No. 68-W6-001, Delivery Order No. 13. USDA. (1979-1984) Agricultural Handbook No. 8. USDA. (1989-1991) Continuing Survey of Food Intakes by Individuals (CSFll). U.S. Department of Agriculture. USDA. (1992a) Changes in food consumption and expenditures in American households during the 1980's. U.S. Department of Agriculture. Washington, D.C. Stqtistical Bulletin No. 849. USDA. (1992b) U.S. Department of Agriculture, Human Nutrition Information Service.
Food and nutrient intakes by individuals in the United States, 1 day, 1987-88: Nationwide Food Consumption Survey 1987-88, NFCS Rpt. No. 87-1-1, in preparation. USDA. (1996a) Data tables: results from USDA's 1994 Continuing Survey of Food Intakes by Individuals and 1994 Diet and Health Knowledge Survey. U.S. Department of Agriculture, Agricultural Research Service, Riverdale, MD. USDA. ( 1996b) Data tables: results from USDA's 1995. Continuing Survey of Food Intakes by Individuals and 1995 Diet and Health Knowledge Survey. U.S. Department of Agriculture; Agricultural Research Service, Riverdale, MD. U.S. DHHS. (1995) Final Report: Health study to assess the human health effects of mercury exposure to fish consumed from the Everglades. Prepared by the Florida Department of Health and Rehabilitative Services for the U.S. Department of Health and Human Services, Atlanta, Georgia. PB95-167276. U.S. EPA. (1984) Ambient water quality criteria for 2,3,7,8-tetrachloro-dibenzo-p-dioxin. Washington, DC: Office of Water Regulations and Standards. EPA 440/5-84-007. U.S. EPA. (1989a) Exposure factors handbook. Washington, DC: Office of Health and Environmental Assessment, U.S. EPA. (1989b) Assessing human health risks from chemically contaminated fish and shellfish: a guidance manual. Washington, DC: Office of Marine and Estuarine Protection. EPA 503/8-89-002. U.S. EPA. (1992) Consumption surveys for fish and shellfish; a review and analysis of survey methods. Washington, DC: Office of Water. EPA 822/R-92-001.

U.S. EPA. (1995) Fish consumption estimates based on the 1991-92 Michigan sport anglers fish consumption study. Final Report. Prepared by SAIC for the Office of Science and Technology. U.S. EPA. (1996a) Daily average per capita fish consumption estimates based on the combined USDA 1989, 1990 and 1991 continuing survey of food intakes by individuals (CSFll) 1989-91 data. Volumes I and II. Preliminary Draft Report. Washington, DC: Office of Water. U.S. EPA. (1996b) Estimating exposure to dioxin-like compounds. (Draft). Washington, DC: Office of Research and Development, National Center for Environmental Assessment. West, P.C.; Fly, M.J.; Marans, R.; Larkin, F. (1989) Michigan sport anglers fish consumption survey. A report to the Michigan Toxic Substance Control Commission. Michigan Department of Management and Budget Contract No. 8720141. West, P.C.; Fly, J.M.; Marans, R.; Larkin, F.; Rosenblatt, D. (1993) 1991-92 Michigan sport anglers fish consumption study. Prepared by the University of Michigan, School of Natural Resources for the Michigan Department of Natural Resources, Ann Arbor, Ml. Technical Report No. 6. May. Wolfe, R.J.; Walker, R.J. (1987) Subsistence economies in Alaska: productivity, geography, and development impacts. Arctic Anthropology 24(2):56-81. DOWNLOADABLE TABLES FOR CHAPTER 10 The following selected tables are available for download as Lotus 1-2-3 worksheets. Table 10-3. Percent Distribution of Total Fish Consumption for Females by Age * [WK1, 3 kb] Table 10-4. Percent Distribution of Total Fish Consumption for Males by Age [WK1, 3 kb] . Table 10-7. Per Capita Distribution of Fish Intake (g/day) by Habitat and Fish Type for the U.S. Population (Uncooked Fish Weight) * [WK1, 2 kb] Table 10-8. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) by Habitat for Consumers Only (Uncooked Fish Weight) [WK1, 2 kb] Table 10-9. Per Capita Distribution of Fish Intake (mg/kg-day) by Habitat and Fish Type for U.S. Population (Uncooked Fish Weight) . [WK1, 2 kb] Table 10-10. Per Capita Distribution of Fish .(Finfish and Shellfish) Intake (mg/kg-day) by Habitat for Consumers Only (Uncooked Fish Weight) [WK1, 2 kb] Table 10-11. Capita Distribution of Fish Intake (g/day) by Habitat and Fish Type for the U.S. Population (Cooked Fish Weight -As Consumed) [WK1, 2 kb] Table 10-12. Per Capita Distribution of Fish Intake (g/day) by Habitat for Consumers Only (Cooked Fish Weight -As Consumed) * [WK1, 2 kb] Table 10-13. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the U.S. Population by Age and Gender-As Consumed (Freshwater and Estuarine) [WK1, 2 kb] Table 10-14. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the U.S. Population by Age and Gender -As Consumed (Marine) [WK1, 2 kb] Table 10-15. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the U.S. Population by Age and Gender-As Consumed (All Fish) [WK1, 2 kb]

Table 10-16. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (grams/day) for the U.S. Population Aged 18 Years and Older by Habitat-As Consumed [WK1, 2 kb] Table 10-17. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the U.S. Population by Age and Gender -As Consumed (Freshwater and Estuarine) [WK1, 2 kb] Table 10-18. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the U.S. Population by Age and Gender-As Consumed (Marine) [WK1, 2.kb]

Table 10-19. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the U.S. Population by Age and Gender-As Consumed (All Fish) [WK1, 3 kb] Table 10-20. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) . for the U.S. Population Aged 18 Years and Older by Habitat-As Consumed [WK1, 2 kb] Table 10-21. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for Consumers Only by Age and Gender -As Consumed (Freshwater and Estuarine) [WK1, 2 kb] Table 10-22. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for Consumers Only by Age and Gender -As Consumed (Marine) [WK1, 2 kb] Table 10-23. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for Consumers Only by Age and Gender -As Consumed (All Fish) [WK1, 2 kb] Table 10-24. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for Consumers Only Aged 18 Years and Older by Habitat-As Consumed [WK1, 3 kb] Table 10-25. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for Consumers Only by Age and Gender -As Consumed (Freshwater and Estuarine) [WK1, 2 kb] Table 10-26. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for Consumers Only by Age and Gender -As Consumed (Marine) [WK1, 2 kb] Table 10-27. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for Consumers Only by Age and Gender -As Consumed (All Fish) [WK1, 2 kb] Table 10-28. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for Consumers Only Aged 18 Years and Older by Habitat-As Consumed [WK1, 3 kb] Table 10-29. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the U.S. Population by Age and Gender -Uncooked Fish Weight (Freshwater and Estuarine) [WK1, 2 kb] Table 10-30. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the U.S. Population by Age and Gender-Uncooked Fish Weight (Marine) [WK1, 2 kb] Table 10-31. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the U.S. Population by Age and Gender -Uncooked Fish Weight (All Fish) [WK1, 2 kb] Table 10-32. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for the U.S. Population Aged 18 Years and Older by Habitat-Uncooked Fish Weight [WK1, 2 kb] Table 10-33. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the U.S. Population by Age and Gender-Uncooked Fish Weight (Freshwater and Estuarine) [WK1, 2 kb] Table 10-34. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the U.S. Population by Age and Gender-Uncooked Fish Weight (Marine) [WK1, 3 kb] Table 10-35. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the U.S. Population by Age and Gender-Uncooked Fish Weight (All Fish) [WK1, 3 kb] Table 10-36. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for the U.S. Population Aged 18 Years and Older by Habitat-Uncooked Fish Weight [WK1, 2 kb] Table 10-37. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for Consumers Only by Age and Gender -Uncooked Fish Weight (Freshwater and Estuarine) [WK1, 2 kb] Table 10-38. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for Consumers Only by Age and Gender-Uncooked Fish Weight (Marine) [WK1, 2 kb] Table 10-39. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for Consumers Only by Age and Gender-Uncooked Fish Weight (All Fish) [WK1, 2 kb] Table 10-40. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) for Consumers Only Aged 18 Years and Older by Habitat -Uncooked Fish Weight * [WK1, 3 kb] Table 10-41. Per* Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for Consumers Only by Age and Gender -Uncooked Fish Weight (Freshwater and Estuarine) * [WK1, 2 kb] Table 10-42. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for Consumers Only by Age and Gender-Uncooked Fish Weight (Marine) [WK1, 2 kb] Table 10-43. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for Consumers Only by Age and Gender -Uncooked Fish Weight (All Fish) [WK1, 2 kb] Table 10-44. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) for Consumers Only Aged 18 Years and Older by Habitat-Uncooked Fish Weight [WK1, 3 kb] Table 10-45. Distribution of Quantity of Fish Consumed (in grams) Per Eating Occasion, by Age and Sex [WK1, 2 kb] Table 10-63. Distribution of Usual Fish Intake Among Survey Main Respondents Who Fished and Consumed Recreationally Caught Fish [WK1, 1 kb] Table 10-68. Distribution of Fish Intake Rates (from all sources and from sport-caught sources) For 1992 Lake Ontario Anglers [WK1, 1 kb] Table 10-72. Number of Grams Per Day of Fish Consumed by All Adult Respondents * (Consumers and Non-consumers Combined) -Throughout the Year [WK1, 2 kb] Table 10-74. Children's Fish Consumption Rates -Throughout Year [WK1, 1 kb] Volume II -Food Ingestion Factors Chapter 11 -Intake of Meat and Dairy Products 11. INTAKE OF MEAT AND DAIRY PRODUCTS 11.1. INTAKESTUDIES 11.1.1. U.S. Department of Agriculture Nationwide Food Consumption Survey and Continuing Survey of Food Intake by Individuals 11.1.2. Key Meat and Dairy Products Intake Study Based on the CSF.11 11.1.3. Relevant Meat and Dairy Products Intake Studies . 11.2. FAT CONTENT OF MEAT AND DAIRY PRODUCTS 11.3. CONVERSION BETWEEN AS CONSUMED AND DRY WEIGHT INTAKE RATES 11.4. RECOMMENDATIONS REFERENCES FOR CHAPTER 11 APPENDIX 11 A Table 11-1. Per Capita Intake of Total Meats (g/kg-day as consumed) Table 11-2. Per Capita Intake of Total Dairy Products (g/kg-day as consumed) Table 11-3. Per Capita Intake of Beef (g/kg-day as consumed) Table 11-4. Per Capita Intake of Pork (g/kg-day as consumed) Table 11-5. Per Capita Intake of Poultry (g/kg-day as consumed) Table 11-6. Per Capita Intake of Game (g/kg-day as consumed) Table 11-7. Per Capita Intake of Eggs (g/kg-day as consumed) Table 11-8. Main Daily Intake of Meat and Dairy Products Per Individual in a Day for USDA 1977.:78, 87-88, 89-91, 94, and 95 Surveys Table 11-9. Mean Per Capita Intake Rates for Meat, Poultry, and Dairy Products day as consumed) Based on All Sex/Age/Demographic Subgroups Table 11-10. Mean Meat Intakes Per Individual in a Day, by Sex and Age (g/day as consumed) for 1977-1978 Table 11-11. Mean Meat Intakes Per Individual in a Day, by Sex and Age (g/day as consumed) for 1987-1988 Table 11-12. Mean Dairy Product Intakes Per Individual in a Day, by Sex and Age (g/day as consumed) for 1977-1978 Table 11-13. Mean Dairy Product Intakes Per Individual in a Day, by Sex and Age (g/day as consumed) for 1987-1988 Table 11-14. Mean Meat Intakes Per Individual in a Day, by Sex and Age (g/day as consumed) for 1994 and 1995 Table 11-15. Mean Dairy Product Intakes Per Individual in a Day, by Sex and Age (g/day as consumed) for 1994 and 1995 Table 11-16. Mean and Standard Error for the Dietary Intake of Food Sub Classes Per Capita by Age (g/day as consumed) Table 11-17. Mean and Standard Error for the Per Capita Daily Intake of Food Class and Sub Class by Region (g/day as consumed) Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 11 -Intake of Meat and Dairy Products Table 11-18. Consumption of Meat, Poultry, and Dairy Products for Different Age Groups (averaged across sex), and Estimated Lifetime Average Intakes for 70 Kg Adult Citizens Calculated from the FDA Diet Data Table 11-19. Per Capita Consumption of Meat and Poultry in 1991 Table 11-20. Per Capita Consumption of Dairy Products in 1991 Table 11-21. Adult Mean Daily Intake (as consumed) of Meat and Poultry Grouped by Region and Gender Table 11 '-22. Amount (as consumed) of Meat Consumed by Adults Grouped by Frequency of Eatings Table 11-23. Quantity (as consumed) of Meat, Poultry, and Dairy Products Consumed .Per Eating Occasion and the Percentage of Individuals Using These Foods in Three Days Table 11-24. Percentage Lipid Content (Expressed as Percentages of 100 Grams of Edible Portions) of Selected Meat and Dairy Products Table 11-25. Fat Content of Meat Products Table 11-26. Fat Intake, Contribution of Various Food Groups to Fat Intake, and Percentage of the Population in Various Meat Eater Groups of the U.S. Population

Table 11-27. Mean Total Daily Dietary Fat Intake (g/day) Grouped by Age and Gender Table 1 -28. Percentage Mean Moisture Content (Expressed as Percentages of 100 Grams of Edible Portions)
Table 1"1-29. Summary of Meat, Poultry, and Dairy Intake Studies Table 11-30. Summary of Recommended Values for Per Capita Intake of Meat and Dairy Products and Serving Size Table 11,.31. Confidence in Meats and Dairy Products Intake Recommendations Exposure Factors Handbook August 1997

...-----------------------------Volume II -Food Ingestion Factors Chapter 11 -Intake of Meat and Dairy Products

11. INTAKE OF MEAT AND DAIRY PRODUCTS Consumption of meat, poultry, and dairy products is a potential pathway of exposure to toxic chemicals. These food sources can become contaminated if animals are exposed to contaminated media (i.e., soil, water, or feed_ crops). 1 The U.S. Department of Agriculture's (USDA) Nationwide Food Consumption Survey (NFCS) and Continuing Survey of Food Intakes by Individuals (CSFll) are the primary sources of information on intake rates of meat and dairy products in the United States. Data from the NFCS have been used in various studies to generate consumer-only and per capita intake rates for both individual meat and dairy products and total meat and dairy products. CSFll 1989-91 survey data have been analyzed by EPA to generate per capita
intake rates for various food items and food groups. As described in Volume II, Chapter 9 -Intake of Fruits and Vegetables, consumer-only intake is defined as the quantity of meat and dairy products consumed by individuals who ate these food items during the survey period. Per capita intake rates are generated by averaging consumer-only intakes over the entire population of users and non-users. In general, per capita intake rates are appropriate for use in exposure assessments for which average dose estimates for the general population are of interest because they represent both individuals who ate the foods during the survey period and individuals who may eat the .food items at some time, but did not consume them during the survey period.
Intake rates may be presented on either an as consumed or dry weight basis. As consumed intake rates (g/day) are based on the weight of the food in the form that it is
consumed. In contrast, dry weight intake rates are based on the weight of the food consumed after the moisture content has been removed. In calculating exposures based on ingestion, the unit of weight used to measure intake should be consistent with those used in measuring the contaminant concentration in the produce. Fat content data are also presented for various meat and dairy products. These data are needed for converting between residue levels on a whole-weight or as consumed basis and lipid basis. Intake data from the individual component of the NFCS and CSFll are based on "as eaten" (i.e., cooked or prepared) forms of the food items/groups. Thus, corrections to account for changes in portion sizes from cooking losses are not required. The purpose of this section is to provide: (1) intake data for individual meat and dairy products, total meat, and total dairy; (2) guidance for converting between as consumed and dry weight intake rates; and (3) data on the fat content in meat and dairy products. Recommendations are based on average and upper-percentile intake among the general population of the U.S. Available data have been classified as being either a key or a. relevant study based on the considerations discussed in Volume I, Section 1.3.1 of the Introduction. Recommendations are based on data from the 1989-91 CSFll survey, which was considered the only key intake study for meats and dairy products. Other relevant Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 11 -Intake of Meat and Dairy Products studies are also presented to provide the reader with added perspective on this topic. It should be noted that most of the studies presented in this section are based on data from USDA's NFCS and CSFll. The USDA NFCS and CSFll are described below. 11.1. INTAKE STUDIES 11.1.1. U.S. Department of Agriculture Nationwide Food Consumption Survey and Continuing Survey of Food Intake by Individuals The NFCS and CSFll are the basis of much of the data on meat and dairy intake. presented in this section. Data from the 1977-78 NFCS are presented because the data have been published by USDA in various reports and reanalyzed by various EPA offices according to the food items/groups commonly used to assess exposure. Published day data from the 1987-88 NFCS and 1994 and 1995 CSFll are also presented. Recently, EPA conducted an analysis of USDA's 1989-91 CSFll. These data were the most recent food survey data that were available to the public at the time that EPA analyzed the data for this Handbook. The results of EPA's analyses are presented here. Detailed descriptions of the NFCS and CSFll data are presented in Volume II, Chapter 9 -Intake* of Fruits and Vegetables. Individual average daily intake rates calculated from NFCS and CSFll data are based on averages of reported individual intakes over one day or three consecutive days. Such short term data are suitable for estimating average daily intake rates representative of both short-term and long-term consumption. However, the distributio11 of average daily intake rates generated using short term data (e.g., 3 day) do not necessarily reflect the long-term distribution of average daily intake rates. The distributions generated from short term and long term data will differ to the extent that each individual's intake varies from day to day; the distributions will be similar to the extent that individuals' intakes are constant from day to day. Day-to-day variation in intake among individuals will be great for food item/groups that are highly seasonal and for items/groups that are eaten year around but that are not typically eaten every day. For these foods, the intake distribution generated from short term data will not be a* good reflection of the long term distribution. On the other hand, for broad categories of foods (e.g., total meats) which are eaten on a daily basis throughout the year with minimal seasonality, the short term distribution may be a reasonable approximation of the true long term distribution, although it will show somewhat more variability. In this and the following section then, distributions are shown only for the following broad categories of foods: total meats and total dairy products. Because of the . increased variability of the short-term distribution, the short-term upper percentiles shown will overestimate somewhat the corresponding percentiles of the long-term distribution. Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 11 -Intake of Meat and Dairy Products 11.1.2. Key Meat and Dairy Products Intake Study Based on the CSFll U.S. EPA Analysis of 1989-91 USDA CSFll Data -EPA conducted an analysis of USDA's 1989-91 CSFll data set. The general methodology used in analyzing the data is presented in Volume II, Chapter 9 -Intake of Fruits and Vegetables of this Handbook. Intake rates were generated for the following meat and dairy products: total meats, total dairy, beef, pork, poultry, game, and eggs. Appendix 98 presents the food categories and codes used in generating intake rates for these food groups. These data have been corrected to account for mixtures as described in Volume II, Chapter 9 -Intake of Fruits and Vegetables and Appendix 9A. However, it should be noted that although total meats account for items such as luncheon sausages, and organ meats, these items are not included in the individual meat groups (i.e., beef, poultry, etc.). Per capita intake rates for total meat and total dairy are presented in Tables 11-1 and 11-2 at the end of this Chapter. Tables 11-3 to 11-7 present per capita intake data for individual meats and eggs. The results are presented in units of g/kg-day. Thus, use of these data in calculating potential dose does not require the body weight factor to be included in the denominator of the average daily dose (ADD) equation. It should be noted that converting these intake rates into units of g/day by multiplying by a single average body weight is inappropriate, because individual intake rates were indexed to the reported body weights of the survey respondents. However, if there is a need to compare the intake data presented here to intake data in units of g/day, a body weight 1.ess than 70 kg (i.e., approximately 60 kg; calculated based on the number of respondents in each age category and the average body weights for these age groups, as presented in Volume I, Chapter 7, Body Weight) should be used because the total survey population included children as well as adults. The advantages of using the 1989-91 CSFll data set are that the data are expected to be representative of the U.S. population and that it includes data on a wide variety of food types. The data set was the most recent of a series of' publicly available USDA data sets (i.e., NFCS 1977-78; NFCS 1987-88; CSFll 1989-91) at the time the analysis was conducted for this Handbook,. and should reflect recent eating patterns in the United States. The data set includes three years of intake data combined. However, the 1989-91 CSFll data are based on a three day survey period. Short-term dietary data may not accurately reflect long-term e.ating patterns. This is particularly true for the tails of the distribution of food intake. In addition, the adjustment for including mixtures adds uncertainty to the intake rate distributions. The calculation for including mixtures assumes that intake of any mixture includes all of the foods identified and the. proportions specified in Appendix Table 9A-1. This assumption yields valid estimates of per capita consumption, but results in overestimates of the proportion of the population consuming individual meats; thus, the quantities reported in Tables 11-3 to 11-7 should be interpreted as upper bounds on the proportion consuming beef, pork; poultry, game, and eggs. Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 11 -Intake of Meat and Dairy Products The data presented in this handbook for the USDA 1989-91 CSFI I is not the most to-date information on food intake. USDA has recently made available the data from its 1994 and 1995 CSFll. Over 5,500 people nationwide participated in both of these surveys, providing recalled food intake information for 2 separate days. Although the day data analysis has not been conducted, USDA published the results for the respondents' intakes on the first day surveyed (USDA, 1996a,b ). USDA 1996 survey data will be made available later in 1997. As soon as 1996 data are available, EPA will take steps to get the 3-year data ( 1994, 1995, and 1996) analyzed and the food ingestion factors updated. Meanwhile, Table 11-8 presents a comparison of the mean daily intakes per individual in a dayfor the major meat and dairy groups from USDA survey data from years 1977-78, 1987-88, 1989-91, 1994, and 1995. This table shows that food consumption patterns have changed for beef and meat mixtures when comparing 1977 and 1995 data. In particular, consumption of beef decreased by 50 percent when comparing data from 1977 and 1995, while consumption of meat mixtures increased by 44 percent: However, consumption of the food items presented in Table 11-8 has remained fairly constant when comparing values from 1989-91 with the most recent data from 1994 and 1995. Meat mixtures show the largest change with an increase of 16 percent from 1989 to 1995. This indicates that the 1989-91 CSFll data are probably adequate for assessing ingestion exposure for current populations; however, these data should be used with caution. It is interesting to note that there was not much variation. in beef and poultry. consumption from 1989-91 to 1995. This seems to contradict the other USDA reports that show that in recent years the U.S. population has been substituting beef for other sources of protein such as poultry and fish. One of those reports is th.e report titled Meat and* Poultry Inspection; 1994 Report of the Secretary of Agriculture to the U.S. Congress (USDA, 1994). This USDA .report shows a 39% increase in the number of poultry inspected at federally inspected plants in 1994 compared to 1984. In contrast, the number of meat animals inspected at federally inspected plants increased only by 2% from 1984 to 1994. This trend in food consumption patterns was also reported in the USDA report titled Food Consumption, Prices, and Expenditures, 1970-92 (USDA, 1993). This report shows that in 1992, consumption among Americans averaged 18 pounds less red meat, 26 pounds more poultry, and 3 pounds more fish and shellfish than in 1970. This apparent contradiction may be explained by assuming that most of the increase in poultry consumption has occured in the meat mixtures and grain mixtures categories. There has been a considerable shift from consuming individual food items to food in mixtures (such as pizza, tacos, burritos, frozen entrees, and salads from grocery stores). This may explain why, in Table 11-8, domestic consumption has remained fairly constant in the past few years. Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 11 -Intake of Meat and Dairy Products 11.1.3. Relevant Meat and Dairy Products Intake Studies The U.S. EPA's Dietary Risk Evaluation System (ORES) -U.S. EPA, Office of PestiCide Programs (OPP) -EPA OPP's ORES contains per capita.intake rate data for various items of meat, poultry, and dairy products for 22 subgroups (age, regional, and seasonal) of the population. As described in Volume II, Chapter 9 -Intake of Fruits and Vegetables, intake data in ORES were generated by determining the composition of 1977/78 NFCS food items and disaggregating complex food dishes into their component raw agricultural commodities (RACs) (White et al., 1983). The ORES per capita, as consumed intake rates for all age/sex/demographic groups combined are presented in Table 11-9. These data are based on both consumers and non-consumers of these food items. Data for specific subgroups of the population are not presented in this section, but are available through OPP via direct request. The data in Table 11-9 may be useful for estimating the risks of exposure associated with the consumption of the various meat, poultry, and dairy products presented. It should be noted that these data are indexed to the reported body weights of the survey respondents and are expressed in units of grams of food consumed per kg body weight per day. Consequently, use of these data in calculating potential dose does not require the body weight factor in the denominator of the average daily dose (ADD) equation. It should also be noted that conversion of these intake rates into* units of g/day by multiplying by a single average body weight is not appropriate because the ORES data base did riot rely on a single body weight for all individuals. Instead, ORES used the body weights reported by each individual surveyed to estimate consumption in units of g/kg-day. The advantages of using these data are that complex food dishes have been disaggregated to provide intake rates for a variety.of meat, poultry, and dairy products. These data are also based on the individual body weights of the respondents. Therefore, the use of these data in calculating exposure to toxic chemicals may provide more representative estimates of potential dose per unit body weight. However, because the data are based on NFCS short-term dietary recall, the same limitations discussed previously for other NFCS data sets also apply here.* In addition, consumption patterns may have changed since the data were collected in 1977-78. OPP is in the process of translating consumption information from the USDA CSFll 1989-91 survey to be used in ORES. Food and Nutrient Intakes of Individuals in One Day in the U.S., USDA (1980, 1992, 1996a, 1996b) -USDA calculated mean per capita intake rates for meat and dairy products using NFCS data from 1977-78 and 1987-88 (USDA, 1980; 1992) and CSFll data from 1994 and 1995 (USDA, 1996a; 1996b ). The mean per capita intake rates for meat and dairy products are presented in Tables 11-10 and 11-11 for meats and Tables 11"'.12 and 11-13 for dairy based on intake data for one day from the 1977-78 and 1987-88 USDA Exposure Factors Handbook August 1997 Volume Food Ingestion Factors Chapter 11 -Intake of Meat and Dairy Products NFCSs. Tables 11-14 and 11-15 present similar data from the 1994 and 1995 CSFll for meats and dairy products, respectively. The advantages of using these data are that they provide mean intake estimates for all meat, poultry, and dairy products. The consumption estimates are based on short-ter.m (i.e., 1-day) dietary data which may not reflect long-term consumption. U.S. EPA -Office of Radiation Programs -The U.S. EPA Office of Radiation Programs (ORP) has also used the USDA 1977-78 NFCS to estimate daily food intake. ORP uses food consumption data to assess human intake of radionuclides in foods (U.S. EPA, 1984a; 1984b). The 1977-78 NFCS data have been reorganized by ORP, and food items have been classified according to the characteristics of radionuclide transport. The mean per capita dietary intake offood sub classes (milk, other dairy products, eggs, beef, pork, poultry, and other meat) grouped by age for the U.S. population is presented in Table 11-16. The mean daily intake rates of meat, poultry, and dairy products for the U.S. population grouped by regions are presented in Table 11-17. Because this*study was based on the USDA NFCS, the limitations and advantages associated with the USDA NFCS data also apply to these data. Also, consumption patterns may have changed since the data were collected in 1977-78. U.S. EPA -Office of Science and Technology-The U.S. EPA Office of Science and Technology (OST) within the Office of Water (formerly the Office of Water Regulations .and Standards) used data from the FDA revision of the Total Diet Study Food Lists and Diets (Pennington, 1983) to calculate food intake rates. OST uses these consumption data in its risk assessment model for land application of municipal sludge. The FDA data used are based on the combined results of the USDA 1977-78 NFCS and the second National Health and Nutrition Examination Survey (NHANES II), 1976-80 (U.S. EPA, 1989) . . Because food items are listed as prepared complex foods in the FDA Total Diet Study, each item was broken down into its component parts so that the amount of raw commodities consumed could be determined. Table 11-18 presents intake rates for meat, poultry, and dairy products for various age groups. Estimated lifetime ingestion rates derived by U.S. EPA (1989) are also presented in Table 11-18. Note that these are per capita intake rates tabulated as grams dry weight/day. Therefore, these rates differ from *those in the previous tables because Pao et al. (1982) and U.S. EPA (1984a, 1984b) . . report intake rates on an as consumed basis. The EPA-OST analysis provides intake rates for additional food categories and estimates of lifetime average daily intake on a per capita basis. In contrast to the Other analyses of USDA NFCS data, this study reports the data in terms of dry weight intake rates. Thus, conversion is not required when contaminants are provided on a dry weight basis. These data, however, may not reflect current consumption patterns because they are based on 1977-78 data. Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 11 -Intake of Meat and Dairy Products USDA (1993)-Food Consumption, Prices, and Expenditures, 1970-92-The USDA's Economic Research Service (ERS) calculates the amount of food available for human consumption in the United States annually. Supply and utilization balance sheets are generated. These are based on the flow of food items from production to end uses. Total available supply is estimated as the sum of production (i.e., some products are measured at the farm level or during processing), starting inventories, and imports (USDA, 1993). The availability of food for human use commonly termed as "food disappearance" is determined by subtracting exported foods, products used in industries, farm inputs (seed and feed) and end-of-the year inventories from the total available supply (USDA, 1993). USDA ( 1993) calculates the per capita food consumption by dividing the total food disappearance by the total U.S. population. USDA (1993) estimated per capita consumption data for meat, poultry, and dairy products from 1970-1992 (1992 data are preliminary). In this section, the 1991 values, which are the most recent final data, are presented. The meat consumption data *were reported as carcass weight, retail weight equivalent, and boneless weight equivalent. The poultry consumption data were reported as ready-to-cook (RTC) weight, retail weight, and boneless weig.ht (USDA, 1993). USDA (1993) defined beef carcass weight as the chilled hanging carcass, which includes the kidney and attached internal fat (kidney, pelvic, and heart fat), excludes the skin, head, feet, and unattached internal organs. The pork carcass weight includes the skin and feet, but excludes the kidney and attached internal fat. Retail weight equivalents assume all food was sold through retail foodstores; therefore, conversion factors (Table 11-19) were used to correct carcass or RTC to retail weight to account for trimming, shrinkage, or loss of meat and chicken at these retail outlets (USDA, 1993). Boneless equivalent values for meat (pork, veal, beef) and poultry excludes all bones, but includes separable fat sold on retail cuts of red meat. Pet food was considered as an apparent source of food disappearance for poultry in boneless weight estimates, while pet food was excluded for beef, veal, and pork (USDA, 1993). Table 11-19 presents per capita consumption in 1991 for red meat (carcass weight, retail equivalent, and . boneless trimmed equivalent) and poultry (RTC, retail equivalent for chicken only, and boneless trimmed equivalent). Per capita consumption estimates based on boneless weights appear to be the most appropriate data for use in exposure assessments, because boneless meats are more representative of what peopl*e would actually consume. Table 11-20 .presents per capita consumption in 1991 for dairy products including eggs, milk, cheese, cream, and sour cream. One of the limitations of this study is that disappearance data do not account for losses from the food supply from waste, spoilage, or foods fed. to pets. Thus, intake rates based on these data will overestimate daily consumption because they are based on the total quantity of marketable commodity utilized. Therefore, these data may be useful for estimating bounding exposure estimates. It should also be noted that per capita estimates based on food disappearance are not a direct measure of actual consumption or quantity Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 11 -Intake of Meat and Dairy Products ingested, instead the data are used as indicators of changes in usage over time (USDA, 1993). An advantage of this study is that it provides per capita consumption rates for meat, poultry, and dairy products which are representative of long-term intake because disappearance data are generated annually. Daily per capita intake rates are generated by dividing annual consumption by 365 days/year. National Live Stock and Meat Board (1993} -Eating in America Today: A Dietary Pattern and Intake Report -The National Live Stock and Meat Board (NLMB) (1993) assessed the nutritional value of the current American diet based on two factors: (1) the composition of the foods consumed, and (2) the amount of food consumed. Data used in this study were provided by MRCA Information Services, Inc. through MRCA's Nutritional Marketing Information Division. The survey conducted by MRCA consisted of a 2,000 household panels of over 4, 700 individuals. The survey sample was selected to be representative of the U.S. population. Information obtained from the survey by MRCA's Menu Census included food and beverage consumption over a period of 14 consecutive days. The head of the household recorded daily food and beverage consumption in-home and away-from-home in diaries for each household member. The survey period was from
July 1, 1990 through June 30, 1991. This ensured that all days carried equal weights and provided a seasonally balanced data set. In addition, nutrient intake data calculated by the MRCA's Nutrie!lt Intake Database (NID) (based on the 1987-88 USDA Food Intake Study) and information on food attitudes were also *collected. It should be noted, however, that the 14 daily diaries provided only the incidence of eating each food product by an individual, but not the quantity eaten by each person. The for each individual was estimated by multiplying the eating frequency of a particular food item by the average amount eaten per eating occasion. The data on the average amount eaten per eating occasion were obtained from the USDA NFCS survey. Table 11-21 presents the adult daily mean intake of meat and poultry grouped by region and gender. The adult population was defined as consumers ages 19 and above (NLMB, 1993). Beef consumption was high in all regions compared to other meats and poultry (Table 11-21 ). The average daily consumption of meat in the U.S. was 114.2 g/day which included beef (57 percent), veal (0.5 percent), lamb (0.5 percent), game/variety meats (8 percent), processed meats (1'8 percent), and pork (16 percent) (NLMB, 1993). Table 11-22 shows the amount of meat consumed by the adult population grouped as meat eaters (1 percent), light meat eaters (30 percent), medium meat eaters (33 percent), and heavy meat eaters (36 percent). The advantage of this study is that the survey period is longer (i.e., 14 days) than any other food consumption survey. The survey is also based on a nationally representative sample. The survey also accounts for foods eaten as mixtures. However, only mean values are provided. Therefore, distribution of long-term consumption patterns cannot be derived. In addition, the survey collects data on incidence of eating each food item and Exposure Factors Handbook August 1997

,------:------Volume II -Food Ingestion Factors Chapter 11 -Intake of Meat and Dairy Products not actual consumption rates. This may introduce some bias in the results. The direction of this bias is unknown. AIHC {1994) -Exposure Factors Sourcebook-The AIHC Sourcebook (AIHC, 1994) uses the data presented in the 1989 version of the Exposure Factors Handbook which reported data from the USDA 1977-78 NFCS. In this Handbook, new analyses of more recent data from the USDA 1989-91 CSFll are presented. Numbers, however, cannot be directly compared with previous values since the results from the new analysis are presented on a body weight basis.* The Sourcebook. was selected as a relevant study because it was not the primary source for the data used to make recommendations in this document. However, it is an alternative information source. Pao et al. (1982) -Foods Commonly Eaten by Individuals -Using data gathered in the 1977-78 USDA NFCS, Pao et al. (1982) calculated percentiles for the quantities of meat, poultry, and dairy products consumed per eating occasion by members of the U.S. population. The data were collected during NFCS home interviews of 37,874 respondents, who were asked to recall food intake for the day preceding the interview, and record food intake the day of the interview and the day after the interview. Quantities consumed per eating occasion, are presented in Table 11-23. The advantages of using these data are that they were derived from the USDA NFCS and are representative of the U.S. population. This data set provides distributions of serving sizes for a number of commonly eaten meat, poultry, and dairy products, but the list of foods is limited and does not account for meat, poultry, and dairy products included in complex food dishes. Also, these data are based on short-term dietary recall and may not accurately reflect long-term consumption patterns. Although these data are based on the 1977-78 NFCS, serving size data have been collected but not published for the more

recent USDA surveys. 11.2. FAT CONTENT OF MEAT AND DAIRY PRODUCTS In some cases, the residue levels of contaminants in meat and dairy products are . -reported as the concentration of contaminant per gram of fat. This may be particularly true for lipophilic compounds. When using these residue levels, the assessor should ensure consistency in the exposure assessment calculations by using consumption rates that are based on the amount of fat consumed for the meat or dairy product of interest. Alternately, residue levels for the "as consumed" portions of these products may be estimated by multiplying the levels based on fat by the fraction of fat per product as follows: residue level , residue level x g&fat g&product g&fat g&product (Eqn. 11-1) Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 11 -Intake of Meat and Dairy Products The resulting residue levels may then be used in conjunction with "as consumed" consumption rates. The percentages of lipid fat in and dairy products have been reported in various publications. USDA's Agricultural Handbook Number 8 (USDA, 1979-1984) provides composition data for agricultural products. It includes a listing of the total *saturated, monounsaturated, and polyunsaturated fats for various meat and dairy items. Table 11-24 presents the total fat content for selected meat and dairy products taken from Handbook Number 8. The total percent fat content is based on the sum of saturated, monounsaturated, and polyunsaturated fats. The National Livestock and Meat Board (NLMB) (1993) used data from Agricultural Handbook Number 8 and consumption data to estimate the fat contribution to the U.S. diet. Total fat content in grams, based. on a 3-ounce (85.05 g) cooked serving size, was reported for several categories (retail composites) of meats. These data are presented in Table 11-25 along with the corresponding percent fat content values for each product. NLMB (1993) also reported that 0.17 grams of fat are consumed per gram of meat (i.e., beef, pork, lamb, veal, game, processed meats, and variety meats) (17 percent) and 0.08 grams of fat are consumed per gram of poultry (8. percent).
The average total fat content of the U.S. diet was reported to be 68.3 g/day. The meat group (meat, poultry, fish, dry beans, eggs, and nuts) was reported to contribute the . most to the average total fat in the diet (41 percent)(NLMB, 1993). Meats (i.e., beef, pork, lamb, veal, game, processed meats, and variety meats) reportedly contribute less than 30 percent to the total fat of the average U.S. diet. The milk group contributes approximately 12 percent to the average total fat in the U.S. diet (NLMB, 1993). Fat intake rates and the contributions of the major food groups to fat intake for heavy, medium, and light meat eaters, and non meat eaters are presented in Table 11-26 (NLMB, 1993). NLMB (1993) also reported the average meat fat intake to be 19.4 g/day, with beef contributing about 50 percent of the fat to the diet from all meats. Processed meats contributed 31 percent; pork contributed 14 percent; game and variety meats contributed 4 percent; and lamb and veal contributed 1 percent to the average meat fat intake. The Center for Disease Control (CDC) (1994) used data from NHANES Ill to calculate daiiy total food energy intake (TFEI), total dietary fat intake, and saturated fat intake for the U.S. population during 1988 to 1991. The sample population comprised 20,277 individuals ages 2 months and above, of which 14,001 respondents (73 percent response rate) provided dietary information based on a 24-hour recall. TFEI was defined as "all nutrients (i.e., protein, fat, carbohydrate, and alcohol) derived from consumption of foods
and beverages (excluding plain drinking water) measured in kilocalories (kcal)." Total dietary fat intake was defined as "all fat (i.e., saturated and unsaturated) derived from consumption of foods and beverages measured in grams." Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 11 -Intake of Meat and Dai.ry Products CDC (1994) estimated and provided data on the mean daily TFEI and the mean percentages of TFEI from total dietary fat grouped by age and gender. The overall mean daily TFEI was 2,095 kcal for the total population and 34 percent (or 82 g) of their TFEI was from total dietary fat (CDC, 1994). Based on this information, the mean daily fat intake was calculated for the various age groups and genders (see Appendix 11A for detailed* calculation). Table 11-27 presents the grams of fat per day obtained from the daily consumption of foods and beverages grouped by age and gender for the U.S. population, based on this calculation. 11.3. CONVERSION BETWEEN AS CONSUMED AND DRY WEIGHT INTAKE RATES As noted previously, intake rates may be reported in terms of units as consumed or units of dry weight. It is essential that exposure assessors be aware of this difference so that they may ensure consistency between the units used for intake rates and those used for concentration data (i.e., if the unit of food consumption is grams dry weight/day, then the unit for the amount of pollutant in the food should be grams dry weight). If necessary, as consumed intake rates may be converted to dry weight intake rates using the moisture content percentages of meat, poultry and dairy products presented in Table 11-28 and the following equation: . , IRdw = I Rae * [( 100-W)/100] (Eqn. 11-2) I "Dry weight" intake rates may be converted to "as consumed" rates by using: I Rae= IRdw/[(100-W)/100] (Eqn. 11-3) where: = dry weight intake rate; IRac = as consumed intake rate; and W = percent water content. 11.4. RECOMMENDATIONS The 1989-91 CSFll data described in this section were used in selecting recommended meat, poultry, and dairy product intake rates for the general population and various subgroups of the United States population. The general design of both key and relevant studies are summarized in Table 11-29. The recommended values for intake of meat and dairy products are summarized in Table 11-30 and the confidence ratings for the recommended values for meat and dairy intake rates are presented in Table 11-31. Per Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 11 -Intake of Meat and Dairy Products capita intake rates for specific meat items, on a g/kg-day basis, may be obtained from Tables 11-3 to 11-7. Percentiles of the intake rate distribution in the general population for total meat and total dairy are presented in Tables 11-1 and 11-2. From these tables,
the mean and 95th percentile intake rates for meats are 2.1 g/kg-day and 5.1 g/kg-day, respectively. The mean and 95th percentile intake rates for dairy products are 8.0 day and 29.7 g/kg-day. It is important to note that the data presented in Tables.11-1 through 11-7 are based on data collected over a 3-day period and may not necessarily reflect the long-term distribution of average daily intake rates. However, for these broad categories of food (i.e., total meats and total dairy products), because they may be eaten on a daily basis throughout the year with minimal seasonality, the short-term distribution may be a reasonable approximation of the long-term distribution, although it will display somewhat increased variability. This implies that the upper percentiles shown here will tend to overestimate the corresponding percentiles of the true long-term distribution. Intake rates for the homeproduced form of these food items/groups are presented in Volume II, Chapter 13. It should be noted that because these recommendations are based on 1989-91 CSFll data, they may not reflect recent the most changes in consumption patterns. However, as indicated in Table 11-8, intake has remained fairly constant between 1989-91 and 1995. Thus, the 1989-91 CSFll data are believed to be appropriate for assessing ingestion exposure for current populations. Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Appendix 11A APPENDIX 11A . SAMPLE CALCULATION OF MEAN DAILY FAT INTAKE BASED ON CDC (1994) DATA Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Appendix 11A Sample Calculation of Mean Daily Fat Intake Based on CDC (1994) Data CDC (1994) provided data on the mean daily total food energy intake (TFEI) and the . mean percentages of TFEI from total dietary fat grouped by age and gender. The overall mean daily TFEI was 2,095 kcal for the total population and 34 percent (or 82 g) of their TFEI was from total dietary fat (CDC, 1994). Based on this information, the amount of fat per kcal was calculated as shown in the following example. 0.34 x 2,095 kcal x X g&fat ' 82 g&fat day day day :.ox ' 0.12 g&fat kcal where 0.34 is the fraction of fat intake, 2,095 is the total food intake, and X is the conversion factor from kcal/day tog-fat/day. Using the conversion factor shown above (i.e., 0.12 g-fat/kcal) and the information on the mean daily TFEI and percentage of TFEI for the various age/gender groups, the daily fat intake was calculated for these groups. An example of obtaining the grams of fat from the daily TFEI (1,591 kcal/day) for children ages 3-5 and their percent TFEI from total dietary fat (33 percent) is as follows: 1,591 kcal x 0.33 x 0.12 g&fat ' 63 g&fat day kcal day Exposure Factors Handbook August 1997 Table 11-1. Per Capita Intake of Total Meats (q/kq-dav as c0nsumed) Population Percent Grouo Consumina Mean SE P1 PS P10 P25 PSO P75 P90 P95 P99 P100 Total 96.4% 2.146 0.014 0 0.33 0.63 1.13 1.84 2.78 4.06 5.06 7.67 25.67 Age (years) < 01 66.7% 2.867 0.187 0 0 0 0 2.34 4.72 6.52 8.56 11.52 25.67 01*02 95.6% 4.384 0.116 0 1.07 1.58 2.70 4.13 5.38 7.69 8.41 11.88 21.61 03-05 97.5% 3.873 0.092 0 1.12 1.38 2.21 3.50 5.04 6.64 8.23 11.25 15.00 06-11 97.6% 3.011 0.052 0 0.66 1.02 1.80 2.78 3.98 5.12 6.08 8.38 11.68 12-19 97.7% 2.078 0.034 0 0.42 0.67 1.19 1.99 2.79 3.49 4.40 5.95 8.28 20-39 97.9% 1.923 0.019 0 0.39 0.64 1.09 1.73 2.54 3.49 4.14 5.46 8.37 40-69 97.3% 1.700 0.017 0 0.36 0.59 1.03 1.58 2.20 2.95 3.47 4.73 7.64 70 + 97.1% 1.531 0.028 0 0.32 0.49 0.89 1.42 2.03 2.73 3.20 4.28 6.63 Season Fall 97.1% 2.182 0.029 0 0.37 0.66 1.15 1.85 2.80 4.11 5.16 8.06 25.67 Spring 95.8% 2.053 0.027 0 0.26 0.61 1.09 1.75 2.63 3.93 4.91 7.31 15.00 Summer 96.3% 2.178 0.031 0 0.35 0.63 1.11 1.86 2.84 4.10 5.18 7.86 18.19 Winter 96.4% 2.173 0.029 0 0.30 0.63 1.18 1.88 2.87 4.06 5.05 7.35 14.61 Urbanization Central City 96.7% 2.163 0.028 0 0.25 0.59 1.09 1.79 2.82 4.14 5.22 7.97 25.67 Nonmetropolitan 95.7% 2.168 0.028 0 0.30 0.63 1.15 1.90 2.79 4.04 5.12 7.69 14.61 Suburban 96.6% 2.126 0.021 0 0.39 0.64 i.13 1.84 2.74 4.03 4.94 7.31 15.00 Race Asian 89.3% 2.233 0.131 0 0 0.60 1.10 1.86 3.23 4.49 4.66 6.86 8.13 Black 95.5% 2.434 0.053 0 0.'33 0.62 1.15 1.94 3.02 5.03 6.14 9.87 25.67 Native American 86.5% 2.269 0.131 0 0 0.41 1.32 1.87 3.38 4.64 5.09 7.32 8.57 Other/NA 95.1% 2.628 0.109 0 0 0.65 1.40 2.29 3.34 4.90 6.03 11.25 11.25 White 96.9% 2.083 0.015 0 0.34 0.63 1.12 1.81 2.72 3.87 4.87 7.18 18.19 Region Midwest 96.5% 2.204 0.029 0 0.44 0.69 1.21 1.85 2.82 4.08 5.05 7.86 21.61 Northeast 96.5% 2.148 0.033 0 0.35 0.67 1.16 1.89 2.75 3.98 4.99 8.27 15.00 South 96.7% 2.249 0.025 0 0.37 0.68 1.18 1.90 2.88 4.35 5.34 7.73 13.42 West 95.8% 1.903 0.030 0 0.08 0.47 0.92 1.60 2.54 3.69 4.57 6.64 25.67 NOTE: SE = Standard error P = Percentile of the distribution Source: Based on EPA's analvses of the 1989-91 CSFll Table 11-2. Per Capita Intake of Total Dairv Products (a/ka-dav as consumed) Population Percent Grouo Consumina Mean SE P1 PS P10 P25 P50 P75 P90 P95 P99 P100 Total 97.1% 8.015 0.147 0 0.15 0.,40 1.36 3.61 8.18 18.55 29.72 72.16 390.53 Age (years) < 01 89.6% 62.735 2.800 0 0 0.61 24.68 45.78 91.12 136.69 170.86 210.72 390.53 01,02 95.6% 26.262 0.743 0 2.69 8.19 15.22 23.48 36.13 45.72 55.07 69.42 108.95 03-05 97.5% 21.149 0.517 0 3.27 6.75 11.89 19.52 28.31 39.54 44.16 57.58 62.88 06-11 97.4% 13.334 0.264 0 1.81 3.54 6.72 11.88 18.58 25.38 28.76 39.60 62.55 12-19 97.9% 6.293 0.147 0 0.27 0.61 2.31 5.29 9.20 12.75 15.12 23.58 53.47 20-39 97.9% 3.618 0.062 0 0.12 0.30 0.95 2.64 5.04 8.15 10.64 17.23 43.31 40-69 96.9% 3.098 0.053 0 0.10 0.26 0.94 2.23 4.36 '6.99 9.05 12.99 34.42 70 + 97.6% 3.715 0.104 0 0.16 0.47 1.46 3.03 4.93 8.03 9.63 16.49 26.33 Season Fall 97.7% 8.262 0.286 0 0.17 0.38 1.32 3.53 8.31 20.16 32.71 75.83 351.48 Spring 96.8% 8.273 0.335 0 0.13 0.39 1.37 3.50 7.88 18.02 27.02 116.00 390.53 Summer 96.8% 7.561 0.257 0 0.14 0.37 1.37 3.51 7.93 18.01 30.86 64.95 347.93 Winter 97.1% 7.964 0.293 0 0.16 0.43 1.39 3.90 8.77 17.60 27.34 63.27 307.54 Urbanization Central City 97.2% 8.528 0.309 0 0.17 0.41 1.44 3.78 8.05 18.25 29.51 106.93 318.93 Non metropolitan 96.6% 7.224 0.261 0 0.10 0.28 1.08 3.34 7.82 17.28 24.70 59.17 390.53 Suburban 97.4% 8.058 0.209 0 0.17 0.43 1.42 3.61 8.45 19.50 32.04 69.42 351.48 Race Asian 94.0% 8.730 1.264 0 0 0.14 0.63 3.86 7.23 21.62 36.16 72.01 124.26 Black 94.8% 7.816 0.498 0 0.03 0.11 0.64 2.49 7.29 17.28 27.78 116.00 347.93 Native American 88.9% 6.987 1.057 0 0.02 0.14 0.81 2.83 8.06 20.20 24.17 66.71 139.37 Other/NA 97.1% 10.727 1.002 0 0.12 0.33 1.03 4.15 11.28 34.64 40.33 121.50 166.48 White 97.7% 7.943 0.156 0 0.22 0.49 1.50 3.76 8.24 18.16 28.76 66.11 390.53 Region Midwest 97.3% 9.291 0.341 0 0.20 0.50 1.66 4.20 9.61 21.33 34.35 90.88 390.53 Northeast 97.2% 7.890 0.330 0 0.18 0.42 1.42 3.41 7.54 18.07 32.04 78.15 307.54 South 97.3% 6.926 0.225 0 0.11 0.27 1.01 3.10 7.49 15.86 25.76 54.94 347.93 West 96.7% 8.454 0.313 0 0.17 0.49 1.60 3.93 8.67 19.88 29.89 84.46 174.65 NOTE: SE = Standard error P = Percentile of the distribution Source: Based on EPA's analvses of the 1989*91 CSFll Table 11-3. Per Caoita Intake of Beef (a/ka-dav as consumed) Population Percent Grouo Consumina Mean SE P1 PS P10 P25 P50 P75 P90 P95 P99 P100 Total 91% 0.825 0.007 0 0 0.055 0.268 0.626 1.163 1.804 2.327 3.478 7.959 Age (years) < 01 64% 0.941 0.075 0 0 *o 0 0.488 1.417 2.536 3.205 5.776 7.959 01-02 93% 1.46 0.056 0 0 0.187 0.531 1.339 2.166 2.783 3.65 4.741 7.571 03-05 95% 1.392 0.05 0 0 0.14 0.506 1.162 1.905 3.163 3.573 5.908 6.769 06-11 95% 1.095 0.028 0 0.028 0.102 0.337 0.924 1.56 2.376 2.92 3.944 6.024 12-19 95% 0.83 0.02 0 0.032 0.114 0.3 0.654 1.204 1.775 2.192 3.108 4.508 20-39 94% 0.789 0.012 0 0 0.087 0.297 0.644 1.109 1.662 2.165 3.059 6.086 40-69 90% 0.667 0,011 0 0 0.031 0.221 0.536 0.977 1.458 1.76 2.474 4.968 70 + 87% 0.568 0.018 0 0 0 0.151 0.427 0.817 1.324 1.651 . 2.62 4.02 Season Fall 92% 0.834 0.014 0 0 0.063 0.296 0.665 1.167 1.785 2.277 3.339 6.086 Spring 91% 0.797 0.014 *O 0 0.046 0.254 0.595 1.132 1.788 2.295 3.531 7.959 Summer 90% 0.845 0.017 0 0 0.045 0.254 0.605 1.187 1.887 2.519 3.707 7.085 Winter 92% 0.823 0.015 0 0 0.066 0.272 0.636 1.157 1.767 2.271 3.266 7.571 Urbanization Central City 91% 0.808 0.013 0 0 0.037 0.271 0.611 1.13 1.777 2.329 3.325 6.182 Nonmetropolitan 91% 0.841 0.015 0 0 0.064 0.269 0.637 1.196 1.852 2.308 3.531 6.66 Suburban 92% 0.828 0.011 0 0 0.059 0.265 0.63 1.163 1.797 2.337 3.511 7.959 Race Asian 89% 0.895 0.072 0 0 0.08 0.228 0.694 1.251 2.065 2.444 3.135 5.862 Black 87% 0.665 0.019 0 0 0 0.151 0.42 0.963 1.488 2.177 3.126 6.769 Native American 82% 0.995 0.088 0 0 0.016 0.182 0.73 1.299 2.338 2.825 4.958 6.66 Other/NA 90% 1.159 0.069 0 0 0 0.389 0.739 1.63 2.756 3.269 5.908 6.182 White 93% 0.833 0.008 0 0 0.068 0.284 0.651 1.18 1.784 2.28 3.41 7.959 Region Midwest 92% 0.853 0,015 0 0 0.07 0.31 0.66 1.191 1.853 2.345 3.65 6.468 Northeast 93% 0.805 0.017 0 0 0.054 0.253 0.595 1.136 1.816 2.352 3.41 6.769 South 90% 0.846 0.013 0 0 0.058 0.268 0.648 1.195 1.805 2.324 3.511 7.959 West 92% 0.775 0.016 0 0 0.039 0.235 0.562 1.105 1.73 2.226 3.219 6.66 NOTE: SE= Standard error P = Percentile of the distribution Source: Based on EPA's analyses of the 1989-91 CSFll I 1* ---------------------------------------c---------------Table 11*4. Per Caoita Intake of Pork ta/ka-dav as consumed) Population Percent Grouo Consumino Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100. Total 90.2% 0.261 0.005 0 0 0.005 0.031 0.083 0.263 0.735 1.137 2.384 8.231 Age (years) < 01 63.0% 0.291 0.04 0 0 0 0 0.078 0.228 0.69 1.671* 3.269 5.431 01-02 92.4% 0.492 0.041 0 0 0.033 0.071 0.182 0.424 1.525 2.633 3:633 6.94 03-05 . 95.0% 0.473 0.035 0 0 0.021 0.057 0.147 0.362 1.372 2.35 3.309 8.231 06-11 94.5% 0.352 0.018 0 0 0.015 0.052 0.116 0.311 1.098 1.418 2.869 5.024 12-19 94.0% 0.27 0.013 0 0 0.012 0.039 0.09 0.289 0.742 1.118 2.699 5.157 20-39 92.5% 0.23 0.007 0 0 0.009 0.031 0.08 0.233 0.704 1.039 1.747 6.363 40-69 88.3% 0.212 0.007 0 0 0 0.025 0.068 0.242 0.613 0.915 1.865 4.342 70+ 86.5% 0.207 0.011 0 0 0 0.016 0.061 0.223 0.667 0.924 1.74 3.035 Season Fall 91.9% 0.254 0.008 0 0 0.01 0.037 0.098 0.267 0.723 1.045 2.118 5.338 Spring 88.8%. 0.264 0.009 0 0 0 0.027 0.076 0.265 0.728 1.19 2.762 6.94 Summer 89.4% 0.245 0.01 0 0 0 0.027 0.072 0.22 0.688 1.097 2.43 8.231 Winter 90.6% 0.279 0.009 0 0 0.006 0.032 0.084 0.3 0.819 1.195 2.608 5.946 Urbanization Central City 89.5% 0.258 0.009 0 0 0.001 0.027 0.076 o*.235 0.736 1.085 2.699 6.94 Nonmetropolitan 90.3% 0.299 0.01 0 0 0.007 0.038 0.099 0.324 0.863 1.212 2.808 8.231 Suburban 90.6% 0.244 0.006 0 0 0.006 0.03 0.078 0.253 0.678 1.098 2.269 5.946 Race Asian 85.9% 0.256 0.049 0 0 0.003 0.027 0.057 0.192 0.72 1.157 2.487 3.966 Black 89.2% 0.418 0.019 0 0 0.002 0.035 0.123 0.48 1.19 2.108 3.178 8.231 Native American 83.6% 0.188 0.024 0 0 0 0.027 0.08 0.179 0.473 0.889 1.317 1.662 Other/NA 88.3% 0.191 0.021 0 0 0 0.027 0.075 0.183 0.48 0.845 1.638 5.252 White 90.6% 0.241 0.005 0 0 0.006 0.031 0.081 0.249 0.685 1.061 2.035 5.946 Region Midwest 91.3% 0.284 0.009 0 0 0.006 0.034 0.095 0.318 0.776 1.113 2.487 6.362 Northeast 90.4% 0.236 0.01 0 0 0.005 0.027 0.071 0.227 0.699* 1.064 2.11 5.338 South 89.5% 0.283 0.008 0 0 0.005 0.032 0.09 0.281 0.802 1.212 2.769 8.231 West 89.7% 0.22 0.009 0 0 0 0.028 0.072 0.198 0.59 1.009 1.944 5.946 NOTE: SE = Standard error P = Percentile of the distribution Source: Based on EPA's analyses of the 1989-91 CSFll Table 11-5. Per Caoita Intake of Poultrv la/ka-dav as consumed\ Population Percent Grouo Consumina .Mean SE P1 PS P10 P25 PSO P75 P90 P95 P99 P100 Total 91.7% 0.598 0.007 0 0 0.015 0.097 0.344 Q.83 1.506 2.035 3.273 12.239 Age (years) < 01 64.9% 0.816 0.087 0 0 0 0 0.178 1.07 2.467 3.453 7.373 12.239 01-02 94.2% 1.156 0.064 0 0.017 0.08 0.211 0.636 1.695 2.931 4.144 5.429 11.747 03-05 95.0% 1.068 0.049 0 0 0.044 0.18 0.607 1.647 2.662 3.603 5.024 7.565 06-11 95.7% 0.871 0.028 0 0.022 0.047 0.166 0.556 1.364 2.182 2.851 3.861 6.936 12-19 94.3% 0.558 0.017 0 0 0.02 0.088 0.378 0.813 1.476 1.806 2.394 3.535 20-39 !;14.6% i>.53 0.01 0 0.005 0.021 0.098 0.332 0.768 . 1.35 1.744 2.666 3.801 40-69 90.5% 0.477 0.01 0 0 0.011 0.084 0.294 0.696 1.192 1.528 2.358 6.219 70 + 86.7% 0.463 0.017 0 0 0 0.072 0.286 0.692 1.189 1.539 2.284 4.092 Season Fall 92.9% 0.635 0.015 0 0 0.022 0.112 0.366 0.867 1.571 2.209 3.543 12.239 Spring 91.0% 0.538 0.013 0 0 0.009 0.071 0.305 0.74 1.368 1.829 3.052 11.543 . Summer 90.4% 0.625 0.015 0 0 0.013 0.089 0.359 0.905 1.562 2.171 3.863 6.596 Winter 92.6% 0.595 0.014 0 0 0.025 0.113 0.372 0.82 1.443 1.94 3.091 8.418 Urbanization Central City 91.7% 0.627 0.014 0 0 0.011 0.095 0.333 0.877 1.589 2.218 3.518 12.239 Non metropolitan 90.6% 0.54 0.013 0 0 0.014 0.093 0.314 0.781 1.321 1.71 3.077 11.543 Suburban 92.4% 0.608 0.011 0 0 0.02 0.1 0.37 0.842 1.542 2.06 3.111 8.306 Race Asian 88.6% 0.79 0.068 0 0 0.035 0.112 0.503 1.15 1.901 2.368 2.939 4.7:45 Black 91.9% 0.798 0.025 0 0 0.02 0.143 0.521 1.133 1.867 2.352 4.288 12.239 Native American 80.7% 0.54 0.051 0 0 0 0.071 0.324 0.985 1.343 1.545 2.348 4.158 Other/NA 91.7% 0.81 .0.049 0 0 0.005 0.169 0.467 1.252 2.11 2.695 3.863 4.002 White 92.0% 0.559 0.007 0 0 0.016 0.092 0.318 0.771 1.419 1.906 3.091 11.543 Region Midwest 91.7% 0.551 0.014 0 0 0.013 0.095 0.318 0.735 1.328 1.938 3.244 11.747 Northeast 92.7% 0.651 0.017 0 0 0.016 0.093 0.391. 0.934 1.687 2.134 3.38 8.306 South 91.7% 0.643 0.012 0 0 0.02 0.106 0.394 0.93 1.581 2.173 3.426 8.418 West 91.0% 0.526 0.014 0 0 0.011 0.086 0.28 0.754 1.33 1.766 2.942 12.239 NOTE: SE = Standard error P = Percentile of the distribution Source: Based on EPA's analyses ofthe 1989-91 CSFll Table 11*6. Per Caoita Intake of Game Ca/ka*dav as consumed) Population Percent Grouo Consumina Mean SE P1 PS P10 P25 P50 P75 P90 P95 P99 P100 Total 1.2% 0.01 0.01 0 0 0 0 0 0 0 0 0.098 5.081 Age (years) < 01 0.5% 0.014 0.091 0 0 0 0 0 0 0 0 1.113 1.866 01*02 0.9% 0.026 0.125 0 .o 0 0 0 0 0 0 0.692 2.638 03-05 1.5% 0.01 0.04 0 0 0 0 0 0 0 0 0 2.953 06-11 1.1% 0.004 0.016 0 0 0 0 0 0 0 0 0 1.176 12-19 1.0% 0.004 0.019 . 0 0 0 0 .o 0 0 0 0 1.78 20-39 1.3% 0.01 0.021 0 0 0 0 0 0 0 0 0.098 5.081 40-69 1.3% 0.012 0.017 0 0 0 0 0 0 0 0 0.462 2.882 70 + 1.1% 0.002 0.01 0 0 0 0 0 0 0 0 0 2.261 Season Fall 1.7% 0.016 0.022 0 0 0 0 0 0 0 0 0.521 3.488 Spring 0.7% 0.006 0.019 0 0 0 0 0 0 0 0 0 2.882 Summer 0.7% 0.003 0.012 0 0 0 0 0 0 0 0 0 1.78 Winter 1.6% 0.013 0.021 0 0 0 0 0 0 0 0 0.446 5.081 Urbanization Central City 0.7% 0.005 0.014 0 0 0 0 0 0 0 0 0 1.8 Nonmetropolitan 2.0% 0.019 0.018 0 0 0 0 0 0 0 0 0.822 1.866 Suburban 1.1% 0.008 0.018 0 0 0 0 0 0 0 0 0 5.081 Race* Asian 0.0% *o 0 0 0 0 0 0 0 0 0 0 0 Black 0.1% 0.001 0.027 0 0 0 0 0 0 0 0 0 0.887 Native American 0.6% 0.001 0.012 0 0 0 0 0 0 0 0 0 0.255 Other/NA 0.3% 0.003 0.046 0 0 0 0 0 0 0 0 0 0.636 White 1.4% 0.011 0.011 0 0 0 0 0 0 0 0 0.329 5.081 Region. Midwest 2.2%' 0.012 0.012 0 0 0 0 0 0 0 0 0.588 1.866 Northeast 0.5% 0.005 0.026 0 0 0 0 0 0 0 0 0 2.055 South 0.8% 0.009 0.025 0 0 0 0 0 0 0 0 0 5.081 West 1.3% 0.012 0.022 0 0 0 0 0 0 0 0 0.446 2.953 NOTE: SE = Standard error P = Percentile of the distribution Source: Based on EPA's analvses of the 1989-91 CSFll Table 11-7. Per Caoita Intake of Enns fo/ka-dav as consumed) Population Percent Grouo Consumina Mean SE P1 PS P10 P25 P50 P75 P90 P95 P99 P100 Total 41.4% 0.317 0.009 0 0 0 0 0 0.445 0.,968 1.422 2.953 13.757 Age (years) < 01 32.3% 0.791 0.126 0 0 0 0 0 1.537 2.744 3.645 5.487 13.757 01-02 43.3% 0.822 0.087 0 0 0 0 0 1.381 2.604 3.299 5.242 8.577 03-05 39.6% 0.677 0.088 0 0 0 0 0 0.89. 2.224 3.106 7.475 10.799 06-11 36.6% 0.414 0.033 0 0 0 0 0 0.735 1.312 1.617 3.037 6.331 12-19 36.0% 0.244 0.023 0 0 0 0 0 0.345 0.828 1.26 2.137 4.12 20-39 43.3% 0.271 0.012 0 0 0 0 0 0.439 0.897 1.193 1.764 5.392 40-69 44.0% 0.225 0.009 0 0 0 0 0 0.375 0.725 1.029 1.496 3.216 70+ 42.0% 0.218 0.017. 0 0 0 0 0 0.328 0.653 0.969 1.582 2.791 Season Fall 40.1% 0.291 0.017 0 0 0 0 *o 0.422 0.871 1.237 2.744 6.331 Spring 42.7% 0.307 0.017 0 0 0 0 0 0.402 1.015 1.42 2.604 13.548 Summer 40.5% 0.344 0.02 0 0 0 0 0 0.476 1.035 1.496 3.533 13.757 Winter 42.2% 0.325 0.019 0 0 0 0 0 0.47 0.98 1.409 2.841 11.39 Urbanization Central City .41.6% 0.315 0.018 0 0 0 0 0 0.423 0.924 1.422 3.106 13.757 Nonmetropolitan 43.8% 0.338 0.018 0 0 0 0 0 0.493 1.043 1.438 2.826 13.548 Suburban 39.7% 0.309 0.013 0 0 0 0 0 0.434 0.95 1.399 2.73 11.39 Race Asian 38.9% 0.452 0.094 0 0 0 0 0 0.615 1.47 2.604 2.672 2.672 Black 48.9% 0.385 0.023 0 0 0 0 0 0.595 1.134 1.486 2.881 6.213 Native American 49.7% 0.491 0.17 0 0 0 0 0 0.457 1.395 1.61 10.799 13.548 Other/NA 55.1% 0.472 0.056 0 0 0 0 0 0.712 1.26 2.247 3.292 5.997 White 39.5% 0.297 0.01 0 0 0 0 0 0.408 0.922 1.368 2.906 13.757 Region Midwest 36.9% 0.288 0.019 0 0 0 0 0 0.35 0.893 1.44 3.106 13.548 Northeast 35.9% 0.264 0.02 0 0 0 0 0 0.376 0.791 1.229 2.815 11.39 South 44.3% 0.325 0.014 0 0 0 0 0 0.469 0.999 1.422 2.531 8.737 West 46.6% 0.392 0.022 0 0 0 0 0 0.563 1.135 1.603 3.08 13.757 NOTE: SE = Standard error P = Percentile of the distribution Source: Based on EPA's analyses of the 1989-91 CSFll Table 11-8. Main Daily Intake of Meat and Dairy Products Per Individual in a Day for USDA 1977-78, 87-88, 89-91, 94, and 95 Surveys _7J-78 Data 87-88 Data 89-91 Data 94 Data 95 Data Food Product (g-day) (g/day) (g/day) (g/day) (g/day) Beef 52 32 26 24 27 Poultry 25 26 27 29 24 Meat Mixtures 1 69 86 90 95 104 Dairy Products' 314 290 286 277 284 1 Includes mixtures having meat, poultry, or fish as a main ingredient; frozen meals in which the main course is a meat, poultry, or fish item; meat, poultry, or fish sandwiches coded as a single item; and baby-food meat and poultry mixtures. ' 2 Includes total milk, cream, milk desserts, and cheese. Total inilk inclL1des fluid milk, yogurt, flavored milk, milk drinks, meal replacements with milk, milk-based infant formulas, and unreconstituted dry milk and powdered mixtures. Sources: USDA, 1980; 1992; 1996a; 1996b.

Table 11-9. Mean Per Capita Intake Rates for Meat, Poultry, and Dairy Products (g/kg-d as consumed) Based on All Sex/Age/Demographic Subgroups Average Consumption Raw Aaricultural Commodity* (Grams/k!I Body Wei11ht/Dav) Standard Error Milk-Non-Fat Solids 0.9033354 0.0134468 Milk-Non-Fat Solids (Food additive) 0.9033354 0.0134468 Milk-Fat Solids 0.4297199 0.0060264 Milk-Fat Solids (Food additive) 0.4297199 0.0060264 Milk Sugar (Lactose) 0.0374270 0.0033996 Beef-Meat Byproducts 0.0176621 0.0005652 Beef (Organ -Other 0.0060345 0.0007012 Beef-Dried 0.0025325 0.0004123 Beef (Boneless) -Fat (Beef Tallow) 0.3720755 0.0048605 Beef (Organ Meats) -Kidney 0.0004798 0.0003059 Beef (Organ Meats) -Liver 0.0206980 0.0014002 Beef (Boneless) -Lean (w/o Removeable Fat) 1.1619987 0.0159453 Goat-Meat Byproducts 0.0000000 NA Goat (Organ Meats) -Other 0.0000000 NA Goat (Boneless) -Fat 0.0000397 . 0.0000238 Goat (Organ Meats) -Kidney 0.0000000 NA Goat (Organ Meats) -Liver 0.0000000 NA Goat (Boneless) -Lean (w/o Removeable Fat) 0.0001891 0.0001139 Horse 0.0000000 NA Rabbit 0.0014207 0.00003544 Sheep -Meat Byproducts 0.0000501 0.0000381 Sheep (Organ Meats) -Other 0.0000109 0.0000197 Sheep (Boneless) -Fat 0.0042966 0.0005956 Sheep (Organ Meats) -Kidney 0.0000090 0.0000079 Sheep (Organ Meats) -Liver 0.0000000 NA Sheep (Boneless) -Lean (w/o Removeable Fat) 0.0124842 0.0015077 Pork -Meat Byproducts 0.0250792 0.0022720 Pork (Organ Meats) -Other 0.0038496 0.0003233 Pork (Boneless) -Fat (Including Lard) 0.2082022 0.0032032 Pork (Organ Meats) -Kidney 0.0000168 0.0000106 Pork (Organ Meats) -Liver 0.0048194 0.0004288 Pork (Boneless) -Lean {w/o Removeable Fat) 0.3912467 0.0060683 Meat, Game 0.0063507 0.0010935 Turkey -Byproducts 0.0002358 0.0000339 Turkey -Giblets (Liver) 0.0000537 0.0000370 Turkey -Flesh (w/o Skin, w/o Bones) 0.0078728 0.0007933 Turkey -Flesh (+ Skin, w/o Bones) 0.0481655 0.0026028 Turkey -Unspecified 0.0000954 0.0000552 Poultry, Other -Byproducts 0.0000000 NA Poultry, Other -Giblets (Liver) 0.0002321 0.0001440 Poultry, Other -Flesh (+ Skin, w/o Bones) 0.0053882 0.0007590 Eggs-Whole 0.5645020 0.0076651 Eggs -White Only 0.0092044 0.0004441 Eggs -Volk Only 0.0066323 0.0004295 Chicken -Byproducts 0.0000000 NA Chicken -Giblets (Liver) 0.0050626 0.0005727 Chicken -Flesh (w/o Skin, w/o Bones) 0.0601361 0.0021616 Chicken -Flesh I+ Skin w/o Bones\ 0.3793205 0.0104779 NA = Not applicable

Consumed in any raw or prepared form. *source: ORES database lbased on 1977-78 NFCSl Table 11-10, Mean Meat Intakes Per Individual.in a Day, by Sex and Age (g/day as consumed)" for 1977-1978 Total Lamb, Frankfurters, Meat, Veal, Sausages, Total Chicken Meat* Group Age (yrs.) Poultry and Beef Pork Game Luncheon Meats, Poultry Only Mixtures* Fish Spreads Males and Females 1 and Under 72 9 4 3 2 4 1 51 1-2 91 18 6 (b) 15 16 13 32 3-5 121 23 8 (b) 15 *19 19 49 6-8 149 33 15 1 17 20 19 55 Males 9-11 188 41 22 3 19 24 21 71 12-14 218 53 18 (b) 25 27 24 87 15-18 272 82 24 1 25 37 32 93 19-22 310 90 21 2 33 45 43 112 23-34 285 86 27 1 30 31 29 94 35-50 295 75 28 1 26 31 28 113 51-64 274 70 32 1 29 31 29 86 65-74 231 54 25 2 22 29 26 72 75 and Over 196 41 39 7 19 28 25 54 Females 9-11 162 38 17 1 20 27 23 55 12-14 176 47 19 1 18 23 22 61 15-18 180 46 14 2 16 28 27 61 19-22 184 52 19 1 .18 26 24 61 23-34 183 48 17 1 16 24 22 66 35-50 187 49 19 2 14 24 21 63 51-64 187 52 19 2 12 26 24 60 65-74 159 34 21 4 12 30 25 47 75 and Over 134 31 17 2 9 19 16 49 Males and Females All Aaes 207 54 20 2 20 27 24 72
Based on USDA Nationwide Food Consum*ption Survey 1977-78 data for one day.
Less than 0.5 g/day but more than 0.
Includes mixtures containing meat, poultry, or fish as a main ingredient. Source: USDA, 1980.

Table 11-11. Mean Meat Intakes Per Individual in a Day, by Sex and Age (g/day as consumed)" for 1987-1988 Total Meat, Lamb, Frankfurters, Group Poultry, and Veal, Sausages, Total , Chicken Meat Age (yrs.) Fish Beef Pork Game Luncheon Poultry Only Mixturesb Meats Males and Females 5 and Under 92 10 9 <0.5 11 14 12 39 Males 6-11 156 22 14 <0.5 13 27 24 74 12-19 252 38 17 1 20 27 20 142 20 and over 250 44 19 23 2 31 25 108 Females 6-11 151 26 9 1 11 20 17 74 12-19 169 31 10 <0.5 18 17 13 80 20 and over 170 29 12 1 13 24 18 73 All individuals 193 32 14 1* 17 26 20 86

Based on USDA Nationwide Food Consumption Survey 1987-.88 data for one day. b Includes mixtures containing meat, poultry, or fish as a main ingredient. Source: USDA, 1992.

Table 11-12. Mean Dairy Product Intakes Per Individual in a Day, by Sex and Age (g/day as consumed)" for 1977-1978 Group A!:!e (vrs.) Total Milk Fluid Milk Cheese Eaas 1 and Under 618 361 1 5 1-2 404 397 8 20 3-5 353 330 9 22 6-8 433 401 10 18 9-1°1 432 402 8 26 12-14 504 461 9 28 15-18 519 467 13 . 31 19-22 388 353 15 32 23-34 243 213 21 38 35-50 203 192 18 41 51-64 180 173 17 36 65-74 217 204 14 36 75 and Over 193

134 18 41 9-11 402 371 7* 14 12-14 387 343 11 19 15-18 316 279 11 21 19-22 224 205 18 26 23-34 182 158 19 26 35-50 130 117 18 23 51-64 139 128 19 24 65-74 166 156 14 22 75 and Over 214 205 20 19 All Aaes 266 242 15 27
Based on USDA Nationwide Food Consumption Survey 1977-78 data for one day. Source: USDA, 1980.

Table 11-13. Mean Dairy Product Intakes Per Individual in a Day, by Sex and Age (g/day as consumed)* for 1987-1988 Group Age (yrs.) Total Fluid Milk Whole Milk Lowfat/Skim Cheese Eggs Milk Males and Fem<1les 5 and under 347 177 129 7 11 Males* 6-11 439 159 10 17 12-19 392 183 168 12 17 20 and over 202 88 94 17 27 Females 6-11 310 135 135 9 14 12-19 260 124 114 12 18 20 and over 148 55 81 15 17 All individuals 224 99 102 14 20

Based on USDA Nationwide Food Consumption Survey 1987-88 data for one day. Source: USDA, 1992. \

Table 11-14. Mean Meat Intakes Per Individual in a Day, by Sex and Age (g/day as consumed)* for 1994 and 1995 Frankfurters, Total Meat, Sausages, Group Poultry, and _Lamb, Veal, Luncheon Meat Age (yrs.) Fish Beef Pork Game Meats Total Poultry Chicken Only Mixtures* 1994 1995 1994 1995 1994 1995 1994 1995 1994 1995 1994 1995 1994 1995 1994 1995 Males and Females 5 and Under 94 87 10 8 6 4 (b) (b) 17 18 16 15 14 14 41 39 Males 6-11 131 161 19 18 9 7 0 (b) 22 27 19 25 16 22 51 68 12-19 238 256 31 29 11 11 1 1 21 27 40 26 29 23 119 150 20 and over 266 283 35 41 17 14 2 1 29 27 39 31 30 27 124 149 Females 6-11 117 136 18 16 5 5 (b) (b) 18 20 19 17 15 14 51 69 12-19 164 158 23 22 5 7 (b) 0 16 10 20 19 15 18 94 82 20and over 168 167 18 21 9 11 1 1 16 15 25 22 20 19 87 83 All individuals 195 202 24 27 11 10 1 1 21 21 29 24 23 21 91! 104

Based on USDA CSE"ll 1994 and 1995 data for one day.
Less than 0.5 g/day but more than o. 0 Includes mixtures containing meat, poultry, or fish as a main ingredient. Source: USDA, 1996a; 1996b.

Table 11-15. Mean Dairy Product Intakes Per Individual in a Day, by Sex and Age (g/day as consumed)" for 1994 and Group Age (yrs.) Total Fluid Milk Whole Milk Lowfat Milk Cheese Eggs 1994 1995 1994 1995 1994 1995 1994 1995 1994 1995 Males and Females 5 and under ' 424 441 169 165 *130 129 12 9 11 13 Males 6-11 407 400 107 128 188 164 11 12 13 15 12-19 346 396 105 105 160 176 19 20 18 24 20 and over 195 206 50 57 83 88 19 16 23 23 Females 6-11 340 330 101 93 136 146 17 13 12 15 12-19 239 235 75 71 88 107 14 13 13 17 20 and over 157 158 37 32 56 57 16 15 15 16 All individuals 229 236 65 66 89 92 17 15 17 19

Based on USDA CSFll 1994 and 1995 data for one day. Source: USDA, 1996a; 1996b. ----------------------------------------------

Table 11-16. Mean and Standard Error for the Dietary Intake of Food Sub Classes Per Capita by Age (g/day as consumed) Fresh Cows' Other Dairy Age (yrs.) Milk Products Eggs Beef Pork Poultry Other Meat All Ages 253.5 +/- 4.9 55.1 +/- 1.2 26.9 +/- 0.5 87.6 +/- 1.1 28.2 +/- 0.6 31.3 +/- 0.8 25.1+/-0.4 <1 272.0 +/- 31.9 296.7 +/- 7.6 4.9 +/- 3.2 18.4 +/- 7.4 5.8 +/- 3.6 18.4 +/- 4.9 2.6 +/- 2.8 1-4 337.3 +/- 15.6 41.0 +/- 3.7 19.8 +/- 1.6 42.2 +/- 3.7 13.6 +/- 1.8 19.0 +/- 2.4 17.6 +/- 1.4 5-9 446.2 +/- 13.1 47.3 +/- 3.1 17.0+/-1.3 63.4 +/- 3.1 18.2 +/- 1.5 24.7 +/- 2.0 22.3 +/- 1.2 10-14 456.0+/-12.3 53.3 +/- 2.9 19.3 +/- 1.2 81.9 +/- 2.9 22.2 +/- 1.4 30.0 +/- 1.9 26.1+/-1.1 15-19 404.8+/-12.9 52.9 +/- 3.1 .. 24.8 +/- 1.3 99.5 +/- 3.0 29.5 +/- 1.5 33.0 +/- 2.0 27.6+/-1.1 20-24 264.3 +/- 16.4 44.2 +/- 4.0 28.3 +/- 1.7 103.7 +/- 3.9 29.6 +/- 1.9 33.0 +/- 2.6 28.8 +/- 1.5 25-29 217.6 +/- 17.2 51.5 +/- 4.1 27.9 +/- 1.7 103.8 +/- 4.0 31.8 +/- 2.0 33.8 +/- 2.7 28.9 +/- 1.5 30-39 182.9 +/- 13.5 53.8 +/- 3.2 30.1+/-1.4 105.8 +/- 3.2 33.0 +/- 1.5 34.0 +/- 2.1 28.4 +/- 1.2 40-59 169.1+/-10.5 52.0 +/- 2.5 31.1+/-1.0 99.0 +/- 2.5 33.5 +/- 1.2 33.8 +/- 1.6 . 27.4 +/- 0.9 ;,60 192.4 +/- 11.8 55.9 +/-.2.8 28.7 +/- 1.2 74.3 +/- 2.8 27.5 +/- 1.3 31.5 +/- 1.8 21.1+/-1.0 Source: U.S. EPA, 1984a (based on 1977-78 NFCS). Table 11-17. Mean and Standard Error for the Per Capita Daily Intake of Food Class and Sub Class by Region (g/day as consumed) US Population Northeast North Central South West Products ([otal} 308.6 +/- 5.3 318.6+/-10.4 336.1 +/- 10.0 253.6 +/- 8.4 348.1 +/- 12.3 Fresh Cows Milk 253.5 +/- 4.9 256.1 +/- 9.7 279.7 +/- 9.4 211.0 +/- 7.8 283.5 +/- 11.5 Other 55.1 +/- 1.2 62.5 +/- 2.3 56.5 +/- 2.2 42.6 +/- 1.9 64.6 +/- 2.7 26.9 +/- 0.5 23.8 +/- 1.0 23.5 +/- 0.9 31.0 +/- 0.8 29.1 +/- 1.2 Meats (Total) 172.2 +/- 1.6 169.9 +/- 3.3 176.9 +/- 3.1 171.9 +/- 2.6 168.6 +/- 3.9 Beef and Veal 87.6 +/- 1.1 82.3 +/- 2.3 92.9 +/- 2.2 84.0 +/- 1.8 92.9 +/- 2.7 Pork 28.2 +/- 0.6 28.8+/-1.1 29.6 +/- 1.1 *30.1+/-0.9 22.1+/-1.3 Poultry 31.3 +/- 0.8 31.7 +/- 1.5 26.6 +/- 1.4 36.5 +/- 1.2 28.9 +/- 1.8 Other 25.1+/-0.4 27.1+/-0.9 27.8 +/- 0.8 21.3 +/- 0.7 24.7 +/- 1.0 NOTE: Northeast= Maine, New Hampshire, Vermont, Massachusetts, Connecticut, Rhode Island, New York, New Jersey, and Pennsylvania. North Central = Ohio, Illinois, Indiana, Wisconsin, Michigan, Minnesota, Iowa, Missouri, North Dakota, South Dakota, Nebraska, and Kansas. South = Marylam;l. Delaware, District of Columbia, Virginia, West Virginia, North Carolina, South Carolina, Georgia, Florida, Kentucky, Tennessee, Alabama, Mississippi, Arkansas, Louisiana, Texas, and Oklahoma. West = Montana, Idaho, Wyoming, Utah, Colorado, New Mexico, Arizona, Nevada, Washington, Oregon, and California. Source: U.S. EPA, 1984b (based on 1977-78 NFCS). Table 11*18. Consumption of Meat, Poultry, and Dairy Products for Different Age Groups (averaged across sex), and Estimated Lifetime Average Intakes for 70 Kg Adult Citizens Calculated from the FDA Diet Data. Baby Toddler Child Teen Adult Old Estimated Produce (0*1 yrs) 1-6 yrs) (6-14 yrs) (14*20 yrs) (20-45 yrs) (45-70 yrs) Lifetime Intake' !'.I

dry weiQhl/dav Beef 3.99 9.66 15.64 21.62 23.28 18.34 19.25 Beef Liver 0.17 0.24 0.30 0.36 1.08 1.2 0.89 Lamb 0.14 0.08 0.06 0.05 0.30 0.21 0.20 Pork 1.34 4.29 6.57 8.86 10.27 9.94 9.05 Poultry 2.27 3.76 5.39 7.03 7.ji4 6.87 6.70 Dairy 40.70 32.94 38.23 43.52 27.52 22.41 28.87 Eggs 3.27 6.91 7.22 7.52 8.35 9.33 8.32 Beef Fat 2.45 6.48 11.34 16.22 20.40 14.07 15.50 Beef Liver Fat 0.05 0.07 0.08 0.10 0.29 0.33 0.25 Lamb Fat 0.14 0.08 0.07 0.06 0.31 0.22 0.21 Dairy Fat 38.99 16.48 20.46 24.43 18.97 14.51 18.13 Pork Fat 2.01 8.19 10.47 12.75 14.48 13.04 12.73 Poultry Fat 1.10 0.83 1.12 1.41 1.54 1.31 1.34 *The estimated lifetime dietary in.takes were estimated by: Estimated lifetime intake= IR(0-1} + 5yrs" IR (1-5} + 8 yrs* IR (6-13} + 6 yrs" IR {14-19} + 25 yrs" IR {20-44) + 25 yrs" IR {45-70) 70 years* where IR = the intake rate for a specific age group. Source: U.S. EPA, 1989 (based in 1977-78 NFCS and NHANES II data).

Table 11-19. Per Capita Consumption of Meat and Po1:1ltry in 1991a Per Capita Consumption Per Capita Per Capita Consumption Retail Per Capita Consumption Boneless Carcassb Weight Consumption RTC". Cut Equivalentd Trimmed Equivalente Food Item ln/daul1 ln/dau\I ln/da" ln/da;,\I Red Meat Beef 118.3 ---82.8 78.4 Veal 1.5 ---1.2 0.99 Pork 8.0 ---62.1 58.3 Lamb and Mutton 2.0 --1.7 1.2 Totalg 201.7 --147.9 *139.1 Poultry Young Chicken ------78.3 ---Other Chicken ------1.7 ---Chicken ---91.3 ---54.Sh,i Turkey ---22.2 ---17.5" Total* ---109.2 77.0 72.1 . Includes processed meats and poultry in a fresh basis; excludes shipments to U.S. territories; uses U.S. total population, July 1, and does not include residents of the U.S. territories. b Beef-Carcass-Weight is the weight of the chilled hanging*carcass, which includes the kidney and attached internal fat [kidney, pelvic, and heart fat (kph)] but not head, feet, and unattached internal organs. Definitions of carcass weight for other red meats differ slightly. RTC -ready-to-cook poultry weight is the entire dressed bird which includes bones, skin, fat, liver, heart, gizzard, and neck. ' Retail equivalents in 1991 were converted from carcass weight by multiplying by a factor of 0.7, 0.83, 0.89, and 0.776 for beef, veal, lamb, and pork, respectively; 0.877 was the factor used each for young chicken and other chicken. Boneless equivalent for red meat derived from carcass weight in 1991 by using conversion factors of 0.663, 0.685, 0.658 and 0.729 for beef, veal, lamb, and pork, respectively; 0.597, 0.597 and 0.790 were the factors used for young chicken, other chicken, and turkey. I Original data were presented in lbs; converted to g/day by multiplying by a factor of 453.6 glib and dividing by 365 days/yr. g Computed from unrounded data. h Includes skin, neck, and giblets. I Excludes amount of RTC chicken going to pet food as well as some water leakage that occurs when chicken is cut-up before packaging. Source: USDA 1993. Table 11-20. Per Capita Consumption of Dairy Products in 1991" Food Item Per Capita Food Item Per Capita Consumption Consumption (a/dav)i (a/dav)i Cheese Farm Weightb,e 37.8 American Retail Weightc,e 37.3 Cheddar 11.2 Otherd 2.5 Fluid Milk and Cream 289.7 Italian Plain Whole Milk 105.3 Provolone 0.8 Lowfat Plain Milk (2%) 98.1 Romano 0.2 Lowfat Plain Milk (1 %) 25.8 Parmesan 0.6 Skim Plain Milk 29.7 Mozzarella 9.0 Whole Flavored Milk and Drink 3.4 Ricotta 1.0 Lowfat Flavored Milk and Drink 8.5 Other 0.07 Buttermilk (lowfat and skim) 4.2 Miscellaneous Half and Half Cream 3.9 Swiss' 1.5 Light Cream 0.4 Brick 0.07 Heavy Cream 1.6 Muenster 0.5 Sour Cream 3.2 Cream 1.9 Eggnog 0.5 Neufchatel 0.3 Blue9 0.2 Eva(!orated and Condensed Milk; Other 1.2 Canned Whole Milk 2.6 Processed Products Bulk Whole Milk 1.4 Cheese 6.1 Bulk and Canned Skim Milk 6.2 Foods and spreads 4.7 Total* 10.2 Cheese Content 8.5 Consumed as Natural 22.6 Da Milk Products; Cottage Cheese (lowfat) 1.6 Dry Whole Milk 0.5 Nonfat Dry Milk . 3.2 Frozen DairJl Products Dry Buttermilk 0.3 Ice Cream 20.3 Total" 4.0 Ice Milk 9.2 Dried Whey 4.5 Sherbet 1.5 Other Frozen Productsh 5.3 Butter 5.2 Total* 36.4 All Diary Products USDA Donations 17.1 Commercial Sales 685.2 Total 702.4 a All per capita consumption figures use U.S. total populations, except fluid milk and cream data, which are based on U.S. residential population. For eggs, excludes shipments to U.S. territories, uses U.S. total population, July 1, which does not include U.S. territories. b A dozen eggs converted at 1.57 pounds. c The factor for converting farm weight to retail weight was 0.97 in 1960 and was increased 0.003 per year until 0.985 was reached in 1990. d Includes Colby, washed curd, Monterey, and Jack. e Computed from unrounded data. f Includes imports of Gruyere and Emmenthaler. 9 Includes Gorgonzola. h Includes mellorine, frozen yogurt beginning 1981, and other nonstandardized frozen diary products. ; Includes quantities used in other dairy products. j Original data were presented in lbs, conversions to g/day were calculated by multiplying by a factor of 453.6 and dividing by 365 days. Source: USDA 1993. Table 11-21. Adult Mean Dailv Intake (as consumed) of Meat and Poultrv Grouoed bv Reaion and Gender* Mean Daily Intake (g/day) Region Pacific Mountain North Central Northeast South Food Item Male Female Male Female Male Female Male Female Male Female Beef 84.8 52.8 89.8 59.6 86.8 55.9 71.8 46.6 87.3 54.9 Pork 18.6 12.6 23.7 16.8 26.5 18.8 22.4 15.9 24.4 17.2 Lamb 1.3 1.2 0.5 0.3 0.4 0.4 1.3 1.0 0.5 0.3 Veal 0.4 0.2 0.2 0.2 0.4 0.4 2.8 1.5 0.3 0.3 Variety Meats/Game 11.1 7.9 9.1 7.4 11.9 8.0 8.1 6.8 9.4 7.8 Processed Meats 22.8 15.4 22.9 13.2 26.3 15.8 21.2 15.5 26.0 17.0 Poultrv 67.3 56.1 51.0 45.2 51.7 44.7 56.2 49.2 57.7 50.2 a Adult population represents consumers ages 19 and above. NOTE: Pacific = Washington, Oregon and California Mountain = Montana, Idaho, Wyoming, Utah, Colorado, New Mexico, Arizona, and Nevada North Central = Ohio, Illinois, Indiana, Wisconsin, Michigan, Minnesota, Iowa, Missouri, North Dakota, South Dakota, Nebraska, and Kansas. Northeast= Maine, New Hampshire, Vermont, Massachusetts, Connecticut, Rhode Island, New York, New Jersey, and Pennsylvania. South = Maryland, Delaware, District of Columbia, Virginia, West Virginia, North Carolina, South Carolina, Georgia, Florida, Kentucky, Tennessee, Alabama, Mississippi, Arkansas, Louisiana, Texas, and Oklahoma. Source: National Livestock and Meat Board, 1993. Table 11-22. Amount las consumed) of Meat Consumed bv Adults Grouoed bv Freauencv of Eatinas* Percent of Eaters Total Consumption Median Daily Percent of Total Male Female for 14 Days Intake Freciuencv of Eatini:is Eaters (Q) (Q/dav) Non-Meat Eaters* 1% 20 80 None None Light Meat Eatersb 30% 27 73 <1025 54 Medium Meat Eaters' 33% 39 61 1025-1584 93 Heavv Meat Eaters* 36% 73 27 >1548 144

A female who is employed and on a diet. She lives alone 01'. in a small household (without children). b Female who may or may not be on a diet. There are probably 2-4 people in her household but that number is not likely to include children. ' This person may be of either sex, might be on a diet, and probably lives in a household of 2-4 people, which may include children.
Male who is not on a diet and lives in a household of 2-4 individuals, which may include children.
Adult population represents consumers ages 19 and above. Source: National Livestock and Meat Board 1993.

Table 11-23. Quantity (as consumed) of Meat, Poultry, and Dairy Products Consumed Per Eating Occasion and the PercentaQe of Individuals UsinQ These Foods in Three Days % lndiv. using Quantity consumed per eating food in 3 days occasion Consumers-only Food category (g) Quantity consumed per eatinQ occasion at Specified Percentiles (!'.!) Average Standard 5 25 50 75 90 95 99 Deviation Meat* 84.6 107 85 16 46 86 140 224 252 432 Beef 67.3 133 85 41 84 112 168 224 280 448 Pork 49.9 69 69 8 16 44 92 160 194 320 Lamb 1.5 146 84 43 88 123 184 227 280 448 Veal 2.3 130 71 42 84 112 168 224 276 352 Poultry 42.8 128 77 42 82 112 168 224 280 388 Chicken 38.7 131 76 43 84 112 170 224 280 388 Turkey 5.8 105 73 28 57 86 129 172 240 350 Dairy: Products Eggs 54.3 82 44 40 50 64 100 128 150 237 Butter 31.4 12 13 2 5 7 14 28 28 57 Margarine 43.1 11 11 2 5 7 14 28 28 57 Mil kb 82.5 203 134 15 122 244 245 366 488 552 Cheese* 40 41 28 14 28 28 56 58 85 140

Meat -beef, pork, lamb, and veal.
Milk -fluid milk, milk beverages, and milk-based infant formulas. c Cheese -natural and processed cheese. Source: Pao et al., 1982 (based on 1977-78 NFCS).

Table 11-24. Percentage Lipid Content (Expressed as Percentages of 100 Grams of Edible Portions) of Selected Meat and Dairv Products* Product Fat Percentage Comment Meats Beef Lean only 6.16 Raw Lean and fat, 1/4 in. fat trim 9.91 Cooked Brisket (point halO 19.24 Raw Lean and fat 21.54 Cooked Brisket (flat halO Lean and fat 22.40 Raw Lean only 4.03 Raw Pork Lean only 5.88 Raw 9.66 Cooked Lean and fat 14.95 Raw 17.18 Cooked Cured shoulder, blade roll, lean and fat 20.02 Unheated Cured ham, lean and fat 12.07 Center slice Cured ham, lean only 7.57 Raw, center, 'country style Sausage 38.24 Raw, fresh Ham *4.55 Cooked, extra lean (5% fat) Ham 9.55 Cooked, (11 % fat) Lamb Lean 5.25 : Raw 9.52 Cooked Lean and fat 21.59 Raw 20.94 Cooked Veal Lean 2.87 Raw 6.58 Cooked Lean and fat 6.77 Raw 11.39 Cooked Rabbit Composite of cuts 5.55 Raw 8.05 Cooked Chicken Meat only 3.08 Raw 7.41 Cooked Meat and skin 15.06 Raw 13.60 Cooked Turkey Meat only 2.86 Raw 4.97 Cooked Meat and skin 8.02 Raw 9.73 Cooked Ground 6.66 Raw Table 11-24. Percentage Lipid Content (Expressed as Percentages of 100 Grams of Edible Portions) of Selected Meat and Dairv Products* (continued) Product Fat Percentage Comment Dairy Milk Whole 3.16 3.3% fat, raw or pasteurized Human 4.17 Whole, mature, fluid Lowfat (1%) 0.83 Fluid Lowfat (2%) 1.83 Fluid Skim 0.17 Fluid Cream Half and half 18.32 Table or coffee, fluid Medium 23.71 25% fat, fluid Heavy-whipping 35.09 Fluid Sour 19.88 Cultured Butter 76.93 Regular Cheese American 29.63 Pasteurized Cheddar 31.42 Swiss 26.02 Cream 33.07 Parmesan 24.50; 28.46 Hard; grated Cottage 1.83 Lowfat, 2% fat Colby 30.45 Blue 27.26 Provolone 25.24 Mozzarella 20.48 Yogurt 1.47 Plain, lowfat Eggs 8.35 Chicken, whole raw, fresh or frozen

Based on the lipid content in 100 grams, edible portion. Source: USDA, 1979-1984.

Table 11-25. Fat Content of Meat Products Meat Product Total Fat Percent Fat 3-oz cooked servinci (85.05 ci) (Cl) Content(%) Beef, retail composite, lean only 8.4 9.9 Pork, retail composite, lean only 8.0 9.4 Lamb, retail composite, lean only 8.1 9.5 Veal, retail composite, lean only 5.6 6.6 Broiler chicken, flesh only 6.3 7.4 Turkev. flesh onlv 4.2 4.9 Source: National Livestock and Meat Board 1993 .-------------------------Table 11-26. Fat Intake, Contribution of Various Food Groups to Fat Intake, and Percentage of the Population in Various Meat Eater Groups of the U.S. Population Total Heavy Meat Medium Meat

Light Meat Non-Meat Pooulation Eaters Eaters Eaters Eaters Average Fat Intake (g) 68.3 84.5 62.5 53.5 32.3 Percent of Population 100 36 33 30 1 Meat Group (%)" 41 44 40 37 33 Bread Group (%) 24 23 24 26 25 Milk Group (%) 12 11 13 14 14 Fruits(%) 1 1 1 1 1 Vegetables (%) 9 9 9 9 11 Fats/oil/sweets (%) 13 12 13 14 17 a Meat Group includes meat, poultry, dry beans, eggs, and nuts. Source: National Livestock and MeatBoard, 1993.

Table 11-27. Mean Total Daily Dietary Fat Intake (ci/day) Grouped by Acie and Gender" Total Males Females Age N Mean Fat Intake N Mean Fat Intake N Mean Fat Intake (vrs) (ci/day) Ca/dav) (Cl/day) 2-11 (months) 871 37.52 439 38.31 432 36.95 1-2 1,231 49.96 ) 601 51.74 630 48.33 3-5 1,647 60.39 744 70.27 803 61.51 6-11 1,745 74.17 868 79.45 877 68.95 12-16 711 85.19 338 101.94 373 71.23 16-19 785 100.50 308 123.23 397 77.46 20-29 1,882 97.12 844 118.28 638 76.52 30-39 1,628 93.84 736 114.28 791 74.06 40-49 1,228 84.90 626 99.26 602 70.80 50-59 929 79.29 473 96.11 456 63.32 60-69 1,108 69.15 646 80.80 560 59.52 70-79 851 61.44 444 73.35 407 53.34 :;., 80 809 54.61 290 68.09 313 47.84 . Total 14,801 81.91 7,322 97.18. 7,479 67.52 :;., 2 13 314 82.77 6 594 98.74 8720 68.06 a Total dietary fat intake includes all fat (i.e., saturated and unsaturated) derived from consumption of foods and beverages (excluding plain drinking water). Source: Adaoted from CDC 1994. Table 11-28. Percentage Mean Moisture Content (Expressed as Percentages of 100 Grams of Edible Portions)" Food Moisture Content Comments Percent Meat Beef " 71.60 Raw, composite, trimmed, retail cuts Beef liver 68.99 Raw Chicken (light meat) 74.86 Raw, without skin Chicken (dark meat) 75.99 Raw, without skin Duck-domestic 73.77 Raw Duck-wild 75.51 Raw Goose -domestic 68.30 Raw Ham -cured 66.92 . Raw Horse 72.63 Raw, roasted 63.98 Cooked, roasted Lamb 73.42 Raw, composite, trimmed, retail cuts Lard 0.00 Pork 70.00 Raw Rabbit -domestic 72.81 Raw 69.11 Raw, roasted Turkey 74.16 Cooked, roasted Dairy Products Eggs 74.57 Raw Butter 15.87 Raw Cheese American pasteurized. 39.16 Regular Cheddar 36.75 Swiss 37.21 Parmesan, hard 29.16 Parmesan, grated 17.66 Cream, whipping, heavy 57.71 Cottage, lowfat 79.31 Colby 38.20 Blue 42.41 Cream 53.75 Yogurt Plain, lowfat 85.07 Plain, with fat 87.90 Made from whole milk Human milk -estimated from USDA Survey Human *87.50 Whole, mature, fluid Skim 90.80 Lowfat . 90.80 1%

Based on the water content in 100 grams, edible portion. Source: USDA, 1979-1984.

Table 11-29. Summarv of Meat, Poultrv, and Dairv Intake Studies Survey Population Used in Study Calculating Intake Tvoes of Data Used Units Food Items KEV STUDIES EPA Analysis of Per capita 1989-91 CSFll data; gikg-day; as consumed Distributions of intake rates for total 1989-91 CSFll Data Based on. 3-day average meats and total dairy; individual individual intake rates. food items. RELEVANT STUDIES AIHC, 1994 Adults, Per Capita USDA NFCS 1977-78 data g/day Distribution for beef consumption presented in the 1989 version presented in @Risk format. of the Exposure Factors Handbook that were analyzed by Finley and Paustenbach (1992). EPA's ORES Per capita (i.e., consumers 1977-78 NFCS g/kg-day; as consumed Intake for a wide variety of meats, (White et al., 1983) and nonconsumers) 3-day individual intake data poultry, and dairy products presented; complex food groups. were disaggregated -NLMB, 1993 Adult daily mean intake MRCA's Menu Census g/day; as consumed Intake rates for various meats by rates region and gender. Pao et al., 1982 Consumers only serving 1977-78 NFCS g; as consumed Distributions of serving sizes for size data provided 3-day individual intake data meats, poultry, and diary products. USDA, 1980; 1992; Per capita and consumer 1977-78 and 1987-88 NFCS, g/day; as consumed Total meat, poultry and fish, total 1996a; 1996b only grouped by age and and 1994 and 1995 CSFll poultry, total milk, cheese and eggs. sex 1-day individual intake data USDA, 1993 Per capita consumption Based on food supply and g/day; as consumed Intake rates of meats, poultry, and based on "food utilization data which were diary products; intake rates of disappearance" provided by National individual food items. Agricultural Statistics Service (NASS), Customs Service reports, and trade associations. U.S. EPA/ORP, Per capita 1977-78 NFCS g/day; as consumed Mean intake rates for total meats, 1984a; 1984b Individual intake data total diary products, and individual food items. U.S. EPA/OST, Estimated lifetime dietary Based on FDA Total Diet g/day; dry weight Various food groups; complex 1989 intake Study Food List which used *foods disaggregated 1977-78 NFCS data, and NHANES II data Table 11-30. Summary of Recommended Values for Per Capita Intake of Meat and Dairy Products and Serving Size Mean 95th Percentile Multiple Percentiles Study Total Meat Intake 2.1 g/kg-day 5.1 g/kg-day see Table 11-1 EPA Analysis of CSFll 1989-91 Data Total Dairy Intake 8.0 g/kg-day 29.7 g/kg-day see Table 11-2 EPA Analysis of CSFll 1989-91 Data Individual Meat and Dairy: Products see Tables 11-3 to 11-7 see Tables 11-3 to see Tables 11-3 to 11-7 EPA Analysis of CSFll 1989-91 Data 11-7 Table 11-31. Confidence in Meats and Dairy Products Intake Recommendations Considerations Study Elements

Level of peer review
Accessibility
Reproducibility
Focus on factor of interest
Data pertinent to U.S.
Primary data *Currency
Adequacy of data collection period
Validity of approach *Study size
Representativeness of the population
Characterization of variability
Lack of bias in study design (high rating is desirable)
Measurement error Other Elements
Number of studies
Agreement between researchers Overall Rating Rationale USDA CSFll survey receives high level of peer High review. EPA analysis of these data has been peer reviewed outside the Agency. CSFll data are publicly available. High Enough information is included to reproduce High results. Analysis is specifically designed to address food High intake. Data focuses on the U.S. population. High This is new analysis of primary data. High Were the most current data publicly available at High the time the analysis was conducted for this Handbook. Rating Survey is designed to collect short-term data. Medium confidence for average values; Low confidence for long term percentile distribution Survey methodology was adequate. High Study size was very large and therefore High adequate. The population studied was the U.S. population. High Survey was not designed to capture long term Medium day-to-day variability. Short term distributions are provided for various age groups, regions, etc. Response rate was adequate. Medium No measurements. were taken. The study relied N/A on survey data. 1 CSFll was the most recent data set publicly available at the time the analysis was conducted for this Handbook. Therefore, it was the only study classified as key study. Although the CSFll was the only study classified as key study, the results are in good agreement with earlier data. The survey is representative of U.S. population. Although there was only one study considered key, these data are the most recent and are in agreement with earlier data. The approach used to analyze the data was adequate. However, due to the limitations of the survey design, estimation of long-term percentile values (especially the upper percentiles) is uncertain. Low High High confidence in the average; Low confidence in the long-term upper percentiles REFERENCES FOR CHAPTER 11 American Industrial Health Council (AIHC). (1994) Exposure factors sourcebook. Washington, DC., AIHC. CDC. ( 1994) Dietary fat and total food-energy intake. Third National Health and Nutrition Examination Survey, Phase 1, 1988-91. Morbidity and Mortality Weekly Report, February 25, 1994: 43(7)118-125. Finley, B.L.; Paustenbach, B.L. (1992) Opportunities for improving exposure assessments using population distribution estimates. Presented for the Committee on Risk Assessment Methodology, February 10-11, Washington, DC. National Livestock and Meat Board (NLMB). (1993) Eating in America today: A dietary pattern and intake report. National Livestock and Meat Board. Chicago, IL. Pao, E.M.; Fleming, K.H.; Guenther, P.M.; Mickle, S.J. (1982) Foods commonly eaten by individuals: amount per day and per eating occasion. U.S. Department of Agriculture. Home Economics Report No. 44. Pennington, J.A.T. (1983) Revision of the total diet study food list and diets. J. Am. Diet. Assoc. 82:166-173. USDA. (1979-1984) Agricultural Handbook No. 8. United States Department of Agriculture. USDA. (1980) Food and nutrient intakes of individuals in one day in the United States, Spring 1977. U.S. Department of Agriculture. Nationwide Food Consumption Survey 1977-1978. Preliminary Report No. 2. USDA. (1992) Food and nutrient intakes by individuals in the United States, 1 day, 1987-88. U.S. Department of Agriculture, Human Nutrition Information Service. Nationwide Food Consumption Survey 1987-88, NFCS Rpt. No. 87-1-1. USDA. (1993) Food consumption, prices, and expenditures (1970-1992) U.S. Department of Agriculture, Economic Research Service. Statistical Bulletin, No. 867. USDA. ( 1994) Meat ano poultry inspection; 1994 report of the Secretary of Agriculture to the U.S. Congress. Washington, DC: U.S. Department of Agriculture. USDA. (1996a) Data tables: results from USDA's 1994 Continuing Survey of Food Intakes by Individuals and 1994 Diet and Health Knowledge Survey. U.S. Department of Agriculture, Agricultural Research Service, Riverdale, MD.

USDA. (1996b) Data tables: results from USDA's 1995 Continuing Survey of Food Intakes by Individuals and 1995 Diet and Health Knowledge Survey. U.S. Department of Agriculture, Agricultural Research Service, Riverdale, MD. U.S. EPA. (1984a) An estimation of the daily average food intake by age and sex for use in assessing the radionuclide intake of individuals in the general population. EPA-520/1-84-021. U.S. EPA. (1984b) An estimation of the daily food intake based on data from the 1977-1978 USDA Nationwide Food Consumption Survey. Washington, DC: Office of Radiation Programs. EPA-520/1-84-015. U.S. EPA. (1989) Development of risk assessment methodologies for land application and distribution and marketing of municipal sludge. Washington, DC: Office of Science and Technology. EPA 600/-89/001. White, S.B.; Peterson, B.; Clayton, C.A.; Duncan, D.P. (1983) Interim Report Number 1: The construction of a raw agricultural commodity consumption data base. Prepared by Research Triangle Institute for EPA Office of Pesticide Programs. DOWNLOADABLE TABLES FORCHAPTER 11 The following selected tables are available for download as Lotus 1-2-3 worksheets. Table 11-1. Per Capita Intake of Total Meats (g/kg-day as consumed) [WK1, 6 kb] Table 11-2. Per Capita lhtake of Total Dairy Products (g/kg-day as consumed) [WK1, 6 kb] Table 11-3. Per Capita Intake of Beef (g/kg-day as consumed) [WK1, 6 kb] Table 11-4. Per Capita Intake of Pork (g/kg-day as consumed) [WK1, 6 kb] Table 11-5. Per Capita Intake of Poultry (g/kg-day as consumed) [WK1, 6 kb] Table 11-6. Per Capita Intake of Game (g/kg-day as consumed). [WK1, 5 kb] Table 11-7. Per Capita Intake of Eggs (g/kg-day as consumed) [WK1, 6 kb] Table 11-23. Quantity (as consumed) of Meat, Poultry, and Dairy Products Consumed Per Eating Occasion and the Percentage of Individuals Using These Foods in Three Days [WK1, 2 kb] Volume II -Food Ingestion Factors Chapter 12 -Intake of Grain Products 12. INTAKE OF GRAIN PRODUCTS 12.1. INTAKE STUDIES 12.1.1. U.S. Department of Agriculture Nationwide Food Consumption 12.1.2. 12.1.3. 12.1.4. Survey and Continuing Survey of Food Intake by Individuals Key Grain Products Intake Studies Based on the CSFll Relevant Grain Products Intake Studies Key Grain Products Serving Size Study Based on the USDA NFCS 12.2. CONVERSION BETWEEN AS CONSUMED AND DRY WEIGHT INTAKE RATES 12.3. RECOMMENDATIONS REFERENCES FOR CHAPTER 12 APPENDIX 12A Table 12-1. Per Capita Intake of Total Grains Including Mixtures (g/kg-day as consumed) Table 12-2. Per Capita Intake of Breads (g/kg-day as consumed) Table 12-3. Per Capita Intake of Sweets (g/kg-day as consumed) Table 12-4. Per Capita Intake of Snacks Containing Grain (g/kg-day as consumed) Table 12-5. Per Capita Intake of Breakfast Foods (g/kg-day as consumed) Table 12-6. Per Capita Intake of Pasta (g/kg-day as consumed) . Table 12-7. Per Capita Intake of Cooked Cereals (g/kg-day as consumed) Table 12-8. Per Capita Intake of Rice (g/kg-day as consumed) Table 12-9. Per Capita Intake of Ready-to-Eat Cereals (g/kg-day as consumed) Table 12-10. Per Capita Intake of Baby Cereals (g/kg-day as consumed) Table 12-11. Mean Daily Intakes of Grains Per Individual in a Day for USDA 1977-78, 87-88,_ 89-91, 94, and 95 Surveys Table 12-12. Mean Per Capita Intake Rates for Grains Based on All Sex/Age/Demographic Subgroups Table 12-13. Mean Grain Intake Per Individual in a Day by Sex and Age (g/day as consumed) for 1977-1978 . Table 12-14. Mean Grain Intakes Per Individual in a Day by Sex and Age (g/day as consumed) for 1987-1988 Table 12-15. Mean Grain Intakes Per Individual in a Day by Sex and Age (g/day as consumed) for 1994 and 1995

Table 12-16. Mean and Standard Error for the Daily Per Capita Intake of Grains, by Age (g/day as consumed) * . Table 12-17. Mean and Standard Error for the Daily Intake of Grains, by Region (g/day as consumed) Table 12-18. Consumption of Grains (g dry weight/day) for Different Age Groups and Estimated Lifetime Average Daily Food Intakes for a U.S. Citizen (averaged across sex) Calculated from the FDA Diet Data Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors* Chapter 12-Intake of Grain Products Table 12-19. Per Capita Consumption of Flour and Cereal Products in 1991 Table 12-20. Quantity (as consumed) of Grain Products Consumed Per Eating Occasion and the Percentage of Individuals Using These Foods in Three Days Table 12-21. Mean Moisture Content .et Selected Grains Expressed as Percentages of Edible Portions Table 12-22. Summary of Grain Intake Studies
Table 12-23. Summary of Recommended Values for Per Capita Intake of Grain Products Table 12-24. Confidence in Grain Products Intake Recommendation Table 12A-1. Food Codes and Definitions Used in the Analysis of the 1989-91 USDA CSFll Grains Data Exposure Factors Handbook August 1997 /

Volume II -Food Ingestion Factors Chapter 12 Intake of Grain Products 12. INTAKE OF GRAIN PRODUCTS Consumption of grain products is a potential pathway of exposure to toxic chemicals. These food sources can become contaminated by absorption or deposition of ambient air pollutants onto the plants, contact with chemicals dissolved in rainfall or irrigation waters, or absorption of chemicals through plant roots from soil and ground water. The addition of pesticides, soil additives, and fertilizers may also result in contamination of grain products. The U.S. Department of Agriculture's (USDA) Nationwide Food Consumption Survey (NFCS) and Continuing Survey of Food Intakes by Individuals (CSFll) are the primary sources of information on intake rates of grain products in the United States. Data from. the NFCS have been used in various studies to generate consumer-only and per capita intake rates for both individual grain products and total grains. CSFll 1989-91 survey data have been analyzed by EPA to generate per capita intake rates for various food items and food groups. As described in Volume II, Chapter 9 -Intake of Fruits and Vegetables, consumer-only intake is defined as the quantity of grain products consumed by individuals who ate these food items during the survey period. Per capita intake rates are generated by averaging consumer-only intakes over the entire population of users and non-users. In general, per capita intake rates are appropriate for use in exposure assessments for which average dose estimates for the general population are of interest because they represent both individuals who ate the. foods during the survey period and individuals who may eat the food items at some time, but did not consume them during the survey period. This Chapter provides intake data for individual grain products and total grains. Recommendations are based on average and upper-percentile intake among the general population of the U.S. Available data have been classified as being either a key or a relevant study based on the considerations discussed in Volume I, Section 1 .. 3.1 of the Introduction. Recommendations are based on data from the 1989-91 CSFll survey, which was considered the only key intake study for grain products. Other relevant studies are also presented to the reader with added perspective on this topic. It should be noted that most of the key and relevant studies presented in this Chapter are based on data from USQA's NFCS and CSFll. The USDA NFCS. and CSFll are described below. 12.1. 12.1.1. INTAKE STUDIES U.S. Department of Agriculture Nationwide Food Consumption Survey and Continuing Survey of Food Intake by Individuals The NFCS and CSFll are the basis of much of the data on grain intake presented in this section. Data from the 1977-78 NFCS are presented because the data have been Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 12 -Intake of Grain Products published by USDA in various reports and reanalyzed by various EPA offices according to the food items/groups commonly used to assess exposure. Published one-day data from the 1987-88 NFCS and 1994 and 1994 CSFll are also presented. Recently, EPA conducted an analysis of USDA's 1989:.91 CSFll. These data were the most recent food survey data available to the public at the time that EPA analyzed the data for this Handbook. The results of EPA's analyses are presented here. Detailed descriptions of the NFCS and CSFll data are presented in Volume II, Chapter 9 -Intake of Fruits and Vegetables. Individual average daily intake rates calculated from NFCS and CSFll data are based on averages of reported individual intakes over one day or three consecutive days. Such short term data are suitable for estimating average daily intake rates representative of both short-term and long-term consumption. However, the distrib_ution of average daily intake rates generated using short term data (e.g., 3-day) do not necessarily reflect the long-term distribution of average daily intake rates. The distributions generated from short term and long term data will differ to the extent that each individual's intake varies from day to day; the distributions will be similar to the extent that individuals' intakes are constant from day to day. Day-to-day variation in intake among individuals will be great for food item/groups that are highly seasonal and for items/groups that are eaten year around, but that are not typically eaten every day. For these foods, the intake distribution generated from short term data will not be a good reflection of the long term distribution. On the other hand, for broad categories of foods (e.g., total grains) which are eaten on a daily basis throughout the year with minimal seasonality, the short terni distribution may be a reasonable approximation of the true long term distribution, although it will show somewhat more variability. In this Chapter, distributions are shown for the various grain categories. Because of the increased variability of the short-term distribution, the short-term upper percentiles shown will overestimate somewhat the corresponding percentiles of the term distribution. 12.1.2. Key Grain Products Intake Studies Based on the CSFll U.S. EPA Ana_lysis of 1989-91 USDA CSFll Data -EPA conducted an analysis of . USDA's 1989-91 CSFll data set. The general methodology used in analyzing the data is presented in Volume II, Chapter 9 -Intake of Fruits and Vegetables of this Handbook. Intake rates were generated for the following grain products: total grains, breads, sweets, snacks, breakfast foods, pasta, cooked cereals, rice, ready-to-eat cereals, and baby cereals. Appendix 12A provides the food codes and descriptions used in this grain analysis. The data for total grains have been_ corrected to account for mixtures as described in Volume II, Chapter 9 -Intake of Fruits and Vegetables and Appendix 9A using an assumed grain content of 31 percent for grain mixtures and 13 percent for meat Exposure Factors Handbook

August 1997 Volume II -Food Ingestion Factors Chapter 12 -Intake of Grain Products mixtures. Per capita intake rates for total grains are presented in Tables 12-1. Table 12-2 through 12-10 present per capita intake data for individual grain products. The results are presented in units of g/kg-day. Thus, use of these data in calculating potential dose does not require the body weight factor to be inpluded in the denominator of the average daily dose (ADD) equation. It should be noted that converting these intake rates into units of g/day by multiplying by a single average body weight is inappropriate, because individual intake rates were _indexed to the reported body weights of the survey respondents. However, if there is a need to compare the intake data presented here to intake data in units of g/day, a body weight less than 70 kg (i.e., approximately 60 kg; calculated based on the number of respondents in each age category and the average body weights for these age groups, as presented in Volume I, Chapter 7) should be used because the total survey population included children as well as adults.
The advantages of using the 1989-91 CSFll data set are that the data are expected to be representative of the U.S. population and that it includes data on a wide variety of food types. The data set was the most recent of a series of publicly available USDA data sets (i.e., NFCS 1977-78; NFCS 1987-88; CSFll 1989-91) at the time the analysis was . conducted for this Handbook, and should reflect recent eating patterns in the United States. The data set includes three years of intake data However, the 1989-91 CSFll data are based on a three day survey period. Short-term dietary data may not accurately reflect long-term eating patterns. This is particularly true for the tails of the distribution of food intake. In addition, the adjustment for including mixtures adds uncertainty to the intake rate distributions. The calculation for including mixtures assumes that intake of any mixture includes grains in the proportions specified in Appendix 9A-1. This assumption yields valid estimates of per capita consumption, but results in overestimates of the proportion of the population consuming total grains; thus, the quantities reported in Table 12-1 should be interpreted as upper bounds*on the proportion of the population consuming grain products. The data presented in this handbook for the USDA 1989-91 CSFI I is not the most to-date information on food intake. USDA has recently made available the data from its 1994 and 1995 CSFll. Over 5,500 people nationwide participated in both of these surveys providing recalled food intake informatin for 2 separate days. Although the 2-day data analysis has not been conducted, USDA published the results for the respondents' intakes on the first day surveyed (USDA, 1996a; 1996b). USDA 1996 survey data will be made available later in 1997. As soon as 1996 data are available, EPA will take steps to get the 3-year data (1994, 1995, and 1996) analyzed and the food ingestion factors updated. Meanwhile, Table 12-11 presents a comparison of the mean daily intakes per individual in a day for grains from the USDA survey data from years 1977-78, 1987-88, 1989-91, 1994, and 1995. This table shows that food consumption patterns have changed for grains and grain mixtures when comparing 1977 and 1995 data. When comparing data from 1977 and 1995, consumption of grains mixtures and grain increased by 106 percent and Exposure Factors Handbook August 1997

Volume II -Food Ingestion Factors Chapter 12 -Intake of Grain Products . 41 percent, respectively. However, consumption of grains has remained fairly constant when comparing values from 1989-91 with the most recent data from 1994 and 1995. Grain mixtures and grains increase 20 percent and 11 percent, respectively from 1989 to 1995. The 1989-91 CSFI I data are probably adequate for assessing ingestion exposure for current populations, but these data should be used with caution. 12.1.3. Relevant Grain Products Intake Studies The U.S. EPA '.s Dietary Risk Evaluation System (ORES) -USEPA, Office of Pesticide Programs (OPP) -EPA OPP's ORES contains per capita intake rate data for various grain products for 22 subgroups (age, regional, and seasonal) of the population. As described in Volume II, Chapter 9 -Intake of Fruits and Vegetables, intake data in ORES were generated by determining the composition of

1977 /78 NFCS food items and disaggregating complex food dishes into their component raw agricultural commodities (RACs) (White et al., 1983). The ORES per capita, as consumed intake rates for all age/sexidemographic groups combined are presented in Table 12-12. These data are based on both consumers and non-consumers of these food items. Data for specific subgroups of the population are not presented in this section, but are available through OPP via direct request. The data in Table 12-12 may l:!e useful for estimating the risks of exposure associated with the consumption of the various grain products presented. It should be noted that these data are indexed to the reported body weights of the survey . respondents and are expressed in units of grams *of food consumed per kg body weight per day. Consequently, use of these data in calculating potential does not require the body weight factor in the denominator of the average daily dose (ADD) equation. It should also be noted that conversion of these intake rates into units of g/day by multiplying by a single average body weight is not appropriate because the ORES data base did not rely on a single body weight for all individuals. Instead, ORES used the body weights reported by each individual surveyed to estimate consumption in units of g/kg-day. The advantages of using these data are that complex food dishes have been disaggregated to provide intake rates for a variety of grains. These data are also based on the individual body weights of the respondents. Therefore, the use of these data in calculating exposure to toxic chemicals may provide more representative estimates of potential dose per unit body weight. However, because the data are based on NFCS short-term dietary recall, the same limitations discussed previoµsly for other NFCS data sets also apply here. In addition, consumption patterns may have changed since the data were collected in 1977-78. OPP is in the process of translating consumption information from the USDA CSFll 1989-91 survey to be used in ORES. Food and Nutrient Intakes of Individuals in One Day in the U.S., USDA {1980, 1992; 1996a; 1996b) -USDA calculated mean per capita intake rates for total and individual grc;iin products using NFCS data from 1977-78 and 1987-88 (USDA 1980; 1992) and CSFll data Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 12 -Intake of Grain Products from 1994 and 1995 (USDA, 1996a; 1996b ). The mean per capita intake rates for grain products are presented in Tables 12-13 and 12-14 for the two NFCS survey years, respectively. Table 12-15 presents similar data from the 1994 and 1995 CSFll for grain products. The advantages of using these data are that they provide mean intake estimates for various grain products. The consumption estimates are based on short-term (i.e., 1-day) dietary data which may not reflect long-term consumption. U.S. EPA -Office of Radiation Programs-The U.S. EPA Office of Radiation Programs (ORP) has also used the USDA 1977-78 NFCS to estimate daily food intake. ORP uses food consumption data to assess human intake of radionuclides in foods (U.S. EPA, 1984a; 1984b). The 1977-78 NFCS data have been reorganized by ORP, and food items have been classified according to the characteristics of radionuclide transport.* The mean dietary per capita intake of grain products, grouped by age, for the U.S. population are presented in Table 12-16. The mean daily intake rates of grain products for the U.S. population grouped by regions are presented in Table 12-17 .. Because this study was based on the USDA NFCS, the limitations and advantages associated with the NFCS data also apply to this data set. Also, consumption patterns may have changed since the data were collected in 1977-78. U.S. EPA -Office of Science and Technology-The U.S. EPA Office of Science and Technology (OST) within the Office of Water (formerly the Office of Water Regulations and Standards) used data from the FDA revision of the Total Diet Study Food Lists and Diets (Pennington, 1983) to calculate food intake rates. OST uses these consumption data in its risk assessment model for land application of municipal sludge. The FDA data used are based on the combined results of the USDA 1977-78 NFCS and the second National Health and Nutrition Examination Survey (NHANES 11), 1976-80 (U.S. EPA, 1989). Because food items are listed as prepared complex.foods in the FDA Total Diet Study, each
item was broken down into its component parts so that the amount of raw commodities consumed could be determined. Table 12-18 presents intake rates for grain products for various age groups. Estimated lifetime ingestion rates derived by U.S. EPA (1.g89) are also presented in Table 12-18. Note that these are per.capita intake rates tabulated *as grams dry weight/day. Therefore, these rates differ from those in the previous tables because USDA (1980; 1992) and U.S. EPA (1984a, 1984b) report intake rates on an as consumed basis. The EPA-OST analysis provides intake rates for additional food categories and estimates of lifetime average daily intake on a per capita basis. In contrast to the other analyses of USDA NFCS data, this study reports the data in terms of dry weight intake rates. Thus, conversion is not required when contaminants are provided on a dry weight Exposure F,actors Handbook AUf{USt 1997

***-------Volume II -Food Ingestion Factors Chapter 12-Intake of Grain Products basis. These data, however, may not reflect Qurrent consumption patterns because they are based on 1977-78 data.

USDA (1993) -Food Consumption, Prices, and Expenditures, 1970-92-The USDA's
Economic Research Service (ERS) calculates the amount of food available for human consumption in the United States annually. Supply and utilization balance sheets are generated. These are based on the flow of food items from production to end uses. Total available supply is estimated as the sum pf production (i.e., some products are measured at the farm level or during processing), starting inventories, and imports (USDA, 1993). The availability of food for human use commonly termed as "food disappearance" is determined by subtracting exported foods, products used in industries, farm inputs (seed and feed) and end-of-the year inventories from the total available supply (USDA, 1993). USDA (1993) calculates the per capita food consumption by dividing the total food .. disappearance by the total U.S. population.
USDA (1993) estimated per capita consumption data for grain products from 1970-1992 (1992 data are preliminary). In this section, the 1991 values, which are the most recent final data, are presented. Table 12-*19 presents per capita consumption in 1991 for grains. One of the limitations of this study is that disappearance data do not account for losses from the food supply from waste, spoilage, or foods fed to pets. Thus, intake rates based on these data may overestimate daily consumption because they are based on the total quantity of marketable commodity utilized. Therefore, these may be useful for estimating bounding exposure estimates. It should also be noted that per capita estimates based on food disappearance are not a direct measure of actual consumption or quantity ingested, instead the data are used as indicators of changes in usage over time (USDA, 1993). An advantage of this study is that it provides per capita consumption rates for grains which are representative of long-term intake because disappearance data are generated annually. Daily per capita intake rates are generated by dividing annual consumption by 365 days/year. 12.1.4. Key Grain Products Serving Size Study Based on the USDA NFCS Pao et al. {1982) -Foods Commonly Eaten by Individuals -Using data gathered in the 1977-78 USDA NFCS, Pao et al. (1982) calculated percentiles for the quantities of grain products consumed per eating occasion by members of the U.S. population. The data were collected during NFCS home interviews of 37,874 respondents, who were asked to recall food intake for the day preceding the interview, and record food intake the day of the intervi.ew and the day after the interview. Quantities consumed per eating occasion, are presented in Table 12-20. Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 12 -Intake of Grain Products The advantages of using these data are that they were derived from the USDA NFCS and are representative of the U.S. population. This data set provides distributions of serving sizes for a number of commonly eaten grain products, but the list of foods is limited and does not account for grain products included in complex food dishes. Also, these data are based on short-term dietary recall and may not accurately reflect long-term consumption patterns. Although these data are based on the 1977-78 NFCS, serving size data have been collected, but not published, for the more recent USDA surveys . . 12.2. CONVERSION BETWEEN AS CONSUMED AND DRY WEIGHT INTAKE RATES As noted previously, intake rates may be reported in terms of units as consumed or units of dry weight. It is essential that exposure assessors be aware of this difference so that they may ensure consistency between the units used for intake rates and those used for concentration data (i.e., if the unit of food consumption is grams dry weight/day, then the unit for the amount of pollutant in the food should be grams dry weight). If necessary, as consumed intake rates may be converted to dry weight intake rates using the moisture content percentages of grain products presented in Table 12-21 and the following equation: I IRciw = IRac * [(100-W)/100] (Eqn. 12-1) I "Dry weight" intake rates may be converted to "as consumed" rates by using: IRac = IRdw/[(100-W)/100] (Eqn. 12-2) where: IRdw = dry weight intake rate; IRac = as consumed intake rate; and W = percent water content. 12.3. RECOMMENDATIONS The 1989-91 CSFll data described in this section were used in selecting recommended grain, product intake rates for the general population and various subgroups of the United States population. The general design of both key and relevant' studies are summarized in Table 12-22 The recommended values for intake of grain products are summarized in Table 12-23 and the confidence ratings for the recommended values for grain intake rates are presented in Table 12-.24. Per capita intake rates for specific grain items, on a g/kg-day basis, may be obtained from Tables 12-2 through 12-Exposure Factors Handbook August 1997

---Volume II -Food Ingestion Factors Chapter 12 -Intake of Grain Products 10. Percentiles of the intake rate distribution in the general population for total grains, are presented in Table 12-1. From these tables, the mean and 95th percentile intake rates for grains are 4.1 g/kg-day and 10.8 g/kg-day, respectively. It is important to note that the data presented in Tables 12-1 through 12-10 are based on data collected over a 3-day period and may not necessarily reflect the long-term distribution of average daily intake rates. However, for the broad categories offoods (i.e., total grains, breads), because they may be eaten on a daily basfs throughout the year with minimal seasonality, the short-term distribution may be a reasonable approximation of the long-term distribution, although it will display somewhat increased variability. This implies that the upper percentil_es shown will tend to overestimate the corresponding percentiles of the true long-term distribution. It should be noted that because these recommendations are based on 1989-91 CSFll data, they may not reflect the most recent changes in consumption patterns. However, as indicated in Table 12-11, intake has remained fairly constant between 1989-19 and 1995. Thus, the 1989-91 CSFll data are believed to be appropriate for assessing ingestion exposure for current populations. Exposure Factors Handbook August 1997 Table 12-1. Per Capita Intake ofTotal Grains Including Mixtures (g/kg-day as consumed)a Population Group Percent MEAN SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Consuminq Total 97.5% 4.061 0.033 0 0.74 1.16 1.90 3.06 4.96 8.04 10.77 18.53 42.98 Age (years) < 01 80.4% 7.049 0.361 0 0 0 1.46 6.05 10.18 16.75 19.50 27.61 37.41 1-2 95.8% 10.567 0.285 0 2.86 4.34 6.55 9.59 14.06 18.92 21.57 28.22 42.98 3-5 97.5% 9.492 0.201 0 3.13 4.35 6.09 8.91 11.88 15.13 19.14 23.87 33.08 6-11 97.7% 6.422 0.117 0 2.14 2.88 4.07 5.70 7.82 10.26 12.85 21.40 31.93 12-19 98.2% 3.764 0.065 0 1.15 1.52 2.16 3.31 4.81 6.46 8.03 10.92 19.30 20-39 98.4% 3.095 0.035 0 0.70 1.08 1.75 2.73 4.00 5.47 6.55 9.57 25.71 40-69 98.3% 2.792 0.031 0 0.69 0.98 1.59 2.47 3.54 4.96 6.09 8.40 20.34 70 + 98.7% 3.263 0.066 0.38 0.89 1.24 1.86 2.72 4.04 5.81 7.63 10.47 21.45 Season Fall 97.9% 4.282 0.066 0 0.84 1.24 2.07 3.19 5.19 8.54 11.88 19.10 37.77 Spring 97.0% 3.983 0.071 0 0.70 1.10 1.79 2.95 4.73 7.78 10.52 23.87 31.93 Summer 97.5% 3.948 0.062 0 .0.74 1.13 1.82 2.99 4.96 7.98 10.16 15.34 30.13 Winter 97.6% 4.031 0.063 0 0.70 1.17 1.95 3.17 4.99 8.00 10.48 16.86 42.98 Urbanization Central City 97.6% 4.159 0.061 0 0.75 1.13 1.91 3.06 5.07 8.71 11.61 17.69 37.77 Nonmetropolitan 96.9% 4.013 0.067 0 0.60 1.11 1.85 3.12 4.93 7.81 10.08 21.05 31.93 Suburban 97.8% 4.02 0.049 0 0.80 1.18 1.90 3.04 4.91 7.79 10.63 18.53 42.98 Race Asian 94.0% 6.479 0.402 0 0 1.46 3.02 5.44 9.07 14.13 14.63 20.65 23.78 Black 96.9% 4.372 0.103 0 0.55 0.94 1.81 3.05 5.69 9.47 12.47 18.96 40.07. Native American 87.7% 3.98 0.276 0 0 0.61 1.63 3.67 5.81 6.90 9.00 20.43 21.84 Other/NA 97.1% 4.561 0.208 0 0 1.21 2.26 3.56 5.36 8.87 11.72 22.07 30.51 White 97.9% 3.962 0.035 0 0.79 1.18 1.90 3.03 4.80 7.79 10.20 18.07 42.98 Region Midwest 97.3% 4.016 0.07 0 0.79 1.17 1.90 2.92 4.69 7.80 11.04 20.36 31.93 Northeast 97.6% 4.255 0.079 0 0.78 1.26 2.02 3.19 5.37 8.44 11.61 17.73 42.98 South 97.9% 3.943 0.052 0 0.71 1.10 1.83 3.06 4.89 8.13 10.20 16.42 40.07 West 97.2% 4.116 0.072 0 0.69 1.13 1.92 3.13 5.03 7.98 10.90 19.50 25.89 a Includes breads; sweets such as cakes, pie, and pastries; snack and breakfast foods made with grains; pasta; cooked ready-to-eat, and baby cereals, rice and grain mixtures. Note: SE = Standard error P = Percentile of the distribution Source: Based on EPA's analvsis of the 1989-91 CSFll. Table 12-2. Per Capita Intake of Breads (g/kg-day as consumed)a Population Group Percent MEAN SE .P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Consumina Total 91.6% 1.133 0.010 0 0 0.19 0.48 0.90 1.50 2.31 3.04 4.67 12.99 Age (years) < 01 50.9% 1.072 0.102 0 0 0 0 0.34 1.65 3.29 4.06 6.09 12.99 1-2 88.9% 2.611 0.089 .0 0 0.44 1.17 2.39 3.86 4.68 5.42 8.23 10.29 3-5 91.9% 2.217 0.063 0 0 0.44 1.19 2.03 3.04 4.01 5.14 6.95 12.35 6-11 93.4% 1.668 0.037 0 0 0.40 0.88 1.44 2.18 3.16 3.98 5.95 9.17 12-19 91.8% 1.068 0.025 0 0 0.21 0.45 0.91 1.46 2.15 2.78 3.43 7.44 20-39 92.9% 0.936 0.012 0 0 0.18 0.43 0.81 1.27 1.81 2.27 3.41 7.04 40-69 93.7% 0.915 0.011 0 0 0.20 0.46 0.81 1.25 1.77 2.08 2.83 11.16 70 + 95.1% 0.976 0.021 0 0.15 0.29 0.56 0.87 1.31 1.76 2.15 2.76 11.81 Season Fall 91.3% 1.181 0.020 0 0 0.17 0.50 0.94 1.57 2.45 3.16 5.27 11.81 Spring 91.4% 1.095 0.018 0 0 0.18 0.48 0.89 1.45 2.18 2.91 4.54 12.35 Summer 92.4% 1.126 0.018 0 0 0.21 0.48 0.90 1.51 2.24 2.98 4.43 9.17 Winter 91.2% 1.129 0.019 0 0 0.19 0.47 0.89 1.50 2.37 3.07 4.66 12.99 Urbanization Central City 91.2% 1.127 0.017 0 0 0.18 0.49 0.91 1.50 2.33 2.98 4.50 11.81 Non metropolitan 91.7% 1.184 0.020 0 0 0.18 . 0.48 0.93 1.54 2.51 3.24 4.97 12.99 Suburban 91.8% 1.113 0.014 0 0 0.19 0.49 0.89 1.49 2.20 2.89 4.68 12.35 Race Asian 78.5% 0.981 0.078 0 0 0 0.34 0.86 1.51 2.57 2.61 3.34 3.34 Black 88.8% 1.159 0.030 0 0 0.11 0.37 0.84 1.55 2.59 3.29 5.58 8.94 Native American 81.3% 1.336 0.133 0 0 0.13 0.41 0.72 1.80 2.91 4.13 9.09 11.71 Other/NA 89.1% 1.333 0.067 0 0 0 0.62 1.11 1.70 2.66 3.79 6.16 9.98 White 92.5% 1.121 0.010 0 0 0.20 0.51 0.91 1.48 2.23 2.95 4.51 12.99 Region Midwest 91.2% 1.109 0.018 0 0 0.20 0.50 0.90 1.49 2.22 2.91 4.43 7.97 Northeast 91.1% 1.104 0.021 0 0 0.18 0.51 0.90 1.48 2.26 2.83 4.50 9.98 South 91.8% 1.155 0.017 0 0 0.18 0.46 0.92 1.54 2.41 3.13 4.89 12.99 West 92.1% 1.153 0.022 0 0 0.19 0.49 0.91 1.48 2.35 3.12 5.14 12.35 a Includes b.reads, rolls, muffins, bagels, biscuits, cornbread, and tortillas. Note: SE = Standard error P = Percentile of the distribution Source: Based on EPA's analysis of the 1989-91 CSFll. Table 12-3. Per Capita Intake of Sweets (g/kg-day as consumed) a Population Percent MEAN SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Grouo Consumina Total 50.2% 0.508 0.011 0 0 0 0 0.13 0.71 1.50 2.12 3.96 13.39 Age (years) < 01 28.1% 0.447 0.096 0 0 0 0 0 0.41 1.42 2.26 5.51 9.35 1-2 49.6% 1.144 0.111 0 0 0 0 0.43 1.75 3.32 4.87 6.51 13.39 3-5 59.2% 1.139 0.079 0 0 .o 0 0.56 1.82 3.01 4.33 6.78 9.25 6-11 63.7% 0.881 0.046 0 0 0 0 0.43 1.29 2.33 3.28 5.39 12.97 12-19 54.0% 0.511 0.030 0 0 0 0 0.22 0.75 1.47 1.99 3.25 9.65 20-39 45.0% 0.383 0.015 0 0 0 0 0 0.59 1.24 1.66 2.48 7.45 40-69 49.1% 0.381 0.015 0 0 0 0 0.08 0.55 1.13 . 1.58 2.70 5.70 70 + 56.3% 0.444 0.029 0 0 0 0 0.16 0.63 1.29 1.64 2.73 6.94 Season Fall 52.9% 0.533 0.022 0 0 0 0 0.14 0.76 1.55 2.21 3.82 13.39 Spring 48.3% 0.466 0.021 0 0 0 0 0.10 0.65 1.36 1.82 3.58 9.35 Summer 48.5% 0.527 0.025 0 0 0 0 0.06 0.70 2.35 4.54 8.73 Winter 51.2% 0.508 0.022 0 0 *o 0 0.19 0.71 1.50 2.00 4.00 10.84 Urbanization Central City 45.3% 0.495 0.021 0 0 0 0 0.11 0.65 1.55 2.12 4.24 9.94 Nonmetropolitan 52.3% 0.593 0.025 0 0 0 0 0.25 0.82 1.58 2.34 4.52 13.39 Suburban 52.4% 0.477 0.015 0 0 0 0 0.10 0.69 1.42 2.00 3.55 9.65 Race Asian 37.6% 0.515 0.101 0 0 0 0 0.05 0.78 1.82 2.22 2.52 4.06. Black 39.3% 0.387 0.030 0 0 0 0 0 0.46 1.20 1.71 3.51 9.6.7 Native American 33.9% 0.325 0.075 0 0 0 0 0 0.33 1.47 1.48 2.44 3.78 Other/NA 32.3% 0.283 0.088 0 0 0 0 0 0.21 0.64 1.45 3.04 9.94 White 53.2% 0.537 0.012 0 0 0 0 0.17 0.77 1.55 2.17 4.09 13.39 Region Midwest 53.0% 0.573 0.024 0 0 0 0 0.17 0.79 1.65 2.41 4.00 12.97 Northeast 55.9% 0.587 0.027 0 0 0 0 0.22 0.83 1.63 2.21 4.60 13.39 South 47.5% 0.471 0.018 0 0 0 0 0.09 0.65 1.39 1.98 3.89 10.84 .West 46.7% 0.416 0.022 0 0 0 0 0 0.55 1.25 1.91 3.33 9.65 a Includes cakes, cookies, pies, pastries, doughnuts, breakfast bars, and coffee cakes. NOTE: SE= Standard error P = Percentile of the distribution Source: Based on EPA's analvsis of the 1989-91 CSFll. Table 12-4. Per Capita Intake of Snacks Containing Grain (g/kg-day as consumed) a Population Group Percent MEAN SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Consumino Total 40.3% 0.160 0.005 0 0 0 0 0 0.18 0.47 0.78 1.74 6.73 Age (years) < 01 31.4% 0.321 0.064 0 0 0 0 0 0.35 1.24 1.82 4.66 5.73 1-2 46.7% 0.398 0.040 0 0 0 0 0.10 0.65 1.30 1.61 2.03 6.73 3-5 48.9% 0.393 0.034 0 0 0 0 0.12 0.58 1.22 1.65 2.20 4.76 6-11 43.1% 0.269 0.023 0 0 0 0 0 0.32 0.86 1.24 2.43 4.00 12-19 40.2% 0.170 0.016 0 0 0 0 0 0.21 0.50 0.74 1.94 3.51 20-39 38.2% 0.123 0.007 0 0 0 0 *o 0.15 0.41 0.60 1.21 4.60 40-69 40.3% 0.104 0.006 0 0 0 0 0 0.14 0.33 0.46 1.06 2.85 70 + 40.9% 0.074 0.007 0 0 0 0 0 0.10 0.20 0.36 0.70 1.47 Season Fall 41.6% 0.180 0.012 0 0 0 0 0 0.18 0.50 0.87 1.99 6.73 Spring 38.3% 0.136 0.009 0 0 0 0 0 0.15 0.43 0.67 1.29 3.43 Summer 37.5% 0.165 0.010 0 0 0 0 0 0.18 0.52 0.86 1.72 5.73 Winter 43.9% 0.160 0.010 0 0 0 0 0 0.19 0.44 0.76 1.77 4.60 Urbanization Central City 36.5% 0.158 0.010 0 0 0 0 0 0.16 0.46 0.81 1.81 3.70 Nonmetropolitan 39.8% 0.144 0.009 0 0 0 0 0 0.17 0.44 0.66 1.32 4.76 Suburban 43.3% 0.169 0.008 0 0 0 0 0 0.18 0.50 0.80 1.75 6.73 Race Asian 22.1% 0.077 0.035 0 0 0 0 0 0.04 0.27 0.37 1.09 1.34 Black 25.9% 0.107 0.014 0 0 0 0 0 0.07 0.33 0.59 1.19 4.76 Native American 30.4% 0.142 0.050 0 0 0 0 0 0.16 0.32 0.44 1.29 4.60 Other/NA 28.3% 0.139 0.026 0 0 0 0 0 0.17 0.43 0.69 1.27 1.91 White 43.7% 0.170 0.006 0 0 0 0 0 0.19 0.49 0.81 1.80 6.73 Region Midwest 45.2% 0.202 0.012 0 0 0 0 0 0.23 0.57 0.99 1.95 6.73 Northeast 35.8% 0.113 0.010 0 0 0 0 0 0.10 0.35 0.61 1.28 5.73 South 39.8% 0.162 0.008 0 0 0 0 0 0.19 0.46 0.80 1.63 4.76 West 39.4% 0.155 0.011 0 0 0 0 0 0.16 0.46 0.76 1.81 4.60 a Includes grain snacks such as crackers, salty snacks, popcorn, and pretzels. NOTE: SE = Standard error P = Percentile of the distribution Source: Based on EPA's analvsis of the 1989-91 CSFll. ---I Table 12-5. Per Capita Intake of Breakfast Foods (g/kg-day as consumed) a Population Group Percent MEAN SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Consuminr:l Total 15.0% 0.144 0.012 0 0 0 0 0 0 0.46 0.95 2.46 13.61 Age (years) < 01 13.2% 0.255 0.108 0 0 0 0 0 0 0.57 2.08 3.82 5.72 1-2 20.9% 0.418 0.103 0 0 0 0 0 0.37 1.54 2.50 4.62 9.92. 3-5 24.5% 0.446 0.078 0 0 0 0 0 0.56 1.63 2.33 3.92 11.90 6-11 25.0% 0.307 0.045 0 0 0 0 0 0.31 1.12 1.69 2.82 13.61 12-19 18.4% 0.193 0.038 0 0 0 0 0 0 0.65 1.16 3.06 5.38 20"39 13.2% 0.086 0.014 0 0 0 0 0 0 0.31 0.61 1.53 4.41 40-69 10.8% 0.063 0.011 0 0 0 0 0 0 0.23 0.51 0.95 2.98 70 + 12.5% 0.096 0.025 0 0 0 0 0 0 0.41 0.65 1.37 3.09 Season Fall 15.1% 0.146 . 0.021 0 0 0 0 0 0 0.49 0.93 2.61 6.83 Spring 13.2% 0.120 0.023 0 0 0 0 0 0 0.34 0.71 2.32 6.23 Summer 14.8% 0.145 0.022 0 0 0 0 0 0 0.53 0.98 2.02 7.41 Winter 17.0% 0.168 0.027 0 0 0 0 0 0 0.55 1.04 2.94 13.61 Urbanization Central City 15.1% 0.142 0.021 0 0 0 0 0 0 0.42 0.93 2.61 7.17 Nonmetropolitan 13.3% 0.120 0.020 0 0 0 0 0 0 0.39 0.85 1.97 7.41 Suburban 15.9% 0.157 0.019 0 0 0 0 0 0 0.52 1.06 2.45 13.61 Race Asian 10.1% 0.076 0.060 0 0 0 0 0 0 0.24 0.61 1.04 1.46 Black 11.9% 0.114 0.032 0 0 0 0 0 0 0.20 0.78 2.46 7.41 Native American 18.7% 0.156 0.073 0 0 0 0 o. 0.21 0.53 0.61 1.23 6.83 Other/NA 13.7% 0.079 0.037 0 o* 0 0 0 0 0.40 0.43 1.40 2.33 White 15.6% 0.152 0.013 0 0 0 0 0 0 0.51 0.97 2.56 Region Midwest 14.7% 0.121 0.020 0 0 0 0 0 0 0.38 0.75 2.06 7.41 Northeast 15.2% 0.158 0.034 0 0 0 0 0 0 0.43 1.02 2.61 13.61 South 12.3% 0.130 0.019 0 0 0 0 0 0 0.42 0.92 2.33 4.59 West 19.7% 0.184 0.024 0 0 0 0 0 0 0.67 1.14 2.58 6.96 a Includes breakfast foods made with grains such as pancakes, waffles, and frenct:i toast. NOTE: SE = Standard error P = Percentile of the distribution Source: Based on EPA's analysis of the 1989-91. Table 12-6. Per Capita Intake of Pasta (g/kg-day as consumed) Populat'ion Percent MEAN SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Group Consuminq trotal 13.6% 0.233 0.018 0 0 0 0 0 0 0.90 1.60 3.67 24.01 !Age (years) < 01 7.3% 0.172 0.124 0 0 0 0 0 0 0.00 1.18 3.79 6.43 1-2 14.0% 0.569 0.212 0 0 0 0 0 0 1.72 5.14 6.68 24.01 15.3% 0.543 0.142 0 0 0 0 0 0 2.19 3.37 6.51 7.72 15.9% 0.338 0.063 0 0 0 0 0 0 1.47 2.35 3.43 7.72 12-19 14.3% 0.194 0.047 0 0 0 0 0 0 0.77 1.47 3.36 7.24 120-39 15.2% 0.232 0.027 0 0 0 0 0 0 0.96 1.57 2.83 7.17 40-69 12.5% 0.172 0.028 0 0 0 0 0 0 0.62 1.32 2.67 10.20 70+ 9.9% 0.083 0.029 0 0 0 0 0 0 0.03 0.76 1.57 2.62 Season Fall 14.0% 0.239 0.038 0 0 0 0 0 0 0.94 1.72 3.77 24.01 Spring 13.9% 0.250 0.036 0 0 0 0 0 0 0.96 1.65 3.28 9.47 Summer 13.6% 0.251 0.039 0 0 0 0 0 0 0.97 1.72 3.80 11.12 Winter 12.9% 0.193 0.034 0 0 0 0 0 0 0.68 1.33 3.22 8.73 Urbanization Central City 12.9% 0.197 0.034 0 0 0 0 0 0 0.65 1.34 3.43 24.01 Non metropolitan 11.4% 0.171 0.032 0 0 0 0 0 0 0.63 1.33 2.48 11.12 Suburban 15.4% 0.286 0.028 0 0 0 0 0 0 1.12 1.96 3.92 10.20 Race Asian 18.8% 0.918 0.355 0 0 0 0 0 0.70 3.80 5.78 6.51 10.20 Black 6.6% 0.138 0.054 . 0 0 0 0 0 0 0.00 1.08 3.27 5.14 Other/NA 8.6% 0.115 0.083 0 0 0 0 0 0 0.60 1.16 2.43 3.86 White 15.1% 0.243 0.019 0 0 0 0 0 0 0.94 1.65 3.46 24.01 Region Midwest 12.8% 0.182 0.030 0 0 0 0 0 0 0.74 1.24 2.76 9.46 Northeast 21.9% 0.367 0.043 0 0 0 0 0 0 1.47 2.14 4.62 24.01 South 9.2% 0.179 0.035 0 0 0 0 0 0 0.45 1.32 3.63 11.12 West 14.7% 0.252 0.038 0 0 0 0 0 0 1.07 1.63 3.25 10.20 NOTE: SE = Standard error P = Percentile of the distribution Source: Based on EPA's analvsis of the 1989-91 CSFll. Table 12-7. Per Capita Intake of Cooked Cereals (g/kg-day as consumed) Population Percent MEAN SE P1 P5. P10 P25 P50 P75 P90 P95 P99 P100 Grouo Consumina Total 17.1% 0.441 0.035 0 0 0 0 0 0 1.37 2.79 8.18 28.63 Age (years) < 01 17.9% 1.350 0.417 0 0 0 0 0 0 7.17 8.60 20.47 . 24.16 1-2 23.6% 1.783 0.365 0 0 0 0 0 1.39 7.00 9.41 14.84 28.63 3-5 21.2% 1.335 0.258 0 0 0 0 0 0 4.99 8.18 12.51 18.66 6-11 18.1% 0.669 0.142 0 0 0 0 0 0 2.32 4.49 10.76 16.42 12-19 11.0% 0.156 0.065 0 0 0 0 0 0 0 1.26 3.34 11.85 20-39 10.5% 0.166 0.040 0 0 0 0 0 0 0 1.33 3.33 13.18 40-69 18.3% 0.307 0.036 0 0 0 0 0 0 1.30 2.20 3.97 18.23 70 + 35.3% 0.782 0.079 0 0 0 0 0 1.08 2.71 3.80 7.37 10.03 Season Fall 21.2% 0.573 0.066 0 0 0 0 0 0 1.90 3.71 9.15 28.63 Spring 15.8% 0.439 0.082 0 0 0 0 0 0 1.07 2.29 12.28 21.84 Summer 12.1% 0.288 0.069 0 0 0 0 0 0 0.55 1.98 5.37 24.16 Winter 19.1% 0.463 0.062 0 0 0 0 0 0 1.57 3.12 7.00 24.34 Urbanization Central City 19.3% 0.523 0.068 0 0 0 0 0 0 1.52 3.27 10.03 28.63 Nonmetropolitan 20.0% 0.483 0.066 0 0 0 0 0 0 1.52 2.72 7.41 20.94 Suburban 13.9% 0.369 0.052 0 0 0 0 0 0 1.09 2.35 7.37 24.34 Race Black 30.3% 0.838 0.092 0 0 0 0 0 0.65 2.95 4.45 10.03 28.63 Native American 17.5% 0.372 0.196 0 0 0 0 0 0 2.15 2.99 4.80 5.73 Other/NA 12.6% 0.510 0.293 0 0 0 0 0 0 1.12 3.18 7.60 20.94 White 15.1% 0.382 0.039 0 0 0 0 0 0 1.11 2.32 7.38 24.34 Region Midwest 15.5% 0.507 0.083 0 0 0 0 0 0 1.39 3.01 10.32 21.85 Northeast 13.2% 0.395 0.093 0 0 0 0 0 0 1.00 2.73 7.02 24".34 South 21.4% 0.396. 0.044 0 0 0 0 0 0 1.40" 2.48 5.53 28.63 West 15.2% 0.483 0.086 0 0 0 0 0 0 1.45 3.12 9.41 16.47 NOTE: SE = Standard error P = Percentile of the distribution* Source: Based on EPA's analysis of the 1989-91 CSFll. Table 12-8. Per Capita Intake of Rice (g/kg-day as consumed) Population Percent MEAN SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Grouo Consumina Total 20.0% 0:357 0.022 0 0 0 0 0 0 1.26 2.15 4.85 17.59 Age (years) < 01 11.8% 0.405 0.209 0 0 0 0 0 0 1.40 2.89 7.87 15.54 1-2 24.4% 0.811 0.192 0 0 0 0 0 0.36 3.36 4.52 9.81 17.59 3-5 25.0% 0.736 0.127 0 0 -0 0 0 0.76 2.83 3.77 6.70 14.35 6-11 2Q.8% 0.504 0.090 0 0 0 0 0 0 1.71 3.33 7.86 13.39 12-19 20.1% 0.316 0.052 0 0 0 0 0 0 1.26 1.91 3.74 9.60 20-39 21.3% 0.341 0.037 0 0 0 . 0 0 0 1.20 1.90. 5.02 12.69 40-69 19.6% 0.259 0.028 0 0 0 0 0 0 0.94 1.64 3.35 12.00 70 + 14.9% 0.229 0.050 0 0 0 0 0 0 0.81 1.73 3.12 : 7.97 Season Fall 18.8% 0.307 0.041 0 0 0 0 0 0 0.94 2.13 4.92 16.74 Spring 21.5% 0.395 0.046 0 0 0 0 0 0 1.34 2.47 5.05 15.54 Summer 19.3% 0.376 0.045 0 0 0 0 0 0 1.31 2.05 5.02 12.55 Winter 20.5% 0.350 0.041 0 0 0 0 o. 0 1.37 2.09 4.17 17.59 Urbanization Central City 26.1% 0.449 0.039 0 0 0 0 0 0.18 1.51 2.51 5.54 16.74 Nonmetropolitan 15.9% 0.311 0.046 0 0 0 0 0 0 1.04 1.90 5.02 12.91 Suburban 18.3% 0.320 0.031 0 0 0 0 0 0 1.16 2.01 4.30 17.59 Race Asian 72.5% 2.353 0.316 0 0 0 0 1.32 2.83 6.20 10.39 15.06 17.59 Black 37.2% 0.603 0.048 0 0 0 0 0 0.87 2.08 2.93 5.16 12.91 other/NA 37.7% 0.655 0.116 0 0 0 0 0 0.80 2.15 3.78 6.06 10.71 White 15.9% 0.281 0.023 0 0 0 0 0 0 0.94 1.79 4.30 15.54 Region* Midwest 12.3% 0.207 0.046 0 0 0 0 0 0 0.62 1.25 3.59 13.39 Northeast 20.3% 0.378 0.050 0 0 0 0 0 0 1.45 2.15 4.65 16.74 South 25.2% 0.455 0.036 0 0 0 0 0 0 1.62 2.71 5.21 15.54 West 20.4% 0.349 0.045 0 0 0 0 0 0 1.25 1.84 4.52 17.59 NOTE: SE = Standard error P = Percentile of the distribution Source: Based on EPA's analysis of the 1989-91 CSFll. Table 12-9. Per Capita Intake of Ready-to-Eat Cereals (g/kg-day as consumed)* Population Group Percent MEAN SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Consumina Total 45.6% 0.306 0.007 0 0 o. 0 0 0.42 0.92 1.37 2.61 7.12 Age (years) < 01 38.9% 0.431 0.059 0 0 0 0 0 0.64 1.55 1.94 3.40 4.40 1-2 70.7% 0.954 0.057 0 0 0 0 0.74 1.46 2.28 2.89 4.77 6.47 3-5 77.3% 1.026 0.044 0 0 0 0.31 0.83 1.48 2.35 2.99 3.67 5.65 6-11 69.0% 0.631 0.025 0 0 0 0 0.45 0.92 1.55 1.97 3.12 7.12 12-19 50.8%* 0.317 0.019 0 0 0 0 0.16 0.48 0.90 1.14 2.61 4.06 20-39 34.3% 0.174 0.010 0 0 0 0 0 0.23 0.61 0.88 1.51 5.11 40-69 37.1% 0.166 0.008 0 0 0 0 0 0.25 0.55 0.74 1.32 3.36 70+ 52.4% 0.222 0.013 0 0 0 0 0.08 0.36 0.64 0.83 1.55 2.71 Season Fall 45.2% 0.293 0.014 0 0 0 0 0 0.40 0.94 1.42 2.38 7.12 Spring 45.6% 0.320 0.015 0 0 0 0 0 0.44 0.95 1.42 2.69 5.88 Summer 46.6% 0.330 0.016 0 0 0 0 0 0.45 0.99 1.42 2.82. 5.65 Winter 44.8% 0.280 0.014 0 0 0 0 0 0.39 0.81 1.22 2.61 6.47 Urbanization Central City 46.6% 0.319 0.014 0 0 0 0 0 0.43 0.94 1.42 2.86 5.11 Nonmetropolitan 43.6% 0.283 0.014 0 0 0 0 0 0.38 0.85 1.33 2.52 7.12 Suburban 46.0% 0.307 0.011 0 0 0 0 0 . 0.44 0.93 1.36 2.46 6.47 Race Asian 33.6% 0.218 0.065 0 0 0 0 0 0.24 0.81 1.28 2.79 3.12 Black 41.1% 0.269 0.018 0 0 0 0 0 0.40 0.82 1.16 2.50 4.46 Native American 38.6% 0.298 O.D78 0 0 0 0 0 0.32 0.76 1.23 3.26 4.40 Other/NA 42.9% 0.340 0.050 0 0 0 0 0 0.43 1.12 1.59 2.69 4.18 White 46.7% 0.311 0.008 0 0 0 0 0 0.42 0.94 1.39 2.61 7.12 Region Midwest 48.7% 0.328 0.015 0 0 0 0 0 0.47 0.98 1.37 2.55 7.12 Northeast 46.9% 0.286 0.017 0 0 0 0 0 0.38 0.89 1.33 2.70 6.47 South 41.4% . 0.284 0.012 0 0 0 0 0 0.40 0.81 1.26 2.34 5.88 West 47.7% 0.336 0.016 0 0 0 0 0 0.46 1.05 1.47 2.84 5.11 a lncluldes dry ready-to-eat corn, rice, wheat, and bran cereals in the form of flakes, puffs, etc. NOTE: SE = Standard error P = Percentile of the distribution Source: Based on EPA's analvsis of the 1989-91 CSFll. Table 12-10. Per Capita Intake of Baby Cereals (g/kg-day as consumed) Population Group Percent MEAN SE P1 P5 P10

P25 P50 P75 P90 P95 P99 P100 Consumina Total 1.1% 0.037 0.051 0 0 0 0 0 0 0 0 0 22.57 Age (years)" < 01 28.5% 1.205 0.280 0 0 0 0 0 0.64 4.59 6.94 16.99 22.57 Season Fall 1.1% 0.036 0.075 0 0 0 0 0 0 0 0 0.69 14.94 Spring 1.1% 0.059 0.138 0 0 0 0 0 0 0 0 0.13 16.99 Summer 1:0% 0.017 0.068 0 0 0 0 0 0 0 0 0 12.03 Winter 1.0% 0.035 0.107 0 0 0 0 0 0 0 0 0 22.57 Urbanization Central City 1.3% 0.048 0.088 0 0 0 0 0 0 0 0 1.05 22.57 Nonmetropolitan 0.9% 0.011 0.040 0 0 0 0 0 0 0 0 0 9.41 Suburban 1.0% 0.042 0.093 0 0 0 0 0 0 0 0 0 16.99 Race Asian 0.7% 0.017 0.137 0 0 0 0 0 0 0 0 1.10 1.10 Black 2.1% 0.092 0.151 0 0 0 0 0 0 0 0 4.59 22.57 Native American 1.2% 0.010 0.088 0 0 0 0 0 0 0 0 0 1.63 Other/NA 3.1% 0.050 0.133 0 0 0 0 0 0 0 0 2.94 13.42 White 0.8% 0.029 0.059 0 0 0 0 0 0 0 0 0 16.99 Region Midwest 1.1% 0.020 0.050 0 0 0 0 0 0 0 0 0 12.50 Northeast 1.0% 0.084 0.208 0 0 0 0 0 0 0 0 1.25 16.99 South 1.0% 0.016 0.060 0 0 0 0 0 0 0 0 0 22.57 West 1.1% 0.046 0.101 0 0 0 0 0 0 0 0 1.18 10.18
Data presented only for children less than 1 year of age. Available data for other age groups was based on a very small number of observations NOTE: SE = Standard error P = Percentile of the distribution Source: Based on EPA's analvsis of the 1989-91 CSFll.

Food Product Grains Grains Mixtures Table 12-11. Mean Daily Intakes of Grains Per Individual in a Day for USDA 1977-78, 87-88, 89-91, 94, and 9.5 Surveys 77-78 Data 87-88 Data 89-91 Data 94 Data (g/day) (g/day) (g/day) (g/day) 215 237 273 300 52 72 89 112 Source: USDA, 1980; 1992; 1996a; 1996b. 95 Data (g/day) 303 107 Table 12-12. Mean Per Capita Intake Rates for Grains Based on All Sex/Age/Demographic Subgroups Average Consumption Raw Aaricultural Commoditv" <Grams/kc Bodv Weioht-Davl Standard Error Oats 0.0825748 0.0026061 Rice-rough 0.0030600 0.0004343 Rice-milled 0.1552627 0.0083546 Rye-rough 0.0000010 --Rye-germ 0.0002735 0.0000483 Rye-flour 0.0040285 0.0002922 Wheat-rough 0.1406118 0.0050410 Wheat-germ 0.0008051 0.0000789 Wheat-bran 0.0004864 Wheat-flour 1.2572489 0.0127412 Millet 0.0000216 0.0000104

Consumed in any raw or prepared form. Source: ORES data base (based on 1977-78 NFCS).

Table 12-13. Mean Grain Intake Per Individual in a Dav by Sex and Age (g/day as consumed)* for 1977-1978 Breads, Rolls, other Baked Mixtures, Group Age (years) Total Grains Biscuits Goods Cereals, Pasta Mainly Grain" Males and Females Under 1 42 4 5 30 3 1-2 158 27 24 44 63 3-5 181 46 37 54 45 6-8 206 53 56 60 38 Males 9-11 238 67 56 51 64 12-14 288 76 80 57 74 15-18 303 91 77 53 82 19-22 253 84 53 64 52 23-34 256 82 60 40 74 35-50 234 82 58 44 50 51-64 229 78 57 48 46 65-74 235 71 60 69 35 75 and Over 196 70 50 58 19 Females 9-11 214 58 59 44 53 12-14 235 57 61 45 72 15-18 196 57 43 41 55 19-22 161 44 36 33 48 23-34 163 49 38 32 44 35-50 161 49 37 32 43 51-64 155 52 40 36 27 65-74 175 57 42 47 29 75 and Over 178 54 44 58 22 Males and Females All Ages 204 62 49 44 49

Based on USDA Nationwide Food Consumption Survey 1977-78 data for one day. " Includes mixtures containing grain as the main ingredient. Source: USDA 1980.

Table 12-14. Mean Grain Intakes Per Individual in a Day by Sex and Age (g/day as consumed)* for 1987-1988 Quick Breads, Cakes, Crackers, Yeast Pancakes, Cookies, Popcorn, Mixtures Group Total Breads French Pastries, Pretzels, Cereals , Mostly Aqe (years) Grains* and Rolls Toast Pies Com Chips and Pastas Grainb Males and Females 5 and Under 167 30 8 22 4 52 51 Males 74 83 6-11 268 51 16 37 8 72 82 12-19 304 65 28 45 10. 58 83 20 and Over 272 65 20 37 8 Females 6-11 231 43 19 30 6 66 68 12-19 239 45 13 29 *7 52 91 20 and Over 208 45 14 28 6 53 62 All Individuals 237 52 16 32 7 57 72 a Based on USDA Nationwide Food Consumption Survey 1987-88. data for one day. b Includes mixtures containing grain as the main ingredient. Source: USDA, 1992. Table 12-15. Mean Grain Intakes Per Individual in a Dav bv Sex and Aae (a/day as consumed)' for 1994 and 1995 Crackers, Quick Breads, Cakes, Cookies, Popcorn, Group Yeast Breads Pancakes, Pastries, Pies Pretzels, Corn Cereals and Mixtures, Mostly Aae lvearsl Total Grains and Rolls French Toast Chios Pastas Grainb 1994 1995 1994 1995 1994 1995 1994 1995 1994 1995 1994 1995 1994 1995 Males and Females 5 and Under 213 210 26 28 11 11 22 23 8 7 58 57 89 84 Males 6-11 285 341 51 45 15 21 42 46 12 18 66 97 101 115 12-19 417 364 53 54 30 21 54 43 17 22 82 84 180 138 20 and Over 357 365 64 61 22 24 43 46 13 15 86 91 128 128 Females 6-11 260 286 43 46 16 21 37 51 11 14 57 54 94 100 12-19 317 296 40 37 16 14 39 35 17 16 63 52 142 143 20 and Over 254 257 44 45 16 15 33 34 9 10 59 69 92 83 All Individuals 300 303 50 49 18 19 38 39 12 13 70 76 112 107 . Based on USDA CSFll 1994 and 1995 data for one day . b Includes mixtures containing grain as the main ingredient. Source: USDA, 1996a; 1996b.

Table 12-16. Mean and Standard Error for the Daily Per Capita Intake of Grains, bv Age I g/dav as consumed) Age (years) Breads Cereals Other Grains All ages 147.3.+/-.1.4 29.9.+/-.1.3 22.9.+/-.1.7 Under1 16.2.+/-.9.2 37.9.+/-.8.2 1.8.+/-.10.9 1to4 104.6.+/-.4.5 38.4.+/-.4.0 14.8.+/-.5.4 5 to 9 154.3.+/-.3.8 39.5.+/-.3.4 22.7.+/-.4.5 10 to 14 186.2.+/-.3.6 36.4.+/-.3.2 25.6.+/-.4.2 15 to 19 188.5.+/-.3.7 28.8.+/-.3.3 27.8.+/-.4.4 20 to 24 166.5.+/-.4.9 20.2.+/-.4.3 25.0.+/-.5.8 25 to 29 170.0.+/-.5.0 18.2.+/-.4.4 26.6.+/-.5.9 30 to 39 156.8.+/-.3.9 18.8.+/-.3.5 26.4.+/-.4.6 40 to 59 144.4.+/-.3.1 24.7.+/-.2.7 23.3.+/-.3.6 60 and over 122.1.+/-.3.4 42.5.+/-.3.0 19.3.+/-.4.0 Source: U.S. EPA, 1984a (based on 1977-78 NFCS).

Table 12-17. Mean and Standard Error for the Daily Intake of Grains, by Reaion (a/day as consumed) Region Total Grains Breads Cereals Other Grains All Regions 200.0+/-3.0 147.3+/-1.4 29.9+/-1.3 22.9+/-1.7 Northeast 203.5+/-5.8 153.1+/-2.8 24.6+/-2.5 25.9;!:3.3 North Central 192.8;!:5.6 150.9+/-2.7 28.7+/-2.4 13.3+/-3.2 South 202.2+/-4.7 143.9+/-2.3 34.6+/-2.0 23.7+/-2.7 West 202.6+/-6.9 139.5;!:3.3 30.9+/-3.0 32.1+/-4.0 NOTE: Northeast= Maine, New Hampshire, Vermont, Massachusetts, Connecticut, Rhode Island, New York, New Jersey, and Pennsylvania.

North Central =Ohio, Illinois, Indiana, Wisconsin, Michigan, Minnesota, Iowa, Missouri, North Dakota, South Dakota, Nebraska, and Kansas. South = Maryland, Delaware, District of Columbia, Virginia, West Virginia, North Carolina, South Carolina, Georgia, Florida, Kentucky, Tennessee, Alabama, Mississippi, Arkansas, Louisiana, Texas, and Oklahoma. West= Montana, Idaho, Wyoming, Utah, Colorado, New Mexico, Arizona, Nevada, Washington, Oregon, and California. Source: U.S. EPA, 1984b (based on 1977-78 NFCS).

Wheat Corn Rice Oats Other Grain Total Grain Table 12-18. Consumption of Grains (g dry weight/day) for Different Age Groups and Estimated Lifetime Average Daily Food Intakes for a U.S. Citizen (averaged across sex) Calculated from the FDA Diet Data Age (years) (0-1) (1-5) (6-13) (14-19) (20-44) (45-70) 27.60 42.23 60.80 79.36 65.86 55.13 4.00 15.35 19.28 23.21 12.83 14.82 2.22 4.58 5.24 5.89 5.78 4.21 3.73 2.65 2.27 1.89 1.32 2.00 0.01 0.08 0.41 0.73 13.45 4.41 37.56 64.82 87.58 110.34 90.59 76.12 *The estimated lifetime dietary intakes were estimated by: Estimated21ifetime 60.30 12.01 5.03 1.85 6.49 84.19 Estimated lifetime= IR(0-1) + 5yrs *JR (1-5) + 8 yrs* IR (6-13) + 6 yrs* JR (14-19) + 25 yrs* IR (20-44) + 25 yrs* JR (45-70) 70 years where JR =the intake rate for a specific age group. Source: U.S. EPA, 1989 {based on 1977-78 NFCS and NHANES II data). Table 12-19. Per Capita Consumption of Flour and Cereal Products in 1991" Per Capita Consumption Food Item (a/dav)* Total Wheat Flour" 169.8 Rye Flour 0.7 Ricec 20.9 Total Corn Productsd 27.2 Oat Products* 10.7 Barley Products' 1.1 Total Flour and Cereal Products0 230.6 a Original data were presented in lbs/yr; data were converted to g/day by multiplying by a factor of 454 g/lb and dividing by 365 days/yr. Consumption of most items at the processing level. Excludes quantities used in alcoholic beverages and fuel. b Includes white, whole wheat, and durum flour. ' Milled basis. d Includes com flour and meal, hominy and grits, and corn starch. a Includes rolled oats, ready-to-eat cereals, oat flour, and oat bran. f Includes barley flour, pearl barley, and malt and malt extract used in food processing. g Excludes wheat not ground into flour, for example, shredded wheat breakfast cereals. Source: USDA, 1993. Table 12-20 .. Quantity (as consumed) of Grain Products Consumed Per Eating Occasion and the Percentaqe of Individuals Using These Foods in Three Days % lndiv. Quantity consumed .using per eating occasion Consumers-only Food category food in 3 (g) Quantity consumed per eatinq occasion at specified percentiles (q) days Average Standard 5 25 50 75 90 95 99 Deviation Yeast Breads 93.7 46 26 21 25 44 50 75 100 140 Pancakes 8.3 113 85 27 54 81 146 219 282 438 Waffles 2.9 87 74 20 40 78 100 158 200 400 Tortillas 2.9 69 39 28 30 60 90 120 140 210 Cakes and Cupcakes 25.5 79 59 23 41 63 99 144 184 284 Cookies 30.8 32 30 7 14 26 40 60 84 144 Pies 11.9 129 60 57 97 120 150 195 236 360 Doughnuts 9.9 64 40 26 42 43 84 106 126 208 Crackers 26.2 22 21 6 12 15 24 42 57 113 Popcorn 5.6 19 22 5 9 15 18 36 45 108 Pretzels 2.2 29 28 3 12 21 36 57 85 160 Corn-based Salty Snacks 5.9 33 30 9 18 21 40 60 80 156 Pasta 11.4 153 108 35 70 140 210 280 320 560 Rice 18.5 147 91 41 88 165 125 263 350 438 Cooked Cereals 12.4 203 110 31 143 240 245 360 480 490 Readv-to-Eat Cereals 43.4 36 25 8 22 29 45 60 84 120 Source: Pao et al. 1982 (based on 1977-78 NFCS\. Table 12-21. Mean Moisture Content of Selected Grains Expressed as Percentages of Edible Portions Moisture Content (Percent) Food Raw Cooked Comments Barley -pearled 10.09 68.80 Corn -grain -endosperm 10.37 Corn -grain -bran 3.71 crude Millet 8.67 71.41 Oats 8.22 Rice -rough -white 11.62 68.72 Rye -rough 10.95 Rye -flour-'medium 9.85 Sorghum (including milo) 9.20 Wheat -rough -hard white 9.57 Wheat-germ 11.12 crude Wheat-bran 9.89 crude Wheat -flour -whole grain 10.27 Source: USDA, 1979-1986. Table 12-22. Summary of Grain Intake Studies Survey Population Used in Study Calculatin!l Intake Types of Data Used Units Food Items KEY STUDIES EPA Analysis of 1989-91 Per capita 1989-91 CSFll data; g/kg-day; as Distributions of intake rates for total CSFll Data Based on 3-day average consumed grain; individual grain items individual intake rates. RELEVANT STUDIES EPA's ORES Per capita (i.e., consumers 1977-78 NFCS g/kg-day; as Intake for a wide variety of grain (White et al., 1983) and nonconsumers) 3-day individual intake data consumed products presented; complex food groups were disaggregated Pao et al., 1982 Consumers only serving size 1977-78 NFCS g; as consumed Distributions of serving sizes for grain data provided 3-day individual intake data products USDA, 1980; 1992; Per capita and consumer 1977-78 and 1987-88 NFCS, g/day; as consumed Total grains and various grain 1996a; 1996b only grouped by age and sex and 1994 and 1995 CSFll products 1-day individual intake data USDA, 1993b Per capita consumption Based on food supply and g/day; as consumed Intake rates of grain products based on "food utilization data disappearance" U.S. EPA/ORP, Per capita 1977-78 NFCS g/day; as consumed Mean intake rates for total grain 1984a; 1984b Individual intake data products, and individual grain items. U.S. EPA/OST, 1989

Estimated lifetime dietary Based on FDA Total Diet Study g/day; dry weight Various food groups; complex foods intake Food List which used 1977-78 disaggregated NFCS data, and NHANES II data Table 12-23. Summary of Recommended Values for Per Capita Intake of Grain Products Mean 95th Percentile Multiple Percentiles Study Total Grain Intake 4.1 g/kg-day 10.8 g/kg-day see Table 12-1 EPA Analysis of CSFll 1989-91 Data Individual Grain Products see Tables 12-2 to 12-10 see Tables 12-2 to 12-10 see Table 12-2 to 12-10 EPA Analvsis of CSFll 1989-91 Data /

Considerations Study Elements

Level of peer review . Accessibility . Reproducibility . Focus on factor of interest . Data pertinent to U.S. Primary data . Currency
Adequacy of data collection period Validity of approach
Study size
Representativeness of the population
Characterization of variability
Lack of bias in study design (high rating is desirable)
Measurement error Other Elements
Number of studies
Agreement between researchers Overall Rating Table 12-24. Confidence in Grain Products Intake Recommendation Rationale USDA CSFll survey receives high level of peer review. EPA analysis of these data has been peer reviewed outside the Agency. High CSFll data are publicly available. High Enough information is included to reproduce results. High Analysis is specifically designed to address food High intake. Data focuses on the U.S. population. High This is new analysis of primary data. High Were the most current data publicly available at the High time the analysis was conducted for this Handbook. Rating Survey is designed to collect short-term data. Medium confidence for average values; Low confidence for long term percentile distribution Survey methodology was adequate. High Study size was very large and therefore adequate. High The population studied was the U,S. population. High Survey was not designed to capture long term day-to-Medium day variability. Short term distrib.utions are provided for various age groups, regions, etc. Response rate was adequate. Medium No measurements were taken. The study relied on N/A survey data. 1 CSFll was the most recent data set publicly available at the time the analysis was conducted for this Handbook. Therefore, it was the only study classified as key study. Although the CSFll was the only study classified as key study, the results are in good agreement with earlier data. The survey is representative of U.S. population. Although there was only one study considered key, these data are the most recent and are in agreement with earlier data. The approach used to analyze the data was adequate. However, due to the limitations of the survey design estimation of long-term percentile values (especially the upper percentiles) is uncertain. Low High High confidence in the average; Low confidence in the long-term upper percentiles Table 12A-1. Food Codes and Definitions Used in the Analysis of the 1989-91 USDA CSFll Grains Data Food Product Food Codes and Descriptions Food Product Food Codes and Descriptions Total Grains 51-breads Pasta 561-macaroni 52-tortillas noodles 53-sweets spaghetti 54-snacks 55-breakfast foods 561-pasta 562-cooked cereals and rice 57-ready-to-eat and baby cereals Also includes the average portion of grain mixtures (i.e., 31 percent) and the average portion of meat mixtures (i.e., 13 percent) made up by grain. Breads 51-breads Cooked 56200-includes grits,oatmeal, rolls Cereals 56201-cornmeal mush, millet, muffins 56202-etc. bagel 56203-biscuits 562069-corn bread 56207-52-tortillas 56208-56209-Sweets 53-cakes Rice 56204-includes all varieties of cookies 56205-rice pies 5620601 pastries doughnuts breakfast bars coffee cakes Snas:;ks 54-crackers Ready-to-eat 570-includes all varieties of salty snacks Cereals 571-ready-to-eat cereals popcorn 572-pretzels 573-574-575-576-Breakfast 55-pancakes Baby Cereals 578-baby cereals Foods waffles trench toast Grain Mixtures .58-grain mixtures Meat Mixtures 27-meat mixtures 28---------

REFERENCESFORCHAPTER12 Pao, E.M.; Fleming, K.H.; Guenther, P.M.; Mickle, S.J. (1982) Foods commonly eaten by individuals: amount per day and per eating occasion. U.S. Department of Agriculture. Home Economics Report No. 44. Pennington, J.A.T. (1983) Revision of the total diet study food list and diets. J. Am. Diet. Assoc. 82:166-173. USDA. (1980) Food and* nutrient intakes of individuals in one day in the United States, Spring 1977. U.S. Department of Agriculture. Nationwide Food Consumption Survey 1977-1978. Preliminary Report No. 2. USDA. (1992) Food and nl!trient intakes by individuals in the United States, 1 day, 1987-88. U.S. Department of Agriculture, Human Nutrition Information Service. Nationwide Food Consumption Survey 1987-88, NFCS Rpt. No. 87-1-1. USDA. (1993) Food consumption prices and expenditures (1970-1992) U.S. Department of Agriculture, Economic Research Service. Statistical Bulletin, No. 867. USDA. (1996a) Data tables: results from USDA's 1994 Continuing Survey of Food Intakes by Individuals and 1994 Diet and Health Knowledge Survey. U.S. Department of Agriculture, Agricultural Research Service, Riverdale, MD. USDA. ( 1996b) Data tables: results from USDA's 1995 Continuing Survey of Fo.od Intakes by Individuals and 1995 Diet and Health Knowledge Survey. U.S. Department of Agriculture, Agricultural Research Service, Riverdale, MD. U.S. EPA. ( 1984a) An estimation of the daily average food intake by age and sex for use in assessing the radionudide intake of individuals in the general population. EPA-520/1-84-021. U.S. EPA. (1984b) An estimation of the daily food intake based on data from the 1977-1978 USDA Nationwide Food Consumption Survey. Washington, DC: Office of Radiation Programs. EPA-520/1-84-015. U.S. EPA. (1989) Development of risk assessment methodologies for land application and distribution and marketing of municipal sludge. Washington, DC: Office of Science and Technology. EPA 600/-89/001. White, S.B.; B.; Clayton, C.A.; Duncan, D.P. (1983) Interim Report Number 1: The construction of a raw agricultural commodity consumption data base. Prepared by Research Triangle Institute for EPA Office of Pesticide Programs. DOWNLOADABLE TABLES FOR CHAPTER 12 The following selected tables are available for download as Lotus 1-2-3 worksheets. Table 12-1. Per Capita Intake of Total Grains Including Mixtures (g/kg-day as consumed) [WK1, 6 kb] Table 12-2. Per Capita Intake of Breads (g/kg-day as consumed) [WK1, 6 kb] Table 12-3. Per Capita Intake of Sweets (g/kg-day as consumed) [WK1, 6 kb] Table 12-4. Per Capita Intake of Snacks Containing Grain (g/kg-day as consumed) [WK1, 6 kb] Table 12-5. Per Capita Intake of Breakfast Foods (g/kg-day as consumed) [WK1, 6 kb] Table 12-6. Per Capita Intake of Pasta (g/kg-day as consumed) [WK1, 5 kb] Table 12-7. Per Capita Intake of Cooked Cereals (g/kg-day as consumed) [WK1, 5 kb] Table.12-8. Per Capita Intake of Rice (g/kg-day as consumed) [WK1, 5 kb] Table 12-9. Per*Capita Intake of Ready-to-Eat Cereals (g/kg-day as consumed) [WK1, 6 kb] Table 12-10. Per Capita Intake of Baby Cereals (g/kg-day as consumed) [WK1, 4 kb] Table 12-20. Quantity (as consumed) of Grain Products Consumed Per Eating Occasion and the Percentage of Individuals Using These Foods in Three Days [WK1, 3 kb] Volume II -Food Ingestion Factors Chapter 13 -Intake Rates for Various Home Produced Food Items 13. INTAKE RATES FOR VARIOUS HOME PRODUCED FOOD ITEMS 13.1. BACKGROUND 13.2. METHODS 13.3. RESULTS 13.4. ADVANTAGES AND LIMITATIONS. 13.5. RECOMMENDATIONS REFERENCES FOR CHAPTER 13 APPENDIX 13A Table 13-1. 1986 Vegetable Gardening by Demographic Factors Table 13-2. Percentage of Gardening Households Growing Different Vegetables in 1986 Table 13-3. Sub-category Codes and Definitions Table 13-4. Weighted and Unweighted Number of Observations (Individuals) for NFCS Data Used in Analysis of Food Intake . Table 13-5. Percent Weight Losses from Preparation of Various Meats Table 13-6. Percent Weight Losses from Preparation of Various Fruits Table 13-7. Percent Weight Losses from Preparation of Various Vegetables Table 13-8. Consumer Only Intake of Homegrown Fruits (g/kg-day) -All Regions Combined Table 13-9. Consumer Only Intake of Homegrown Fruits (g/kg-day) -Northeast Table 13-10. Consumer Only Intake of Homegrown Fruits (g/kg-day)-Midwest Table 13-11. Consumer Only Intake of Homegrown Fruits (g/kg:-day) -South Table 13-12. Consumer Only Intake of Homegrown Fruits (g/kg-day)-West Table 13-13. Consumer Only Intake of Homegrown Vegetables (g/kg-day)-All Regions Combined Table 13-14. Consumer Only Intake of Homegrown Vegetables (g/kg-day) -Northeast

Table 13-15; Consumer Only Intake of Homegrown Vegetables (g/kg-day)-Midwest Table 13-16. Consumer Only Intake of Homegrown Vegetables (g/kg-day)-South Table 13-17. Consumer Only Intake of Homegrown Vegetables (g/kg-day) -West Table 13-18. Consumer Only Intake of Home Produced Meats (g/kg-day) -All Regions Combined Table 13-19. Consumer Only Intake of Home Produced Meats (g/kg-day)-Northeast Table 13-20. Consumer Only Intake of Home Produced Meats (g/kg-day),.. Midwest Table 13-21. Consumer Only Intake of Home Produced Meats (g/kg-day) -South Table 13-22. Consumer Only Intake of Home Produced Meats (g/kg-day) -West Table 13-23. Consumer Only Intake of Home Caught Fish (g/kg-day) -All Regions Combined Table 13-24. Consumer Only Intake of Home Caught Fish (g/kg-day) -Northeast Table 13-25. Consumer Only Intake of Home Caught Fish (g/kg-day) -Midwest Table 13-26. Consumer Only Intake of Home Caught Fish (g/kg-day) -South Table 13-27. Consumer Only Intake of Home Caught* Fish (g/kg-day) -West Table 13-28. Consumer Only Intake of Home Produced Dairy (g/kg-day) -All Regions Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 13 -Intake Rates for Various Home Produced Food Items Table 13-29. Consumer Only Intake of Home Produced Dairy (g/kg-day) -Northeast Table 13-30. Consumer Only Intake of Home Produced Dairy (g/kg-day) -Midwest Table 13-31. Consumer Only Intake-of Home Produced Dairy (g/kg-day)-South Table 13-32. Consumer Only Intake of Home Produced Dairy (g/kg-day) -West Table 13-33. Seasonally Adjusted Consumer Only Homegrown Intake (g/kg-day) Table 13-34. Consumer Only Intake of Homegrown Apples (g/kg-day) Table 13-35. Consumer Only Intake of Homegrown Asparagus (g/kg-day) Table 13-36. Consumer Only Intake of Home Produced Beef (g/kg-day) Table 13-37. Consumer Only Intake of Homegrown Beets (g/kg-day) Table 13-38. Consumer Only Intake of Homegrown Broccoli (g/kg-day) Table 13-39. Consumer Only Intake of Homegrown Cabbage (g/kg-day) Table 13-40. Consumer Only Intake of Homegrown Carrots (g/kg-day) Table 13-41 . Consumer Only Intake of Homegrown Corn (g/kg-day) Table 13-42. Consumer Only Intake of Homegrown Cucumbers (g/kg-day) Table 13-43. Consumer Only Intake of Home Produced Eggs (g/kg-day) Table 13-44. Consumer Only Intake of Home Produced Game (g/kg-day) Table 13-45. Consumer Only Intake of Home Produced Lettuce (g/kg-day) Table 13-46. Consumer Only Intake of Home Produced Lima Beans (g/kg-day) Table 13-47. Consumer Only Intake of Homegrown Okra (g/kg-day) Table 13-48. Consumer Only Intake of Homegrown Onions (g/kg-day) Table 13-49. Consumer Only Intake of Homegrown Other Berries (g/kg-day) Table 13-50. Consumer Only Intake of Homegrown Peaches (g/kg-day) Table 13-51. Consumer Only Intake of Homegrown Pears (g/kg-day) Table 13-52. Consumer Only Intake of Homegrown Peas (g/kg-day) Table 13-53. Consumer Only Intake of Homegrown Peppers (g/kg-day) Table 13-54. Consumer Only Intake of Home Produced Pork (g/kg-day) Table 13-55. Consumer Only Intake of Home Produced Poultry (g/kg-day) Table 13-56. Consumer Only Intake of Homegrown Pumpkins (g/kg-day) Table 13-57. Consumer Only Intake of Homegrown Snap Beans (g/kg-day) . Table 13-58. Consumer Only Intake of Homegrown Strawberries (g/kg-day) Table 13-59. Consumer Only Intake of Homegrown Tomatoes (g/kg-day) Table 13-60. Consumer Only Intake of Homegrown White Potatoes (g/kg-day) Table 13-61. Consumer Only Intake of Homegrown Exposed Fruit (g/kg-day) Table 13-62. Consumer Only Intake of Homegrown Protected Fruits (g/kg-day) Table 13-63. Consumer Only Intake of Homegrown Exposed Vegetables (g/kg-day) Table 13-64. Consumer Only Intake of Homegrown Protected Vegetables (g/kg-day) Table 13-65. Consumer Only Intake of Homegrown Root Vegetables (g/kg-day) Table 13-66. Consumer Only Intake of Homegrown Dark Green Vegetables (g/kg-day) Table 13-67. Consumer Only Intake of Homegrown Deep Yellow Vegetables (g/kg-day) Table 13-68. Consumer Only Intake of Homegrown Other Vegetables (g/kg-day) Table 13-69. Consumer Only Intake of Homegrown Citrus (g/kg-day) Table 13-70. Consumer Only Intake of Homegrown Other Fruit (g/kg-day) Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 13 -Intake Rates for Various Home Produced Food Items Table 13-71. Fraction of Food Intake that is Home Produced Table 13-72. Confidence in Homegrown Food Consumption Recommendations Table 13A-1. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data Exposure Factors Handbook August 1997 I _I Volume II -Food Ingestion Factors Chapter 13 -Intake Rates for Various Home Produced Food Items 13. INTAKE RATES FOR VARIOUS HOME PRODUCED FOOD ITEMS 13.1. BACKGROUND Ingestion of contaminated foods is a potential pathway of exposure to toxic chemicals. Consumers of home produced food products may be of particular concern because exposure resulting from local site contamination may be higher for this subpopulation. According to a survey by the National Gardening Association (1987), a total of 34 million (or 38 percent) U.S. households participated in vegetable gardening in 1986. Table 13-1 contains demographic data on vegetable gardening in 1986 by region/section, community size, and household size. Table 13-2 contains information on the types of vegetables grown by home gardeners in 1986. Tomatoes, peppers, onions, cucumbers, lettuce, beans, carrots, and corn are among the vegetables grown by the largest percentage of gardeners. Home produced foods can become contaminated in a variety of ways. Ambient pollutants in the air may be deposited on plants, adsorbed onto or absorbed by the plants, or dissolved in rainfall or irrigation waters that contact the plants. Pollutants may also be adsorbed onto plants roots from contaminated soil arid water. Finally, the addition of pesticides, soil additives, and fertilizers to crops or gardens may result in contamination of food products. Meat and dairy products can become contaminated if animals consume contaminated soil, water, or feed crops. Intake rates for home produced food products are needed to assess exposure to local contaminants present in homegrown or home caught foods. Recently, EPA analyzed data from the U.S: Department of Agriculture's (USDA) Nationwide Food Consumption Survey (NFCS) to generate distributions of intake rates for home produced foods. The methods used and the-results of these analyses are presented below. 13.2. . METHODS Nationwide Food Consumption Survey (NFCS) data were used to generate intake rates for home produced foods. USDA conducts the NFCS every 10 years to analyze the food consumption behavior and dietary status of Americans (USDA, 1992). The most recent NFCS was conducted in 1987-88. The survey used a statistical sampling technique designed to ensure that all seasons, geographic regions of the 48 conterminous states in the U.S., and socioeconomic and demographic groups were represented (USDA, 1994). There were two components of the NFCS. The household component collected information over a s*even-day period on the socioeconomic and demographic characteristics of households, and the types, amount, value, and sources of foods consumed by the household (USDA, 1994). The individual intake component collected information on food intakes of individuals within each household over a three-day period (USDA, 1993). The sample size for the 1987-88 survey was approximately 4,300 Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 13 -Intake Rates for Various Home Produced Food Items households (over 10,000 individuals). This is a decrease over the previous survey conducted in 1977-78 which sampled approximately 15,000 households (over 36,000 individuals) (USDA, 1994). The sample size was lower in the 1987-88 survey as a result of budgetary constraints and low response rate (i.e., 38 percent for the household survey and 31 percent for the individual survey) (USDA, 1993). However, NFCS data from 1987-88 were used to generate homegrown intake rates because they were the most recent data available and were believed to be more reflective of current eating patterns among the U.S. population. The USDA data were adjusted by applying the sample weights calculated by USDA to the data set prior to analysis. The USDA sample weights were designed to "adjust for survey non-response and other vagaries of the sample selection process" (USDA, 1987-88). Also, the USDA weights are calculated "so that the weighted sample total equals the known population total, in thousands, for several characteristics thought to be correlated with eating behavior" (USDA, 1987-88). For the purposes of this study, home produced foods were defined as homegrown fruits and vegetables, meat and dairy products derived from consumer-raised livestock or game meat, and home caught fish. The food items/groups selected for analysis included major food groups (i.e., total fruits, total vegetables, total meats, total dairy, total fish and shellfish), individual food items for which >30 households reported eating the home produced form of the item, fruits and vegetables categorized as exposed, protected, and roots, and various USDA fruit and vegetable subcategories (i.e., dark green vegetables, citrus fruits, etc.). Food items/groups were identified in the NFCS data base according to NFCS-defined food codes. Appe!ldix 13A presents the codes used to determine the various food groups. Although the individual intake component of the NFCS gives the best measure of the amount of each food item eaten by each individual in the household, it could not be used directly to measure consumption of home produced food because the individual component does not identify the source of the food item (i.e., as home produced or not). Therefore, an analytical method which incorporated data from both the household and individual survey components was developed to estimate individual home produced food intake. The USDA household data were used to determine (t) the amount of each home produced food item used during a week by household members and (2) the number of meals eaten in the household by each household member during a week. Note that the household survey reports .the total amount of each food item used in the household* (whether by guests or household members); the amount used by household members was derived by multiplying the total amount used in the household by the proportion of all meals served in the household (during the survey week) that were consumed by. household members. Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 13 -Intake Rates for Various Home Produced Food Items The individual survey data were used to generate average sex-and age-specific serving sizes for each food item. The age categories used in the analysis were as follows: 1 to 2 years; 3 to 5 years; 6 to 11 years; 12 to 19 years; 20 to 39 years; 40 to 69 years; and over 70 years (intake rates were not calculated for children under 1; the rationale for this is discussed below). These serving sizes were used during subsequent analyses to generate homegrown food intake rates for individual household members. Assuming that the proportion of the household quantity of each homegrown food item/group was a function ofthe number of meals and the mean sex-and age-specific serving size for each family member, individual intakes of home produced food were calculated for all members . of the survey population using SAS programming in which the following general equation was used:
where: w.' I W. m;q; f -n--' m;q; i'1 (Eqn. 13-1) W; = Homegrown amount of food item/group attributed to member i during the week (g/week); W 1 = Total quantity of homegrown food item/group used by the family members (g/week); m; = Number of meals of househoid food consumed by member i during the week (meals/week); and q; = Serving size for an individual within the age and sex category of the member (g/meal). Daily intake of a homegrown food item/group was determined by dividing the weekly value (wJ by seven. Intake rates were indexed to the self-reported body weight of the survey respondent and reported in units of g/kg-day. Intake rates were not calculated for children under one year of age because their diet differs markedly from that of other household members, and thus the assumption that all household members share all foods would be invalid for this age group. In Section 13.5, a method for per-capita homegrown intake in this age group is suggested. For the major food groups (fruits, vegetables, meats, dairy, and fish) and individual foods consumed by at least 30 households, distributions of home produced intake among consumers were generated for the entire data set and according to the following subcategories: age groups, urbanization categories, seasons, racial classifications, regions, and responses to the questionnaire. Consumers were defined as members of survey households who reported consumption of the food item/group of interest during the one week survey period. In addition, for the major food groups, distributions were generated for each region by season, urbanization, and responses to the questionnaire. Table 13-3 presents the codes, definitions, and a description of the data included in each of the subcategories. Intake rates were not calculated for food items/groups for which less than 30 households reported Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 13 -Intake Rates for Various Home Produced Food Items home produced usage because the number of observations may be inadequate for generating distributions that would be representative of that segment of consumers. Fruits and vegetables were also classified as exposed, protected, or roots, as shown in Appendix 13A of this document. Exposed foods are those.that are grown above ground and are ** likely to be contaminated by pollutants deposited,on surfaces that are eaten. *Protected products are those that have outer protective coatings that are typically removed before . consumption. Distributions of intake were tabulated for these food classes for the same subcategories listed above. Distributions were also tabulated for the following USDA food classifications: dark green vegetables, deep yellow vegetables, other vegetables, citrus fruits, and other fruits. Finally, the percentages of total intake of the food items/groups consumed within survey households that can be attributed to home production were tabulated. The percentage of intake that was homegrown was calculated as the ratio of
total intake of the homegrown food item/group by the survey population to the total intake of all forms of the food by the survey population. As disccussed in Section 13.3, percentiles of average daily intake derived from short time intervals (e.g., 7 days) will not, in general, be reflective of long term patterns. This is especially true regarding consumption of many homegrown products (e.g., fruits, vegetables), where there is often a strong seasonal component associated with their use. To try to derive, for the major food categories, the long term distribution of average daily intake rates from the short-term data available here, an approach was developed which attempted to account for seasonal variability in consumption. This approach used regional "seasonally adjusted distributions" to approximate regional long term distributions and then
combined these regional adjusted distributions (in proportion fo the weights for each region) to obtain a U.S. adjusted distribution which approximated the U.S. long term distribution. The percentiles of the seasonally adjusted distribution for a given region were generated by averaging the corresponding percentiles of each of the four seasonal distributions of the region. More formally, the seasonally adjusted distribution for each region is such that its inverse cumulative distribution function is the average of the inverse cumulative distribution functions of each of the seasonal distributions of that region. The use of regional seasonally adjusted distributions to approximate regional long term distributions is based on the assumption that each individual consumes at the same regional percentile levels for each season and consumes at a constant weekly rate throughout a given season. Thus, for instance, if the 60th percentile weekly intake level in the South is 14.0 g in the summer and 7 .0 g in each of the three other seasons, then an individual in the South with an average weekly intake of.14.0 g over the summer would be assumed to have an intake of 14.0 g for each week of the summer and an intake of 7 .0 g for each week of the other seasons. Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 13 -Intake Rates for Various Home Produced Food Items Note that the seasonally adjusted distributions derived above were generated using the overall distributions, i.e., both consumers and non-consumers. However, since all the other distributions presented in this section are based on consumers only, the for the adjusted distributions have been revised to reflect the percentiles among consumers only. Given the above assumption about how each individual consumes, the percentage consuming for the seasonally adjusted distributions give an estimate of the percentage of the population consuming the specified food category at any time during the yea,r. The intake data presented here for consumers of home produced foods and the total number of individuals surveyed may be used to calculate the mean and the percentiles of the distribution of home produced food consumption in the overall population (consumers and non-consumers) as follows: , Assuming that IRP is the homegrown intake rate of food item/group at the pth percentile and Ne is the weighted number of individuals consuming the homegrown food item, and NT is the weighted total number of individuals surveyed, then NT -Ne is,the weighted number _ of individuals who reported zero consumption of the food item. In addition, there are (p/100 x Ne) individuals below the pth percentile. Therefore, the percentile that corresponds to a particular intake rate (IRP) for the overall distribution of homegrown food consumption (including consumers and nonconsumers) can be obtained by: ( X Ne % (NT & Ne)) p th ' 100 x 100 ' overall N ,T (Eqn. 13-2) Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 13 -Intake Rates for Various Home Produced Food Items For example, the percentile of the overall population that is equivalent to the 50th percentile consumer only intake rate for homegrown fruits would be calculated as follows: From Table 13-8, the 50th percentile homegrown fruit intake rate (IR50) is 1.07 g/kg-day. The weighted number of individuals consuming fruits (N0) is 14,7 44,000. From Table 13-4, the weighted total number of individuals surveyed (NT) is 188,019,000. The number of individuals consuming fruits below the 50th percentile is: p/100 x NC = (0.5) x (14,744,000) = 7,372,000 The number of individuals that did not consume fruit during the survey period is: NT-NC = 188,019,000 -14,744,000 = 173,275,000 The total number of individuals with homegrown intake rates at or below 1.07 g/kg-day is (p/100 x Ne)+ (NT -Ne) = 7,372,000 + 173,275,000 = 180,647,000 The percentile of the overall population that is represented by this intake rate is: th ' 100 x (180,647,000 I 188,109,000) Poverall ' 96th percentile Therefore, an intake rate of 1.07 g/kg-day of homegrown fruit corresponds to the 96th percentile of the overall population. Following the same procedure described above, 5.97 g/kg-day, which.is the 90th percentile of the consumers only population, corresponds to the 99th percentile of the overall"populatioh. Likewise, 0.063 g/kg-day, which is the 1st percentile of the consumers only population, corresponds to the 92nd percentile of the overall population. Note that the consumers only distribution corresponds to the tail of the distribution for the overall population. Consumption rates below the 92nd percentile are very close to zero. The mean intake rate for the overall population can be calculated by multiplying the mean intake rate among consumers by the proportion of individuals consuming the homegrown food item, N/Nr. Table 13-4 displays the weighted numbers Nr, as well as the unweighted total survey sample sizes, for each subcategory and overall. It should be noted that the total unweighted number of observations in Table 13-4 (9,852) is somewhat lower than the number of observations reported by USDA because this study only used observations for family members for which age and body weight were specified. As mentioned above, the intake rates derived in this section are based on the amount of household food consumption. As measured by the NFCS, the amount of food "consumed" by the household is a measure of consumption in an economic sense, i.e., a measure of the weight of food brought into the household that has been consumed (used Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 13 -Intake Rates for Various Home Produced Food Items up) in some manner. In addition to food being consumed by persons, food may be used up by spoiling, by being discarded (e.g., inedible parts), through cooking processes, etc. USDA estimated preparation losses for various foods (USDA, 1975). For meats, a net cooking loss, which includes dripping and volatile losses, and a net post cooking loss, which involves losses from cutting, bones, excess fat, scraps and juices, were derived for a variety of cuts and cooking methods. For each meat type (e.g., beef) EPA has averaged these losses across all cuts and cooking methods to obtain a mean net cooking loss and a mean net post cooking loss; these are displayed in Table 13-5. For individual fruits and vegetables, USDA (1975) also gave cooking and post-cooking losses. These data are presented in Tables 13-6 and 13-7. The following formulas can be used to convert the intake rates tabulated here to rates reflecting actual consumption: (Eqn. 13-3) I * (Eqn. 13-4) I where IA is the adjusted intake rate, I is the tabulated intake rate, L1 is the cooking loss, L2 is the post-cooking loss and Lp is the paring or preparation loss. For fruits, corrections based on postcooking losses only apply to fruits that are eaten in cooked forms. For raw forms of the fruits, paring or preparation loss data should be used to correct for losses from . removal of skin, peel, core, caps, pits, stems, and defects, or draining of liquids from canned or frozen forms. To obtain preparation losses for food categories, the preparation losses of the individual foods making up the category can be averaged. In calculating ingestion exposure, assessors should use consistent forms in combining intake rates with contaminant concentrations. This issue has been previously discussed in the other food Chapters. 13.3. RESULTS The intake rate distributions (among consumers) for total home produced fruits, vegetables, meats, fish and dairy products are shown, respectively, in Tables 13-8 through 13-32 (displayed at the end of Chapter 13). Also shown in these tables is the proportion of respondents consuming the item during the (one-week) survey period. Homegrown vegetables were the most commonly consumed of the major food groups (18.3%), followed by fruit (7.8%), meat (4.9%), fish (2.1%), and dairy products (0.7%). The intake rates for . Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 13 -Intake Rates for Various Home Produced Food Items the major food groups vary according to region, age, urbanization code, race, and response to survey questions. In general, intake rates of home produced foods are higher an:iong populations in non-metropolitan and suburban areas and lowest in central city areas. Results of the regional analyses indicate that intake of homegrown fruits, vegetable.s, meat and dairy products is generally highest for individuals in the Midwest and South and lowest for those in the Northeast. Intake rates of home caught fish were generally highest among consumers in the South. Homegrown intake was generally higher among individuals who indicated that they operate a farm, grow their own vegetables, raise animals, and catch their own fish. The results of the seasonal analyses for all regions combined indicated that, in general, homegrown fruits and vegetables were eaten at a higher rate in summer, and home caught fish was consumed at a higher rate in spring; however, seasonal intake varied based on individual regions. Seasonally adjusted intake rate distributions for the major food groups are presented in Table 13-33. Tables through 13-60 present distributions of intake for individual home produced food items for households that reported consuming the homegrown form of the food during the survey period. Intake rate distributions among consumers for homegrown foods categorized as exposed fruits and vegetables, protected fruits and vegetables, and root vegetables are presented in Tables 13-61 through 13-65; the intake distributions for various USDA classifications (e.g., dark green vegetables) are presented in Tables 13-66 through 13-70. The results are presented .in units of g/kg-day. Table 13-71 presents the fraction of household intake attributed to home produced forms of the food items/groups evaluated. Thus, use of these data in calculating potential dose does not require the body weight factor to be included in the*denominator of the average daily dose (ADD) equation. It should be noted that converting these intake rates into units of g/day by multiplying by a single average body weight is inappropriate, because individual intake rates were indexed to the reported body weights of the survey respondents. However, if there is a need to compare the total intake data presented here to other intake data in units of g/day, a body weight less than 70 kg (i.e., approximately 60 kg; calculated based on the number of respondents in each age category and the average body weights for these age groups, as presented in Volume I, Chapter 7) should be used because the total survey population included children as well as adults. 13.4 .. ADVANTAGES AND LIMITATIONS The USDA NFCS data set is the largest publicly available source of information on food consumption habits in the United States. The advantages of using this data set are that it is expected to be representative of the U.S. population and that it provides information on a wide variety of food groups. However, the data collected by the USDA NFCS are based on short-term dietary recall and the intake distributions generated from them may not accurately reflect long-term intake patterns, particularly with respect to the tails (extremes) of the distributions. Also, the two survey components (i.e., household and Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 13 -Intake Rates for Various Home Produced Food Items individual) do not define food items/groups in a consistent manner; as* a result, some errors may be introduced into these analyses because the two survey components are linked. The results presented here may also be biased by assumptions that are inherent in the analytical method The analytical method may not capture all high-end consumers within households because average serving sizes are used in calculating the proportion of homegrown food consumed by eac.h household member. Thus, for instance, in a person household where one member had high intake and one had low intake, the method used here would assume that both members had an equal and moderate level of intake. In addition, the analyses assume that all family members consume a portion of the home produced food used within the household. However, not all family members may consume each home produced food item and serving sizes allocated here may not be entirely representative of the portion of household foods consumed by each family member. As was mentioned in Section 13.2; no analyses were performed for th*e under 1 year age group due to the above concerns. Below, in Section 13.5, a recommended approach for dealing with this age group is presented. The preparation loss factors discussed in Section 13.2 are intended to convert intake rates based on "household consumption" to rates reflective of what individuals actually consume. However, these factors do not include losses to spoilage, feeding to pets, food thrown away, etc . . It should also be noted that because this analysis is based on the 1987-88 NFCS, it may not reflect recent changes in food consumption patterns. The low response rate associated with the 1987-88 NFCS also contributes to the uncertainty of the homegrown intake rates generated using these data. 13.5. RECOMMENDATIONS The distribution data presented in this study may be used to assess exposure to contaminants in foods grown, raised, or caught at a specific site. Table 13-72 presents the confidence ratings for homegrown food intake. The recommended values for mean intake rates among consumers for the various home produced foods can be taken from the tables presented here; these can be converted to per capita rates by multiplying by the fraction consuming. The data presented here for consumers of home produced foods represent average daily intake rates of food items/groups over the seven-day survey period and do not account for variations in *eating habits during the rest of the year; thus the percentiles presented here (except the seasonally adjusted) are only valid when considering exposures over time of about one week. Similarly, the figures for percentage consuming are also only valid over a one week time period. Since the tabulated percentiles reflect the distribution among consumers only, Eqn. 13-2 must be used to convert the percentiles shown here to ones valid for the general population. Exposure Factors Handbook August 1997*

VolumeII -Food Ingestion Factors Chapter 13 -Intake Rates for Various Home Produced Food Items In contrast, the seasonally adjusted percentiles are designed to give percentiles of the long term distribution of average daily intake and the percentage consuming shown . with this distribution is designed to estimate the percent of the population consuming at any time during a year. However, because the assumptions mentioned in Section 13.2 can not be verified to hold, these upper percentiles must be assigned a low confidence rating. Eqn. 13-2 may also be used with this distribution to convert percentiles among consumers to percentiles for the general population. *

For all the rates tabulated here, preparation loss factors should be applied, where appropriate. The form of the food used to estimate intake should be consistent with the form used to measure contaminant concentration. As described above, the tables do not display rates for children under 1 year of age. For thi.s age group, it is recommended that per-capita homegrown consumption rates be estimated using the following approach. First, for each specific home produced food of interest, the ratio of per capita intake for children under 1 year compared to that of children 1 to 2 years is calculated using the USDA CSFll 1989-1991 results displayed in Volume II, Chapters 9 and 11. Note these results are based on individual food intakes; however, they consider all sources of food, not just home produced. Second, the per-capita intake rate in the 1 to 2 year age group of the home produced food of interest is calculated as described above by multiplying the fraction consuming by the mean intake rate among consumers (both these numbers are displayed in the tables). Finally, the per capita homegrown intake rate in children under 1 year of the food of interest is estimated by multiplying the homegrown per-capita intake rate in the 1 to 2 year age group by the above ratio of intakes in the under 1 year age group as compared to the 1 fo 2 year age group. The AIHC Sourcebook (AIHC, 1994) used data presented in the 1989 version of the Exposure Factors Handbook which reported data from the USDA 1977-78 NFCS. In this Handbook, new analyses of more recent data from USDA were conducted. Numbers, however, cannot be directly COfT!pared with previous values since the results from the new analyses are presented on a body weight basis. Exposure Factors Handbook August 1997 Table 13-1. 1986 Vegetable Gardening by Demographic Factors Percentage of total households that have Number of Demographic gardens(%) households (million) Factor Total 38 34 Region/section East 33 7.3 New England 37 1.9 Mid-Atlantic 32 5.4. Midwest 50 11.0 East Central 50 6.6 West Central 50 4.5 South 33 9.0 Deep South 44 3.1 Rest of South 29 5.9 West 37 6.2 Rocky Mountain 53 2.3 Pacific 32 4.2 Size of community City 26 6.2 Suburb 33 10.2 Small town 32 3.4 Rural 61 14.0 Household size Single, separated, 54 8.5 divorced, widowed Married, no children 45 11.9 Married, with children 44 13.2 Source: National Gardening Association, 1987.

Table 13-2. Percentage of Gardening Households Growing Different Vegetables in 1986 Vegetable Percent Artichokes 0.8 Asparagus 8.2 Beans 43.4 Beets 20.6 Broccoli 19.6 Brussel sprouts 5.7 Cabbage 29.6 Carrots 34.9 Cauliflower 14.0 Celery 5.4 Chard 3.5 Corn 34.4 Cucumbers 49.9 .Dried peas 2.5 Dry beans 8.9 Eggplant 13.0 Herbs 9.8 Kale 3.1 Kohlrabi 3.0 Leeks 1.2 Lettuce 41.7 Melons 21.9 Okra 13.6 Onions 50.3 Oriental vegetables 2.1 Parsnips 2.2 Peanuts 1.9 Peas 29.0 Peppers 57.7 Potatoes 25.5 Pumpkins 10.2 Radishes 30.7 Rhubarb 12.2 Spinach 10.2 Summer squash 25.7 Sunflowers \ 8.2 Sweet potatoes 5.7 Tomato 85.4 Turnips 10.7 Winter squash 11.1 Source: National Gardening Association, 1987. Table 13-3. Sub-category Codes and Definitions Code Definition Descriotion Region* 1 Northeast Includes Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, and Vermont 2 Midwest Includes Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin 3 South Includes Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, and West Virginia 4 West Includes Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming Urbanization 1 Central City Cities with populations of 50,000 or more that is the main city within the metropolitan statistical area (MSA). 2 Suburban An area that is generally within the boundaries of an MSA, but is not within the legal limit of the central city. 3 Nonmetropolitan An area that is not within an MSA. Race 1 --White (Caucasian) 2 --Black 3 --Asian and Pacific Islander 4 --Native American, Aleuts, and Eskimos 5,8,9 Other/NA Don't know, no answer, some other race Responses to Survey Questions Grow Question 75 Did anyone in the household grow any vegetables or fruit for use in the household? Raise Question 76 Did anyone in the household produce any animal products such as milk, eggs, meat, Animals or poultry for home use in your household? Fish/Hunt Question 77 Did anyone in the household catch any fish or shoot game for home use? Farm Question 79 Did anyone in the household operate a farm or ranch? Season Spring -April, May, June Summer -July, August, September Fall -October, November, December Winter -Januarv, February, March

Alaska and Hawaii were not included. Source: USDA 1987-88.

Table 13-4. Weighted and Unweighted Number of Observations (Individuals) for NFCS Data Used in Analysis of Food Intake All Reaions Northeast Midwest South West wgtd unwgtd wgtd unwgtd wgtd unwgtd wgtd unwgtd wgtd unwgtd trotal 188019000 9852 41167000 2018 46395000 2592 64331000 3399 36066000 1841 IAge (years) < 01 2814000 156 545000 29 812000 44 889000 51 568000 32 01-02 5699000 321 1070000 56 1757000 101 1792000 105 1080000 59 03-05 8103000 461 1490000 92 2251000 133 2543000 140 1789000 95 06-11 16711000 937 3589000 185 4263000 263 5217000 284 3612000 204 12-19 20488000 1084 4445000 210 5490000 310 6720000 369 3833000 195 20-39 61606000 3058 12699000 600 15627000 823 21786000 1070 11494000 565 40-69 56718000 3039 13500000 670 13006000 740 19635000 1080 10577000 549 70 + 15880000 796 3829000 176 3189000 178 5749000 300 3113000 142 Season Fall 47667000 1577. 9386000 277 14399000 496 13186000 439 10696000 365 Spring 46155000 3954 10538000 803 10657000 1026 16802000 1437 8158000 688 Summer 45485000 1423 9460000 275 10227000 338 17752000 562 7986000 246 Winter 48712000 2898 11783000 663 11112000 732 16591000 961 9226000 542 Urbanization Central City 56352000 2217 9668000 332 17397000 681 17245000 715 12042000 489 Nonmetropolitan 45023000 3001 5521000 369 14296000 1053 19100000 1197 6106000 382 Surburban 86584000 4632 25978000 1317 14702000 858 27986000 1487 17918000 970 Race Asian 2413000 114 333000 13 849000 37 654000 32 577000 32 Black 21746000 1116 3542000 132 2794000 126 13701000 772 1709000 86 Native American 1482000 91 38000 4 116000 6 162000 8 1166000 73 Other/NA 4787000 235 1084000 51 966000 37 1545000 86 1192000 61 White 157531000 8294 36170000 1818 41670000 2386 48269000 2501 31422000 1589 Response to Questionnaire Do you garden? 68152000 3744 12501000 667 22348000 1272 20518000 1136 12725000 667 Do you raise animals? 10097000 631 1178000 70 3742000 247 2603000 162 2574000 152 Do you hunt? 20216000 1148 3418000 194 6948000 411 6610000 366 3240000 177 Do you fish? 39733000 2194 5950000 321 12621000 725 13595000 756 7567000 392 Do vou farm? 7329000 435 830000 42 2681000 173 2232000 130 158600Ci 90 Table 13-5. Percent Weiaht Losses from Preparation of Various Meats Mean Net Cooking Loss(%)' Mean Net Post Cooking Loss (%)b Standard Standard Meat Type Mean Range of Means Deviation Mean Range of Means Deviation Beef 27 11 to 42 7 24 10 to 46 9 Pork 28 1to67 10 36 14 to 52 11 Chicken 32 ?to 55 9 31 16 to 51 8 Turkey 32 11 to 57 7 28 8 to 48 10 Lamb 30 25 to 37 5 34 14 to 61 14 Veal 29 10.to 45 11 25 18 to 37 9 Fish' 30 -19 to 81 19 11 1to26 6 Shellfishd 33 1to94 30 10 10 to 10 0 ' Includes dripping and volatile losses during cooking. Averaged over various cuts and preparation methods. b Includes losses from cutting, shrinkage, excess fat, bones, scraps, and juices. Averaged over various cuts and preparation methods. ' Averaged over a variety of fish, to include: bass, bluefish, butterfish, cod, flounder, haddock, halibut, lake trout, makerel, perch, porgy, red l?napper, rockfish, salmon, sea trout, shad, smelt, sole, spot, squid, swordfish steak, trout, and whitefish. d Averaged over a variety of shellfish, to include: clams, crab, crayfish, lobster, oysters, and shrimp and shrimp dishes. Source: USDA 1975. Table 13-6. Percent Weight Losses from Preparation of Various Fruits Mean Net Post Cooking Loss(%)' Mean Paring or Preparation Loss(%)**' Range of Standard Range of Type of Fruit Mean Means Deviation Mean Means Standard Apples 25 3to42 13 22* 13 to 40b NA* Pears ----22* 12 to 60* NA" 41' 25 to 47' NA' Peaches 36 19 to 50 12 24b 6 to 68b NA* Strawberries ------1 o* 6 to 14b NA" 30' 96 to 41' 15' Ora noes ------29* 19 to 38b NAb ' Includes losses from draining cooked forms. b Includes losses from removal of skin or peel, core or pit, stems or caps, seeds and defects. ' Includes losses from removal of drained liquids from canned or frozen forms. Source: USDA 1975 Table 13-7. Percent Weiqht Losses from Preparation of Various Veqetables Mean Net Cooking Loss(%)" Mean Net Post Cooking Loss (%)b Type of Standard Standard Vegetable Mean Range of Means Deviation Mean Ranqe of Means Deviation Asparagus 23 5 to 47 16 -----Beets 28 4to 60 17 ------Broccoli 14 0 to 39 13 -----Cabbage 11 4to 20 6 -----Carrots 19 2 to 41 12 ------Corn 26 -1 to 64 22 ------Cucumbers 18 5 to 40 14 -----Lettuce 22 6 to 36 12 ------Lima Beans 143 to 56 69 ------Okra 12 -10 to 40 16 ------Onions 5 -90 to 63 38 ---Peas, green 2 -147 to 62 63 ----Peppers 13 3to 27 9 ------Pumpkins 19 8to 30 11 -----Snap Beans 18 5to 42 13 ---Tomatoes 15 2to 34 10 ----Potatoes 527 to 46

121 22 1 to 33 11 a Includes losses due to paring, trimming, flowering the stalk, thawing, draining, scraping, shelling, slicing, husking, chopping, and dicing and gains from the addition of water, fat, or other ingredients. Averaged over various preparation methods. b Includes losses from draining or removal of skin. Source: USDA 1975 Table 13-8. Consumer Only Intake of Homeqrown Fruits (g/kg-day) -All Regions Combined Population Ne Ne % Graue watd unwatd Consumina Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 14744000 817 7.84 2.68E+OO 1.89E-01 6.26E-02 1.68E-01 2.78E-01 4.97E-01 1.07E+OO 2.37E+OO 5.97E+OO 1.11E+01 2.40E+01 6.06E+01 Age (years) 01-02 360000 23 6.32 8.74E+OO 3.10E+OO 9.59E-01 1.09E+OO 1.30E+OO 1.64E+OO 3.48E+OO 7.98E+OO 1.93E+01 6.06E+01 6.06E+01 6.06E+01 03-05 550000 34 6.79 4.07E+OO 1.48E+OO 1.00E-02 1.00E-02 3.62E-01 9.77E-01 1.92E+OO 2.73E+OO 6.02E+OO 8.91E+OO 4.83E+01 4.83E+01 06-11 1044000 75 6.25 3.59E+OO 6.76E-01 1.00E-02 1.91E-01 4.02E-01 6.97E-01 1.31E+OO 3.08E+OO 1.18E+01 1.58E+01 3.22E+01 3.22E+01 12-19 1189000 67 5.80 1.94E+OO 3.66E-01 8.74E-02 1.27E-01 2.67E-01 4.41E-01 6.61E-01 2.35E+OO 6.76E+OO 8.34E+OO 1.85E+01 1.85E+01 20-39 3163000 164 5.13 1.95E+OO 3.33E-01 8.14E-02 1.28E-01 2.04E-01 3.74E-01 7.03E-01 1.77E+OO 4.17E+OO 6.84E+oo 1.61E+01 3.70E+01 40-69 5633000 309 9.93 2.66E+OO 3.04E-01 6.26E-02 1.91E-01 2.86E-01 4.69E-01 1.03E+OO 2.33E+OO 5.81E+OO 1.30E+01 2.38E+01 5.33E+01 70+ 2620000 134 16.50 2.25E+OO 2.34E-01 4.41E-02 2.24E-01 3.80E-01 6.11E-01 1.18E+OO 2.35E+OO 5.21E+OO 8.69E+OO 1.17E+01 1.53E+01 Season Fall 3137000 108 6.58 1.57E+OO 1.59E-01 2.63E-01 3.04E-01 3.90E-01 5.70E-01 1.04E+OO 1.92E+OO 3.48E+OO 4.97E+OO 1.06E+01 1.06E+01 Spring 2963000 301 6.42 1.58E+OO 1.37E-01 8.89E-02 1.98E-01 2.54E-01 4.23E-01 8.57E-01 1.70E+OO 4.07E+OO 5.10E+OO 8.12E+OO 3.17E+01 Summer 4356000 145 9.58 3.86E+OO 6.40E-01 1.00E-02 9.18E-02 1.56E-01 4.45E-01 1.26E+OO 3.31E+OO 1.09E+01 1.46E+01 5.33E+01 6.06E+01 Winter 4288000 263 8.80 3.08E+OO 3.41 E-01 4.41E-02 1.72E-01 2.69E-01 5.56E-01 1.15E+OO 2.61E+OO 8.04E+OO 1.53E+01 2.49E+01 4.83E+01 Urbanization Central City 3668000 143 6.51 2.31E+OO 2.64E-01 4.41E-02 1.82E-01 3.33E-01 5.67E-01 1.08E+OO 2.46E+OO 5.34E+OO 1.05E+01 1.43E+01 1.93E+01 Nonmetropolitan 4118000 278 9.15 2.41E+OO 3.09E-01 6.26E-02 1.27E-01 2.32E-01 4.50E-01 1.15E+OO 2.42E+OO 4.46E+OO 8.34E+OO 2.40E+01 5.33E+01 Suburban 6898000 394 7.97 3.07E+OO 3.22E-01 1.25E-01 2.30E-01 2.95E-01 4.91E-01 9.93E-01 2.33E+OO 7.26E+OO 1.52E+01 3.70E+01 6.06E+01 Race Black 450000 20 2.07 1.87E+OO 8.53E-01 1.32E-01 2.84E-01 4.55E-01 6.08E-01 1.13E+OO 1.53E+OO 2.29E+OO 2.29E+OO 1.93E+01 1.93E+01 White 14185000 793 9.00 2.73E+OO 1.94E-01 7.22E-02 1.82E-01 2.82E-01 5.10E-01 1.07E+OO 2.46E+OO 6.10E+OO 1.17E+01 2.40E+01 6.06E-t'01 Questionnaire Households who garden 12742000 709 18.70 2.79E+OO 2.10E-01 5.60E-02 1.84E-01 2.87E-01 5.30E-01 1.12E+OO 2.50E+OO 6.10E+OO 1.18E+01 2.49E+01 6.06E+01 Households who farm 1917000 112 26.16 2.58E+OO 2.59E-01 7.22E-02 2.76E-01 4.13E-01 7.53E-01 1.61E+OO 3.62E+OO 5.97E+OO 7.82E+OO 1.58E+01 1.58E+01 NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers: Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987/88 NFCS Table 13-9. Consumer Onlv Intake of Homearown Fruits fa/ka-davl -Northeast Population Ne Ne % Graue wntd unwntd Consuminn Mean SE P1 PS P10 P25 PSO P75 P90 P95 P99 P100 Total 1279000 72 3.11 9.29E-01 2.20E-01 7.91E-02 8.48E-02 1.61E-01 3.11E-01 4.85E-01 7.82E-01 1.29E+OO 2.16E+OO 1.17E+01 1.17E+01 Season Fall 260000 8 2.77 . . . . . . . . . . . . Spring 352000 31 3.34 8.80E-01 2.32E-01 8.74E-02 1.61E-01 1.68E-01 2.87E-01 4.85E-01 8.79E-01 1.83E+OO 2.16E+OO 7.13E+OO 7.13E+OO Summer 271000 9 2.86 . . . . . . . . . . . . Winter 396000 24 3.36 7.10E-01 1.13E-01 1.84E-01 2.07E-01 2.30E-01 2.93E-01 5.42E-01 8.81E-01 1.38E+OO 1.79E+OO 2.75E+OO 2.75E+OO Urbanization Central City 50000 3 0.52 . . . . . . . . . . . . Nonmetropalitan 176000 10 3.19 . . . . . . . . . . . Suburban 1053000 59 4.05 1.0SE+OO 2.63E-01 1.84E-01 2.30E-01 2.93E-01 4.37E-01 5.43E-01 8.12E-01 1.29E+OO 2.75E+OO 1.17E+01 1.17E+01 Questionnaire Response Households who garden 983000 59 7.86 1.04E+OO 2.64E-01 8.74E-02 1.82E-01 2.13E-01 3.75E-01 5.43E-01 8.81E-01 1.38E+OO 2.75E+OO 1.17E+01 1.17E+01 Households who farm 132000 4 15.90 . . . . . . . . .
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE= standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-10. Consumer Onlv Intake of Homearown Fruits la/ka-davl -Midwest Population t>/c Ne % Grouo watd unwatd Consumina Mean SE P1 PS P10 P25 P50 P75 P90 P95 P99 P100 Total 4683000 302 10.09 3.01E+OO 4.13E-01 4.41E-02 1.25E-01 2.35E-01 4.68E-01 1.03E+OO 2.31E+OO 6.76E+OO 1.39E+01 5.33E+01 6.06E+01 Season Fall 1138000 43 7.90 1.54E+OO 1.86E-01 2.63E-01 3.04E-01 4.74E-01 6.11E-01 1.07E+OO 1.92E+OO 3.48E+OO 4.34E+OO 5.33E+OO 5.33E+OO Spring 1154000 133 10.83 1.69E+OO 2.76E-01 8.89E-02 2.09E-01 2.62E-01 4.23E-01 9.23E-01 1.72E+OO 2.89E+OO 4.47E+OO 1.60E+01 3.17E+01 Summer 1299000 44 12.70 7.03E+OO 1.85E+OO 6.26E-02 9.18E-02 1.25E-01 4.28E-01 1.55E+OO 8.34E+OO 1.61E+01 3.70E+01 6.06E+01 6.06E+01 Winter 1092000 82 9.83 1.18E+OO 1.80E-01 2.57E-02 5.60E-02 1.46E-01 3.62E-01 6.09E-01 1.42E+OO 2.61 E+OO 3.73E+OO 1.09E+01 1.09E+01 Urbanization Central City 1058000 42 6.08 1.84E+OO 3.93E-01 4.15E-02 1.01E-01 2.63E-01 5.21E-01 1.07E+OO 1.90E+OO 2.82E+OO 9.74E+OO 1.09E+01 1.09E+01 Nonmetropolitan 1920000 147 13.43 2.52E+OO 5.43E-01 5.60E-02 1.08E-01 1.46E-01 3.96E-01 1.03E+OO 2.07E+OO 4.43E+OO 6.84E+OO 5.33E+01 5.33E+01 Suburban 1705000 113 11.60 4.29E+OO 8.72E-01 9.18E-02 2.04E-01 3.10E-01 4.81E-01 7.64E-01 3.01E+OO 1.39E+01 1.80E+01 6.06E+01 6.06E+01 Response to Questionnaire Households who garden 4060000 267 18.17 3.27E+OO 4.69E-01 4.41E-02 1.01E-01 2.04E-01 4.48E-01 1.07E+OO 2.37E+OO 7.15E+OO 1.46E+01 5.33E+01 6.06E+01 Households who farm 694000 57 25.89 2.59E+OO 3.01E-01 5.60E-02 1.91E-01 4.08E-01 1.26E+OO 1.63E+OO 3.89E+OO 6.76E+OO 8.34E+OO 1.11E+01 1.11E+01 NOTE: SE = standard error P = percer:itile of the distribution Ne wgtd = weighted number of consumers; Ne unwgtd = unweighted number of consumers in. survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-11. Consumer Onlv Intake of Homearown Fruits la/ka-dav) -South Population Ne Ne % Grouo watd unwatd Consumino Mean SE P1 PS P10 P25 PSO P75 P90 P95 pgg P100 Total 4148000 208 6.45 2.97E+OO 3.00E-01 1.12E-01 2.42E-01 3.55E-01 5.97E-01 1.35E+OO 3.01E+OO 8.18E+OO 1.41E+01 2.38E+01 2.40E+01 Season Fall 896000 29 6.80 1.99E+OO 4.39E-01 3.92E-01 4.27E-01 4.46E-01 6.SOE-01 1.13E+OO 1.96E+OO 4.97E+OO 8.18E+OO 1.06E+01 1.06E+01 Spring 620000 59 3.69 2.05E+OO 2.55E-01 1.55E-01 2.82E-01 3.11E-01 4.SOE-01 1.06E+OO 4.09E+OO 5.01E+OO 6.58E+OO 7.05E+OO 7.05E+OO Summer 1328000 46 7.48 2.84E+OO 6.SOE-01 8.14E-02 1.56E-01 2.67E-01 4.41E-01 1.31E+OO 2.83E+OO 6.10E+OO 1.43E+01 2.40E+01 2.40E+01-Winter 1304000 74 7.86 4.21E+OO 6.51E-01 1.12E-01 2.36E-01 3.82E-01 8.92E-01 1.88E+OO 3.71E+OO 1.41E+01 1.97E+01 2.38E+01 2.38E+01 Urbanization Central City 1066000 39 6.18 3.33E+OO 5.39E-01 2.36E-01 3.92E-01 4.55E-01 8.34E-01 2.55E+OO 4.77E+OO 8.18E+OO 1.06E+01 1.43E+01 1.43E+01 Nonmetropolitan 1548000 89 8.10 2.56E+OO 3.87E-01 8.14E-02 2.67E-01 3.38E-01 6.12E-01 1.40E+OO 2.83E+OO 5.97E+OO 1.04E+01 2.40E+01 2.40E+01 Suburban 1534000 80 5.48 3.14E+OO 6.02E-01 1.12E-01 1.56E-01 2.84E-01 5.08E-01 1.10E+OO 2.29E+OO 1.18E+01 1.55E+01 2.38E+01 2.38E+01 Response to Questionnaire Households who garden 3469000 174 16.91 2.82E+OO . 2.94E-01 1.56E-01 2.84E-01 3.84E-01 6.50E-01 1.39E+OO 2.94E+OO 6.10E+OO 1.41E+01 2.11E+01 2.40E+01 Households who farm 296000 16 13.26 . . . . . . . . . . .
Intake data nat provided for subpopulatins for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-12. Consumer Onlv Intake of Homearown Fruits fa/ka-davl -West Population Ne Ne % brouo watd unwatd Consumino Mean SE P1 PS P10 P25 PSO P75 P90 P95 P99 P100 trotal 4574000 233 12.68 2.62E+OO 3.07E-01 1.SOE-01 2.75E-01 3.33E-01 6.17E-01 1.20E+OO 2.42E+OO 5.39E+OO 1.09E+01 2.49E+01 4.83E+01 Fall 843000 28 7.88 1.47E+OO 2.49E-01 2.91E-01 2.91E-01 2.95E-01 4.83E-01 1.04E+OO 2.15E+OO 2.99E+OO 4.65E+OO 5.39E+OO 5.39E+OO Spring 837000 78 10.26 1.37E+OO 1.59E-01 1.73E-01 1.96E-01 2.51E-01 5.10E-01 9.81E-01 1.61E+OO 2.95E+OO 5.29E+OO 6.68E+OO 7.02E+OO Summer 1398000 44 17.51 2.47E+OO . 4.72E-01 1.86E-01 2.75E-01 4.04E-01 6.17E-01 1.28E+OO 3.14E+OO 7.26E+OO 1.09E+01 1.30E+01 1.30E+01 Winter 1496000 83 16.22 4.10E+OO 7.91E-01 7.14E-02 2.96E-01 3.33E-01 7.74E-01 1.51E+OO 3.74E+OO 1.11E+01 1.85E+01 4.83E+01 4.83E+01 Urbanization Central City 1494000 59 12.41 1.99E+OO 4.24E-01 7.14E-02 2.35E-01 3.42E-01 5.26E-01 8.63E-01 2.04E+OO 4.63E+OO 9.52E+OO 1.93E+01 1.93E+01 Nonmetropolitan 474000 32 7.76 2.24E+OO 5.25E-01 1.84E-01 2.76E-01 4.24E-01 6.25E-01 7.68E-01 2.64E+OO 4.25E+OO 1."09E+01 1.09E+01 1.09E+01 Suburban 2606000 142 14.54 3.04E+OO 4.63E-01 1.83E-01 2.75E-01 3.14E-01 7.10E-01 1.39E+OO 3.14E+OO 5.81E+OO 1.03E+01 3.22E+01 4.83E+01 Response to Questionnaire Households who garden 4170000 207 32.77 2.76E+OO 3.39E-01 1.00E-01 2.75E-01 3.14E-01 6.29E-01 1.20E+OO 2.54E+OO 5.8.1E+OO 1.09E+01 2.49E+01 4.83E+01 Households who farm 795000 35 50.13 1.85E+OO 2.59E-01 2.75E-01 2.76E-01 5.98E-01 7.10E-01 1.26E+OO 2.SOE+OO 4.63E+OO 5.00E+OO 6.B1E+OO 6.81E+OO NOTE: SE= standard error P = percentile of the distribution Ne wgtd = weighted number of consumers; Ne unwgtd = unweighted number of consumers in survey. Source: Based on EPA's analvses of the 1987-88 NFCS Table 13-13. Consumer Only Intake of Homeqrown Vegetables (q/kq-day) -All Regions Combined Population Ne Ne % Grouo watd unwatd Consumino Mean SE P1 PS P10 P25 PSO P75 P90 P95 P99 P100 Total 34392000 1855 18.29 2.08E+OO 6.76E-02 4.79E-03 1.10E-01 1.80E-01 4.47E-01 1.11E+OO 2.47E+OO 5.20E+OO 7.54E+OO 1.55E+01 2.70E+01 Age 01-02 951000 53 16.69 5.20E+OO 8.47E-01 2.32E-02 2.45E-01 3.82E-01 1.23E+OO 3.27E+OO 5.83E+OO 1.31E+01 1.96E+01 2.70E+01 2.70E+01 03-05 1235000 76 15.24 2.46E+OO 2.79E-01 0.00E+OO 4.94E-02 3.94E-01 7.13E-01 1.25E+OO 3.91E+OO 6.35E+OO 7.74E+OO 1.06E+01 1.28E+01 06-11 3024000 171 18.10 2.02E+OO 2.54E-01 5.95E-03 1.00E-01 1.60E-01 4.00E-01 8.86E-01 2.21E+OO 4.64E+OO 6.16E+OO 1.76E+01 2.36E+01 12-19 3293000 183 16.07 1.48E+OO 1.35E-01 O.OOE+OO 6.46E-02 1.45E-01 3.22E-01 8.09E-01 1.83E+OO 3.71E+OO 6.03E+OO 7.71E+OO 9.04E+OO 20-39 8593000 437 13.95 1.47E+OO 9.59E-02 1.69E-02 7.77E-02 1.57E-01 2.73E-01 7.61E-01 1.91E+OO 3.44E+OO 4.92E+OO 1.05E+01 2.06E+01 40-69 12828000 700 22.62 2.07E+OO 1.02E-01 5.13E-03 1.19E-01 2.14E-01 5.26E-01 1.18E+OO 2.47E+OO 5.12E+OO 6.94E+OO 1.49E+01 2.29E+01 70 + 4002000 211 25.20 2.51E+OO 1.94E-01 5.21E-03 1.51E-01 2.39E-01 5.81E-01 1.37E+OO 3.69E+OO 6.35E+OO 8.20E+OO 1.25E+01 1.55E+01 Seasons Fall 11026000 394 23.13 1.88E+OO 1.28E-01 4.98E-02 1.13E-01 1.80E-01 4.13E-01 9.83E-01 2.11E+OO 4.88E+OO 6.94E+OO 1.25E+01 1.89E+01 Spring 6540000 661 14.17 1.36E+OO 7.23E-02 2.44E-03 4.47E-02 1.35E-01 3.21E-01 7.04E-01 1.63E+OO 3.37E+OO 5.21E+OO 8.35E+OO 2.36E+01 Summer 11081000 375 24.36 2.86E+OO 1.93E-01 6.93E-02 1.57E-01 2.24E-01 7.12E-01 1.62E+OO 3.44E+OO 6.99E+OO 9.75E+OO 1.87E+01 2.70E+01 Winter 5745000 425 11.79 1.79E+OO 1.14E-01 3.73E-03 4.49E-02 1.56E-01 4.69E-01 1.05E+OO 2.27E+OO 3.85E+OO 6.01E+OO 1.06E+01 2.06E+01 Urbanizations Central City 6183000 228 10.97 1.40E+OO 1.23E-01 1.01E-02 6.59E-02 1.50E-01 3.00E-01 7.SOE-01 1.67E+OO 3.83E+OO 4.67E+OO 9.96E+OO 1.66E+01 Nonmetropolitan 13808000 878 30.67 2.68E+OO 1.19E-01 2.12E-02 1.58E-01 2.58E-01 5.99E-01 1.45E+OO 3.27E+OO 6.35E+OO 9.33E+OO 1.75E+01 2.70E+01 Suburban 14341000 747 16.56 1.82E+OO 9.12E-02 3.34E-03 1.10E-01 1.63E-01 3.94E-01 9.63E-01 2.18E+OO 4.32E+OO 6.78E+OO 1.25E+01 2.06E+01 Race Black 1872000 111 8.61 1.78E+OO 2.33E-01 0.00E+OO 7.77E-02 1.39E-01 4.38E-01 9.32E-01 2.06E+OO 4.68E+OO 5.70E+OD 8.20E+OO 1.89E+01 White 31917000 1714 20.26 2.10E+OO 7.09E-02 7.34E-03 1.13E-01 1.84E-01 4.54E-01 1.12E+OO 2.48E+OO 5.18E+OO 7.68E+OO 1.55E+01 2.70E+01 Response to Questionnaire Households who garden 30217000 1643 44.34 2.17E+OO 7.09E-02 5.21E-03 1.11E-01 1.85E-01 4.84E-01 1.18E+OO 2.68E+OO 5.35E+OO 7.72E+OO 1.55E+01 2.36E+01 Households who farm 4319000 262 58.93 3.29E+OO 2.51E-01 O.OOE+OO 1.61E-01 2.92E-01 8.46E-01 1.67E+OO 3.61E+OO 8.88E+OO 1.18E+01 1.76E+01 2.36E+01 NOTE: SE = standard error P = percentile of the distribution Ne wgtd = weighted number of consumers; Ne unwgtd = unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-14. Cnnsumer Onlv Intake of Homegrown Vegetables lo/ko-davl -Northeast Population Ne Ne % Grau w td unw td Consumin Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 4883000 236 11.86 1.78E+OO 1.68E-01 2.18E-03 8.27E-02 1.43E-01 2.80E-01 7.47E-01 1.89E+OO 6.03E+OO 7.82E+OO 1.27E+01 1.49E+01 Seasons Fall 1396000 41 14.87 1.49E+OO 4.06E-01 8.27E-02 1.34E-01 1.74E-01 2.69E-01 5.81E-01 1.17E+OO 6.64E+OO 9.97E+OO 1.02E+01 1.02E+01 Spring 1204000 102 11.43 8.18E-01 1.07E-01 O.OOE+OO 2.B9E-03 4.47E-02 1.72E-01 4.55E-01 9.52E-01 2.26E+OO 3.11E+OO 6.52E+OO 6.78E+OO Summer 1544000 48 16.32 2.83E+OO 4.67E-01 1.11E-01 1.45E-01 1.59E-01 7.38E-01 1.29E+OO 3.63E+OO 7.82E+OO 9.75E+OO 1.49E+01 1.49E+01 Winter 739000 45 6.27 1.67E+OO 2.74E-01 3.23E-03 4.23E-03 9.15E-02 2.56E-01 1.25E+OO 2.77E+OO 3.63E+OO 6.10E+OO 8.44E+OO 8.44E+OO Urbanizations Central City 380000 14 3.93 Nonmetropolitan 787000 48 14.25 3.05E+OO 5.41E-01 O.OOE+OO 4.68E-02 1.14E-01 2.02E-01 2.18E+OO 4.61E+OO 9.04E+OO 1.27E+01 1.49E+01 1.49E+01 Suburban 3716000 174 14.30 1.59E+OO 1.74E-01 2.44E-03 8.27E-02 1.42E-01 2.75E-01 7.18E-01 1.64E+OO 4.B2E+OO 6.80E+OO 1.02E+01 1.02E+01 Response to Questionnaire Households who garden 4381000 211 35.05* 1.92E+OO 1.84E-01 2.18E-03 8.27E-02 1.42E-01 3.10E-01 8.83E-01 2.18E+OO 6.16E+OO 7.82E+OO 1.27E+01 1.49E+01 Households who farm 352000 19 42.41
Intake data not provided for subpopulations for which there were Jess than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd = weighted number of consumers; Ne unwgtd = unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-15. Consumer Onlv Intake of Homearown Veaetables (alka-davl -Midwest Population Ne Ne % Groun watd unwatd Consumina Mean SE P1 PS P10 P25 P50 P75 P90 P95 P99 P100 Total 12160000 699 26.21 2.26E+OO 1.20E-01 1.59E-02 7.77E-02 1.80E-01 4.88E-01 1.15E+OO 2.58E+OO 5.64E+OO 7.74E+OO 1.75E+01 2.36E+01 Seasons Fall 4914000 180 34.13 1.84E+OO 1.76E-01 1.01E-02 6.51E-02 1.60E-01 4.16E..Q1 1.03E+OO 2.10E+OO 5.27E+OO 6.88E+OO 1.31E+01 1.31E+01 Spring 2048000 246 19.22 1.65E+OO 1.49E-01 6.04E-02 1.53E-01 2.21E-01 4.59E-01 9.13E-01 1.72E+OO 4.49E+OO 5.83E+OO 1.28E+01 2.36E+01 Summer 3319000 115 32.45 3.38E+OO 3.87E-01 1.05E-01 1.62E-01 3.02E-01 8.47E-01 2.07E+OO 3.94E+OO 7.72E+OO 1.40E+01 1.96E+01 2.29E+01 Winter 1879000 158 16.91 2.05E+OO 2.64E-01 2.41E-03 2.14E-02 6.59E-02 3.62E..Q1 8.77E-01 2.13E+OO 5.32E+OO 7.83E+OO 1.67E+01 2.06E+01 Urbanizations Central City 3177000 113 18.26 1.36E+OO 1.91E-01 O.OOE+OO . 6.0SE-02 1.10E-01 2.45E-01 7.13E-01 1.67E+OO 3.94E+OO 5.50E+OO 9.96E+OO 1.66E+01 Nonmetropolitan 5344000 379 37.38 2.73E+OO 1.86E-01 2.12E-02 1.13E-01 2.61E-01 5.98E..Q1 1.31E+OO 3.15E+OO 7.19E+OO 1.06E+01 1.75E+01 2.36E+01 Suburban 3639000 207 24.75 2.35E+OO 2.16E..Q1 3.26E-02 1.54E-01 2.22E-01 6.36E..Q1 1.39E+OO 2.75E+OO 4.87E+OO 7.18E+OO 1.96E+01 2.06E+01 Response to Questionnaire Households who garden 10927000 632 48.89 2.33E+OO 1.27E-01 1.59E-02 1.04E-01 1.76E-01 5.03E-01 1.18E+OO 2.74E+OO 5.81E+OO 7.75E+OO 1.67E+01 2.36E+01 Households who farm 1401000 104 52.26 3.97E+OO 4.31E..01 1.40E-01 3.35E-01 5.51E-01 8.67E..Q1 2.18E+OO 5.24E+OO 1.06E+01 1.44E+01 1.75E+01 2.36E+01 NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analvses of the 1987-88 NFCS Table 13-16. Consum*er Only Intake of Homegrown Vegetables (glkg-day) -South Population Ne Ne % Group wold unwotd Consumino Mean SE P1 PS P10 P25 P50 P75 P90 P95 P99 P100 Total 1125400 618 17.49 2.19E+OO 1.21E-01 2.92E-02 1.60E-01 2.41E-01 5.63E-01 1.24E+OO 2.69E+OO 4.92E+OO 7.43E+OO 1.70E+01 2.70E+01 0 Seasons Fall 2875000 101 21.80 2.07E+OO 2.82E-01 9.59E-02 1.13E-01 1.91E-01 5.24E-0.1 1.14E+OO 2.69E+OO 4.48E+OO 6.02E+OO 1.55E+01 1.89E+01 Spring 2096000 214 12.47 1.55E+OO 1.13E-01 1.41E-02 9.21E-02 2.61E-01 5.33E-0°1 9.35E-01 2.07E+OO 3.58E+OO 4.81E+OO 8.35E+OO 1.03E+01 Summer 4273000 151 24.07 2.73E+OO 3.16E-01 1.10E-01 1.72E-01 2.50E-01 6.15E-01 1.54E+OO 3.15E+OO 5.99E+OO 9.70E+OO 2.36E+01 2.70E+01 Winter 2010000 152 12.12 1.88E+OO 1.37E-01 3.03E-03 1.63E-01 3.53E-01 6.40E-01 1.37E+OO 2.69E+OO 3.79E+OO 5.35E+OO 7.47E+OO 8.36E+OO Urbanizations Central City 1144000 45 6.63 1.10E+OO 1.62E-01 1.10E-02 9.59E-02 1.50E-01 2.63E-01 6.15E-01 1.37E+OO 2.79E+OO 3.70E+OO 4.21E+OO 4.58E+OO Nonmetropolitan 6565000 386 34.37 2.78E+OO 1.84E-01 5.0BE-02 2.23E-01 3.50E-01 7.12E-01 1.66E+OO 3.31E+OO 5.99E+OO 9.56E+OO 1.89E+01 2.70E+01 Suburban 3545000 187 12.67 1.44E+OO 1.13E-01 .O.OOE+OO 1.13E-01 1.99E-01 3.96E-01 9.33E-01 1.72E+OO 3.61E+OO 5.26E+OO 8.20E+OO 8.20E+OO Response b Questionnaire Households who garden 9447000 522 46.04 2.27E+OO 1.22E-01 3.46E-02 1.61E-01 2.62E-01 6.10E-01 1.37E+OO 3.02E+OO 5.18E+OO 7.43E+OO 1.55E+01 2.36E+01 Households who farm 1609000 91 72.09 3.34E+OO 4.57E-01 0.00E+OO 1.32E-01 2.33E-01 1.03E+OO 1.72E+OO 3.15E+OO 9.56E+OO 1.18E+01 2.36E+01 2.36E+01 NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-17. Consumer Only Intake of Homegrown Vegetables (g/kg-day) -West Population Ne Ne % Grouo watd unwatd Consumina Mean SE P1 PS P10 P25 PSO P75 P90 P95 P99 P100 Total 6035000 300 16.73 1.81E+OO 1.38E-01 7.35E-03 9.85E-02 1.66E-01 3.79E-01 9.01E-01 2.21E+OO 4.64E+OO 6.21E+OO 1.14E+01 1.55E+01 Seasons Fall 1841000 72 17.21 2.01E+OO 2.93E-01 9.83E-02 1.50E-01 2.04E-01 4.81E-01 1.21E+OO 2.21E+OO 4.85E+OO 7.72E+OO 1.25E+01 1.25E+01 Spring 1192000 99 14.61 1.06E+OO 1.74E-01 3.31E-03 7.35E-03 4.66E-02 1.95E-01 3.56E-01 9.08E-01 3.37E+OO 5.54E+OO 8:60E+OO 8.60E+OO Summer 1885000 59 23.60 2.39E+OO 3.71E-01 6.93E-02 1.04E-01 2.46E-01 5.45E-01 1.37E+OO 3.23E+OO 4.67E+OO 8.36E+OO 1.55E+01 1.55E+01 Winter 1117000 70 12.11 1.28E+OO 1.72E-01 1.29E-02 1.52E-01 1.99E-01 4.83E-01 7.65E-01 1.43E+OO 2.81E+OO 5.12E+OO 7.57E+OO 7.98E+OO Urbanizations Central City 1482000 56 12.31 1.80E+OO 2.76E-01 2.58E-02 7.39E-02 1.57E-01 4.81E-01 1.10E+OO 2.95E+OO 4.64E+OO 4.85E+OO 1.14E+01 1.14E+01 Nonmetropolitan 1112000 65 18.21 1.52E+OO 2.24E-01 3.42E-03 9.80E-03 2.04E-01 2.69E-01 6.75E-01 2.13E+OO 4.13E+OO 5.12E+OO 8.16E+OO 8.16E+OO Suburban 3441000 179 19.20 1.90E+OO 1.98E-01 1.29E-02 1.04E-01 1.52E-01 3.94E-01 9.32E-01 2.20E+OO 4.63E+OO 7.98E+OO 1.25E+01 1.55E+01 Response to Questionnaire Households who garden 5402000 276 42.45 1.91E+OO 1.04E-03 8.53E-03 1.04E-01 1.66E-01 4.33E-01 1.07E+OO 2.37E+OO 4.67E+OO 6.21E+OO 1.25E+01 1.55E+01 Households who farm 957000 48 60.34 2.73E+OO 3.32E-03 1.17E-01 4.14E-01 4.69E-01 7.65E-01 1.42E+OO 3.27E+OO 6.94E+OO 1.09E+01 1.55E+01 1.55E+01 NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-18. ConsumerOnlv Intake of Home Produced Meats ln/kn-dav\ -All Renions Combined Population Ne Ne % Group watd unwatd Consumina Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 9257000 569 4.92 2.21E+OO 1.07E-01 1.21E-01 2.37E-01 3.74E-01 6.60E-01 1.39E+OO 2.89E+OO 4.89E+OO 6.78E+OO 1.40E+01 2.32E+01 Age 01-02 276000 22 4.84 3.65E+OO 6.10E-01 3.85E-01 9.49E-01 9.49E-01 1.19E+OO 2.66E+OO 4.72E+OO 8.68E+OO 1.00E+01 1.15E+01 1.15E+01 03-05 396000 26 4.89 3.61E+OO 5.09E-01 8.01E-01 8.01E-01 1.51E+OO 2.17E+OO 2.82E+OO 3.72E+OO 7.84E+OO 9.13E+OO 1.30E+01 1.30E+01 06-11 1064000 65 6.37 3.65E+OO 4.51E-01 3.72E-01 6.52E-01 7.21E-01 1.28E+OO 2.09E+OO 4.71E+OO 8.00E+OO 1.40E+01 1.53E+01 1.53E+01 12-19 1272000 78 6.21 1.70E+OO 1.68E-01 1.90E-01 3.20E-01 4.70E-01 6.23E-01 1.23E+OO 2.35E+OO 3.66E+OO 4.34E+OO 6.78E+OO 7.51E+OO 20-39 2732000 158 4.43 1.82E+OO 1.53E-01 1.23E-01 1.85E-01 2.95E-01 5.28E-01 1.11E+OO 2.65E+OO 4.52E+OO 6.23E+OO 9.17E+OO 1.09E+01 40-<39 2872000 179 5.06 1.72E+OO 1.11E-01 1.81E-02 2.12E-01 3.43E-01 5.84E-01 1.17E+OO 2.38E+OO 3.67E+OO 5.16E+OO 5.90E+OO 7.46E+OO 70 + 441000 28 ' 2.78 1.39E+OO 2.34E-01 9.26E-02 9.26E-02 1.25E-01 5.47E-01 1.01E+OO 1.81E+OO 2.82E+OO 3.48E+OO 7.41E+OO 7.41E+OO Seasons Fall 2852000 107 5.98 1.57E+OO 1.39E-01 1.23E-01 2.10E-01 3.52E-01 5.21E-01 1.11E+OO 2.27E+OO 3.19E+OO 4.41E+OO 6.78E+OO 7.84E+OO Spring 1726000 197 3.74 2.37E+OO 1.52E-01 2.44E-01 3.20E-01 4.46E-01 7.76E-01 1.69E+OO 3.48E+OO 5.00E+OO 6.67E+OO 1.01E+01 1.30E+01 Summer 2368000 89 5.21 3.10E+OO 3.82E-01 1.81E-02 1.85E-01 4.06E-01 8.52E-01 1.77E+OO 4.34E+OO 7.01E+OO 1.05E+01 2.23E+01 2.23E+01 Winter 2311000 176 4.74 1.98E+OO 1.74E-01 1.35E-01 2.37E-01 3.67E-01 6.48E-01 1.33E+OO 2.43E+OO 3.96E+OO 6.40E+OO 1.09E+01 2.32E+01 Urbanizations Central City 736000 28 1.31 1.15E+OO 1.83E-01 1.82E-01 1.85E-01 2.10E-01 4.42E-01 7.21E-01 1.58E+OO 2.69E+OO 3.40E+OO 3.64E+OO 3.64E+OO Nonmetropolitan 4932000 315 10.95 2.70E+OO 1.76E-01 1.23E-01 2.63E-01 4.06E;-01 7.49E-01 1.63E+OO 3.41E+OO 6.06E+OO 8.47E+OO 1.53E+01 2.32E+01 Suburban 3589000 226 4.15 1.77E+OO 1.03E-01 2.90E-02 2.87E-01 3.67E-01 6.80E-01 1.33E+OO 2.49E+OO 3.66E+OO 4.71E+OO 7.20E+OO 1.01E+01 Race Black 128000 6 0.59 . . . . . . . . White 8995000 556 5.71 2.26E+OO 1.09E-01 9.26E-02 2.57E-01 3.86E-01 6.80E-01 1.41E+OO 2.91E+OO 5.00E+OO 7.01E+OO 1.40E+01 2.32E+01 Response to Questionnaire Households who 5256000 343 52.06 2.80E+OO 1.45E-01 2.12E-01 3.86E-01 6.23E-01 1.03E+OO 1.94E+OO 3.49E+OO 5.90E+OO 7.84E+OO 1.40E+01 2.32E+01 raise animals Households who farm 3842000 243 52.42 2.86E+OO 1.85E-01 1.97E-01 4.45E-01 5.98E-01 8.94E-01 1.84E+OO 3.64E+OO 6.09E+OO 8.00E+OO 1.40E+01 2.32E+01
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd = weighted number of consumers; Ne unwgtd = unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-19. Consumer Only Intake of Home Produced Meats (g/kg-dav\ -Northeast Population Ne Ne % Grouo wold unwatd Consumina Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 1113000 52 2.70 1.46E+OO 2.10E-01 2.92E-01 3.40E-01 3.52E-01 6.44E-01 B.94E-01 1.87E+OO 2.6BE+OO 2.89E+OO 1.09E+01 1.09E+01 Seasons Fall 569000 ts 6.06 . . . . . . . . . . . . Spring 66000 8 0.63 . . . . . . . . . . . . Summer 176000 6 1.86 . . . . . . . . . . . . Winter 302000 20 2.56 2.02E+OO 5.56E-01 2.92E-01 3.14E-01 4.30E-01 6.19E-01 1.11E+OO 2.38E+OO 2.93E+OO 7.46E+OO 1.09E+01 1.09E+01 Urbanizations Central City 0 0 0.00 Nonmetropolitan 391000 17 7.08 . . . . . . . . . . . . Suburban 722000 35 2.78 1.49E+OO 1.53E-01 2.92E-01 3.52E-01 4.30E-01 6.BOE-01 1.39E+OO 2.34E+OO 2.68E+OO 2.89E+OO 3.61E+OO 3.61E+OO Response to Questionnaire Households who raise animals 509000 25 43.21 2.03E+OO 3.85E-01 6.19E-01 6.46E-01 6.46E-01 8.78E-01 1.62E+OO 2.38E+OO 2.93E+OO 7.46E+OO 1.09E+01 1.09E+01 Households who farm 373000 15 44.94 . . . . . . . . . . . .
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE= standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS
Table 13-20. Consumer Only Intake of Home Produced Meats (g/kg-dav\ -Midwest Population Ne Ne % Grouo wold unwatd Consuminn Mean SE P1 P5 P10 P25 PSO P75 P90 P95 P99 P100 Total 3974000 266 8.57 2.55E+OO 1.81E-01 1.25E-01 2.57E-01 3.85E-01 6.60E-01 1.40E+OO 3.39E+OO 5.75E+OO 7.20E+OO 1.53E+01 2.23E+01 Seasons Fall 1261000 49 8.76 1.76E+OO 2.31E-01 2.10E-01 2.57E-01 3.72E-01 4.95E-01 1.19E+OO 2.66E+OO 3.49E+OO 6.06E+OO 6.78E+OO 6.78E+OO Spring 940000 116 8.82 2.58E+OO 2.24E-D1 2.44E-01 3.11E-01 4.08E-01 7.33E-01 1.98E+OO 3.67E+OO 5.14E+OO 7.79E+OO 1.15E+01 1.30E+01 Summer 930000 38 9.09 4.10E+OO 7.45E-01 9.26E-02 1.25E-01 5.78E-01 8.93E-D1 2.87E+OO 5.42E+OO 8.93E+OO 1.53E+01 2.23E+01 2.23E+01 Winter 843000 63 7.59 2.00E+OO 2.41E-01 1.21E-01 2.37E-01 3.28E-01 6.48E-01 1.36E+OO 2.69E+OO 4.11E+OO 5.30E+OO 8.10E+OO 1.22E+01 Urbanizations Central City 460000 18 2.64 . . . . . . . . . ' . . Nonmetropolitan 2477000 175 17.33 3.15E+OO 2.58E-01 9.26E-02 2.95E-01 4.25E-01 8.16E-01 2.38E+OO 4.34E+OO 6.15E+OO 9.17E+OO 1.53E+01 2.23E+01 Suburban 1037000 73 7.05 1.75E+OO 1.99E-01 2.87E-01 3.65E-01 4.08E-01 6.6DE-01 1.11E+OO 2.03E+OO 4.16E+OO 5.39E+OO 7.20E+OO 1.01E+01 Response to Questionnaire Households who raise animals 2165000 165 57.86 3.20E+OO 2.23E-01 2.56E-01 3.86E-01 5.78E-01 1.07E+OO 2.56E+OO 4.42E+OO 6.06E+OO 9.13E+OO 1.53E+01 1.53E+01 Households who farm 1483000 108 55.32 3.32E+OO 2.91E-01 3.65E-01 5.43E-01 5.89E-01 1.07E+OO 2.75E+OO 4.71E+OO 6.78E+00 9.17E+OO 1.53E+01 1.53E+01
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number.of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-21. Consumer Onlv Intake of Home Produced Meats (q/ko-day) -South Population Ne Ne % Groua watd unwatd Consumina Mean SE P1 PS P10 P25 P50 P75 P90 P95 P99 P100 Total 2355000 146 3.66 2.24E+OO 1.94E-01 1.81E-02 1.56E-01 2.97E-01 7.21E-01 1.53E+OO 3.07E+OO 5.07E+OO 6.71E+OO 1.40E+01 1.40E+01 Seasons Fall 758000 28 5.75 1.81E+OO 2.87E-01 1.23E-01 1.56E-01 1.90E-01 8.19E-01 1.53E+OO 2.38E+OO 3.19E+OO 4.41E+OO 7.84E+OO 7.84E+OO Spring 511000 53 3.04 2.33E+OO 2.66E-01 1.93E-01 2.97E-01 4.99E-01 7.52E-01 1.80E+OO 2.82E+OO 5.16E+OO 6.71E+OO 7.51E+OO 7.51E+OO Summer 522000 18 2.94 . . . . . . . . . . . . Winter 564000 47 3.40 1.80E+OO 2.45E-01 3.70E-02 1.97E-01 2.51E-01 7.16E-01 1.40E+OO 2.17E+OO 3.55E+OO 4.58E+OO 8.47E+OO 8.47E+OO Urbanizations Central City 40000 1 0.23 . . . . . . . . . . Nonmetropolitan 1687000 97 8.83 2.45E+OO 2.59E-01 1.23E-01 1.90E-01 4.02E-01 7.77E-01 1.61E+OO 3.19E+OO 6.09E+OO 7.84E+OO 1.40E+01 1.40E+01 Suburban 628000 48 2.24 1.79E+OO 2.30E-01 1.81E-02 2.90E-02 3.70E-02 6.28E-01 1.40E+OO 2.31E+OO 4.56E+OO 4.61E+OO 6.40E+OO 6.40E+OO Response to Questionnaire Households who raise animals 1222000 74 46.95 3.16E+OO 3.16E-01 2.63E-01 6.67E-01 8.35E-01 1.34E+OO 2.11E+OO 3.79E+OO 6.67E+OO 8.47E+OO 1.40E+01 1.40E+01 Households who farm 1228000 72 55.02 2.85E+OO 3.24E-01 1.95E-01 4.99E-01 5.98E-01 1.01E+OO 1.93E+OO 3.48E+OO 6.23E+OO 8.47E+OO 1.40E+01 1.40E+01
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE= standard error P = percentile of the distribution Ne wgtd = weighted number of consumers; Ne unwgtd = unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-22. Consumer Onlv Intake of Home Produced Meats Ca/ka-day) -West Population Ne Ne % Groun watd unwatd Consumina Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 1815000 105 5.03 1.89E+OO 2.12E-01 1.52E-01 2.25E-01 3.90E-01 6.58E-01 1.42E+OO 2.49E+OO 3.66E+OO 4.71E+OO 8.00E+OO 2.32E+01 Seasons Fall 264000 12 2.47 . . . . . . . . . . . . Spring 209000 20 2.56 1.86E+OO 2.27E-01 2.99E-01 4.25E-01 8.70E-01 1.22E+OO 1.56E+OO 2.43E+OO 3.48E+OO 4.20E+OO 4.20E+OO 4.20E+OO Summer 740000 27 9.27 2.20E+OO 3.18E-01 1.85E-01 4.06E-01 5.35E-01 1.07E+OO 1.69E+OO 3.27E+OO 4.44E+OO 4.71E+OO 8.00E+OO 8.00E+OO Winter 602000 46 6.53 2.11E+OO 4.SSE-01 1.35E-01 3.56E-01 4.28E-01 6.72E-01 1.19E+OO 2.35E+OO 3.64E+OO 7.02E+OO 2.32E+01 2.32E+01 Urbanizations Central City 236000 9 1.96 . . . . . . . . . . . Non metropolitan 377000 26 6.17 2.10E+OO 7.00E-01 3.30E-01 3.30E-01 4.06E-01 6.721';-01 1.19E+OO 1.77E+OO 3.72E+OO 4.97E+OO 2.32E+01 2.32E+01 Suburban 1202000 70 6.71 1.95E+OO 1.99E-01 1.52E-01 2.25E-01 3.67E-01 l-80E-01 1.52E+OO 2.71E+OO 4.20E+OO "4.71E+OO 8.00E+OO 8.00E+OO Response to Questionnaire Households who raise animals 1360000 79 52.84 2.12E+OO 2.65E-01 1.52E-01 2.25E-01 3.90E-01 8.15E-01 1.56E+OO 2.71E+OO 4.20E+OO 4.97E+OO 8.00E+OO 2.32E+01 Households who farm 758000 48 47.79 2.41E+OO 4.26E-01 1.35E-01 3.30E-01 4.67E-01 7.85E-01 1.55E+OO 2.91E+OO 4.71E+OO 7.02E+OO 2.32E+01 2.32E+01
Intake data not provided for for which there were less _than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd = weighted number of consumers: Ne unwgtd = unweighted number of consumers in surVey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-23. Consumer Only Intake of Home Caught Fish (g/kg-day) -All Regions Combined Population. Ne Ne % Grouo watd unwatd Consumina Mean SE P1 PS P10 P25 P50 P75 P90 P95 P99
P100 Total 3914000 239 2.08 2.07E+OO 2.38E-01 8.16E-02 9.11E-02 1.95E-01 2.28E-01 4.31E-01 9.97E-01 2.17E+OO 4.68E+OO 7.83E+OO 1.55E+01 Age 01-02 82000 6 1.44 . . . . . . . . . . . . 03-05 142000 11 1.75 . . . . . . . . . . . . . 06-11 382000 29 2.29 2.78E+OO 8.40E-01 1.60E-01 1.60E-01 1.84E-01 2.28E-01 5.47E-01 1.03E+OO 3.67E+OO 7.05E+OO 7.85E+OO 2.53E+01 12-19 346000 21 1.69 1.52E+OO 4.07E-01 1.95E-01 1.95E-01 1.95E-01 1.95E-01 3.11E-01 9.84E-01 1.79E+OO 4.68E+OO 6.67E+OO 8.44E+OO 20-39 962000 59 1.56 1.91E+OO 3.34E-01 8.16E-02 8.16E-02 9.11E-02 1.18E-01 4.43E-01 1.06E+OO 2.18E+OO 4.46E+OO 9.57E+OO 1.30E+01 40.09 1524000 86 2.69 1.79E+OO 2.56E-01 9.47E,02 9.47E-02 2.10E-01 2.75E-01 3.45E-01 9.85E-01 "1.99E+OO 4.43E+OO 6.56E+OO 1.08E+01 70+ 450000 24 2.83 1.22E+OO 2.30E-01 9.88E-02 9.88E-02 2.33E-01 2.33E-01 5.68E-01 7.64E-01 1.56E+OO 3.73E+OO 3.73E+OO 5.12E+OO Season Fall 1220000 45 2.56 1.31E+OO 2.16E-01 1.84E-01 1.84E-01 1.96E-01 2.10E-01 3.18E-01 9.16E-01 1.79E+OO 2.64E+OO 3.73E+OO 6.56E+OO Spring 1112000 114 2.41 3.08E+OO 5.55E-01 9.88E-02 1.16E-01 3.08E-01 3.40E-01 5.59E-01 1.27E+OO 2.64E+OO 6.68E+OO 1.08E+01 3.73E+01 Summer 911000 29 2.00 1.88E+d0 '4.24E-01 8.16E-02 8.16E-02 9.11E-02 2.04E-01 3.01E-01 . 7.64E-01 3.19E+OO 4.43E+OO 5.65E+OO 9.57E+OO Winter 671000 51 1.38 2.05E+OO 3.68E-01 9.47E-02 9.47E-02 1.11E-01 1.60E-01 5.10E-01 1.06E+OO 2.09E+OO 5.89E+OO 7.85E+OO 1.31E+01 Urbanization Central City 999000 46 1.77 1.79E+OO 3.40E-01 9.47E-02 9.47E-02 1.60E-01 2.84E-01 6.08E-01 1.07E+OO 1.85E+OO 3.73E+OO 9.57E+OO 9.57E+OO Nonmetropolitan 1174000 94 2.61 3.15E+OO 5.74E-01 9.88E-02 1.16E-01 3.10E-01 3.62E-01 5.68E-01 1.88E+OO 3.86E+OO 6.52E+OO 7.83E+OO 3.73E+01 Suburban 1741000 99 2.01 1.50E+OO 2.30E-01 8.16E-02 8.16E-02 1.84E-01 2.01E-01 2.86E-01 5.87E-01 1.38E+OO 4.37E+OO 7.05E+OO 1.08E+01 Race Black 593000 41 2.73 1.81E+OO. 3.74E-01 1.84E-01 1.84E-01 2.01E-01 2.86E-01 3.18E-01 9.84E-01 2.17E+OO 4.68E+OO 9.57E+OO 9.57E+OO White 3228000 188 2.05 2.07E+OO 2.81E-01 8.16E-02 8.16E-02 1.60E-01 2.27E-01 3.93E-01 9.97E-01 2.16E+OO 4.99E+OO 6.68E+OO 1.61E+01 Response to Questionnaire Households who fish 3553000 220 9*_94 2.22E+OO 2.58E-01 8.16E-02 8.16E-02 1.84E-01 2.27E-01 4.66E-01 . 1.09E+OO 2.23E+OO 5.61E+OO 7.85E+OO 1.61E+01
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE= standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd = unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-24. Consumer Only Intake of Home Cauaht Fish (a/ka-davl -Northeast Population Ne Ne % Grouo watd unwotd Consumina Mean SE P1 P5 P10 P25 P50 P75 P90 P95 pgg P100 Total 334000 12 0.81 . . . . . . . . . . . . Season Fall 135000 4 1.44 . . . . . . . . . . . . Spring 14000 2 0.13 . . . . . . . . . . . . Summer 132000 3 1.40 . . . . . . . . . . . . Winter 53000 3 0.45 . . . . . . . . . . . . Urbanization Central City 0 Nonmetropolitan 42000 4 0.76 . . . . . . . . . . . Suburban 292000 8 1.12 . . . . . . . . Response to Questionnaire Households who fish 334000 12 5.61 . . . . . . . . . . .
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error p = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-25. Consumer Only Intake of Home Cauaht Fish (gll<a-day) -Midwest Population Ne Ne % Graue watd unwatd Consumina Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 1113000 71 2.40 2.13E+OO 4.19E-01 8.16E-02 8.16E-02 1.96E-01 2.27E-01 .4.71E-01 1.03E+OO 1.95E+OO 6.10E+OO 6.56E+OO 1.61E+01 Season Fall 362000 13 2.51 . . . . . . . . . . . Spring 224000 27 2.10 3.45E+OO 1.22E+OO 1.16E-01 1.16E-01 1.18E-01 3.10E-01 4.87E-01 8.21E-01 1.67E+OO 1.55E+01 1.61E+01 2.53E+01 Summer 264000 8 2.58 . . . . . . . . . . . . Winter 263000 23 2.37 2.38E+OO 5.33E-01 5.10E-01 5.10E-01 5.10E-01 5.48E-01 1.03E+OO 1.56E+OO 2.13E+OO 5.89E+OO 6.10E+OO 1.31E+01 Urbanization Central City 190000 9 1.09 . . . . . . . . . . . Nonmetropolitan 501000 40 3.50 3.42E+OO 7.17E-01 1.16E-01 1.16E-01 3.30E-01 4.66E-01 5.33E-01 1.88E+OO 5.65E+OO 6.56E+OO 1.31E+01 2.53E+01 Suburban 422000 22 2.87 9.09E-01 1.81E-01 8.16E-02 8.16E-02 8.16E-02 1.96E-01 3.01E-01 5.48E-01 1.28E+OO 2.09E+OO 2.7BE+OO 3.73E+OO Response to Questionnaire Households who fish 956000 60 7.57 2.35E+OO 4.85E-01 8.16E-02 8.16E-02 1.18E-01 2.27E-01 4.66E-01 1.12E+OO 2.16E+OO 6.52E+OO 6.56E+OO 2.53E+01
Intake data not provided far subpopulations far which there were less than 20 observations NOTE: SE= standard error P = percentile of the distribution Ne wgtd = weighted number of consumers; Ne unwgtd = unweighted number of consumers in survey. Source: Based an EPA's analyses of the 1987-88 NFCS Table 13-26. Consumer Onlv Intake of Home Cauqht Fish (q/kq-dav) -South Population Ne Ne % Grouo watd unwatd Consumina Mean SE P1 PS P10 P25 P50 P75 P90 P95 P99 P100 Total 1440000 101 2.24 2.74E+OO 4.76E-01 9.47E-02 9.47E-02 2.04E-01 2.86E-01 5.07E-01 1.48E+OO 3.37E+OO 5.61E+OO 8.44E+OO 3.73E+01 Season Fall 274000 11 2.08 . . . . . . . . . . . Spring 538000 58 3.20 4.00E+OO 9.42E-01 3.08E-01 3.08E-01 3.87E-01 4.46E-01 8.74E-01 1.94E+OO 3.71E+OO 8.33E+OO 1.30E+01 4.52E+01 Summer 376000 14 2.12 . . . . . . . . . . . . Winter 252000 18 1.52 . . . . . . . . . . . Urbanization Central City 281000 16 1.63 . . . . . . . . . . . Nonmetropolitan 550000 41 2.88 3.33E+OO 1.06E+OO 2.85E-01 2.85E-01 3.38E-01 5.07E-01 1.12E+OO 1.94E+OO 3.19E+OO 4.43E+OO 6.67E+OO 4.52E+01 Suburban 609000 44 2.18 2.73E+OO 4.98E-01 2.04E-01 2.04E-01 2.75E-01 2.86E-01 4.26E-01 1.08E+OO 4.37E+OO 8.33E+OO 1.04E+01 1.30E+01 Response to Questionnaire Households who fish 1280000 95 9.42 3.00E+OO 5.14E-01 9.47E-02 9.47E-02 2.04E-01 2.80E-01 7.06E-01 1.93E+OO 3.67E+OO 6.68E+OO 8.44E+OO 3.73E+01
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standrad error P = percentile of the distribution Ne wgtd =weighted number of consumers: Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-27. Consumer Only Intake of Home Caught Fish (g/kg-day) -West Population Ne Ne % Grouo watd unwatd Consumina Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 1027000 55 2.85 1.57E+OO 2.72E-01 9.88E-02 1.60E-01 2.01E-01 2.38E-01 4.43E-01 8.38E-01 1._79E+OO 3.73E+OO 5.67E+OO 9.57E+OO Season Fall 449000 17 4.20 . . . . . . . . . . . . Spring 336000 27 4.12 1.35E+OO 2.94E-01 9.88E-02 9.88E-02 2.38E-01 3.27E-01 4.43E-01 6.08E-01 1.68E+OO 4.68E+OO 5.61E+OO 5.67E+OO Summer 139000 4 1.74 . . . . . . . . . . . Winter 103000 7 1.12 . . . . . . . . . . . . Urbanization Central City 528000 21 4.38 2.03E+OO 5.25E-01 3.27E-01 3.27E-01 4.33E-01 5.29E-01 7.12E-01 1.45E+OO 1.85E+OO 3.73E+OO 9.57E+OO 9.57E+OO Nonmetropolitan 81000 9 1.33 . . . . . . . . . . . Suburban 418000 25 2.33 1.09E+OO 2.49E-01 1.84E-01 1.84E-01 2.01E-01 2.10E-01 3.08E-01 5.87E-01 1.21E+OO 2.90E+OO 4.68E+OO 5.61E+OO Response to Questionnaire Households who fish 983000 53 12.99 1.63E+OO 2.81E-01 9.88E-02 1.60E-01 2.01E-01 2.18E-01 5.47E-01 9.64E-01 1.79E+OO 3.73E+OO 5.67E+OO 9.57E+OO
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE ; standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-28. Consumer Onlv Intake of Home Produced Dairv (a/ka-dav) -All Reoions Population Ne Ne % Grouo watd unwatd Consumina Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 1409000 89 0.75 1.40E+01 1.62E+OO 1.80E-01 4.46E-01 5.08E-01 3.18E+OO 1.02E+01 1.95E+01 3.42E+01 4.40E+01 7.26E+01 1.11E+02 Age 01-02 79000 6 1.39 . . . . . . . . . . . . 03-05 57000 5 0.70 . . . . . . . . . . . 06-11 264000 16 1.58 . . . . . . . . . . . 12-19 84000 5 0.41 . . . . . . . . . . . 20-39 612000 36 0.99 7.41E+OO 1.02E+OO 2.05E-01 3.96E-01 4.46E-01 1.89E+OO 6.46E+OO .1.21E+01 1.54E+01 1.95E+01 2.30E+01 2.30E+01 40-69 216000 16 0.38 . . . . * . . . . * . . 70 + 77000 3 0.48 . . . . . . * . . . . . Seasons Fall 211000 7 0.44 . . . . . . . . . . . Spring 253000 27 0.55 1.78E+01 4.27E+OO 6.28E-01 6.54E-01 6.72E-01 5.06E+OO 1.22E+01 1.95E+01 5.09E+01 8.01E+01 1.11E+02 1.11E+02 Summer 549000 22 1.21 1.53E+01 2.73E+OO 4.46E-01 4.46E-01 5.08E-01 5.36E+OO 1.06E+01 2.51E+01 3.49E+01 3.67E+01 4.68E+01 4.68E+01 Winter 396000 33 0.81 8.08E+OO 1.99E+OO 1.80E-01 2.05E-01 2.80E-01 7.36E-01 5.47E+OO 1.15E+01 1.98E+01 2.04E+01 7.26E+01 7.26E+01 Urbanizations Central City 115000 7 0.20 . . . . . . . . . . Nonmetropolitan 988000 59 2.19 1.68E+01 2.10E+OO 4.79E-01 9.58E-01 1.89E+OO 6.74E+OO 1.08E+01 2.04E+01 3.49E+01 4.40E+01 8.01E+01 1.11E+02 Suburban 306000 23 0.35 9.86E+OO 2.38E+OO 3.96E-01 3.96E-01 4.46E-01 5.71E-01 5.36E+OO 1.31E+01 2.81E+01 2.89E+01 5.09E+01 5.09E+01 Race Black 0 0 0.00 White 1382000 86 0.88 1.43E+01 1.65E+OO 1.80E-01 4.46E-01 5.08E-01 3.82E+OO 1.03E+01 1.95E+01 3.42E+01 4.40E+01 8.01E+01 1.11E+02 Response to Questionnaire Households who raise animals 1228000 80 12.16 1.59E+01 1.73E+OO 1.80E-01 3.96E-01 1.89E+OO 6.13E+OO 1.08E+01 1.96E+01 3.49E+01 4.40E+01 8.01E+01 1.11E+02 Households who farm 1020000 63 13.92 1.71E+01 1.99E+OO 3.96E-01 7.36E-01 3.18E+OO 9.06E+OO 1.21E+01 2.D4E+D1 3.49E+01 4.40E+D1 8.D1E+01 1.11E+02
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS

. Table 13-29. Consumer Only Intake of Home Produced Dairy (g/kg-day)-Northeast Population Ne Ne % Graue wotd unwatd Consumina Mean SE P1 P5 P10 P25 P50 P75 P90 P95 . P99 P100 Total 312000 16 0.76 * . . . * * * * . . . . Seasons Fall 48000 2 0.51 . . . . * * . . . * . . Spring 36000 4 0.34 . . . . . . . . . . Summer 116000 4 1.23 . . . . . . . . . . . . Winter 112000 6 0.95 . . . . . . . . . . . . Urbanizations Central City 0 0 0.00 Non metropolitan 240000 10 4.35 . . . . * . . . . . . . Suburban 72000 6 0.28 . . . . * . . . . . . . Response to Questionnaire Households who raise animals 312000 16 26.49 . . . . . . . . . . . Households who farm 312000 16 37.59 . . . . . . . . . . . .

Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P. = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd = unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-30. Consumer Onlv Intake of Home Produced Dairv {a/ka-dav\ -Midwest Population Ne Ne % Graue wold unwatd Consumina Mean SE P1 PS P10 P25 PSO P75 P90 P95 P99 P100 Total 594000 36 1.28 1.86E+01 3.15E+OO 4.46E-01 4.46E-01 1.97E+OO 8.27E+OO 1.24E+01 2.30E+01 4.40E+01 4.68E+01 1.11E+02 1.11E+02 Seasons Fall 163000 5 1.13 . . . . . . . . . . . Spring 94000 12 0.88 . . . . . . . . . . . . Summer 252000 11 2.46 . . . . . . . . . . . . Winter 85000 8 0.76 . . . . . . . . . . . . Urbanizations Central City 43000 1 0.25 . . . . . . . . . . . Nonmetropolitan 463000 31 3.24 2.33E+01 3.40E+OO 4.25E+OO 8.27E+OO 9.06E+OO 1.21E+01 1.60E+01 3.14E+01 4.40E+01 4.68E+01 1.11E+02 1.11E+02 Suburban 88000 4 0.60 . . . . . . . . . . . Response to Questionnaire Households who raise animals 490000 32 13.09 2.23E+01 3.33E+OO 4.25E+OO 5.36E+OO 8.27E+OO 1.08E+01 1.54E+01 3.14E+01 4.40E+01 4.68E+01 1.11E+02 1.11E+02 Households who farm 490000 32 18.28 2.23E+01 3.33E+OO 4.25E+OO 5.36E+OO 8.27E+OO 1.08E+01 1.54E+01 3.14E+01 4.40E+01 4.68E+01 1.11E+02 1.11E+02
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-31. Consumer Onlv Intake of Home Produced Dairv la/ka-davl -South Population Ne Ne % Groun watd unwntd Consuminn Mean SE P1 P5 P10 P25 P50 P75 P90 P95 pgg P100 Total 242000 17 0.38 . . . . . . . . . * . . Seasons Fall 0 0 0.00 Spring 27000 3 0.16 . . . . . . . . . . . . Summer 131000 5 0.74 . . . . . . . . . . Winter 84000 9 0.51 . . . . . . . . . . . . Urbanizations Central City 27000 3 0.16 . . . . * . . . .
Non metropolitan 215000 14 1.13 . * . . . . . . .. . Suburban 0 0 0.00 Response to Questionnaire Households who raise animals 215000 14 8.26 . * . * . . . . Households who farm 148000 8 6.63 . . . . . . . .
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE= standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-32. Consumer Onlv Intake oi Home Produced Dairy (q/kq-day) -West Population Ne Ne % Grouo watd unwatd Consumina Mean SE P1 PS P10 P25 PSO P75 P90 P95 P99 P100 Total 261000 20 0.72 1.00E+01 2.75E+OO 1.80E-01 1.80E-01 2.0SE-01 5.08E-01 6.10E+OO 1.33E+01 2.81E+01 2.89E+01 5.09E+01 5.09E+01 Seasons Fall 0 0 0.00 Spring 96000 8 1.18 . . . . . . . . . . . . Summer 50000 2 0.63 . . . . . . . . . Wnter 115000 10 1.25 . . . . . . . . . . ** Urbanizations Central City 45000 3 0.37 . . . . . . . . . . . Nonmetropolitan 70000 4 1.15 . . . . . . . . . . Suburban 146000 13 0.81 . . . . . . . . . . . . Response to Questionnaire Households who raise animals 211000 18 8.20 . . . . . . . . . . Households who farm 70000 7 4.41 . . . . . . . . . . .
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd::: weighted number of consumers; Ne unwgtd::: unweighted number of consumers in survey. Source: Based on EPA's analvses of the 1987-88 NFCS Table 13-33. Seasonally Adjusted Consumer Only Homegrown Intake (g/kg-day) Population Percent P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Group Consuming Total Vegetables Northeast 16.50 1.16E-03 1.59E-02
3.56E-02 1.99E-01 4.55E-01 1.37E+OO 3.32E+OO 5.70E+OO 8.78E+OO 1.01 E+01 Midwest 33.25 3.69E-03 4.11 E-02 8.26E-02 2.91 E-01 8.11E-01 1.96E+OO 4.40E+OO 7.41 E+OO 1.31 E+OO 2.01 E+01 South 24.00 4.78E-03 3.24E-02 5.58E-02 2.05E-01 6.10E-01 1.86E+OO 3.95E+OO 5.63E+OO 1.2bE+01 1.62E+01 West 23.75 1.80E-03 1.91 E-02 3.83E-02 1.14E-01 4.92E-01 1.46E+OO 2.99E+OO 5.04E+OO 8.91E+OO 1.12E+01 All Regions 24.60 5.00E-03 2.90E-02 5.90E-02 2.19E-01 6.38E-01 1.80E+OO 4.00E+OO 6.08E+OO 1.17E+01 2.01 E+01 Total Fruit Northeast 3.50 3.96E-03 1.97E-02 4.76E-02 1.73E-01 3.61 E-01 6.55E-01 1.48E+OO 3.00E+OO 5.1 OE+OO 5.63E+OO Midwest 12.75 1.22E-03 7.01E-03 1.46E-02 1.36E-01 7.87E-01 2.98E+OO 5.79E+OO 9.52E+OO 2.22E+01 2.71 E+01 South 8.00 6.13E-03 3.23E-02 1.09E-01 3.84E-01 9.47E-01 2.10E+OO 6.70+00 1.02E+01 1.49E+01 1.64E+01 West 17.75 5.50E-04 5.66E-02 8.82E-02 2.87E-01 6.BBE-01 1.81 E+OO 4.75E+OO 8.54E+OO 1.45E+01 1.84E+01 All Regions 10.10 2.00E-03 1.90E-02 6.20E-02 2.50E-01 7.52E-,01 2.35E+OO 5.61 E+OO 9.12E+OO 1.76E+01 2.71 E+01 Total Meat Northeast 6.25 3.78E-03 3.01E-02 7.94E-02 1.25E-01 2.11 E-01 7.00E-01 1.56E+OO 1.91 E+OO 4.09E+OO 4.BOE+OO Midwest 9.25 1.77E-03 3.68E-02 2.21 E-01 5.25E-02 1.61 E+OO 3.41 E+OO 5.25E+OO 7.45E+OO 1.19E+01 1.36E+01 South 5.75 6.12E-03 2.88E-02 5.02E-02 1.86E-01 5.30E-01 1.84E+OO 3.78E+OO 4.95E+OO 8.45E+OO 9.45E+OO West 9.50 7.24E-04 2.83E-02 9.56E-02 2.35E-01 5.64E-01 1.30E+OO 2.29E+OO 3.38E+OO 7.20E+OO 9.10E+OO All Regions 7.40 3.20E-03 3.90E-02 9.20E-02 2.20E-01 6.55E-01 1.96E+OO 4.05E+OO 5.17E+OO 9.40E+OO 1.36E+01 Table 13-34. Consumer Only Intake of Homeqrown Apples (q/kq-day) Population Ne Ne % Group watd unwatd Consumina M8an SE P1 P5 P10 P25 P50 P75 P90 P95 pgg P100 Total 5306000 272 2.82 1.19E+OO 7.58E-02 8.34E-02 2.30E-01 2.84E-01 4.50E-01 8.17E-01 1.47E+OO 2.38E+OO 3.40E+OO 5.42E+OO 1.01E+01 Age 01-02 199000 12 3.49 * * * . . * . . * . . . 291000 16 3.59 * . . . * * . . . * . 06-11 402000 25 2.41 1.28E+OO 1.88E-01 .4.72E-01 4.72E-01 5.63E-01 7.40E-01 9.56E-01 1.29E+OO 2.98E+OO 4.00E+OO 4.00E+OO 4.00E+OO 12-19 296000 12 1.44 . * . * . * . . . . . . 20-39 1268000 61 2.06 7.95E-01 1.07E-01 1.85E-01 2.30E-01 2.56E-01 3.04E-01 6.02E-01 9.22E-01 1.55E+OO 1.97E+OO 5.42E+OO 5.42E+OO 40-69 1719000 90 3.03 9.61E-01 1.37E-01 5.57E-02 8.94E-02 2.55E-01 3.98E-01 6.48E-01 1.08E+OO 1.59E+OO 2.38E+OO 9.83E+OO 9.83E+OO 70+ 1061000 52 6.68 1.45E+OO 1.41E-01 1.99E-01 2.60E-01 4.46E-01 6.27E-01 1.18E+OO 1.82E+OO 3.40E+OO 3.62E+OO 4.20E+OO 4.20E+OO Season Fall 1707000 60 3.58 1.28E+OO 1.24E-01 2.56E-01 2.95E-01 3.20E-01 5.83E-01 1.03E+OO 1.66E+OO 2.69E+OO 3.40E+OO 4.25E+OO 4.25E+OO Spring 639000 74 1.38 9.SOE-01 1.14E-01 1.94E-01 2.38E-01 2.84E-01 3.76E-01 5.67E-01 1.10E+OO 2.00E+OO 2.78E+OO 5.87E+OO 5.87E+OO Summer 1935000 68 4.25 1.12E+OO 1.69E-01 5.57E-02 8.94E-02 1.86E-01 3.98E-01 6.92E-01 1.41E+OO 2.29E+OO 2.98E+OO 9.83E+OO 9.83E+OO Winter 1025000 70 2.10 1.30E+OO 1.78E-01 1.85E-01 2.30E-01 3.23E-01 5.71E-01 8.81E-01 1.59E+OO 2.75E+OO 3.40E+OO 1.01E+01 1.01E+01 Urbanization Central City 912000 30 1.62 1.24E+OO 2.60E-01 2.31E-01 2.56E-01 3.92E-01 5.10E-01 9.17E-01 1.59E+OO 2.19E+OO 2.26E+OO 1.01E+01 1.01E+01 Nonmetropolitan 2118000 122 4.70 1.27E+OO 1.26E-01 5.57E-02 1.18E-01 2.49E-01 4.11E-01 9.00E-01 1.55E+OO 2.92E+OO 3.48E+OO 9.83E+OO 9.83E+OO Suburban 2276000 120 2.63 1.09E+OO 9.16E-02 1.86E-01 2.37E-01 2.91E-01 4.37E-01 7.74E-01 1.29E+OO 2.29E+OO 3.40E+OO 5.42E+OO 5.42E+OO Race Black 84000 4 0.39 * . . . . . . * . . *
White 5222000 268 3.31 1.18E+OO 7.67E-02 8.34E-02 2.30E-01 2.79E-01 4.48E-01 7.98E-01 1.41E+OO 2.38E+OO 3.40E+OO 5.42E+OO 1.01E+01 Region Midwest 2044000 123 4.41 1.38E+OO 1.45E-01 2.16E-01 2.85E-01 3.04E-01 5.20E-01 9.23E-01 1.61E+OO 2.69E+OO 3.40E+OO 9.83E+OO 1.01E+01 Northeast 442000 18 1.07 . * . * . . . . . *
South 1310000 65 2.04 1.10E+OO 1.07E-01 1.99E-01 2.38E-01 3.01E-01 4.39E-01 9.17E-01 1.38E+OO 1.90E+OO 2.98E+OO 4.00E+OO 4.91E+OO West 1510000 66 4.19 1.20E+OO 1.29E-01 5.57E-02 1.86E-01 2.64E-01 4.72E-01 7.89E-01 1.82E+OO 2.75E+OO 3.62E+OO 4.25E+OO 4.25E+OO Response to Questionnaire Households who garden 4707000 246 6.91 1.21E+OO 8.22E-02 1.27E-01 2.49E-01 2.95E-01 4.?0E-01 8.17E-01 1.47E+OO 2.38E+OO 3.40E+OO 5.87E+OO 1.01E+01 Households who farm 1299000 68 17.72 1.39E+OO 1.31E-01 5.57E-02 3.57E-01 5.36E-01 7.03E-01 9.56E-01 1.58E+OO 2.99E+oo* 4.00E+OO 4.91E+OO 5.87E+OO
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distibution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-35. Consumer Onlv Intake of Homearown Asoaraaus la/kn-dav\ Population Ne Ne % Grouo watd unwatd Consumina Mean SE P1 PS P10 P25 P50 P75 P90 P95 P99 P100 Total 763000 66 0.41 5.59E-01 5.12E-02 1.00E-01 1.41E-01 1.91E-01 2.75E-01 4.00E-01 7.07E-01 1.12E+OO 1.63E+OO 1.97E+OO 1.97E+OO Age 01-02 8000 1 0.14 . . . . . . . . . . 03-05 25000 3 0.31 . . . . . . . . . . 06-11 31000 3 0.19 . . . . . . . .. . . . . 12-19 70000 5 0.34 . . . . . . . . . . 20-39 144000 11 0.23 . . . . . . . . . . 40-69 430000 38 0.76 4.65E-01 5.38E-02 1.10E-01 1.13E-01 1.81E-01 2.34E-.01 4.00E-01 5.96E-01 8.84E-01 1.24E+OO 1.75E+OO 1.75E+OO 70 + 55000 5 0.35 . . . . . . . . Season Fall 62000 2 0.13 . . . . . . . .. . . . Spring 608000 59 1.32 6.12E-01 5.75E-02 1.00E-01 1.57E-01 1.91E-01 2.98E-01 4.46E-01 8.8/.4E-01 1.18E+OO 1.63E+OO 1.97E+OO 1.97E+OO Summer 0 0 0.00 Winter 93000 5 0.19 . . . . . . . . . . . . -Urbanization Central City 190000 9 0.34 . . . . . . . . . . Nonmetropolitan 215000 27 0.48 7.59E-01 1.19E-01 1.00E-01 1.13E-01 1.41E-01 2.30E-01 5.43E-01 1.24E+OO 1.75E+OO 1.92E+OO 1.97E+OO 1.97E+OO Suburban 358000 30 0.41 4.27E-01 4.05E-02 1.10E-01 1.69E-01 1.81E-01 2.75E-01 3.65E-01 5.79E-01 7.01E-01 9.31E-01 1.12E+OO 1.12E+OO Race Black 0 0 0.00 White 763000 66 0.48 5.59E-01 5.12E-02 1.00E-01 1.41E-01 1.91E-01 2.75E-01 4.00E-01 7.07E-01 1.12E+OO 1.63E+OO 1.97E+OO 1.97E+OO Region Midwest 368000 33 0.79 4.78E-01 6.49E-02 1.00E-01 1.10E-01 1.41E-01 2.28E-01 4.00E-01 6.14E-01 9.31E-01 1.12E+OO 1.97E+OO 1.97E+OO Northeast 270000 20 0.66 7.17E-01 9.99E-02 1.81E-01 2.34E-01 2.34E-01 3.65E-01 5.96E-01 9.29E-01 1.24E+OO 1.63E+OO 1.92E+OO 1.92E+OO South 95000 9 0.15 . . . . . * . . . . . . West 30000 4 0.08 . . . . . . . . . . . Response to Questionnaire Households who garden 669000 59 0.98 5.33E-01 5.50E-02 1.00E-01 1.41E-01 1.81E-01 2.75E-01 4.00E-01 6.99E-01 1.12E+OO 1.63E+OO 1.97E+OO 1.97E+OO Households who farm 157000 16 2.14 . . . . . . . . . . .
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd = weighted number of consumers: Ne unwgtd = unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-36. Consumer Onlv Intake of Home Produced Beef la/ka-davl Population Ne Ne % Graue watd unwntd Consumina Mean SE P1 PS P10 P25 P50 P75 P90 P95 P99 P100 Total 4958000 304 2.64 2.45E+OO 1.49E-01 1.83E-01 3.74E-01 4.65E-01 8.78E-01 1.61E+OO 3.07E+OO 5.29E+OO 7.24E+OO 1.33E+01 1.94E+01 Age 01-02 110000 8 1.93 . . . . . . . . . . . . 03-05 234000 13 2.89 . . . . . . . . . . . . 06-11 695000 38 4.16 3.77E+OO 5.94E-01 3.54E-01 6.63E-01 7.53E-01 1.32E+OO 2.11E+OO 4.43E+OO 1.14E+01 1.25E+01 1.33E+01 1.33E+01 12-19 656000 41 3.20 1.72E+OO 1.63E-01 3.78E-01 4.78E-01 5.13E-01 8.96E-01 1.51E+OO 2.44E+OO 3.53E+OO 3.57E+OO 4.28E+OO 4.28E+OO 20-39 1495000 83 2.43 2.06E+OO 2.00E-01 2.69E-01 3.52E-01 3.94E-01 6.80E-01 1.59E+OO 2.73E+OO 4.88E+OO 6.50E+OO 8.26E+OO 8.26E+OO 40-69 1490000 105 2.63 1.84E+OO 1.41E-01 1.83E-01 3.61E-01 4.55E-01 _8.33E-01 1.52E+OO 2.38E+OO 4.10E+OO 5.39E+OO 5.90E+OO 5.90E+OO 70 + 188000 11 1.18 . . . . . . . . . . . . Season Fall 1404000 55 2.95 1.55E+OO 1.74E-01 1.83E-01 3.52E-01 3.61E-01 5.17E-01 1.33E+OO 2.01E+OO 2.86E+OO 3.90E+OO 7.24E+OO 7.24E+OO Spring 911000 108 1.97 2.32E+OO 1.63E-01 2.70E-01 3.90E-01 5.10E-01 1.04E+OO 1.96E+OO 3.29E+OO 4.22E+OO 5.23E+OO 8.62E+OO 9.28E+OO Summer 1755000 69 3.86 3.48E+OO 4.12E-01 1.02E-01 6.08E-01 7.45E-01 1.02E+OO 2.44E+OO . 4.43E+OO 7.51E+OO 1.14E+01 1.87E+01 1.87E+01 Winter 888000 72 1.82 1.95E+OO 2.75E-01 3.93E-02 3.75E-01 3.94E-01 6.74E-01 1.33E+OO 2.14E+OO 4.23E+OO 5.39E+OO 1.94E+01 1.94E+01 Urbanization Central City 100000 5 0.18 . . . . . . . . . . . . Nonmetropolitan 3070000 194 6.82 2.80E+OO 2.18E-01 1.83E-01 3.77E-01 4.99E-01 8.64E-01 1.81E+OO 3.57E+OO 6.03E+OO 8.44E+_oo 1.87E+01 1.94E+01 Suburban 1788000 105 2.07 1.93E+OO 1.SOE-01 2.67E-01 3.75E-01 4.16E-01 9.07E-01 1.52E+OO 2.44E+OO 4.06E+OO 5.10E+OO 7.51E+OO 9.28E+OO Race Black 0 0 0.00 Wllite 4950000 303 3.14 2.45E+OO 1.SOE-01 1.83E-01 3.74E-01 4.65E-01 8.78E-01 1.61E+OO 3.07E+OO 5.29E+OO 7.24E+OO 1.33E+01 1.94E+01 Region Midwest 2261000 161 4.87 2.83E+OO 2.31E-01 1.83E-01 3.54E-01 4.16E-01 8.47E-01 2.01E+Ob 3.66E+OO 5.90E+OO 8.39E+OO 1.87E+01 1.87E+01 Northeast 586000 25 1.42 1.44E+OO 2.13E-01 3.52E-01 3.52E-01 4.73E-01 7.42E-01 1.06E+OO 1.68E+OO 2.62E+OO 2.62E+OO 6.03E+OO 6.03E+OO South 1042000 61 1.62 2.45E+OO 3.46E-01 1.02E-01 3.90E-01 5.84E-01 8.16E-01 1.59E+OO 2.41E+OO 6.36E+OO 7.24E+OO 1.33E+01 1.33E+01 West 1069000 57 2.96 2.20E+OO 2.83E-01 3.13E-01 3.80E-01 5.56E-01 1.04E+OO 1.60E+.OO 2.86E+OO 4.06E+OO 4.42E+OO 7.51E+OO 1.94E+01 Response to Questionnaire Households who raise animals 3699000 239 36.63 2.66E+OO 1.60E-01 1.83E-01 3.88E-01 6.63E-01 1.04E+OO 1.83E+OO 3.48E+OO 5.39E+OO 7.51E+OO 1.25E+01 1.94E+01 Households who farm 2850000 182 38.89 2.63E+OO 1.96E-01 2.70E-01 3.94E-01 5.85E-01 8.96E-01 1.64E+OO 3.25E+OO 5.39E+OO 7.51E+OO 1.13E+01 1.94E+01
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-37. Consumer Onlv Intake of Homenrown Beets ln/kn-dav\ Population Ne Ne % Grouo wold unwatd Consumina Mean SE P1 PS P10 P25 P50 P75 P90 P95 P99 P100 Total 2214000 125 1.18 5.12E-01 4.96E-02 3.21E-02 7.37E-02 1.09E-01 1.88E-01 3.97E-01 5.87E-01 1.03E+OO 1.36E+OO 3.69E+OO 4.08E+OO Age 01-02 27000 2 0.47 . . . . . . . . . . . . 03-05 51000 4 0.63 . . . . . . . . . . . . 06-11 167000 10 1.00 . . . . . . . . . . . . 12-19 227000 13 1.11 . . . . . . . . . . . . 20-39 383000 22 0.62 3.81E-01 6.26E-02 7.57E-02 7.57E-02 1.22E-01 1.43E-01 2.85E-01 5.56E-01 9.99E-01 9.99E-01 1.12E+OO 1.12E+OO 40-69 951000 51 1.68 4.28E-01 4.34E-02 5.00E-02 7.31E-02 7.46E-02 2.0SE-01 3.97E-01 5.49E-01 9.25E-01 1.15E+OO 1.40E+OO 1.40E+OO 70+ 408000 23 2.57 5.80E-01 8.80E-02 3.21E-02 3.21E-02 4.76E-02 2.71E-01 4.49E-01 9.09E-01 1.36E+OO 1.36E+OO 1.59E+OO 1.59E+OO Season Fall 562000 21 1.18 5.45E-01 9.36E-02 3.21E-02 4.76E-02 5.00E-02 2.57E-01 3.56E-01 9.49E-01 1.36E+OO 1.36E+OO 1.40E+OO 1.40E+OO Spring 558000 55 1.21 4.70E-01 8.98E-02 7.46E-02 8.06E-02 1.096-01 1.43E-01 2.73E-01 4.47E-01 8.73E-01 1.59E+OO 4.08E+OO 4.08E+OO Summer 676000 22 1.49 3.85E-01 4.54E-02 7.57E-02 1.20E-01 1.22E-01 1.84E-01 3.97E-01 5.49E-01 6.24E-01 9.09E-01 9.09E-01 9.09E-01 Winter 418000 27 0.86 7.30E-01 1.54E-01 7.31E-02 7.31E-02 7.37E-02 2.80E-01 5.20E-01 8.28E-01 1.13E+OO 2.32E+OO 3.69E+OO 3.69E+OO Urbanization Central City 651000 27 1.16 5.18E-01 1.15E-01 1.11E-01 1.35E-01 1.83E-01 2.57E-01 4.01E-01 5.49E-01 9.09E-01 1.12E+OO 3.69E+OO 3.69E+OO Nonmetropolitan 758000 '51 1.68 5.77E-01 9.06E-02 5.00E-02 7.31E-02 7.37E-02 1.80E-01 3.86E-01 6.61E-01 1.36E+OO 1.40E+OO 4.08E+OO 4.08E+OO Suburban 805000 47 0.93 4.45E-01 5.77E-02 3.21E-02 4.76E-02 8.06E-02 1.43E-01 3.97E-01 5.56E-01 9.25E-01 9.99E-01 2.32E+OO 2.32E+OO Race " Black 0 0 0.00 White 2186000 124 1.39 5.18E-01 4.99E-02 3.21E-02 7.46E-02 1.13E-01 2.05E-01 3.97E-01 5.87E-01 1.03E+OO 1.36E+OO 3.69E+OO 4.08E+OO *Region Midwest 885000 53 1.91 6.30E-01 7.93E-02 5.00E-02 1.13E-01 1.83E-01 3.15E-01 4.54E-01 9.09E-01 1.15E+OO 1.36E+OO 3.69E+OO 3.69E+OO Northeast 230000 13 0.56 . . . . . . . . . . . South 545000 31 0.85 4.51E-01 1.17E-01 7.46E-02 7.57E-02 8.06E-02 1.80E-01 2.64E-01 4.84E-01 6.61E-01 9.44E-01 4.08E+OO 4.08E+OO West 554000 28 1.54 3.96E-01 7.75E-02 3.21E-02 4.76E-02 7.31E-02 1.21E-01 2.86E-01 5.49E-01 6.24E-01 7.04E-01 2.32E+OO 2.32E+OO Response to Questionnaire Households who garden 2107000 120 3.09 5.26E-01 5.16E-02 3.21E-02 7.37E-02 9.56E-02 2.05E-01 4.01E-01 6.06E-01 1.03E+OO 1.36E+OO 3.69E+OO 4.08E+OO Households who farm 229000 11 3.12 . . . . . . . . . . . .
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd = unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-38. Consumer Onlv Intake of Homeorown Broccoli (o/ko-davl Population Ne Ne % Graue watd unwotd Consumina Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 1745000 80 0.93 4.20E-01 4.75E-02 7.61E-02 8.24E-02 1.56E-01 1.96E-01 2.90E-01 4.59E-01 8.15E-01 9.74E-01 2.48E+OO 3.02E+OO Age 01-02 o o 0.00 03-05 13000 1 0.16 . . . . . . . . . . . . 06-11 187000 9 1.12 . . . . . . . . . . . 12-19 102000 4 0.50 . . . . . . . . . . 20-39 486000 19 0.79 . . . . . . . . . 40-69 761000 37 1.34 4.12E-01 6.50E-02 8.24E-02 1.06E-01 1.64E-01 2.22E-01 3.51E-01 4.61E-01 6.14E-01 8.15E-01 3.02E+OO 3.02E+OO 70+ 196000 10 1.23 . . . . . . . . . . Season Fall 624000 20 1.31 2.87E-01 3.70E-02 7.99E-02 7.99E-02 8.24E-02 1.75E-01 2.31E-01 3.79E-01 4.52E-01 5.29E-01 8.15E-01 8.15E-01 Spring 258000 27 0.56 5.43E-01 1.18E-01 4.50E-02 1.54E-01 1.70E-01 2.65E-01 3.31E-01 5.89E-01 1.25E+OO 2.37E+OO 3.02E+OO 3.02E+OO Summer 682000 22 1.50 5.08E-01 1.05E-01 7.61E-02 1.29E-01 1.78E-01 2.15E-01 3.99E-01 6.61E-01 8.86E-01 9.74E-01 2.48E+OO 2.48E+OO Winter 181000 11 0.37 . . . . . . . . . . Urbanization Central City 165000 5 0.29 . . . . . . . . Nonmetropolitan 647000 34 1.44 4.23E-01 4.21E-02 4.50E-02 1.29E-01 1.70E-01 2.23E-01 3.69E-01 5.89E-01 7.47E-01 8.86E-01 9.74E-01 9.74E-01 Suburban 933000 41 1.08 4.29E-01 8.26E-02 7.99E-02 8.24E-02 1.44E-01 2.13E-01 2.44E-01 4.41E-01 6.84E-01 2.37E+OO 2.48E+OO 3.02E+OO Race Black 0 o 0.00 White 1719000 79 1.09 4.22E-01 4.81E-02 7.61E-02 8.24E-02 1.56E-01 1.96E-01 2.88E-01 4.59E-01 8.15E-01 9.74E-01 2.48E+OO 3.02E+OO Region Midwest 792000 38 1.71 2.63E-01 5.86E-02 7.61E-02 7.99E-02 8.24E-02 1.75E-01 2.13E-01 2.75E-01 3.44E-01 4.03E-01 3.02E+OO 3.02E+OO Northeast 427000 19 1.04 . . . . . . . . . . South 373000 16 0.58 . . . . . . . . . . . West 153000 7 0.42 . . . . . . . . . . . . Response to Questionnaire Households who garden 1729000 78 2.54 4.22E-01 4.83E-02 7.61E-02 8.24E-02 1.64E-01 1.96E-01 2.90E-01 4.59E-01 8.15E-01 9.7.4E-01 2.48E+OO 3.02E+OO Households who farm 599000 29 8.17 4.66E-01 8.37E-02 4.50E-02 7.61E-02 1.54E-01 1.95E-01 3.10E-01 6.61E-01 8.86E-01 9.74E-01 3.02E+OO 3.02E+OO
Intake data not provided for subpopulations for which there. were less than 20 observations NOTE: SE = standard error P = percentile of the distibution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-39. Consumer Onlv Intake of Homenrown Cabbane ln/kn-davl Population Ne Ne % Grouo wntd unwntd Consuminn Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 2019000 89 1.07 1.03E+OO 1.00E-01 1.07E-01 2.03E-01 3.17E-01 4.21E-01 7.76E-01 1.33E+OO 1.97E+OO 2.35E+OO 5.43E+OO 5.43E+OO Age 01-02 14000 2 0.25 . . . . . . . . . . . 03-05 29000 1 0.36 . . . . . . . . . . . 06-11 61000 3 0.37 . . . . . . . . . . . . 12-19 203000 9 0.99 . . . . . . . . . . . 20-39 391000 16 0.63 . . . . . . . . . . . . 40-69 966000 44 1.70 1.14E+OO 1.80E-01 2.17E-01 2.22E-01 3.25E-01 4.08E-01 7.13E-01 1.41E+OO 1.82E+OO 5.29E+OO 5.43E+OO 5.43E+OO 70 + 326000 13 2.05 . . . . . . . . . . Season Fall 570000 21 1.20 1.28E+OO 3.24E-01 1.86E-01 1.86E-01 2.03E-01 3.85E-01 5.42E-01 1.49E+OO 5.29E+OO 5.43E+OO 5.43E+OO 5.43E+OO Spring 126000 15 0.27 . . . . . Summer 1142000 39 2.51 9.65E-01 9.35E-02 2.01E-01 2.22E-01 3.25E-01 5.55E-01 8.28E-01 1.24E+OO 1.79E+OO 2.35E+OO 2.77E+OO 2.77E+OO Winter 181000 14 0.37 . . . . . . . . . . Urbanization Central City 157000 5 0.28 . . . . . . . . . . . Nonmetropolitan 1079000 48 2.40 9.37E-01 8.83E-02 2.01E-01 3.17E-01 3.40E-01 4.54E-01 7.13E-01 1.33E+OO 1.79E+OO 2.35E+OO 2.77E+OO 2.77E+OO Suburban 783000 36 0.90 1.26E+OO 2.11E-01 3.20E-02 2.22E-01 3.25E-01 4.49E-01 1.05E+OO 1.37E+OO 2.17E+OO 5.29E+OO 5.43E+OO 5.43E+OO Race Black 7000 1 0.03 . . . . . . . . . . . . White 1867000 83 1.19 1.05E+OO 1.07E-01 1.07E-01 2.03E-01 2.46E-01 4.13E-01 7.88E-01 1.37E+OO 1.97E+OO 2.35E+OO 5.43E+OO 5.43E+OO Region Midwest 884000 37 1.91 7.42E-01 7.35E-02 1.07E-01 1.86E-01 2.22E-01
3.55E-01 5.95E-01 1.10E+OO 1.29E+OO 1.49E+OO 1.82E+OO 1.98E+OO Northeast 277000 11 0.67 . . . . . . . . . . . South 616000 32 0.96 1.11E+OO 1.34E-01 3.20E-02 2.01E-01 2.17E-01 4.49E-01 8.50E-01 1.79E+OO 2.17E+OO 2.35E+OO 2.77E+OO 2.77E+OO West 242000 9 0.67 . . . . . . . . . . Response to Questionnaire Households who garden 1921000 86 2.82 1.07E+OO 1.03E-01 1.07E-01 2.03E-01 3.17E-01 4.54E-01 7.88E-01 1.37E+OO 1.97E+OO 2.35E+OO 5.43E+OO 5.43E+OO Households who farm 546000 26 7 45 9 96E-01 115E-01 2 01<'-01 2 06E-01 3.51<'-01 5 87E-01 8.28E-01 1.37E+OO 1 79E+OO 2.35E+OO ?.35E+OO 2 35<'+00
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd = unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-40. Consumer Onlv intake of Homearown Carrots fa/ka-dav\ Population Ne Ne % Grouo wntd unwntd Consuminn Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 4322000 193 2.30 4.38E-01 4.29E-02 4.12E-02 6.35E-02 9.23E-02 1.79E-01 3.28E-01 5.25E-01 7.95E-01 1.08E+OO 2.21E+OO 7.79E+OO Age 01-02 51000 4 0.89 . . . . . . . . . . . . 03-05 53000 3 0.65. . . . . . . . . . . . . 06-11 299000 14 1.79 . . . . . . . . . . . . 12-19 389000 17 1.90 . . . . . . . . . . . 20-39 1043000 46 1.69 2.83E-01 3.46E-02 4.47E-02 5.02E-02 8.00E-02 1.20E-01 1.99E-01 4.09E-01 5.64E-01 7.56E-01 1.19E+OO 1.19E+OO 40-09 1848000 82 3.26 4.25E-01 3.42E-02 3.90E-02 6.74E-02 1.23E-01 2.15E-01 3.67E-01 5.50E-01 7.76E-01 1.01E+OO 1.53E+OO 2.21E.+OO 70+ 574000 24 3.61 4.44E-01 5.50E-02 7.39E-02 1.79E-01 1.96E-01 2.60E-01 3.70E-01 5.39E-01 9.64E-01 1.08E+OO 1.08E+OO 1.08E+OO Season Fall 1810000 66 3.80 4.61E-01 9.77E-02 9.09E-02 1.10E-01 1.20E-01 1.99E-01 3.08E-01 5.09E-01 7.76E-01 1.08E+OO 1.71E+OO 7.79E+OO Spring 267000 28 0.58 5.55E-01 1.01E-01 1.39E-01 1.49E-01 2.02E-01 2.16E-01 3.92E-01 6.09E-01 9.94E-01 2.11E+OO 2.94E+OO 2.94E+OO Summer 1544000 49 3.39 3.88E-01 3.95E-02 4.12E-02 5.02E-02 6.74E-02 1.64E-01 3.76E-01 5.13E-01 8.40E-01 9.64E-01 1.19E+OO 1.19E+OO Winter 701000 50 1.44 4.44E-01 7.44E-02 3.90E-02 4.34E-02 6.35E-02 1.56E-01 2.25E-01 6.40E-01 1.05E+OO 1.53E+OO 3.06E+OO 3.06E+OO Urbanization Central City 963000 29 1.71 2.82E-01 3.86E-02 3.90E-02 6.35E-02 8.00E-02 1.63E-01 2.09E-01 3.85E-01 5.25E-01 5.88E-01 *9.64E-01 9.64E-01 Nonmetropolitan 1675000 94 3.72 5.18E-01 8.98E-02 4.12E-02 5.36E-02 6.81E-02 2.00E-01 3.28E-01 5.13E-01 9.55E-01 1.19E+OO 7.79E+OO 7.79E+OO Suburban 1684000 70 1.94 4.48E-01 4.02E-02 6.74E-02 9.09E-02 1.16E-01 2.02E-01 3.77E-01 6.35E-01 7.95E-01 1.09E+OO 1.71E+OO 1.71E+OO Race Black 107000 7 0.49 . . . . . . . . . . White 3970000 178 2.52 4.13E-01 2.58E-02 4.34E-02 7.96E-02 1.11E-01 1.94E-01 3.33E-01 5.27E-01 7.76E-01 1.01E+OO 1.59E+OO 3.06E+OO Region Midwest 2001000 97 4.31 4.57E-01 3.99E-02 3.90E-02 8.00E-02 1.37E-01 2.00E-01 3.73E-01 5.39E-01 9.55E-01 1.10E+OO 2.11E+OO 3.06E+OO Northeast 735000 29 1.79 4.05E-01 8.79E-02 4.12E-02 5.36E-02 6.15E-02 9.34E-02 1.49E-01 6.35E-01 1.09E+OO 1.71E+OO 2.21E+OO 2.21E+OO South 378000 20 0.59 6.27E-01 3.60E-01 4.47E-02 4.47E-02 5.02E-02 1.49E-01 2.72E-01 4.09E-01 5.02E-01 9.94E-01 7.79E+OO 7.79E+OO West 1208000 47 3.35 3.68E-01 3.24E-02 6.74E-02 9.11E-02 1.43E-01 1.90E-01 3.33E-01 4.59E-01 7.56E-01 8.40E-01 9.64E-01 9.64E-01 Response to Questionnaire Households who garden 4054000 182 5.95 4.04E-01 2.67E-02 4.12E-02 6.81E-02 9.34E-02 1.79E-01 3.28E-01 5.09E-01 7.62E-01 1.08E+OO 1.71E+OO 3.06E+OO Households who farm 833000 40 11.37 3.60E-01 5.95E-02 9.09E-02 9.34E-02 1.10E-01 1.79E-01 2.28E-01 4.59E-01 6.19E-01 1.19E+OO 2.11E+OO 2.94E+OO
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd = unweighted number of consumers in survey. Source: Based on EPA' analyses of the 1987-88 NFCS Table 13-41. Consumer Only Intake of Homearown Corn (a/ka-dav\ Population Ne Ne % Grouo watd unwntd Consumino Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 6891000 421 3.67 8.92E-01 6.48E-02 5.15E-02 1.22E-01 1.65E-01 2.44E-01 4.80E-01 9.07E-01 1.88E+OO 3.37E+OO 7.44E+OO 9.23E+OO Age 01-02 205000 13 3.60 . . . . . . . . . . . . 03-05 313000 24 3.86 1.25E+OO 2.57E-01 3.25E-01 3.25E-01 4.00E-01 5.98E-01 1.00E+OO 1.21E+OO 1.67E+OO 5.35E+OO 5.35E+OO 5.35E+OO 06-11 689000 43 4.12 9.32E-01 1.66E-01 1.10E-01 1.19E-01 1.89E-01 2.52E-01 5.13E-01 1.08E+OO 3.13E+OO 3.37E+OO 4.52E+OO 4.52E+OO 12-19 530000 32 2.59 5.92E-01 9.56E-02 9.87E-02 1.05E-01 1.35E-01 2.12E-01 3.43E-01 7.11E-01 1.55E+OO 1.88E+OO 1.88E+OO 1.88E+OO 20-39 1913000 108 3.11 5.97E-01 6.00E-02 6.59E-02 1.41E-01 1.52E-01 2.08E-01 3.71E-01 7.0BE-01 1.53E+OO 2.04E+OO 3.70E+OO 3.70E+OO 40-09 2265000 142 3.99 8.64E-01 1.05E-01 1.13E-01 1.52E-01 1.66E-01 2.55E-01 5.16E-01 8.83E-01 1.42E+OO 3.22E+OO 7.44E+OO 7.44E+OO 70 + 871000 53 5.48 9.43E-01 2.59E-01 3.91E-02 5.15E-02 1.05E-01 1.88E-01 3.64E-01 7.57E-01 1.34E+OO 6.49E+OO 9.23E+OO 9.23E+OO Season Fall 2458000 89 5.16 5.44E-01 8.37E-02 3.91E-02 1.05E-01 1.42E-01 1.88E-01 3.17E-01 5.46E-01 1.27E+OO 1.42E+OO 5.35E+OO 5.69E+OO Spring 1380000 160 2.99 6.35E-01 5.57E-02 1.42E-01 1.68E-01 1.93E-01 2.64E-01 4.48E-01 7.68E-01 1.21E+OO 1.57E+OO 5.15E+OO 6.68E+OO Summer 1777000 62 3.91 1.82E+OO 2.62E-01 6.59E-02 1.78E-01 3.43E-01 6.44E-01 9.36E-01 2.13E+OO 4.52E+OO 6.84E+OO 9.23E+OO 9.23E+OO Winter 1276000 110 2.62 5.45E-01 4.67E-02 1.14E-01 1.20E-01 1.49E-01 2.22E-01 4.05E-01 6.14E-01 1.16E+OO 1.47E+OO 2.04E+OO 3.94E+OO Urbanization Central City 748000 27 1.33 7.37E-01 1.41E-01 3.91E-02 3.91E-02 5.15E-02 1.77E-01 5.46E-01 9.29E-01 2.04E+OO 2.23E+OO 3.04E+OO 3.04E+OO Nonmetropolitan 4122000 268 9.16 9.63E-01 8.18E-02 7.40E-02 1.22E-01 1.66E-01 2.49E-01 5.31E-01 1.00E+OO 2.13E+OO 3.38E+OO 7.44E+OO 8.97E+OO Suburban 2021000 126 2.33 8.04E-01 1.30E-01 1.05E-01 1.53E-01 1.66E-01 2.39E-01 3.96E-01 6.47E-01 1.34E+OO 1.71E+OO 9.23E+OO 9.23E+OO Race Black 188000 9 0.86 . . . . . . . White 6703000 412 4.26 8.87E-01 6.51E-02 5.15E-02 1.22E-01 1.63E-01 2.37E-01 4.80E-01 8.84E-01 .1.88E+OO 3.22E+OO 7.44E+OO 9.23E+OO Region Midwest 2557000 188 5.51 9.34E-01 9.74E-02 3.91E-02 1.19E-01 1.68E-01 2.47E-01 4.56E-01 9.29E-01 2.28E+OO 3.22E+OO 6.84E+OO 7.44E+OO Northeast 586000 33 1.42 6.14E-01 8.42E-02 9.87E-02 1.66E-01 1.86E-01 2.44E-01 3.81E-01 8.83E-01 1.34E+OO
1.71E+OO 1.71E+OO 1.71E+OO South 2745000 153 4.27 8.73E-01 9.52E-02 7.40E-02 1.22E-01 1.66E-01 2.83E-01 5.61E-01 9.35E-01 1.55E+OO 3.37E+OO 5.69E+OO 8.97E+OO West 1003000 47 2.78 9.99E-01 2.77E-01 1.05E-01 1.47E-01 1.52E-01 1.77E-01 3.96E-01 7.45E-01 2.23E+OO 6.49E+OO 9.23E+OO 9.23E+OO Response to Questionnaire Households who garden 6233000 387 9.15 8.75E-01 6.30E-02 5.15E-02 1.35E-01 1.65E-01 2.44E-01 5.02E-01 9.14E-01 1.82E+OO 3.13E+OO 6.84E+OO 9.23E+OO Households who farm 1739000 114 23.73 1.20E+OO 1.77E-01 3.91E-02 1.08E-01 1.66E-01 2.29E-01 3.81E-01 9.74E-01 3.37E+OO 6.49E+OO 9.23E+OO 9.23E+OO
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE= standard error P = percentile of the distributions Ne wgtd =weighted number of consumers; Ne unwgtd = unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-42. Consumer Onlv Intake of Honiearown Cucumbers (a/ka-davl Population Ne Ne % Grouo wntd unwntd Consuminn Mean SE P1 PS P10 P25 P50 P75 P90 P95 *p99 P100 Total 3994000 141 2.12 1.02E+OO 1.55E-01 3.08E-02 6.71E-02 1.08E-01 2.40E-01 5.40E-01 1.13E+OO 2.11E+OO 2.79E+OO 1.34E+01 1.37E+01 Age 01-02 132000 5 2.32 . . . . . . . . . . . 03-05 107000 4 1.32 . . . . . . . . . . . 06-11 356000 12 2.13 . . . . . . . . . . . 12-19 254000 10 1.24 . . . . . . . . . . . 20-39 864000 29 1.40 5.04E-01 9.27E-02 3.08E-02 5.45E-02 6.31E-02 1.83E-01 3.09E-01 6.17E-01 1.35E+OO 1.49E+OO 2.12E+OO 2.12E+OO 40-69 1882000 68 3.32 1.33E+OO 3.01E-01 4.16E-02 7.46E-02 1.76E-01 3.93E-01 6.84E-01 1.29E+OO 2.11E+OO 3.27E+OO 1.37E+01 1.37E+01 70+ 399000 13 2.51 . . . . . . . . . . Season Fall 370000 12 0.78 . . . . . . * . . . Spring 197000 15 0.43 . . . . . . . . . . . Summer 3427000 114 7.53 1.06E+OO 1.83E-01 0.00E+OO 7.46E-02 1.08E-01 2.42E-01 5.18E-01 1.13E+OO 2.12E+OO 2.79E+OO 1.34E+01 1.37E+01 Winter 0 0 0.00 Urbanization Central City 640000 18 1.14 . . . . . . . . . . . . Nonmetropolitan 1530000 64 *3.40 1.74E+OO 3.43E-01 1.01E-01 1.21E-01 1.90E-01 3.86E-01 1.06E+OO 1.67E+OO 3.09E+OO 4.50E+OO 1.37E+01 1.37E+01 Suburban 1824000 59 2.11 6.71E-01 7.52E-02 o.o*oE+oo 7.46E-02 1.62E-01 2.78E-01 4.99E-01 8.33E-01 1.34E+OO 1.73E+OO 3.27E+OO 3.27E+OO Race Black 86000 2 0.40 . . . . . . . White 3724000 132 2.36 9.35E-01 1.62E-01 3.08E-02 6.31E-02 1.01E-01 2.22E-01 5.01E-01 1.03E+OO 1.49E+OO 2.40E+OO 1.34E+01 1.37E+01 Region Midwest 969000 31 2.09 1.00E+OO 3.92E-01 3.08E-02 4.16E-02 5.45E-02 1.35E-01 4.53E-01 1.03E+OO 2.35E+OO 2.45E+OO 1.34E+01 1.34E+01 Northeast 689000 22 1.67 1.92E+OO 6.78E-01 2.33E-01 2.78E-01 2.78E-01 4.75E-01 6.84E-01 1.53E+OO 4.18E+OO 1.17E+01 1.37E+01 1.37E+01 South 1317000 54 2.05 8.85E-01 1.0SE-01 O.OOE+OO 1.21E-01 1.83E-01 2.87E-01 7.53E-01 1.28E+OO 1.73E+OO 2.13E+OO 4.50E+OO 4.50E+OO West 1019000 34 2.83 6.01E-01 1.06E-01 6.71E-02 7.46E-02 1.01E-01 2.09E-01 4.30E-01 7.01E-01 1.29E+OO 2.11E+OO 3.27E+OO 3.27E+OO Response to Questionnaire Households who garden 3465000 123 5.08 1.05E+OO 1.75E-01 3.08E-02 6.71E-02 1.01E-01 2.78E-01 5.18E-01 1.13E+OO 2.11E+OO 2.79E+OO 1.34E+01 1.37E+01 Households who farm 710000 29 9.69 6.99E-01 1.0?E-01 0.00E+OO 0.00E+OO 1.43E-01 1.88E-01 3.86E-01 1.27E+OO 1.49E+OO 1.71E+OO 2.09E+OO 2.09E+OO
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. SoUrce: Based on EPA's analyses of the 1987-88 NFCS -

Table 13-43. Consumer Onlv Intake of Home Produced Eaas (a/ka-dav\ Population Ne Ne % Grouo watd unwatd Consumina Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 2075000 124 1.10 7.31E-01 1.00E-01 7.16E-02 1.50E-01 1.75E-01 2.68E-01 4.66E-01 9.02E-01 1.36E+OO 1.69E+OO 6.58E+OO 1.35E+01 Age 01-02 21000 3 0.37 . . . . . . . . . . . 03-05 20000 2 0.25 . . . . . . . . . . 06-11 170000 12 1.02 . . . . . . . . . . 12-19 163000 14 0.80 . . . . . . . . . . 20-39 474000 30 0.77 6.32E-01 9.23E-02 7.16E-02 7.16E-02 2.15E-01 3.00E-01 4.16E-01 8.14E-01 1.32E+OO 1.93E+OO 2.50E+OO 2.50E+OO 40-69 718000 43 1.27 5.91E-01 5.77E-02 1.37E-01 1.41E-01 1.52E-01 3.17E-01 5.14E-01 8.44E-01 1.30E+OS 1.36E+OO 1.38E+OO 1.38E+OO 70+ 489000 18 3.08 . . . . . . . . . . . Seasons Fall 542000 18 1.14 . . . . . . . . . . . . Spring 460000 54 1.00 1.31E+OO 2.88E-01 1.57E-01 3.25E-01 3.94E-01 5.02E-01 6.66E-01 1.31E+OO 2.10E+OO 3.26E+OO 1.35E+01 1.35E+01 Summer 723000 26 1.59 4.96E-01 8.14E-02 7.16E-02 1.37E-01 1.41E-01 2.60E-01 3.32E-01 5.41E-01 1.36E+OO 1.51E+OO 1.65E+OO 1.65E+OO Winter 350000 26 0.72 8.60E-01 9.50E-02 1.67E-01 1.75E-01 2.15E-01 4.03E-01 7.51E-01 1.17E+OO 1.62E+OO 1.93E+OO 1.93E+OO 1.93E+OO Urbanization Central City 251000 9 0.45 . . . . . . . . . . . Nonmetropolitan 1076000 65 2.39 7.34E-01 1.23E-01 7.16E-02 1.41E-01 1.67E-01 2.60E-01 4.74E-01 9.16E-01 1.34E+OO 1.65E+OO 6.58E+OO 9.16E+OO Suburban 748000 50 0.86 8.54E-01 1.98E-01 1.37E-01 1.50E-01 2.06E-01 3.80E-01 5.88E-01 1.17E+OO 1.36E+OO 1.85E+OO 1.35E+01 1.35E+01 Race Black 63000 9 0.29 . . . . . . . . . . . White 2012000 115 1.28 7.41 E-01 1.05E-01 7.16E-02 1.50E-01 1.75E-01 2.68E-01 4.82E-01 9.03E-01 1.36E+OO 1.69E+OO 6.58E+OO 1.35E+01 Region Midwest 665000 37 1.43 7.93E-01 1.96E-01 7.16E-02 1.37E-01 1.41E-01 2.17E-01 3.39E-01 1.08E+OO 1.51E+OO 2.10E+OO 9.16E+OO 9.16E+OO Northeast 87000 7 0.21 . . . . . . . . . . . South 823000 44 1.28 5.36E-01 6.46E-02 1.52E-01 1.77E-01 1.96E-01 2.60E-01 3.60E-01 5.99E-01 1.18E+OO 1.62E+OO 1.93E+OO 1.93E+OO West 500000 36 1.39 9.21E-01 2.75E-01 1.67E-01 2.06E-01 2.08E-01 4.58E-01 6.66E-01 1.05E+OO 1.36E+OO 1.36E+OO 1.35E+01 1.35E+01 Response to Questionnaire Households who raise animals 1824000 113 18.06 7.46E-01 1.11E-01 7.16E-02 1.50E-0.1 1.65E-01 2.56E-01 4.82E-01 9.02E-01 1.36E+OO 1.85E+OO 6.58E+OO 1.35E+01 Households who farm 741000 44 10.11 8.98E-01 1.70E-01 1.52E-01 1.65E-01 1.77E-01 2.72E-01 6.66E-01 1.19E+OO 1.65E+OO 1.85E+OO 6.58E+OO 9.16E+OO

Intake daia not provided for subpopulations for which there were Jess than 20 observations NOTE: SE ; standard error P ; percentile of the distribution Ne wgtd; weighted number of consumers; Ne unwgtd; unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-44. Consumer Only Intake of Home Produced Game (g/kg-day) Population Ilic Ne % Grouo watd unwatd Consumina Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 2707000 185 1.44 9.67E-01 6.14E-02 0.00E+OO 1.17E-01 2.10E-01 3.97E-01 7.09E-01 1.22E+OO 2.27E+OO 2.67E+OO 3.61E+OO 4.59E+OO Age 01-02 89000 8 1.56 . . . . . . . . . . . . 03-05 94000 8 1.16 . . . . . . . . . . . . 06-11 362000 28 2.17 1.09E+OO 1.44E-01 1.16E-01 2.31E-01 4.28E-01 6.33E-01 7.61E-01 1.48E+OO 2.67E+OO 2.85E+OO 2.90E+OO 2.90E+OO 12-19 462000 27 2.25 1.04E+OO 1.39E-01 2.10E-01 2.10E-01 2.91E-01 6.30E-01 8.46E-01 1.22E+OO 1.99E+OO 3.13E+OO 3.13E+OO 3.13E+OO 20-39 844000 59 1.37 8.24E-01 1.08E-01 1.04E-01 1.17E-01 1.88E-01 3.01E-01 6.31E-01 1.09E+OO 1.57E+OO 2.50E+OO 4.59E+OO 4.59E+OO 40-69 694000 41 1.22 9.64E-01 1.40E-01 1.24E-01 1.72E-01 2.87E-01 3.42E-01 5.10E-01 1.41E+OO 2.51E+OO 3.19E+OO 3.61E+OO 3.61E+OO 70 + 74000 7 0.47 . . . . . . . . . Season Fall 876000 31 1.84 9.97E-01 1.56E-01 1.17E-01 1.48E-01 2.18E-01 4.28E-01 6.33E-01 1.19E+OO 2.50E+OO 3.13E+OO 3.19E+OO 3.19E+OO Spring 554000 68 1.20 9.06E-01 8.78E-02 0.00E+OO 1.04E-01 1.72E-01 4.43E-01 7.46E-01 1.22E+OO 1.75E+OO 2.52E+OO 3.61E+OO 3.61E+OO Summer 273000 9 0.60 . . . . . . . . . . Winter 1004000 77 2.06 1.07E+OO 1.05E-01 0.00E+OO 0.00E+OO 1.65E-01 3.88E-01 8.18E-01 1.52E+OO 2.20E+OO 2.67E+OO 4.59E+OO 4.59E+OO Urbanization Central City 506000 20 0.90 6.89E-01 1.27E-01 0.00E+OO O.OOE+OO 1.88E-01 2.??E-01 6.30E-01 7.74E-01 1.48E+OO 1.99E+OO 2.34E+OO 2.34E+OO Nonmetropolitan 1259000 101 2.80 9.45E-01 8.91E-02 0.00E+OO 1.17E-01 1.65E-01 3.20E-01 6.59E-01 1.19E+OO 2.27E+OO 3.05E+OO 4.59E+OO 4.59E+OO Suburban 942000 64 1.09 1.15E+OO 1.04E-01 0.00E+OO 2.56E-01 3.97E-01 5.21E-01 8.18E-01 1.52E+OO 2.51E+OO 2.85E+OO 3.13E+OO 3.61E+OO Race Black 0 0 0.00 White 2605000 182 1.65 9.77E-01 6.30E-02 0.00E+OO 1.17E-01 2.02E-01 3.76E-01 7.29E-01 1.38E+OO 2.34E+OO 2.85E+OO 3.61E+OO 4.59E+OO Region Midwest 1321000 97 2.85 8.83E-01 8.32E-02 0.00E+OO 7.53E-02 2.18E-01. 3.42E-01 6.12E-01 1.10E+OO 1.99E+OO 2.51E+OO 4.59E+OO 4.59E+OO Northeast 394000 20 0.96 1.13E+OO 2.16E-01 2.87E-01 2.87E-01 3.21E-01 4.30E-01 7.74E-01 1.41E+OO 3.13E+OO 3.13E+OO 3.61E+OO 3.61E+OO South 609000 47 0.95 1.26E+OO 1.29E-01 O.OOE+OO 1.17E-01 1.48E-01 6.32E-01 1.09E+OO 1.93E+OO 2.38E+OO 3.19E+OO 3.19E+OO 3.19E+OO West 383000 21 1.06 6.28E-01 7.21E-02 1.24E-01 1.51E-01 1.88E-01 3.97E-01 6.33E-01 7.74E-01 1.12E+OO 1.22E+OO 1.52E+OO 1.52E+OO Response to Questionnaire Households who hunt 2357000 158 11.66 1.04E+OO 6.84E-02 O.OOE+OO 1.40E-01 2.77E-01 4.42E-01 7.46E-01 1.44E+OO 2.38E+OO 2.90E+OO 3.61E+OO 4.59E+OO
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd = unweighted number of consumers in survey. Source: Based*on EPA's analyses of the 1987-88 NFCS Table 13-45. Consumer Onlv Intake of Home Produced Lettuce (o/ko-dav) Population Ne Ne % Groun watd unwatd Consumina Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 1520000 BO 0.81 3.B7E-01 3.1BE-02 O.OOE+OO 4.49E-02 9.43E-02 1.70E-01 2.84E-01 5.45E-01 8.36E-01 1.03E+OO 1.05E+OO 1.2BE+OO Age 01-02 54000 4 0.95 . . . . . . . . . . . 03-05 25000 2 0.31 . . . . . . . . . . 06-11 173000 7 1.04 . . .. . . . . . . . . . 12-19 71000 3 0.35 . . . . . . . . . 20-39 379000 17 0.62 . . . . . . . . .. . 40-69 485000 26 0.86 4.84E-01 6.07E-02 1.15E-01 1.15E-01 1.24E-01 2.21E-01 4.91E-01 6.84E-01 B.86E-01 1.05E+OO 1.2BE+OO 1.2BE+OO 70 + 317000 20 2.00 4.52E-01 7.17E-02 5.04E-02 6.71E-02 1.12E-01 2.23E-01 2.BBE-01 5.6BE-01 1.03E+OO 1.03E+OO 1.03E+OO 1.03E+OO Season Fall 214000 B 0.45 . . . . . . . . . . . Spring 352000 35 0.76 4.52E-01 4.B6E-02 5.04E-02 6.71E-02 1.24E-01 1.99E-01 4.53E-01 5.79E-01 7.9BE-01 9.94E-01 1.2BE+OO 1.2BE+OO Summer 856000 30 1.88 3.02E-01 3.96E-02 1.9BE-02 3.35E-02 4.93E-02 1.42E-01 2.30E-01 4.24E-01 5.9BE-01 B.14E-01 B.B6E-01 B.86E-01 Winter 98000 7 0.20 . . . . . . . . . . . . Urbanization Central City 268000 B 0.48 . . . . . . . . . . Non metropolitan 566000 36 1.26 3.67E-01 4.78E-02 1.9BE-02 3.35E-02 4.49E-02 1.23E-01 2.88E-01 5.45E-01 8.14E-01 8.86E-01 1.28E+OO 1.28E+OO Suburban 686000 36 0.79 3.49E-01 4.32E-02 0.00E+OO 9.43E-02 9.68E-02 , 1.53E-01 2.30E-01 4.91E-01 7.67E-01 9.94E-01 1.05E+OO 1.05E+OO Race Black 51000 3 0.23 . . . . . . . . . White 1434000 75 0.91 3.79E-01 3.33E-02 O.OOE+OO 4.49E-02 9.43E-02 1.56E-01 2.75E-01 5.45E-01 8.B6E-01 1.03E+OO 1.05E+OO 1.2BE+OO Region Midwest 630000 33 1.36 3.83E-01 5.54E-02 1.9BE-02 3.35E-02 4.49E-02 1.56E-01 2.34E-01 5.6BE-01 9.42E-01 1.03E+OO 1.03E+OO 1.03E+OO Northeast 336000 16 0.82 . . . . . . . . . . South 305000 20 0.47 3.52E-01 5.74E-02 O.OOE+OO O.OOE+OO 1.27E-01 1.64E-01 2.75E-01 4.83E-01 5.79E-01 1.04E+OO 1.28E+OO 1.28E+OO West 249000 11 0.69 . . . . . . . . . . . Responses to Questionnaire Households who garden 1506000 78 2.21 3.90E-01 3.22E-02 O.OOE+OO 4.49E-02 9.43E-02 1.74E-01 2.B4E-01 5.45E-01 B.36E-01 1.03E+OO 1.05E+OO 1.28E+OO Households who farm 304000 18 4.15 . . . . . . . . . . . .
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source; Based on EPA's analyses of the 1987-88 NFCS
Table 13-46. Consumer Only Intake of Home Produced Lima Beans (g/kg-day) Population Ne Ne % Groun wold unwntd Consumina Mean SE P1 PS P10 P25 P50 P75 P90 P95 P99 P100 Total 1917000 109 1.02 4.53E-01 4.11E-02 0.00E+OO 9.19E-02 1.21E-01 1.88E-01 2.90E-01 5.45E-01 9.90E-01 1.69E+OO 1.86E+OO 1.91E+OO Age 01-02 62000 3 1.09 . . . . . . . . . . . . 03-05 35000 2 0.43 . . . . . . . . . . . . 06-11 95000 7 0.57 . . . . . . . . . . . 12-19 108000 6 0.53 . . . . . . . . 20-39 464000 20 0.75 3.84E-01 6.87E-02 3.23E-02 1.08E-01 1.30E-01 1.77E-01 2.34E-01 4 .. 87E-01 9.37E-01 1.10E+OO 1.10E+OO 1.10E+OO 40-69 757000 44 1.33 4.54E-01 6.30E-02 9.19E-02 1.06E-01 1.21E-01 2.04E-01 2.93E-01 5.60E-01 8.69E-01 1.71E+OO 1.91E+OO 1.91E+OO 70+ 361000 25 2.27 5.23E-01 1.0SE-01 8.20E-02 1.86E-01 1.88E-01 2.25E-01 2.86E-01 6.38E-01 1.86E+OO 1.86E+OO 1.86E+OO 1.86E+OO Season Fall 375000 14 0.79 . . . . . . . Spring 316000 39 0.68 4.19E-01 5.SOE-02 8.20E-02 9.02E-02 1.31E-01 2.32E-01 3.06E-01 5.45E-01 7.48E-01 1.31E+OO 1.91E+OO 1.91E+OO Summer 883000 29 1.94 4.99E-01 9.68E-02 O.OOE+OO 9.43E-02 1.21E-01 1.72E-01 2.90E-01 4.87E-01 1.53E+OO 1.71E+OO 1.86E+OO 1.86E+OO Winter 343000 27 0.70 5.27E-01 6.25E-02 0.00E+OO 3.23E-02 1.08E-01 3.0SE-01 5.39E-01 7.58E-01 8.61E-01 8.69E-01 1.69E+OO 1.69E+OO Urbanization Central City 204000 8 0.36 . . . . . . . . . . . Nonmetropolitan 1075000 69 2.39 2.99E-01 3.22E-02 3.23E-02 9.43E-02 1.21E-01 1.71E-01 2.12E-01 3.ZOE-01 4.87E-01 7.69E-01 1.69E+OO 1.91E+OO Suburban 638000 32 0.74 7.53E-01 9.60E-02 O.OOE+OO 8.20E-02 9.19E-02 3.20E-01 6.78E-01 9.90E-01 1.71E+OO 1.86E+OO 1.86E+OO 1.86E+OO Race Black 213000 9 0.98 . . . . . . . . . White 1704000 100 1.08 3.83E-01 3.27E-02 O.OOE+OO 9.19E-02 1.08E-01 1.77E-01 2.54E-01 4.87E-01 8.61E-01 9.90E-01 1.53E+OO 1.91E+OO Region Midwest 588000 36 1.27 4.28E-01 6.17E-02 0.00E+OO 0.00E+OO 1.06E-01 2.53E-01 3.06E-01 4.15E-01 9.90E-01 1.53E+OO* 1.69E+OO 1.69E+OO Northeast 68000 6 0.17 . . . . . . . . . South 1261000 67 1.96 4.72E-01 5.62E-02 3.23E-02 1.03E-01 1.30E-01 1.77E-01 2.49E-01 6.34E-01 1.10E+OO 1.71E+OO 1.86E+OO 1.91E+OO West 0 0 0.00 Response to Questionnaire Households who garden 1610000 97 2.36 4.47E-01 4.49E-02 3.23E-02 9.43E-02 1.21E-01 1.77E-01 2.85E-01 5.26E-01 9.37E-01 1.71E+OO 1.86E+OO 1.91E+OO Households who farm 62000 6 0.85 . . . . . . . . . . .
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 f\!FCS Table 13-47. Consumer Onlv Intake of HomeQrown Okra (QlkQ-day) Population Ne Ne % Grouo wotd unwatd Consumina Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 1696000 82 0.90 3.91E-01 3.81E-02 0.00E+OO 5.03E-02 9.59E-02 1.48E-01 2.99E-01 4.58E-01 7.81E-01 1.21E+OO 1.53E+OO 1.53E+OO Age 01-02 53000 2 0.93 . . . . . . . . . . . . 03-05 68000 3 0.84 . . . . . . . . . . . . 06-11 218000 11 1.30 . . . . . . . . . . . 12-19 194000 9 0.95 . . . . . . . . . 20-39 417000 18 0.68 . . . . . . . . . . 40-69 587000 32 1.03 4.00E-01 4.73E-02 6.57E-02 1.11E-01 1.37E-01 2.47E-01 3.07E-01 4.62E-01 7.81E-01 1.14E+OO 1.14E+OO 1.14E+OO 70 + 130000 6 0.82 . . . . . . . . . . Season Fall 228000 9 0.48 . . . . . . . . . . . . Spring 236000 24 0.51 3.87E-01 6.22E-02 2.98E-02 4.58E-02 6.57E-02 1.10E-01 4.10E-01 5.95E-01 7.81E-01 9.99E-01 1.07E+OO 1.07E+OO Summer 1144000 41 2.52 3.86E-01 5.75E-02 O.OOE+OO 5.03E-02 9.59E-02 1.44E-01 2.99E-01 4.38E-01 1.15E+OO 1.53E+OO 1.53E+OO 1.53E+OO Winter 88000 8 0.18 . . . . . . . . . . . Urbanization Central City 204000 6 0.36 . . . . . . . . . . . . Nonmetropolitan 1043000 55 2.32 3.65E-01 4.99E-02 0.00E+OO 2.69E-02 8.48E-02 1.48E-01 2.57E-01 4.38E-01 7.81E-01 1.53E+OO 1.53E+OO 1.53E+OO Suburban 449000 21 0.52 5.14E-01 6.97E-02 6.57E-02 9.60E-02 1.11E-01 3.13E-01 4.62E-01 6.00E-01 1.14E+OO 1.15E+OO 1.15E+OO 1.15E+OO Race Black 236000 13 1.09 . . . . . . . . . . . White 1419000 68 0.90 4.26E-01 4.40E-02 0.00E+OO 6.57E-02 9.60E-02 1.76E-01 3.30E-01 5.23E-01 1.14E+OO 1.21E+OO 1.53E+OO 1.53E+OO Region Midwest 113000 7 0.24 . . . . . . . . . . Northeast South 1443000 70 2.24 3.73E-01 4.21E-02 0.00E+OO 5.03E-02 8.48E-02 1.44E-01 2.59E-01 4.38E-01 7.47E-01 1.21E+OO 1.53E+OO 1.53E+OO West 140000 5 0.39 . . . . . . . . . Response to Questionnaire Households who garden 1564000 77 2.29 3.84E-01 4.05E-02 0.00E+OO 5.03E-02 9.59E-02 1.48E-01 2.98E-01 4.52E-01 1.07E+OO 1.21E+OO 1.53E+OO 1.53E+OO Households who farm 233000 14 3.18 . . . . . . . . . . . .
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd = unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-48. Consumer Onlv Intake of Homeqrown Onions (q/kq-dav) Population Ne Ne % Groua watd unwntd *Consuminq Mean SE P1 PS P10 P25 PSO P75 P90 P95 P99 P100 Total 6718000 370 3.57 2.96E-01 1.87E-02 3.68E-03 9.09E-03 2.90E-02 8.81E-02 2.06E-01 3.77E-01 6.09E-01 9.12E-01 1.49E+OO .3.11E+OO Age 01-02 291000 17 5.11 . . . . . . . . . . . . 03-05 178000 9 2.20 . . . . . . . . . . . . 06-11 530000 31 3.17 3.03E-01 5.61E-02 9.80E-03 1.08E-02 2.76E-02 1.06E-01 2.28E-01 3.83E-01 6.09E-01 1.36E+OO 1.36E+OO 1.36E+OO 12-19 652000 37 3.18 2.11E-01 3.65E-02 5.14E-03 8.36E-03 8.58E-03 5.97E-02 1.42E-01 2.55E-01 5.74E-01 7.59E-01 9.12E-01 9.12E-01 20-39 1566000 78 2.54 2.88E-01 3.40E-02 9.09E-03 3.80E-02 5.80E-02 9.40E-02 1.91E-01 3.04E-01 6.38E-01 9.35E-01 1.49E+OO 1.49E+OO 40-69 2402000 143 4.23 2.SOE-01 2.07E-02 3.03E-03 4.59E-03 1.11E-02 7.66E-02 1.72E-01 3.58E-01 5.52E-01 6.90E-01 1.11E+OO 1.41E+OO 70 + 1038000 52 6.54 4.33E-01 8.86E-02 4.76E-03 6.68E-03 2.68E-02 1.35E-01 2.86E-01 4.61E-01 5.63E-01 2.68E+OO 3.11E+OO 3.11E+OO Season Fall 1557000 59 3.27 3.75E-01 6.93E-02 3.68E-03 2.55E-02 5.80E-02 1.23E-01 2.55E-01 4.36E-01 6.03E-01 7.83E-01 3.11E+OO 3.11E+OO Spring 1434000 147 3.11 1.95E-01 1.96E-02 2.01E-03 5.47E-03 2.68E-02 5.73E-02 1.06E-01 2.59E-01 4.26E-01 . 5.23E-01 1.41E+OO 1.77E+OO Summer 2891000 101 6.36 3.06E-01 2.91E-02 8.58E-03 1.68E-02 4.22E-02 1.08E-01 2.28E-01 3.76E-01 6.90E-01 9.69E-01 1.49E+OO 1.49E+OO Winter 836000 63 1.72 2.88E-01 3.86E-02 3.03E-03 4.59E-03 5.04E-03 3.06E-02 1.99E-01 4.60E-01 6.42E-01 9.16E-01 1.36E+OO 1.36E+OO Urbanization Central City 890000 37 1.58 2.16E-01 2.85E-02 4.76E-03 1.02E-02 2.55E-02 6.60E-02 1.93E-01 2.96E-01 5.18E-01 5.63E-01 5.63E-01 5.63E-01 Nonmetropolitan 2944000 177 6.54 3.24E-01 2.06E-02 8.12E-03 3.14E-02 6.75E-02 1.42E-01 2.55E-01 4.33E-01 6.30E-01 9.12E-01 1.49E+OO 1.77E+OO Suburban 2884000 156 3.33 2.92E-01 3.70E-02 3.03E-03 5.20E-03 1.10E-02 5.85E-02 1.30E-01 3.56E-01 6.35E-01 .9.69E-01 3.11E+OO 3.11E+OO Race Black 253000 16 1.16 . . . . . . . . . . . . White 6266000 345 3.98 3.08E-01 1.99E-02 3.57E-03 9.09E-03 3.06E-02 9.16E-02 2.24E-01 3.86E-01 6.18E-01 9.35E-01 1.77E+OO 3.11E+OO Region Midwest 2487000 143 5.36 2.70E-01 1.94E-02 4.25E-03 4.02E-02 5.73E-02 1.02E-01 2.24E-01 3.43E-01 5.63E-01 7.24E-01 1.34E+OO 1.34E+OO Northeast 876000 52 2.13 2.32E-01 4.43E-02 2.01E-03 3.73E-03 8.36E-03 1.08E-02 1.08E-01 3.53E-01 6.35E-01 1.05E+OO 1.36E+OO 1.41E+OO South 1919000 107 2.98 3.32E-01 2.93E-02 4.79E-03 2.76E-02 3.70E-02 1.46E-01 2.51E-01 3.93E-01 6.90E-01 1.08E+OO 1.49E+OO 1.77E+OO West 1436000 68 3.98 3.32E-01 6.90E-02 3.57E-03 6.68E-03 1.68E-02 5.68E-02 1.52E-01 3.86E-01 5.49E-01 9:69E-01 3.11E+OO 3.11E+OO Response to Questionnaire Households who garden 6441000 356 9.45 3.00E-01 1.93E-02 3.68E-03 9.09E-03 3.06E-02 9.11E-02 2.13E-01 3.81E-01 6.09E-01 9.16E-01 1.77E+OO 3.11E+OO Households who farm 1390000 81 3.75E-01 3.84E-02 . 3.00E-02 4.04E-02 5.15E-02 1.11E-01 2.78E-01 5.15E-01 9.35E-01 1.11E+OO 1.49E+OO 1.49E+OO
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distributions Ne wgtd =weighted number of consumers; Ne unwgtd = unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS
Table 13-49. Consumer Only Intake of Homegrown other Berries (g/kg-day) Population Ne Ne % Grouo wold unwatd Consuminn Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 1626000 99 0.86 4.80E-01 4.24E-02 O.OOE+OO 4.68E-02 9.24E-02 2.32E-01 3.84E-01 5.89E-01 1.07E+OO 1.28E+OO 2.21E+OO 2.21E+OO Age 01-02 41000 2 0.72 . . . . . . . . 03-05 53000 3 0.65 . . . . . . . . . . . 06-11 106000 10 0.63 . . . . . . . . . . . . 12-19 79000 5 0.39 . . . . . . . . . . . . 20-39 309000 20 0.50 3.90E-01 6.31E-02 7.95E-02 9.18E-02 9.18E-02 1.25E-01 3.30E-01 5.52E-01 7.94E-01 1.07E+OO 1.07E+OO 1.07E+OO 40-69 871000 51 1.54 4.89E-01 5.72E-02 7.69E-02 1.01E-01 1.34E-01 2.48E-01 3.89E-01 6.12E-01 7.68E-01 1.28E+OO 2.21E+OO 2.21E+OO 70 + 159000 7 1.00 . . . . . . . . . Season Fall 379000 13 0.80 . . . . . . . . . . . . Spring 287000 29 0.62 3.06E-01 4.11E-02 4.68E-02 4.68E-02 7.69E-02 1.84E-01 2.54E-01 4.08E-01 5.40E-01 7.24E-01 1.07E+OO 1.07E+OO Summer 502000 18 1.10 . . . . . . . . . . . . Winter 458000 39 0.94 5.35E-01 7.39E-02 O.OOE+OO 1.02E-01 1.59E-01 2.32E-01 3.89E-01 6.23E-01 1.07E+OO 1.95E+OO 2.08E+OO 2.08E+OO Urbanization Central City 378000 15 0.67 . . . . . . . . . . . Nonmetropolitan 466000 37 1.04 6.43E-01 8.96E-02 0.00E+OO 9.24E-02 1.02E-01 2.51E-01 4.39E-01 1.02E+OO 1.31E+OO 2.21E+OO 2.21E+OO 2.21E+OO Suburban 722000 45 0.83 4.48E-01 5.32E-02 9.18E-02 1.25E-01 1.58E-01 2.58E-01 3.84E-01 5.35E-01 5.89E-01 9.02E-01 2.08E+OO 2.08E+OO Race Black 76000 4 0.35 . . . . . . . . . . . White 1490000 93 0.95 5.03E-01 4.43E-02 4.68E-02 9.18E-02 1.01E-01 2.51E-01 3.95E-01 6.04E-01 1.07E+OO 1.31E+OO 2.21E+OO 2.21E+OO Region Midwest 736000 56 1.59 4.57E-01 6.26E-02 O.OOE+OO 7.69E-02 9.18E-02 1.25E-01 3.00E-01 5.87E-01 1.12E+OO 1.28E+OO 2.21E+OO 2.21E+OO Northeast 211000 11 0.51 . . . . . . . . . . . South 204000 12 0.32 . . . . . . . . . . . . West 415000 18 1.15 . . . . . . . . . . . . Response to Questionnaire Households who garden 1333000 84 1.96 4.72E-01 4.83E-02 1.00E-02 O.OOE+OO 9.18E-02 2.00E-01 3.53E-01 5.52E-01 1.07E+OO 1.28E+OO 2.21E+OO 2.21E+OO Households who farm 219000 16 2.99 . . . . . . . . . . . .
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd = unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-50. Consumer Only Intake of Homegrown Peaches (g/kg-day) Population Ne Ne % Grouo watd unwatd Consumina Mean SE P1 PS P10 P25 P50 P75 P90 P95 P99 P100 Total 2941000 193 1.56 1.67E+OO 1.70E-01 5.20E-02 1.65E-01 2.25E-01 4.74E-01 8.97E-01 1.88E+OO 3.79E+OO 6.36E+OO 1.23E+01 2.23E+01 Age 01-02 103000 8 1.81 . . . . . . . . . . . 03-05 65000 6 0.80 . . . . . . . . . . 06-11 329000 26 1.97 3.11E+OO 6.32E-01 9.75E-02 1.01E-01 1.40E-01 6.25E-01 1.13E+OO 6.36E+OO 8.53E+OO 8.53E+OO 1.15E+01 1.15E+01 12-19 177000 13 0.86 . . . . . . . . . . . 20-39 573000 35 0.93 1.17E+OO 1.74E-01 5.07E-02 5.50E-02 2.25E-01 4.74E-01 8.09E-01 1.30E+OO 2.92E+OO 2.99E+OO 5.27E+OO 5.27E+OO 40-69 1076000 70 1.90 1.53E+OO 2.83E-01 5.87E-02 1.90E-01 2.39E-01 5.56E-01 8.92E-01 1.61E+OO 2.63E+OO 4.43E+OO 1.23E+01 1.23E+01 70 + 598000 33 3.77 1.01E+OO 1.97E-01 9.13E-02 1.38E-01 1.79E-01 2.82E-01 8.22E-01 1.19E+OO 1.60E+OO 3.79E+OO 7.13E+OO 7.13E+OO Season Fall 485000 19 1.02 . . . . . . . . . . . Spring 756000 91 1.64 1.67E+OO 3.04E-01 5.07E-02 5.87E-02 1.01E-01 2.76E-01 7.74E-01 1.45E+OO 4.44E+OO 6.77E+OO 2.23E+01 2.23E+01 Summer 1081000 35 2.38 2.26E+OO 4.78E-01 1.65E-01 2.25E-01 3.61E-01 5.67E-01 1.12E+OO 2.99E+OO 6.36E+OO 8.53E+OO '1.23E+01 1.23E+01 Winter 619000 48 1.27 1.25E+OO 1.03E-01 3.52E-02 2.39E-01 5.56E-01 7.79E-01 1.04E+OO 1.71E+OO -2.35E+OO 2.60E+OO 3.56E+OO 3.56E+OO Urbanization Central City 429000 12 0.76 . . . . . . . . . Nonmetropolitan 1110000 99 2.47 1.87E+OO 2.59E-01 5.87E-02 2.62E-01 3.93E-01 6.46E-01 1.02E+OO 2.18E+OO 3.86E+OO 6.36E+OO 1.15E+01 2.23E+01 Suburban 1402000 82 1.62 1.47E+OO 1.75E-01 5.07E-02 1.40E-01 2.04E-01 4.61E-01 9.20E-01 1.87E+OO 3.79E+OO 4.43E+OO 7.37E+OO 7.37E+OO Race Black 39000 1 0.18 . . . . . . . . . . . White 2861000 191 1.82 1.70E+OO 1.73E-01 5.20E-02 1.65E-01 2.30E-01 5.03E-01 8.97E-01 1.96E+OO 3.79E+OO 6.36E+OO 1.23E+01 2.23E+01 Region Midwest 824000 75 1.78 1.39E+OO 2.91E-01 1.76E-01 2.20E-01 2.59E-01 4.60E-01 7.40E-01 1.19E+OO 3.06E+OO 3.56E+OO 1.15E+01 2.23E+01 Northeast 75000 5 0.18 ' . . . . . . . . . . . South 852000 51 1.32 1.67E+OO 2.57E-01 3.52E-02 1.38E-01 1.79E-01 6,43E-01 1.02E+OO 1.96E+OO 3.83E+OO 6.36E+OO 8.53E+OO 8.53E+OO West 1190000 62 3.30 1.80E+OO 3.26E-01 5.07E-02 1.40E-01 2.25E-01 4.68E-01 8.63E-01 1.94E+OO 4.43E+OO 7.37E+OO 1.23E+01 1.23E+01 Response to Questionnaire Households who garden 2660000 174 3.90 1.75E+OO 1.85E-01 5.20E-02 1.66E-01 2.59E-01 5.26E-01 9.25E-01 1.96E+OO 3.79E+OO 6.36E+OO 1.23E+01 2.23E+01 Households who farm 769000 54 10.49 1.56E+OO 2.49E-01 6.79E-02 1.76E-01 2.26E-01 4.61E-01 9.02E-01 2.02E+OO 2.99E+OO 6.36E+OO 8.53E+OO 8.53E+OO
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers: Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-51. Consumer Onlv Intake of Homearown Pears lo/ko-davl Population Ne Ne % Grouo watd unwatd Consumina Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 1513000 94 0.80 9.37E-01 9.68E-02 1.01E-01 1.84E-01 2.38E-01 4.28E-01 6.82E-01 1.09E+OO 1.60E+OO 2.76E+OO 5.16E+OO 5.16E+OO Age 01-02 24000 3 0.42 . . . . . . . .. . . . . 03-05 45000 3 0.56 . . . . . . . . . . . . 06-11 145000 10 0.87 . . . . . . . . . . . . 12-19 121000 7 0.59 . . . . . . . . . . . . 20-39. 365000 23 0.59 6.19E-01 6.42E-02 1.13E-01 3.18E-01 3.79E-01 4.28E-01 5.03E-01 6.82E-01 1.22E+OO 1.24E+OO 1.24E+OO 1.24E+OO 40-69 557000 33 0.98 6.57E-01 5.53E-02 1.01E-01 1.08E-01 3.33E-01 4.23E-01 6.45E-01 9.22E-01 1.10E+OO 1.13E+OO 1.51E+OO 1.51E+OO 70 + 256000 15 1.61 . . . . . . . . . . . . Season Fall 308000 11 0.65 . . . . . . . . . . . Spring 355000 39 0.77 6.87E-01 7.89E-02 1.01E-01 1.13E-01 1.82E-01 3.38E-01 6.02E-01 8.66E-01 1.15E+OO 1.83E+OO 2.54E+OO 2.54E+OO Summer 474000 16 1.04 . . . . . . . . . . . Winter 376000 28 0.77 1.48E+OO 2.77E-01 1.0BE-01 1.08E-01 3.79E-01 6.45E-01 9.49E-01 1.38E+OO 4.82E+OO 5.16E+OO 5.16E+OO 5.16E+OO Urbanization Central City 222000 11 0.39 . . . . . . . . . . . . Nonmetropolitan 634000 44 1.41 7.81E-01 8.52E-02 3.33E-01 3.52E-01 4.19E-01 4.43E-01 5.70E-01 8.13E-01 1.56E+OO 1.86E+OO 2.88E+OO 2.88E+OO Suburban 657000 39 0.76 8.50E-01 1.17E-01 1.01E-01 1.08E-01 1.82E-01 3.89E-01 7.29E-01 1.10E+OO 1.50E+OO 2.57E+OO 4.79E+OO 4.79E+OO Race Black 51000 3 0.23 . . . . . . . . . . . . White 1462000 91 0.93 9.65E-01 9.88E-02 1.08E-01 2.38E-01 3.52E-01 4.43E-01 7.01E-01 1.09E+OO 1.60E+OO 2.88E+OO 5.16E+OO 5.16E+OO Region Midwest 688000 57 1.48 8.71E-01 9.49E-02 2.22E-01 3.38E-01 3.76E-01 4.43E-01 6.45E-01 1.04E+OO 1.60E+OO 2.57E+OO 4.79E+OO 4.79E+OO Northeast 18000 2 0.04 . . . . . . . . . . . . South 377000 13 -0.59 . . . . . . . . . . . . West 430000 22 1.19 1.14E+OO 2.89E-01 1.01E-01 1.08E-01 1.13E-01 3.56E-01 7.52E-01 1.13E+OO 2.76E+OO 4.82E+OO 5.16E+OO 5.16E+OO Response to Questionnaire Households who 1312000 85 1.93 9.45E-01 1.04E-01 1.01E-01 1.82E-01 3.52E-01 4.31E-01 6.75E-01 1.09E+OO 1.56E+OO 2.88E+OO 5.16E+OO 5.16E+OO Households who farm 528000 35 7.20 1.09E+OO 2.10E-01 1.08E-01 2.22E-01 3.76E-01 4.28E-01 6.14E-01 1.09E+OO 2.76E+OO 4.82E+OO 5.16E+OO 5.16E+OO
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE= standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-52. Consumer Onlv Intake of Homearown Peas fa/ka-dav\ Population Ne Ne % Grouo watd unwatd Consumina Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 4252000 226 2.26 5.05E-01 3.23E-02 4.58E-02 1.02E-01 1.40E-01 2.28E-01 3.21E-01 6.22E-01 1.04E+OO 1.46E+OO 2.66E+OO 2.89E+OO Age 01-02 163000 9 2.86 . . . . . . . . . . . . 03-05 140000 7 1.73 . . . . . . . . . . . . 06-11 515000 26 3.08 6.05E-01 8.91E-02 1.54E-01 1.54E-01 2.18E-01 3.04E-01 3.87E-01 9.00E-01 1.35E+OO 1.40E+OO 2.06E+OO 2.06E+OO 12-19 377000 22. 1.84 4.08E-01 4.28E-02 5.81E-02 1.33E-01 1.58E-01 2.35E-01 3.58E-01 5.02E-01 7.10E-01 8.22E-01 8.22E-01 8.22E-01 20-39 1121000 52 1.82 4.08E-01 6.21E-02 9.96E-02 1.15E-01 1.40E-01 1.80E-01 2.54E-01 4.06E-01 8.47E-01 1.36E+OO 2.71E+OO 2.71E+OO 40-69 1366000 80 2.41 4.58E-01 4.61E-02 6.78E-02 1.02E-01 1.20E-01 2.26E-01 3.04E-01 6.10E-01 9.95E-01 1.30E+OO 2.36E+OO 2.36E+OO 70 + 458000 26 2.88 3.34E-01 5.58E-02 3.48E-02 3.48E-02 4.58E-02 1.84E-01 2.73E-01 3.72E-01 9.95E-01 9:95E-01 1.46E+OO 1.46E+OO Season Fall 1239000 41 2.60 3.03E-01 2.97E-02 3.48E-02 4.58E-02 1.15E-01 2.09E-01 2.62E-01 3.53E-01 5.99E-01 7.14E-01 9.95E-01 9.95E-01 Spring 765000 78 1.66 4.38E-01 4.26E-02 5.81E-02 1.08E-01 1.18E-01 1.90E-01 3.26E-01 5.16E-01 9.19E-01 1.40E+OO 2.06E+OO 2.06E+OO Summer 1516000 51 3.33 5.85E-01 7.36E-02 6.7BE-02 1.27E-01 1.74E-01 2.24E-01 3.87E-01 8.22E-01 1.35E+OO 1.60E+OO 2.66E+OO 2.66E+OO Winter 732000 56 1.50 7.53E-01 8.86E-02 1.17E-01 1.84E-01 2.12E-01 2.73E-01 5.44E-01 9.48E-01 1.54E+OO 2.36E+OO 2.89E+OO 2.89E+OO Urbanization Central City 558000 19 0.99 . . . . . . . . . . . . Nonmetropolitan 2028000 126 4.50 4.81E-01 3.55E-02 8.42E-02 1.36E-01 1.74E-01 2.48E-01 3.53E-01 5.79E-01 1.04E+OO 1.36E+OO 1.89E+OO 2.89E+OO Suburban 1666000 81 1.92 5.13E-01 4.63E-02 6.78E-02 1.15E-01 1.34E-01 2.29E-01 3.87E-01 6.84E-01 9.95E-01 1.30E+OO 2.28E+OO 2.36E+OO Race Black 355000 19 1.63 . . . . . . . . . . White 3784000 203 2.40 4.95E-01 3.35E-02 3.48E-02 1.02E-01 1.33E-01 2.18E-01 3.26E-01 6.00E-01
9.99E-01 1.40E+OO 2.66E+OO 2.89E+OO ' Region Midwest 1004000 55 2.16 4.03E-01 7.24E-02 3.48E-02 4.58E-02 9.96E-02 1.40E-01 2.52E-01 3.53E-01 8.80E-01 1.54E+OO 2.71E+OO 2.89E+OO Northeast 241000 14 0.59 . . . . . . . . . . South 2449000 132 3.81 5.67E-01 4.30E-02 1.27E-01 1.74E-01 1.96E-01 2.62E-01 3.72E-01 6.82E-01 1.24E+OO 1.60E+OO 2.66E+OO 2.66E+OO West 558000 25 1.55 3.77E-01 5.70E-02 6.78E-02 6.78E-02 1.02E-01 2.18E-01 2.73E-01 4.79E-01 9.00E-01 9.40E-01 1.40E+OO 1.40E+OO Response to Questionnaire Households who garden 3980000 214 5.84 5.13E-01 3.39E-02 3.48E-02 1.02E-01 1.40E-01 2.28E-01 3.21E-01 6.28E-01 1.04E+OO 1.54E+OO 2.66E+OO 2.89E+OO Households who farm 884000 55 12.06 4.59E-01 5.83E-02 3.48E-02 4.58E-02 8.65E-02 2.08E-01 3.53E-01 5.16E-01 9.00E-01 1.40E+OO 1.60E+OO 2.89E+OO
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-53. Consumer Onlv Intake of Homeorown Peooers lo/ko-dav\ Population Ne Ne % Graue watd unwntd Con sum inn Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 5153000 208 2.74 Age 01-02 163000 6 2.86 . . . . . . . . . . . . 03-05 108000 5 1.33 . . . . . . . . . . . . 06-11 578000 26 3.46 2.26E-01 4.09E-02 0.00E+OO O.OOE+OO 3.03E-02 8.99E-02 1.62E-01 2.98E-01 4.25E-01 7.70E-01 B.45E-01 8.45E-01 12-19 342000 16 1.67 . . . . . . . . .. . . . 20-39 104BOOO 40 1.70 2.24E-01 6.10E-02 1.74E-02 3.26E-02 5.66E-02 8.55E-02 1.19E-01 2.18E-01 3.97E-01 6.24E-01 2.4BE+OO 2.4BE+OO 40-09 2221000 BB 3.92 2.50E-Oi 2.7BE-02 5.32E-03 3.40E-02 4.52E-02 7.5BE-02 1.66E-01 3.21E-01 4.77E-01 7.44E-D1 1.50E+OO 1.50E+OO 70+ 646000 25 . 4.07 2.56E-01 6.22E-02 1.73E-02 2.15E-02 2.30E-02 7.47E-02 1.38E-01 2.39E-01 9.24E-01 9.39E-01. 1.07E+OO 1.07E+OO Season Fall 1726000 53 3.62 1.97E-01 2.51E-02 0.00E+OO 3.26E-02 4.05E-02 B.55E-02 1.66E-01 2.39E-01 3.49E-01 3.97E-01 1.07E+OO 1.07E+OO Spring 255000 28 0.55 2.95E-01 7.15E-02 O.OOE+OO 1.73E-02 3.86E-02 6.93E-02 1.47E-01 3.21E-01 1.09E+OO 1.20E+OO 1.53E+OO 1.53E+OO Summer 2672000 94 5.87 Winter 500000 33 1.03 Urbanization Central City 865000 30 1.53 2.46E-01 4.23E-02 3.86E-02 5.66E-02 6.72E-02 1.10E-01 1.84E-01 2.73E-01 3.61E-01 9.39E-01 1.10E+OO 1.10E+OO Nonmetropolitan 1982000 89 4.40 2.42E-01 3.93E-02 5.32E-03 2.22E-02 3.34E-02 6.93E-02 1.19E-01 2.72E-01 5.37E-01 7.70E-01 2.4BE+OO 2.48E+OO Suburban 2246000 87 2.59 2.47E-01 3.00E-02 O.OOE+OO 2.70E-02 3.50E-02 8.55E-02 1.60E-01 2.91E-01 4.90E-01 9.73E-01 1.50E+OO 1.53E+OO Race Black 127000 6 0.58 . . . . . . . . . . . White 4892000 198 3.11 2.47E-01 2.23E-02 1.74E-02 2.96E-02 4.05E-02 8.55E-02 1.54E-01 2.91E-01 4.90E-01 9.24E-01 1.81E+OO 2.48E+OO Region Midwest 1790000 74 3.86 2.34E-01 4.06E-02 5.32E-03 2.22E-02 3.26E-02 5.98E-02 1.47E-01 2.57E-01 3.90E-01 8.45E-01 2.48E+OO 2.48E+OO Northeast 786000 31 1.91 South 1739000 72 2.70 2.30E-01 2.89E-02 3.34E-02 6.74E-02 7.60E-02 1.07E-01 1.66E-01 2.73E-01 4.25E-01 5.26E-01 1.81E+OO 1.81E+OO West 77BOOO 29 2.16 2.13E-01 5.04E-02 1.73E-02 2.30E-02 2.70E-02 4.05E-02 8.5BE-02 2.53E-01 5.37E-01 9.24E-01 1.07E+OO 1.07E+OO Response to Questionnaire Households who garden 4898000 199 7.19 2.35E-01 2.09E-02 O.OOE+OO 2.22E-02 3.40E-02 7.58E-02 1.54E-01 2.85E-01 4.77E-01 8.45E-01 1.50E+OO 2.48E+OO Households who farm 867000 35 11.83 3.03E-01 7.50E-02 O.OOE+OO 2.70E-02 2.96E-02 7.11E-02 1.66E-01 3.55E-01 6.00E-01 8.45E-01 2.48E+OO 2.48E+OO
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE= standard error P = percentile of the distribution Ne wgtd = weighted number of consumers; Ne unwgtd = unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-54. Consumer Onlv Intake of Home Produced Pork (a/ka-davl Population -Ne Ne % Grouo watd unwatd Consumina Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 1732000 121 0.92 1.23E+OO 9.63E-02 9.26E-02 1.40E-01 3.05E-01 5.41E-01 8.96E-01 1.71E+OO 2.73E+OO 3.37E+OO 4.93E+OO 7.41E+OO Age 01-02 38000 5 0.67 . . . . . . . . . . . . 03-05 26000 3 0.32 . . . . . . . . . . . . 06-11 129000 11 0.77 . . . . . . . . . . . . 12-19 291000 20 1.42 1.28E+OO 2.42E-01 3.05E-01 3.23E-01 3.37E-01 5.24E-01 8.85E-01 1.75E+OO 3.69E+OO 3.69E+OO 4.29E+OO 4.29E+OO 20-39 511000 32 0.83 1.21E+OO 1.80E-01 1.11E-01 2.83E-01 . 4.09E-01 5.52E-01 7.89E-01 1.43E+OO 2.90E+OO 3.08E+OO 4.93E+OO 4.93E+OO 40-<39 557000 38 0.98 1.02E+OO 1.15E-01 1.19E-01 1.81E-01 2.22E-01 4.05E-01 8.11E-01 1.71E+OO 1.78E+OO 2.28E+OO 3.16E+OO 3.16E+OO 70+ 180000 12 1.13 . . . . . . . . . . Season Fall 362000 13 0.76 . . . . . . . . . . . Spring 547000 59 1.19 1.13E+OO 1.29E-01 1.11E-01 1.40E-01 2.22E-01 3.52E-01 8.96E-01 1.50E+OO 2.68E+OO 3.68E+OO 4.29E+OO 4.29E+OO Summer 379000 15 0.83 . . . .. . . . . . . Winter 444000 34 0.91 1.40E+OO 2.39E-01 1.26E-01 2.58E-01 3.77E-01 5.03E-01 8.83E-01 2.21E+OO 3.08E+po 4.93E+OO 7.41E+OO 7.41E+OO Urbanization Central City 90000 2 0.16 . . . . . . . . . . . Nonmetropolitan 1178000 77 2.62 1.39E+OO .1.31E-01 9.26E-02 2.15E-01 4.05E-01 6.17E-01 9.66E-01 1.75E+OO 3.16E+OO 3.69E+OO 4.93E+oo 7.41E+OO Suburban 464000 42 0.54 8.77E-01 1.20E-01 1.11E-01 1.19E-01 1.81E-01 3.31E-01 5.89E-01 1.10E+OO 2.28E+OO 2.73E+OO 2.90E+OO 2.90E+OO Race Black 0 0 0.00 White 1732000 121 1.10 1.23E+OO 9.63E-02 9.26E-02 1.40E-01 3.05E-01 5A1E-01 8.96E-01 1.71E+OO 2.73E+OO 3.37E+OO 4.93E+OO 7.41E+OO Region Midwest 844000 64 1.82 1.06E+OO 1.19E-01 9.26E-02 1.19E-01 2.13E-01 5.02E-01 6.72E-01 1.20E+OO 2.68E+OO 3.37E+OO 3.69E+OO 3.73E+OO Northeast 97000 5 0.24 . . . . . . . . . . . South 554000 32 0.86 1.35E+OO 1.46E-01 1.81E-01 2.58E-01 3.37E-01 8.11E-01 1.26E+OO 1.75E+OO 2.44E+OO 3.08E+OO 4.29E+OO 4.29E+OO . West 237000 20 0.66 1.15E+OO 3.Q9E-01 1.26E-01 3.23E-01 3.77E-01 4.40E-01 7.29E-01 1.10E+OO 1.75E+OO 2.73E+OO 7.41E+OO 7.41E+OO Response to Questionnaire Households who raise animals 1428000 100 14.14 1.34E+OO 9.86E-02 1.40E-01 3.23E-01 4.05E-01 5.89E-01 9.66E-01 1.75E+OO 2.90E+OO 3.37E+OO 4.29E+OO 4.93E+OO Households who farm 1218000 82 16.62 1.30E+OO 1.11E-01 2.15E-01 3.42E-01 4.08E-01 5.85E-01 9.24E-01 1.71E+OO 3.08E+OO 3.69E+OO 4.93E+OO 4.93E+OO
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-55. Consumer Onlv Intake of Home Produced Poultrv (g/kg-dav) Population Ne Ne % Groun watd unwatd Consumina Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 1816000 105 0.97 1.57E+OO 1.15E-01 1.95E-01 3.03E-01 4.1BE-01 6.37E-01 1.23E+OO 2.19E+OO 3.17E+OO 3.B3E+OO 5.33E+OO 6.17E+OO Age 01-02 91000 B 1.60 . . . . . . . . . . . . 03-05 70000 5 0.86 . . . . . . . . . . . 06-11 205000 12 1.23 . . . . . . . . . . . . 12-19 194000 12 0.95 . . . . . . . . . . 20-39 574000 33 0.93 1.17E+OO . 1.47E-01 1.73E-01 4.02E-01 4.02E-01 5.57E-01 1.15E+OO 1.37E+OO 1.80E+OO 2.93E+OO 4.59E+OO 4.59E+OO 40-69 568000 30 1.00 1.51E+OO 2.43E-01 1.95E-01 1.97E-01 3.03E-01 4.91E-01 7.74E-01 2.69E+OO 3.29E+OO 4.60E+OO 5.15E+OO 5.15E+OO 70+ 80000 3 0.50 . . . . . . . . . . . . Season Fall 562000 23 1.18 1.52E+OO 1.75E-01 4.07E-01 4.18E-01 4.60E-01 8.11E-01 1.39E+OO 2.23E+OO 2.69E+OO 3.17E+OO 3.17E+OO 3.17E+OO s"pring 374000 34 0.81 1.87E+OO 2.79E-01 1.73E-01 2.28E-01 3.03E-01 5.22E-01 1.38E+OO 3.29E+OO 4.60E+OO 5.15E+OO 5.33E+OO 5.33E+OO Summer 312000 11 0.69 . . . . . . . . . . . Winter 568000 37 1.17 1.55E+OO 2.00E-01 1.95E-01 1.97E-01 4.33E-01 5.95E-01 1.23E+OO 2.18E+OO 2.95E+OO 3.47E+OO 6.17E+OO 6.17E+OO Urbanization Central City 230000 8 0.41 . . . . . . . . . . . Nonmetropolitan 997000 56 2.21 1.48E+OO 1.32E-01 1.95E-01 2.82E-01 4.07E-01 6.72E-01 1.19E+OO 2.10E+OO 3.17E+OO 3.29E+OO 3.86E+OO 5.33E+OO Suburban 589000 41 0.68 1.94E+OO 2.30E-01 2.28E-01 2.67E-01 4.33E-01 6.24E-01 1.59E+OO 2.69E+OO 4.59E+OO 4.83E+OO 6.17E+OO 6.17E+OO Race Black 44000 2 0.20 . . . . . . . . . White 1772000 103 1.12 1.57E+OO 1.17E-01 1.95E-01 3.03E-01 4.18E-01 6.24E-01 1.23E+OO 2.19E+OO 3.17E+OO 3.86E+OO 5.33E+OO 6.17E+OO Region Midwest 765000 41 1.65 1.60E+OO 1.40E-01 4.07E-01 4.18E-01 5.57E-01 9.79E-01 1.39E+OO 2.19E+OO 2.70E+OO 3.17E+OO 3.86E+OO 5.33E+OO Northeast 64000 4 0.16 . . . . . . . . . . South 654000 38 1.02 1.67E+OO 2.50E-01 1.73E-01 1.97E-01 3.03E-01 4.60E-01 9.08E-01 2.11E+OO 4.59E+OO 4.83E+OO 6.17E+OO 6.17E+OO West 333000 22 0.92 1.24E+OO 1.80E-01 2.67E-01 2.67E-01 4.27E-01 5.60E-01 1.02E+OO 1.89E+OO 2.45E+OO 2.93E+OO 2.93E+OO 2.93E+OO Response to Questionnaire Households who raise animals 1333000 81 13.20 1.58E+OO 1.18E-01 2.28E-01 4.07E-01 4.72E-01 7.09E-01 1.37E+OO 2.19E+OO 2.93E+OO 3.29E+OO 5.33E+OO 6.17E+OO Households who farm 917000 59 12.51 1.54E+OO 1.79E-01 1.95E-01 2.28E-01 3.03E-01 5.95E-01 1.06E+OO 2.18E+OO 3.47E+OO 4.83E+OO 6.17E+OO 6.17E+OO *Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd; weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-56. Consumer Onlv Intake of Honiearown Pumakins la/ka-davl Population Ne Ne % Grouo watd unwotd Consuminn Mean SE P1 PS P10 P25 PSO P75 P90 P95 P99 P100 Total 2041000 87 1.09 7.78E-01 6.83E-02 1.25E-01 1.84E-01 2.41E-01 3.18E-01 5.SSE-01 1.07E+OO 1.47E+OO 1.79E+OO 3.02E+OO 4.48E+OO Age 01-02 73000 4 1.28 . . . . . . . . . . . . 03-05 18000 2 0.22 . . . . . . . . . . . . 06-11 229000 9 1.37 . . . . . . . . . . . . 12-19 244000 10 1.19 . . . . . . . . . . . 20-39 657000 . 26 1.07 8.01E-01 1.29E-01 1.76E-01 1.84E-01 3.01E-01 3.77E-01 4.77E-01 1.03E+OO 1.73E+OO 2.67E+OO 2.67E+OO 2.67E+OO 40-69 415000 20 0.73 8.22E-01 1.57E-01 2.86E-01 2.86E-01 3.16E-01 3.71E-01 5.23E-01 9.62E-01 1.47E+OO 3.02E+OO 3.02E+OO 3.02E+OO 70 + 373000 15 2.35 . . . . . . . . . . . . Season Fall 1345000 49 2.82 8.19E-01 8.91E-02 1.25E-01 1.76E-01 2.81E-01 3.71E-01 6.14E-01 1.17E+OO 1.73E+OO 1.79E+OO 3.02E+OO 3.02E+OO Spring 48000 6 0.10 . . . . . . . . . . Summer 405000 13 0.89 . . . . . . . . . . Winter 243000 19 0.50 . . . . . . . . Urbanization Central City 565000 20 1.00 6.29E-01 1.08E-01 1.84E-01 1.84E-01 2.41E-01 2.81E-01 3.77E-01 9.40E-01 1.24E+OO 1.33E+OO 2.24E+OO 2.24E+OO Nonmetropolitan 863000 44 1.92 6.44E-01 9.64E-02 1.25E-01 1.65E-01 1.89E-01 3.10E-01 5.10E-01 6.65E-01 1.22E+OO 1.45E+OO 4.48E+OO 4.48E+OO Suburban 613000 23 0.71 1.10E+OO 1.34E-01 2.86E-01 2.88E-01 3.01E-01 4.67E-01 1.04E+OO 1.47E+OO 1.79E+OO 2.67E+OO 2.67E+OO 2.67E+OO Race Black 22000 1 0.10 . . . . . . . . . . White 2019000 86 1.28 7.82E-01 6.90E-02 1.25E-01 1.84E-01 2.41E-01 3.16E-01 5.SSE-01 1.10E+OO 1.47E+OO 1.79E+OO 3.02E+OO 4.48E+OO Region Midwest 1370000 54 2.95 8.21E-01 9.68E-02 1.25E-01 2.34E-01 2.41E-01 3.18E-01 5.72E-01 1.04E+OO 1.73E+OO 2.67E+OO 3.02E+OO 4.48E+OO Northeast 15000 1 0.04 . . . . . . . . . . South 179000 10 0.28 . . . . > . . . . West 477000 22 1.32 7.87E-01 9.65E-02 1.76E-01 1.89E-01 3.08E-01 3.71E-01 7.44E-01 1.17E+OO 1.47E+OO 1.51E+OO 1.51E+OO 1.51E+OO Response to Questionnaire Households who garden 1987000 85 2.92 7.70E-01 6.93E-02 1.25E-01 1.B4E-01 2.41E-01 3.16E-01 5.SSE-01 1.04E+OO 1.46E+OO 1.79E+OO 3.02E+OO 4.48E+OO Households who farm 449000 18 6.13 . . . . . . . . . . .
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd = unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-57. Consumer Onlv Intake of Homearown Snao Beans la/ka-dav\ Population Ne Ne % Grouo watd unwatd Consumina Mean SE P1 P5 P10 P25 P50 P75
P90 P95 P99 P100 Total 12308000 739 6.55 8.00E-01 3.02E-02 5.65E-02 1.49E-01 1.88E-01 3.38E-01 5.69E-01 1.04E+OO 1.58E+OO 2.01E+OO 3.90E+OO 9.96E+OO Age 01-02 246000 17 4.32 . . . . . . . . . . . . 03-05 455000 32 5.62 1.49E+OO 2.37E-01 O.OOE+OO 0.00E+OO 3.49E-01 9.01E-01 1.16E+OO 1.E;6E+OO 3.20E+OO 4.88E+OO 6.90E+OO 6.90E+OO 06-11 862000 62 5.16 8.97E-01 1.15E-01 O.OOE+OO 1.99E-01 *2.21E-01 3.21E-01 6.42E-01 1.21E+OO 1.79E+OO 2.75E+OO 4.81E+OO 5.66E+OO 12-19 1151000 69 5.62 6.38E-01 6.10E-02 0.00E+OO 1.61E-01 2.22E-01 3.20E-01 5.04E-01 8.11E-01 1.34E+OO 1.79E+OO 2.72E+OO 2.72E+OO 20-39 2677000 160 4.35 6.13E-01 4.09E-02 7.05E-02 1.31E-01 1.57E-01 2.60E-01 4.96E-01 7.85E-01 1.24E+OO 1.64E+OO 2.05E+OO 4.26E+OO 40-69 4987000 292 8.79 7.19E-01 3.20E-02 9.99E-02 *1.61E-01 2.28E-01 3.62E-01 5.61E-01 8.59E-01 1.45E+OO 1.77E+OO 2.70E+OO 4.23E+OO 70 + 1801000 100 11.34 9.15E-01 1.16E-01 5.65E-02 7.44E-02 1.51E-01 3.69E-01 6.38E-01 1.22E+OO 1.70E+OO 2.01E+OO 9.96E+OO 9.96E+OO Season Fall 3813000 137 8.00 8.12E-01 *8.19E-02 5.65E-02 1.50E-01 1.83E-01 2.72E-01 5.39E-01 1.18E+OO 1.52E+OO 2.01E+OO 4.82E+OO 9.96E+OO *Spring 2706000 288 5.86 9.00E-01 5.44E-02 2.93E-02 1.51E-01 2.19E-01 3.70E-01 5.91E-01 1.11E+OO 1.72E+OO 2.85E+OO 5.66E+OO 6.90E+OO Summer 2946000 98 6.48 6.33E-01 4.81E-02 O.OOE+OO 1.18E-01 1.57E-01 3.31E-01 5.04E-01 8.50E-01 1.30E+OO 1.70E+OO 2.05E+OO 2.63E+OO Winter 2843000 216 5.84 8.64E-01 5.28E-02
1.14E-01 1.80E-01 2.44E-01 4.24E-01 6.20E-01 1.12E+OO 1.72E+OO 2.02E+OO 3.85E+OO 7.88E+OO Urbanization Central City 2205000 78 3.91 5.97E-01 5.59E-02 5.65E-02 7.44E-02 1.59E-01 2.56E-01 5.12E-01 7.12E-01 1.23E+OO 1.54E+OO 1.93E+OO 3.35E+OO Nonmetropolitan 5696000 404 12.65 9.61E-01 5.06E-02 9.35E-02 1.77E-01 2.29E-01 3.67E-01 6.75E-01 1.19E+OO 1.89E+OO 2.70E+OO 4.88E+OO 9.96E+OO Suburban 4347000 255 5.02 7.04E-01 3.76E-02 9.67E-02 1.39E-01 1.88E-01 3.41 E-01 5.20E-01 9.32E-01 1.36E+OO 1.77E+OO 2.98E+OO 6.08E+OO Race Black 634000 36 2.92 7.55E-01 1.43E-01 2.51E-01 2.51E-01 2.79E-01 2.99E-01 4.78E-01 1.04E+OO 1.30E+OO 1.34E+OO 5.98E+OO 5.98E+OO Vvhite 11519000 694 7.31 8.10E-01 3.12E-02 7.05E-02 1.50E-01 1.89E-01 3.49E-01 5.73E-01 1.06E+OO 1.63E+OO 2.01E+OO 3.90E+oo* 9.96E+OO Region Midwest 4651000 307 10.02 8.60E-01 6.11E-02 7.44E-02 1.54E-01 1.89E-01 3.36E-01 5.50E-01 9.88E-01 1.70E+OO 2.47E+OO 4.88E+OO 9.96E+OO Northeast 990000 52 2.40 5.66E-01 6.63E-02 0.00E+OO 9.66E-02 1.06E-01 1.81E-01 4.91E-01 8.15E-01 1.28E+OO 1.36E+OO 1.97E+OO 3.09E+OO South 4755000 286 7.39 8.82E-01 4.04E-02 1.33E-01 2.13E-01 2.51E-01 3.98E-01 6.75E-01 1.22E+OO 1.72E+OO 2.01E+OO 3.23E+OO 5.98E+OO West 1852000 92 5.14 5.92E-01 4.35E-02 7.05E-02 1.43E-01 1.83E-01 2.72E-01 5.14E-01 7.41E-01 1.20E+OO 1.52E+OO 2.19E+OO 2.19E+OO Response to Questionnaire Households who garden 11843000 700 17.38 7.90E-01 3.08E-02 5.65E-02 1.49E-01 1.87E-01 3.31E-01 5.63E-01 1.02E+OO 1.60E+OO 2.01E+OO 3.85E+OO 9.96E+OO Households who farm 2591000 157 35.35 7.95E-01 4.78E-02 5.65E-02 1.27E-01 1.89E-01 4.05E-01 6.59E-01 1.12E+OO 1.54E+OO 1.98E+OO 2.96E+OO 4.23E+OO
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd = weighted number of consumers; Ne unwgtd = unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-58. Consumer Onlv Intake of Homearown Strawberries la/ka-dav\ Population Ne Ne % Graue watd unwatd Consuminn Mean SE P1 PS P10 P25 P50 P75 P90 P95 P99 P100 Total 2057000 139 1.09 6.52E-01 5.15E-02 4.15E-02 8.16E-02 1.18E-01 2.55E-01 4.67E-01 8.20E-01 1.47E+OO 1.77E+OO 2.72E+OO 4.83E+oo Age 01-02 30000 2 0.53 . . . . . . . . . . . . 03-05 66000 6 0.81 . . . . . . . . . . . . 06-11 153000 15 0.92 . . . . . . . . . . . . 12-19 201000 11 0.98 . . . . . . . . . . 20-39 316000 22 0.51 3.21E-01 6.41E-02 7.92E-02 8.16E-02 1.05E-01 1.18E-01 2.05E-01 4.59E-01 8.20E-01 9.73E-01 1.56E+OO 1.56E+OO 40-69 833000 55 1.47 6.44E-01 6.37E-02 2.44E-02 6.53E-02 1.75E-01 3.55E-01 5.83E-01 9.41 E-01 1.42E+OO 1.47E+OO 2.37E+OO 2.37E+OO 70+ 449000 27 2.83 6.36E-01 1.11E-01 4.15E-02 4.41E-02 8.64E-02 2.62E-01 4.69E-01 7.00E-01 1.66E+OO 1.89E+OO 2.72E+OO 2.72E+OO Season Fall 250000 8 0.52 . . . . . . . . . Spring 598000 66 1.30 8.30E-01 1.03E-01 7.92E-02 8.92E-02 1.80E-01 2.75E-01 4.69E-01 9.73E-01 1.93E+OO 2.54E+OO 4.83E+OO 4.83E+OO Summer 388000 11 0.85 . . . . . . . . . . Winter 821000 54 1.69 5.13E-01 6.42E-02 2.44E-02 4.41E-02 1.05E-01 2.07E-01 3.86E-01 6.01E-01 1.27E+OO 1.46E+OO 2.37E+OO 2.37E+OO Urbanization Central City 505000 23 0.90 7.54E-01 1.22E-01 4.15E-02 4.41E-02 8.92E-02 3.82E-01 4.88E-01 1.33E+OO 1.47E+OO 1.69E+OO 2.37E+OO 2.37E+OO Nonmetropolitan 664000 52 1.47 6.18E-01 1.05E-01 2.44E-02 6.53E-02 8.16E-02 1.25E-01 3.85E-01 8.14E-01 1.66E+OO 2.16E+OO 4.83E+OO 4.83E+OO Suburban. 888000 64 1.03 6.20E-01 5.88E-02 7.92E-02 1.81E-01 2.21E-01 3.45E-01 5.30E-01 6.96E-01 1.27E+OO 1.56E+OO 2.97E+OO 2.97E+OO Race Black o o 0.00 White 2057000 139 1.31 6.52E-01 5.15E-02 4.15E-02 8.16E-02 1.18E-01 2.55E-01 4.67E-01 8.20E-01 1.47E+OO 1.77E+OO 2.72E+OO 4.83E+OO Region Midwest 1123000 76 2.42 6.85E-01 8.28E-02 2.44E-02 6.53E-02 8.16E-02 1.82E-01 4.16E-01 1.00E+OO 1.66E+OO 1.93E+OO 2.97E+OO 4.83E+OO Northeast 382000 25 0.93 6.35E-01 1.01E-01 8.92E-02 1.59E-01 1.82E-01 2.55E-01 4.67E-01 8.65E-01 1.46E+OO 1.83E+OO 2.16E+OO 2.16E+OO South 333000 23 0.52 6.69E-01 8.41E-02 1.33E-01 2.05E-01 3.77E-01 5.15E-01 6.21E-01 6.96E-01 1.00E+OO 1.00E+OO 2.72E+OO 2.72E+OO West 219000 15 0.61 . . . . . . . . Response to Questionnaire Households who garden 1843000 123 2.70 6.37E-01 5.48E-02 4.15E-02 7.92E-02 1.18E-01 2.28E-01 4.53E-01 8.20E-01 1.46E+OO 1.77E+OO 2.54E+OO 4.83E+OO Households who farm 87000 9 1.19 . . . . . . . . . . . .
Intake data not provided for subpopulations for which there were less than 20 observation's NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-59. Consumer Only Intake of Homeqrown Tomatoes (q/kq-day) Population Ne Ne % Grouo wold unwotd Consumina Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 16737000 743 8.90 1.18E+OO 5.26E-02 7.57E-02 1.52E-01 2.34E-01 3.92E-01 7.43E-01 1.46E+OO 2.50E+OO 3.54E+OO 7.26E+OO 1.93E+01 Age 01-02 572000 26 10.04 3.14E+OO 5.30E-01 7.26E-01 8.55E-01 9.34E-01 1.23E+OO 1.66E+OO 4.00E+OO 7.26E+OO 1.07E+01 1.07E+01 1.07E+01 03-05 516000 26 6.37 1.61E+OO 2.65E-o1 4.96E-01 5.07E-01 5.07E-01 7.54E-01 1.25E+OO 1.65E+OO 3.00E+OO 6.25E+OO 6.25E+OO 6.25E+OO 06-11 109JOOO 51 6.54 1.63E+OO 2.68E-01 2.17E-01 3.10E-01 3.92E-01 5.30E-01 7.55E-01 1.66E+OO 5.20E+OO 5.70E+OO 9.14E+OO 9.14E+OO 12-19 1411000 61 6.89 7.15E-01 8.52E-02 0.00E+OO 0.00E+OO 1.82E-01 2.68E-01 5.21E-01 8.50E-01 1.67E+OO 1.94E+OO 3.39E+OO 3.39E+OO 20-39 4169000 175 6.77 8.54E-01 1.03E-Q1 7.32E-02 1.31E-01 1.47E-01 2.54E-01 5.15E-01 1.00E+OO 1.83E+OO 2.10E+OO 5.52E+OO 1.93E+01 40-69 6758000 305 11.92 1.05E+OO 5.23E-02 1.13E-01 1.73E-01 2.81E-01 3.97E-01 7.46E-01 1.41E+OO 2.40E+OO 3.05E+OO 4.50E+OO 5.00E+OO 70 + 1989000 89 12.53 1.26E+OO 9.40E-02 1.13E-01 2.36E-01 2.98E-01 4.82E-01 1.14E+OO 1.77E+OO 2.51E+OO 2.99E+OO 3.67E+OO 3.67E+OO Season Fall 5516000* 201 11.57 1.02E+OO 8.55E-02 7.32E-02 1.35E-01 2.23E-01 3.43E-01 5.95E-01 1.34E+OO 2.24E+OO 2.87E+OO 6.25E+OO 1.07E+01 Spring 1264000 127 2.74 8.39E-01 6.26E-02 1.36E-01 1.89E-01 2.39E-01 3.73E-01 6.31E-01 1.11E+OO 1.75E+OO 2.00E+OO 3.79E+OO 5.28E+OO Summer 8122000 279 17.86 1.30E+OO 8.75E-02* 1.05E-01 1.66E-01 2.36E-01 4.08E-01 8.03E-01 1.55E+OO 3.05E+OO 4.05E+OO 7.26E+OO 1.09E+01 Winter 1835000 136 3.77 1.37E+OO 1.77E-01 9.07E-02 2.07E-01 2.85E-01 4.97E-01 8.29E-01 1.49E+OO 2.48E+OO 3.38E+OO 8.29E+OO 1.93E+01 Urbanization Central City 2680000 90 4.76 1.10E+OO 1.27E-01 O.OOE+OO 1.52E-01 2.25E-01 3.54E-01 7.54E-01 1.51E+OO 2.16E+OO 2.95E+OO 7.26E+OO 8.29E+OO Nonmetropolitan 7389000 378 16.41 1.26E+OO 7.35E-02 1.13E-01 2.16E-01 2.62E-01 4.23E-01 7.62E-01 1.47E+OO 2.77E+OO 3.85E+OO 6.87E+OO 1.07E+01 Suburban 6668000 275 7.70 1.13E+OO 9.14E-02 7.57E-02 1.35E-01 1.78E-01 3.70E-01 6.68E-01 1.38E+OO 2.35E+OO 3.32E+OO 5.52E+OO 1.93E+01 Race Black 743000 28 3.42 6.14E-01 8.60E-02 O.OOE+OO O.OOE+OO 7.32E-02 2.36E-01 5.07E-01 9.02E-01 1.18E+OO 1.55E+OO 1.66E+OO 1.66E+OO White 15658000 703 9.94 1.22E+OO 5.54E-02 1.05E-01 1.68E-01 2.41E-01 4.06E-01 7.55E-01 1.49E+OO 2.55E+OO 3.59E+OO 7.26E+OO 1.93E+01 Region Midwest 6747000 322 14.54 1.18E+OO 8.91E-02 6.34E-02 1.45E-01 2.06E-01 3.62E-01 6.82E-01 1.41E+OO 2.51E+OO 3.69E+OO 6.87E+OO 1.93E+01 Northeast 2480000 87 6.02 1.17E+OO 1.64E-01 7.57E-02 1.35E-Q1 1.48E-01 3.50E-01 7.51E-01 1.38E+OO 2.44E+OO 3.52E+OO 1.09E+01 1.09E+01 South 4358000 202 6.77 1.15E+OO 9.07E-02 0.00E+OO 2.07E-01 2.53E-01 4.23E-01 7.46E-01 1.43E+OO 2.32E+OO 3.67E+OO 6.82E+OO 9.14E+OO West 3152000 132 8.74 1.23E+OO 9.90E-02 1.80E-01 2.39E-01 2.84E-01 4.11E-01 7.65E-01 1.84E+OO
2.78E+OO 3.08E+OO 7.26E+OO 7.26E+OO Response to Questionnaire Households who garden 14791000 661 21.70 1.21E+OO 5.70E-02 7.57E-02 1.52E-01 2.34E-01 4.06E-01 7.58E-01 1.50E+OO 2.51E+OO 3.52E+OO 7.26E+OO 1.93E+01 Households who farm 2269000 112 30.96 1.42E+OO 1.58E-01 0.00E+OO 1.80E-01 2.26E-01 4.23E-01 7.66E-01 1.86E+OO 3.55E+OO 5.20E+OO 9.14E+OO 9.14E+OO NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-60. Consumer Only Intake of Homegrown White Potatoes lo/ka-day) Population Ne Ne % Grouo watd unwatd Consumino Mean SE P1 PS P10 P25 PSO P75 P90 P95 P99 P100 Total 5895000 281 3.14 1.66E+OO 1.0SE-01 0.00E+OO 1.87E-01 3.08E-01 5.SOE-01 1.27E+OO 2.07E+OO 3.11E+OO 4.76E+OO 9.52E+OO 1.28E+01 Age 01-02 147000 10 2.58 . . . . . . . . . 03-05 119000 6 1.47 . . . . . . . . 06-11 431000 24 2.58 2.19E+OO 3.85E-01 O.OOE+OO 0.00E+OO 4.10E-01 7.20E-01 1.76E+OO 3.10E+OO 5.94E+OO 6.52E+OO 6.52E+OO 6.52E+OO 12-19 751000 31 3.67 1.26E+OO 1.85E-01 6.67E-02 1.87E-01 2.59E-01 3.84E-01 1.22E+OO 1.80E+OO 2.95E+OO 3.11E+OO 4.14E+OO 4.14E+OO 20-39 1501000 66 2.44 1.24E+OO f21E-01 1.64E-01 1.64E-01 1.96E-01 4.77E-01 1.00E+OO 1.62E+OO 2.54E+OO 3.08E+OO 4.29E+OO 5.09E+OO 40-69 1855000 95 3.27 1.86E+OO 2.29E-01 1.27E-01 2.62E-01 3.SOE-01 6.99E-01 1.31E+OO 2.04E+OO 3.43E+OO 5.29E+OO 1.28E+01 1.28E+01 70+ 1021000 45 6.43 1.27E+OO 1.22E-01 2.06E-01 2.17E-01 3.57E-01 5.SOE-01 1.21E+OO 1.69E+OO 2.35E+OO 2.88E+OO 3.92E+OO 3.92E+OO Season Fall 2267000 86 4.76 1.63E+OO 2.23E-01 1.64E-01 2.23E-01 2.65E-01 4.61E-01 1.13E+OO 1.79E+OO 3.43E+OO 4.14E+OO 1.28E+01 1.28E+01 Spring 527000 58 1.14 1.23E+OO 1.28E-01 6.67E-02 1.0SE-01 1.96E-01 4.10E-01 8.SSE-01 1.91E+OO 2.86E+OO 3.08E+OO 4.28E+OO 4.28E+OO Summer 2403000 81 5.28 1.63E+OO 1.82E-01 O.OOE+OO 1.87E-01 3.19E-01 6.20E-01 1.32E+OO 2.09E+OO 3.08E+OO 5.29E+OO 9.43E+OO 9.43E+OO Winter 698000 56 1.43 2.17E+OO 1.98E-01 1.41E-01 3.95E-01 4.97E-01 8.64E-01 2.02E+OO 2.95E+OO 4.26E+OO 5.40E+OO 6.00E+OO 6.00E+OO Urbanization Central City 679000 25 1.20 9.60E-01 1.51E-01 1.64E-01 1.64E-01 1.75E-01 3.75E-01 5.SSE-01 1.52E+OO 2.07E+OO 2.25E+OO 2.54E+OO 2.54E+OO Non metropolitan 3046000 159 ' 6.77 1.96E+OO 1.SSE-01 1.B4E-01 2.65E-01 3.68E-01 7.67E-01 1.SOE+OO 2.38E+OO 3.SSE+OO 5.64E+OO 1.28E+01 1.28E+01 Suburban 2110000 95 2.44 1.49E+OO 1.67E-01 1.0SE-01 1.87E-01 3.19E-01 5.40E-01 9.29E-01 1.68E+OO 3.11E+OO 4.76E+OO 9.43E+OO 9.43E+OO Race Black 140000 5 0.64 . . . . . . . . . . . White 5550000 269 3.52 1.67E+OO 1.09E-01 1.41E-01 2.06E-01 3.08E-01 5.SOE-01 1.28E+OO 2.09E+OO 3.11E+OO 4.76E+OO 9.52E+OO 1.28E+01 Region Midwest 2587000 133 5.58 1.77E+OO 1.47E-01 1.75E-01 2.36E-01 3.39E-01 6.41E-01 1.35E+OO 2.15E+OO 3.77E+OO 5.29E+OO 9.43E+OO 9.43E+OO Northeast 656000 31 1.59 1.28E+OO 2.04E-01 6.67E-02 1.27E-01 1.67E-01 3.48E-01 B.64E-01 1.97E+OO 2.95E+OO 3.80E+OO 5.09E+OO 5.09E+OO South 1796000 84 2.79 2.08E+OO 2.39E-01 1.64E-01 3.SOE-01 4.61E-01 9.24E-01 1.56E+OO 2.40E+OO 3.44E+OO 5.64E+OO 1.28E+01 1.28E+01 West 796000 31 2.21 7.61E-01 1.05E-01 1.64E-01 2.16E-01 2.59E-01 4.11E-01 5.43E-01 9.63E-01 1.40E+OO 1.95E+OO 3.11E+OO 3.11E+OO Response to Questionnaire Households who garden 5291000 250 7.76 1.65E+OO 1.09E-01 0.00E+OO 2.06E-01 3.08E-01 5.55E-01 1.28E+OO 2.09E+OO 3.10E+OO 4.28E+OO 9.52E+OO 1.28E+01 Households who farm 1082000 62 14.76 1.83E+OO 1.78E-01 6.67E-02 2.osE-01 5.76E-01 9.24E-01 1.46E+OO 2.31E+OO 3.80E+OO 5.09E+OO 6.52E+OO 6.52E+OO
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-61. Consumer Only Intake of Homegrown Exposed Fruit lalka-day) Population Ne Ne % Groun wntd unwatd Consuminn Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 11770000 679 6.26 1.49E+OO 8.13E-02 4.41E-02 1.37E-01 2.55E-01 4.46E-01 8.33E-01 1.70E+OO 3.16E+OO 4.78E+OO 1.20E+01 3.25E+01 Age 01-02 306000 19 5.37 . . . . . . . . . . . . 03-05 470000 30 5.80 2.60E+OO 7.78E-01 O.OOE+OO 0.00E+OO 3.73E-01 1.00E+OO 1.82E+OO 2.64E+OO 5.41E+OO 6.07E+OO 3.25E+01 3.25E+01 06-11 915000 68 5.48 2.52E+OO 4.24E-01 0.00E+OO 1.71E-01 3.73E-01 6.19E-01 1.11E+OO 2.91E+OO 6.98E+OO 1.1-7E+01 1.57E+01 1.59E+01 12-19 896000 50 4.37 1.33E+OO 2.06E-01 8.46E-02 1.23E-01 2.58E-01 4.04E-01 6.09E-01 2.27E+OO 3.41E+OO 4.78E+OO 5.90E+OO 5.90E+OO 20-39 2521000 139 4.09 1.09E+OO 1.44E-01 7.93E-02 1.30E-01 1.67E-01 3.04E-01 6.15E-01 1.07E+OO 2.00E+OO 3.58E+OO 1.29E+01 1.29E+01 40-69 4272000 247 7.53 1.25E+OO 1.10E-01 6.46E-02 1.64E-01 2.54E-01 4.39E-01 7.19E-01 1.40E+OO 2.61E+OO 3.25E+OO 1.30E+01 1.30E+01 70 + 2285000 118 14.39 1.39E+OO 1.17E-01 4.41E-02 2.07E-01 2.82E-01 5.71E-01 9.57E-01 1.66E+OO 3.73E+OO 4.42E+OO 5.39E+OO 7.13E+OO Season Fall 2877000 100 6.04 1.37E+OO 1.16E-01 2.59E-01 2.91E-01 3.42E-01 5.43E-01 1.03E+OO 1.88E+OO 2.88E+OO 4.25E+OO 5.41 E+OO 5.41E+OO Spring 2466000 265 5.34 1.49E+OO 1.51E-01 8.91E-02 1.98E-01 2.54E-01 4.32E-01 8.56E-01 1.65E+OO 2.91E+OO 4.67E+OO 8.27E+OO 3.25E+01 Summer 3588000 122 7.89 1.75E+OO 2.50E-01 O.OOE+OO 8.66E-02 1.30E-01 3.89E-01 6.41E-01 1.76E+OO 4.29E+OO 6.12E+OO 1.30E+01 1.57E+01 Winter 2839000 192 5.83 1.27E+OO 1.06E-01 4.15E-02 1.04E-01 2.31E-01 4.59E-01 8.29E-01 1.55E+OO 2.61E+OO 4.66E+OO 8.16E+OO 1.13E+01 Urbanization Central City 2552000 99 4.53 1.34E+OO 1.98E-01 4.41E-02 1.01E-01 2.59E-01 4.46E-01 8.63E-01 1.60E+OO 2.37E+OO 2.88E+OO 1.30E+01 1.30E+01 Non metropolitan 3891000 269 8.64 1.78E+OO 1.67E-01 6.46E-02 1.04E-01 1.67E-01 4.15E-01 9.42E-01 1.94E+OO 4.07E+OO 5.98E+OO 1.57E+01 3.25E+01 Suburban 5267000 309 6.08 1.36E+OO 9.00E-02 9.18E-02 2.07E-01 2.93E-01 4.69E-01 7.73E-01 1.65E+OO 3.16E+OO 4.67E+OO 7.29E+OO 1.29E+01 Race Black 250000 12 1.15 . . . . . . . . . . . White 11411000 663 7.24 1.51E+OO 8.33E-02 6.49E-02 1.55E-01 2.59E-01 4.49E-01 8.56E-01 1.72E+OO 3.31E+OO 4.78E+OO 1.20E+01 3.25E+01 Region Midwest 4429000 293 9.55 1.60E+OO 1.42E-01 4.41E"02 1.25E-01 2.23E-01 4.23E-01 8.78E-01 1.88E+OO 3.58E+OO 4.78E+OO 1.20E+01 3.25E+01 Northeast 1219000 69 2.96 -7.55E-01 1.18E-01 8.0SE-02 8.66E-02 1.65E-01 3.00E-01 4.74E-01 7.84E-01 1.39E+OO 2.86E+OO 5.21E+OO 1.13E+OO South 2532000 141 3.94 1.51E+OO 1.84E-01 7.93E-02 2.32E-01 3.01E-01 5.08E-01 9.16E-01 1.63E+OO 2.63E+OO 5.98E+OO 1.57E+01 1.57E+01 West 3530000 174 9.79 1.60E+OO 1.43E-01 1.00E-01 2.40E-01 3.17E-01 5.69E-01 9.57E-01 1.97E+OO 3.72E+OO 5.00E+OO 1.30E+01 1.30E+01 Response to Questionnaire Households who garden 10197000 596 14.96 1.55E+OO 9.12E-02 4.15E-02 1.58E-01 2.58E-01 4.49E-01 8.78E-01 1.73E+OO 3.41E+OO 5.00E+OO 1.29E+01 3.25E+01 Households who farm 1917000 112 26.16 2.32E+OO 2.50E-01 7.21E-02 2.76E-01 3.71E-01 6.81E-01 1.30E+OO 3.14E+OO 5.00E+OO 6.12E+OO 1.57E+01 1.57E+01
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of 1987-88 NFCS Table 13--02. Consumer Onlv Intake of Homearown Protected Fruits (a/ka-davl Population Ne Ne % Grouo watd unwotd Consumina Mean SE P1 PS P10 P25 PSO P75 P90 P95 P99 P100 Total 3855000 173 2.05 5.74E+OO 6.25E-01 1.SOE-01 2.66E-01 3.35E-01 9.33E-01 2.34E+OO 7.45E+OO 1.60E+01 1.97E+01 4.73E+01 5.36E+01 Age 01-02 79000 5 1.39 . . . . . . . . . . . . 03-05 80000 4 0.99 . . . . . . . . . . . . 06-11 181000 9 1.08 . . . . . . . . . . . . 12-19 377000 20 1.84 2.96E+OO 9.93E-01 1.17E-01 1.60E-01 2.83E-01 3.93E-01 1.23E+OO 2.84E+OO 7.44E+OO 1.14E+01 1.91E+01 1.91E+01 20-39 755000 29 1.23 4.51E+OO 1.08E+OO 1.81E-01 3.62E-01 4.87E-01 1.22E+OO 1.88E+OO 4.47E+OO 1.46E+01 1.61E+01 2.41E+01 2.41E+01 40-69 1702000 77 3.00 5.65E+OO 8.66E-01 1.12E-01 2.44E-01 2.87E-01 6.69E-01 2.22E+OO 9.36E+OO 1.55E+01 2.12E+01 4.13E+01 4.13E+01 70 + 601000 26 3.78 4.44E+OO 6.91E-01 2.62E-.01 2.62E-01 2.85E-01 1.95E+OO 3.29E+OO 7.06E+OO 8.97E+OO 9.97E+OO 1.52E+01 1.52E+01 Season Fall 394000 12 0.83 . . . . . . . . . . Spring 497000 36 1.08 2.08E+OO 3.47E-01 1.60E-01 1.81E-01 2.SSE-01 3.78E-01 1.22E+OO 4.08E+OO 5.10E+OO 6.57E+OO 6.79E+OO 6.79E+OO Summer 1425000 47 3.13 7.39E+OO 1.45E+OO 1.12E-01 -2.66E-01 3.93E-01 1.25E+OO 3.06E+OO 1.03E+01 1.66E+01 2.41E+01 5.36E+01 5.36E+01 Winter 1539000 78 3.16 6.24E+OO 9.10E-01 1.SOE-01 3.02E-01 3.76E-01 1.39E+OO 2.65E+OO 8.23E+OO 1.78E+01 2.12E+01 4.73E+01 4.73E+01 Urbanization Central City 1312000 50 2.33 3.94E+OO 5.80E-01 1.SOE-01 2.62E-01 3.33E-01 8.34E-01 3.01E+OO 5.01E+OO 9.23E+OO 9.97E+OO 1.88E+01 1.88E+01 Nonmetropolitan 506000 19 1.12 . . . . . . . . . . . . Suburban 2037000 104 2.35 6.83E+OO 9.38E-01 1.12E-01 2.53E-01 2.92E-01 5.94E-01 2.01E+OO 1.03E+01 1.79E+01 2.38E+01 5.36E+01 5.36E+01 Race Black 200000 8 0.92 . . . . . . . . . . . White 3655000 165 2.32 5.91E+OO 6.48E-01 1.17E-01 2.62E-01 3.33E-01 1.06E+OO 2.44E+OO 7.46E+OO 1.60E+01 2.12E+01 4.73E+01 5.36E+01 Region Midwest 657000 24 1.42 1.07E+01 2.60E+OO 2.53E-01 2.62E-01 2.85E-01 1.18E+OO 7.44E+OO 1.46E+01 2.41E+01 4.13E+01 5.36E+01 5.36E+01 Northeast 105000 5 0.26 . . . . . . . . . South 1805000 74 2:81 4.77E+OO 6.47E-01 1.60E-01 3.64E-01 4.SOE-01 1.23E+OO 2.54E+OO 5.10E+OO 1.52E+01 1.66E+01 2.38E+01 2.40E+01 West 1288000 70 3.57 4.85E+OO 9.26E-01 1.12E-01 1.81E-01 2.68E-01 4.94E-01 1.84E+OO 5.34E+OO . 1.23E+01 1.88E+01 4.73E+01 4.73E+01 Response to Questionnaire Households who garden 3360000 146 4.93 5.90E+OO 6.97E-01 1.17E-01 2.65E-01 3.35E-01 1.16E+OO 2.42E+OO 7.46E+OO 1.60E+01 1.91E+01 4.73E+01 5.36E+01 Households who farm 357000 14 4.87 . . . . . . . . . . . .
Intake data not provided for subpopulations for which there were Jess than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd =.weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-63. Consumer Onlv Intake of Homearown Exoosed Veaetables (a/kg-davl Population Ne Ne % Groua watd unwatd Consumina Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 28762000 1511-15.30 1.52E+OO 5.10E-02 3.25E-03 9.15E-02 1.72E-01 3.95E-01 8.60E-01 1.83E+OO 3.55E+OO 5.12E+OO 1.03E+01 2.06E+01 Age 01-02 815000 43 14.30 3.48E+OO 5.14E-01 2.28E-02 2.39E-01 8.34E-01 1.20E+OO 1.89E+OO 4.23E+OO 1.07E+01 1.19E+01 1.21E+01 1.21E+01 03-05 1069000 62 13.19 1.74E+O.O 2.20E-01 0.00E+OO 7.23E-03 4.85E-02 5.79E-01 1.16E+OO 2.53E+OO 3.47E+OO 6.29E+OO 7.36E+OO 8.86E+OO 06-11 2454000 134 14.68 1.39E+OO 1.76E-01 0.00E+OO 4.44E-02 9.42E-02 3.12E-01 6.43E-01 1.60E+OO 3.22E+OO 5.47E+OO 1.33E+01 1.33E+01 12-19 2611000 143 12.74 1.07E+OO 9.43E-02 O.OOE+OO 2.92E-02 1.42E-01 3.04E-01 6.56E-01 1.46E+OO 2.35E+OO 3.78E+OO 5.67E+OO 5.67E+OO 20-39 6969000 348 11.31 1.05E+OO 8.14E-02 8.20E-03 6.56E-02 1.17E-01 2.55E-01 5.58E-01 1.26E+OO 2.33E+OO 3.32E+OO 7.57E+OO 2.06E+01 40-69 10993000 579 19.38 1.60E+OO 8.32E-02 3.25E-03 1.41E-01 2.44E-01 4.79E-01 9.81E-01 1.92E+OO 3.59E+OO 5.22E+OO 8.99E+OO 1.90E+01 70 + 3517000 185 22.15 1.68E+OO 1.21E-01 5.21E-03 1.51E-01 2.39E-01 5.22E-01 1.13E+OO 2.38E+OO 4.08E+OO 4.96E+OO 6.96E+OO 1.02E+01 Season Fall 8865000 314 18.60 1.31E+OO 9.80E-02 5.24E-02 1.11E-01 1.80E-01 3.33E-01 6.49E-01 1.56E+OO 3.13E+OO 4.45E+OO 8.92E+OO 1.22E+01 Spring 4863000 487 10.54 1.14E+OO 6.35E-02 2.35E-03 4.53E-02 1.53E-01 3.38E-01 6.58E-01 1.39E+OO 2.76E+OO 4.02E+OO 7.51E+OO 1.07E+01 Summer 10151000 348 22.32 2.03E+OO 1.26E-01 2.17E-03 1.13E-01 2.04E-01 6.07E-01 1.30E+OO 2.52E+OO 4.32E+OO 6.35E+OO 1.27E+01 1.90E+01 Winter 4883000 362 10.02 1.21E+OO 9.50E-02 4.23E-03 2.28E-02 1.37E-01 3.70E-01 6.67E-01 1.42E+OO 2.76E+OO 3.69E+OO 8.86E+oo 2.06E+01 Urbanization Central City 4859000 173 8.62 1.11E+OO 1.02E-01 1.01E-02 . 6.04E-02 8.02E-02 2.83E-01 7.01E-01 1.43E+OO 2.49E+OO 3.29E+OO 8.34E+OO 1.21E+01 Nonmetropolitan 11577000 711 25.71 1.87E+OO 8.79E-02 1.65E-02 1.72E-01 2.52E-01 5.01E-01 1.16E+OO 2.20E+OO 4.12E+OO 6.10E+OO 1.22E+01 1.90E+01 Suburban 12266000 625 14.17 1.35E+OO 7.01E-02 2.93E-03 9.68E-02 1.56E-01 3.55E-01 7.44E-01 1.58E+OO 3.22E+OO 5.22E+OO 8.61E+OO 2.06E+01 Race Black 1713000 100 7.88 1.23E+OO 1.27E-01 O.OOE+OO 7.74E-02 1.41E-01 3.52E-01 8.93E-01 1.51E+OO 3.32E+OO 3.92E+OO 5.55E+OO 7.19E+OO White 26551000 1386 16.85 *1.53E+OO 5.41E-02 4.67E-03 9.74E-02 1.77E-01 3.95E-01 8.59E-01 1.82E+OO 3.48E+OO 5.12E+OO 1.03E+01 2.06E+01 Region Midwest 10402000 570 22.42 1.48E+OO 8.91E-02 1.00E-02 7.14E-02 1.57E-01 3.88E-01 8.06E-01 1.69E+OO 3.55E+OO 4.67E+OO 1.19E+01 2.06E+01 Northeast 4050000 191 9.84 1.65E+OO 1.78E-01 2.35E-03 8.05E-02 1.38E-01 2.61E-01 6.65E-01 1.75E+OO 5.58E+OO 6.80E+OO 1.27E+01 1.49E+01 South 9238000 503 14.36 1.55E+OO 7.79E-02 5.20E-02 1.63E-01 2.61E-01 5.18E-01 9.99E-01 1.92E+OO 3.19E+OO 4.52E+OO 9.92E+OO 1.33E+01 West 5012000 245 13.90 1.43E+OO 1.02E-01 3.25E-03 2.61E-02 1.45E-01 3.91E-01 7.63E-01 2.13E+OO 3.45E+OO 4.84E+OO 7.51E+OO 8.34E+OO Response to Questionnaire Households who garden 25737000 1361 37.76 1.57 5.50E-02 3.25E-03 8.87E-02 1.68E-01 4.13E-01 8.89E-01 1.97E+OO 3.63E+OO 5.45E+OO 1.03E+01 2.06E+01 Households who farm 3596000 207 49.07 2.17 . 1.61E-01 O.OOE+OO 1.84E-01 3.72E-01 6.47E-01 1.38E+OO 2.81E+OO 6.01E+OO 6.83E+OO 1.03E+01 1.33E+01 NOTE: SE = standard error P = percentile of the distribution Ne wgtd = weighted number of consumers; Ne unwgtd = unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-64. Consumer Onlv Intake of Homeorown Protected Veoetables (q/ko-davl Population Ne Ne % Grouo watd unwatd Consumina Mean SE P1 PS P10 P25 P50 P75 P90 P95 P99 P100 Total 11428000 656 6.08 1.01E+OO 4.95E-02 1.03E-01 1.54E-01 1.94E-01 3.22E-01 6.25E-01 1.20E+OO 2.24E+OO 3.05E+OO 6.49E+OO 9.42E+OO Age 01-02 348000 21. 6.11 2.46E+OO 4.91E-01 3.15E-01 3.15E-01 5.38E-01 1.36E+OO 1.94E+OO 2.96E+OO 3.88E+OO 9.42E+OO 9.42E+OO 9.42E+OO 03-05 440000 32 5.43 1.30E+OO 2.13E-01 2.33E-01 2.33E-01 3.22E-01 4.80E-01 1.04E+OO 1.48E+OD 2.51E+OO 5.10E+OO 5.31E+OO 5.31E+OO 06-11 1052000 63 6.30 1.10E+OO 1.34E-01* 1.89E-01 2.08E-01 3.18E-01 3.87E-01 7.91E-01 1.31E+OO 2.14E+OO 3.12E+OO 5.40E+OO 5.40E+OO 12-19 91000G 51 4.44 7.76E:o1 8.71E-02 5.88E-02 1.61E-01 2.39E-01 3.54E-01 5.83E-01 8.24E-01 1.85E+OO 2.20E+OO 2.69E+OO 2.69E+OO 20-39 3227000 164 5.24 7.62E-01 6.03E-02 1.13E-01 1.52E-01 1.71E-01 2.41E-01 5.08E-01 9.67E-01 1.73E+OO 2.51E+OO 3.63E+OO 4.76E+OO 40-69 3818000 226 6.73 9.30E-01 7.32E-02 6.87E-02 1.35E-01 1.66E-01 3.16E-01 6.03E-01 1.11E+OO 1.87E+OO 3.04E+OO 6.84E+OO 7.44E+OO 70+ 1442000 89 9.08 1.05E+OO 1.62E-01 1.19E-01 2.10E-01 2.42E-01 3.57E-01 5.72E-01 1.21E+OO 1.86E+OO 3.05E+OO 9.23E+OO 9.23E+OO Season Fall 3907000 143 8.20 8.51E-01 7.02E-02 1.19E-01 1.61E-01 2.04E-01 3.22E-01 5.68E-01 1.10E+OO 1.73E+OO 2.51E+OO 4.78E+OO 5.31E+OO Spring 2086000 236 4.52 7.02E-01 4.48E-02 5.88E-02 1.35E-01 1.70E-01 2.66E-01 4.90E-01 9.08E-01 1.44E+OO 1.86E+OO 3.74E+OO 5.73E+OO Summer 3559000 118 7.82 1.40E+OO 1.56E-01 1.03E-01 1.77E-01 2.33E-01 3.81E-01 7.81E-01 1.69E+OO 3.05E+OO 5.40E+OO 9.23E+OO 9.42E+OO Winter 1876000 159 3.85 9:30E-01 7.70E-02 1.18E-01 1.42E-01 1.82E-01 3.12E-01 6.01E-01 1.20E+OO 2.32E+OO 3.06E+OO 4.76E+OO 6.39E+OO Urbanization Central City 1342000 49 2.38 9.96E-01 1.51E-01 1.19E-01 1.53E-01 1.67E-01 3.18E-01 7.21E-01 1.18E+OO 2.36E+OO 2.83E+OO 4.78E+OO 4.78E+OO Nonmetropolitan 5934000 391 13.18 1.07E+OO 6.36E-02 1.14E-01 1.66E-01 2.14E-01 3.53E-01 6.48E-01 1.30E+OO 2.51E+OO 3.55E+OO 6.84E+OO 9.42E+OO Suburban 4152000 216 4.80 9.26E-01 7.97E-02 6.87E-02 1.50E-01 1.88E-01 2.94E-01 5.64E-01 1.15E+OO 1.85E+OO 2.67E+oo 6.49E+OO 9.23E+OO Race Black 479000 27 2.20 1.50E+OO 2.25E-01 1.62E-01 2.64E-01 3.31E-01 8.66E-01 9.35E-01 2.20E+OO 3.05E+OO 3.23E+OO 4.95E+OO 4.95E+OO White 10836000 625 6.88 9.93E-01 4.83E-02 1.03E-01 1.53E-01 1.92E-01 3.21E-01 6.10E-01 1.20E+OO 2.17E+OO 3.04E+OO 6.49E+OO 9.42E+OO Region Midwest 4359000 273 9.40 1.01E+OO 7.38E-02 1.13E-01 1.71E-01 2.31E-01 3.26E-01 5.72E-01 1.08E+OO 2.45E+OO 3.68E+OO 6.84E+OO 7.44E+OO Northeast 807000 48 1.96 7.01E-01 8.99E-02 5.88E-02 1.50E-01 1.68E-01 2.65E-01 5.09E-01 9.91E-01 1.71E+OO 2.33E+OO 2.77E+OO 2.77E+OO South 4449000 253 6.92 1.08E+OO 7.17E-02 1.29E-01 1.71E-Q1 2.14E-01 3.76E-01 7.12E-01 1.38E+OO 2.32E+OO 3.0SE+OO 5.40E+OO 9.42E+OO West 1813000 82. 5.03 9.57E-01 1.62E-01 6.87E-02 1.19E-01 1.52E-01 2.08E-01 4.79E-01 1.01E+OO 1.86E+OO 3.12E+OO 9.23E+OO 9.23E+OO Response to Questionnaire Households who garden 10286000 602 15.09 1.01E+OO 4.73E-02 1.03E-01 1.53E-01 1.92E-01 3.36E-01 6.42E-01 1.21E+OO 2.32E+OO 3.05E+OO 6.49E+OO 9.23E+OO Households who farm 2325000 142 31.72 1.30E+OO 1.45E-01 8.65E-02 1.66E-01 2.09E-01 3.37E-01 5.99E-01 1.40E+OO 3.55E+OO 5.40E+OO 9.23E+OO 9.23E+OO NOTE: SE= standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-65. Consumer Onlv Intake of Homeorown Root Veoetables lo/ka-day) ,. Population Ne Ne % Groun wold unwotd Consumina Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 13750000 743 7.31 1.16E+OO 5.84E-02 4.72E-03 3.64E-02 1.12E-01 2.51E-01 6.66E;01 1.47E+OO 2°.81E+OO 3.71E+OO 9.52E+OO 1.28E+01 Age 01-02 371000 22 6.51 2.52E+OO 6.10E-01 1.66E-01 1.66E-01 2.19E-01 3.59E-01 9.20E-01 3.67E+OO 7.25E+OO 1.04E+01 1.04E+01 1.04E+01 03-05 390000 23 4.81 1.28E+OO 3.24E-01 0.00E+OO O.OOE+OO 1.17E-01 2.25E-01 4.62E-01 1.68E+OO 4.26E+OO 4.73E+OO 4.73E+OO 4.73E+OO 06-11 1106000 67 6.62 1.32E+OO 2.14E-01 0.00E+OO 1.39E-02 3.64E-02 2.32E-01 5:23E-01 1.63E+OO 3.83E+OO 5.59E+OO 7.47E+OO 7.47E+OO 12-19 1465000 76 7.15 9.37E-01 1.19E-01 7.59E-03 8.00E-03 6.84E-02 2.69E-01 5.65E-01 1.37E+OO 2.26E+OO 3.32E+OO 5.13E+OO 5.13E+OO 20-39 3252000 164 5.28 8.74E-01 7.39E-02 1.21E-02 5.35E-02 9.93E-02 2.00E-01 5.64E-01 1.24E+OO 2.11E+OO 3.08E+OO 4.64E+OO 6.03E+OO 40-69 4903000 276 8.64 1.13E+OO 9.86E-02 3.34E-03 3.29E-02 1.17E-01 2.51E-01 6.75E-01 1.27E+OO 2.74E+OO 3.56E+OO 9.52E+OO 1.28E+01 70 + 2096000 107 13.20 1.22E+OO 1.02E-01 1.73E-02 2.90E-02 1.69E-01 3.76E-01 8.51E-01 1.71E+OO 2.86E+OO 3.21E+OO 4.01E+OO 4.77E+OO Season Fall 4026000 153 8.45 f42E+OO 1.53E-01 5.15E-02 1.38E-01 1.72E-01 3.09E-01 9.20E-01 1.67E+OO 3.26E+OO 3.85E+OO 1.23E+01 1.28E+01 Spring 2552000 260 5.53 6.87E-01 6.08E-02 3.34E-03 1.73E-02 3.00E-02 1.44E-01 3.65E-01 7.69E-01 1.69E+OO 2.80E+OO 4.24E+OO 7.69E+OO Summer 5011000 169 11.02 1.19E+OO 1.20E-01 0.00E+OO 4.76E-02 1.32E-01 2.77E-01 7.26E-01 1.51E+OO 2.74E+OO 3.64E+OO 1.04E+01 1.19E+01 Winter 2161000 161 4.44 1.17E+OO 1.19E-01 3.23E-03* 8.57E-03 4.34E-02 2.38E-01 5.57E-01 1.56E+OO 3.08E+OO 4.14E+OO 6.21E+OO 1.13E+01 Urbanization Central City 2385000 96 4.23 7.49E-01 8.40E-02 2.68E-02 3.90E-02 1.43E-01 2.23E-01 4.26E-01 9.16E-01 1.91E+OO 2.70E+OO 3.56E+OO 3.93E+OO Nonmetropolitan 6094000 366 13.54 1.43E+OO 9.81E-02 8.57E-03 6.87E-02 1.29E-01 2.78E-01 7.58E-01 1.85E+OO 3.32E+OO 4.24E+OO 1.13E+01 1.28E+01 Suburban 5211000 279 6.02 1.06E+OO 8.62E-02 3.73E-03 1.21E-02 7.17E-02 2.32E-01 7.34E-01 1.19E+OO 2.34E+OO 3.26E+OO 6.29E+OO 1.19E+01 Race Black 521000 31 2.40 8.83E-01 3.93E-01 4.72E-03 9.28E-03 3.64E-02 8.82E-02 5.42E-01 7.65E-01 1.06E+OO 1.25E+OO 1.23E+01 1.23E+01 White 12861000 697 8.16. 1.18E+OO 5.97E-02 4.58E-02 1.29E-01 2.61E-01 6.80E-01 1.50E+OO 2.82E+OO 3.72E+OO 9.52E+OO 1.28E+01 Region Midwest 5572000 314 12.01 1.31E+OO 9.54E-02 3.37E-02 7.48E-02 1.66E-01 2.69E-01 7.39E-01 1.67E+OO 3.23E+OO 4.26E+OO 1.04E+01 1.19E+01 Northeast 1721000 92 4.18 8.38E-01 1.03E-01 3.23E-03 7.79E-03 8.69E-03 1.43E-01 4.81E-01 1.18E+OO 2.05E+OO 2.77E+OO 4.78E+OO 6.03E+OO South 3842000 205 5.97 1.38E+OO 1.38E-01 1.10E-02 5.35E-02 1.32E-01 2.77E-01 6.90E-01 1.70E+OO 3.32E+OO 3.83E+OO 1.23E+01 1.28E+01 West 2555000 130 7.08 7.68E-01 6.43E-02* 4.72E-03 2.24E-02 1.14E-01 2.38E-01 5.70E-01 9.??E-01 1.69E+OO 2.45E+OO 3.72E+OO 3.72E+OO Response to Questionnaire Households who garden 12578000 682 18.46 1.15E+OO 5.72E-02 4.79E-03 3.64E-02 1.17E-01 2.58E-01 6.74E-01 1.50E+OO 2.81E+OO 3.64E+OO 7.47E+OO 1.28E+01 Households who farm 2367000 136 32.30 1.39E+OO 1.26E-01 1.11E-01 1.58E-01 1.84E-01 3.65E-01 8.83E-01 1.85E+OO 3.11E+OO 4.58E+OO 7.47E+OO 7.69E+OO NOTE: SE = standard error P = percentile of the distribution Ne wgtd = weighted number of consumers; Ne unwgtd = unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-66. Consumer Only Intake of Homeorown Dark Green Veoetables (q/kq-davl Population Ne Ne % Grouo wntd unwntd Consuminn Mean SE P1 P5 P10 P25 P50 P75 P90 P95 pgg P100 Total 8855000 428 4.71 3,91E-01 2.95E-02 2.01E-03 4.28E-03 1.01E-02 8.70E-02 2.11E-01 4.35E-01 9.19E-01 1.25E+OO 3.53E+OO 5.82E+OO Age 01-02 180000 8 3.16 . . . . . . . * . . . 03-05 226000 12 2.79 . . . . . . . . . . . . 06-11 826000 39 4.94 3.05E-01 5.19E-02 0.00E+OO 6.34E-03 2.42E-02 9.00E-02 1.81E-01 3.87E-01 9.48E-01 1.04E+OO 1.28E+OO 1.28E+OO 12-19 628000 32 3.07 4.20E-01 1.47E-01 4.92E-03 5.38E-03 6.65E-03 5.62E-02 2.03E-01 3.73E-01 9.24E-01 1.64E+OO 4.86E+OO 4.86E+OO 20-39 1976000 87 3.21 3.36E-01 6.09E-02 2.21E-03 3.74E-03 1.00E-02 8.70E-02 1.76E-01 3.79E-01 6.69E-01 9.19E-01 2.94E+OO 4.29E+OO 40-69 3710000 184 6.54 4.01E-01 4.24E-02 2.25E-03 3.67E-03 2.60.E-02 8.19E-02 2.33E-01 4.80E-01 9.79E-01 1.25E+OO 3.29E+OO 5.82E+OO 70 + 1253000 63 7.89 4.08E-01 7.27E-02 2.84E-03 4.23E-03 5.68E-03 1.10E-01 2.31E-01 4.69E-01 9.29E-01 1.08E+OO 3.45E+OO 3.45E+OO Season Fall 2683000 88 5.63 4.41E-01 7.42E-02 1.01E-02 4.46E-02 8.70E-02 1.45E-01 2.38E-01 4.59E-01 7.90E-01 1.08E+OO 3.86E+OO 4.29E+OO Spring 1251000 127 2.71 5.59E-01 7.90E-02 1.63E-03 3.66E-03 5.72E-03 1.01E-01 3.09E-01 5.38E-01 1.28E+OO 2.81E+OO 4.86E+OO 5.82E+OO Summer 3580000 124 7.87 3.39E-01 4.10E-02 0.00E+OO 2.84E-03 5.68E-03 6.34E-02 1.51E-01 4.05E-01 9.79E-01 1.15E+OO 2.48E+OO 2.48E+OO Winter 1341000 89 2.75 2.72E-01 3.92E-02 2.01E-03 3.97E-03 5.21E-03 2.30E-02 1.51E-01 *3.71E-01 6.59E-01 1.17E+OO 2.04E+OO 2.18E+OO Urbanization Central City 1298000 48 2.30 2.69E-01 3.68E-02 2.84E-03 4.71E-03 1.01E-02 1.06E-01 2.05E-01 3.24E-01 6.32E-01 9.19E-01 1.07E+OO 1.07E+OO Nonmetropolitan 3218000 167 7.15 3.31E-01 3.54E-02 2.21E-03 4.67E-03 1.70E-02 6.86E-02 1.72E-01 4.52E-01 7.52E-01 1.00E+OO 2.48E+OO 5.82E+OO Suburban 4279000 211 4.94 4.79E-01 5.23E-02 2.25E-03 5.21E-03 2.15E-02 9.22E-02 2.33E-01 4.59E-01 1.15E+OO 2.18E+OO 3.86E+OO 4.86E+OO Race Black 724000 49 3.33 1.04E+OO 1.80E-01 0.00E+OO 1.00E-01 1.13E-01 2.21E-01 5.52E-01 1.17E+OO 3.29E+OO 3.86E+OO 4.86E+OO 4.86E+OO White 7963000 373 5.05 3.21E-01 2.20E-02 2.25E-03 4.67E-03 1.01E-02 7.75E-02 1.99E-01 3.79E-01 7.76E-01 1.07E+OO 2.37E+OO 5.82E+OO Region Midwest 2668000 121 5.75 2.81E-01 3.54E-02 2.84E-03 4.77E-03 6.26E-03 6.34E-02 2.11E-01 3.58E-01 4.96E-01 9.79E-01 2.48E+OO 3.02E+OO Northeast 1554000 76 3.77 5.08E-01 9.14E-02 2.17E-03 2.80E-03 4.23E-03 5.62E-02 1.96E-01 4.92E-01 1.25E+OO 1.93E+OO 3.53E+OO 5.82E+OO South 2945000 148 4.58 4.78E-01 5.07E-02 3.64E-02 6.83E-02 9.23E-02 1.45E-01 2.87E-01 6.43E-01 9.24E-01 1.28E+OO 3.86E+OO 4.29E+OO West 1628000 81 4.51 3.18E-01 7.25E-02 2.25E-03 3.37E-03 6.34E-03 3.50E-02 1.10E-01 3.09E-01 6.59E-01 9.29E-01 4.86E+OO 4.86E+OO Response to Questionnaire Households who garden 8521000 412 12.50 3.95E-01 3.03E-02 1.63E-03 4.23E-03 1.05E-02 8.76E-02 2.12E-01 4.48E-01 9.19E-01 1.25E+OO 3.53E+OO 5.82E+OO Households who farm 1450000 66 19.78 3.80E-01 6.08E-02 1.62E-03 4,67E-03 5.38E-03 6.68E-02 2.31E-01 4.84E-01 9.48E-01 1.25E+OO 2.48E+OO 3.02E+OO
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-67. Consumer Onlv Intake of Homearown Deep Yellow Veaetables fa/ka-davl Population Ne Ne % Grouo watd unwatd Consumino Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 5467000 245 2.91 6.43E-01 4.44E-02 4.34E-02 6.70E-02 1.26E-01 2.22E-01 4.17E-01 7.74E-01 1.44E+OO 2.03E+OO 2.67E+OO 6.63E+OO Age 01-02 124000 8 2.18 * . . * * . . * . . . . 03-05 61000 4 0.75 * . * * . . * . .
06-11 382000 17 2.29 . . * . . * . . . * . . 12-19 493000 21 2.41 4.73E-01 9.18E-02 6.05E-02 6.05E-02 6.29E-02 9.07E-02 3.63E-01 7.79E-01 1.13E+OO 1.44E+OO 1.58E+OO 1.58E+OO 20-39 1475000 63 2.39 5.32E-01 7.54E-02 4.89E-02 5.55E-02 1.15E-01 1.66E-01 3.05E-01 5.11E-01 1.22E+OO 2.03E+OO 2.67E+OO 2.67E+OO 40-69 2074000 96 3.66 5.39E-01 5.15E-02 3.90E-02 9.22E-02 1.43E-01 2.21E-01 4.03E-01 6.54E-01 1.09E+OO 1.33E+OO 3.02E+OO 3.02E+OO 70+ 761000 32 4.79 7.81E-01 9.20E-02 7.64E-02 2.02E-01 2.77E-01 3.70E-01 5.72E-01 1.24E+OO 1.61E+OO 1.99E+OO 1.99E+OO 1.99E+OO Season Fall 2664000 97 5.59 7.38E-01 8.18E-02 9.21E-02 1.22E-01 1.43E-01 2.61E-01 4.51E-01 9.74E-01 1.73E+OO 2.23E+OO 3.02E+OO 6.63E+OO Spring 315000 34 0.68 5.64E-01 7.52E-02 1.43E-01 1.45E-01 1.98E-01 2.47E-01 4.45E-01 6.43E-01 1.01E+OO 1.42E+OO 2.41E+OO 2.41E+OO Summer 1619000 52 3.56 5.09E-01 6.37E-02 4.16E-02 5.49E-02 6.48E-02 2.26E-01 4.10E-01 6.35E-01 9.64E-01 1.67E+OO 2.31E+OO 2.31E+OO Winter 869000 62 1.78 6.29E-01 9.15E-02 3.90E-02 4.34E-02 6.29E-02 1.72E-01 3.52E-01 7.96E-01 1.54E+OO 2.23E+OO 4.37E+OO 4.37E+OO Urbanization Central City 1308000 43 2.32 5.07E-01 7.07E-02 3.90E-02 6.29E-02 1.43E-01 2.13E-01 3.88E-01 5.88E-01 9.64E-01 1.41E+OO 2.24E+OO 2.24E+OO Nonmetropolitan 2100000 118 4.66 6.66E-01 7.72E-02 4.16E-02 5.55E-02 9.07E-02 2.20E-01 3.70E-01 8.65E-01 1.39E+OO *2.12E+OO 4.37E+OO 6.63E+OO Suburban 2059000 84 2.38 7.07E-01 6.99E-02 6.48E-02 9.22E-02 1.26E-01 2.62E-01 4.25E-01 9.74E-01 1.67E+OO 2.03E+OO 2.67E+OO 2.67E+OO Race Black 129000 8 0.59 * . . * * . . * . . . White 5093000 229 3.23 6.45E-01 4.03E-02 4.89E-02 9.21E-02 1.43E-01 2.41E-01 4.25E-01 7.96E-01 1.50E+OO 2.03E+OO 2.67E+OO 4.37E+OO Region Midwest 2792000 128 6.02 7.52E-01 6.01E-02 4.34E-02 1.32E-01 1.93E-01 2.82E-01 5.09E-01 9.55E-01 1.73E+OO 2.23E+OO 3.02E+OO 4.37E+OO Northeast 735000 29 1.79 3.96E-01 8.06E-02 4.16E-02 5.55E-02 6.05E-02 9.22E-02 1.50E-01 6.35E-01 1.09E+OO 1.37E+OO 2.21E+OO 2.21E+OO South 557000 30 0.87 5.39E-01 2.08E-01 4.89E-02 5.49E-02 7.74E-02 2.20E-01 3.05E-01 4.38E-01 7.74E-01 1.22E+OO 6.63E+OO 6.63E+OO West 1383000 58 3.83 5.97E-01 7.07E-02 6.48E-02 1.27E-01 1.43E-01 2.21E-01 4.10E-01 6.42E-01 1.44E+OO 1.89E+OO 2.31E+OO 2.31E+OO Response to Questionnaire Households who garden 5177000 233 7.60 6.23E-01 3.93E-02 4.16E-02 9.07E-02 1.32E-01 2.32E-01 4.15E-01 7.50E-01 1.42E+OO 1.99E+OO 2.67E+OO 4.37E+OO Households who farm 1088000 51 14.85 6.06E-01 8.52E-02 9.21E-02 9.22E-02 1.22E-01 1.94E-01 3.40E-01 9.40E-01 1.28E+OO 1.73E+OO 3.02E+OO 3.02E+OO
Intake data not provided for subpopulations for which tbere were less than 20 observations NOTE: SE = standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table13-68. Consumer Onlv Intake of Homearown Other Veaetables la/ka-davl Population Ne Ne % Grouo watd unwatd Consumina Mean SE P1 PS P10 P25 P50 P75 P90 PSS P99 P100 Total 25221000 1437 13.41 1.38E+OO 5.00E-02 9.44E-03 1.07E-01 1.76E-01 3.62E-01 7.78E-01 1.65E+OO 3.09E+OO 4.52E+OO 9.95E+OO 1.84E+01 Age 01-02 613000 38 10.76 3.80E+OO 6.27E-01 1.92E-01 2.73E-01 4.04E-01 1.04E+OO 2.61E+OO 4.55E+OO 7.74E+OO 1.12E+01 1.80E+01 1.80E+01 03-05 887000 59 10.95 2.15E+OO 2.67E-01 O.OOE+OO 2.28E-01 3.72E-01 7.20E-01 1.37E+OO 3.16E+OO 4.47E+OO 5.96E+OO 8.41E+OO 1.40E+01 06-11 2149000 134 12.86 1.30E+OO 1.38E-01 0.00E+OO 1.21E-01 1.93E-01 3.54E-01 8.00E-01 1.61E+OO 3.04E+OO 4.57E+OO 9.95E+OO 9.95E+OO 12-19 2379000 141 11.61 9.80E-01 8.56E-02 0.00E+OO 5.76E-02 1.15E-01 3.17E-01 6.40E-01 1.33E+OO 2.05E+OO 3.17E+OO 5.41E+OO 5.41 E+OO 20-39 6020000 328 9.77 9.30E-01 6.00E-02 3.19E-02 9.37E-02 1.48E-01 2.43E-01 5.60E-01 1.12E+OO 2.19E+OO 3.04E+OO 5.10E+OO 7.00E+OO 40-69 9649000 547 17.01 1.40E+OO 8.72E-02 5.20E-03 1.11E-01 1.86E-01 3.95E-01 8.43E-01 1.58E+OO 2.92E+OO 4.65E+OO 1.41E+01 1.84E+01 70+ 3226000 174 20.31 1.58E+OO 1.41E-01 1.85E-02 1.52E-01 2.38E-01 4.62E-01 9.48E-01 1.91E+OO 3.46E+OO 5.79E+OO 9.96E+OO 1.14E+01 Season Fall 6934000 253 14.55 1.19E+OO 8.62E-02 4.92E-02 : 1.48E-01 1.86E-01 3.28E-01 7.16E-01 1.44E+OO 2.74E+OO 4.00E+OO 6.74E+OO 9.96E+OO Spring 5407000 567 11.71 1.16E+b0 6.19E-02 3.66E-03 4.32E-02 1.04E-01 3.10E-01 7.10E-01 1.39E+OO 2.67E+OO 4.21E+OO 7.35E+OO 1.40E+01 Summer 8454000 283 18.59 1.79E+OO 1.53E-01 O.OOE+OO 1.18E-01 1.81E-01 3.85E-01 9.68E-01 1.97E+OO 4.13E+OO 6.14E+OO 1.46E+01 1.84E+01 Winter 4426000 334 9.09 1.19E+OO 7.28E-02 4.79E-03 1.41E-01 2.31E-01 4.09E-01 7.33E-01 1.49E+OO 2.41E+OO 3.37E+OO 7.00E+OO 1.10E+01 Urbanization Central City 4148000 161 7.36 9.66E-01 8.81E-02 3.SOE-02 9.37E-02 1.63E-01 3.24E-01 6.07E-01 1.23E+OO 1.97E+OO 3.22E+OO 7.00E+OO 8.85E+OO Nonmetropolitan 10721000 710 23.81 1.78E+OO 8.99E-02 2.74E-02 1.60E-01 2.26E-01 4.68E-01 1.01E+OO 2.01E+OO 4.05E+OO 5.74E+OO 1.41E+01 1.84E+01 Suburban 10292000 564 11.89 1.14E+OO 5.98E-02 4.79E-03 8.98E-02 1.46E-01 3.06E-01 6.47E-01 1.44E+OO 2.69E+OO 3.77E+OO 6.81E+OO 1.14E+01 Race Black 1347000 84 6.19 1.30E+OO 1.70E,01 4.41E-02 1.74E-01 2.06E-01 3.SOE-01 7.11E-01 1.49E+OO 3.88E+OO 5.47E+OO 6.21E+OO 7.72E+OO White 23367000 1327 14.83 1.39E+OO 5.26E-02 1.29E-02 1.10E-01 1.79E-01 3.76E-01 7.93E-01 1.65E+OO 3.04E+OO 4.49E+OO 9.96E+OO 1.84E+01 Region Midwest 8296000 522 17.88 1.43E+OO 9.25E-02 3.19E-02 1.21E-01 1.90E-01 3.66E-01 7.29E-01 1.65E+OO 3.05E+OO 4.65E+OO 1.12E+01 1.84E+01 Northeast 2914000 162 7.08 1.33E+OO 1.65E-01 1.97E-03 5.69E-02 1.07E-01 2.44E-01 5.97E-01 1.64E+OO 3.07E+OO 5.41 E+OO 1.20E+01 1.41E+01 South 9218000 518 14.33 1.53E+OO 7.82E-02 1.41E-02 1.68E-01 2.53E-01 4.87E-01 1.03E+OO 1.76E+OO 3.37E+OO 4.70E+OO 8.33E+OO 1.80E+01 West 4733000 .233 13.12 1.08E+OO 9.85E-02 1.11E-02 7.06E-02 1.22E-01 2.SSE-01 5.73E-01 1.21E+OO 2.41E+OO 3.73E+OO 8.02E+OO 1.14E+01 Response to Questionnaire Households who garden 22417000 1291 32.89 1.44E+OO 5.25E-02 1.11E-02 1.11E-01 1.80E-01 3.84E-01 8.18E-01 1.70E+OO 3.22E+OO 4.65E+OO 9.95E+OO 1.84E+01 Households who farm 3965000 239 54.10 1.95E+OO 1.63E-01 1.41E-02 1.36E-01 2.34E-01 5.20E-01 1.21E+OO 2.04E+OO 5.32E+OO 7.02E+OO 1.46E+01 1.59E+01 NOTE: SE= standard error P = percentile of the distribution Ne wgtd = weighted 'number of consumers; Ne unwgtd = unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-69. Consumer Onlv Intake of Homeqrown Citrus (q/ko-dav) Population Ne Ne % Groun watd unwotd Consumina Mean SE P1 PS P10 P25 PSO P75 P90 P95 P99 P100 Total 2530000 125 1.35 4.76E+OO 6.0SE-01 7.82E-02 1.57E-01 2.86E-01 7.56E-01 1.99E+OO 5.10E+OO 1.41E+01 1.97E+01 3.22E+01 4.79E+01 Age 01-02 54000 4 0.95 . . . . . . . . . . . . 03-05 51000 3 0.63 . . . . . . . . . . . 06-11 181000 9 1.08 . . . . . . . . . . . . 12-19 194000 14 0.95 . . . . . . . . . . 20-39 402000 18 0.65 . . . . . . . . . . . 40-69 1183000 55 2.09 4.54E+OO 8.06E-01 8.11E-02 1.SOE-01 2.47E-01 5.21E-01 1.74E+OO 5.24E+OO 1.52E+01 1.97E+01 2.38E+01 2.38E+01 70 + 457000 21 2.88 4.43E+OO 7.58E-01 7.82E-02 7.82E-02 4.94E-01 1.95E+OO 3.53E+OO 6.94E+OO 8.97E+OO 8.97E+OO 1.57E+01 1.57E+01 Season Fall 280000 8 0.59 . . . . . . . . . . . . Spring 437000 33 0.95 2.31E+OO 3.76E-01 1.57E-01 1.84E-01 2.35E-01 3.69E-01 1.36E+OO 4.15E+OO 5.10E+OO 6.SOE+OO 7.52E+OO 7.52E+OO Summer 334000 11 0.73 . . . . . . . . . . . . Winter 1479000 73 3.04 6.47E+OO 9.53E-01 1.SOE-01 3.33E-01 4.94E-01 1.64E+OO 2.93E+OQ 8.59E+OO 1.91E+01 2.38E+01 4.79E+01 4.79E+01 Urbanization Central City 1053000 43 1.87 3.57E+OO 5.18E-01 1.SOE-01 3.33E-01 4.SOE-01 1.13E+OO 3.01E+OO 4.97E+OO 7.46E+OO 8.97E+OO 2.00E+01 2.00E+01 Nonmetropolitan 0 0 0.00 Suburban 1477000 82 1.71 5.61E+OO 9.14E-01 7.82E-02 1.14E-01 2.47E-01 5.17E-01 1.81E+OO 8.12E+OO 1.79E+01 2.38E+01 4.79E+01 4.79E+01 Race Black 200000 8 0.92 . . . . . . . . While 2330000 117 1.48 4.93E+OO 6.31E-01 7.82E-02 1.SOE-01 2.84E-01 7.82E-Oi 2.34E+OO 5.34E+OO 1.41E+01 1.97E+01 3.22E+01 4.79E+01 Region Midwest 64000 4 0.14 . . . . . . . . . . Northeast 0 0 0.00 South 1240000 55 1.93 5.18E+OO 7.37E-01 1.57E-01 3.76E-01 6.44E-01 1.60E+OO 3.42E+OO 60SOE+OO 1.41E+01 1.97E+01 2.38E+01 2.38E+01 West 1226000 66 3.40 4.56E+OO 9.79E-01 7.82E-02 1.14E-01 2.35E-01 3.69E-01 1.42E+OO 4.53E+OO 1.24E+01 2.00E+01 4.79E+01 4.79E+01 Response to Qu9stionnaire Households who garden 2151000 102 3.16 4.SSE+OO 6.61E-01 7.82E-02 1.SOE-01 2.84E-01 7.56E-01 1.99E+OO 4.99E+OO. 1.24E+01 1.79E+01 3.22E+01 4.79E+01 Households who farm 130000 5 1.77 . . . . . . . . . . .
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE = standard error P = percentile of the distributions Ne wgtd =weighted number of consumers; Ne unwgtd = unweighted number of consumers in survey. Sources: Based on EPA's of the 1987-88 NFCS Table 13-70. Consumer Only Intake of Homegrown other Fruit fa/ka-dav\ Population Ne Ne % Grouo wntd unwntd Consumina Mean SE P1 P5 P10 P25 P50 P75 P90 P95 P99 P100 Total 12615000 706 6.71 2.20E+OO 1.86E-01 5.41E-02 1.47E-01 2.55E-01 4.60E-01 9.06E-01" 1.91E+OO 4.59E+OO 8.12E+OO 1.84E+01 6.26E+01 Age
01-02 306000 19 5.37 . . . . . . . . . . . . 03-05 499000 31 6.16 2.66E+OO 7.60E-01 O.OOE+OO 0.00E+OO 3.80E-01 1.02E+OO 1.87E+OO 2.71E+OO 5.54E+OO 6.30E+OO 3.32E+01 3.32E+01 06-11 915000 68 *5.48 2.60E+OO 4.38E-01 0.00E+OO 1.77E-01 3.86E-01 6.37E-01 1.14E+OO 2.99E+OO 7.13E+OO 1.21E+01 1.62E+01 1.65E+01 12-19 1021000 54 4.98 1.62E+OO 2.77E-01 8.40E-02 1.20E-01 2.57E-01 3.86E-01 6.09E-01 2.36E+OO 3.92E+OO 6.81E+OO 8.12E+OO 8.12E+OO 20-39 2761000 146 4.48 1.85E+OO 3.72E-01 7.94E-02 1.30E-01 1.80E-01 3.07E-01 6.20E-01 1.39E+OO 3.70E+OO 6.64E+OO 3.70E+01 3.70E+01 40-69 4610000 259 8.13 2.09E+OO 3.08E-01 6.52E-02 1.47E-01 2.54E-01 4.44E-01 7.68E-01 1.77E+OO 3.17E+OO 9.77E+OO 1.84E+01 5.33E+01 70+ 2326000 119 14.65 1.66E+OO 1.84E-01 4.41E-02 2.07E-01 3.56E-01 5.71E-01 1.07E+OO 1.65E+OO 4.06E+OO 5.21E+OO 1.17E+01 1.17E+01 Season Fall 2923000 102 6.13 1.39E+OO 1.14E-01 2.59E-01 3.04E-01 3.81E-01 5.67E-01 1.07E+OO 1.88E+OO 2.89E+OO 4.06E+OO 5.39E+OO 5.54E+OO Spring 2526000 268 5.47 1.47E+OO 1.51E-01 8.66E-02 1.98E-01 2.54E-01 4.25E-01 8.33E-01 1.65E+OO 2.89E+OO 4.59E+OO 8.26E+OO 3.32E+01 Summer 4327000 144 9.51 Winter 2839000 192 5.83 1.29E+OO 1.08E-01 4.15E-02 1.01E-01 2.25E-01 4.54E-01 8.33E-01 1.55E+OO 2.70E+OO 4.79E+OO 8.06E+OO 1.13E+01 Urbanization Central City 2681000 102 4.76 1.79E+OO 2.88E-01 4.41E-02 1.66E-01 2.91E-01 5.21E-01 8.87E-01 1.60E+OO 2.61E+OO 1.04E+01 1.54E+01 1.54E+01 Nonmetropolitan 4118000 278 9.15 2.43E+OO 3.10E-01 6.52E-02 1.20E-01 2.38E-01 4.50E-01 1.13E+OO 2.43E+OO 4.60E+OO 8.12E+OO 2.40E+01 5.33E+01 Suburban 5756000 324 6.65 2.25E+OO 3.06E-01 1.25E-01 1.99E-01 2.82E-01 4.46E-01 7.64E-01 1.81E+OO 4.72E+OO 7.61E+OO 1.84E+01 6.26E+01 Race Black 250000 12 1.15 . . . . . . . . . . . . White 12256000 690 7.78 2.24E+OO 1.91E-01 6.96E-02 1.50E-01 2.59E-01 4.66E-01 9.16E-01 1.94E+OO 4.65E+OO 8.26E+OO 1.84E+01 6.26E+01 Region Midwest 4619000 298 9.96 3.07E+OO 4.25E-01 4.41E-02 1.25E-01 2.35E-01 4.54E-01 1.04E+OO 2.35E+OO 6.73E+OO 1.42E+01 5.33E+01 6.26E+01 Northeast 1279000 72 3.11 9.32E-01 2.20E-01 7.98E-02 8.55E-02 1.62E-01 3.11E-01 4.75E-01 8.12E-01 1.29E+OO 2.16E+OO 1.17E+01 1.17E+01 South 3004000 157 4.67 1.99E+OO 2.59E-01 7.94E-02 2.38E-01 2.99E-01 5.46E-01 1.10E+OO 1.82E+OO 4.06E+OO 6.30E+OO 1.62E+01 2.40E+01 West 3653000 177 10.13 1.76E+OO 1.64E-01 1.00E-01 2.16E-01 2.91E-01 5.44E-01 9.71E-01 2.04E+OO 4.35E+OO 5.75E+OO 1.30E+01 1.30E+01 Response to Questionnaire Households who garden 10926000 619 16.03 2.38E+OO 2.12E-01 4.41E-02 1.58E-01 2.57E-01 4.74E-01 9.94E-01 1.96E+OO 4.94E+OO 1.04E+01 1.84E+01 6.26E+01 Households who farm 1917000 112 26.16 2.57E+OO 2.65E-01 6.96E-02 2.76E-01 3.61E-01 7.33E-01 1.55E+OO 3.62E+OO 5.80E+OO 8.06E+OO 1.62E+01 1.62E+01
Intake data not provided for subpopulations for which there were less than 20 observations NOTE: SE= standard error P = percentile of the distribution Ne wgtd =weighted number of consumers; Ne unwgtd =unweighted number of consumers in survey. Source: Based on EPA's analyses of the 1987-88 NFCS Table 13-71. Fraction of Food Intake that is Home Produced Total Total Total Total Total Exposed Protected Root Exposed Protected Fruits Veaetables Meats Dairv Fish Veaetables Veoetables Veaetables Fruits Fruits Total 0.040 0.068 0.024 0.012 0.094 0.095 0.069 0.043 0.050 0.037 Season Fail 0.021 0.081 0.020 0.008 0.076 0.106 0.073 0.06 0.039 0.008 Spring 0.021 0.037 0.020 0.011 0.160 0.05 0.039 0.02 0.047 0.008 Summer 0.058 0.116 0.034 0.022 0.079 0.164 0.101 0.066 0.068 0.054 Winter 0.059 0.041 0.022 0.008 0.063 0.052 0.048 0.026 0.044 0.068 Urbanization Central City 0.027 0.027 0.003 0.000 0.053 0.037 0.027 0.016 0.030 0.026 Nonmetropolitan 0.052 0.144 0.064 0.043 0.219 0.207 0.134 0.088 0.100 0.025 Surburban 0.047 0.058 O.D18 0.004 0.075 0.079 0.054 0.035 0.043 0.050 Race ---sia°ck 0.007 0.027 0.001 0.000 0.063 0.037 0.029 0.012 0.008 0.007 White 0.049 0.081 0.031 0.014 0.110 0.109 0.081 0.050 0.059 0.045 Regions Northeast 0.005 0.038 0.009 0.010 0.008 0.062 0.016 0.018 0.010 0.002 Midwest 0.059 0.112 0.046 0.024 0.133 0.148 0.109 0.077 0.078 0.048 South 0.042 0.069 ' 0.017 0.006 0.126 0.091 0.077 0.042 0.040 0.044 West 0.062 0.057 0.023 0.007 .0.108 0.079 0.060 0.029 0.075 0.054 Questionnaire Resgonse Households who garden 0.101 0.173 0.233 0.178 0.106 0.116 0.094 Households who raise animals 0.306 0.207 Households who farm 0.161 0.308 0.319 0.254 0.420 0.394 0.173 0.328 0.030 Households who fish 0.325 Table 13-71. Fraction of Food Intake that is Home Produced continued Dark Green Deep Yellow Other Citrus Other Ve stables Ve stables Ve etables Fruits Fruits A les Peaches Pears Strawberries Other Berries Total 0.044 0.065 0.069 0.Q38 0.042 0.030 0.147 0.067 0.111 0.217 Season Fail 0.059 0.099 0.069 0.114 0.027 0.032 0.09 O.Q38 0.408 0.163 Spring 0.037 0.017 0.051 0.014 0.025 0.013 0.206 0.075 0.064 0.155 Summer 0.063 0.08 0.114 0.01 0.07 0.053 0.133 0.066 0.088 0.232 Winter 0.018 0.041 0.044 0.091 0.03 0.024 0.183 0.111 0.217 0.308 Urbanization Central City 0.012 0.038 0.026 0.035 0.022 0.017 0.087 O.Q38 0.107 0.228 Non metropolitan 0.090 0.122 0.154 0.000 0.077 0.066 0.272 0.155 0.133 0.282 Surburban 0.054 0.058 0.053 0.056 0.042 0.024 0.121 0.068 0.101 0.175 Race -siii°ck 0.053 0.056 0.026 0.012 0.004 0.007 0.018 0.004 0.000 0.470 White 0.043 0.071 0.082 0.045 0.051 0.035 0.164 0.089 0.125 0.214 Regions Northeast 0.039 0.019 0.034 0.000 0.008 0.004 0.027 0.002 0.085 0.205 Midwest 0.054 0.174 0.102 0.001 o;083 0.052 0.164 0.112 0.209 0.231 South 0.049 0.022 0.077 0.060 0.031 0.024 0.143 0.080 0.072 0.177 West 0.034 0.063 0.055 0.103 0.046 0.043 0.238 0.093 0.044 0.233 Questionnaire Res12onse Households who garden 0.120 0.140 0.180 0.087 0.107 0.070 0.316 0.169 0.232 0.306 *Households who farm 0.220 0.328 0.368 0.005 0.227 0.292 0.461 0.606 0.057 0.548 Table 13-71. Fraction of food Intake that is Home Produced (continued) Asparaous Beets Broccoli Cabbaoe Carrots Corn Cucumbers Lettuce Lima Beans Okra Onions Total 0.063 0.203 0.015 0.038 0.043 0.078 0.148 0.010 0.121 0.270 0.056 Season Fail 0.024 0.199 0.013 0.054 0.066 0.076 0.055 0.013 0.07 0.299 0.066 Spring 0.103 0.191 0.011 0.011 0.015 0.048 0.04 0.01 0.082 0.211 0.033 Summer 0 0.209 0.034 0.08 0.063 0.118 0.32 0.017 0.176 0.304 0.091 Winter 0.019 0.215 0.006 0.008 0.025 0.043 0 0.002 0.129 0.123 0.029 Urbanization Central City 0.058 0.212 0.004 0.004 0.018 0.025 0.029 0.009 0.037 0.068 0.017 Nonmetropolitan 0.145 0.377 0.040 0.082 0.091 0.173 0.377 0.017 0.132 0.411 0.127 Surburban 0.040 0.127 O.o16 0.045 0.039 0.047 0.088 0.009 0.165 0.299 0.050 Race ---siack 0.000 0.000 0.000 0.001 0.068 0.019 0.060 0.007 0.103 0.069 0.009 White 0.071 0.224 . 0.018 0.056 0.042 0.093 0.155 0.011 0.135 0.373 0.068 Regions Northeast 0.091 0.074 0.020 0.047 0.025 0.020 0.147 0.009 0.026 0.000 0.022 Midwest 0.194 0.432 0.025 0.053 0.101* 0.124 0.193 0.020 0.149 0.224 0.098 South 0.015 0.145 0.013 0.029 0.020 0.088 0.140 0.006 0.140 0.291 0.047 West 0.015 0.202 0.006 0.029 0.039 0.069 0.11,9 0.009 0.000 0.333 0.083 Questionnaire ResQ_onse Households who garden 0.125 0.420 0.043 0.099 0.103 0.220 0.349 0.031 0.258 0.618 0.148 Households who farm 0.432 0.316 0.159 0.219 0.185 0.524 0.524 0.063 0.103 0.821 o.:i61 Table 13-71. Fraction of Food Intake that is Home Produced (continued) Peas Peppers Pumpkin Snap Beans Tomatoes White Beef Game Pork Poultry Eggs Potatoes Total 0.069 0.107 0.155 0.155 0.184 0.038 0.038 0.276 0.013 0.011 0.014 Season Fail 0.046 0.138 0.161 0.199 0.215 0.058 0.028 0.336 0.012 0.011 0.009 Spring 0.048 0.031 0.046 0.152 0.045 0.01 0.027 0.265 0.015 0.012 0.022 Summer 0.126 0.194 0.19 0.123 0.318 0.06 0.072 0.1 0.01 0.007 0.013 Winter 0.065 0.03 0.154 0.147 0.103 0.022 0.022 0.33 0.014 0.014 0.011 Urbanization Central City 0.033 0.067 0.130 0.066 0.100 0.009 0.001 0.146 0.001 0.002 0.002 Nonmetropolitan 0.123 0.228 0.250 0.307 0.313 0.080 0.107 0.323 0.040 0.026 0.029 Surburban 0.064 0.086 0.127 0.118 0.156 0.029 0.026 0.316 0.006 0.011 0.014 Race ---sia°ck 0.047 0.039 0.022 0.046 0.060 0.007 0.000 0.000 0.000 0.001 0.002 White 0.076 0.121 0.187 0.186 0.202 0.044 0.048 0.359 0.017 0.014 0.017 Regions Northeast 0.021 0.067 0.002 0.052 0.117 0.016 0.014 0.202 0.006 0.002 0.004 Midwest 0.058 0.188 0.357 0.243 0.291 0.065 0.076 0.513 0.021 0.021 0.019 South 0.106 0.113 0.044 0.161 0.149 0.042 0.022 0.199 0.012 0.012 0.012 West 0.051 0.082 0.181 0.108 0.182 0.013 0.041 0.207 0.011 0.008 0.021 Questionnaire Res12onse Households who garden 0.193 0.246 0.230 0.384 0.398 0.090 Households who farm 0.308 0.564 0.824 0.623 0.616 0.134 0.485 0.242 0.156 0.146 Households who raise animals 0.478 0.239 0.151 0.214 Households who hunt 0.729 Source: Based on EPA's analvses of the 1987-88 NFCS Table 13-72. Confidence in Homegrown Food Consumption Recommendations Considerations Rationale Rating Study Elements . Level of Peer Review USDA and EPA review High . Accessibility Methods described in detail in Handbook High . Reproducibility see above High . Focus on factor of interest Yes High . Data pertinent to U.S. U.S. population High . Primary data Yes High . Currency 1987-88 Medium . Adequacy of data Statistical method used to estimate long-High (Means & Short-term distributions) collection period term distribution from one-week survey Low (Long-term distributions) data. . Validity of approach Individual intakes inferred from household Medium (Means) consumption. Low (Distributions)
Study size 10,000 individuals, 4500 households High
Representativeness of the Nationwide survey representative of High population general U.S. population . Bias in study design (high Non-response bias can not be ruled out Medium rating desirable) due to low response rate. . Measurement Error Individuals' estimates of food weights Medium (high rating desirable) imprecise Other Elements . Number of studies 1 Low . Agreement between N/A researchers Overall Rating Highest confidence in means, lowest Medium (Means) confidence in long term percentiles Medium (Short-term distributions) Low (Long-term distributions l Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data Food Household Code/Definition Individual. Code Product MAJOR FOOD GROUPS Total Fruits 50-Fresh Fruits 6-Fruits citrus citrus fruits and juices other vitamin-C rich dried fruits other fruits other fruits 512-Commercially Canned Fruits fruits/juices & nectar 522-Commercially Frozen Fruits fruit/juices baby food 533-Canned Fruit Juice (includes baby foods) 534-Frozen Fruit Juice 535-Aseptically Packed Fruit Juice 536-Fresh Fruit Juice 542-Dried Fruits (includes baby foods) Total 48-Potatoes, Sweetpotatoes 7-Vegetables (all forms) Vegetables 49-Fresh Vegetables white potatoes & PR starchy dark green dark green vegetables deep yellow deep yellow vegetables tomatoes tomatoes and tom. mixtures light green other vegetables other veg. and mixtures/baby food 511-Commercially Canned Vegetables veg. with meat mixtures 521-Commercially Frozen Vegetables (includes baby foods; mixtures, mostly vegetables) 531-Canned Vegetable Juice 532-Frozen Vegetable Juice 537-Fresh Vegetable Juice 538-Aseptically Packed Vegetable Juice 541-Dried Vegetables (does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby foods except mixtures/dinners) Total Meats 44-Meat 20-Meat, type not specified beef 21-Beef pork 22-Pork veal 23-Lamb, veal, game, carcass meat lamb 24-Poultry mutton 25-Organ meats, sausages, lunchmeats, meat goat spreads game (excludes meat, poultry, and fish with non-meat items; lunch meat frozen plate meals; soups and gravies with meat, poultry mixtures and fish base; and gelatin-based drinks; includes baby 451-Poultry foods) (does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby foods except mixtures) Total Dairy 40-Milk Equivalent 1-Milk and Milk Products fresh fluid milk milk and milk drinks processed milk cream and cream substitutes cream and cream substitutes milk desserts, sauces, and gravies frozen desserts with milk cheeses cheese (includes regular fluid milk, human milk, imitation milk dairy-based dips products, yogurt, milk-based meal replacements, and (does not include soups, sauces, gravies, mixtures, and infant formulas) readv-to-eat dinners)

Food Product Total Fish White Potatoes Peppers Onions Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) Household Code/Definition 452-Fish, Shellfish various species fresh, frozen, commercial, dried (does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners) Individual Code 26-Fish, Shellfish various species and forms (excludes meat, poultry, and fish with non-meat items; frozen plate meals; soups and gravies with meat, poultry and fish base; and Qelatin-based drinks) INDIVIDUAL FOODS 4811-White Potatoes, fresh 4821-White Potatoes, commercially canned 4831-White Potatoes, commercially frozen 4841-White Potatoes, dehydrated 4851-White Potatoes, chips, sticks, salad (does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners) 4913-Green/Red Peppers, fresh 5111201 Sweet Green Peppers, commercially canned 5111202 Hot Chili Peppers, commercially canned 5211301 Sweet Green Peppers, commercially frozen 5211302 Green Chili Peppers, commercially frozen 5211303 Red Chili Peppers, commercially frozen 5413112 Sweet Green Peppers, dry 5413113 Red Chili Peppers, dry (does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners) 4953-Onions, Garlic, fresh onions chives garlic leeks 5114908 Garlic Pulp, raw 5114915 Onions, commercially canned 5213722 Onions, commercially frozen 5213723 Onions with Sauce, commercially frozen 5413103 Chives, dried 5413105 Garlic Flakes, dried 541311 O Onion Flakes, dried {does not include soups; sauces, gravies, mixtures, and ready-to-eat dinners) 71-White Potatoes and PR Starchy Veg. baked, boiled, chips, sticks, creamed, scalloped, au gratin, fried, mashed, stuffed, puffs, salad, recipes, soups, Puerto Rican starchy vegetables (does not include vegetables soups; vegetable mixtures; or veQetable with meat mixtures) 7512100 Pepper, hot chili, raw g.-7512200 Pepper, raw 7512210 Pepper, sweet green, raw 7512220 Pepper, sweet red, raw 7522600 Pepper, green, cooked, NS as to fat added 7522601 Pepper, green, cooked, fat not added 7522602 Pepper, green, cooked, fat added 7522604 Pepper, red, cooked, NS as to fat added 7522605 Pepper, red, cooked, fat not added 7522606 Pepper, red, cooked, fat added 7522609 Pepper, hot, cooked, NS as to fat added 7522610 Pepper, hot, cooked, fat not added 7522611 Pepper, hot, cooked, fat added 7551101 Peppers, hot, sauce 7551102 Peppers, pickled (does not include vegetable soups; vegetable mixtures; or veQetable with meat mixtures) 7510950 Chives, raw 7511150 Garlic, raw 7511250 Leek, raw 7511701 Onions, young green, raw 7511702 Onions, mature 7521550 Chives, dried 7521740 Garlic, cooked 7522100 Onions, mature cooked, NS as to fat added 7522101 Onions, mature cooked, fat not added 7522102 Onions, mature cooked, fat added 7522103 Onions, pearl cooked 7522104 Onions, young green cooked, NS as to fat 7522105 Onions, young green cooked, fat not added 7522106 Onions, young green cooked, fat added 7522110 Onion, dehydrated 7541501 Onions, creamed 7541502 Onion rings (does not include vegetable soups; vegetable mixtures; or veaetable with meat mixtures\ Food Product Corn Apples Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) Household Code/Definition 4956-Corn, fresh 5114601 Yellow Corn, commercially canned 5114602 White Corn, commercially canned 5114603 Yellow Creamed Corn, commercially canned 5114604 White Creamed Corn, commercially canned 5114605 Corn on Cob, commercially canned 5114607 Hominy, canned 5115306 Low Sodium Corn, commercially canned 5115307 Low Sodium Cr. Corn, commercially canned 5213501 Yellow Corn on Cob, commercially frozen 5213502 Yellow Corn off Cob, commercially frozen 5213503 Yell. Com with Sauce, commercially frozen 5213504 Com with other Veg., commercially frozen 5213505 White Com on Cob, commercially frozen 5213506 White Corn off Cob, commercially frozen 5213507 Wh. Corn with Sauce, commercially frozen 5413104 Corn, dried 5413106 Hominy, dry 5413603 Corn, instant baby food (does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby food) 5031-Apples, fresh 5122101 Applesauce with sugar, commercially canned 5122102 Applesauce without sugar, comm. canned 5122103 Apple Pie Filling, commercially canned 5122104 Apples, Applesauce, baby/jr., comm. canned 5122106 Apple Pie Filling, Low Cal., comm. canned 5223101 Apple Slices, commercially frozen

5332101 Apple Juice, canned 5332102 Apple Juice, baby, Comm. canned 5342201 Apple Juice, comm. frozen 5342202 Apple Juice, home frozen 5352101 Apple Juice, aseptically packed 5362101 Apple Juice, fresh 5423101 Apples, dried (includes baby food; except mixtures) Individual Code 7510960 Corn, raw 7521600 Corn, cooked, NS as to color/fat added 7521601 Corn, cooked, NS as to color/fat not added 7521602 Corn, cooked, NS as to color/fat added 7521605 Corn, cooked, NS as to color/cream style 7521607 Corn, cooked, dried 7521610 Corn, cooked, yellow/NS as to fat added 7521611 Corn, cooked, yellow/fat not added 7521612 Corn, cooked, yellow/fat added 7521615 Corn, yellow, cream style 7521616 Corn, cooked, yell. & wh./NS as to fat 7521617 Corn, cooked, yell. & wh./fat not added 7521618 Corn, cooked, yell. & wh./fat added 7521619 Corn, yellow, cream style, fat added 7521620 Corn, cooked, white/NS as to fat added 7521621 Corn, cooked, white/fat not added 7521622 Corn, cooked, white/fat added 7521625 Corn, white, cream style 7521630 Corn, yellow, canned, low sodium, NS fat 7521631 Corn, yell., canned, low sod., fat not add 7521632 Corn, yell., canned, low sod., fat added 7521749 Hominy, cooked 752175-Hominy, cooked 7541101 Corn scalloped or pudding 7541102 Corn fritter 7541103 Corn with cream sauce 7550101 Corn relish 76405-Corn, batiy *(does not include vegetable soups; vegetable mixtures; or veQetable with meat mixtures; includes baby food) 6210110 Apples, dried, uncooked 6210115 Apples, dried, uncooked, low sodium 6210120 Apples, dried, cooked, NS as to sweetener 6210122 Apples, dried, cooked, unsweetened 6210123 Apples, dried, cooked, with sugar 6310100 Apples, raw
6310111 Applesauce, NS as to sweetener 6310112 Applesauce, unsweetened 6310113 Applesauce with sugar 6310114 Applesauce with low calorie sweetener 6310121 Apples, cooked or canned with syrup 6310131 Apple, baked NS as to sweetener 6310132 Apple, baked, unsweetened 6310133 Apple, baked with. sugar 6310141 Apple rings, fried 6310142 Apple, pickled 6310150 Apple, fried 6340101 Apple, salad 6340106 Apple, candied 6410101 Apple cider 6410401 Apple juice 6410405 Apple juice with vitamin C 6710200 Applesauce baby fd., NS as to str. or jr. 6710201 Applesauce baby food, strained 6710202 Applesauce baby food, junior 6720200 Apple juice, baby food lincludes babv food* exceot mixtures\

Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) Food Household Code/Definition Individual Code Product Tomatoes 4931-Tomatoes, fresh 74-Tomatoes and Tomato Mixtures 5113-Tomatoes, commercially canned raw, cooked, juices, sauces, mixtures, soups, 5115201 Tomatoes, low sodium, commercially canned sandwiches 5115202 Tomato Sauce, low sodium, comm. canned 5115203 Tomato Paste, low sodium, comm. canned 5115204 Tomato Puree, low sodium, comm. canned 5311-Canned Tomato Juice and Tomato Mixtures 5321-Frozen Tomato Juice 5371-Fresh Tomato Juice 5381102 Tomato Juice, aseptically packed 5413115 Tomatoes, dry 5614-Tomato Soup 5624-Condensed Tomato Soup 5654-Dry Tomato Soup (does not include mixtures, and ready-to-eat dinners) Snap Beans 4943-Snap or Wax Beans, fresh 7510180 Beans, string, green, raw 5114401 Green or Snap Beans, commercially canned 7520498 Beans, string, cooked, NS color/fat added 5114402 Wax or Yellow Beans, commercially canned 7520499 Beans, string, cooked, NS color/no fat 5114403 Beans, commercially canned 7520500 Beans, string, cooked, NS color & fat 5115302 Green Beans, low sodium, comm. canned 7520501 Beans, string, cooked, green/NS fat 5115303 Yell. or Wax Beans, low sod., comm. canned 7520502 Beans, string, cooked, green/no fat 5213301 Snap or Green Beans, comm. frozen 7520503 Beans, string, cooked, green/fat 5213302 Snap or Green w/sauce, comm. frozen 7520511 Beans, sir., canned, low sod.,green/NS fat 5213303 Snap or Green Beans w/other veg., comm. fr. 7520512 Beans, sir., *canned, low sod.,green/no fat 5213304 Sp. or Gr. Beans w/other veg./sc., comm. fr. 7520513 Beans, sir., canned, low.sod.,green/fat 5213305 Wax or Yell. Beans, comm. frozen 7520600 Beans, string, cooked, yellow/NS fat (does not include soups, mixtures, and ready-to-eat 7520601 Beans, string, cooked, yellow/no fat dinners; includes baby foods) 7520602 Beans, string, cooked, yellow/fat 7540301 Beans, string, green, creamed 7540302 Beans, string, green, w/mushroom 7540401 Beans, string, yellow, creamed 7550011 Beans, string, green, pickled 7640100 Beans, green, string, baby 7640101 Beans, green, string, baby, sir. 7640102 Beans, green, string, baby, junior 7640103 Beans, green, string, baby, creamed *(does not include vegetaqle soups; vegetable mixtures; or. veaetable with meat mixtures; includes babv foods) Beef 441-Beef 21-Beef (does not include soups, sauces, gravies, mixtures, and beef, nfs ready-to-eat dinners; includes baby foods except beef steak *mixtures) beef oxtails, neckbones, ribs roasts, stew meat, corned, brisket, sandwich steaks ground beef, patties, meatballs other beef items beef baby food (excludes meat, poultry, and fish with non-meat items; frozen plate meals; soups and gravies with meat, poultry and fish base; and gelatin-based drinks; includes baby food\ Food Product Pork Game Poultry Eggs Broccoli Carrots Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) Household Code/Definition 442-Pork (does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby foods except mixtures) 445-Variety Meat, Game (does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby foods except mixtures) 451-Poultry (does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby foods except mixtures) 46-Eggs (fresh equivalent) fresh processed eggs, substitutes (does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby foods except mixtures) 4912-Fresh Broccoli (and home canned/froz.) 5111203 Broccoli, comm. canned 52112-Comm. Frozen Broccoli (does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby foods except mixtures) 4921-Fresh Carrots (and home canned/froz.) 51121-Comm. Canned Carrots 5115101 Carrots, Low Sodium, Comm. Canned 52121-Comm. Frozen Carrots 5312103 Comm. Canned Carrot Juice 5372102 Carrot Juice Fresh 5413502 Carrots, Dried Baby Food (does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby foods except mixtures) Individual Code 22-Pork pork, nfs; ground dehydrated chops steaks, cutlets ham roasts Canadian bacon bacon, salt pork other pork items pork baby food (excludes meat, poultry, and fish with non-meat items; frozen plate meals; soups and gravies with meat, poultry and fish base; and gelatin-based drinks; includes baby food)

233-Game (excludes meat, poultry, and fish with non-meat items; frozen plate meals; soups and gravies with meat, poultry and fish base; and gelatin-based drinks) 24-Poultry chicken turkey duck other poultry poultry baby food (excludes meat, poultry, and fish with non-meat items; frozen plate meals; soups and gravies with meat, poultry and fish base; and gelatin-based drinks; includes baby food) 3-Eggs eggs egg mixtures egg substitutes eggs baby food froz. meals with egg as main ingred. (includes baby foods) 722-Broccoli (all forms) (does not include vegetable soups; vegetable mixtures; or vegetable with meat mixtures) 7310-*carrots (all forms) 7311140 Carrots in Sauce 7311200 Carrot Chips 76201-Carrots, baby (does not include vegetable soups; vegetable mixtures; or vegetable with meat mixtures; includes baby foods except mixtures)

Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) Food Household Code/Definition Individual Code Product Pumpkin 4922-Fresh Pumpkin, Winter Squash (and home . 732-Pumpkin (all forms) canned/froz.) 733-Winter squash (all forms) 51122-Pumpkin/Squash, Baby or Junior, Comm. 76205-Squash, baby Canned (does not include vegetable soups; vegetables mixtures; 52122-Winter Squash, Comm. Frozen or vegetable with meat mixtures; includes baby foods) 5413504 Squash, Dried Baby Food (does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby foods except mixtures) Asparagus 4941-Fresh Asparagus (and home canned/froz.) 7510080 Asparagus, raw 5114101 Comm. Canned Asparagus 75202-Asparagus, cooked 5115301 Asparagus, Low Sodium, Comm. Canned 7540101 Asparagus, creamed or with cheese 52131-Comm. Frozen Asparagus (does not include vegetable soups; vegetables mixtures, (does not include soups, sauces, gravies, mixtures, and or vegetable with meat mixtures) ready-to-eat dinners; includes baby foods except mixtures) Lima Beans 4942-Fresh Lima and Fava Beans (and home 7510200 Lima Beans, raw canned/froz.) 752040-Lima Beans, cooked 5114204 Comm. Canned Mature Lima Beans 752041-Lima Beans, canned 5114301 Comm. Canned Green Lima Beans 75402-Lima Beans with sauce 5115304 Comm. Canned Low Sodiuni Lima Beans (does not include vegetable soups; vegetable mixtures; 52132-Comm. Frozen Lima Beans or vegetable with meat mixtures; does not include 54111-Dried Lima Beans succotash) 5411306 Dried Fava Beans (does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby foods except mixtures; does not include succotash) Cabbage 4944-Fresh Cabbage (and home canned/froz.) 7510300 Cabbage, raw 4958601 Sauerkraut, home canned or pkgd 7510400 Cabbage, Chinese, raw 5114801 Sauerkraut, comm. canned 7510500 Cabbage, red, raw 5114904 Comm. Canned Cabbage 7514100 Cabbage salad or coleslaw 5114905 Comm. Canned Cabbage (no sauce; incl. 7514130 Cabbage, Chinese, salad baby) 75210-Chinese Cabbage, cooked 5115501 Sauerkraut, low sodium., comm. canned 75211-Green Cabbage, cooked 5312102 Sauerkraut Juice, comm. canned 75212-Red Cabbage, cooked (does not include soups, sauces, gravies, mixtures, arid 752130-Savoy Cabbage, cooked ready-to-eat dinners; includes baby foods except 75230-Sauerkraut, cooked mixtures) 7540701 Cabbage, creamed 755025-Cabbage, pickled or in relish (does not include vegetable soups; vegetable mixtures; or vegetable with meat mixtures) Lettuce 4945-Fresh Lettuce, French Endive (and home 75113-Lettuce, raw canned/froz.) 75143-Lettuce salad with other veg. (does not include soups, sauces, gravies, mixtures, and 7514410 Lettuce, wilted, with bacon dressing ready-to-eat dinners; includes baby foods except 7522005 Lettuce, cooked mixtures) (does not include vegetable soups; vegetable mixtures; or vegetable with meat mixtures) Okra 4946-Fresh Okra (and home canned/froz.) 7522000 Okra, cooked, NS as to fat 5114914 Comm. Canned Okra 7522001 Okra, cooked, fat not added 5213720 Comm. Frozen Okra 7522002 Okra, cooked, fat added 5213721 Comm. Frozen Okra with 0th. Veg. & Sauce 752201 O Lufta, cooked (Chinese Okra) (does not include soups, sauces, gravies, mixtures, and 7541450 Okra, fried ready-to-eat dinners; includes baby foods except 7550700 Okra, pickled mixtures) (does not include vegetable soups; vegetable mixtures; or veaetable with meat mixtures) Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) Food Product Peas Cucumbers Beets Strawberries Household Code/Definition 4947-Fresh Peas (and home canned/froz.) 51147-Comm Canned Peas (incl. baby) 5115310 Low Sodium Green or English Peas (canned) 5115314 Low Sod. Blackeye, Gr. or Imm. Peas (canned) 5114205 Blackeyed Peas, comm. canned 52134-Comm. Frozen Peas 5412-Dried Peas and Lentils (does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby foods except mixtures) 4952-Fresh Cucumbers (and home canned/froz.) (does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby foods except mixtures) 4954-Fresh Beets (and home canned/froz.) 51145* Canned Beets (incl. baby) 5115305 Low Sodium Beets (canned) 5213714 Comm. Frozen Beets 5312104 Beet Juice (does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby foods except mixtures) 5022-Fresh Strawberries 5122801 Comm. Canned Strawberries with sugar 5122802 Comm. Canned Strawberries without sugar 5122803 Canned Strawberry Pie Filling 5222-Comm. Frozen Strawberries (does not include ready-to-eat dinners; includes baby foods exceot mixtures) Individual Code 7512000 Peas, green, raw 7512775 Snowpeas, raw 75223-Peas, cowpeas, field or blackeye, cooked 75224-Peas, green, cooked 75225-Peas, pigeon, cooked 75231-Snowpeas, cooked 7541650 Pea salad 7541660 Pea salad with cheese 75417-Peas, with sauce or creamed ' 76409-Peas, baby, 76411-Peas, creamed, baby (does not include vegetable soups; vegetable mixtures; or vegetable with meat mixtures; includes baby foods except mixtures) 7511100 Cucumbers, raw 75142-Cucumber salads 752167-Cucumbers, cooked 7550301 Cucumber pickles, dill 7550302 Cucumber pickles, relish 7550303 Cucumber pickles, sour 7550304 Cucumber pickles, sweet 7550305 Cucumber pickles, fresh 7550307 Cucumber, Kim Chee 7550311 Cucumber pickles, dill, reduced salt 7550314 Cucumber pickles, sweet, reduced salt * (does not include vegetable soups; vegetable mixtures; or vegetable with meat mixtures) 7510250 Beets, raw 752080-Beets, cooked 752081-Beets, canned 7540501 Beets, harvard 7550021 Beets, pickled 76403-Beets, baby (does not include vegetable soups; vegetable mixtures; or vegetable with meat mixtures; includes baby foods except mixtures) 6322-Strawberries

6413250 Strawberry Juice (includes baby food; except mixtures)

Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) Food Household Code/Definition *Individual Code Product Other 5033-Fresh Berries Other than Strawberries 6320-Other Berries Berries 5122804 Comm. Canned Blackberries with sugar 6321-Other Berries 5122805 Comm. Canned Blackberries without sugar 6341101 Cranberry salad 5122806 Comm. Canned Blueberries with sugar 6410460 Blackberry Juice 5122807 Comm. Canned Blueberries without sugar 64105-Cranberry Juice 5122808 Canned Blueberry Pie Filling (includes baby food; except mixtures) 5122809 Comm. Canned Gooseberries with sugar 5122810 Comm. Ca.nned Gooseberries without sugar 5122811 Comm. Canned Raspberries with sugar 5122812 Comm. Canned Raspberries without sugar 5122813 Comm. Canned Cranberry Sauce 5122815 Comm. Canned Cranberry-Orange Relish 52233-Comm. Frozen Berries (not strawberries) 5332404 Blackberry Juice (home and comm. canned) 5423114 Dried Berries (not strawberries) (does not include ready-to-eat dinners; includes baby foods exceot mixtures\ Peaches 5036-Fresh Peaches 62116-Dried Peaches 51224-Comm. Canned Peaches (incl. baby) 63135-Peaches 5223601 Comm. Frozen Peaches 6412203 Peach Juice 5332405 Home Canned Peach Juice 6420501 Peach Nectar 5423105 Dried Peaches (baby) 67108-Peaches,baby 5423106 Dried Peaches 6711450 Peaches, dry, baby (does not include ready-to-eat dinners; includes baby (includes baby food; except mixtures) foods except mixtures) Pears 5037-Fresh Pears 62119-Dried Pears 51225-Comm. Canned Pears (incl. baby) 63137-Pears 5332403 Comm, Canned Pear Juice, baby 6341201 Pear salad 5362204 Fresh Pear Juice 6421501 Pear Nectar 5423107 Dried Pears 67109-Pears, baby (does not include ready-to-eat dinners; includes baby 6711455 Pears, dry, baby foods exceot mixtures\ (includes babv food* exceot mixtures\ Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) Food Household Code/Definition Individual Code Product EXPOSED/PROTECTED FRUITSNEGETABLES, ROOT VEGETABLES Exposed 5022-Strawberries, fresh 62101-Apple, dried Fruits 5023101 Acerola, fresh 62104-Apricot, dried 5023401 Currants, fresh 62108-Currants, dried 5031-Apples/Applesauce, fresh 62110-Date, dried 5033-Berries other than Strawberries, fresh 62116-Peaches, dried 5034-Cherries, fresh 62119-Pears, dried 5036-Peaches, fresh 62121-Plum, dried 5037-Pears, fresh 62122-Prune, dried 50381-Apricots, Nectarines, Loquats, fresh 62125-Raisins 5038305 Dates, fresh 63101-Apples/applesauce 50384-Grapes, fresh 63102-Wi-apple 50386-Plums, fresh 63103-Apricots 50387-Rhubarb, fresh 63111-Cherries, maraschino 5038805 Persimmons, fresh 63112-Acerola 5038901 Sapote, fresh 63113-Cherries, sour 51221-Apples/Applesauce, canned 63115-Cherries, sweet 51222-Apricots, canned 63117-Currants, raw 51223-Cherries, canned 63123-Grapes 51224-Peaches, canned 6312601 Juneberry 51225-Pears, canned 63131-Nectarine 51228-Berries, canned 63135-Peach 5122903 Grapes with sugar, canned 63137-Pear 5122904 Grapes without sugar, canned 63139-Persimmons 5122905 Plums with sugar, canned 63143-Plum 5122906 Plums without sugar, canned 63146-Quince 5122907 Plums, canned, baby 63147-Rhubarb/Sapodillo 5122911 Prunes, canned, baby 632-Berries 5122912 Prunes, with sugar, canned 64101-Apple Cider 5122913 Prunes, without sugar, canned 64104-Apple Juice 5122914 Raisin Pie Filling 64105-Cranberry Juice 5222-Frozen Strawberries 64116-Grape Juice 52231-Apples Slices, frozen 64122-Peach Juice 52233-Berries, frozen 64132-Prune/Strawberry Juice 52234-Cherries, frozen 6420101 Apricot Nectar 52236-Peaches, frozen 64205-Peach Nectar 52239-Rhubarb, frozen 64215-Pear Nectar 53321-Canned Apple Juice 67102-Applesauce, baby 53322-Canned Graoe Juice 67108-Peaches babv Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) Food Household Code/Definition Individual Code Product Exposed 5332402 Canned Prune Juice 67109-Pears, baby Fruits 5332403 Canned Pear Juice 6711450 Peaches, baby, dry (continued) 5332404 Canned Blackberry Juice 6711455 Pears, baby, dry 5332405 Canned Peach Juice 67202-Apple Juice, baby 53421-Frozen Grape Juice 6720380 White Grape Juice, baby 5342201 Frozen Apple Juice, comm. fr. 67212-Pear Juice, baby 5342202 Frozen Apple Juice, home fr. (includes baby except mixtures; excludes 5352101 Apple Juice, asep. packed fruit mixtures) 5352201 Grape Juice, asep. packed 5362101 Apple Juice, fresh 5362202 Apricot Juice, fresh 5362203 Grape Juice, fresh 5362204 Pear Juice, fresh 5362205 Prune Juice, fresh 5421-Dried Prunes 5422-Raisins, Currants, dried 5423101 Dry Apples 5423102 Dry Apricots 5423103 Dates without pits 5423104 Dates with pits 5423105 Peaches, dry, baby 5423106 Peaches, dry 5423107 Pears, dry 5423114 Berries, dry 5423115 Cherries, dry (includes baby foods) Protected 501-Citrus Fruits, fresh 61-Citrus Fr., Juices (incl. cit. juice mixtures) Fruits 5021-Cantaloupe, fresh 62107-Bananas, dried 5023201 Mangoes, fresh 62113-Figs, dried 5023301 Guava, fresh 62114-Lychees/Papayas, dried 5023601 Kiwi, fresh 62120-Pineapple, dried 5023701 Papayas, fresh 62126-Tamarind, dried 5023801 Passion Fruit, fresh 63105-Avocado, raw 5032-Bananas, Plantains, fresh 63107-Bananas 5035-Melons other than Cantaloupe, fresh 63109-Cantaloupe, Carambola 50382-Avocados, fresh 63110-Cassaba Melon 5038301 Figs, fresh 63119-Figs 5038302 Figs, cooked 63121-Genip 5038303 Figs, home canned 63125-Guava/Jackfruit, raw 5038304 Figs, home frozen 6312650 Kiwi 50385-Pineapple, fresh 6312651 Lychee, raw 5038801 Pomegranates, fresh 6312660 Lychee, cooked 5038902 Cherimoya, fresh 63127-Honeydew 5038903 Jackfruit, fresh 63129-Mango 5038904 Breadfruit, fresh 63133-Papaya 5038905 Tamarind, fresh 63134-Passion Fruit 5038906*Carambola, fresh 63141-Pineapple 5038907 Longan, fresh 63145-Pomegranate 5121-Citrus, canned 63148-Sweetsop, Soursop, Tamarind 51226-Pineapple, canned 63149-Watermelon 5122901 Figs with sugar, canned 64120-Papaya Juice 5122902 Figs without sugar, canned 64121-Passion Fruit Juice 5122909Bananas,canned,baby 64124-Pineapple Juice 5122910 Bananas and Pineapple, canned, baby 64133-Watermelon Juice 5122915 Litchis canned 6420150 Banana Nectar Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) Food Household Code/Definition Individual Code Product Protected 5122916 Mangos with sugar, canned 64202-Cantaloupe Nectar Fruits 5122917 Mangos without sugar, canned 64203-Guava Nectar (continued) 5122918 Mangos, canned, baby 64204-Mango Nectar 5122920 Guava with sugar, canned 64210-Papaya Nectar 5122921 Guava without sugar, canned 64213-Passion Fruit Nectar 5122923 Papaya with sugar, canned 64221-Soursop Nectar 5122924 Papaya without sugar, canned 6710503Bananas, baby 52232-Bananas, frozen 6711500 Bananas, baby, dry 52235-Melon, frozen 6720500 Orange Juice, baby 52237-Pineapple, frozen 6721300 Pineapple Juice, baby 5331-Canned Citrus Juices (includes baby except mixtures; excludes 53323-Canned Pineapple Juice fruit mixtures) 5332408 Canned Papaya Juice 533241 O Canned Mango Juice 5332501*Canned Papaya Concentrate 5341-Frozen Citrus Juice 5342203 Frozen Pineapple Juice 5351-Citrus and Citrus Blend Juices, asep. packed 5352302 Pineapple Juice, asep. packed 5361-Fresh Citrus and Citrus Blend Juices 5362206 Papaya Juice, fresh 5362207 Pineapple-Coconut Juice, fresh 5362208 Mango Juice, fresh 5362209 Pineapple Juice, fresh 5423108 Pineapple, dry 5423109 Papaya, dry 5423110 Bananas, dry 5423111 Mangos, dry 5423117 Litchis, dry 5423118 Tamarind, dry 5423119 Plantain, dry (includes babv foods\ Food Product Exposed Veg. Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) Household Code/Definition 491-Fresh Dark Green Vegetables 493-Fresh Tomatoes 4941-Fresh Asparagus 4943-Fresh. Beans, Snap or Wax 4944-Fresh Cabbage 4945-Fresh Lettuce 4946-Fresh Okra 49481-Fresh Artichokes 49483-Fresh Brussel Sprouts 4951-Fresh Celery 4952-. Fresh Cucumbers 4955-Fresh Cauliflower 49581,03 Fresh Kohlrabi 4958111 Fresh Jerusalem Artichokes 4958112 Fresh Mushrooms 4958113 Mushrooms, home canned 4958114 Mushrooms, home frozen 4958118 Fresh Eggplant 4958119 Eggplant, cooked 4958120 Eggplant, home frozen 4958200 Fresh Summer Squash 4958201 Summer Squash, cooked 4958202 Summer Squash, home canned 4958203 Summer Squash, home frozen 4958402 Fresh Bean Sprouts 4958403 Fresh Alfalfa Sprouts 4958504 Bamboo Shoots* 4958506 Seaweed 4958508 Tree Fern, fresh 4958601 Sauerkraut 5111-Dark Green Vegetables (all are exposed) 5113-Tomatoes 5114101 Asparagus, comm. canned 51144-Beans, green, snap, yellow, comm. canned 5114704 Snow Peas, comm. canned 5114801 Sauerkraut, comm. canned 5114901 Artichokes, comm. canned 5114902 Bamboo Shoots, comm. canned . 5114903 Bean Sprouts, comm. canned 5114904 Cabbage, comm. canned 5114905 Cabbage, comm. canned, no sauce

5114906 Cauliflower, comm. canned, no sauce 5114907 Eggplant, comm. canned, no sauce 5114913 Mushrooms, comm. canned 5114914 Okra, comm. canned 5114918 Seaweeds, comm. canned 5114920 Summer Squash, comm. canned Individual Code 721-Dark Green Leafy Veg. 722-Dark Green Nonleafy Veg. 74-Tomatoes and Tomato Mixtures 7510050 Alfalfa Sprouts 7510075 Artichoke, Jerusalem, raw 7510080 Asparagus, raw 75101-Beans, sprouts and green, raw 7510275 Brussel Sprouts, raw 7510280 Buckwheat Sprouts, raw 7510300 Cabbage, raw 7510400 Chinese, raw 7510500 Cabbage, Red, raw 7510700 Cauliflower, raw 7510900 Celery, raw 7510950 Chi_ves, raw 7511100 Cucumber, raw 7511120 Eggplant, raw 7511200 Kohlrabi, raw 75113-Lettuce, raw 7511500 Mushrooms, raw 7511900 Parsley 7512100 Pepper, hot chili 75122-Peppers, raw 7512750 Seaweed, raw 7512775 Snowpeas, raw 75128-Summer Squash, raw 7513210 Celery Juice 7514100 Cabbage or coleslaw 7514130 Chinese Cabbage Salad 7514150 Celery with cheese 75142-Cucumber salads 75143-Lettuce salads 7514410 Lettuce, wilted with bacon dressing 7514600 Greek salad 7514700 Spinach salad 7520600 Algae, dried
75201-Artichoke, cooked 75202-Asparagus, cooked 75203-Bamboo shoots, cooked 752049-Beans, string, cooked 75205-Beans, green, cooked/canned 75206-Beans, yellow, cooked/canned 75207-Bean Sprouts, cooked 752085-Breadfruit 752090-Brussel Sprouts, cooked 75210-Cabbage, Chinese, cooked 75211-Cabbage, green, cooked Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) Food Household Code/Definition Individual Code Product Exposed 5114923 Chinese or Celery Cabbage, comm. canned 75212-Cabbage, red, cooked Veg. 51152-Tomatoes, canned, low sod. 752130-Cabbage, savoy, cooked (cont.) 5115301 Asparagus, canned, low sod. 75214-Cauliflower 5115302 Beans, Green, canned, low sod. 75215-Celery, Chives, Christophine (chayote) 5115303 Beans, Yellow, canned, low sod. 752167-Cucumber, cooked 5115309 Mushrooms, canned, low sod. 752170-Eggplant, cooked 51154-Greens, canned, low sod. 752171-Fern shoots 5115501 Sauerkraut, low sodium 752172-Fern shoots 5211-Dark Gr. Veg., comm. frozen (all exp.) 752173-Flowers of sesbania, squash or lily 52131-Asparagus, comm. froz. 7521801 Kohlrabi, cooked 52133-Beans, snap, green, yellow, comm. froz. 75219-Mushrooms, cooked 5213407 Peapods, comm froz. 75220-Okra/lettuce, cooked 5213408 Peapods, with sauce, comm froz. 7522116 Palm Hearts, cooked 5213409 Peapods, with other veg., comm froz. 7522121 Parsley, cooked 5213701 Brussel Sprouts, comm. froz. 75226-Peppers, pimento, cooked *5213702 Brussel Sprouts, comm. froz. with cheese 75230-Sauerkraut, cooked/canned 5213703 Brussel Sprouts,. comm. froz. with other veg. 75231-Snowpeas, cooked 5213705 Cauliflower, comm. froz. 75232-Seaweed 5213706 Cauliflower, comm. froz. with sauce 75233-Summer Squash 5213707 Cauliflower, comm. froz. with other veg. 7540050 Artichokes, stuffed 5213708 Caul., comm. froz. with other veg. & sauce 7540101 Asparagus, creamed or with cheese 5213709 Summer Squash, comm. froz. 75403-Beans, green with sauce 5213710 s.umm.er Squash, comm. froz. with other veg. 75404-Beans, yellow with sauce 5213716 Eggplant, comm. froz. 7540601 Brussel Sprouts, creamed 5213718 Mushrooms with sauce, comm. froz. 7540701 Cabbage, creamed 5213719 Mushrooms, comm. froz. 75409-Cauliflower, creamed 5213720 Okra, comm. froz. 75410-Celery/Chiles, creamed 5213721 Okra, comm. froz., with sauce 75412-Eggplant, fried, with sauce, etc. 5311-Canned Tomato Juice and Tomato Mixtures 75413-Kohlrabi, creamed 5312102 Canned Sauerkraut Juice 75414-Mushrooms, Okra, fried, stuffed, creamed 5321-Frozen Tomato Juice 754180-Squash, baked, fried, creamed, etc. 5371-Fresh Tomato Juice 7541822 Christophine, creamed 5381102 Aseptically Packed Tomato Juice 7550011 Beans, pickled 5413101 Dry Algae 7550051 Celery, pickled 5413102 Dry Celery 7550201 Cauliflower, pickled 5413103 Dry Chives 755025-Cabbage, pickled 5413109 Dry Mushrooms 7550301 Cucumber pickles, dill 5413111 Dry Parsley 7550302 Cucumber pickles, relish 5413112 Dry Green Peppers 7550303 Cucumber pickles, sour 5413113 Dry Red Peppers 7550304 Cucumber pickles, sweet 5413114 Dry Seaweed 7550305 Cucumber pickles, fresh 5413115 Dry Tomatoes 7550307 Cucumber, Kim Chee (does not include soups, sauces, gravies, mixtures, and 7550308 Eggplant, pickled ready-to-eat dinners; includes baby foods except 7550311 Cucumber pickles, dill, reduced salt mixtures) 7550314 Cucumber pickles, sweet, reduced salt 7550500 Mushrooms, pickled 7550700 Okra, pickled 75510-Olives 7551101 Peppers, hot 7551102 Peppers, pickled 7551301 Seaweed, pickled 7553500 Zucchini, pickled 76102-Dark Green Veg., baby 76401-Beans babv lexcl. most souos & mixtures\
Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) Food Household Code/Definition Individual Code Product Protected 4922-Fresh Pumpkin, Winter Squash 732-Pumpkin Veg. 4942-Fresh Lima Beans 733-Winter Squash 4947-Fresh Peas 7510200 Lima Beans, raw 49482-Fresh Soy Beans 7510550 Cactus, raw 4956-Fresh Corn 7510960 Corn, raw 4958303 Succotash, home canned 7512000 Peas, raw 4958304 Succotash, home frozen 7520070 Aloe vera juice 4958401 Fresh Cactus (prickly pear) 752040-Lima Beans, cooked 4958503 Burdock 752041-Lima Beans, canned 4958505 Bitter Melon 7520829 Bitter Melon 4958507 Horseradish Tree Pods 752083-Bitter Melon, cooked 51122-Comm. Canned Pumpkin and Squash (baby) 7520950 Burdock 51142-Beans, comm. canned 752131-Cactus 51143-Beans, lima and soy, comm. canned 752160-Com, cooked 51146-Corn, comm. canned 752161-Com, yellow, cooked 5114701 Peas, green, comm. canned 752162-Com, white, cooked 5114702 Peas, baby, comm. canned 752163-Com, canned 5114703 Peas, blackeye, comm. canned 7521749 Hominy 5114705 Pigeon Peas, comm. canned 752175-Hominy 5114919 Succotash, comm. canned 75223-Peas, cowpeas, field or blackeye, cooked 5115304 Lima Beans, canned, low sod. 75224-Peas, green, cooked 5115306 Com, canned, low sod. 75225-Peas, pigeon, cooked 5115307 Creamed Corn, canned, low sod. 75301-Succotash 511531-Peas and Beans, canned, low sod. 75402-Lima Beans with sauce 52122-Winter Squash, comm. froz. 75411-Corn, scalloped, fritter, with cream 52132-Lima Beans, comm. froz. 7541650 Pea salad 5213401 Peas, gr., comm. froz. 7541660 Pea salad with cheese 5213402 Peas, gr., with sauce, comm. froz. 75417-Peas, with sauce or creamed 5213403 Peas, gr., with other veg., comm. froz. 7550101 Corn relish 5213404 Peas, gr., with other veg., comm. froz. 76205-Squash, yellow, baby 5213405 Peas, blackeye, comm froz. 76405-Corn, baby 5213406 Peas, blackeye, with sauce, comm froz. 76409-Peas, baby 52135-Corn, comm. froz. 76411-Peas, creamed, baby 5213712 Artichoke Hearts, comm. froz. (does not include vegetable soups; _vegetable mixtures; 5213713 Baked Beans, comm. froz. or vegetable with meat mixtures) 5213717 Kidney Beans, comm. froz. 5213724 Succotash, comin. froz. 5411-Dried Beans 5412-Dried Peas and Lentils 5413104 Dry Corn 5413106 Dry Hominy 5413504 Dry Squash, baby 5413603 Dry Creamed Corn, baby (does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby foods except mixtures\

Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) Food Product Root Vegetables Household Code/Definition 48-Potatoes, Sweetpotatoes 4921-Fresh Carrots 4953-Fresh Onions, Garlic 4954-Fresh Beets

4957-Fresh Turnips 4958101 Fresh Celeriac 4958102 Fresh Horseradish 4958104 Fresh Radishes, no greens 4958105 Radishes, home canned 4958106 Radishes, home frozen 4958107 Fresh Radishes, with greens 4958108 Fresh Salsify 4958109 Fresh Rutabagas 495811 O Rutabagas, home frozen 4958115 Fresh Parsnips 4958116 Parsnips, home canned 4958117 Parsnips, home frozen 4958502 Fresh Lotus Root 4958509 Ginger Root 4958510 Jicama, including yambean 51121-Carrots, comm. canned 51145-Beets, comm. canned 5114908 Garlic Pulp, comm. canned 5114910 Horseradish, comm. prep. 5114915 Onions, comm. canned 5114916 Rutabagas, comm. canned 5114917 Salsify, comm. canned 5114921 Turnips, comm. canned 5114922 Water Chestnuts, comm. canned 51151-Carrots, canned, low sod. 5115305 Beets, canned, low sod. 5115502 Turnips, low sod. 52121-Carrots, comm. froz. 5213714 Beets, comm. froz. 5213722 Onions, comm. froz. 5213723 Onions, comm. froz., with sauce 5213725 Turnips, comm. froz. 5312103 Canned Carrot Juice 5312104 Canned Beet Juice 5372102 Fresh Carrot Juice 5413105 Dry Garlic 5413110 Dry Onion 5413502 Dry Carrots, baby 5413503 Dry Sweet Potatoes, baby (does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby foods except mixtures\ Individual Code 71-White Potatoes and Puerto Rican St. Veg. 7310-Carrots 7311140 Carrots in sauce 7311200 Carrot chips 734-Sweetpotatoes 7510250 Beets, raw 7511150 Garlic, raw 75.11180 Jicama (yambean), raw 7511250 Leeks, raw 75117-Onions, raw 7512500 Radish, raw 7512700 Rutabaga, raw 7512900 Turnip, raw 752080-Beets, cooked 752081-Beets, canned 7521362 Cassava 7521740 Garlic, cooked 7521771 Horseradish 7521850 Lotus root 752210-Onions, cooked 7522110 Onions, dehydrated 752220-Parsnips, cooked 75227-Radishes, cooked 75228-Rutabaga, cooked 75229-Salsify, cooked 75234-Turnip, cooked 75235-Water Chestnut 7540501 Beets, harvard 75415-Onions, creamed, fried 7541601 Parsnips, creamed 7541810 Turnips, creamed 7550021 Beets, pickled 7550309 Horseradish 7551201 Radishes, pickled 7553403 Turnip, pickled 76201-Carrots, baby 76209-Sweetpotatoes, baby 76403-Beets, baby (does not include vegetable soups; vegetable mixtures; or vegetable with meat mixtures)

Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued) Food Household Code/Definition Individual Code Product USDA SUBCATEGORIES Dark Green 491-Fresh Dark Green Vegetables 72-Dark Green Vegetables Vegetables 5111-Comm. Canned Dark Green Veg. all forms 51154-Low Sodium Dark Green Veg. leafy, nonleafy, dk. gr. veg. soups 5211-Comm. Frozen Dark Green Veg. 5413111 Dry Parsley 5413112 Dry Green Peppers 5413113 Dry Red Peppers (does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby foods except mixtures/dinners; excludes vegetable juices and dried veaetablesl Deep Yellow 492-Fresh Deep Yellow Vegetables 73-Deep Yellow Vegetables Vegetables 5112-Comm. Canned Deep Yellow Veg. all forms 51151-Low Sodium Carrots carrots, pumpkin, squash, sweetpotatoes, dp. 5212-Comm. Frozen Deep Yellow Veg. yell.veg.soups 5312103 Carrot Juice 54135-Dry Carrots, Squash, Sw. Potatoes (does not include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby foods except mixtures/dinners; excludes vegetable juices and dried vegetables) Other 494-Fresh Light Green Vegetables 75-Other Vegetables Vegetables 495-Fresh Other Vegetables all forms 5114-Comm. Canned Other Veg. 51153-Low Sodium Other Veg. 51155-Low Sodium Other Veg. 5213-Comm. Frozen Other Veg. 5312102 Sauerkraut Juice 5312104 Beet Juice 5411-Dreid Beans 5412" Dried Peas, Lentils 541310-Dried Other Veg. 5413114 Dry Seaweed 5413603 Dry Cr. Corn, baby (does no\ include soups, sauces, gravies, mixtures, and ready-to-eat dinners; includes baby foods except mixtures/dinners; excludes vegetable juices and dried veqetables) Citrus Fruits 501-Fresh Citrus Fruits 61-Citrus Fruits and Juices 5121-Comm. Canned Citrus Fruits 6720500 Orange Juice, baby food 5331-Canned Citrus and Citrus Blend Juice 6720600 Orange-Apricot Juice, baby food 5341-Frozen Citrus and Citrus Blend Juice 6720700 Orange-Pineapple Juice, baby food 5351-Aseptically Packed Citrus and Citr. Blend 6721100 Orange-Apple-Banana Juice, baby food Juice (excludes dried fruits) 5361-Fresh Citrus and Citrus Blend Juice (includes babv foods; excludes dried fruits) Other Fruits 502-Fresh Other Vitamin C-Rich Fruits 62-Dried Fruits 503-Fresh Other Fruits 63-Other Fruits 5122-Comm. Canned Fruits Other than Citrus 64-Fruit Juices and Nectars Excluding Citrus 5222-Frozen Strawberries 671-Fruits, baby 5223-Frozen Other than Citr. or Vitamin C-Rich Fr. 67202-Apple Juice, baby 5332-Canned Fruit Juice Other than Citrus 67203-Baby Juices 5342-Frozen Juices Other than Citrus 67204-Baby Juices 5352-Aseptically Packed Fruit Juice Other than Citr. 67212-Baby Juices 5362-Fresh Fruit Juice Other than Citrus 67213-Baby Juices 542-Dry Fruits 673-Baby Fruits (includes baby foods; excludes dried fruits) 674-Baby Fruits REFERENCES FOR CHAPTER -13 American Industrial Health Council (AIHC) (1994) Exposure factors sourcebook. AIHC, Washington, DC. National Gardening Association. ( 1987) National gardening survey: 1986-1987. Burlington, Vermont: The National Gardening Association, Inc. USDA. (1975) Food yields summarized by different stages of preparation. Agriculture Handbook No. 102. U.S. Department of Agriculture, Agricultural Research Service, Washington, DC. USDA. (1987-88) Dataset: Nationwide Food Consumption Survey 1987/88 Household Fo_od Use. U.S. Department of Agriculture. Washington, D.C. 1987/88 NFCS Database. USDA. (1992) Changes in food consumption and expenditures in American households during the_ 1980's. U.S. Department of Agriculture. Washington, D.C. Statistical Bulletin No. 849. USDA. (1993) Food and nutrient intakes by individuals in the United States, 1 Day, 1987-88. Nationwide Food Consumption Survey 1987-88, NFCS Report No. 87-1-1. USDA. (1994) Food *consumption and dietary levels of households in the United States, 1987-88. U.S. Department of Agriculture, Agricultural Research Service. Report No. 87-H-1. DOWNLOADABLE TABLES FOR CHAPTER 13 The following selected tables are available for download as Lotus 1-2-3 worksheets. Table 13-8. Consumer Only Intake of Homegrown Fruits (g/kg-day) -All Regions Combined [WK1, 6 kb] Table 13-9. Consumer Only Intake of Homegrown Fruits (g/kg-day) -Northeast [WK1, 3 kb] Table 13-10. Consumer Only Intake of Homegrown Fruits (g/kg..:day)-Midwest [WK1, 3 kb] Table 13-11. Consumer Only Intake of Homegrown Fruits (g/kg-day) -South [WK1, 4 kb] Table 13-12. Consumer Only Intake of Homegrown Fruits (g/kg-day) -West [WK1, 3 kb] Tabl.e 13-13. Consumer Only Intake of Homegrown Vegetables (g/kg-day)-All Regions Combined [WK1, 6 kb] Table 13-14. Consumer Only Intake of Homegrown Vegetables (g/kg-day) -Northeast. [WK1, 3 kb] Table 13.-15. Consumer Only Intake of Homegrown Vegetables (g/kg-day) -Midwest [WK1, 3 kb] Table 13-16. Consumer Only Intake of Homegrown Vegetables (g/kg-day)-South [WK1, 3 kb] Table 13-17. Consumer Only Intake of Homegrown Vegetables (g/kg-day) -West [WK1, 3kb] Table 13-18. Consumer Only Intake of Home Produced Meats (g/kg-day) -All Regions Combined [WK1, 6 kb] Table 13-19. Consumer Only Intake of Home Produced Meats (g/kg-:-day)-Northeast [WK1, 3 kb] Table 13-20. Consumer Only Intake of Home Produced Meats (g/kg-day)-Midwest [WK1, 3 kb] Table 13-21. Consumer Only Intake of Home Produced Meats (g/kg-day) -South [WK1, 3 kb] Table 13-22. Consumer Only Intake of Home Produced Meats (g/kg-day) -West * [WK 1, 3 kb] . Table 13-23. Consumer Only Intake of Home Caught Fish (g/kg-day) -All Regions [WK1, 5 kb] Table 13-24. Consumer Only Intake of Home Caught Fish (g/kg-day)-Northeast [WK1, 2 kb] Table 13-25. Consumer Only Intake of Home Caught Fish (g/kg-day) -Midwest [WK1, 3 kb] . Table 13-26. Consumer Only Intake of Home Caught Fish (g/kg-day) -South [WK1, 3 kb] Table 13-27. Consumer Only.Intake of Home Caught Fish (g/kg-day) -West [WK1, 3 k.b] Table 13-28. Consumer Only Intake of Home Produced Dairy (g/kg-day) -AU Regions [WK1, 5 kb] Table 13-29. Consumer Only Intake of Home Produced Dairy (g/kg-day) -Northeast [WK1, 3 kb] Table 13-30. Consumer Only Intake of Home Produced Dairy (g/kg-day)-Midwest [WK1, 3 kb] Table 13-31. Consumer Only Intake of Home Produced Dairy (g/kg-day) -South [WK1, 2 kb] Table 13-32. Consumer Only Intake of Home Produced Dairy (g/kg-day) -West [WK1, 3 kb] Table 13-33. Seasonally Adjusted Consumer Only Homegrown Intake (g/kg-day) [WK1, 3 kb] , Table 13-34. Consumer Only Intake of Homegrown Apples (g/kg-day) [WK1, 7 kb] Table 13-35. Consumer Only Intake of Homegrown Asparagus (g/kg-dc1y) [WK1, 6 kb] Table 13-36. Consumer Only Intake of Home Produced Beef(g/kg-day) [WK1, 6 kb] Table 13-37. Consumer Only Intake of Homegrown Beets (g/kg-day) [WK1, 6 kb] Table 13-38. Consumer Only Intake of Homegrown Broccoli (g/kg-day) [WK1, 6 kb] Table 13-39. Consumer Only Intake of Homegrown Cabbage (g/kg-day) [WK1, 6 kb] Table 13-40. Consumer Only Intake of Homegrown Carrots (g/kg-day) [WK1, 7 kb] Table 13-41. Consumer Only Intake of Homegrown Corn (g/kg-day) [WK1, 7 kb] Table 13-42. Consumer Only Intake of. Homegrown Cucumbers (g/kg-day) [WK1, 6 kb] Table 13-43. Consumer Only Intake of Home Produced Eggs (g/kg-day) [WK1, 6 kb] Table 13-44. Consumer Only Intake of Home Produced Game (g/kg-day) [WK1, 6 kb] Table 13-45. Consumer Only Intake of Home Produced Lettuce (g/kg-day) [WK1, 6 kb] Table 13-46. Consumer Only Intake of Home Produced Lima Beans (g/kg-day) [WK1, 6 kb] Table 13*.47. Consumer Only Intake of Homegrown Okra (g/kg-day). [WK1, 6 kb] Table 13-48. Consumer Only Intake of Homegrown Onions (g/kg-day) [WK1, 7 kb] ' ' Table 13-49 .. consumer Only Intake of Homegrown Other Berries (g/kg-day) [WK1, 6 kb] Table 13-50. Consumer Only Intake of Homegrown Peaches (g/kg-day) [WK1, 6 kb] Table 13-51. Consumer Only Intake of Homegrown Pears (g/kg-day) [WK1, 6 kb] . Table 13-52. Consumer Only Intake of Homegrown Peas (g/kg-day) [WK1, 7 kb] Table 13-53. Consumer Only Intake of Homegrown Peppers (g/kg-day) [WK1, 6 kb] Table 13-54. Consumer Only Intake of Home Produced Pork (g/kg-day) [WK1, 6 kb] Table 13-55. Consumer Only lnta.ke of Home Produced Poultry (g/kg-day) [WK1, 6 kb] Table 13-56. Consumer Only Intake of Homegrown Pumpkins (g/kg-day) [WK1, 6 kb] Table 13-57. Consumer Only Intake of Homegrown Snap Beans (g/kg-day) [WK1, 7 kb] Table 13-58. Consumer Only Intake of Homegrown Strawberries (g/kg-day) [WK1, 6 kb] Table 13-59. Consumer Only Intake of Homegrown Tomatoes (g/kg-day) [WK1, 7 kb] Table 13-60. Consumer Only Intake of Homegrown White Potatoes (g/kg-day) [WK1, 7 kb] Table 13-61. Consumer Only Intake of Homegrown Exposed Fruit (g/kg-day) [WK1, 7 kb] Table 13-62. Consumer Only Intake of Homegrown protected Fruits (g/kg-day) [WK1, 6 kb] Table 13-63. Consumer Only Intake of Homegrown Exposed Vegetables (g/kg-day) [WK1, 7 kb] Table 13-64. Consumer Only Intake of Homegrown Protected Vegetables (g/kg-day) * [WK1, 7 kb] Table 13-65. Consumer Only Intake of Homegrown Root Vegetables (g/kg-day) [WK1, 7 kb] Table 13-66. Consumer Only Intake of Homegrown Dark Green Vegetables (g/kg-day) [WK1, 7 kb] Table 13-67. Cons'umer Only Intake of H.omegrown Deep Yellow Vegetables (g/kg-day) [WK1, 7 kb] Table 13-68. Consumer Only Intake of Homegrown Other Vegetables (g/kg-day) [WK1, 7 kb] . Table 13-69. Consumer Only Intake of Homegrown Citrus (g/kg-day) [WK1, 6 kb] Table 13-70. Consumer Only Intake of Homegrown Other Fruit (g/kg-day) [WK1, 6 kb] Volume II -Food Ingestion Factors Chapter 14 -Breast Milk Intake 14. BREAST MILK INTAKE 14.1. BACKGROUND 14.2. KEY STUDIES ON BREAST MILK INTAKE 14.3. RELEVANT STUDIES ON BREAST MILK INTAKE 14.4. KEY STUDIES ON LIPID CONTENT AND FAT INTAKE FROM BREAST MILK 14.5. OTHER FACTORS 14.6. RECOMMENDATIONS REFERENCES FOR CHAPTER 14 Table 14-1. Daily Intakes of Breast Milk Table 14-2. Breast Milk Intake for Infants Aged 1 to 6 Months Table 14-3. Breast Milk Intake Among Exclusively Breast-fed Infants During the First 4 Months of Life Table 14-4. Breast Milk Intake During a 24:-Hour Period Tabl*e 14-5. Breast Milk Intake Estimated by the DARLING Study Table 14-6. Milk Intake for Bottle-and Breast-fed Infants by Age Group Table 14-7. Milk Intake for Boys and Girls Table 14-8. Intake of Breast Milk and Formula Table 14-9. Lipid Content of Human Milk and Estimated Lipid Intake Among Exclusively Breast-fed Infants Table 14-10. Predicted Lipid Intakes for Breast-fed Infants Under 12 Months of Age Table 14-11. Number of Meals Per Day Table 14-12. Percentage of Mothers Breast-feeding Newborn Infants in the Hospital and Infants at 5 or 6 Months of Age in the United States in 1989, by Ethnic Background and Selected Demographic Variables Table Breast Milk Intake Studies Table 14-14. Confidence in Breast Milk Intake Recommendations Table 14-15. Breast Milk Intake Rates Derived From Key Studies Table 14-16. Summary of Recommended BreastMilk and Lipid Intake Rates Exposure Factors Handbook August 1997 Volume II -Food Ingestion FaCtors Chapter 14 -Breast Milk Intake 14. BREAST MILK INTAKE 14.1. BACKGROUND Breast milk is a potential source of exposure to toxic substances for nursing infants. Lipid soluble chemical compounds accumulate in body fat and may be transferred to breast-fed infants in the lipid portion of breast milk. Because nursing infants obtain most (if not all) of their dietary intake from breast milk, they are especially vulnerable to exposures to these compounds. Estimating the magnitude of the potential dose to infants from breast milk requires information on the quantity of breast milk consumed per day and the duration (months) over which breast-feeding occurs. Information on the fat content of breast milk is also needed for estimating dose from breast milk residue concentrations that have been indexed to lipid content. Several studies have generated data on breast milk intake. Typically, breast milk intake has been measured over a 24-hour period by weighing the infant before and after each feeding without changing its clothing (test weighing). The-sum of the difference between the measured weights over the 24-hour period is assumed to be equivalent to the amount of breast milk consumed daily. Intakes measured using this procedure. are often corrected for evaporative water losses (insensible water losses) between infant weighings (NAS, 1991 ). Neyille et al. (1988) evaluated the validity of the test weight approach among bottle-fed infants by comparing the weights of milk taken from bottles with the differences between the infants' weights before and after feeding. Wh'en test weight data were corrected for insensible water loss, they were not significantly different from bottle weights. Conversions between weight and volume of breast milk consumed are made using the density of human milk (approximately 1.03 g/ml) (NAS, 1991 ). Recently, techniques for measuring breast milk intake using stable isotopes have been developed. However, few data based on this new technique have been published (NAS, 1991 ). Studies among nursing mothers in industrialized countries have shown that intakes among infants average approximately 750 to 800 g/day (728 to 777 ml/day) during the first 4 to 5 months of life with a range of 450 to 1,200 g/day ( 437 to 1, 165 ml/day) (NAS, 1991 ). Similar intakes have also been reported for developing countries (NAS, 1991 ). Infant birth weight and nursing frequency have been shown to influence the rate of intake (NAS, 1991 ). Infants who are larger at birth and/or nurse more frequently have been shown to have higher intake rates. Also, breast milk production among nursing mothers .. has been reported to be somewhat higher than the amount actually consumed by the infant (NAS, 1991 ). The available studies on breast milk intake are summarized in the following sections. Studies on breast milk intake rates have been classified as either key studies or relevant studies based on the criteria described in the Introduction (Volume I, Section 1.3.1 ). Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 14 -Breast Milk Intake Recommended intake rates are based on the results of key studies, but relevant studies are also presented to provide the reader with added perspective on the current state of knowledge pertaining to breast milk intake. Relevant data on lipid content and fat intake, breast-feeding duration and frequency, and the estimated percentage of the U.S. population that breast-feeds are also presented. 14.2. KEY STUDIES ON BREAST MILK INTAKE *Pao et al. (1980) -Milk Intakes and Feeding Patterns of Breast-fed Infants -Pao et al. (1980) conducted a study of 22 healthy breast-fed infants to estimate breast milk intake rates. Infants were categorized as completely breast-fed or partially breast-fed. Breast feeding mothers were recruited through LaLeche League groups. Except for one black infant, all other infants were from white middle-class families in southwestern Ohio. The goal of the study was to eriroil infants as close to one month of age as possible and to obtain records near one, three, six, and nine months of age (Pao et al., 1980). However, not all mother/infant pairs participated at each time interval. Data were collected for these 22 infants using the test weighing method. Records were collected for three consecutive 24-hour periods at each test interval. The weight of breast milk was converted to volume by assuming a density of 1.03 g/ml. Daily intake rates were calculated for each infant based on the mean of the three 24-hour periods. Mean daily breast milk intake rates for the infants surveyed at each time interval are presented in Table 14-1. For completely breast-fed infants, the mean intake rates were 600 ml/day at 1 month of age and 833 ml/day at 3 months of age. Partially breast-fed infants had mean intake rates of 485 ml/day, 467 ml/day, 395 ml/day, and 554 ml/day at 1, 3, 6, and 9 months of age,

respectively. Pao et al. (1980) also noted that intake rates for boys in both groups were slightly higher than for girls. The advantage of this study is that data for both exclusively and partially breast-fed infants were collected for multiple time periods. Also, data for individual infants were colJected over 3 consecutive days which would account for some individual variability. However, number of infants in the study was relatively small and may not be entirely representative of the U.S. population, based on race and socioeconomic status, which may introduce some bias in the results. *In addition, this study did not account for insensible water loss which may underestimate the amount of breast milk ingested. Dewey and Lonnerdal {1983) -Milk and Nutrient Intakes of Breast-fed Infants from 1 to 6 Months -Dewey and Lonnerdal (1983) monitored the dietary intake of 20 breast-fed infants between the ages of 1 and 6 months. Most of the infants in the study were exclusively breast-fed (five were given some formula, and several were given small amounts of solid foods.after 3 months of age). According to Dewey and Lonnerdal (1983), the mothers were all well educated and recruited through Lamaze childbirth classes in the Exposure Factors Handbook August 1997 (

Volume II -Food Ingestion Factors

Chapter 14 -Breast Milk Intake Davis area of California. Breast milk intake volume was estimated based on two 24-h'our test weighings per month. Breast milk intake for the various* age groups are presented in Table 14-2. Breast milk intake averaged 673, 782, and 896 ml/day at 1, 3, and 6 months of age, respectively. The advantage of this study is that it evaluated breast-fed infants for a period of 6 months based on two 24-hour observations per infant per month. Corrections for insensible water loss apparently were not made. Also, the number of infants in the study was relatively small and may not be representative of U.S. population, based on race and socioeconomic status. Butte et al. (1984) -Human Milk Intake and Growth in Exclusively Breast-fed Infants -Breast milk intake was studied in exclusively breast-fed infants during the first 4 months of life (Butte et al., 1984 ). Breastfeeding mothers were recruited through the Baylor Milk Bank Program in Texas. Forty-five mother/infant pairs participated in the study. However, data for some time periods (i.e., 1, 2, 3, or 4 months) were missing for some mothers as a result of illness or other factors. The mothers were from the middle-to upper-socioeconomic stratum and had a mean age of 28.0 +/- 3.1 years. A total of 41 mothers were white, 2 were Hispanic, 1 was Asian, and 1 was West Indian. Infant growth progressed satisfactorily over the course of the study. The amount of milk ingested over a 24-hour period was determined using the test weighing procedure. Test weighing occurred over a 24-hour period for most participants,c but intake among several infants was studied over longer periods (48 to 96 hours) to assess individual variation in intake. The study did not indicate whether the data were corrected for insensible water loss. Mean breast milk intake ranged from 723 g/day (702 ml/day) at 3 months to 751 g/day (729 ml/day) at 1 month, with an overall mec;in of 733 g/day (712 ml/day) for the entire study period (Table 14-3). Intakes were also calculated on the basis of body weight (Table 14-3). Based on the results of test weighings conducted over 48 to 96 hours, the mean variation in individual daily intake was estimated to be 7.9+/-3.6 percent. The advantage of this study is that data for a larger number of exclusively breast-fed infants were collected than were collected by Pao et al. (1980). However, data were . collected over a shorter time period (i.e., 4 months compared to 6 months) and day-to-day variability was not characterized for all infants. In addition, the population studied may not be representative of the U.S. population based on race and socioeconomic status. Neville et al. (1988) -Studies on Human Lactation -Neville et al. (1988) studied breast milk intake among 13 infants during the first year of life. The mothers were all multiparous, nonsmoking, Caucasian women of middle-to upper-socioeconomic status living in Denver, Colorado (Neville et al., 1988). All women in the study practiced exclusive breast-feeding for.at least 5 months. Solid foods were introduced at mean age of 7 months. Daily milk intake was estimated by the test weighing method with corrections Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 14 -Breast Mille Intake for insensible weight loss. Data were collected daily from birth to 14 days, weekly from *weeks 3 through 8, and monthly until the study period ended at 1 year after inception. The estimated breast milk intakes for this study are listed in Table 14-4. Mean breast milk intakes were 770 g/day (748 ml/day), 734 g/day (713 ml/day), 766 g/day (744 ml/day), and 403 g/day (391 ml/day) at 1, 3, 6, and 12 months of age, respectively. In comparison to the previously described studies, Neville et al. (1988) collected data on numerous days over a relatively long time period (12 months) and they were corrected for insensible weight loss. However, the intake rates presented in Table 14-4 are estimated based on intake during only a 24-hour period. Consequently, these intake rates are based on short-term data that do not account for day-to-day variability among individual infants. Also, a smaller number of subjects was included than in the previous studies, and the population studied may not be representative of the U.S. population, based on race and socioeconomic status. Dewey et al. (1991a; 1991b) -The DARLING Study-The Davis Area Research on Lactation, . Infant Nutrition and Growth (DARLING) study was conducted in 1986 to evaluate growth patterns, nutrient intake, morbidity, and activity levels in infants who were breast-fed for at least the first 12 months of life (Dewey et al., 1991 a; 1991 b ). three infants aged 3 months were included in the study. The number of infants included in the study at subsequent time intervals was somewhat lower as a result of attrition. All infants in the study were healthy and of normal gestational age and weight at birth, and did not consume solid foods until after the first 4 months of age. The mothers were highly educated and of "relatively high socioeconomic status" from the Davis area of California (Dewey et al., 1991a; 1991b). Breast milk intake was estimated by weighing the infants before and after each feeding and correcting for insensible water loss. Test weighings were conducted over a 4-day period every 3 months. The results of the study indicate that breast milk intake declines over the first 12 months of life. Mean breast milk intake was estimated to be 812 g/day (788 ml/day) at 3 months and 448 g/day (435 ml/day) at 12 months (Table 14-5). Based on the estimated intakes at 3 months of age, variability between individuals (coefficient of variation (CV) = 16.3 percent) was higher than individual day-to-day variability (CV= 5.4 percent) for the infants in the study (Dewey et al., 1991a). The advantages _of this study are that data were collected over a relatively long-time (4 days) period at each test interval which would account for some day-to-day infant variability, and corrections for insensible water loss were made. However, the population studied may not be representative of the U.S. population, based on race and socioeconomic status. Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 14 -Breast Milk Intake 14.3. RELEVANT STUDIES ON BREAST MILK INTAKE Hofvander et al. {1982) -The Amount of Milk Consumed by 1-to 3-Month Old or Bottle-Fed Infants-Hofvander et al. (1982) compared milk intake among breast-fed and bottle-fed infants at ages 1, 2, and 3 months of age. Intake of breast milk and breast milk substitutes was tabulated for 25 Swedish infants in each age group. Daily intake among breast-fed infants was estimated using the test weighing method. Test weighings were conducted over a 24-hour time period at each time interval. Daily milk intake among bottle:-fed infants was estimated by measuring the volumetric differences in milk contained in bottles at the beginning and end of all feeding sessions in a 24-hour period. The mean intake rates for bottle-fed infants were slightly higher than for breast-fed infants for all age groups (Table 14-6). Also, boys consumed breast milk or breast milk substitutes at a slightly higher rate than girls (Table 14-7). Breast milk was estimated to be 656 g/day (637 ml/day) at 1 month and 776 g/day (753 ml/day) at 3 months. This study was conducted among a small number of Swedish infants, but the results are similar to those summarized previously for U.S. studies. Insensible water losses were apparently not considered in this study, and only shorHerm data were collected. Kohler et al. (1984) -Food Intake and Growth of Infants Between Six and Twenty-six Weeks of Age on Breast Milk, Cow's Milk, Formula, and Soy Formula -Kohler et al. (1984) evaluated breast milk and formula intake among normal infants between the ages of 6 and 26 weeks. The study included 25 fully breast-fed and 34 formula-fed infants from suburban communities in Sweden. Intake among breast-fed infants was estimated using the test weighing method over a 48-hour test period. Intake among formula-fed infants was estimated by feeding infants from bottles with known volumes of formula and recording the amount consumed over a 48-hour period. Table 14-8 presents the mean breast milk *and formula intake rates for the infants studied. Data were collected for both cow's based formula and soy-based formula. The results indicated that the daily intake for bottle-fed infants was greater than for breast-fed infants. The advantages of this study are that it compares breast milk intake to formula intake and that test weightings were conducted over 2 consecutive days to account for variability in individual intake. Although the popu.lation studied was not representative of the U.S. population, similar intake rates were observed in the studies that were previously summarized. Axelsson et al. (1987) -Protein and Energy Intake During Weaning -Axelsson et al. (1987) measured food consumption and energy intake in 30 healthy Swedish infants between the ages of 4 and 6 months. Both formula-fed and breast-fed infants were studied. All infants were fed supplemental foods (i.e., pureed fruits and vegetables after 4 months, and pureed meats and fish after 5 months). Milk intake among breast-fed Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 14 -Breast Mille Intake infants was estimated by weighing the infants before and after each feeding over a 2-day period at each sampling interval. Breast milk intake averaged 765 ml/day at 4.5 months of age, and 715 ml/day at 5.5 months of age. / This study is based on short-term data, a small number of infants, and may not be representative of the U.S. population. However, the intake rates estimated by this study are similar to those generated by the U.S. studies that were summarized previously. 14.4. KEV STUDIES ON LIPID CONTENT AND FAT INTAKE FROM BREAST MILK Human milk contains over 200 constituents including lipids, various proteins, carbohydrates, vitamins, minerals, and trace elements as well as enzymes and hormones (NAS, 1991 ). The lipid content of breast milk varies according to the length of time that an .infant nurses. Lipid content increases from the beginning to the end of a single nursing session (NAS, 1991 ). The lipid portion accounts for approximately 4 percent of human breast milk (39 +/- 4.0 g/L) (NAS, 1991 ). This value is supported by various studies that evaluated lipid content from human breast milk. Several studies also estimated the quantity of lipid consumed by breast-feeding infants. These values are appropriate for performing exposure assessments for nursing infants when the contaminant(s) have residue concentrations that are indexed to the fat portion of human breast milk. Butte et al. (1984) -Human Milk Intake and Growth in Exclusively Breast-fed Infants -Butte et al., (1984) analyzed the lipid content of breast milk samples taken from women who participated in a study of breast milk intake among exclusively breast-fed infants. The study was conducted with over 40 women during a 4-month period. The mean lipid content of breast milk at various infants' ages is presented in Table 14-9. The overall lipid content for the 4-month study period was 34.3 +/- 6.9 mg/g (3.4 percent). Butte et aL ( 1984) also calculated lipid intakes from 24-hour breast milk intakes and the lipid content of the human milk samples. Lipid intake was estimated to range from 23.6 g/day (3.8 g/kg-day) to 28.0 g/day (5.9 g/kg-day). The number of women included in this study was small, and these women were selected primarily from middle-to upper-socioeconomic classes. Thus, data on breast milk iipid content from this study may not be entirely representative of breast milk lipid content among the U.S. population. Also, these estimates are based on short-term data and day-. to-day variability was not characterized. Maxwell and Burmaster (1993) -A Simulation Model to Estimate a Distribution of Lipid Intake from Breast Milk Intake During the First Year of Life -Maxwell and Burmaster (1993) used a hypothetical population of 5,000 infants between birth and 1* year of age to simulate a distribution of daily lipid intake from breast milk. The hypothetical population Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 14 -Breast Milk Intake represented both bottle-fed and breast-fed infants aged 1 to 365 days. A distribution of *daily lipid intake was developed based on data in Dewey et al. (1991b) on breast milk intake for infants at 3, 6, 9, and 12 months and breast milk lipid content, and survey data in Ryan et al. ( 1991) on the percentage of breast-fed infants under the age of 12 months (i.e., approximately 22 percent). A model was used to simulate intake among 1, 113 of the 5,000 infants that were expected to be breast-fed. The results of the model indicated that lipid intake among nursing infants under 12 months of age can be characterized by a normal distribution with a mean of 26.8 g/day and a standard deviation of 7.4 g/day (Table 14-10). The model assumes that nursing infants are completely breast-fed and does not account for infants who are breast-fed longer than 1 year. Based on data collected by Dewey etal. (1991b), Maxwell and Burmaster (1993) estimated the lipid content of breast milk to be 36.7 g/L at 3 months (35.6 mg/g or 3.6%) and 40.2 g/L (39.0 mg/g or 3.9%) at 12 months. The advantage of this study is that it provides a "snapshot" of daily lipid intake from breast milk for breast-fed infants. These results are, however, based on a simulation model and there are uncertainties associated with the assumptions made. The estimated
mean lipid intake rate represents the average daily intake for nursing infants under 12 months of age. These data are useful for performing exposure assessments when the age of the infant cannot be specified (i.e., 3 months or 6 months). Also, because intake rates are indexed to the lipid portion of the breast milk, they may be used in conjunction with residue concentrations indexed to fat content. 14.5. OTHER FACTORS Other faCtors associated with breast . milk intake include: the frequency of breast"-feeding sessions per day, the duration of breast-feeding per event, the duration of breast-feeding during childhood, and the magnitude and nature of the population that breast-feeds.
Frequency and Duration of Feeding -Hofvander et al. .(1982) reported on the frequency . of feeding among 25 bottle-fed and 25 breast-fed infants1at ages 1, 2, and 3 months. The mean number of meals for these age groups was approximately 5 meals/day (Table 14-11 ). Neville et al. (1988) reported slightly higher mean feeding frequencies. The mean number of meals per day for exclusively breast-fed infants was 7.3 at ages 2 to 5 months and 8.2 at ages 2 weeks to 1 month. Neville et al. (1988) reported that, for infants between the ages of 1 week and 5 months, the average duration of a breast feeding session is 16-.18 minutes. Population of Nursing Infants and Duration/ of Breast-Feeding During Infancy -According to NAS ( 199.1 ), the percentage of breast-feeding women has changed dramatically over the years. Between 1936 and 1940, approximately 77 percent of infants Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 14 -Breast Milk Intake were breast fed, but the incidence of breast-feeding fell to approximately 22 percent in 1972. The duration of breast-feeding also dropped from about 4 months in the early 1930s to 2 months in the late 1950s. After 1972, the incidence of breast-feeding began to rise again, reaching its peak at approximately 61 percent in 19.82. The duration of breast-feeding also increased between 1972 and 1982. Approximately 10 percent of the mothers who initiated breast-feeding continued for at least 3 months in 1972; however, in 1984, 37 percent continued breast-feeding beyond 3 months. In 1989, breast-feeding was initiated among 52.2 percent of newborn infants, and 40 percent continued for 3 months or longer (NAS, 1991 ). Based on the data for 1989, only about 20 percent of infants were still breast fed by age 5 to 6 months (NAS, 1991 ). Data on the actual length of time that infants continue to breast-feed beyond 5 or 6 months are limited (NAS, 1991 ). However, Maxwell and Burmaster (1993) estimated that approximately 22 percent of infants under 1 year of age are breast-fed. This estimate is based on a reanalysis of survey data in Ryan et al. (1991) collected by Ross.Laboratories (Maxwell and Burmaster, 1993). Studies have also indicated that breast-feeding practices may differ among ethnic and socioeconomic groups and among regions of the United States. . The percentages of mothers who breast feed, based on ethnic background and demographic variables, are presented in Table 14-12 (NAS, 1991 ). Intake Rates Based on Nutritional Status -Information on differences in the quality and quantity of breast milk consumed based on ethnic or socioeconomic characteristics of the population is limited. Lonnerdal et al. (1976) studied breast.milk volume and composition (nitrogen, lactose, proteins) among L!nderprivileged and privileged Ethiopian mothers. No significant differences were observed between the data for these two groups; and similar data for well-nourished Swedish mothers were observed. Lonnerdal et al. (1976) stated that these results indicate that breast milk quality and quantity are not affected by maternal malnutrition. However, Brown et al. (1986a; 1986b) noted thafthe ladational capacity and energy concentration of marginally-nourished women in Bangladesh. were "modestly less *than in better nourished rnothers." Breast milk intake rates for infants of marginally-nourished women in this study were 690+/-122 g/day at 3 months, 722+/-105 g/day at 6 / months, and 719+/-119 g/day at 9 months of age (Brown et al., 1986a). Brown et al. (1986a) observed that breast milk from women with larger measurements of arm circumference and triceps skinfold thickness had higher concentrations of fat and energy than mothers with less body fat. Positive correlations between maternal weight and milk fat concentrations were also observed. These results suggest that milk composition may be affected by maternal nutritional status. 14.6. RECOMMENDATIONS The key studies described in this section were used in selecting recommended values for breast milk intake, fat content and fat intake, and other related factors. Although different survey designs, testing periods, and populations were utilized by the key and Exposure Factors Handbook August 1997 Volume II -Food Ingestion Factors Chapter 14 -Breast Milk Intake relevant studies to estimate intake, the mean and*standard deviation estimates reported in these studies are relatively consistent. There are, however, limitations with the data. Data are not available for infants under 1 month of age. This subpopulation may be of particular concern since a larger number of newborns are totally breast fed. In addition, with the exception of Butte (1984), data were not presented on a body weight basis. This is particularly important since intake rates may be higher on a body weight basis for younger infants. Also, the data used to derive the recommendations are over 10 years old and the sample size of the studies was small. Other subpopulations of concern such as mothers highly committed to breast feeding, sometimes for periods longer than 1 year, may not be captured by the studies presented in this chapter. Further research is needed to identify these subgroups and to get better estimates of breast milk intake rates. The general designs of both key and relevant studies and their are summarized in Table 14-13. Table 14-14 presents the confidence rating for breast milk intake recommendations. Breast Milk Intake -The breast milk intake rates for nursing infants that have been reported in the key studies described in this section are summarized in Table 14-15. Based on the combined results of these studies, 7 42 mUday is recommended to represent an average breast milk intake rate, and 1,033 ml/day represents an upper-perceritile intake rate (based on the middle range of the mean plus 2 standard deviations) for infants between the ages of 1 and 6 months of age. The average value is the mean of the average intakes at 1, 3, and 6 months from the key studies listed in Table 14-15. It is . consistent with the average intake rate of 718 to 777 ml/day estimated by NAS (1991) for infants during the first 4 to 5 months of life. Intake among older infants is somewhat lower, averaging 413 mUday for 12-month olds (Neville et al. 1988; Dewey et al. 1991 a; 1991 b ). When a time weighted average is calculated for the 12-month period, average breast milk intake is approximately 688 ml/day, and upper-percentile intake is approximately 980 ml/day. Table 14-16 summarizes these recommended intake rates. Lipid Content and Lipid Intake -Recommended lipid intake rates are based on data from Butte et al. (1984) and Maxwell and Burmaster (1993). Butte et al. (1984) estimated that average lipid intake ranges from 23.6 +/- 7.2 g/day (22.9 +/- 7.0 mUday) to 28.0 +/- 8.5 g/day (27 .2 +/- 8.3 ml/day) between 1 and 4 months of age. These intake rates are consistent with those observed by Burmaster and Maxwell (1993) for infants under 1 year of age [(26.8 +/- 7.4 g/day (26.0 +/- 7.2 ml/day)]. Therefore, the recommended breast milk lipid intake rate for infants under 1 year of age is 26.0 ml/day and the upper-percentile value is 40.4 ml/day (based on the mean plus 2 standard deviations). The recommended value for breast milk fat content is 4.0 percent based on data from NAS (1991 ), Butte et al. (1984), and Maxwell and Burmaster (1993}: Exposure Factors Handbook August 1997

*------Table 14-1. Daily Intakes of Breast Milk Number of Infants Surveyed Range of at Each Time Mean Intake Daily Intake Age Period (ml/day) a (ml/day) ' Completely Breast-fed 1 month 11 600 +/- 159 426 -989 3 months 2 833 645 -1,000 6 months 1 682 616-786 Partially Breast-fed 1 month 4 485 +/- 79 398 -655 3 months 11 467 +/- 100 242 -698 6 months 6 395 +/- 175 147 -684 9 months 3 <554 451 -732 a Data expressed as mean +/- standard deviation. Source: Pao et al., 1980.

Table 14-2. Breast Milk Intake for Infants Aged 1 to 6 Months Age Number of Mean SD Range (months) Infants (ml/day) (ml/day) a (ml/day) 1 16 673 192 341-1,003 2 19 756 170 449-1,055 3 16 782 172 492-1,053 4 13 810 142 593-1,045 5 11 805 117 554-1,045 6 11 896 122 675-1 096 a Standard deviation. Source: Dewey and Lonnerdal 1983. Table 14-3. Breast Milk Intake Among Exclusively Breast-fed Infants During the First 4 Months of Life Number Breast Milk Breast Milk Body Age (months) of Intake* Intake* Weightb Infants (g/day) (g/kg-day) (kg) 1 37 751.0 +/- 130.0 159.0 +/- 24.0 4.7 2 40 725.0 +/- 131.0 129.0 +/- 19.0 5.6 3 37 723.0 +/- 114.0 117.0+/-20.0 6.2 4 41 740.0 +/- 128.0 111.0+/-17.0 6.7 a Data expressed as mean +/- standard deviation. b Calculated by dividing breast milk intake (g/day) by breast milk intake (g/kg-day). Source: Butte et al., 1984. ,_ Table 14-4. Breast Milk Intake During a 24-Hour Period Standard Age Number of Mean Deviation Range (days) Infants (g/day) (g/day) (g/day) 1 7 44 71 149 a 2 10 182 86 44-355 3 11 371 153 209-688 4 11 451 176 164-694 5 12 498 129 323-736 6 10 508 167 315-861 7 8 573 167 .406-842 8 9 581 159 410-923 9 10 580 76 470-720 10 10 589 132 366-866 11 8 615 168 398-934 14 10 653 154* 416-922 ' 21 10 651 84 554-786 28 13 770 179 495-1144 35 12 668 117 465-930 42 12 711 111 554-896 49 10 709 115 559-922 56 13 694 98 556-859 90 12 734 114 613-942 120 13 711 100 570-847 150 13 838 134 688-1173 180 13 766 121 508-936 210 12 721 154 486-963 240 10 622 210 288-1002 270 12 618 220 223-871 300 11 551 234 129-894 330 9 554 240 120-860 360 9 403 250 65-770 a Negative value due to insensibfe water loss correction. Source: Neville et al., 1988. Table 14-5. Breast Milk Intake Estimated by the DARLING Study Age (months) Number of Mean Intake Standard Deviation Infants (g/day) (g/day) 3 73 812 133 6 60 769 171 9 50 646 217 12 42 448 251 Source: Dewev et al. (1991 b ). Table 14-6. Milk Intake for Bottle-and Breast-fed Infants by Age Group Age Breast Milk Substitutes Breast Milk (months) Mean (g/day)8 Mean (g/day)8 1 713 656 (500-1,000) (360-860) 2 811 773 (670-1, 180) (575-985) 3 853 776 (655-1 065) (600-930) a Range given in parentheses. Source: Hofvander et al. 1982. Table 14-7. Milk Intake for Boys and Girls Bovs Girls Mean Mean Aae (a/dav) N (a/dav) N Breast milk 1 663 12 649 13 2 791 14 750 11 3 811 12 743 13 Breast milk substitute 1 753 10 687 15 2 863 13 753 12 3 862 13 843 12 Source: Hofvander et al., 1982. Table 14-8. Intake of Breast Milk and Formula Breast Milk Cow's Formula Sov Formula Age N Mean SD N Mean SD N Mean SD (wks) (o/dav) (q/dav) (o/dav) (g/dav) (g/day) (g/day) 6 26 746 101 20 823 111 13 792 127 14 21 726 143 19 921 95 13 942 78 22 13 722 114 18 818 201 13 861 196 26 12 689 120 18 722 209 12 776 159 Source: Kohler et al. 1984. Table 14-9. Lipid Content of Human Milk and Estimated Lipid Intake

Amona Exclusivelv Breast-fed Infants Age (months) Number Lipid Lipid Lipid Lipid of Content Content* Intake Intake Observations (mq/q) a (percent) b (q/day) a (g/kg-day) a 1 37 36.2 +/- 7.5 3.6 28.0 +/- 8.5 5.9 +/- 1.7 2 40 34.4 +/- 6.8 3.4 25.2 +/- 7.1 4.4 +/- 1.2 3 37 32.2 +/- 7.8 3.2 23.6 +/- 7.2 3.8 +/- 1.2 4 41 34.8 +/- 10.8 3.5 25.6 +/- 8.6 3.8 +/- 1.3 a Data expressed as means +/- standard deviations. b Percents calculated from lipid content reported in mg/g. Source: Butte et al. 1984.

Table 14-10. Predicted Lipid Intakes for Breast-fed Infants Under 12 Months of Age Statistic Value Number of Observations in Simulation 1, 113 Minimum Lipid Intake 1.0 g/day Maximum Lipid Intake 51.5 g/day Arithmetic Mean Lipid Intake 26.8 g/day Standard Deviation Lioid Intake 7.4 q/dav Source: Maxwell and Burmaster 1993.

Table 14-11. Number of Meals Per Day Age (months) Bottle-fed Infants Breast-fed meals/day a meals/da ) a 1 5.4 (4-7) 2 4.8 (4-6) 3 4.7 3-6 a Data expressed as mean with range in parentheses. Source: Hofvander et al., 1982. 5.8 (5-7) 5.3 (5-7) 5.1 4-8

-1 Table 14-12. Percentage of Mothers Breast-feeding Newborn Infants in the Hospital and Infants at 5 or 6 Months of Aqe in the United States in 1989', by Ethnic Backqround and Selected Demographic Variables* Total White Black Hisoanicc Category Newborns 5-6 Mo Newborn 5-6 Mo Newborns 5-6 Mo Newborns 5-6 Mo Infants s Infants *infants Infants All mothers 52.2 19.6 58.5 22.7 23.0 7.0 48.4 15.0 Parity Primiparous 52.6 16.6 58.3 18.9 23.1 5.9 49.9 13.2 Multiparous 51.7 22.7 58.7 26.8 23.0 7.9 47.2 16.5 Marital status Married 59.8 24.0 61.9 25.3 35.8 12.3 55.3 18.8 Unmarried 30.8 7.7 40.3 9.8 17.2 4.6 37.5 8.6 Maternal age <20 yr 30.2 6.2 36.8 7.2 13.5 3.6 35.3 6.9 20-24 yr 45.2 12.7 50.8 14.5 19.4 4.7 46.9 12.6

25-29 yr 58.8 22.9 63.1 25.0 29.9 9.4 56.2 19.5 30-34 yr 65.5 31.4 70.1 34.8 35.4 13.6 57.6 23.4. yr 66.5 36.2 71.9 40.5 35.6 14.3 53.9 24.4 Maternal educ.alien No college 42.1 13.4 48.3 15.6 17.6 5.5 42.6 12.2 Colleged 70.7 31.1 74.7 34.1 41.1 12.2 66.5 23.4 Family income <$7,000 28.8 7.9 36.7 9.4 14.5 4.3 35.3 10.3 $7,000-$14,999 44.0 13.5 49.0 15.2 23.5 7.3 47.2 13.0 $15,000-$24,999 54.7 20.4 57.7 22.3 31.7 8.7 52.6 16.5 66.3 27.6 67.8 28.7 42.8 14.5 65.4 23.0 Maternal employment Full time 50.8 10.2 54.8 10.8 30.6 . 6.9 50.4 . 9.5 Part time 59.4 23.0 63.8 . 25.5 26.0 6.6 59.4 17.7 Not employed 51.0 23.1 58.7 27.5 19.3 7.2 46.0 16.7 U.S. census region New England 52.2 20.3 53.2 21.4 35.6 5.0 47.6 14.9 Middle Atlantic 47.4 18.4 52.4 21.8 30.6 9.7 41.4 10.8 East North Central 47.6 18.1 53.2 20.7 21.0 7.2 46.2 12.6 West North Central 55.9 19.9 58.2 20.7 27.7 7.9 50.8 22.8 South Atlantic 43.8 -14.8 53.8 18.7 19.6 5.7 48.0 13.8 East South Central 37.9 12.4 45.1 15.0 14.2 3.7 23.5 5.0 West South Central 46.0 14.7 56.2 18.4 14.5 3.8 39.2 11.4 Mountain . 70.2 30.4 74.9 33.0 31.5 11.0 53.9 18.2 Pacific 70.3 28.7 76.7 33.4 43.9 15.0 58.5 19.7 a Mothers were surveyed when their infants were 6 months of age. They were asked to recall the method of feeding the infant when in the hospital, at age 1 week,,at months 1 through 5, and on the day preceding completion of the survey. Numbers in b the columns labeled "5-6 Mo Infants" are an average of the 5-month and previous day responses. Based on data from Ross Laboratories. c Hispanic is not exclusive of white or black. d College includes all women who reported completing at least 1 year of college. Source: NAS 1991.

Table 14-13. Breast Milk Intake Studies Number of Study Individuals Type of Feeding Sampling Time and Interval Population Studied Comments KEY STUDIES Butte et al., 1984 45 Exclusively breast-fed Most infants studied over 1 Mid-to upper-Estimated breast milk intake; for first 4 months day only, at 1, 2, 3, 4 months socioeconomic stratum corrected for insensible water loss some studied over 48 to 96 hours to study individual variability Dewey etal., 73 Breast-fed for 12 Test weighing over 4-day Highly educated, high-Estimated breast milk intake; 1991a; 1991b months; exclusively period every 3 months for 1 socioeconomic class from corrected for insensible water loss breast-fed for at least year Davis area of California first 4 months Dewey and 20 Most infants exclusively Two test weighings per month Mid to upper class from Estimated breast milk intake; did Uinnerdal, 1983 breast-fed for 6 months Davis area of California not correct for insensible water loss Neville et al., 13 Exclusively breast-fed Infants studied over 24-hour Nonsmoking Caucasian Estimated breast milk intake and 1988 infants period at each sampling mothers; middle-to lipid intake; *corrected for interval; numerous sampling. upper-socioeconomic insensible water loss; estimated intervals over first year of life status frequency and duration of feeding Pao et al., 1980 22 Completely or partially Three consecutive days at 1, White middle class from Estimated breast milk intake; did breast-fed infants 3, 6, and 9 months southeastern Ohio not correct for insensible water loss Table 14-13. Breast Milk Intake Studi_es (continued} Number of : Study Individuals Type of Feeding Sampling Time and Interval Population Studied Comments RELEVANT STUDIES Axelsson et al., 30 Breast-fed infants and Studied over 2-day periods Swedish infants Measured intake rates; not 1987 infants fed formula with at 4.5 and 5.5 months of corrected for insensible water loss two different energy age contents Brown et al., 1986a; 58,60 Breast-fed infants Studied over 3 days at each Bangledeshi infants; Measured milk and nutrient intake 1986b interval marginally nourished based on nutritional status; not mothers corrected for insensible water loss

Hofvander et al., 50 25 breast-fed and 25 Studied 24-hour period at 1, Swedish infants Estimated breast milk and formula 1982 formula-fed infants 2, and 3 months intake; no corrections for insensible water loss among breast-fed infants; estimated frequency of feeding Kohler et al., 1984 59 25 fully breast-fed and 34 Studied over.48-hour Swedish infants Estimated breast milk and formula formula-fed infants periods at 6, 14, 22, and 26 intake based on nutritional status; weeks of age no corrections for insensible water loss among breast-fed infants Maxwell and 1, 113 Population of 1, 113 NA NA Simulated distribution of breast milk Burmaster, 1993 breast-fed infants based *intake based on data from Dewey on a hypothetical 1991 a; estimated percent of breast-population of 5,000 fed infants under 12 months of age breast-fed and bottle-fed infants NAS, 1991 NA Breast-fed infants NA NA Summarizes current state-of-knowledge on breast milk volume, composition and breast-feedina oooulations

-Table 14-14. Confidence in Breast Milk Intake Recommendations Considerations Rationale Rating Study Elements *D Level of peer review All key studies are from peer review literature. High *D Accessibility Papers are widely available from peer review journals. High *D Reproducibility Methodology used was clearly presented. High *D Focus on factor of interest The focus of the studies was on estimating breast milk intake. High *D Data pertinent to U.S. Subpopulations of the U.S. were the focus of all the key studies. High *D Primary data All the studies were based on primary data. High *D Currency Studies were conducted between 1980-1986. Although incidence of Medium breast feeding may change with time, breast milk intake among breastfed infants may not. *D Adequacy of data collection period Infants were not studied long enough to fully characterize day to day Medium variability. *D Validity of approach Methodology uses changes in body weight as a surrogate for total Medium ingestion. This is the best methodology there is to estimate breast milk ingestion. Mothers were instructed in the use of infant scales to minimize measurement errors. Three out of the 5 studies corrected data for insensible water loss. *D Study size The sample sizes used in the key studies were fairly small (range 13-73). *D Representativeness of the Population is not representative of the U.S.; only mid-upper class, well Low population nourished mothers were studied. Socioeconomic factors may affect the incidence of breastfeeding. Mother's nourishment may affect milk production. *D Characterization of variability Not very well characterized. Infants under 1 month not captured, Low mothers committed to breast feeding over 1 year not captured. *D Lack of bias in study design (high Bias in the studies was not characterized. Three out of 5 studies Low rating is desirable) corrected for insensible water loss. Not correcting for insensible water loss may underestimate intake. Mothers selected for the studies were volunteers; therefore response rate does not apply: Population studied may introduce some bias in the results (see above). *D *Measurement error All mothers were well educated and trained in the use of the scale Medium which helped minimize measurement error. Other Elements *D Number of studies There are 5 key studies. High *D Agreement between researchers There is good agreement among researchers. High Overall Rating Studies were well designed. Results were consistent. Sample size Medium was fairly low and not representative of U.S. population or population of nursing mothers. Variability cannot be characterized due to limitations in data collection period. Table 14-15. Breast Milk Intake Rates Derived From Key Studies Upper Percentile (mUday) Mean (mUday) N (mean plus 2 standard Reference deviations) Age: 1 Month 600 11 918 Pao et al., 1980 729 37 981 Butte et al., 1984 747 13 1,095 Neville et al., 1988 673 16 1,057 Dewey and Uinnerdal, 1983 weighted avg = 702 1,007" Age: 3 Months 833 2 ---Pao et al., 1980 702 37 923 Butte et al.. 1984 712 12 934 Neville et al., 1988 782 16 1,126 Dewey and Li:innerdal, 1983 788 73 1,046 Deweyetal., 1991b weighted avg = 759 1,025* Age: 6 Months 682 1 ---Pao et al., 1980 744 13 978 Neville et al., 1988 896 11 1,140 Dewey and Li:innerdal, 1983 747 60 1,079 Dewey et al., 1991 b weighted avg = 765 1,059* Age: 9 Months 600 12 1,027 Neville et al., 1988 627 50 1,049 Dewey et al., 1991 b avg =622 1,038 Age: 12 Months 391 9 877 Neville et al., 1988 435 42 923 Deweyetal., 1991a; 1991b weighted avg = 427 900 12-MONTH TIME WEIGHTED AVERAGE Range 900-1,059 (middle of the range 980) 688

Middle of the ranee.

Table 14-16. Summary of Recommended Breast Milk and Lipid Intake Rates Age Mean Upper Percentile Breast Milk 1-6 Months 742 mUday 1,033 mUday 12 Month Average 688 mUday 980 mUday Lipids" <1 Year 26.0 mUday 40.4 mUday

The recommended value for the linirl rnntent of breastmilk is 4.0 oercent.

REFERENCES FOR CHAPTER 14 Axelsson, I.; Borulf, S.; Righard, L.; Raiha, N. (1987) Protein and energy intake during weaning: effects and growth. Acta Paediatr. Scand. 76:321-327. Brown, K.H.; Akhtar, N.A.; Robertson, A.O.; Ahmed, M.G. (1986a) Lactational capacity of marginally nourished mothers: relationships maternal nutritional status and quantity and proximate composition of milk. Pediatrics. 78: 909-919. Brown, K.H.; Robertson, A.O.; Akhtar, N.A. (1986b) Lactational capacity of marginally nourished mothers: infants' milk nutrient consumption and patterns of growth. Pediatrics. 78: 920-927. Butte, N.F.; Garza, C.; Smith, E.O.; Nichols, B.L. (1984) Human milk intake and growth in exclusively breast-fed infants. Journal of Pediatrics. 104: 187-195. Dewey, K.G.; Lonnerdal, B. (1983) Milk and nutrient intake of breast-fed infants from 1 to 6 months: relation to growth and fatness. Journal of Pediatric Gastroenterology and Nutrition. 2:497-506. Dewey, K.G.; Heinig, J.; Nommsen, L.A.; Lonnerdal, B. (1991a) Maternal versus infant factors related to breast milk intake and residual volume: the DARLING study. Pediatrics. 87:829-837. Dewey, K.G.; Heinig, J.; Nommsen, L.; Lonnerdal, B. (1991b) Adequacy of energy intake among breast-fed infants in the DARLING study: relationships to growth, velocity, morbidity, and activity levels. The Journal of Pediatrics. 119:538-547. Hofvander, Y.; Hagman, U.; Hillervik, C.; Sjolin, S. (1982) The amount of milk consumed by 1-3 months old breast-or bottle-fed infants. Acta Paediatr. Scand. 71 :953-958. Kohler, L.; Meeuwisse, G.; Mortensson, W. (1984) Food intake and growth of infants between six and twenty-six weeks of age on breast milk, cow's milk formula, and soy formula. Acta Paediatr. Scand. 73:40-48. Lonnerdal, B.; Forsum, E.; Gebre-Medhim, M.; Hombraes, L. (1976) Breast milk composition in Ethiopian and Swedish mothers: lactose, nitrogen, and protein contents. The American Journal of Clinical Nutrition. 29:1134-1141. Maxwell, N.I.; Burmaster, D.E. (1993) A simulation model to estimate a distribution of lipid intake from breast milk during the first year of life. Journal of Exposure Analysis and Environmental Epidemiology. 3:383-406. National Academy of Sciences (NAS). (1991) Nutrition during lactation. Washington, DC. National Academy Press. Neville, M.C.; Keller, R.; Seacat, J.; Lutes, V.; Neifert, M.; et al. (1988) Studies in human lactation: milk volumes in lactating women during the onset of lactation and full lactation. American Journal of Clinical Nutrition. 48:1375-1386. Pao, E.M.; Hines, J.M.; Roche, A.F. (1980) Milk intakes and feeding patterns of fed infants. Journal of the American Dietetic Association. 77:540-545. Ryan, A.S.; Rush, D.; Krieger, F.W.; Lewandowski, G.E. (1991) Recent declines in breastfeeding in the United States, 1984-1989. Pediatrics. 88:719-727. Volume III -Activity Factors Chapter 15 -Activity Factors 15. ACTIVITY FACTORS 15.1. ACTIVITY PATIERNS 15.1.1. Key Activity Pattern Studies 15.1.2. Relevant Activity Pattern Studies 15.2. OCCUPATIONAL MOBILITY 15.2.1. Background 15.2.2. Key Occupational Mobility Studies 15.3. POPULATION MOBILITY 15.3.1. Background 15.3.2. Key Population Mobility Studies 15.3.3. Relevant Population Mobility Studies 15.4. RECOMMENDATIONS 15.4.1. Recommendations for Activity Patterns 15.4.2. Recommendations:* Occupational Mobility 15.4.3. Recommendations: Population Mobility 15.4.4. Summary of Recommended Activity Factors REFERENCES FOR CHAPTER 15 APPENDIX 15A APPENDIX 15B Table 15-1. Time Use Table Locator Guide Table 15-2. Mean Time Spent (minutes) Performing Major Activities Grouped by Age, Sex and Type of Day Table 15-3. Mean Time Spent (minutes) in Major Activities Grouped by Type of Day for Five Different Age Groups Table 15-4. Cumulative Frequency Distribution of Average Shower Duration for 2,550 Households Table 15-5. Mean Time Spent (minutes/day) in Ten Major Activity Categories Grouped by Total Sample and Gender for the GARB and National Studies (age 18-64 years) Table 15-6. Total Mean Time Spent at Three Major Locations Grouped by Total Sample and Gender for the GARB and National Study (ages 18-64 years) Table 15-7. Mean Time Spent at Three Locations for both CARB and National Studies (ages 1.2 years and older) Table 15-8. Mean Time Spent (minutes/day) in Various Microenvironments Grouped by Total Population and Gender (12 years and over) in the National and CARB Data Table 15-9. Mean Time Spent (minutes/day) in Various Microenvironments by Type of Day for the California and National Surveys (sample population ages 12 years and older) Table 15-10. Mean Time Spent (minutes/day) in Various Microenvironments by Age Groups for the National and California Surveys Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activity Factors Table 15-11. Mean Time (minutes/day) Children Spent in Ten Major Activity Categories for All Respondents Table Mean Time Children Spent in Ten Major Activity Categories Grouped by Age and Gender Table 15-13. Mean Time Children Spent in Ten Major Activity Categories Grouped by Seasons and Regions

Table 15-14. Mean Time Children Spent in Six Major Location Categories for All Respondents (minutes/day) Table 15-15. Mean Time Children Spent in Six Location Categories Grouped by Age and *Gender Table 15-16. Mean Time Children Spent in Six Location Categories Grouped by Season and Region Table 15-17 .. Mean Time Children Spent in Proximity to Three Potential Exposures Grouped by All Respondents, Age, and Gender Table 15-18. Range of Recommended Defaults for Dermal Exposure Factors Table 15-19. Number of Times Taking a Shower at Specified Daily Frequencies by the Number of Respondents Table 15-20. Times (minutes) Spent Taking Showers by the Number of Respondents Table 15-21. Number of Minutes Spent Taking a Shower (minutes/shower) Table 15-22. Time (minutes) Spent in the Shower Room Immediately After Showering by the Number of Respondents Table 15-23. Number of Minutes Spent in the Shower Room Immediately After Showering .. (minutes/shower) Table 15-24. Number of Baths Given or Taken in One Day by Number of Respondents Table 15-25. Total Time Spent Taking or Giving a Bath by the Number of Respondents Table 15-26. Number of Minutes Spent Giving and Taking the Bath(s) (minutes/bath) Table 15-27. Time Spent in the Bathroom Immediately After the Bath(s) by the Number of Respondents .
Table 15-28. Number of Minutes Spent in the Bathroom Immediately After the Bath(s) (minutes/bath) Table 15-29. Total Time Spent Altogether in the Shower or Bathtub by the Number of Respondents Table 15-30. Total Number of Minutes Spent Altogether in the Shower or Bathtub (minutes/bath) Table 15-31. Time Spent in the Bathroom Immediately Following a Shower or Bath by the Number of Respondents Table 15-32. Number of Minutes Spent in the Bathroom Immediately Following a Shower or Bath (minutes/bath) * . . Table 15-33. Range of Number of Times Washing the Hands at Specified Daily Frequencies by the Number of Respondents Table 15-34. Number of Minutes Spent (at home) Working or Being Near Food While
Fried, Grilled, or Barbequed (minutes/day) Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activity Factors Table 15-35. Number of Minutes Spent (at home) Working or Being Near Open Flames lncluding.Barbeque Flames (minutes/day) Table 15-36. Number of Minutes Spent Working or Being Near Excessi_ve Dust in the Air (minutes/day) Table 15-37. Range of the Number of Times an Automobile or Motor Vehicle was Started ' in a Garage or Carport at Specified Daily Frequencies by the Number of Respondents Table 15-38. Range of the Number of Times Motor Vehicle Was Started with Garage Door
Closed at Specified Daily Frequencies by the Number of Respondents Table 15-39. Number of Minutes Spent at a Gas Station or Auto Repair Shop (minutes/day) Table 15-40. Number of Minutes Spent at Home While the Windows Were Left Open (minutes/day) Table 15-41. Number of Minutes the Outside Door Was Left Open While at Home (minutes/day) Table 15-42. Number of Times an Outside Door Was Opened in the Home at Specified *Daily Frequencies by the Number of Respondents Table 15-43. Number of Minutes Spent Running, Walking, or Standing Alongside a Road with Heavy Traffic (minutes/day) Table 15-44. Number of Minutes Spent in a Car, Van, Truck, or Bus in Heavy Traffic (minutes/day) Table 15-45. Number of Minutes Spent in a Parking Garage or Indoor Parking Lot (minutes/day) Table 15-46. Number of Minutes Spent Walking Outside to a Car in the Driveway or Outside Parking Areas (minutes/day) Table 15-47. Number of Minutes Spent Running or Walking Outside Other Than to the Car (minutes/day) Table 15-48. Number of Hours Working for Pay (hours/week) Table 15'."49. Number of Hours Spent Working for Pay Between 6PM and 6AM (hours/week) Table 15-50. Number of Hours Worked in a Week That Was Outdoors (hours/week) table 15-51. Number of Times Floors Were Swept or Vacuumed at Specified Frequencies by the Number of Respondents Table 15-52. Number of Days Since the Floor Area in the Home Was Swept or Vacuumed by the Number of Respondents Table 15-53. Number of Loads of Laundry Washed in a Washing Machine at Home by the Number of Respondents Table 15-54. Number of Times Using a Dishwasher at Specified Frequencies by the Number of Respondents Table 15-55. Number of Times Washing Dishes by Hand at Specified Frequencies by the Number of Respondents Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activify Factors Table 15-56. Number of Times for Washing Clothes in a Washing Machine at Specified Frequencies by the Number of Respondents Table 15-57. Number of Minutes Spent Playing on Sand or Gravel in a Day by the Number of Respondents
Table 15-58. Number of Minutes Spent Playing in Sand or Gravel (minutes/day) Table 15-59. Number of Minutes Spent Playing in Outdoors on Sand, Gravel, Dirt, or Grass When Fill Dirt Was Present by the Number of Respondents Table 15-60. Number of Minutes Spent Playing on Sand, Gravel, Dirt, or Grass When Fill Dirt Was Present (minutes/day) Table 15-61. Range of the Time Spent Working in a Garden or Other Circumstances in a. Month by the Number of Respondents Table 15-62. Number of Hours Spent Working with Soil in a Garden or Other Circumstances Working (hours/month) Table 15-63. Range of Number of Minutes Spent Playing on Grass in a Day by the Number of Respondents Table 15-64. Number of Minutes Spent Playing on Grass (minutes/day) Table 15-65. Number of Times Swimming in a Month in Freshwater Swimming Pool by the Number of Respondents Table 15-66. Range of the Average Amount of Time Actually Spent in the Water by Swimmers by the Number of Respondents Table 15-67. Number of Minutes Spent Swimming in a Month in Freshwater Swimming Pool (minutes/month) Table 15-68. Statistics for 24-Hour Cumulative Number of Minutes Spent Working in a Main Job Table 15-69. Statistics for 24-Hour Cumulative Number of Minutes Spent in Food Preparation Table 15-70. Statistics for 24-Hour Cumulative Number of Minutes Spent in Food Cleanup Table 15-71. Statistics for 24-Hour Cumulative Number of Minutes Spent Cleaning House Table 15-72. Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor Cleaning Table 15-73. Statistics for 24-Hour Cumulative Number of Minutes Spent in Clothes Care Table 15-74. Statistics for 24-Hour Cumulative Number of Minutes Spent in Car Repair/Maintenance Table 15-75. Statistics for 24-Hour Cumulative Number of Minutes Spent in Other Repairs Table 15-76. Statistics for 24-Hour Cumulative Number of Minutes Spent in Plant Care Table 15-77. Statistics for 24-Hour Cumulative Number of Minutes Spent in Animal Care Table 15-78. Statistics for 24-Hour Cumulative Number of Minutes Spent in Other Household Work Table 15-79. Statistics for 24-Hour Cumulative Number of Minutes Spent in Indoor Playing Table 15-80. Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor Playing Exposure Factors Handbook August 1997 \

Volume III -Activity Factors Chapter 15 Factors Table 15-81'. Statistics for 24-Hour Cumulative.Number of Minutes Spent for Car Repair Services Table 15-82. Statistics for 24-Hour Cumulative Number of Minutes Spent Washing, etc. Table 15-83. Statistics for 24-Hour Cumulative Number of Minutes Spent Sleeping/Napping Table 15-84. Statistics for 24-Hour Cumulative Number of Minutes Spent Attending Full Time School Table 15-85. Statistics for 24-Hour Cumulative Number of Minutes Spent in Active Sports Table 15-86. Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor . Recreation Table 15-87. Statistics for 24-Hour Cumulative Number of Minutes Spent in Exercise Table 15-88. Statistics for 24-Hour Cumulative Number of Minutes Spent in Food Preparation Table 15-89. Statistics for 24-Hour Cumulative Number of Minutes Spent Doing Dishes/Laundry Table 15-90. Statistics for 24-Hour Cumulative Number of Minutes Spent in Housekeeping Table 15-91. Statistics for 24-Hour Cumulative Number of Minutes Spent in Bathing Table 15-92. Statistics for 24-Hour Cumulative Number of Minutes Spent in Yardwork/Maintenance Table 15-93. Statistics for 24-Hour Cumulative Number . of Minutes Spent in Sports/Exercise Table 15-94. Statistics for 24-Hour Cumulative Number of Minutes Eating or Drinking . Table 15-95. Statistics for 24-Hour Cumulative Number of Minutes Spent *Indoors at an Auto Repair Shop/Gas Station Table 15-96. Statistics for 24-.Hour Cumulative Number of Minutes Spent Indoors at a

Gym/Health Club Table 15-97. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at the Laundromat Table 15-98. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at Work (non-specific) *Table 15-99. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at the Dry Cleaners Table 15-100. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at a Bar/Nightclub/Bowling Alley Table 15-101. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at a Restaurant Table 15-102. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors a( School Table 15-103. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at a Plant/Factory/Warehouse Table 15-104. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors on a Sidewalk, Street, or in the Neighborhood Exposure Factors Handbook August 1997
Volume III -Activity Factors Chapter 15 -Activify Factors Table 15-105. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors in a Parking Lot _ Table 15-106. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a Service Station or Gas Station Table 15-107. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a Construction Site
Table 15-108. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors on School Grounds/Playground Table 15-109. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors Park/Golf Course Table 15-110. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a Pool/River/Lake Table 15-111. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a Restaurant/Picnic
Table 15-112. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a Farm Table 15-113. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Kitchen Table 15-114. Statistics for 24-Hour Cumulative Number of Minutes Spent in the Bathroom Table 15-115. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Bedroom Table 15-116. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Garage Table 15-117. Statistics for 24-Hour Cumulative Number of Minutes Spent in the Basement Table 15-118. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the -Utility Room or Laundry Room Table 15-119. Statistics for 24-Hour Cumulative Number of Minutes Spent at H<;>me in the Outdoor Pool or Spa Table 15-120. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Yard or Other Areas Outside the House Table 15-121. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling in a Car Table 15-122. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling in a Truck (Pick-upNan) Table 15-123. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on a Motorcycle, Moped, or Scooter Table 15-124. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling in Other Trucks Table 15-125. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on a Bus Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activity Factors Table 15-126. Statistics for 24-Hour Cumulative Number of Minutes Spent Walking Table 15-127. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on a Bicycle/Skateboard/ Rollerskate Table 15-128. Statistics for 24-Hour Cumulative Number of Minutes Spent Waiting on a Bus, Train etc., Stop Table 15-129 .. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on
a Train/Subway/Rapid Transit Table 15-130. Statistics for 24-Hour Cµmulative Number of Minutes Spent Traveling on an Airplane . Table 15-131. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors in a Residence (all rooms) Table 15-132. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoprs (outside the residence) Table 1 S-133. *Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling Inside a Vehicle Table 15-134. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors Near a Vehicle Table 15-135. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors Other Than Near a Residence or Vehicle Such as Parks, Golf Courses, or Farms .Table 15-136. Statistics for 24-Hour Cumulative Number of Minutes Spent in an Office or Factory Table 15-137. Statistics for 24-Hour Cumulative Number of Minutes Spent in Malls, Grocery Stores, or Other Stores Table 15-138. Statistics for 24-Hour Cumulative Number of Minutes Spent in Schools, Churches, Hospitals, and Public Buildings Table 15-139. Statistics for 24-Hour Cumulative Number* of Minutes Spent in Bars/Nightclubs, Bowling Alleys, and Restaurants Table 15-140. Statistics for 24-Hour Cumulative Number of Minutes Spent in Other Outdoors Such as Auto Repair Shops, Laundromats, Gyms, and at Work (non-specific) Table 15-141. Statistics for 24-Hour Cumulative Number of Minutes Spent with Smokers Present Table 15-142. Range of Time (minutes) Spent Smoking Based on the Number of Respondents Table 15-143. Number of Minutes Spent Smoking (minutes/day) Table 15-144. Range of Time Spent Smoking Cigars or Pipe Tobacco by the Number of Respondents Table 15-145. Number of Minutes Spent Smoking Cigars or Pipe Tobacco (minutes/day) Table 15-146. Range of Numbers of Cigarettes Smoked Based on the Number of Respondents Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activify Factors Table 15-147. Range of Numbers of Cigarettes Smoked by Other People Based on Number of Respondents Table 15-148. Range of Numbers of Cigarettes Smoked While at Home Based on the Number of Respondents , Table 15-149. Differences in Time Use (hours/week) Grouped by Employment Status, and Marital Status for the Surveys Conducted in 1965 and 1975 Table 15-150. Time Use (hours/week) Differences by Age for the Surveys Conducted in 1965 and 1975 Table 15-151. Time Use (hours/week) Differences by Education for the Surveys Conducted in 1965 and 1975
Table 15-152. Time Use (hours/week) Differences by Race for the Surveys Conducted in 1965 and 1975 Table 15-153. Mean Time Spent (hours/week) in Ten Major Activity Categories Grouped by Regions Table 15-154. Total Mean Time Spent (minutes/day) in Ten Major Activity _Categories. Grouped by Type of Day *
Table 15-155. Mean Time Spent (minutes/day) in Ten Major Activity Categories During Four Waves of Interviews Table 15-156. Mean Time Spent (hours/week) in Ten Major Activity Categories Grouped by Gender Table 15-157. Percent Responses of Children's "Play" (activities) Locations in Maryvale, Arizona Table 15-158. Table 15-159. Table 15-160. Occupational Tenure of Employed Individuals by Age and Sex Occupational Tenure for Employed Individuals Grouped by Sex and Race Occupational Tenure for Employfd Individuals Grouped by Sex and Employment Status Table 15-161. Occupational Tenure of Employed Individuals Grouped by Major Occupational Groups and Age Table 15-162. Voluntary Occupational Mobility Rates for Workers Age 16 Years and Older Table 15-163. Values and Their Standard Errors for Average Total Residence Time, T, for Each Group in Survey Table 15-'164. Total Residence Time, t (years), Corresponding to Selected Values of R(t) by Housing Category Table 15-165. Residence Time of Owner/Renter Occupied Units Table 15-166. Percent of Householders Living in Houses for Specified Ranges of Time Table 15-167. Descriptive Statistics for Residential Occupancy Period . Table 15-168. Descriptive Statistics for Both Genders by Current Age Table 15-169. Summary of Residence Time of Recent Home Buyers (1993) Table 15-170. Tenure in Previous Home (Percentage Distribution) Table 15-171. Number of Miles Moved (Percentage Distribution) Table 15-172. Confidence in Activity Patterns Recommendations Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activify Factors Table 15-173. Confidence in Occupational Mobility Recommendations Table 15-17 4. Recommendations for Population Mobility Table 15-175. Confidence in Population Mobility Recommendations Table 15-176. Summary of Recommended Values for Activity Factors Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries Table 15A-2. Differences in Average Time Spent in Different Activities Between California and National Studies (minutes per day for age 18-64 years) Table 15A-3. Time Spent in Various Microenvironments Ta.ble 15A-4. Major Time Use Activity Categories Table 15A-5.
Mean Time Spent (minutes/day) for 87 Activities Grouped by Day of the Week Table 15A-6. Weighted Mean Hours Per Week by Gender: 87 Activities and 10 Subtotals Table 15A-7. Ranking of Occupations by Median Years of Occupational Tenure Table 158-1 . Annual Geographical Mobility Rates, by Type of Movement for Selected 1-Year Periods: 1960-1992 (numbers in thousands) Table 158-2. Mobility of the Resident Population by State: 1980 Figure 15-1. Distribution of Individuals Moving by Type of Move: 1991-92 Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activify Factors 15. ACTIVITY FACTORS In calculating exposure, a person's average daily dose is determined from a combination of variables including the pollutant concentration, exposure duration, and frequency of exposure (Sexton and Ryan, 1987). These variables can be dependent on human activity patterns and time spent at each activity and/or location. A person's total exposure can be predicted using indirect approaches such as computerized mathematical models. This indirect approach of predicting exposure also requires activity patterns (time use) data. Thus, individual or group activities are important determinants of potential exposure because toxic chemicals introduced into the environment may not cause harm to an individual until an activity is performed subjecting the individual to contact with those contaminants. An individual's choice on how to spend time will vary according to their occupation, hobbies, culture, location,* gender, age, and personal preferences. Educational level attained and socioeconomic status also influence chosen activities and their duration. The purpose of this section is to describe published time use studies that provide information on activities in which various individuals engage, length of time spent performing various activities, locations in which individuals spend time and length of time spent by individuals within those various microenvironments. According to Robinson and Thomas (1991), microenvironments refer to a combination of activities and locations that yield potential exposures. Information on time spent in specific occupations and residing in specific areas also is included in this section. This section summarizes data on how much time individuals spend doing various activities and in various microenvironments. These data cover a wide scope of activities and populations. The following table (Table 15-1) should be used as a guide to locating ttie information relevant to activities and microenvironments of concern. Assessors can consider using these data to develop exposure duration estimates for specific exposure scenarios. Available studies are grouped as key or relevant studies. The classifications of these studies are based on the applicability of their data to exposure assessments. All tables that provide data from these studies are presented at the back of this chapter. 15.1. ACTIVITY PATTERNS The purpose of this section is to describe published time use studies that provide information on time-activity patterns of the national population and various sub-populations in the U.S. The studies involve survey designs where time diaries were used to collect information on the time spent at various activities and locations for children, adolescents, and adults, and to collect certain demographic and socioeconomic data. Available studies on time:-activity data are summarized in the following sections. It should be noted that other site-limited studies, based on small sample sites, are available, but are not Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activi(y Factors presented in this section. The studies presented in this section are ones believed to be the most appropriate for the purpose of the handbook. Activity pattern studies are presented in Sections 15.1.1 and 15.1.2. 15.1.1. Key Activity Pattern Studies Timmer et al. (1985) -How Children Use Time -Timmer et al. (1985) conducted a study using the data obtained on children's time use from a 1981-1982 Panel study. This study was a follow-up of households from a previous survey conducted in 1975-76. The 922 respondents in the 1981-82 study were those who had completed at least three out offour waves of interview in the 1975 -1976 survey. Timmer et al. (1985) conducted the survey during February through December 1981, and households were. contacted four times during a 3 month interval of the survey period. The first contac! was a personal interview, followed by subsequent telephone interviews for most of the respondents. However, families with children were contacted personally and questionnaires were * . . administered to a maximum of three children per household. The children surveyed were between the ages of 3 and 17 years and were interviewed twice. The questionnaires administered to children had two components: a time diary and a standardized interview. The time diary involved children reporting their activities beginning at 12.00 a.m. the previous night; the duration and lbcation of each activity; the presence of another .individual; and whether they were performing other activities at the same time. The standardized interview administered to the children was to gather information about their psychological, intellectual (using reading comprehension tests), and emotional well-being; their hopes and goals; their family environment; and their attitudes and beliefs. For preschool children, parents provided information about the child's previous day's activities. Children in first through third grades completed the time diary with their parents assistance and, in addition, completed reading tests. Children in fourth grade and above provided their own diary information and participated in the interview. Parents were asked to assess their children's socioemotional and intellectual development. A survey form was sent to a teacher of each school-age child to evaluate each child's socioemotional and intellectual development. The activity descriptor codes used in this study were developed by Juster et al. (1983). The* activity codes and descriptors used for the adult time diaries in both surveys are presented in Appendix Table 15A-1. ' The mean time spent performing major activities on weekdays and weekends by age . and sex, and type of day is presented in Table 15-2. On weekdays, children spend about 40 percent of their time sleeping, 20 percent in school, and 10 percent eating, washing, dressing, and performing other personal activities (Timmer et al., 1985). The data in Table 15-2 indicates that girls spend more time than boys performing household work and Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activify Factors personal care activities, and less time playing sports. Also, children spend most of their free time watching television. Table 15-3 presents the mean time children spend during weekdays and weekends performing major activities by five different age groups. Also, the significant effects of each variable (i.e., age, sex) are shown in Table 15-3. Older children spend more time performing household and market work, studying and watching television, and less time eating, sleeping, and playing. Timmer et al. (1985) estimated that on the average, boys spend 19.4 hours a week watching television and girls spend 17 .8 hours per week performing the same activity. /\ limitation* associated with this study is that the data do not provide overall annual estimates of children's time use since the data were collected only during the time of the year when children attend school and not during school vacation. Another limitation is that . a distribution pattern of children's time use was not provided. In addition, the survey was condu_cted in 1981 so there is a potential that activity patterns in children may have changed significantly from that period to the present. Therefore*, application of these data for current exposure situations may bias exposure assessments results. An advantage of this survey is that diary recordings of activity patterns were kept and the data obtained were not based completely on recall. Another advantage is that because parents assisted younger children with keeping their diaries and with interviews, any bias that may have been created by having younger children record their data should have been minimized. James and Knuiman (1987} -An Application of Bayes Methodology to the Analysis of Diary Records from a Water Use Study -In 1987, James and Knuiman provided a distribution of the amount of time (1-20 minutes) spent showering by individuals in households located in Australia. The distribution presented in the study of James and Knuiman was based on diary records of 2,500 households. James and Knuiman (1987) reported that 50 additional households provided data for shower durations exceeding 20 minutes, but were excluded from their analysis because specific values over 20 minutes were not reported. Using the data of James and Knuiman, a cumulative frequency distribution was derived for the handbook, based on the 2,550 households and is presented in Table 15-3. Based on the resul_ts in Table 15-3, approximate showering times are 7 minutes for the median value, 13 minutes for the 90th percentile, 16 mi.nutes for the . 95th percentile, and >20 minutes for the 99th percentile. The mean shower length is approximately 8 minutes using the shower durations of 1 to 20 minutes. A mean value could not be calculated using the data for the 50 households that reported showering time >20 minutes. However, if a 30 minute showering time was assumed for the >20 minutes duration, the mean value would be 8.5 minutes as compared to a mean of 8 minutes if these households are excluded. Therefore, including the 50 additional households would give a similar mean and the results at the upper end of the distribution would not be affected. Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activity Factors A limitation of the study is that the data are from households in Australia and may not be representative of U.S. households. An advantage is that it presents cumulative distribution data. Robinson and Thomas (1991) -Time Spent in Activities, Locations, and Microenvironments: A California-National Comparison -Robinson and Thomas ( 1991) reviewed and compared data from the 1987-88 California Air Resources Board (GARB) time activity study and from a similar 1985 national study, American's Use of Time. Data from the national study were recorded similarly to the GARB code categories, in order to make data comparisons (Robinson *and Thomas, 1991 ). The GARB study residents who lived in the state of California. One adult 18 years or older was randomly sampled in each household and was asked to complete a diary with entries for the previous day's activities and the location of each activity. Time use patterns for other individuals 12 years and older in the households contacted were also included in the diaries. interviews based on the random-digit-dialing (ROD) procedure were conducted for approximatel.y 1,762 respondents in the GARB survey. These interviews were distributed across all days of the week and across different months of the year (between October 1987-August 1988). In the 1985 National study, single day diaries were collected from over 5,000 respondents across the U.S., 12 years of age and older. The study was conducted during January through December 1985. Three modes of time diary collection were employed for this survey: mailback, telephone interview, and personal interview. Data obtained from the personal interviews were not used in this study (Robinson and Thomas, 1991 ). The sample population for the mail-back and telephone interview was selected based on a ROD method. The ROD was designed to represent all telephone households in the contiguous United States (Robinson and Thomas, 1991 ). In addition to estimates of time spent at various activities and locations, the survey design provided information on the employment status, age, education, race, and gender for each member of the respondent's
hou*sehold. The mail-back procedure was based on a "tomorrow" approach, and the telephone interview was based on recall. In the "tomorrow". approach, respondents know, and agree ahead of time, that they will be a diary (Robinson and Thomas, 1991 ). Data comparisons by Robinson and Thomas ( 1991) were based on 10 major activity categories ( 100 sub-category codes) and 3 major locations ( 44 sub-location codes) employed in both the GARB and the 1985 national study. In order to make data comparisons, Robinson and Thomas (1991) excluded responses from individuals of ages 65 years and older and 18 years or younger in both surveys. In addition, only mail-back responses were analyzed for the 1985 national study. The data were then weighted to project both the California and national population in terms of days of the week, region, Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activity Factors numbers of respondents per household, and 3 monthly seasons of the year (Robinson and Thomas, 1991 ). Table 15-5 shows the mean time spent in the 10 major activities by gender and for all respondents between the ages of 18-64 years (tiine use data for the individual activities are presented in Appendix Table 15A-2). In both studies respondents spent most of their time (642 mins/day) on personal needs and care (i.e., sleep). Californians spent more time on paid work, education and training, obtaining goods and services, and communication, and less time on household work, child care, organizational activities, entertainment/social activities, and recreation than the national population. The male and female population closely followed the same trends as the general Table 15-6 shows the mean time spent at 3 major locations for the GARB and national study grouped by total sample and gender, ages 18-64 years (time use data for the 44 detailed microenvironments are presented in Appendix Table 15A-3). Respondents spent most of their time at home, 892 minutes/day for the GARB and 954 minutes/day for the national study. Californians spent more of their time away from home and traveling compared to the national population. In addition, Robinson and Thomas (1991) defined a set of 16 microenvironments based on the activity and location codes employed in both studies. The analysis included data for adolescents (12-17 years) and adults (65 years and older) in both the GARB study and the mail-back portion of the 1985 national study (Robinson and Thomas, 1991 ). The mean duration of time spent in locations for total sample population, 12 years and older, across three types of locations is presented in Table 15-7 for both studies. Respondents spent most of their time indoors, 1255 and 1279 minutes/day for the GARB and national study, respectively. Table 15-8 presents the mean duration of time and standard mean error for the 16 microenvironments grouped by total sample population and gender. Also included is the mean time spent for respondents ("Doers") who reported participating in each activity. Table 15-8 shows that in both studies men spend more time in work locations, automobiles and other vehicles, autoplaces (garages), and physical outdoor activities, outdoor sites. In contrast, women spend more time cooking, engaging in other kitchen activities, performing other chores, and shopping. The same trends also occur on a per
participant basis. Table 15-9 shows the mean time spent in various microenvironments grouped by type of the day (weekday or weekend) in both studies. Generally, respondents spent most of their time during the weekends in restaurants/bars (GARB study), motor vehicles, outdoor activities, social-cultural settings, leisure/communication* activities, and sleeping. Microenvironmental differences by age are presented in Table 15-10. Respondents in the age groups 18-24 years and 25-44 years spent most of their time in restaurants/bars and Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15. -Activity Factors traveling. The oldest age group, 65 years and older, spent most of their time in the kitchen (cooking and other kitchen related activities) and in communication Limitations associated with the Robinson and Thomas (1991) study are that the GARB survey was based on recall and the survey was performed in California only. Therefore, if applied to other populations, the data set may be biased. Another limitation is that time distribution patterns (statistical analysis) were not provided for both studies. Also, the data are based on short term studies. An advantage of this study is that the 1985 national study represents the general U.S. population. Also, the 1985 national study provides time estimates by activities, locations, and microenvironments grouped by age, gender, and type of day. Another advantage is that the data were compared and that, overall, both data sets showed similar patterns of activity (Robinson and Thomas, 1991 ). Wiley et al. (7991) -Study of Children's Activity Patterns -The California children's activity pattern survey design provided time estimates of children (under 12 years old) in various activities and locations (microenvironments) on a typical day (Wiley et al., 1991 ). The sample population, which consisted of 1,200 respondents (including children under 12 years of age and adult informants residing in the child's household), was selected using Waksberg ROD methods from English-speaking households. One child was selected from each household. If the selected child was 8 years old or less, the adult in the same household who spent the most time with the child responded. However, if the selected child was between 9 and 11 years old, that child responded. The population was also stratified to provide representative estimates for major regions of the state. The survey question.naire included a time diary which provided information on the children's activity and location patterns based on a 24-hour recall period. In addition, the survey questionnaire included questions about potential exposure to sources of indoor air pollution (i.e., presence of smokers) on the diary day and the socio-demographic characteristics (i.e., age, gender, marital status of adult) of children and adult respondents. The questionnaires and the time diaries were administered via a computer-assisted telephone interviewing (CATI) technology (Wiley et al., 1991). The telephone interviews were conducted during April 1989 to February 1990 over four seasons: Spring (April-June 1989), Summer (July-September 1989), Fall (October-December 1989), and Winter (January-February 1990). The data obtained from the survey interviews resulted in ten major activity categories, 113 detailed activity codes, 6 major categories of locations, and 63 detailed location codes. The average time respondents spent during the 10 activity categories for all children are presented in Table 15-11. Also included in this table are the detailed activity, including its code, with the highest mean duration of time; the percentage of respondents who reported participating in any activity (percent doing); and the mean, median, and maximum time duration for "doers." The dominant activity category, personal care (night sleep being the highest contributor), had the time expenditure of 794 mins/day Exposure Factors Handbook August 1997

( ) Volume III -Activity Factors Chapter 15 -Activity Factors (13.2 hours/day). All respondents reported sleeping at night, resulting in a mean daily time per participant of 794 mins/day spent sleeping. The activity category "don't know" had a duration of about 2 mins/day and only 4 percent of the respondents reported missing activity time. Table 15-12 presents the mean time spent in the 10 activity categories by age and Differences in activity patterns for boys and girls tended to be small. Table 15-13 presents the mean time spent in the 10 activity categories grouped by seasons and California regions. There were seasonal differences for 5 activity categories: personal care, educational activities, social/entertainment, recreation, and communication/ passive *leisure. Time expenditure differences in yarious regions of the State were minimal for childcare, work-related activities, shopping, personal care, education, social life, and recreation. Table 15-14 presents the distribution, of time across six location categories. The participation rates (percent) of respondents, the* mean, median, and maximum time for "doers." The detailed location with the highest average time expenditure are also shown. The largest amount of time spent was at home (1,078 minutes/day); 99 percent of respondents spent time at home (1,086 minutes/ participant/day). Tables 15-15 and 15-16 show the average time spent in the six locations grouped by age and gender, and season and region, respectively. There are age differences in time expenditure in educational settings for boys and girls (Table 15-.15). There are no differences in time expenditure at the six locations by regions, and time spent in school decreased in the summer months compared to other seasons (Table 15-16). Table 15-17 shows the average potential exposure time children spent in proximity to tobacco smoke, gasoline fumes, and gas oven fumes grouped by age and gender. The sampled children spent more time closer to tobacco smoke (77 mins/day) than gasoline'fumes (2 mins/day) and gas oven fumes (11 mins/day). A limitation of this study is that the sampling population was restricted to only speaking households; therefore, the data obtained does not represent the diverse population group present in California. Another limitation is that time use values obtained from this survey were based on short-term recall (24-hr) data; therefore, the data set obtained may be biased. Other limitations are: the survey was conducted in California and is not representative of the national population, and the significance of the observed differences in the data obtained (i.e., gender, age, seasons, and regions) were not tested statistically. An advantage of this study is that time expenditure in various activities and locations were presented for children grouped by age, gender, and seasons. Also, potential exposures of respo'ndents to pollutants were explored in the survey. Another advantage is the use of the CATI program in obtaining time diaries, which allows automatic coding of activities and locations onto a computer tape, and allows activities forgotten by Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activity Factors respondents to be inserted into its appropriate position during interviewing (Wiley et al., 1991 ). U.S. EPA (1992) -Dermal Exposure Assessment: Principles and Applications -U.S. EPA (1992) addressed the variables of exposure time, frequency, and duration needed to calculate dermal exposure as related to activity. The reader is referred to the document for a detailed discussion of these variables in relation to soil and water related activities. The suggested values that can be used for dermal exposure are presented in Table 15-18. ' Limitations of this study are that the values are based on small data sets and a limited number of studies. An advantage is that it presents default values for frequency and duration for use in exposure assessments when specific data are not available. Tsang and Klepeis (1996) -National Human Activity Pattern Survey (NHAPS) -The National Human Activity Pattern Survey was conducted by the U.S. EPA (Tsang and . Klepeis, 1996). It is the largest and most current human activity pattern survey available (Tsang and Klepeis, 1996). Data for 9,386 respondents in the 48 contiguous United States were collected via minute-by-minute 24-hour diaries between October 1992 and September 1994. Detailed data were collected for a maximum of 82 different possible locations, and a maximum cif 91 different activities. Participants wer:e selected using a Random Digit Dial (ROD) method and Computer Assisted Telephone Interviewing (CATI). The response rate was 63 percent, overall. If the chosen respondent was a child too . young to interview, an adult in the household gave a proxy interview. Each participant was asked to recount their entire daily routine from midnight to midnight immediately previous to the day that they were interviewed. The survey collected information on duration and frequency of selected activities and of the time spent in selected microenvironments. In addition, demographic information was collected for each respondent to allow for statistical summaries to be generated according to specific subgroups of the U.S. population (i.e.,. by gender, age, race, employment status, census region, season, etc.). The participants' responses were weighted according to geographic, socioeconomic, time/season, and other demographic factors to ensure that results were representative of the U.S. The weighted sample matches the 1990 U.S. census. population for each gender, age group, census region, and the day-of-week and seasonal responses are equally distributed. Saturdays and Sundays were over sampled to ensure an adequate weekend sample. The data presented are a compilation of 24..:hour diary locations, activities, and up exposure questions based on exposure-related events (personal, exposure, household characteristics, medical background) (Tsang and Klepeis, 1996). Data presented are reported in the form of means, percentages of time spent, and percentages of respondent occurrences. The diary data are useful for obtaining national representative distributions of time spent in a large variety of .activities and locations in a single day (Tsang and Klepeis, 1996). According to Tsang and Klepeis (1996), the 24-hour diaries in the NHAPS are useful in probabilistic modeling (Monte-Carlo) that frequency distributions of Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activify Factors exposure. Overall survey results indicate that for time spent in microenvironments, the largest overall percentage of time was spent in residential-indoors (67 percent), followed by time spent outdoors (8 percent), and then time spent in vehicles (5 percent) (Tsang and Klepeis, 1996). Tables 15-19 through 15-146 provide data *from the NHAPS study. NHAPS data on the time spent in selected activities are presented in Tables 15-19 through 1_5-92. NHAPS.data on the time spent in selected microenvironments are*presented in Tables 15-93 to 15-139 and of these tg_bles, Tables 15-66 through 15-139 present 24-hour cumulative statistics (mean, minimum, maximuim, and percentiles) data for time spent in various activities and in various microenvironments. *

Tables 15-19 through 15-32 provide information on the frequency and duration
of baths, frequency of taking showers, and on the amount of time spent in the shower or bathroom after completion of the activity.
Table 15-33 provides the frequency for washing the hands in a day.
Tables 15-34 through 15-36 present information on time spent by persons working with or being near foods while being grilled or barbecued; working with or near open flames; and working or being near excessive 9ust in the air.
Tables 15-37 through 15-39 prov_ide data for the number oftimes a vehicle was started in a garage or. carport and if started with the door closed; and for time spent at a gas station or repair shop. *
Tables 15-40 through 15-42 present information on the number of times windows and doors were opened and the number of minutes they were left open at home while the respondent was at home.
Tables 15-43 through 15-47 provide data for time spent in heavy traffic either running, walking, standing, or in a vehicle; and for time spent in indoor and outdoor parking lots and garages.
Tables 15-48 through 15-50 present information for time spent working for pay; working at different times of day; and for the amount of that time was spent working outdoors.
Tables 15-51 through 15-56 provide information for number of times of performing household tasks in a day such as vacuuming, and washing dishes and clothes in a residence. Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activify Factors *D Tables 15-57 through 15-64 present data for number of times per day and the duration for playing in sand, gravel, and dirt; and for working in circumstances where one comes in contact with soil such as in a garden. *D Tables 15-65 through 15-67 provide information on the frequency of swimming in a fresh water swimming pool and the amount of time spent swimming during a 1-month, period.*
Tables 15-68 through 15-87 present statistics for time spent in various major categories. They are as follows: Paid Work (main job); Household Work (food preparation and cleanup, cleaning house, clothes care); Child Care (indoor and outdoor playing); Obtaining Goods and Services (car repair); Personal Needs and Care (sleeping/napping); Free Time and Education (school); and* Recreation (active sports, exercise, outdoor recreation).
Tables 15-88 through 15-94 provide statistics for time spent in various activities that are the results of regrouping/combining activities described in Tables 15-68 through 15-87. Because the occurrences in some major categories were too small to conduct analyses, these categories were regrouped into broader categories so that new categories could be developed with a larger number of occurrences (Tsang and Klepeis, 1996). This regrouping was performed to create a better data set for estimating exposure activities from the available data (Tsang and Klepeis, 1996).
Tables 15-95 through 15-103 provide cumulative statistics for time spent in various indoor microenvironments such as repair shops/gas stations; tiar/ night club/bowling alley; and at school.
Tables 15-104 through 15-112 present statistical data for time spent in various outdoor locations. . These tables include data for locations such as schoolgrounds/ playground; parking lots; construction sites; parks and golf courses; and farms.
Tables 15-113 through 15-120 present statistics for time spent in various locations in the home. Data are presented for the number of minutes spent in the kitchen, bathroom, bedroom, garage, basement, utility room or laundry room; in the outdoor pool or spa; and in the yard or other areas outside the house.
Tables 15-121 through 15-130 provide data on time spent traveling and for traveling in various types of vehicles; and for time spent walking. Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activity Factors *D Tables 15-131 through 15-140 provide statistics for total time spent indoors at home (categories regrouped/combined based on various data described in Tables 15-95 through 15-130), including all rooms; outdoors at home; traveling inside a vehicle; outdoors near a vehicle; outdoors other than near a residence; in an office or factory; in malls and other stores; in various public buildings; in bars, restaurants, etc.; and outdoor locations such as auto repair shops and laundromats.
Table 15-141 provides the number of minutes spent in an activity or microenvironment where a smoker was present.
Tables 15-142 and 15-143 present data for time spent smoking in a day.
Tables 15-144 15-148 provide information for time spent smoking selected tobacco products such as cigars, cigarettes, and pipe tobacco. ; ' Advantages of the NHAPS dataset are that it is representative of the U.S. population and it has been adjusted to be balanced geographically, seasonally, and for day/time. Also, it is representative of all ages, gender, and is race specific. A disadvantage of the study is that means cannot be calculated for time spent over 60, 120, and 181 minutes in selected activities. Therefore, actual time spent at the high end of the distribution for these activities cannot be captured. 15.1.2. Relevant Activity Pattern Studies Robinson -Changes in Americans' Use of Time: 1965-1975 (1977) -Robinson (1977) compared time use data obtained from national surveys that were conducted in 1965-1966 and in 1975. Each survey used the time-diary method to collect data. The 1965-66 survey excluded people in the following categories: (a) Non-Standard Metropolitan Statistical Area (non-SMSA) (designation of Census Bureau areas having no city with more than 50,000 population); (b) households where no adult members were in the labor force for at least 10 hours per week; (c) age 65 and over; and (d) farm-related occupations (Robinson, 1977). The 1,244 respondents in the 1965-66 study included either employed men and women or housewives (Robinson, 1977). The survey was conducted between November-December 1965 and March-April 1966. Respondents recorded their daily activities in time diaries by using the "tomorrow" approach. In this approach, diarieswere kept cin the day following the interviewer's initial contact. The interviewer then made a second call to the respondent to determine if the information in diaries were correct and to obtain additional data. Only one person per household was interviewed. The survey was designed to obtain information on time spent with family members, time spent at various locations during activities, and performing primary and secondary activities:
Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activity Factors A similar study was conducted in 1975 from October through December. Unlike the 1965-1966 survey, the 1975 survey included rural areas, farmers, the unemployed, students, and retirees. Time diary data were collected using the "yesterday" approach. In this approach, interviewers made only one contact with respondents (greater than 1500) and the diaries were filled out based on a 24-hour recall (Robinson, 1977). Time diary data were also collected from the respondents' spouses. In both surveys, the various activities were coded into 96 categories, and then were combined into five major categories. Free-time activities were grouped into 5 categories (Appendix Table 15A-2). In order to compare data obtained from both surveys, Robinson (1977) excluded the same population groups in the 1975 survey that were excluded in the 1965-66 survey (i.e., farmers, rural residents). Results obtained from the surveys were presented by gender, age, marital and employment status, race, and education. Robinson (1977) reported the data collected in hours/week; however, the method for converting daily activities to hours/week were not presented. Table 15-149 shows the differences in time use by gender, employment, and marital status for five major activity categories and five subcategories for 1965 and 1975. Time spent on work related activities (i.e., work for pay and family care) was lower in 1975 than in 1965 for employed men and women. Table 15-149 also shows that there was an overall increase in free time activities for all the six groups. The difference in time use in 1965 and 1975 are presented by age, education, and race in Tables 15-150, 15-151, and . 15-152, respectively. These tables include data for students and certain employed respondents that were excluded in Table 15-148 (Robinson, 1977). In 1975, the eldest group (ages 56-65 years) showed a decline in paid work, and an increase in family care, personal care and sleep (Table 15-150). Education level comparisons across the ten-year interval indicated that the less educated had a decrease in paid work and an increase in sleep and personal care; the most educated had an increase in work time and a decrease in other leisure (Table 15-151 ). For racial comparisons, Blacks spent less time at paid work than Whites across the ten-year interval (Table 15-152). Table 15-152 also shows that Blacks spent more time than Whites at free time activities in 1975. A limitation of the study survey design is that time use data were gathered as social indicators. Therefore, -the activity categories presented may not be relevant in exposure assessments. Another limitation is that statistical analysis of the data set was not provided. Additional limitations are that the time use data are old and the data may not reflect recent changes in time use. The 1965 and 1975 data sets excluded certain population groups and, therefore, may not be entirely representative of the U.S. population. Another limitation is that are short-term studies and may not necessarily represent long-term activity patterns. An advantage of this study is that time use data were presented by age, gender, race, education level, and employment and marital status. -Another advantage is that earlier investigations on *the study method (24-hr recall) Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activity Factors employed in the 1965 study revealed no systematic biases in reported activities (Robinson, 1977). Robinson (1977) also noted that the time-diary method provides a "zero-sum" measure (i.e., since there are only 24 daily hours or 168 weekly hours, if time on one activity increases then time on another activity must decrease). Juster et al. (1983) -1975-1981 Time Use Longitudinal Panel Study -The Time Allocation longitudinal study of the U.S. population began as part of a multinational project with the first survey conducted in 1965-66. A second national time use survey was conducted in 1975-1976 and another in 1981 (Juster et al. 1983). Juster et al. (1983) provided study descriptions of the second and third surveys. The surveys included a probability sample of the adult population (18 years and older) and children between the ages of 3 and 17 years in the United States. In both surveys, time,use was measured from 24-hour recall diaries administered to respondents and their spouses. The 1975-1976 survey involved four waves of interview: wave 1, October-November 1975; wave 2, February 1976; wave 3, May-June 1976; wave 4, September 1976. The first wave was a personal interview and the other three waves were telephone. interviews. The 1975-1976 survey sample consisted of 2,300 individuals, and of that sample, 1,519 respondents. Four recall diaries (one from each wave of interviews) were obtained from -947 respondents, with data on time use measures for two weekdays, one Saturday and one Sunday. The survey was designed to gather information for: employment status; earnings . and other income; "consumption benefits for activities of respondents and their spouses;" health, friendships and.associations of the respondents; stock technology available to the household, house repair, and maintenance activities of the family; division of labor in household work and related attitudes; physical characteristics of the respondents housing structure, net worth and housing values; job characteristics; and characteristics of mass media usage on a typical day (Juster et al., 1983). The 1981 survey was a follow-up of respondents and spouses who had completed at least three waves of interview in the 1975-1976 survey. For the 1981 survey, 920 -individuals were The survey design was similar to the 1975-1976 survey, however in this survey, the adult population was 25 years and older and consisted of 620 respondents. Four waves of interviews were conducted between February -March 1981 (wave 1), May -June 1981 (wave 2), _September 1981 (wave 3), and November -December (wave 4). The 1981 survey included the respondents' children between the ages of 3 and 17 years. The survey design for children provided information on time use measures from two time diary reports: one school day and one non-school day. In addition, information for academic achievement measures, school and family life measures, and ratings from the children'.s teachers were gathered during the survey . . Juster et al. (1983) did not report the time use data qbtained for the 1975-1976 survey or the 1981 survey. These data are stored in four tape files and can be obtained from the Inter-university Consortium for Political and Social Research (ICPSR) in Michigan. Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activify Factors The response rate for the first wave of interview (1975-76 survey) based on the original sample population was 66 percent, and response rates for the subsequent waves ranged from 42 percent (wave 4) to 50 percent (wave 2). In the 1981 survey, the response rate based on eligible respondents was 67 percent for the first interview, and ranged from 54 percent (wave 4) to 60 percent (wave 2) in the subsequent interviews (Juster et al., 1983). The 1975-1976 survey included 87 activities. In the 1981 survey, these 87 activities were broken down into smaller components, resulting in 223 activities (Juster et al., 1983). The activity codes and descriptors used for the adult time diaries in both surveys are presented in Appendix Table 15A-1. A limitation of this study is that the surveys were not designed for exposure assessment purposes. Therefore, the time use data set may be biased. Another limitation is that time use data collected were based on a 24-hour diary recall. This may somewhat bias the data set obtained from this survey. An advantage associated with this survey is that it provides a database of information on various human activities. This information can be used to assess various exposure pathways and scenarios associated with these activities. Also, some of the data from these surveys were used in the studies conducted by Timmer et al. (1985) and Hill (1985). In addition, the activity descriptor codes developed in these studies were used by Timmer et al (1985), Hill (1985), and Robinson and Thomas (1991 ). These studies are presented in Sections 15.1.1 and 15.1.2.* Another advantage of this survey is that the data are based on a national survey and conducted over a one year period, resulting in a seasonally balanced survey and one representative of the U.S. population. Hill (1985) -Patterns of Time Use -Hill ( 1985) investigated the total amount of time American adults spend in one year performing various activities and the variation in time use across three different dimensions: demographic characteristics, geographical location, and seasonal characteristics. In this study, time estimates were based on data collected from time diaries in four waves (1 per season) of a survey conducted in the fall of 1975 through the fall of 1976 for the 1975-1976 Time Allocation Study. The sampling periods included two weekdays, one Saturday and one Sunday. The 1975-1976 Time Allocation Study provided information on the amount of time spent performing primary activities. The information gathered were responses to the survey question "What were you doing?" The survey also provided information on secondary activities (i.e., respondents performing more than one activity at the same time). Hill (1985) analyzed time estimates for 10 broad categories of activities based on data collected from 87 activities. These estimates. included seasonal variation in time use patterns and comparisons of time use patterns for different days of the week. The 10 major categories and ranges of activity codes are listed in Appendix Table 15A-4. Hill (1985) collected data on time use for the major activity patterns in four different age groups (18-24, 25-44, 45-64, and 65 years and older). However, the time use data were summarized in graphs.rather than in tables. Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activity Factors Analysis of the 1975-76 survey data revealed very small regional differences in time use among the broad activity patterns (Hill,. 1985). The weighted mean hours per week spent performing the 10 major activity categories presented by region are shown in . Table 15-153. In all_ regions, adults spent more time on personal care (included night sleep). Adults in the North Central region of the country spent more time on market work activities than adults in other regions of the country. Adults in the South spent more time on leisure activities (passive and active combined) than adults elsewhere (Table 15-153). Table 15-154 presents the time spent per day, by the day of the week for the 10 major activity categories. Time spent on the 87 activities (components of the 1.0 major categories) are presented in Appendix Table 15A-5. Adult time use was dominated in descending order by personal care (including sleep), market work, passive leisure, and house work. Collectively, these activities represent about 80 percent of available time (Hill, 1985). According to Hill (1985), sleep was the single most dominant activity averaging about .56.3 .hours per week. Television watching (passive leisure) averaged about 21.8 hours per week, and housework activities averaged about 14. 7 hours per week. Weekdays were predominantly market-work oriented. Weekends (Saturday and Sunday) were predominantly devoted to household tasks ("sleeping in," socializing, and active leisure) (Hill, 1985). Table 15--155 presents the mean time spent performing these 10 groups of activities during each wave of interview (fall, winter, spring, and summer). Adjustments were made to the data to assure equal distributions of weekdays, Saturdays, and Sundays (Hill, 1985). The data indicates that the time periods adults spent performing market work, child care, shopping, organizational activities, and active leisure were fairly constant throughout the year (Hill, 1985). The mean hours spent per week in performing the 10 major activity patterns are presented by gender in Table 15-156 (time use patterns for all 87 activities are presented in Appendix Table 15A-6). Table 15-156 indicates that time* use patterns determined by data collected for the mid-1970's survey show gender differences. Men spent more time on activities related to labor market work and education, and women spent more time on household work activities. A limitation associated with this study is that the time data were obtained from an old survey conducted in the mid-1970s. Because of fairly rapid changes in American society, applying these data to current exposure assessments may result in some biases. Another limitation is that time use data were not presented for children. An advantage of this study is that time diaries were kept and data were not based on recall. The former approach may, result in a more accurate data set. Another advantage of this study is that the survey . is seasonally balanced since it was conducted throughout the year and the data are from a large survey sample.
Sell (1989) -The Use of Children's Activity Patterns in the Development of a Strategy for Soil Sampling in West Central Phoenix -In a report prepared for the Arizona
Exposure Factors Handbook August 1997 Volume III-Activity Factors Chapter 15 -Activify Factors Department of Environmental Quality, Sell (1989) investigated the activity patterns of preschool and school age children in the west central portion of Phoenix known as Maryvale. The survey was conducted in two parts: (1) most of the school age children were interviewed personally from May through June, 1989 in three schools; and (2) survey. questionnaires were mailed to parents of preschool children. \, In the first survey, 15 percent of the total school population (2,008) was sampled with 111 children in grades K-6 participating (response rate of 37 percent). The surveyed population was 53.2 percent male and 46.8 percent female. Of this population, 41 percent were Hispanics, 49.5 percent Anglos, 7.2 percent Blacks, and 1.7 percent Asians. The children interviewed were between the ages of 5 and 13 years. Within each school, the
children in grades K-6 were stratified into two groups, primary (grades K-3) and intermediate (grades 4-6), and children were selected randomly from each group. Children in grades K-2 were either interviewed in school or at home in the presence of a parent or an adult care-provider. In the course of the interview, children were asked to identify locations of activity areas, social areas (i.e., places they went with friends), favorite areas, and locations of forts or clubhouses. Aerial photographs were used to mark these areas. The second survey involved .only preschool children. Parents completed questionnaires which provided information on the amount of time their children spent outdoors, outdoor play locations, favorite places, digging areas, use of park or playgrounds, and swimming or wading locations. This survey was conducted between .. June-July 1989. One thousand (1,000) parents were sampled, but only 211 questionnaires Were usable out of 886 questionnaires received resulting in a response rate for the preschool's survey of about 24 percent. The sample population consisted of children 1 month and up to preschool age. Of this population, 53 percent were Anglos, 18 percent Hispanics, 2 percen.t Blacks, and 3 percent Asians.
The survey design considered the kinds of activities children engaged in, but not the amount of time children spent in each activity. Therefore, Sell (1989) presented the data obtained from the survey in terms of percent of respondents who engaged in specific activities or locations. A summary of percent responses of the preschool and school-age children's activities at various locations in the Maryvale study areas are presented in *Table 15-157. Also included in this table is a ranking of children's play locations based on other existing research works. Based on the survey data, Sell (1989) reported that the median time preschool children spent outdoors on weekdays was 1-2 hours, and on weekends the median time spent outdoors was 2-5 hours. Most of these children played outside in their own yards, and some played in other people's yards or parks and playgrounds (Sell, 1989). Limitations associated with this study are that the survey design did not report the time spent in various activities or locations and the response rates obtained from the Exposure Factors Handbook August 1997 Volume III -_Activity Factors Chapter 15 -Activify Factors surveys were low and, therefore, may result in biased data. In addition, because the survey was conducted in Arizona, the surveyed population does not represent the children's population on a national basis. Advantages of this study are that it provides data on various activities children engage in and locations of these activities, and provides
for time spent outdoors. This information is useful in determining exposure pathways to toxic pollutants for children. Tarshis (1981) -The AverC]ge American Book -Tarshis (1981) compiled a book addressing the habits, tastes, lifestyles, and attitudes of the American people in which he reported data on time spent in personal grooming. The data presented are gathered from small surveys, the Newspaper Advertising Bureau, and magazines. Tarshis reported frequency and percentage data by gender and age for grooming activities such as showering and bathing as follows:
90 percent take some sort of a bath in an average 24-.hour period;
5 percent average more than 1 shower or bath a day; *
75 percent of men shower, 25 percent take baths;
50 percent of women take showers, 50 percent take baths;
65 percent of teenage girls 16-19 shower daily;
55 percent of teenage girls take at least one bath a week;
50 percent of women use an additive in their bath every time they bathe; .
People are more likely to shower than bathe if they are young and have higher income; and
Showering is more popular than bathing in large cities. Limitations of this study are that the data are compiled from other sources, and that the data are old; it is possible that these data may not reflect the current trends of the general population. An advantage of the study is that it presents frequency data that are useful in exposure assessment, especially concerning volatilization of chemicals from water. AIHC (1994} -Exposure Factors Sourcebook-The activity factors data presented in the Sourcebook are similar to that in this handbook. The AIHC Sourcebook uses tenure data from the Bureau of Labor Statistics (1987), while this handbook uses more recent data (Carey, 1988) and provides general and specific recommendations for various age groups. Distributions were derived using data presented in U.S. EPA (1989) version of this handbook, the Bureau of Labor Statistics (1987), and various other Distribution data and/or recommendations are presented for time in one residence, residential occupancy, time spent indoors/outdoors, hours at home/away from home for adults and children, hours at work for adults, working tenure, and shower duration. For -each distribution, the @Risk formula is provided for direct use in the @Risk software (Palisade, 1992). The Sourcebook has been classified as a relevant rather than a key Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activify Factors study because it is not the primary source for the data used to make recommendations. It is a relevant source of alterative information. 15.2. OCCUPATIONAL MOBILITY 15.2.1. Background The amount of time spent in different types of occupations may affect the duration and/or magnitude of exposures to .contaminants specific to those occupations. For example, an individual who spends an entire lifetime as may experience a longer duration of exposure to certain contaminants, especially pesticides, than individuals who have indoor occupations. Also, individual exposures to specific chemicals in the work place may be significantly reduced when individuals change jobs. Work place exposures among women may be of shorter duration than among men because women's careers may be interrupted by home and family responsibilities. The key studies presented in the following section provide occupational tenure for workers grouped by* age, race, gender, and employment status. 15.2.2. Key Occupational Mobility Studies Carey (1988) -Occupational Tenure in 1987: Many Workers Have Remained in Their Fields -Carey (1988) presented median .occupational and employer tenure for different age groups, gender, earnings, ethnicity, and educational attainment. Occupational tenure was defined as "the cumulative number of years a person worked in his or her current occupation, regardless of number of employers, interruptions in employment, or time spent in other occupe)tions" (Carey, 1988).. The information presented was obtained from supplemental data to the January 1987 Current Population Study, a U.S. Bureau of the" . Census publication. Carey (1988) did not present information on the survey design. The median occupational tenure by age and gender, ethnicity, and employment status are presented in Tables 15-158, 15-159, and 15-160, respectively. T_he median occupational tenure of the working population ( 109.1 million people) 16 years of age and older in January of 1987, was 6.6 years (Table 15-158). Table 15-158 also shows that median occupational tenure increased from 1.9 years for workers 16-24 years old to 21.9 years for workers 70 years arid older. The median occupational tenure for men 16 years and older was higher (7.9 years) than for women of the same age group (5.4 years). Table 15-159 indicates that whites had longer occupational-tenure (6.7 years) than blacks (5.8 years), and Hispanics (4.5 years). Full-time workers had more occupational tenure than part-time workers 7.2 years and 3.1 years, respectively (Table 15-160). Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activify Factors Table 15-161 presents the median occupational tenure among major occupational groups. The median tenure ranged from 4.1 years for service workers to 10.4 years for people employed in farming, forestry, and fishing. In addition, median occupational tenure among detailed occupations ranged from 24.8 years for barbers to 1.5 years for food counter and fountain workers (Appendix Table 15A-7). The strength of an individual's attachment to a specific occupation has been attributed to the individual's investment in_education (Carey, 1988). Carey (1988) reported the median occupational tenure for the surveyed working population by age and educational level. Workers with 5 or more years of college had the highest median occupational tenure of 10.1 years. Workers that were 65 years and older with 5 or more years of college had the highest occupational tenure level of 33.8 years. The median occupational tenure was 10.6 years for self-employed workers and 6.2 years for wage and salary workers (Carey, 1988). A limitation associated with this study is that the survey design employed in the data collection was* not presented. Therefore, the validity and accuracy of the data set cannot be determined. limitation is that only median values were reported in the study. An advantage of this study is that occupational tenure. (years spent in a specific occupation) was obtained for various age groups by gender, ethnicity, employment status, and educational level. Another advantage of this study is that the data were based on a survey population which appears to represent the general U.S. population. Carey (1990) -Occupational Tenure, Employer Tenure, and Occupational Carey (1990) conducted another study that was similar in scope to the study of Carey (1988): The January 1987 Current Population Study (CPS) was used. This study provided data on occupational mobility and employer tenure in addition to occupational tenure. Occupational tenurewas defined in Carey (1988) as the "the cumulative number of years a person worked in his or her current occupation, regardless of number of employees, interruptions in employment, or time spent in other locations." Employer tenure was defined as. "the length of time a worker has been with the same employer," while occupational mobility was defined as "the number of workers who change from one occupation to another" (Carey, 1990). Occupational mobility was measured by asking individuals who were employed in both January 1986 and January 1987 if they were doing the same kind of work in each of these months (Carey, 1990). Carey (1990) further analyzed the occupational mobility data and obtained information on entry and exit rates for occupations. These rates were defined as "the percentage of persons employed in an occupation who had voluntarily entered it from another occupation" and an exit rate was defined as "the percentage of persons employed in an occupation who had voluntarily left for a new occupation" (Carey, 1990). Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activity Factors Table 15-162 shows the voluntary occupational mobility rates in January 1987 for workers 16 years and older. For all workers, the overall voluntary occupational mobility rate was 5.3 percent. These data also show that younger workers left occupations at a higher rate than older workers. Carey ( 1990) reported that 10 million of the 100.1 million individuals employed in January 1986 and in January 1987 had changed occupations during that period, resulting in an overall mobility rate of 9.9 percent. Executive, administrative, and managerial occupations had the highest entry rate of 5.3 percent, followed by administrative support (including clerical) at 4.9 percent. Sales had the highest exit rate of 5.3 percent and service had the second highest exit rate of 4.8 percent (Carey, 1990). In January 1987, the median employer tenure for all workers was 4.2 years. The median employee tenure was 12.4 years for those workers that were 65 years of age and older (Carey, 1990}. Because the study was conducted by Carey (1990) in a manner similar to that of the previous study (Carey, 1988), the same advantages and disadvantages associated with Carey ( 1988) also qpply to this data set. '----15.3. POPULATION MOBILITY 15.3.1. Background An assessment of population mobility can assist in determining the length _of time. a household is exposed in a particular location. For example, the duration of exp*osure to site-specific contamination, such as a polluted stream from which a family fishes or contaminated soil on which children play or vegetables are grown, will be directly related to the period of time residents live near the contaminated site. Information regarding population mobility is compiled and published by the U.S. Bureau of the Census (BOC). Banks, insurance companies, credit card companies, real estate and housing associations use residence history information. However, usually this information is confidential. Information compiled by the BOC provides information about population mobility; however, it is difficult to determine the average residence time of a homeowner or apartment dweller from this information. Census data provide representations of a cross-section of the population at specific points in time, but the surveys are not designed to follow individual families through time. The most current BOC information about annual geographical mobility and mobility by State is summarized in Appendix 15B. Figure 15-1 graphically displays the distribution pf movers by type of move (BOC, 1993a). -*-. e:, *: -:*_-o-... Available information was provided by the Qxforc:i: Corporation, the National Association of Realtors (NIAR), and the BOC.* According to Oxford Development Corporation, a property management firm, the typical for an apartment dweller for their corporation has been to range ..from 18 to 30 months (S. . -*"'::* ---***-----*** August 1997 Exposure Factors Handbook :.*-

Volume III -Activity Factors Chapter 15 -Activify Factors Cameron Hendricks, Sales Department, Oxford Development Corporation, Gaithersburg, MD, personal communication with P. Wood (Versar) August 10, 1992). 15.3.2. Key Population Mobility Studies .Israeli and Nelson (1992) -Distribution and Expected Time of Residence for U.S. Households -In risk assessments, the average current residence time (time since moving into current residence) has often been used as a substitute for the average total residence time (time between moving into and out of a residence) (Israeli and Nelson, 1992). Israeli . and Nelson (1992) have estimated distributions of expected time of residence for U.S. households. Distributions and averages for both current and total residence times were calculated for several housing categories using the 1985 and 1987 BOC housing survey data. The total residence time distribution was estimated from current residence time data by modeling the moving process (Israeli and Nelson, 1992). Israeli and Nelson (1992) estimated the average total residence time for a household to be approximately 4.6 years or 1/6 of the expected life span (see Table 15-163). The maximal total residence time that a given fraction,of households will live in the same residence is presented in Table 15-164. For example, only 5 percent of the individuals in the "All Households" category will live in. the same residence for 23 years and 95 percent will rriove in less than 23 years. The authors note that the data presented are for the expected time a household will stay. in the same residence. The data do not predict the expected residence time for each member of the household, which is* generally expected to be smaller (Israeli and Nelson, 1992). These values are more realistic estimates for the individual total residence time, than the average time a household has been living at its current residence. The . expected total residence time for a household is consistently less than the average current residence time. This is the result of greater weighting of short residence time when calculating the average total residence time than when calculating the average current residence time (Israeli and Nelson, 1992). When averaging total residence over a time interval, frequent movers may appear several times, but when averaging current residence times, each household appears only once (Israeli and Nelson, 1992). According to Israeli and Nelson (1992), the residence time distribution developed by model is skewed and the median values are considerably less than the means (T), which are less than the average current residence times. U.S. Bureau of the Census (1993b) -American Housing Survey for the United States in 1991 -This survey i.s a national sample of 55,000 interviews in which collected data were presented owners, renters, Black householders, and Hispanic householders. The data reflect the number of years a unit has been occupied and represent all occupied housing units that the residents' rented or owned at the time of the survey. Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activify Factors The results of the survey pertaining to residence time of owner/renter occupied units in the U.S. are presented in Table 15-165. Using the data in Table 15-165, the percentages of householders living in houses for specified time ranges were determined and.are presented in Table 15-166. Based on the BOC data in Table 15;..165, the 50th percentile and the 90th percentile values were calculated for the number of years lived in the householder's currenthouse. These values were calculated by apportioning the total sample size (93, 147 households) to the indicated percentile associated with the applicable range of years lived. in the current home. Assuming an even distribution within the appropriate range, the 50th and 90th percentile values for years living in current home were determined to be 9.1 and 32.7 years, respectively. These were then rounded to 9 and 33 years. Based on the above data, the range of 9 to 33 years is assumed to best represent a central tendency estimate of length of residence and upper percentile estimate of residence time, respectively. A limitation associated with the above analysis is the assumption that there is an even distribution within the different ranges. As a result, the 50th and 90th percentile values may be biased. Johnson and Capel (1992) -A Monte Carlo Approach to Simulating Residential Occupancy Periods and Its Application to the General U.S. Population -Johnson and Capel developed a methodology to estimate the distribution of the residential occupancy period (ROP) in the national population. ROP denotes the time (years) between a person moving into a residence and the time the person moves out or dies. The methodology used a Monte Carlo approach to simulate a distribution of ROP for 500,000 persons using data on population, mobility, and mortality. The methodology consisted of six steps. The first step defined the population of

interest and categorized them by location, gender, age,* sex, and race. Next the demographic groups were selected and the fraction of the specified population that fell into each group was developed using U.S. BOC data. A mobility table was developed based on census data, which provided the probability that a person with specified demographics did not move during the previous year. The fifth step used data on vital statistics published by the National Center for Health Statistics and developed a mortality table which provided the probability that individuals with specific demograp_hic characteristics would die during the upcoming year. As a final step, a computer based algorithm was used to apply a. Monte Carlo approach to a series of persons selected at random from the population being analyzed. Table 15-167 presents the results for residential occupancy periods for the total population, by gendeL The estimated mean ROP for the total population was 1. 7 years. The distribution was skewed (Johnson and Capel, 1992): the 25th, 50th, and ?5th percentiles were 4, 9, and 16 years, respectively. The 90th, 95th, and 99th percentiles Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activify Factors were 26, 33, and 47 years, respectively. The mean ROP was 11.1 years for males and 12.3 years for femafes, and the median value was 8 years for males and 9 years for females. Descriptive statistics for subgroups defined by current ages were also calculated. These data, presented by gender, are shown in Table 15-168. The mean ROP increases from age 3 to age 12 and there is a noticeable decrease at age 24. However, there is a steady increase from age 24 through age 81. There are a few biases within this methodology that have been noted by the authors. The probability of not moving is estimated as a function only of gender and age. The Monte Carlo process assumes that this probability is independent of (1) the calendar year to which it is applied, and (2) the past history of the person being simulated. assumptions, according to Johnson and Capel (1992), are not entirely correct. They believe.that extreme values are a function. of sample size and will, for the most part, increase as the number of simulated persons increases. 15.3.3. Relevant Population Mobility Studies
National Association of Realtors (NAR) (1993) The Home Buying and Selling Process -The NAR survey was conducted by mailing a questionnaire to 15,000 home buyers .throughout the U.S. who purchased homes during the second half of 1993. The survey was conducted in December 1993 and 1,763 usable responses were received, equaling a response rate .of 12 percent (NAR, 1993). Of the respondents, forty-one percent were first time buyers. Home buyer names and addresses were obtained from Dataman Information Services (DIS). DIS compiles information on residential real estate transactions from more than 600 counties throughout the United States using courthouse deed records. Most of the 250 Metropolitan Statistical Areas are also covered in the DIS data compilation. The home buyers were questioned on the length of time they owned their previous home. Typical homebuyer ( 41 % ) was found to have lived in their previous home between 4 and 7 years (Table 15-169). The survey results indicate that the average tenure of home buyers is. 7.1 years based on an overall residence history of the respondents (NAR, 1993). In addition, the median length of residence in respondents' previous homes was found to be 6 years (see Table 15-170). The distances the respondents moved to their new homes were typically short distances. Data presented in Table 15-171 indicate that the mean distances range from 230 miles for new home buyers and repeat buyers to 8 years for first time buyers and existing home buyers. Seventeen (17) percent of respondents purchased homes over 100 Exposure Factors Handbook. August 1997 Volume III -Activity Factors Chapter 15 -Activity Factors miles* from their previous homes and 49 percent purchased homes less than 10 miles away. Lehman (1994) -Homeowners Relocating at Faster Pace -Lehman (1994) presents data gathered by the Chicago Title and Trust Family Insurers. The data indicate that, in 1993, average U.S. homeowners moved every 12 years. In 1992, homeowners moved every 13.4 years and in 1991, every 14.3 years. Data from the U.S. Bureau of the Census indicate that 7 percent of the owner population moved in 1991. Based on this information, Lehman has concluded that it would take 12 years for 100 percent of owners to move. According to Lehman, Bill Harriett of the U.S. Bureau of the Census has been said that 14 years is a closer estimate for the time required for 100 percent of home owners to move. An advantage of this study is that it provides percentile data for the residential occupancy period. 15.4. RECOMMENDATIONS Assessors are commonly interested in a number of specific types of time use data including time/frequencies for bathing, showering, gardening, residence time, indoor versus outdoor time, swimming, occupational tenure, and population mobility. Recommendations for each of these are discussed below. The confidence recommendations for activity patterns is presented in Table 15-172. 15.4.1. Recommendations for Activity Patterns Following are recommendations for selected activities known to increase an individual's exposure to certain chemicals. These activities are time spent indoors versus outdoors and gardening, bathing and showering, swimming, residential time spent indoors and outdoors, and traveling inside a vehicle. Time Spent Indoors Versus Outdoors and Gardening -Assessors often require knowledge of time individuals spend indoors versus outdoors. Ideally, this issue would be addressed on a site-specific basis since the times are likely to vary considerably depending on the climate, residential setting (i.e., rural versus urban), personal traits (i.e.,. age, health) and personal habits. The following general recommendation is offered in the absence of site-specific information. The key study by Robinson and Thomas (1991) compares the time use values derived in the CARB and National Studies; data are presented only for persons 12 years and older. The time use values did not differ significantly between the two studies and were averaged to provide following recommended values. These values are applicable to indivi.ouals 12 years_ and older. Approximately 2_1 hrs/day are spent indoors; 1.5 hrs/day are spent-outdoors, and 1.5 hrs/day are spent in a vehicle. .. * ** Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activify Factors Activities can vary significantly with differences in age. Special attention should be given to the activities of populations under the age of 12 years. Timmer et al. (1985) presented data on time spent in various activities for boys and girls ages 3-11 years. The . study focused on activities performed indoors such as household work, personal care, eating, sleeping, school, studying, attending church, ,watching television, and engaging in household conversations. The average times spent in each indoor activity (and half the times spent in each activity which could have occurred indoors or outdoors) were summed. This procedure resulted in the following recommendations:
Indoor activities accounted for about 78 percent of the total time in weekdays and 70 percent total time in weekend days. The corresponding times spent indoors are 19 hrs/day for weekdays and 17 hrs/day on weekends.
Outdoor activities accounted for about 22 percent of children's time during
weekdays and 30 percent during the weekend. The corresponding times spent outdoors are 5 hrs/day for weekdays and 7 hrs/day on weekends. Assessors evaluating soil exposures are commonly interested in data on gardening times and frequencies. No data specific to time spent gardening could be found; thus, no firm recommendation could be made. However, three sets of data were found which indirectly relate to this issue which the assessor can consider in deriving time estimates for gardening:
Robinson and Thomas (1991) estimated the time spent in "other outdoor activities" (Table 15-8) as 1 hr/day. These data apply to populations 12 years and older.
Hill (1985) estimated that time spent in'"house work and/or yard work" (Table 15-* 153) pS 2 hr/day. These data apply to adult populations. *Dfsang and Klepeis (1996) estimated that time spent in the garden or other circumstances working with soil for persons 18-64 years old (Table 15-62) for the 90th, 95th, and 99th percentile at 16, 40, and 200 hours/month, respectively. U.S. EPA's Dermal Exposure Assessment Document (1992) recommends, on the basis of judgement, an event frequency for the adult gardener, working outside: 1 to 2 events/week during warmer months or about 40 events/year. An upper percentile value of 40 hours/month is recommended based on Tsang and Klepeis (1996). Baths and Showers -In the NHAPS study, 649 (-7 percent) of the total participants indicated either taking or giving at least one bath in a day. Those 649 respondents were subsequently asked the number of times they took or gave a bath in one day. The majority, 459 of 649 respondents, recorded taking or giving one bath in a day. The.se Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activity Factors results are presented in Table 15-24. The recommended bathing duration is 20 minutes. This is a 50th percentile value based on the NHAPS distribution shown on Table 15-26; the reported 90th percentile value is 45 minutes. ' The recommended shower frequency of one shower per day is based on the NHAPS data summarized in Table 15-19. This table showed that 3,594 of the 9,386 total participants indicated taking at least one shower the previous day. When asked the *number of actual showers taken the previous day, the reported results ranged from one to ten showers; a majority (76 percent), of those 3,549 respondents, reported taking one shower the previous day. The NHAPS data shown on Table 15-19, Table 15-24, and Table 15-26 provide information grouped according to gender, age, race, employment, education, day of the week, seasonal conditions, and health conditions such as asthma, angina, and bronchitis/emphysema. . Recommendations for showering duration are based on the key study conducted by Tsang and Klepeis (1996). A recommended value for average showering time is 10 minutes (Table 15-20) based on professional judgement. This approximates the average showering value (8 minutes) of James and Knuiman (1987) (Table 15-18). The recommended 50th percentile value is 15 minutes, and the 95th percentile value is 35 minutes (Table 15-21 ). Although values are slightly higher than those of James and Knuiman (1987), they are believed to be more representative of U.S. households. Swimming -Data for swimming frequency is taken from the NHAPS Study (Tsang and Klepeis, 1996). Of 9,386 participants, 653 (about 7 percent), answered yes to the question "in the past month, did you swim in a freshwater pool?". The results to this question are summarized in Table 15-65. The recorded number of times respondents swam in the past month ranged from 1 to 60 with the greatest number of respondents, 147 (23 percent), reporting they swam one time per month. Thus, the recommended swimming frequency is one event/ month for the general population. The recommended swimming duration, 60 minutes per swimming event, is based on the NHAPS distribution shown on Table 15-67. Sixty minutes is based on the 50th percentile value; the 90th percentile value. is 180 minutes per swimming event (based on one event/month); and the 99th percentile value is 181 minutes. This value (181) indicates that more than 180 mimJtes were spent. In addition, users can obtain frequency and duration data grouped according to gender, age, race, employment, education, day of the week, and season. Frequency and duration data is also available in Table 15-65 and Table .15-67, for swimmer respondents reporting health conditions such as asthma, angina, and bronchitis/ emphysema. Residential Time Spent Indoors and Outdoors -The recommendations for time spent indoors at one's residence is 16.4 hours/day. This is based on the NHAPS data summarized in Table 15-131 which records the 50th percentile value of 985.0 minutes per Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activify Factors day (16.4 hours/day); and a 90th perce*ntile value of 1,395 minutes per day (23.3 hours/day), The recommended value for time spent outdoors at one's residence is 2 hours per *
day based on Table 15-102. (generated by the NHAPS data). Values of 105 minutes per day for the 50th percentile and 362 minutes per day for the 90th percentile are shown in Table 15:.102. Traveling Inside a Vehicle -The recommendation for time spent in a vehicle is 1 hour and 20 minutes per day. This recommendation is based. on two studies and (1) Robinson and Thomas (1991) and (2) The NHAPS data. The Robinson and Thomas study evaluated two independent studies, the GARB and the National Study. They respectively reported mean durations for time spent in a vehicle as 98 and 87 minutes per day which averages to 92 minutes per day or about 1.5 hours per day. The NHAPS data, as summarized on Table 15-133, provide a 50th percentile value of 70 minutes per day (or 1 hour and 10 minutes) and a 90th percentile va_lue of 190 minutes per day. Thus, the averaged value from these two studies is about 1 hour and*20 minutes. NHAPS data is grouped according to gender, race, age, employment status, census region, day of the week, season, and health condition of respondents. 15.4.2. Recommendations: Occupational Mobility The median occupational tenure of the working population ( 109.1 million people) ages 16 years of age and older in January 1987 was 6.6 years (Carey, 1988). Since the occupational tenure varies significantly according to age it is recommended to use the age dependent values presented in Carey's 1988 study (Table 15-158). When age cannot be determined, it is recommended to use the median tenure value of 6.6 years for working men and women 16 years and older. For persons 70 years and older, a tenure value of ,21.9 years is recommended for a. working lifetime. A value of 30.5 years and 18.8 years is recommended for men and women, respectively. Part-time employment, race and the position held are important to consider in determining occupational tenure. The ratings indicating confidence in the occupational mobility recommendations are presented in Table 15-173. It should be noted that the recommended values are not for use in evaluating job tenure. These data can be used for determining time spent in an occupation and not for time spent at a specific job site. 15.4.3. Recommendations: Population Mobility There are three key studies from which the population mobility recommendations were derived: Israeli and Nelson (1992), U.S. Bureau of the Census (1993) -and Johnson and Capel ( 1992). *Each study used a unique approach to estimate the length of time a Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 15 -Activity Factors person resides in a household. The respective approaches were to ( 1) average current and total residence time; (2) model current residence time; and (3) determine the residential occupancy period. A summary of the approaches used and values recommended by each of these studies is presented in Table 15-17 4. The three studies provide residence time estimates that are very similar to the 9 year (50th percentile) and 30 year (95th percentile). Tables 15-163 and 15-164 show residence times for different types of residences and are recommended where assessors are interested in specific types of residences. The ratings indicating confidence in the population mobility recommendations is presented in Table 15-175. 15.4.4. Summary of Recommended Activity Factors Table 15-176 includes a summation of the recommended activity pattern factors presented in this section and the studies which provided data on the specific activities. The* type of activities include indoor activities, outdoor activities,. time inside a vehicle, taking a bath or shower, swimming, working at a specific occupation, and residing in a
particular location. Exposure Factors Handbook August 1997 Table 15-1. Time Use Table Locator Guide Percentile Basis Pooulation Aoolication Studv Table Averages Activity Children 3-17 yrs National Timmer et al., 1985 15-2 Distribution Activity Children and Teens National Timmer et al., 1985 15-3 Distribution Showering Adults Foreign-Australia James and Knuiman, 1987 15-4 Tsang and Klepeis, 1996 15-24 Averages. Activity Adults 18-64 yrs National Robinson and Thomas, 1991 15-5 Averages Activity Adults 18-64 yrs Regional-CA Robinson and Thomas, 1991 15-5 Averages Microenvironment Adults 18-64 yrs
National/Regional-CA Robinson and Thomas, 1991 15-6 Averages Microenvironment Children and Adult Regional-California Robinson and Thomas, 1991 15-7 to 15-10 Averages Microenvironment Children and Adults National Robinson and Thomas, 1991 15-7to 15-10 Averages Activity Infants and Children Regional-California Wiley et al., 1991 15-11 Distribution Activity Infants and Children Regional-California Wiley et al., 1991 15-12 Averages Activity by season Infants and Children Regional-California Wiley et al., 1991 15-13 Averages Microenvironment Infants and Children Regional-California Wiley et al., 1991 15-14 Distribution Microenvironment Infant and Children Regional-California Wiley et al., 1991 15-15 Averages Microenvironment by Infants and Children Regional-California Wiley et al., 1991 15-16 season Distribution
Microenvironment near Infant and Children Regional-California Wiley et al., 1991 15-17 pollutant Averages Bathing and swimming Adults Regional-National USEPA, 1992 15-18 Tsang and Klepeis, 1996 15-22, 15-63 Average Activity by employment Adults National Robinson, 1977 15-147 Averages Occupational Tenure Teens and Adults National Carey, 1988 15-157 by race and gender Averages Occupational Tenure Teens and Adults National Carey, 1988 15-158 by employment and gender Distribution Occupational Tenure Teens and Adults National Carey, 1988 15-159 by employment Distribution Occupational Mobility Teens and Adults National Carey, 1990 15-160 by age Distribution Population Mobility by All ages National Census, 1993 Figure 15-1 locale Averages Residence Time by All ages National Israeli and Nelson, 1992 15-161 region, setting Distribution Residence Time by All ages. National Israeli and Nelson, 1992 15-162 region, setting Distribution Residence Time by All ages National Census, 1993 15-163 year moved in Distribution Residence Time by All ages National Census, 1993 15-164 years in current home Distribution Residence Time by All ages National Johnson and Capel, 1992 15-165 gender Distribution Residence Time by age All ages National Johnson and Capel, 1992 15-166 Distribution Residence Time by All ages N<;itional NAR, 1993 1.5-167 years in previous house Distribution Residence Time by All ages National NAR, 1993 15-168 tenure in previous home Distribution Relocation Distance All aqes National NAR, 1993 15-169 Table 15-2. Mean Time Scent (minutes) Performinq Maier Activities Grouoed by Aqe, Sex and Tvoe of Dav Activitv Aae 13-11 vears) Duration of Time (mins/day) Weekdays Weekends Boys Girls Boys Girls (n=118) (n=111) (n=118) (n=111) Market Work 16 0 7 4 Household Work 17 21 32 43 Personal Care 43 44 42 50 Eating 81 78 78 84 Sleeping 584 590 625 619 School 252 259 ----Studying 14 19 4 9 Church 7 4 53 *. 61 ' Visiting 16 9 23 37 Sports 25 12 33 23 Outdoors 10 7 30 23 Hobbies 3 1 3 4 Art Activities 4 4 4 4 Playing 137 115 177 166 TV 117 128 181 122 Reading 9 7 12 10 Household Conversations 10 11 14 9 Other Passive Leisure 9 14 16 17 NA" 22 25 20 29 Percent of Time for bv Activities Above 94% 92% 93% 89% a NA= Unknown Source: Timmer et al. 1985. Aae 112-17 vearsl Duration ofTime (mins/day) Weekdays Weekends Boys Girls (n=77) (n=83) 23 21 16 40 48 71 73 65 504 478 314 342 29 37 . 3 7 17 25 52 37 10 10 7 4 12 6 37 13 143 108 10 13 21 30 21 14 14 17 93% 92% Boys (n=77) 58 46 35 58 550 --25 40 46 65 36 4 11 35 187 12 24 43 10 88% ' ' Girls (n=83) 25 89 76 75 612 -25 36 53 26 19 7 9 24 140 19 30 33 4 89%

Table 15-3. Mean Time Spent (minutes) in Maior Activities Grouped by Type of Dav for Five Different AQe Groups Time Duration (mins) Significant Weekday Weekend Effects" Aae lvearsl 3-5 6-8 9-11 12-14 15-17 3-5 6-8 9-11 12-14 15-17 Activities Market Work --14 8 14 28 --4 10 29 48 Personal Care 41 49 40 56 60 47 45 44 60 51 A,S,Ax.S (F>M) Household Work 14 15 18 27 34 17 27 51 72 60 A,S, Ax.S (F>M) Eating 82 81 73 69 67 81 80 78 68 65 A Sleeping 630 595 548 473 499 634 641 596 604 562 A School 137 292 315 344 314 ----------Studying 2 8 29 33 33 1 2 12 15 30 A Church 4 9 9 9 3 55 56 53 32 37 A Visiting 14 15 10 21 20 10 8 13 22 56 A(Weekend only) Sports 5 24 21 40 46 3 30 42 51 37 A,S (M>F) Outdoor activities 4 9 8 7 11 8 23 39 25 26 Hobbies 0 2 2 4 6 1 5 3 8 3 Art Activities 5 4 3 3 12 4 4 4 . 7 10 Other Passive Leisure 9 1 2 6 4 6 10 7 10 18 A Playing 218 111 65 31 14 267 180 92 35 21 A,S (M>F) TV 111 99 146 142 108 122 136 185 169 157 A,S, Ax.S (M>F) Reading 5 5 9 10 12 4 9 10 10 18 A Being read to 2 2 0 0 0 3 2 0 0 0 A NA 30 14 23 25 7 52 7 14 4 9 A a Effects are significant for weekdays and weekends, unless otherwise specified A = age effect, P<0.05, for both weekdays and . weekend activities; S =sex effect P<0.05, F>M, M>F = spend more time than males, or vice versa; and Ax.S = age by sex interaction, P<0.05. Source: Timmer et al. 1985. I Table 15-4. Cumulative Frequency Distribution of Average Shower Duration for 2,550 Households Shower duration (minutes) Cumulative frequency (percentage) 1 0.2 2 0.8 3 3.1 4 9.6 5 22.1 6 37.5 7 51.6 8 62.5 9 72.0 10 79.4 11 84.5 12 88.4 13 90.6 14 92.3 15 93.7 16 94.9 17 95.7 18 96.7 19 97.6 20 98.0 <20 100.0 Source: Adapted from James and Knuiman, 1987. Table 15-5. Mean Time Spent (minutes/day) in Ten Major Activity Categories Grouped by Total Sample and Gender for the GARB and National Studies (aqe 18-64 years) *Time Duration (minslday) Activity Category* Activity GARB National GARB National Codesb (1987-88) (1985) (1987-88) (1985) . Total Sample Men Women Men Women n° = 1,359 n = 1,980 n =639 n =720 n = 921 n=1,059 Paid Work 00-09 273 252 346 200 323 190 Household Work 10-19 102 118 68 137 79 155 Child Care 20-29 23 25 12 36 11 43 Obtaining Goods and 30-39 61 55 48 73 44 62 Services Personal Needs and 40-49 642 642 630 655 636 645 Care Education and Training 50-59 22 19 25 20 21 16 Organizational Activities 60-69 12 17 11 13 12 20 Entertainment/Social 70-79 60 62 57 55 64 62 Activities Recreation 80-89 43 50 53 31 69 43 Communication 90-99 202 196 192 . 214 197 194 a,b Time use for components of activity categories and codes are shown in Appendix Table 15A-6. c n = total diary days. Source: Robinson and Thomas, 1991 Table 15-6. Total Mean Time Spent at Three Major Locations Grouped by Total Sample and Gender for the GARB and National Study (ages 18-64 years) Location* Godeb GARB National GARB National (1987-88) (1985) (1987-88) (1985) Total Sample Men Women Men Women n° = 1359 n° = 1980 n° = 39 n° = 720 n° = 921 n° = 1059 At Home WG01-13 892 954 822 963 886 1022 Away From Home WG21-40 430 384 487 371 445 324 Travel WG51-61 116 94 130 102 101 87 Not Ascertained WG99 2 8 1 4 8 7 Total Time 1440 1440 1440 1440 1440 1440 a,b Time use data for the 44 components of location and location codes are presented in Appendix Table 15A-7. c n =total diary days. Source: Robinson and Thomas, 1991. Table 15-7. Mean Time Spent at Three Locations for both CARB and National Studies (ages 12 years and older) Mean duration (mins/dav) Location Category CARB National (n = 1762)b S.E." (n = 2762)b S.E. *indoor 1255° 28 1279° 21 Outdoor 86d 5 74d 4 In-Vehicle 98d 4 87d 2 Total Time Soent 1440 1440 a S.E. = Standard Error of Mean b Weighted Number -National sample population was weighted to obtain a ratio of 46.5 males and 53.5 females, in equal proportion for each day of the week, and for each quarter of the year .. c Difference between the mean values for the CARB and national studies is not statistically significant. d Difference between the mean values for the CARB and national studies is statistically significant at the 0.05 level.

Source: Robinson and Thomas, 1991.

Table 15-8. Mean Time Spent (minutes/day) in Various Microenvironments Grouped by Total Population and Gender ( 12 vears and over) in the National and CARB Data National Data Mean Duration (mins/day) (standard error)" N = 1284b * "Doer"0 N = 1478b "Doer N = 2762b "Doer Microenvironment Men Men Women Women Total Total Autoplaces 5 (1) 90 1 (0) 35 3 (0) 66 Restaurant/bar 22 (2) 73 20 (2) 79 21 (1) 77 In-vehicle 92 (3) 99 82 (3) 94 *87(2) 97 In-Vehicle/other 1 (1) 166 1 (0) 69 1 (0) 91 Physical/outdoors 24 (3) 139 11 (2) 101 17 (2) 135 Physical/indoors 11 (1) 84 6 (1) 57 8 (1) 74 Work/study-residence 17 (2) 153 15 (2) 150 16 (1) 142 Work/study-other 221 (10) 429 142 (7) 384 179 (6) 390 Cooking 14 (1) 35 52 (2) 67 34 (1) 57 Other activities/kitchen 54 (3) 69 90 (4) 102 73 (2) 88 Chores/child 88 (3) 89 153 (5) 154 123 93) 124 Shop/errand 23 (2) 56 38 (2) 74 31 (1) 67 Other/outdoors 70 (6) 131 43 (4) 97 56 (4) 120 Social/cultural 71 (4) 118 75 (4) 110 73 (3) 118 Leisure-eat/indoors 235 (8) 241 215 (7) 224 224(5) 232 Sleen/indoors 491 114\ 492 496111) 497 494(9) 495 CARB Data Mean Duration (mins/day) (standard error)* N = 867b "Doer0 N = 895b "Doer N = 1762b "Doer Microenvironment Men Men Women Women Total Total Autoplaces 31 (8) 142 9 (2) 50 20 (4) 108 Restaurant/bar 45 (4) 106 28(3) 86 36 (3) 102 In-vehicle 105 (7) 119 85 (4) 100 95 (4) 111 In-Vehicle/other 4 (1) 79 3 (2) 106 3 (1) 94 Physical/outdoors 25 (3) 131 8 (1) 86 17 (2) 107 Physical/indoors 8 (1) 63 5 (1) 70 7 (1) 68 Wark/study-residence 14 (3) 126 11 (2) 120 13 (2) 131 Wark/study-other 213 (14) 398 156 (11) 383 184 (9) 450 Cooking 12 (1) 43 42 (2) 65 27 (1) 55 Other activities/kitchen 38(3) 65 60 (4) 82 49 (2) 74 Chores/child 66 (4) 75 134 (6) 140 100 (4) 109 Shop/errand 21 (3) 61 41 (3) 78 31 (2) 70 Other/outdoors 95 (9) 153 44(4) 82 69 (5) 117 Social/cultural 47 (4) 112 59(5) 114 53 (3) 112 Leisure-eat/indoors 223 (10) 240 251 (10) 263 237(7) 250 Sleeo/indoors 492117) 499 504 (15) 506 498 (12) 501 a Standard error of the mean b Weighted number

c Doer = Respondents who reported participating in each activity/location spent in microenvironments. so*urce: Robinson and Thomas 1991.

Table 15-9. Mean Time Spent (minutes/day) in Various Microenvironments by Type of Day for the California and National Surveys (sample population ages 12 years and older) Weekday Mean Duration (standard error)* Mean Duration for "Doer"b Microenvironment (mins/day) (mins/day) CARB NAT (n=1259)0 (n=1973)° CARB NAT 1 Autoplaces 21 (5) 3 (1) 108 73 2 Restaurant/Bar 29 (3) 20 (2) 83 73 3 In-Vehicle/Internal Combustion 90 (5) 85 (2) 104 95 4 In-Vehicle/Other 3 (1) 1 (0) 71 116 5 Physical/Outdoors 14 (2) 15 (2) 106 118 6 Physical/Indoors 7 (1) 8 (1) 64 68 7 Work/Study-Residence 14 (2) 16 (2) 116 147 8 Work/Study-Other 228(11) 225 (8) 401 415 9 Cooking 27 (2) 35 (2) 58 57 10 Other Activities/Kitchen 51 (3) 73 (3) 76 87 11 Chores/Child 99 (5) 124 (4) 108. 125 12 Shop/Errand 30 (2) 30 (2) 67 63 13 Other/Outdoors 67 (6) 51 (4) 117 107 14 Social/Cultural 42 (3) 62 (3) 99 101 15 Leisure-Eat/Indoors 230 (9) 211 (6) 244 218 16 Sleep/Indoors 490(14) 481 (10) 495 483 Weekend Mean Duration (standard error)* Mean Duratiqn for "Doer"b Microenvironment (mins/day) (mins/day) CARB NAT (n=503)0 (n=789)° CARB NAT 1 Autoplaces 19 (4) *3 (1) 82 62 2 Restaurant/Bar 55 (6) . 23 (2) 127 84 3 In-Vehicle/Internal Combustion 108 (8) 91 (6) 125 100 4 In-Vehicle/Other 5 (3) 0 (0) 130 30 5 Physical/Outdoors 23 (3) 23 (4) 134 132 6 Physical/Indoors 7 (1) 9. (2) 72 80 7 Work/Study-Residence 10 (2) 15 (3) 155 165 8 Work/Study-Other 74 (11) 64 (6) 328 361 9 Cooking 27 (2) 34 (2) 60 55 10 Other Activities/Kitchen 44 (3) 73 (4) 71 90 11 Chores/Child 103 (7) 120 (5) 114 121 12 Shop/Errand 35 (4) 35 (3). 81 75 13 Other/Outdoors 74 (7) 67 (7) 126 132 14 Social/Cultural 79 (7) 99 (6) 140 141 15 Leisure-Eat/Indoors 256 (12) 257 (11) 273 268 16 Sleep/Indoors 520 (20) 525 (17) 521 525 *Standard Error of Mean b Doer= Respondent who reported participating in each activity/location spent in microenvironments. 0 Weighted Number Source: Robinson and Thomas, 1991. Table 15-10. Mean Ti!Tle Spent (minutes/day) in Various Microenvironments by Age Groups for the National and California Surveys National Data Microenvironment Mean Duration !Standard Error\' Age 12-17 Age 18-24 Age 24-44 Age 45-64 Age 65+ Jears =340b 11Doer110 years N=340 "Doer years N=340 "Doer" years N=340 "Doer" years N=340 "Doer Auto places 2 (1) 73 7 (2) 137 2 (1) 43 4 (1) 73 4 (2) 57 Restaurant/bar 9 (2) .60 28 (3) 70 25 (3) 86 19 (2) 67 20 (5) 74 In-vehicle/internal combustion 79 (7) 88 103 (8) 109 94 (4) 101 82 (5) 91 62 (5) 80 In-vehicle/other 0 (0) 12 1 (1) 160 1 (0) 80 1 (1) 198 1 (1) 277 Physical/outdoors 32 (8) 130 17 (4) 110 19 (4) 164 7 (1) 79 15 (4) 81 Physical/indoors 15 (3) 87 8 (2) 76 7 (1) 71 7 (2) 77 7 (1) 51 Work/study-residence 22 (4) 82 19 (6) 185 16 (2) 181 9 (2) 169 5 (3) 297 Work/study-other 159 (14) 354 207 (20) 391 220 (11) 422 180 (13) 429 35 (6) 341 Cooking 11 (3) 40 18 (2) 39 38 (2) 57 43 (3) 64 50 (5) 65 Other activities/kitchen 53 (4) 64 42 (3) 55 70 (4) 86 90 (6) 101 108 (9) 119 Chores/child 91 (7) 92 124 (9) 125 133 (6) 134 121 (6) 122 . 119 (7) 121 Shop/errands 26 (4) 68 31 (4) 65 33 (2) 66 33 (3) 67 35 (5) 69 Other/outdoors 70 (13) 129 34 (4) 84 48 (6) 105 60 (7) 118 82 (13) 140 Social/cultural 87 (10) 120 100 (12) 141 56 (3) 94 73 (6) 116 85 (8) 122 *Leisure-237 (16) 242 181 (11) 189 200 (8) 208 238 (11) 244 303 (20) 312 eat/indoors Sleep/indoors 548 (31) 551 511 (26) 512 479 (14) 480 472 (15) 472 507 (26) 509 Table 15-10. Mean Time Spent (minutes/day) in Various Microenvironments by Age Groups (continued) CARB Data Microenvironment Mean Duration IStandard Error)" Age 12-17 Age 18-24 Age 24-44 Age 45-64 Age 65+ Jears years years =183b "Doer"' N=250 "Doer" N=749 "Doer" years N=406 11Doer11 years N=158 11Doer" Auto places 16 (8) 124 16 (4) 71 25 (9) 114 20 (5) 94 9 (2) 53 RestauranUbar 16 (4) 44 40 (8) 98 44 (5) 116 31 (4) 82 25 (7) 99 .In-vehicle/internal combustion 78 (11) 89 111 (13) 122 98 (5) 111 100 (11) 117 63 (8) 89 In-vehicle/other 1 (0) 19 3 (1) 60 5 (2) 143 2 (1) 56 2 (1) 53 Physical/outdoors 32 (7) 110 13 (3) 88 17 (3) 128 14 (3) 123 15 (4) 104 Physical/indoors . 20 (4) 65 5 (2) 77 6 (1) 61 5 (1) 77 3 (1) 48 Work/study-residence 25 (5) 76 30 (11) 161 7 (2) 137 10 (3) 139 5 (3) 195 Work/study-other 196 (30) 339 201 (24) 344 215 (14) 410 173 (20) 429 30 (11) 336 Cooking 3 (1) 19 14 (2) 40 32 (2) 59 31 (3) 68 41 (7) 69 Other activities/kitchen 31 (4) 51 31 (5) 55 43 (3) 65 62 (6) 91 97 (14) 119 Chores/child 72 (11) 77 79 (8) 85 110 (6) 119 99 (8) 109 123 (15) 141 Shop/errands 14 (3) 50 35 (7) 71 33 (4) 71 32 (3) 77 35 (5) 76 Other/outdoors 58 (8) 78 80 (15) 130 68 (8) 127 76 (12) 134 55 (7) 101 Social/cultural 63 (14) 109 65 (10) 110 50 (5) 122 50 (5) 107 49 (7) 114 Leisure-eaUindoors 260 (27) 270 211 (19) 234 202 (9) 215 248 (15) 261 386 (34) 394 Sleep/indoors 557 (44) 560 506 (30) 510 487 (17) 491 485 (23)' 491 502 (31) 502 a Standard error. b All N's are weighted number. ' Doer= Respondents who reported participating in each activity/location spent in microenvironments. Source: Robinson and Thomas, 1991. Table 15-11. Mean Time Children Spent in Ten Major Activity Categories for I Respondents Mean Median Maximum Mean Duration Duration Duration Detailed Activi!}' with Duration % for Doersb for Doer for Doers Highest Minutes Activitv Cateaorv lmins/dav) Doino lmins/dav) lmins/dav) lmins/dav) (co el Werk-related* 10 25 39 30 405 Eating at work/school/daycare (06) Household 53 86 61 40 602 Travel to household (199) Childcare < 1 < 1 83 30 290 Other child care (27) Goods/Services 21 26 81 60 450 Errands (38) Personal Needs and Care0 794 100 794 770 1440 Night sleep (45) Educationd 110 35 316 335 790 School classes (50) Organizational Activities *4 4 111 105 435 Attend meetings (60) Entertain/Social 15 17 87 60 490 Visiting with others (75) Recreation 239 92 260 240 835 Games(87) Communication/Passive 192 93 205 180 898 TV use (91) Leisure ' Don't know/Not cocjed 2 \ 4 41 15 600 --\ All Activities* 1441

Includes eating at school or daycare, an not grouped under the "education activities" (codes 50-59, 549). b "Doers" indicate the respondents who reporte participating in each activity category. 0 Personal care includes night sleepand daytime naps, eatinTI, travel for personal care.
d Education includes student and other classes, homework, ibrary, travel for education. 'Column total may not sum to 1440 due to rounding error Source: Wilev et al. 1991.

Table 15-12. Mean Time Children Spent in Ten Major Activity Categories Grouped by AQe and Gender Mean Duration lminutesldav)* Activity Boys Girls Category All All 0-2 yrs 3-5 yrs 6-8 yrs 9-11 yrs AQes 0-2 yrs 3-5 yrs 6-8 yrs 9-11 yrs Ages Wark-related 4 9 14 12 10 5 12 11 10 10 Household 33 45 55 65 48 58 44 51 76 57 Childcare 0 0 0 1 <1 0 0 0 4 1 Goods/Services 20 22 19 14 19 22 25 23 22 23 Personal Needs and 914 799 736 690 792 906 816 766 701 797 Educationb 60 67 171 138 106 41 95 150 176 115 Organizational Activities 1 3. 7 6 4 6 1 4 6 4 EntertainmentlSocial 3 15 5 34 13 5 16 9 36 17 Recreation 217 311 236 229 250 223 255 238 194 228 Communication/Passive 187 166 195 250 197 171 173 189 213 186 Leisure Don't know/Not coded 1 4 1 1 2 3 1 <1 3 2 All Activities' 1440 1441 1439 1440 1442 1440 1438 1441 1441 1440 Sample Sizes 172 151 145 156 624 141 151 124 160 576 UnweiQhted N's ' Personal needs and care includes night sleep and daytime naps, eating, travel for personal care. b Education includes student and other classes, homework, library, travel for education. c The column totals may differ from 1440 due to rounding error. Source: Wiley et al. 1991. Table 15-13. Mean Time Children Spent in Ten Major Activity Categories Grouped by Seasons and Regions Mean Duration (minutes/day) Activity Category Season Region of California Winter Spring Summer Fall All So. Bay Rest of All (Jan-Mar) (Apr-June) (July-Sept) (Oct-Dec) Seasons Coast Area State Regions Werk-related 10 10 6 13 10 10 10 8 10 Household 47 58 53 52 53 45 62 55 53 Childcare <1 1 <1 <1 <1 <1 <1 1 <1 Goods/Services 19 17 26 23 21 20 21 23 21 Personal Needs and' 799 . 774 815 789 794 799 785 794 794 Care* Educationb 124 137 49 131 110 109 115 109 110 Organizational Activities 3 5 5 3 4 2 6 6 4 Entertainment/Social 14 12 12 22 15 17 10 16 15 Recreation 221 243 282 211 239 230 241 249 239 Communication/Passiv 203 180 189 195 192 206 190 175 192 e Leisure Don't know/Not coded <1 2 3 <1 2 1 1 3 2 All Activities0 1442 1439 1441 1441 1441 1440 1442 1439 1441 Sample Sizes (Unweighted) 318 204 . 407 271 1200 224 263 713 1200

Personal needs and care includes night sleep and daytime naps, eating, travel for personal care. 6 Education includes student and other classes, homework, library, travel for education. 0 The column totals may not be equal to 1440 due to rounding error. Source: Wiley et al., 1991.

Table 15-14. Mean Time Children Spent in Six Major Location Categories for All Respondents (minutes/day) Mean Mean Median Maximum Location Category Duration % Duration Duration Duration for Detailed Location with Highest (mins) Doing for Doers for Doers Doers Avg. Time !minsl (mins) (mins) Home 1,078 99 1,086 1, 110 1,440 Home -bedroom School/Childcare 109 33 330 325 1,260 School or daycare facility Friend's/Other's House 80 32 251 144 1,440 Friend's/other's house -bedroom Stores, Restaurants, 24 35. 69 50 475 Shopping mall Shopping Places In-transit 69 83 83 60 1, 111 Traveling in car Other Locations 79 57 139 105 1,440 Park, playground. Don't Know/Not Coded <1 1 37 30 90 --All Locations 1 440 Source: Wilev et al. 1991. Table 15-15. Mean Time Children Spent in Six Location Cateqories Grouped by Aqe and Gender Mean Duration (minutes/dav) Boys Girls Location Category All All 0-2 yrs 3-5 yrs 6-8 yrs 9-11 yrs Boys 0-2 yrs 3-5 yrs yrs 9-11 yrs Girls Home 1,157 1,134 1,044 1,020 1,094 1, 151 . 1,099 1,021 968 1,061 School/Childcare 86 88 144 120 108 59 102 133 149 111 Friend's/Other's House 67 73 77 109 80 56 47 125 102 80 Stores, Restaurants, 21 25 22 15 21 23 35 27 26 28 Shopping Places In-transit 54 62 61 62 59 76 88 53 93 79 Other Locations 54. 58 92 114 77 73 68 81 102 81 Don't Know/Not Coded <1 <1 <1 <1 <1 <1 <1 <1 <1 <1 All Locations* 1,439 1,440 1,439 1,440 1,439 1,438 1,440 1,440 1,440 1,440 Sample Sizes * (Unweiqhted)

172 151 145 156 624 141 151 124 160 576
The column totals may not sum to 1,440 due to rounding error. Source: Wiley et al., 1991 .

Table 15-16. Mean Time Children Spent in Six Location Cateqories Grouped by Season and Region Mean Duration (minutes/day) Season Region of California Location (::ategory Winter Spring Summer Fall All So. Bay Rest of All (Jan-Marl (Apr-June) (July-Sept) (Oct-Dec) Seasons Coast Area State Reqions Home 1,091 1,042 1,097 1,081 1,078 1,078 1,078 1,078 1,078 School/Childcare 119 141 52 124 109 113 103 108 109 Friend's/Other's 69 75 108 69 80 73 86 86 80 House Stores, Restaurants, 22 21 30 24 24 26 23 23 24 Shopping Places In-transit 75 75* 60 65 69 71 73 63 69 Other Locations 63 85 93 76 79 79 76 81 79 Don't Know/Not <1 <1 <1 <1 <1 <1 <1 <1 .<1 Coded All Locations* 1,439 1,439 1,440 1,439 1,439 1,439 1,440 1,440 1,439 Sample Sizes (Unweiqhted N's) 318 204. 407 271 1,200 224 263 713 1,200 *The column totals ma§ not sum to 1,440 due to rounding error. Source: Wiley et al., 1 91.

Table 15-17. Mean Time Children Spent in Proximity to Three Potential Exposures Grouped by All Respondents, Age, and Gender Mean Duration (minutes/day) Potential Exposures Boys Girls All All All Children 0-2 yrs 3-5 yrs 6-8 yrs 9-11 yrs Boys 0-2 yrs 3-5 yrs 6-8 yrs 9-11 yrs Girls Tobacco Smoke 77 115 '75 66 66 82 77 68 71 74 73 Gasoline Fumes 2 2 1 1 4 2 1 1 3 1 1 Gas Oven Fumes 11 10 15 12 11 12 12 10 10 7 10 Sample Sizes (Unweighted N's) 1,166a 168 148 144 150 610 140 147 122 147 556

Respondents with missing data were excluded. Source: Wiley et al., 1991.

Table 15-18. Range of Recommended Defaults for Dermal Exposure Factors Water Contact Soil Contact Bathing Swimming Central Upper Central Upper Central Upper Event time and 1 O min/event 15 min/event 0.5 hr/event 1.0 hr/event 40 events/yr 350 events/yr frequency" 1 event/day 1 event/day 1 event/day 1 event/day 350 days/yr 350 days/yr 5 days/yr 150 days/yr Exposure 9 years 30 years 9 years 30 years 9 years 30 years duration a Bathing event time is presented to be representative of baths as well as Source: U.S. EPA 1992. Table 15-19. Number of Times Taking a Shower at Specified Daily Frequencies by the Number of Respondents Times/Day Total N 0 1 2 3 4 5 8 10 11:1-0+ DK Overall 3594 2 2747 802 30 1 1 1 1 4 5 Gender 1720 * * *

Male 1259 436 21 1 1 2 Female 1872 ? 1486 3§6 1 1 1 Refused 2 2
Age (years) 64
46 17 * * * * *
1 1-4 41
30 9 1 * * * *
1 5-11
26 1 * * * *
1 12-17
65 6 * * * *
18-64 2650 1 1983 636 21 1 1 1 1 3 ? >64 429 1 377 49 1 1 Race * *
White 2911 ? 2323 562 17 1 1 2 Black 349 199 140 7 1 1
1 Asian
j8 14 1 * * * * *
Some others
23 2 * * * * *
His/Ganie 162
103 56 2 * *
1 *
Re sed 43
33 7 1 * * *
2 3269 ? 2521 711 24 1 1 1
1 1 Yes 277 190 81 § 1 DK 17
13 4 * * * *
Refused 31
23 6 1 * * * *
1 EIJlployment 439
330 99 8 * * * *
2 Full Time 1838 1 1361 454 17 * *
1 2 2 . Part Time 328 1 261 65 *
1 * * *
Not Emr;>loyed 967 780 177 § 1
1
2 1 Refusea 22
15 7 * * . *
515
382 121 9 . . . .
3 < High 297
240 54 2 * * * . 1
Hi81i Sc ool Graduate 1042 1 789 243 5
1 1
1 1 < allege 772 1 589 176 4 *
1
1 coneae Graduate 576 434 133 7 1 *
1 Post raduate 392 . 313 75 3 . * *
1
Census Region Northeast 828
622 196 7 * * * *
3 Midwest l25466 . Bl * . . *
1 South 1 1 * *
3 West 764 1 611 141 6
1 1 1 1 1
2481
1889 563 17 1 1 1 1 4 4 eek ay Weekena 1113 2 858 239 13 * * * *
1 swson * * * *
inter 941 732 198 9 1 1 Spring . 889
674 205 7 * * . 1
2 Summer 1003
735 254 10 1 *
2 1 Fall 761 2 606 145. 4
1 1
1 1 Asthma No 3312 ? 2543 730 25 1 1 1 1 4 1 261 189 67 * *' 21
15 5 * . * *
1 AWna 1 2653 219 1 1 1 1 1 1 es 1 77 DK 22 17 4 * * .. .
1 3419 ? 2620 758 27 1 1 1 1 1 1 Yes 154 112 39 * .
DK 21
15 5 . * . *
1 Note:
Signifies missing Dk= don't know; N = sample size. Source: Tsana and Kleoeis 19 6 Table 15-20. Times (minutes) Spent Taking Showers by the Number of Respondents Total N *
0-10 10-20 Minutes/Shower 20-30 30-40 40-50 50-60 60-61 Overall 3594 47 1640 1348 397 72 52 51 17 Gender Male 1720 13 788 625 213 35 25 14 7 Female 1872 3.4 850 1§4 3J 2J 3J \0 Refused 2 2 J\ge 64 6 27 23 3 1
2 ? 1-4 41 1 13 14 10 1
2 5-11 140 1 60 52 18 3 2 4
12-17 f6 104 40 9 {3 111 18-64 977 288 37 >64 429 21 208 148 38 4 4 3 3 2911 38 1406 1070 292 39 31 26 9 Black 349 115 120 58 20 11 \6 4 Asian 64 25 25 10 1 2 1 Some Others 65 . 18 29 6 3. 4 4 1 162 1 57 60 25 8 1 ? Re used 43 3 19 14 6 1 Hispanic . 3269 43 1526 1188 352 61 42 44 13 No Yes 277 1 98 109 40 \0 8 7 1 DK 17 5 9 1 ?
Refused 31 3 11 12 4 1 *
E_mployment 439 4 163 165 66 17 10 12 2 yrne 10 191 32 20 20 art 1me 4 39 4 5 3 No}uEmP,loyed 967 27 431 355 97 \9 16 16 Re sea 22 2 11 4 4 1 E_ducation 515 10 190 186 79 21 13 14 2 < High School 297 8 93 125 51 6 7 6 1 Hi8ti School Graduate 1042 12 451 409 108 23 17 16 6 < ollege 772 12 377 271 79 14 6 7 6 Collee,,e Graduate 576 2 297 211 50 5 5 5 1 Post raduate 392 3 232 116 30 3 4 3 1 Census Region 828 7 374 326 79 15 11 12 4 Northeast Midwest 756 11 385 253 70 16 9 9 3 2:f 461 179 35 26 23 6 est 278 69 6 6 7 4 \1i364 279 10 Wee eno 11 3 118 7 Season la jf 6 rn rn 6 prmg 5 Summer 1003 11 435 366 128 29 17 12 5 Fall 761 10 374 280 81 4 6 5 1 Asthma No 3312 38 1526 1222 362 65 44 41 14 Yes 261 4 108 89 33 I \0 2 DK 21 5 6 7 2 1 Angina 3481 70' No 91 36 1591 1276 389 51 5.1 \7 6f64 408 3 3 5 5 10 10 20 30 30 45 60 61 Race White 2873 3 4 5 5 10 13 20 30 30 45 60 61 Race Black 344 4 4 5 6 10 20 30 40 60 60 61 61 Race Asian 64 1 3 4 5 10 15 20 30 40 48 61 61 Race Some Others 65 3 3 5 10 10 15 30 45 60 60 61 61 Race Hispanic 161 3 4 5 6 10 15 25 40 45 60 61 61 Hispanic No 3226 3 4 5 5 10 15 20 30 30 45 60 61 Hispanic Yes 276 3 4 5 6 10 15 22.5 39 45 60 61 61 Employment Full Time 1828 3 4 5 5 10 15 20 30 30 45 60 61 Employment Part Time 324 2 3 5 5 10 12 20 30 30 45 60 60 Employment Not Employed 940 3 3 5 5 10 15 20 30 40 60 60 61 Education < High School 289 4. 5 5 8 10 15 20 30 40 60 60 61 Education High School Graduate 1030 2 3 5 5 10 15 20 30 40 60 60 61 Education <College 760 3 5 5 5 10 12 20 30 30 45 60 61 Education College Graduate 574 3 3 5 5 10 10 20 25 30 40 60 61 Education Post Graduate 389 2 3 4 5 7 10 15 25 30 45 60 61 Census Region Northeast 821 4 5 5 5 10 15 20 30 32 50 60 61 Census Region Midwest 745 3 4 5 5 10 10 20 30 30 45 60 61 Census Region South 1220 3 3 5 5 10 15 20 30 40 60 60 61 Census Region West 761 2 3 5 5 10 10 15 30 30 45 60 61 Day of Week Weekday 2447 3 4 5 5 10 15 20 30 35 48 60 61 Day of Week Weekend 1100 3 4 5 5 10 15 20 30 40 60 60 61 Season Winter 929 3 4 5 5 10 15 20 30 40 60 60 61 Season Spring 875 3 4 5 5 10 15 20 30 40 60 60 61 Season Summer 992 2 3 5 5 10 15 20 30 40 45 60 61 Season Fall 751 3 4 5 5 10 12 20 30 30 40 48 61 Asthma No 3274 3 4 5 5 10 15 20 30 32 45 60 61 Asthma Yes 257 3 4 5 5 10 15 20 40 50 60 60 61 Angina No 3445 3 4 5 5 10 15 20 30 35 50 60 61 Angina Yes 84 3 4 5 5 10 15 15 30 . 30 40 45 45 Bronchitis/Emphysema No 3379 3 4 5 5 10 . 15 20 30 35 50 60 61 Bronchitis/Emphysema Yes 151 3 4 5 5 10 15 20 30 40 48 60 61 NOTE: A value of 61 for number of minutes signifies that more than 60 minutes were spent. N = doer sample size. Percentiles are the of doers below or to a given number of minutes. ource: sana and Kleoeis, 19 6.

Table 15-22. Time (minutes) Spent in the Shower Room Immediately After Showering by the Number of Respondents Minutes/Shower Total N *-* 0-0 0-10 10-20 20-30 30-40 40-50 50-60 61-61 Overall 3594 61 241 2561 509 138 24 28 27 5 GK\1der ale 1720 22 113 1316 207 46 5 4 6 1 Female 1872 3.9 1?8 1243 3Q2 9.2 1.9 24 2.1 1 Refused 2 2
Age (years) 64 9 37 7 3

1 1

1-4 41 5 31 3 1

1

5-11 140 3 9 110 14 3

1

12-17 270 1 17 206 29 10 3 2 1 1 18-64 2650 31 171 1897 388 99 19 18 23 4 >64 429 20 30 280 68 22 2 6 1

Race White 2911 39 189 2074 430 110 2.0 23 21 Black 349 § 23 254 42 17 2 Asian 64 7 jr 2

1

Some Others 65 3 7 3 3 1

His£anic 162 6 11 118 19 4 1 1 ?

Re sed 43 5 4 29 3 2 *

Hispanic 3269 48 216 2328 470 130 23 26 23 No Yes 277 8 19 200 35 § 1 ? 1 H 1 11 .. 4 22 * * * *

EIJlployment 439 4 28 336 48 14 3 4 2 ?* Full Time 1838 20 109 1332 267 71 12 11 16 .. Part Time 328 5 21 223 55 13 4 4 3

NokiEmP,loyed 967 29 81 655 138 39 Re sea 22 3 2 15 1 1 515 11 38 390 51 15 4 2 1 < fo% H 11'80 16 6 1 1 Hi8ti S oo raduate 37 6 7 13 1 < ollege 772 11 56 536 118 33 7 4 5 ? Graduate 576 3 28 426 86 19 § 3 3 Post raduate 392 5 33 283 46 18 4 3

Census Region 828 6 61 603 116 20 6 8 8

Northeast lf.f6 29 5 P5

out 58 10 3 West 764 10 67 537 104 31 3 2 8 2 eekdaY. 2481 43 165 1784 342 88 20 16 19 4 Weekena 1113 18 76 777 167 50 4 12 8 1 Season 13 4 Winter 941 11 50 678 138 36 9 2 Spring 889 13 56 636 125 37 4 8 9 1 Summer 1003 25 92 691 138 39 5 5 7 1 Fall 761 12 43 556 108 26 2 6 7 1 Asthma No 3312 52 225 2374 465 123 19 24 26 4 2N 2 14 178 42 1.5 3 1 1 7 9 2 1 Awn a 52 233 2495 132 2,.4 27 2J es 3 5 55 5 1 DK 22 6 3 11 1 1 * * *

Bronchitis/Emphysema 3419 53 226 2446 482 131 23 27 26 No Yes 154 2 12 104 26 l 1 1 1 DK 21 6 3 11 1 *

NOTE:

Signifies missing data. DK= respondents answered don't know. Refused = respondents refused to answer. N = doer sample size in specified range of number o minutes spent. A value of 61 for number of minutes signifies that more than 60 minutes . Source: TsanQ and Klepeis, 1996

Table 15-23. Number of Minutes Spent in the Shower Room Immediately After Showering (minutes/shower) Percentiles Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 3533 0 0 0 1 3 5 10 20 30 40 50 61 Gender Male 1698 0 0 0 1 3 5 10 15 20 30 30 61 Gender Female 1833 0 0 0 1 3 5 12 20 30 45 60 61 Age (years) 1-4 41 0 0 0 0 1 5 10 15 20 45 45 45 Age (years) 5-11 137 0 0 0 1 2 5 10 15 20 30 30 60 Age (years) 12-17 2619 0 0 0 1 3 5 10 20 30 40 52 61 Age (years) 18-64 2619 0 0 0 1 3 5 10 20 30 40 52 61 Age (years) >64 409 0 0 0 1 4 5 10 20 30 35 45 60 Race White 2872 0 0 0 1 3 5 10 20 30 40 50 61 Race Black 341 0 0 0 1 3 5 10 20 25 30 45 60 Race Asian 64 0 0 0 0 2 5 10 15 20 30 60 60 Race Some Others 62 0 0 0 0 3 5 10 30 35 45 52 52 Race Hispanic 156 0 0 0 1 3 5 10 20 25 40 60 60 Hispanic No 3221 0 0 0 1 3 5 10 20 30 40 50 61 Hispanic Yes 269 0 0 0 1 3 5 10 20 25 45 60 60 Employment Full Time 1818 0 0 0 1 3 5 10 20 30 35 50 60 Employment Part Time 323 0 0 0 1 3 5 10 20 30 45 50 60 Employment Not Employed 938 0 0 0 1 3 5 10 20 30 45 60 61 Education < High School 283 0 0 0 1 3 5 15 20 30 45 45 61 Education High School Graduate 1025 0 0 0 1 3 5 10 20 30 45 60 61 Education <College 761 0 0 0 1 3 5 10 20 30 35 50 61 Education College Graduate 573 0 0 1 1 3 5 10 20 30 35 45 60 Education Post Graduate 387 0 0 0 1 2 .5 10 20 30 30 45 60 Census Region Northeast 822 0 0 0 1 3 5 10 20 25 40 50 60 Census Region Midwest 737 0 0 0 1 3 5 10 20 30 35 45 60 Census Region South 1220 0 0 0 1 3 5 10 20 30 40 45 61 Census Region West 754 0 0 0 1 2 5 10 20 30 30 60 61 Day of Week Weekday 2438 0 0 0 1 3 5 10 20 30 40 50 61 Day of Week Weekend 1095 0 0 0 1 3 5 10 20 30 40 50 61 Season Winter 930 0 *o 0 1 4 5 10 20 30 40 45 61 Season Spring 876 0 0 0 1 2 5 10 20 30 45 60 61 Season Summer 978 0 0 0 1 3 5 10 20 30 30 50 61 Season Fall 749 0 0 0 1 3 5 10 20 25 40 53 61 Asthma No 3260 0 0 0 1 3 5 10 20 30 38 50 61 Asthma Yes 259 0 0 0 1 3 5 13 20 30 40 45 61 Angina No 3429 0 0 0 1 3 5 10 20 30 40 50 61 Angina Yes 88 0 0 0 2 3 8.5 15 20 30 30 45 45 Bronchitis/Emphysema No 3366 0 0 0 1 3 5 10 20 30 40 50 61 Bronchitis/Emphysema Yes 152 0 0 0 1 2.5 5 10 20 30 30 45 60 NOTE: N = doer samP,le size. Percentiles are the percentage of doers below or equal to a given number of minutes. A value of 61 for number of minutes that more than 60 minutes were spent. Source: Tsang and epeis,1996 Table 15-24. Number of Baths Given or Taken in One Dav bv Number of Resoondents Number of Baths/Dav Total N 1 2 3 4 5 6 7 10 11 15 DK Overall 649 459 144 20 9 4 2 1 1 1 3 5 Gender * * *

Male 159 117 33 5 1 1 1 1 Female 490 342 111 15 8 4 1 1 1 2 5 !\ge (years) 9 8 1 * * * * * * * *

491 1fl 2.0 1 ? 1 1 1 r 2 >6 149 3 Race *

364 13 7 ? 1 1 ? § ac 68 § 1 1 1 Asian 12 5 5 1 * *

1

Some Others 12 7 4 1 * * * * * *

26 10 113 1 * ? * * * * *

e use 6 5 * * * * * *

Hispanic 6.Poo 430 127 19 2 ? 1 1 1 i § 21 16 1 ? DK 6 5 1 * * * * * *

Refused 3 3 * ** * * * * * *

t=:mployment 1 1 * * * * * * * * *

Full Time 283 183 76 12 5 * ? 1 1 1 1 1 Nartlrimfc 76 i167 17 .1 1 1 *

at mJ?oyed 287 5.1 l * * * * ? 1 Refusea 2 2 * * *

t=:ducation 4 4 * * * * * * * * * * < High School 96 66 19 3 2 ? * * *

1 3 School Graduate 235 167 54 8 2 1 1 * * ? < 2 ? 1

1 1 Co lee,e raduate 2

1

Post raduate 49 42 5 1 * * *

1

Census Region 137 100 25 3 4 1 1 *

1 * ? Northeast Midwest 151 116 29 4 1

1

South 255 164 70 9 2 3 1 1

2 West 106 79 20 4 2 * *

1 Dad; of Week W ekdaY. 415 299 89 10 4 2 2 1 1 1 2 4 Weekena 234 160 55 10 5 2 *

1 1 Season * * *

Winter 178 124 37 10 1 1 2 §Pring 160 126 27 4 1

1 *

1 ummer 174 112 49 4 3 1 1 1 * ? 1 Fall 137 97 31 2 4 1

1 1 ma 596 424 129 19 7 1 ? 1 1 1 § Yes 52 34 1.5 1 ? DK 1 1 * * * * * *

Angina 620 435 141 19 1 ? 1 1 1 4 No Yes 26 22 2 1 1 DK 3 2 1 * * * * * *

Bronchitis/Emphysema 610 429 137 z.o 1 ? 1 1 1 2 4 No 6R5 36 27 I

1 1 3 3 * * * * * *

NOTE:

Signifies missing data; Dk= respondents answered don't know; Source: Tsano and Kleneis 1996 N = sample size; Refused = respondents refused to answer.
Table 15-25. Total Time Spent Taking or Givina a Bath by the Number of Respondents Minutes/Bath Total N *-* 0-10 10-20 20-30 30-40 40-50 50-60 61-61 Overall 649 18 153 237 128 27 29 36 21 Gender Male 159 4 48 59 23 8 4 7 6 Female 490 14 105 178 105 19 25 29 15 Age (years) 9 2 2 4 1 * * *
18-64 491 6 105 174 w 22 24 351 \8 > 64 149 10 46 59 5 5 Race 11 124 185 \6 1g9 2gi 1J lac 4 16 35 Asian 12

2 6 3 1 * *

Some Others 12

2 3 5 1 *

1 266 1 8 3 1 1" 2 1 1 Hispanic 600 16 136 224 120 2p 2l 33 18 40 1 15 10 6 3 3 DK 6 1 2 ?

1 *

Refused 3 1 1 1 * * *

Erpployment 1 * *

1 * * *

Full Time 283 4 58 107 64 12 12 19 7 *NartTimfc 76 26 15 5 1 2

at EmP,oyed 287 104 18 \0 \6 \5 13 Refuse a 2 1 *

1 4 1

2 1 . . . * < High School 96 7 15 35 16 3 6 7 7 School Graduate 235 6 57 85 51 13 5 11 7 < 1 53 4 11 y Co raduate 44 5 5 Post raduate 49 . 18 18 8 2 2 1 Census Region Northeast 137 5 43 36 31 6 7 6 3 Midwest 151 2 42 67 26 3 3 5 3 South 255 .9 42 87 55 16 14 21 11 West 106 2 26 47 16 2 5 4 4 eekdaY. 415 12 90 161 84 11 23 23 11 Weekena 234 6 63 76 44 16 6 13 10 Season Wi11ter 178 5 44 63 33 9 11 9 4 §pnng 160 6 39 60 27 9 7 6 6 um mer 174 3 43 62 34 7 4 14 7 Fall 137 4 27 52 34 2 7 7 4 Asthma No 596 16 144 218 114 26 28 33 17 Yes 52 1 1.9 1.4 1 1 3 4 DK 1 1 . . . 620 14 147 226 124 25 28 35 2.1 Yes 26 3 10 3 2 1 1 DK 3 1 1 1 * . * . Bronchitis/Emphysema No 610 15 150 218 119 26 26 35 21 36 2 17 1 1 . 3 1. 2 . NOTE:

Signifies missing data. Dk= respondents answered don't know. Refused = re1rondents refused to answer. N = doer sample size in a specified range of number of minutes spent. A value of 61 for number o minutes signifies that more than 60 minutes were spent. Source: Tsana and Kleoeis 1996 Table 15-26. Number of Minutes Spent Giving and Taking the Bath(s) (minutes/bath\ Percentiles Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 631 2 5 5 10 15 20 30 45 60 61 61 61 Gender Male 155 1 4 5 6 10 15 30 45 60 61 61 61 Gender Female 476 3 5 5 10 15 20 30 45 60 61 61 61 Age (years) 18-64 485 2 5 5 10 15 20 30 60 60 61 61 61 Age (years) >64 139 3 5 5 5 10 15 20 40 60 61 61 61 Race White 476 1 4 5 10 10 20 30 45 60 61. 61 61 Race Black 102 5 5 9 10 15 22.5 40 60 61 61 61 61 Race Asian 12 10 10 10 10 15 20 27.5 30 40 40 40 40 Race Some Others 12 5 5 5 10 15 27.5 30 40 61 61 61 61 Race Hispanic 25 2 2 5 5 10 20 45 61 61 61 61 61 Hispanic No 584 2 5 5 10 15 20 30 45 60 61 61 61 Hispanic Yes 39 2 2 5 5 10 20 30 60 61 61 61 61 Employment Full Time 279 1 4 5 10 15 20 30 45 60 61 61 61 Employment Part Time 75 3 4 5 10 10 20 30 35 40 60 60 60 Employment Not Employed 275 2 5 5 10 10 20 30 60 60 61 61 61 Education < High School 89 1 5 10 10 15 20 35 60 61 61 61 61 Education High School Graduate 229 5 5 5 10 12 20 30 45 60 61 61 61 Education <College 159 1 2 5 6 10 20 30 45 60 61 61 61 Education College Graduate 102 5 5 8 10 15 20 30 45 60 60 60 61 Education Post Graduate 49 1 1 5 5 10 15 25 40 45 60 60 60 Census Region Northeast 132 1 5 5 6 10 15 30 45 60 61 61 61 Census Region Midwest 149 2 4 5 7 10 20 30 30 60 61 61 61 Census Region South 246 3 5 10 10 15 20 35 60 60 61 61 61 Census Region West 104 5 5 5 10 11 20 30 45 60 61 61 61 Day of Week Weekday 403 2 5 5 10. 15 20 30 45 60 61 61 61 Day of Week Weekend 228 4 5 5 10 10 20 30 60 60 61 61 61 Season Winter 173 2 5 5 10 10 20 30 45 60 61 61 61 Season Spring 154 1 3 5 10 10 20 30 45 60 61 61 61 Season Summer* 171 5 5 5 10 10 20 30 60 60 61 61 61 Season Fall 133 4 5 8 10 15 20 30 45 60 61. 61 61 Asthma No 580 2 5 5 10 12 20 30 45 60 61 61 61 Asthma Yes 51 4 5 5 10 15 20 30 60 61 61 61 61 Angina No 606 2 5 5 10 15 20 30 45 60 61 61 61 Angina Yes 23 5 5 5 5 10 15 30 40 45 60 60 60 Bronchitis/Emphysema No 595 2 5 5 10 10 20 30 45 60 61 61 61 Bronchitis/Emphysema Yes 34 5 5 8 15 15 20 30 45 45 60 60 60 NOTE: N = doer sample size. Percentiles are the percentage of doers below or equal to a given number of minutes. A value of 61 for number of minutes that more than 60 minutes were spent. Source: Tsana and leoeis 1996 Table 15-27. Time Soent in the Bathroom Immediately After the Bath(s) by the Number of Respondents Minutes/Bath Total N *

0-0 0-10 10-20 20-30 30-40 40-50 50-60 61-61 Overall 649 25 85 422 74 23 7 6 5 2 169 ai -1'k a *

ae emale 5 2 Age (years) 38j26 * * * *

194 j r § ? >6 R!e ? l =r 361.f § Asian l 1 *

Spme Others * * * * * * * * *

l 1 1 * *

e use 64000 2,5 7-f 329a° 711 20 ? § 1 es

1 1 *

l * * * * *

EIJlployment * * * * * * *

i l *

art 1m *

ohl mgfoyed 1.8 4 § ? Re se 1 1 Equcation 4 1

2 1 * * * * * < r u i

i ? c oo raduate <

Co raduate

Post raduate 49 2 8 32 6 1 * *

Region 8 *

1

c;irtheast 1d:fhest 1 1

ut t ? est 1l ja 16 § § 1 ee aY, Wee enel 7 Sison u 1g2J ! ? inter 110

Fall 5 19 94 14 2

1 2

5516 214 388 69 21 ? l § ? 3.4 t ? * *

Aia 6£o0 13 Bf 7f 2f § § 1 ? 3 1 *

63W 2i v 4J l § ? 3 *

Note:

Si9nifies missing data. Dk= respondents answered don't know. Refused = respondents refused to answer. N = doer sample size in specified range of number of minutes spent. A value of 61 for number of minutes signifies that more than 60 minutes were spent. . Source: Tsana and Kleoeis 1996 Table 15-28. Number of Minutes Spent in the Bathroom Immediately After the Bath(s) (minutes/bath) Percentiles Category

Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 624 0 0 0 0 2 5 10 20 30 45 55 61 Gender Male 153 0 0 0 0 2 5 10 12 20 30 35 45 Gender Female 471 0 0 0 0 2 5 10 20 30 45 60 61 Age (years) 18-64 484 0 0 0 0 2 5 10 15 25 40 50 61 Age (years) > 64 133 0 0 0 1 5 10 15 30 35 55 60 60 Race White 465 0 0 0 0 2 5 10 18 30 45 58 61 Race Black 104 0 0 0 0 2 5 10 20 30 40 45 45 Race Asian 12 0 0 0 0 2 5 7.5 10 20 20 20 20 Race Some Others 12 0 0 0 0 0 3 7.5 10 15 15 15 15 Race Hispanic 26 0 0 0 0 1 5 10 25 25 61 61 61 Hispanic No 575 0 0 0 0 2 5 10 20 30 40 50 61 Hispanic Yes 40 0 0 0 0 1 5 10 22.5 25 61 61 61 Employment Full Time 277 0 0 0 0 2 5 10 15 20 30 30 45 Employment Part Time 75 0 0 0 0 3 5 10 15 25 35 40 40 Employment Not Employed 269 0 0 0 0 2 5 10 25 35 58 60 61 Education < High School 86 0 0 0 0 5 10 15 30 35 61 61 61 Education High School Graduate 229 0 0 0 0 2 5 10 15 30 40 45 58 Education <College 159 0 0 0 0 2 5 10 15 30 45 60 60 Education College Graduate 100 0 0 0 0 1.5 5 10 19 25 30 37.5 45 Education Post Graduate 47 0 0 0 0 1 5 10 15 20 30 30 30 Census Region Northeast 129 0 0 0 0 2 5 10 20 30 30 30 60 Census Region Midwest 146 0 0 0 0 2 5 10 15 25 50 60 60 Census Region South 246 0 0 0 0 3 5 10 20 30 45 55 61 Census Region West 103 o. 0 0 0 1 5 10 20 20 30 45 58 Day of Week Weekday .398 0. 0 0 0 2 5 10 18 30 40 50 61 Day of Week Weekend 226 0 0 0 0 3 5 10 20 30 45 60 61 Season Winter 175 0 0 0 1 3 5 10 20 30 58 61 61 Season Spring 152 0 0 0 0 2 5 10 20 30 40 45 60 Season Summer 165 0 0 0 0 2 5 10 15 20 30 45 50 Season Fall 132 0 0 0 0 2 5 10 15 20 45 55 60 Asthma No ' 572 0 0 0 0 2 5 10 20 30 45 58 61 Asthma Yes 51 0 0 0 0 1 5 10 15 30 30 45 45 Angina No 597 0 0 0 0 2 5 10 20 30 45 58 61 Angina Yes 24 0 0 0 1 5 5 10 15 30 55 55 55 Bronchitis/Emphysema No 588 0 0 0 0 2 5 10 20 30 45 58 61 Bronchitis/Emohysema Yes 33 0 0 0 0 2 5 10 30 40 45 45 45 NOTE: N = doer sample size. Percentiles are the percentage of doers below or equal to a given number of minutes. A value of 61 for number of minutes more than 60 minutes were spent. Source: Tsana and leoeis 1996 Table 15-29. Total Time Spent Altoqether in the Shower or Bathtub by the Number of Respondents Minutes/Bath Total .. 0-0 0-10 10-20 20-30 30-40 40-50 50-60 70-80 80-90 90-100 100-110 110-120 121-121 N Overall 4290 38 5 1903 1577 548 46 65 67 3 6 2 1 21 8 ae 8 4 *18{f1 1 1 1 3.0 § . Age (years) 86 § 1 . 11 4 . . . . . 1 1-4 2 7 1 1 1 . 4 ? . t ? ? 1 t 1 . rn j 3f13 381 365 . . . \3 9 >6 583 . . . . 2f 1 l'i l 3f tt ? 1 16 Asian 1tjo j 1 1 . 1 Others . . . . . . . . . ? 1 . 1 . e use 53 . * . . 33839:f 35 1 V24s4 4Jlo6 51 6? ? 1 1 § es l t4 180 . . 1 . . . 1 . . . . . . Erpployment . 1!t * ? 1 1J art 1m . . . . o}J mP,foyed 146 1.3 1l ?,.2 . . . 1 1 e sea 15 10 6 . . . 1 Ei;!ucation 775 6 . 200 317 175 10 26 24 3 ? 1 7 1 < ;t4 1 u1 66 7 1 c oo raduate v . . . . < . 1 . . lee,e raduate l 7 . . . 5 . est raduate 4 2 3 3 . . . 2 2 927 7 . 436 328 106 11 14 12 1 2 1 . 6 o eas OCP,i'ffiest 1(\3 l 1 . est ? . 1 t Wee en b354f \0/98 yg ? 1 w 14 1 . . . 1riter 194 1 . m er . Fall 856 4 405 323 86 9 11 12 1 1 2 2 3946 35 § Vfl 11'4s5 502 38 6£i l ? 1 19 6 3f! t

4:33 § . . . ? ? 3y4 § 53,P i5 v 616 9 ? 1 41 § . . . . . . . 5¥ 4j 6( l ? 1 I * . . . Note:

Signifies missing data. DK = respondents answered "don't know". Refused = respondents refused to answer. N = doer sample size in specified range of number of minutes spent. A value of "121" for number of minutes signifies that more than 120 minutes were spent. Source: Tsana and Kleoeis 1996 Table 15-30. Total Number of Minutes Spent Altogether in the Shower or Bathtub (minutes/bath\ Percentiles Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 4252 3 4 5 5 10 15 20 30 35 60 60 121 Gender Male 1926 3 4 5 5 10 15 20 30 30 60 60 121 Gender Female . 2325 3 4 5 5 10 15 20 30 40 60 75 121 Age (years) 1-4 198 1 5 5 10 15 20 30 45 60 120 120 120 Age (years) 5-11 263 4 5 5 10 13 20 30 30 60 90 120 121 Age (years) 12-17 239 4 4 5 7 10 15 30 30 45 60 60 120 Age (years) 18-64 2904 3 4 5 5 10 13.5 20\ 30 30 50 60 121 Age (years) > 64 567 2 3 5 5 10 15 20 30 30 45 60 120 Race White 3425 3 4 5 5 10 15 20 30 30 60 60 121 Race Black 446 4 4 5 6 10 15 25 30 45 75 120 121 Race Asian 74 5 5 5 7 10 15 15 30 30 60 90 90 Race Some Others 78 5 5 5 7 10 15 30 30 45 60 60 60 Race Hispanic 178 1 3 5 7 10 15 20 30 45 90 100 120 Hispanic No 3861 3 4 5 5 10 15 20 30 35 60 60 121 Hispanic Yes 328 1 3 5 5 10 15 20 30 45 60 90 120 Employment Full Time 1974 3 4. 5 5 10 10 20 30 30 45 60 121 Employment Part Time 395 3 3 5 5 10 15 20 30 30 45 60 60 Employment Not Employed 1161 2 3 5 5 10 15 20 30 35 60 '60 121 Education < High School 376 1 4 5 5 10 15 25 30 45 60 90 121 Education High School Graduate 1242 3 4 5 5 10 15 20 30 30 60 60 121 Education <College 862 3 4 5 5 10 15 20 30 30 45 60 120 Education College Graduate 554 3 3 5 5 10 10 15 30 30 45 90 120 Education Post Graduate 449 3 4 5 5 8 10 15 20 30 45 60 121 Census Region Northeast 920 4 4 5 5 10 15 20 30 35 60 100 121 Census Region Midwest 947 3 4 5 5 10 15 20 . 30 30 45 60 120 Census Region South 1497 3 4 5 5 10 15 20 30 45 60 75 121 Census Region West 888 3 3 5 5 10 15 20 30 30 45 60 121 Day of Week Weekday 2858 3 4 5 5 10 15 20 30 30 60 60 121 Day of Week Weekend 1394 3 4 5 5 10 15 20 30 40 60 75 121 Season Winter 1116 3 4 5 5 10 15 20 30 35 60 60 121 Season Spring 1130 3 4 5 5 10 15 20 30 40 60 90 121 Season Summer 1154 3* 4 5 5 10 15 20 30 40 60 60 121 Season Fall 852 3 5 5 5 10 15 20 30 30 60 60 121 Asthma No 3911 3 4 5 5 10 15 20 30 30. 60 60 121 Asthma Yes 325 3 4 5 5 10 15 20 30 45 60 120 121 Angina No 4117 3 4 5 5 10 15 20 30 35 60 60 121 Angina Yes 111 3 4 5 5 10 15 20 30 30 45 45 60 Bronchitis/Emphysema No 4025 3 4 5 5 10 15 20 30 30 60 60 121 Bronchitis/Emphysema Yes 205 1 3 5 5 10 15 20 30 45 60 120 121 Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent. N =doer sample size. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996. ' --
Table 15-31. Time Spent in the Bathroom Immediately FollowinQ a Shower or Bath by the Number of Respondents Minutes/Shower or Bath Total N *-* 0-0 0-10 10-20 20-30 30-40 40-50 50-60 70-80 80-90 110-120 121-121 Qverall 4290 108 348 2770 713 250 20 32 35 1 2 7 4 HB 16§'3 5 £4 £9 *
e J ae 1.5 1 ? Age (years) 86 $ 328 Ji\ 9

1 1 * *

1 1-4 1 * *

3 11 *

1

235 * * * >6 583 3 2 1 1 y 34'!f:f 2/91 2tf55 56930 1jl54 \5 1 ? ? 8sian 1 1 * * *

Spme Others 1 * * * * * * * * * * * * * * *

33839:f 9§5 6(65 41-l 119 3.2 3z2 1 1 9 es 7 ?

1

1 1

5 * * *

Erpployment }$t 8 t 3 * *

36 1 1 art 1m !2 .6

1 1 ' 3 4 21 5 2

EcJucation 775 14 114 82 20 3 7 3 *

1 * < I ¥ * ? J 1 c oo raduate 1 < ollegt,

Co lee:,e raduate * *

Post raduate 453 7 29 290 89 31 1 2 3 *

1

Region 927 20 69 614 161 49 3 2 {6 *

1 2 art east i .. * § 1 est 1 ? rn 1 1i9 rn 1 ee en rnK i \o

1 1 111 er

1 1

Fall 856 12 60 548 169 49 3 3 8 1 3

33#6. 101 3{16 2540 673 236 18 30 32 1 1 2 3j 1.4 ? ? * ? Alna 9§9 6?1 2,p 3.2 3i4 1 ? ? 25 * * * * * * \8 3*5 26:?33 6*4 119 311 3;f 1 1 J \4

Note:

Signifies missing data. A value of "121" for number of minutes signifies that more than 120 minutes were spent. DK= respondents answered "don't know". Refused = respondents refused to answer. N = doer sample size in a specified range or number of minutes spent.

Source: Tsana and Kleoeis Table 15-32. Number of Minutes Spent in the Bathroom lmmediatelv Following a Shower or Bath (minutes/bath) Percentiles Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 4182 0 0 0 1 4 5 15 20 30 40 60 121 Gender Male 1897 0 0 0 1 3 5 10 15 20 30 40 121 Gender Female 2284 0 0 0 1 5 10 15 30 30 45 60 121 Age (years) 1-4 196 0 0 0 0 0 2 5 10 15 20 35 45 Age (years) 5-11 260 0 0 0 0 2 5 10 15 15 30 35 120 Age (years) 12-17 238 0 0 0 2 5 5 10 20 30 45 45 60 Age (years) 18-64 2866 0 0 0 1 5 10 15 20 30 45 60 121 Age (years) >64 548 0 0 0 1 4 10 15 20 30 40 60 120 Race White 3372 0 0 0 1 4 5 15 20 30 40 60 121 Race Black 438 0 0 0 0 4 6 15 30 30 60 60 60 Race Asian 74 0 0 0 0 2 5 10 20 30 35 45 45 Race Some Others 76 0 0 0 1 5 10 15 20 25 30 60 60 Race Hispanic 176 0 0 1 1 3 5 10 20 30 30 30 60 Hispanic No 3797 0 0 0 1 4 5 15 20 30 45 60 121 Hispanic Yes 325 0 0 0 1 3 5 10 20 30 30 30 60 Employment Full Time 1949 0 0 0 1 5 10 15 20 30 40 60 121 Employment Part Time 392 0 0 0 2 5 10 15 25 30 45 60 120 Employment Not Employed 1129 0 0 0 1 5 10 15 20 30 45 60 121 Education < High School 358 0 0 0 1 5 10 15 30 30 60 90 121 Education High School Graduate 1220 0 0 0 1 5 10 15 25 30 45 60 121 Education <College 847 0 0 0 1 5 10 15 20 30 30 60 121 Education College Graduate 550 0 0 1 2 5 10 15 20 30 45 45 60 Education Post Graduate 446 0 0 0 1 5 8 15 20 30 30 50 120 Census Region Northeast 907 0 0 0 1 5 5 10 20 30 30 45 121 Census Region Midwest 929 0 0 0 1 5 5 15 20 30 45 60 121 Census Region South 1472 0 0 0 1 3.5 5 15 20 30 40 60 121 Census Region West 874 0 0 0 1 3 5 10 20 30 45 45 60 Day of Week Weekday 2802 0 0 0 1 4 5 10 20 30 35 50 121 Day of Week Weekend 1380 0 0 0 1 4 8 15 20 30 45 60 121 Season Winter 1090 0 0 0 1 5 7 1.5 20 30 45 60 121 Season Spring 1119 0 0 0 1 3 5 10 20 30 45 50 120 Season Summer 1129 0 0 0 1 3 5 10 20 30 40 52 120 Season Fall 844 0 0 0 1 5 8 15 20 30 35 60 121 Asthma No 3845 0 0 0 1 4 5 15 20 30 40 60 121 Asthma Yes 322 0 0 0 0 3 5 10 20 30 60 90 121 Angina No 4052 0 0 0 1 4 5 15 20 30 40 60 121 Angina Yes 108 0 0 0 0 4.5 5.5 12.5 20 30 30 30 60 Bronchitis/emphysema No 3961 0 0 0 1 4 5 15 20 30 40 60 121 Bronchitis/emphysema Yes 201 0 0 0 0 4 10 10 30 30 60 88 121 Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent. N = doer sample size. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsano and Kleoeis *1996.
Table 15-33. Ranae of Number of Times Washing the Hands at Specified Dailv Frequencies bv the Number of Resoondents Number of Times/Dav Total N *-* 0"0 1-2 3-5 6-9 10-19 20-29 30+ DK* Overall 4663 38 34 311 1692 1106 892 223 178 189 '-lBg 1J18 15§94 1?99 ae l5 Re sed 2 1 Age (years) 84 . 1 15 4 1t rn r JJ2 A f f5 >64 670 8 10 163 179 38 23 . 64
314 251 'if 16 1T 181 140 r 1 23 g Some Others \2 1,9J 7 9 1p 4 4244 27 29 276 1536 1022 823 11f4 162 § 3f 1ff 7£ v ¥ 9 . Eipployment 1j 2; .

NB art 1me 11 1 31 90 5 I 2.,6 m 1568 n < c oo raduate 4 < olleg(, lee,,e laduate n* '-6 rn est ra uate 1 96 Census Region 15g 196 !I ;{hes u WP est Wee na9 \4 \\093 \V 1?63 Sl:;on . Hgt 163 1gO ti inter pnng . 1g2,'35 1Ji 2t 3f 19}4 iy 2p1. .* 6 11605 3 1161 8 Aia \CW 3j 83)1 T Vci1-. 3 8 'W34 4J 313 392 1g10 21p3 1F es DK 36 8 2 8 5 2 3 8 Note:

Signifies missing data. N = doer sample size in a specified rarige or number of minutes spent. DK= respondents answered "don't know". Refused= respondents refused to answer. Source: Tsano and Kleoeis 1996

Table 15-34. Number of Minutes Spent (at home) Workin!'.l or Bein!'.l Near Food While Fried, Grilled, or Barbequed (minutes/day) Percentiles Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 1055 0 1 2 5 10 20 30 105 121 121 121 121 Gender Male 485 0 1 2 5 10 20 30 90 121 121 121 121 Gender Female 570 0 0 2 5 10 20 30 120 121 121 121 121 Age (years) 1-4 35 0 0 2 2 5 20 30 45 60 60 60 60 Age (years) 5-11 82 0 0 0 2 5 15 30 60 90 121 121 121 Age (years) 12-17 82 0 0 2 4 10 20 45 60 90 121 121 121 Age (years) 18-64 747 0 2 3 5 10 20 40 120 121 121 121 121 Age (years) >64 96 0 1 3 5 10 20 30 60 120 121 121 121 Race White 848 0 1 2 5 10 20 30 105 121 121 121 121 Race Black 115 2 2 5 5 10 20 30 61 121 121 121 121 Race Asian 18 0 0 0 0 5 10 20 121 121 121 121 121 Race Some Others 16 5 5 5 5 12.5 20 45 121 121 121 121 121 Race Hispanic 48 0 0 5 5 15 30 60 90 121 121 121 121 Hispanic No 960 0 1 2 5 10 20 30 90 121 121 121 121 Hispanic Yes 84 0 1 2 5 10 20 60 121 121 121 121 121 Employment Full Time 506 1 2 3 5 10 20 45 121 121 121 121 121 Employment Part Time 95 0 1 2 5 10 15 40 90 121 121 121 121 Employment Not Employed 252 0 1 3 5 10 20 30 90 121 121 121 121 Education < High School 96 0 1 2 5 10 22.5 52.5 121 121 121 121 121 Education High School Graduate 318 0 2 5 5 10 20 30 120 121 121 121 121 Education <College 208 0 2 3 5 10 20 35 121 121 121 121 121 Education College Graduate 135 1 1 2 5 10 20 30 90 121 121 121 121 Education Post Graduate 83 0 2 5 5 10 15 30 60 121 121 121 121 Census Region Northeast 198 0 2 3 5 10 15 30 go 121 121 121 121 Census Region Midwest 248 0 0 4 5 10 20 30 121 121 121 121 121 Census Region South 399 0 1 2 5 10 20 40 90 121 121 121 121 Census Region West 210 0 0 2 5 7 15 30 60 121 121 121 121 Day of Week Weekday 662 0 1 3 5 10 20 30 90 121 121 121 121 Day of Week Weekend 393 0 1 2 5 10 20 30 120 121 121 121 121 Season Winter 267 0 2 2 5 10 20 30 60 121 121 121 121 Season Spring 296 0 0 3 5 10 20 45 120 121 121 121 121 Season Summer 299 0 0 3 5 10 20 30 90 121 121 121 121 Season Fall 193 0 0 2 5 10 20 30 121 121 121 121 121 Asthma No 960 0 1 2.5 5 10 20 30 90 121 121 121 121 Asthma Yes 92 0 0 2 5 15 30 60 121 121 121 121 121 Angina No 1032 0 1 2 5 10 20 30 95 121 121 121. 121 Angina Yes 19 0 0 0 5 15 30 30 121 121 121 121 121 Bronchitis/Emphysema No 1005 0 1 2 5 10 20 30 90 121 121 121 121 Bronchitis/Emphvsema Yes 47 0 0 3* 5 10 30 60 121 121 121 121 121 Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent N .= doer sample size. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996.
Table 15-35. Number of Minutes Spent (at home) Working or Being Near Open Flames Including Barbeque Flames (minutes/day) Percentiles Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 479 0 0 1 2 10 20 60 121 121 121 121 121 Gender Male 252 0 0 1 2 10 20 60 121 121 121 121 121 Gender Female 227 0 0 2 2 10 20 30 121 121 121 121 121 Age (years) 1-4 14 0 0 0 0 5 10 30 121 121 121 121 121 Age (years) 5-11 29 0 0 0 0 5 15 30 90 121 121 121 121 Age (years) 12-17 28 0 0 1 2 10 22.5 42.5 60 60 90 90 90 Age (years) 18-64 372 0 0 1 3 10 20 60 121 121 121 121 121 Age (years) :> 64 31 2 2 2 4 5 17 30 120 121 .121 121 121 Race White 407 0 0 1 2 10 20 45 121 121 121 121 121 Race Black 31 0 0 0 2 5 20 30 60 121 121 121 121 Race Asian 5 5 5 5 5 20 40 121 12.1 121 121 121 121 Race Some Others 8 10 10 10 10 11 22.5 60 121 121 121 121 121 Race Hispanic 22 2 2 3 5 5 30 60 120 121 121 121 121 Hispanic No 436 0 0 1 2 10 20 42.5 121 121 121 121 121 Hispanic Yes 36 2 2 3 5 11 60 90 121 121 121 121 121 Employment Full Time 262 0 0 1 2 10 20 60 121 121 121 121 121 Employment Part Time 44 0 0 1 4 5 15 52.5 121 121 121 121 121 Employment Not Employed 99 0 1 2 3 10 20 40 120 121 121 121 121 Education < High School 27 2 2 2 3 5 20 60 121 121 121 121 121 Education High School Graduate 130 0 0 2 3 10 20 60 121 121 121 121 121 Education <College 92 0 0 1 2 10 30 90 121 121 121 121 121 Education College Graduate 95 0 1 2 5 10 20 40 121 121 121 121 121 Education Post Graduate 55 0 0 0 2 10 20 40 121 121 121 121 121 Census Region Northeast 124 0 0 1 3 10 15 30 121 121 121 121 121 Census Region Midwest 112 0 0 2 3 10 20 45 121 121 121 121 121 Census Region South 149 0 0 1 2 5 20 60 121 121 121 121 121 Censu? Region West 94 0 0 1 2 10 20 60 121 121 121 121 121 Day of Week Weekday 284 0 0 1 3 10 15 30 121 121 121 121 121 Day of Week Weekend 195 0 0 1 2 10 30 60 121 121 121 121 121 Season Winter 142 0 0 0 2 10 20 60 121 121 121 121 121 Season Spring 115 0 1 2 3 10 20 60 120 121 121 121 121 Season Summer 137 0 0 2 3 10 20 45 121 121 121 121 121 Season Fall 85 1 1 1 3 10 20 40 121 121 121 121 121 Asthma No 443 0 0 1 2 10 20 45 121 121 121 121 121 Asthma Yes 35 0 0 3 3 15 30 120 121 121 121 121 121 Angina No 461 0 0 1 2 10 20 45 121 121 121 121 121 Angina Yes 15 2 2* 2 2 10 15 60 121 121 121 121 121 Bronchitis/Emphysema . No 461 0 0 1 2 10 20 45 121 121 121 121 121 Bronchitis/Emphysema Yes 16 3 3 3 5 12.5 37.5 106 121 121 121 121 121 Note: A value of'121" for number of minutes signifies that more than 120 minutes were spent. N = doer sample size. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996. Table 15-36. Number of Minutes Spent Working or Being Near Excessive Dust in the Air (minutes/day) Percentiles Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 679 0 2 5 7 30 121 121 121 121 121 121 121 Gender Male 341 1 2 5 8 30 121 121 121 121 121 121 121 Gender Female 338 0 2 5 5 30 121 121 121 121 121 121 121 Age (years) 1-4 22 0 0 0 2 5 75 121 121 121 121 121 121 Age (years) 5-11 50 0 0.5 2 4 15 75 121 121 121 121 121 121 Age (years) 12-17 52 0 1 2 5 5 20 120 121 121 121 121 121 Age (years) 18-64 513 2 5 5 10 30 121 121 121 121 121 121 121 Age (years) 5:> 64 38 2 2 2 5 35 105.5 121 121 121 121 121 121 Race White 556 0 2 5 8 30 121 121 121 121 121 121 121 Race Black 66 1 3 5 5 20 121 121 121 121 121 121 121 Race Asian 7 20 20 20 20 60 90 121 121 121 121 121 121 Race Some Others 15 5 5 5 10 60 120 121 121 121 121 121 121 Race Hispanic 29 3 3 5 7 20 121 121 121 121 121 121 121 Hispanic No 611 0 2 5 5 30 121 121 121 121 121 121 121 Hispanic Yes 57 0 3 3 10 30 121 121 121 121 121 121 121 Employment Full Time 368 2 5 7 15 37.5 121 121 121 121 121 121 121 Employment Part Time 66 0 2 5 5 20 120 121 121 121 121 121 121 Employment Not Employed 122 0 2 5 8 30 121 121 121 121 121 121 121 Education < High School 52 2 5 5 7 35 121 121 121 121 121 121 121 Education High School Graduate 199 0 0 5 10 30 121 121 121 121 121 121 121 Education <College 140 5 5 10 20 60 121 121 121 121 121 121 121 Educaiion College Graduate 82 1 2 5 15 30 121 121 121 121 121 121 121 Education Post Graduate 76 3 5 5 10 37.5 121 121 121 121 121 121 121 Census Region Northeast 138 0 0 5 5 20 121 121 121 121 121 121 121 Census Region Midwest 145 2 2 5 10 30 121 121 121 121 121 121 121 Census Region South 227 1 2 5 5 30 121 121 121 121 121 121 121 Census Region West 169 0 3 5 10 30 120 121 121 121 121 121 121 Day of Week Weekday 471 0 1 5 7 30 121 121 121 121 121 121 121 Day of Week Weekend 208 2 2 5 5 30 121 121 121 121 121 121 121 Season Winter 154 0 0 5 5 30 121 121 121 121 121 121 121 Season Spring 193 0 1 3 5 20 121 121 121 121 121 121 121 Season Summer 193 2 2 5 10 30 121 121 121 121 121 121 121 Season Fall 139 3 5 5 10 30 121 121 121 121 121 121 121 Asthma No 606 0 2 5 5 30 121 121 121 121 121 121 121 Asthma Yes 73 0 3 5 10 30 121 121 121 121 121 121 121 Angina No 662 0 2 5 7 30 121 121 121 121 121 121 121 Angina Yes 15 3 3 3 30 60 121 121 121 121 121 121 121 Bronchitis/Emphysema No 637 0 2 5 7 30 121 121 121 121 121 121 121 Bronchitis/Emphvsema Yes 41 0 0 5 5 30 121 121 121 121 121 121 121 Note: A valueof "121" for number of minutes signifies that more than 120 minutes were spent. N = doer sample size. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996.
Table 15-37. Range of the Number of Times an Automobile or Motor Vehicle was Started in a Garage or Carport at Specified Daily Frequencies by the Number of Respondents Times/day Total N 1-2 3-5 6-9 10+ Dk Overall 2009 1321 559 78 17 34 Gender Male 939 588 290 40 7 14 Female 1070 733 269 38 10 20 Age(years) 20 13 2 1 1 1-t U6 2 i 5-1 6 2 12-17 145 86 42 12 1 4 18-64 1287 840 367 50 12 18 > 64 296 221 60 7 1 7 Race White 1763 1164 486 69 1] 27 Black 110 70 r6 4 § Asian 46 34 ?

Some Others 24 19 5 *

His£anic 55 26 24 * ? Re sect 11 8 3

1879 1239 519 74 1] 30 !Sf<S \12' 698 335 1

1 Refused 7 5 2 * *

EIJlployment 398 241 127 20 3 7 Full Time 919 610 253 35 9 12 Part Time 149 93 48 4 2 2 No}uEmgloyed 536 372 129 \9 \3 Re se 7 5 2 Equcation 427 262 134 21 4 6 < High School 84 59 17 2 1 5 Hi81i School Graduate 464 336 107 13 2 6 < allege 440 304 107 20 5 4 Graduate 201 1s°86 1g 2 7 ost raduate 159 3 6 Census Region 213 8 2 2 1dwest 360 29 2 8 South 702 430 221 27 8 16 West 477 318 132 14 5 8 eekdaY. 1383 903 386 63 11 20 Weekena 626 418 173 15 6 14 Season Winter 567 396 136 20 5 10 Spring 518 336 141 25 5 11 Summer 525 313 -178 18 6 10 Fall 399 276 104 15 1 3 Asthma No 1861 1228 5414 70 \7 32 Yes 146 92 § ? DK 2 1 1

1959 1288 545 76 1] 33 Yes 48 3.3 12 ? 1 DK 2 2

Bronchitis/Emphysema 1922 1266 532 74 1l 33 No Yes 84 54 25 4 1 DK 3 1 2 * *

Note: "*" Signifies missing data; "DK" = respondent answered don't know; Refused -the respondent refused to answer; N = doer sample size. Source: Tsano and Kleoeis 1996 Table 15-38. Range of the Number of Times Motor Vehicle Was Started with Garage Door Closed at Specified Daily Frequencies by the Number of Respondents Times/day Total N None 1-2 3-5 6-9 Dk Overall 2009 1830 99 26 2 52 Gender Male 939 860 41 15

23 Female 1070 970 58 11 2 29 l\9e (years) 20 14 1 *

5 1-4 116 1911 ?

2 5-11 15

3 12-17 145 127 9 4 1 4 18-64 1287 1184 57 18 1 27 > 64 296 265 18 2 11 Race White 1763 1616 82 22 1 42 Black 110 6 ? 1 Asian 46 4 Some Others 24 21 2 *

1 His/Ganie 55 46 ? * ? Re sed 11 11

Hispanic 1879 1714 92 23 ? 48 No 6f<S w ? ¥

1 Refused 7 7 * * *

t=:mployment 398 360 22 5 1 10 Full Time 919 840 46 13 1 19 Part Time 149 137 6 2 4 536 488 y

1.9 7 5

fducation 427 3N 223 1 10 < High School 84 7 Hi81i School Graduate 464 429 24 2

9 < ollege 440 399 24 8 1 8 Graduate ost raduate

Census Region 28r 1 3 1dwest 54 14 South 702 628 42 8

24 West 477 432 25 9

11 Dad; of Week

W ekdaY. 1383 1269 66 21 27 Weekena 626 561 33 5 2 25 Season Winter 567 509 32 9 1 16 Spring 518 470 29 3 16 Summer 525 476 23 11

15 Fall 399 375 15 3 1 5 Asthma No 1861 1696 92 23 1 49 Yes 146 132 ? ¥ 1 i DK 2 2 1959 1785 96 26 ? 50 Yes* 48 43 i * ? DK 2 2 *

Bronchitis/Emphysema 1922 1747 96 2.6 ? 51 No Yes 84 80 ¥ 1 DK 3 3 *

Note: "*" Signifies missing data; to answer. "DK" = respondents answered don't know; N = doer sample size; Refused = the respondent refused Source: Tsana and Kleoeis 1996 Table 15-39. Number of Minutes Spent at a Gas Station or Auto Repair Shop (minutes/day) Percentiles Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 967 1 2 3 4 5 6 10 30 90 121 121 121 Gender Male 552 2 2 3 4 5 7 10 30 120 121 121 121 Gender Female 414 0 1 2 3 5 5.5 10 15 30 121 121 121 Age (years) 1-4 29 0 0 0 0 5 5 10 20 60 121 121 121 Age (years) 5-11 42 2 2 2 3 5 5 10 15 15 120 120 120 Age (years) 12-17 57 1 3 3 5 5 5 10 20 30 60 121 121 Age (years) 18-64 760 1 2 3 4 5 5.5 10 30 120 121 121 121 Age (years) > 64 67 0 2 3 4 5 10 15 15 40 120 120 120 Race White 788 1 2 3 4 5 7.5 10 30 120 121 121 121 Race Black 95 0 1 2 3 5 5 10 15 15 20 120 120 Race Asian 13 2 2 2 2 5 5 10 10 10 10 10 10 Race Some Others 22 5 5 5 5 5 5 12 20 30 30 30 30 Race Hispanic 42 0 0 3 4 5 10 15 25 30 121 121 121 Hispanic No 875 1 2 3 4 5 6 10 30 120 121 121 121 Hispanic Yes 82 0 2 2 3 5 8 10 20 35 121 121 121 Employment Full Time 542 1 2 3 4 5 7 10 30 121 121 121 121 Employment Part Time 107 2* 3 4 5 5 10 10 30 120 121 121 121 Employment Not Employed 186 1 1 3 4 5 10 10 20 40 120 120 121 Education < High School 70 0 2 3 4.5 5 10 30 121 121 121 121 121 Education High School Graduate 293 1 2 3 5 5 8 15 30 121 121 121 121 Education <College 213 1 2 2 4 5 8 10 15 60 121 121 121 Education College Graduate 143 2 2 3 4 5 5 10 15 30 121 121 121 Education Post Graduate 106 1 2 3 3 5 7 10 15 35 56 90 120 Census Region Northeast 167 1 2 3 5 5 5 10 30 121 121 121 121 Census Region Midwest 246 0 2 2 3 5 8 10 30 120 121 121 121 Census Region South 348 0 1 3 4 5 6.5 10 20 45 120 121 121 Census Region West 206 2 2 3 4 5 8 10 20 70 121 121 121 Day of Week Weekday 634 1 2 3 4 5 7 10 *30 121 121 121 121 Day of Week Weekend 333 1 1 3 4 5 5 10 15 30 120 121 121 . Season Winter 236 1 1 3 4 5 6 10 20 60 121 121 121 Season Spring 232 2 2 3 5 5 7.5 15 30 120 121 121 121 Season Summer 282 0 2 3 4 5 10 10 30 120 121 121 121 Season Fall 217 1 2 2 3 5 5 10 15 35 121 121 121 Asthma No 892 1 2 3 4 5 7 10 25 90 121 121 121 Asthma Yes 74 0 2 2 3 5 5 10 30 120 121 121 121 Angina No 947 1 2 3 4 5 6 10 30 90 121 121 121 Angina Yes 17 3 3 3 4 10 10 15 15 121 121 121 121 Bronchitis/Emphysema No 920 1 2 3 4 5 7 10 25 60 121 121 121 Bronchitis/Emphysema Yes 45 2 2 2 3 5 5 15 120 120 121 121 121 Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent. N = doer sample size. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996.
Table 15-40. Number of Minutes Soent at Home While the Windows Were Left Ooen (minutes/dav) Percentiles Category* Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 1960 2 10 30 180. 360 840 1 961 961 961 961 961 961 Gender Male 893 5 10 30 180 360 840 961 961 961 961 961 961 Gender Female . 1067 2 10 30 119 360 840 961 961 961 961 961 961, Age (years) 1-4 99 0 1 10 180 180 600 961 961 961 961 961 961 Age (years) . 5-11 159 3 10 20 . 60 360 600 961 961 961 961 961 961 Age (years) 12-17 101 2 5 24 180 360 600 961 961" 961 961 961 961 Age (years) . 18-64 1282 6 16 60 180 360 840 961 961 961 961 961 961 Age (years) >64 282 1 5 30 180 360 840 961 961 961 961 961 961 Race White 1558 2 10 30 180 360 840 961 961 961 961 961 961 Race Black 208 3 10 30 180 360 840 961 961 961 961 961 961 Race Asian 47 10 10 16 180 360 . 600 961 961 961 961 961 961 Race Some Others 44 1 1 60 90 180 600 961 961 961 961 961 961 Race *Hispanic 80 2 20 30 60 360 600 961 961 961 961 961 961 Hispanic No 1775 2 10 30 180 360 840 961 961 961 961 961 961 Hispanic Yes 156 20 20 30 180 180 840 961. 961 961 961 961 961 Employment Full Time 822 5 15 30 180 360 840 961 961 961 961 961 961 Employment Part Time 190 1 7 30 60 180 840 961 961 . 961 961 961 961 Employme.nt Not Employed 576 5 10 60 180 360 840 961 961 961 961 961 961 Education < High School 163 1 6 30 90 360 840 961 961 961 961 961 961 Education High School Graduate 542 2 10 60 180 360 840 961 961 961 961 961 961 Education <College 408 5 15 30 119 360 840 961 961 961 961 961 961 Education College Graduate 247 15 15 60 100 360 840 961 961 961 961 961 961 Education Post Graduate 216 10 19 30 180 360 840 961 961 961 961 961 961 Census Region Northeast 498 3 10 30 119 360 840 961 961 961 961 961 961 Census Region Midwest 390 5 10 60 180 360 840 961 961 961 961 961 961 Census Region South 494 1 6 30 90 360 600 961 961 961 961 961 961 Census Region West 578 2 10' 30 180 360 840 961 961 961 961 961 961 Day of Week Weekday 1285 3 10 30 180 360 840 961 961 961 961 961 961 Day of Week Weekend 675 2 10 30 119 360 840 961 961 961 961 961 961 Season Winter 308 1 2 10 24 180 360 961 961 961 961 961 961 Season Spring 661 10 20 60 180 360 600 961 961 961 961 961 961 Season Summer 680 10 30 180 180 600 961 961 961 961 961 961 961 Season-Fall 311 3 5 30 60 180 600 961 961 961 961 961 961 Asthma No 1809 2 10 30 180 360 840 961 961 961 961 961 . 961 Asthma Yes 145 5 10 60 118 360 840 961 961 961 961 961 961 Angina No 1902 3 10 30 180 360 840 961 961 961 961 961 961 Angina Yes 49 1 1 24 30 180 961 961 961 961 961 961 961 Bronchitis/Emphysema No 1850 2 10 30 180 360 840 961 961 961 961 961 961 Bronchitis/Emphysema Yes 100 5 15 35 180 480 961 961 961 961 961 961 961 Note: Values of "180", "360", "600","840" and "961" fornumber of minutes signify that 2-4 hours, 4-8 hours, 8-12 hours, 12-16 hours, and more than 16 hours, respectively, were spent. N = doer sample size. Percentiles are the percentage of doers below or equal to a siven number of minutes. ource: Tsano and Kleoeis 1996. Table 15-41. Number of Minutes the Outside Door Was Left Ooen While at Home (minutes/day) Percentiles Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 1170 0 1 . 5 10 60 180 600 600 721 721 721 721 Gender Male 505 0 1 3 10 60 180 600 600 721 721 721 721 Gender Female 665 1 1 5 10 60 180 600 600 721 721 721 721 Age (years) 1-4 68 0 0 2 10 30 180 360 721 721 721 721 721 Age (years) 5-11 109 0 1 3 10 60 180 600 600 600 721 721 721 Age (years) 12-17 79 0 1 3 5 60 180 360 600 721 721 721 721 Age (years) 18-64 718 1 1 3 10 60 180 600 600 721 721 721 721 Age (years) >64 180 1 1 10 20 180 360 600 721 721 721 721 721 Race White 968 0 1 5 10 60 180 600 600 721 721 721 721 Race Black 100 1 2.5 5.5. 13 60 180 600 600 600 660.5 721 721 Race Asian 23 1 1 2 60 180 360 600 600 721 721 721 721 Race Some Others 22 1 1 1 15 30 180 600 600 721 721 721 721 Race Hispanic 45 0 0 5 5 45 180 360 600 600 721 721 721 Hispanic No 1073 0 1 3 10 60 180 600 600 721 721 721 721 Hispanic Yes 81 0 1 5 10 45 180 360 600 600 721 721 721 Employment Full Time 451 1 1 3 10 60 180 600 600 721 721 721 721 Employment Part Time 93 0 3 5 15 60 180 600 600 721 721 721 721 Employment Not Employed 362 1 1 5 10 60 360 600 600 721 721 721 721 Education High School 96 1 1 2 11 75 360 600 600 721 721 721 721 Education High School Graduate 309 '1 3 5 10 60 180 600 600 721 721 721 721 Education <College 225 0 1 3 10 60 180 600 600 721 721 721 721 Education College Graduate 150 0 0.5 1 15 60 180 600 600 721 721 721 721 Education Post Graduate 124 2 2 3 5 30 180 600. 600 721 721 721 721 Census Region Northeast 223 1 2 5 10 90 180 600 600 721 721 721 721 Census Region Midwest 221 0 0 2 10 60 180 600 600 721 721 721 721 Census Region South 361 1 1 5 10 60 180 360 600 600 721 721 721 Census Region West 365 0 1 5 15 60 180 600 600 721 721 721 721 Day of Week Weekday 732 0 1 5 10 60 180 600 600 721 721 721 721 Day of Week Weekend 438 1 1 5 10 60 180 600 600 721 721 721 721 Season Winter 184 0 0 2 3 10 60 180 . 600 600 600 600 600 Season Spring 407 1 1 5 20 180 360 600 600 721 721 721 721 Season Summer 385 0 2 10 30 180 360 600 721 721 721 721 721 Season Fall 194 1 1 2 10 30 180 360 600 600 600 600 600 Asthma No 1072 0 1 5 10 60 180 600 600 721 721 721 721 Asthma Yes 97 1 1 3 6 30 180 600 600 721 721 721 721 Angina No 1133 0 1 5 10 60 180 600 600 721 721 721 721 Angina Yes 36 1 1 3 10 104.5 360 360 600 721 721 721 721 Bronchitis/emphysema No 1105 0 1 3 10 60 180 600 600 721 721 721 721 Bronchitis/emphvsema Yes 63 5 5 10 10 90 180 600 600 600 721 721 721 Note: Values of"180", "360","600", and "721" for number of minutes signify that 2-4 hours, 4-8 hours, 8-12 hours, and over 12 hours, respectively, were spent. N = doer sample size. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsano and Kleoeis 1996. Table 15-42. Number of Times an Outside Door Was Opened in the Home at Specified Daily Frequencies by the Number of Respondents Times/Day* Total N 1-2 3-5 6-9 10-19 20+ DK Overall 1187 192 248 229 267 196 55 511 80 96 100 118 93 24 Female 676 112 152 129 149 103 31 Age (years) 19 6 3 2 3 1 4 1-4 68 13 14 8 17 13 3 5-11 109 15 16 18 31 23 6 12-17 8-64 79 730 1111 N5 N6 N1 H3 4 23 > 64 182 35 53 28 32 19 15 Rwe hite 979 155 193 188 233 168 42 Black 103 22 28 21 12 14 6 Asian 23 1 9 4 6 2 1 S9me Others 22 2 7 4 2 46 10 8 1 Re used 14 3* 3 4 1 3 1086 179 227 208 244 180 48 Yes 83 11 17 16 20 15 1 DK 7
2 1 1 Refused 11 2 2 4 3 Erpployment 255 40 46 43 60 53 .13 Time 4g558 79 104 10 art Time 14 22 2 Not EmP,loyed 369 58 81 69 80 52 29 Refuse a 10 1 3 3 1 1 1 267 42 48 46 63 54 14 < High School 98 21 17 15 18 20 7 Hi8ti School Graduate 14 < ollege 12 Collee,,e Graduate 150 21 37 39 31 19 3 Post raduate 126 16 28 27 35 15 5 Census Region 228 37 38 49 53 38 13 Northeast Midwest 225 44 54 39 50 33 5 81 71 rn est 75 93 ow of Week eekdaY, 746 116 167 156 167 106 34 Weekena 441 76 81 73 100 90 21 Season Winter 185 19 51 39 42 27 7 Spring 417 73 94 66 90 73 21 Summer 387 72 68 81 80 66 20 Fall 198 28 35 43 55 30 7 Asthma No 1087 175 228 211 245 179 49 Yes 99 16 2p \8 2*2 \7 DK 1 1 1147 183 241 221 259 192 51 319 ? 1 1 Bronchitis/emphysema 1121 179 230 216 52 64 12 18 12 DK 2 1

1 Note:

data1 "DK" = respondent answered don't know; Source: sanq and leoeis 996 N = sample size; Refused = respondent refused to answer.
Table 15-43. Number of Minutes Spent Runnino, Walkim1, or Standinq Alonoside a Road with Heaw Traffic lminutes/dav\ Percentiles Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 401 0 1 2 2 5 15 30 60 121 121 121 121 Gender Male 202 1 1 2 3 5 17.5 45 120 121 121 121 121 Gender Female 198 0 0 1 2 5 10 30 60 120 121 121 121 Age (years) 1-4 12 1 1 1 2 4 7.5 30 60 60 60 60 60 Age (years) 5-11 20 1 1 1.5 2 5 6 12.5 25 60 90 90 90 Age (years) 12-17 27 0 0 2 2 4 5 30 60 90 120 120 120 Age (years) 18-64 304 0 1 1 2 5 15 30 90 121 121 121 121 Age (years) > 64 31 2 2 2 4 5 20 45 60 121 121 121 121 Race White 306 0 1 2 2 5 15 30 110 121 121 121 121 Race Black 51 0 0 1 1 3 7 30 50 60 60 121 121 Race Asian 10 3 3 3 4 5 7.5 15 17.5 20 20 20 20 Race Some Others 7 2 2 2 2 5 10 45 121 121 121 121 121 Race Hispanic 24 2 2 2 3 10 17.5 40 60 60 120 120 120 Hispanic No 356 0 1 1 2 5 15 30 90 121 121 121 121 Hispanic Yes 43 1 1 2 2 5 10 30 60 120 121 121 121 Employment Full Time 214 0 1 1 2 5 15 30 120 121 121 121 121 Employment Part Time 50 0 0.5 2 2 5 15 30 90 121 121 121 121 Employment Not Employed 76 0 1 2 3 5.5 15 30 60 110 120 121 121 Education < High School 18 4 4 4 5 6 10 15 30 121 121 121 121 Education High School Graduate 106 1 1 2 2 5 15 60 121 121 121 121 121 Education <College 84 0 0 1 3 5.5 20 40 120 121 121 121 121 Education College Graduate 79 0 1 1 2 5 15 30 60 90 121 121 121 Education Post Graauate 50 1 1 2 2 5 10 20 52.5 90 120 120 120 Census Region Northeast 129 1 1 2 2 5 20 50 120 121 121 121 121 Census Region Midwest 83 0 0 1 2 5 10 20 60 121 121 121 121 Census Region South 105 0 0 1 2 5 15 30 90 121 121 121 121 Census Region West 84 1 2 2 3 5 15 30 60 120 121 121 121 Day of Week Weekday 303 0 0 2 2 5 15 30 60 120 121 121 121 Day of Week Weekend 98 1 1 2 3 5 15 30 121 121 121 121 121 Season Winter 1-04 0 0 1 2 4.5 10 20 60 110 121 121 121 Season Spring 114 1 1 2 2 6 20 60 120 121 121 121 121 Season Summer 104 0 1 2 2 5 10 30 60 121 121 121 121 Season Fall 79 0 1 2 3 5 20 35 120 121 121 121 121 Asthma No 370 0 1 2 2 5 15 30 60 121 121 121 121 Asthma Yes 31 0 0 1 2 5 15 30 120 121 121 121 121 Angina No 393 0 1 2 2 5 15 30 90 121 121 121 121 Angina Yes 8 2 2 2 2 6.5 17.5 30 60 60 60 60 60 Bronchitis/Emphysema No 378 0 1 1 2 5 15 30 60 121 121 121 121 Bronchitis/EinPhvsema Yes 22 2 2 5 5 5 17.5 30 121 121 121 121 121 NOTE: A value of "121" for number of minutes signifies that more than 120 minutes were spent. N = doer sample size. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleneis 1996 Table 15-44. Number of Minutes Soent in a Car, Van, Truck, or Bus in Heaw Traffic (minutes/dav) Percentiles Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 1197 1 2 5 5 10 20 60 120 121 121 121 121 Gender Male 534 1 2 4 5 10 20 60 120 121 121 121 121 Gender Female 663 1 2 5 5 10 25 60 120 121 121 121 121 Age (years) 1-4 33 4 4 5 5 10 15 30 60 60 121 121 121 Age (years) 5-11 63 1 2 5 5 10 20 45 60 120 121 121 121 Age (years) 12-17 52 3 3 4 5 9 12.5 27.5 90 120 120 121 121 Age (years) 18-64 889 1 2 5 5 10 25 60 120 121 121 121 121 Age (years) >64 139 3 3 5 5 15 30 60 121 121 121 121 121 Race White 959 1 2 4 5 10 25 60 120 121 121 121 121 Race Black 133 2 3 5 5 10 20 40 90 120 121 121 121 Race Asian 20 5 5 5 5 11 20 30 45 52.5 60 60 60 Race Some Others 24 5 5 10 10 12.5 30 60 90 120 121 121 121 Race Hispanic 55 1 2 5 5 10 20 60 120 121 121 121 121 Hispanic No 1097 1 2 5 5 10 20 60 120 121 121 121 121 Hispanic Yes 95 1 2 5 5 10 20 90 . 121 121 121 121 121 Employment Full Time 659 1 2 5 5 10 30 60 120 121 121 121 121 Employment Part Time 108 2 2 4 5 10 20 48.5 . 121 121 121 121 121 Employment Not Employed 279 1 2 5 5 . 10 30 60 120 121 121 121 121 Education . < High School 81 0 3 5 10 10 20 40 121 121 121 121 121 Education High School Graduate 352 1 2 5 5 10 30 60 120 121 121 121 121 Education <College 276 1 2 3 5 15 30 60 120 121 121 121 121 Education College Graduate 176 1 2 4 5 12.5 30 60 120 121 121 121 121 Education Post Graduate 150 2 2 5 5 10 20 60 97.5 120 121 121 121 Census Region Northeast 229 2 2 4 5 10 20 60 120 121 121 121 121 Census Region Midwest 263 2 2 5 5 10 30 45 120 121 121 121 121 Census Region South 429 1-2 5 5 10 30 60 120 121 121 121 121 Census Region West 276 1 2 5. 5 10 20 60 120 121 121 121 121 Day of Week Weekday 927 1 2 5 5 10 20 60 120 121 121 121 121 Day of Week *weekend 270 2 2 5 5 10 25 60 120 121 121 121 121 Season Winter 286 1 2 5 5 10 20 60 120 121 121 121 121 Season Spring 317 1 2 5 5 10 30 60 120 121 . 121 121 121 Season Summer 312 1 3 5 5 10 30 *60 120 121 121 121 121 Season Fall 282 2 2 4 5 10 20 45 120 121 121 121 121 Asthma No '1108 1 2 5 5 10 20 60 120 121 121 121 121 Asthma Yes 89 2 2 5 5 10 30 60 121 121 121 121 121 Angina No 1159 1 2 5 5 10 20 60 120 121 121 121 121 Angina Yes 35 0 0 5 5 10 30 70 121 121 121 121 121 Bronchitis/emphysema No 1130 2 2 5 5 10 20 60 120 121 121 121 121 Bronchitis/emphysema Yes 64 1 1 2 5 10 27.5 51 120 121 121 121 121 NOTE: A value of "121" for number of minutes signifies that more than 120 minutes were spent. N = doer sample size. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsano and Kleoeis 1996 . Table 15-45. Number of Minutes Soent in a Parkinq Garaqe or Indoor Parkinq Lot (minutes/day) Percentiles Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 294 0 1 1 2 3 5 10 30 60 121 121 121 Gender Male 138 1 1 1 2 4 5 15 60 121 121 121 121 Gender Female 156 0 1 1 2 3 5 10 20 40 60 120 121 Age (years) 1-4 8 0 0 0 0 2 3.5 5 10 10 10 10 10 Age (years) 5-11 15 1 1 1 2 3 5 10 45 60 60 60 60 Age (years) 12-17 20 0 0 0.5 1.5 2 7.5 15 45 90.5 121 121 121 Age (years) 18-64 229 1 1 2 2 5 5 10 30 60 121 121 121 I Age (years) >64 18 0 0 0 2 3 5 15 45 90 90 90 90 Race White 208 1 1 2 2 3 5 10 30 60 121 121 121 Race Black 34 0 0 1 1 5 5 15* 20 30 30 30 30 Race Asian 15 2 2 2 2 2 10 60 120 121 121 121 121 Race Some Others 7 3 3 3 3 3 5 15 121 121 121 121 121 Race Hispanic 28 1 1 1 2 4.5 10 20 60 120 121 121 121 Hispanic No 251 0 1 1 2 3 5 10 30 60 120 121 121 Hispanic Yes 39 1 1 1 3 5 10 30 121 121 121 121 121 Employment Full Time 171 1 1 1 2 3 5 10 30 60 121 121 121 Employment Part Time 23 2 2 5 5 5 5 10 30 60 121 121 121 Employmen_t Not Employed 58 0 1 1 2 4 10 20 40 120 121 121 121 Education < High School 13 0 0 0 5 5 10 10 30 121 121 121 121 Education High School Graduate 58 1 1 1 2 3 9.5 30 90 121 121 121 121 Education <College 54 1 1 2 2 4 5 15 40 120 120 121 121 Education College Graduate 72 1 1 2 2 4.5 5 10 15 60 120 121 121 Education Post Graduate 50 1 1 2 2 5 5 10 12.5 20 40 60 60 Census Region Northeast 53 2 2 2 2 5 6 10 30 90 121 121 121 Census Region Midwest 59 0 0 1 2 3 5 10 30 60 121 121 121 Census Region South 92 1 1 2 2 3.5 5 10 30 60 121 121 121 Census Region West 90 0 1 1 1.5 4 5 15 45 60 121 121 121 Day of Week Weekday 208 0 1 1 2 3 5 10 30 60 121 121 121 Day of Week Weekend 86 1 1 2 2 5 7 15 30 60 121 121 121 Season Winter 67 0 1 1 2 3 5 10 20 30 120 121 121 Season Spring 78 0 1 1 2 3 5.5 15 qO 120 121 121 *121 Season Summer 85 0 1 2 2 5 5 15 30 90 121 121 121 Season Fall 64 1 1 2 2 4.5 5 10 30 45 121 121 . 121 Asthma No 263 1 1 2 2 3 5 10 30 60 121 . 121 121 Asthma Yes 30 0 0 1 1 . 4 7 10 30 121 121 121 121 Angina No 291 0 1 1 2 4 5 10 30 60 121 121 121 Angina Yes 2 3 3 3 3 3 46.5 90 90 90 90 90 90 Bronchitis/emphysema No 281 0 1 1 2 3 5 10 30 60 121 121 121 Bronchitis/emphysema Yes 12 2 2 2 5 5 5.5 10 60 12.0 120 120 120 NOTE: A value of "121" for number of minutes signifies that more than 120 minutes were spent. N = doer sample size. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsano and Kleoeis 1996 Table 15-46 . .Number of Minutes Soent Walkina Outside to a Car in the Driveway or Outside Parkina Areas (minutes/day) Percentiles Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 3303 0 0 0 0 2 5 10 20 30 60 121 121 Gender Male 1511 0 0 0 0 2 4 10 20 30 60 121 121 Gender Female 1791 0 0 0 0 2 5 10 20 30 60 60 121 Age (years) 1-4 132 0 0 0 0 1.5 2 5 15 20 30 60 121 Age (years) 5-11 245 0 0 0 0 1 2 5 15 30 45 80 121 Age (years) 12-17 202 0 0 0 0 1 5 10 20 30 30 60 121 Age (years) 18-64 2303 0 0 0 0 2 5 10 20 30 60 120 121 Age (years) > 64 373 0 0 0 1 2 5 10 15 30 30 88 121 Race White 2756 0 0 0 0 2 5 10 20 30 60 120 121 Race Black 279 0 p 0 0 1 3 5 10 20 30 45 88 Race Asian 53 0 0 0 0 1 3 10 15 30 32 45 45 Race Some Others 63 0 0 0 0 2 5 10 30 30 60 120 120 Race Hispanic 127 0 0 1 1 2 5 10 20 60 120 121 121 Hispanic No 3029 0 0 0 0 2 5 10 20 30 60. 120 121 Hispanic Yes 235 0 0 0 0 2 5 10 20 60 120 121 121 Employment Full Time 1613 0 0 0 0 2 5 10 20 30 w 120 121 Employment Part Time 312 0 0 0 1 2 5 10 20 45 120 121 121 Employment Not Employed 785 0 0 0 0 2. 5 10 20 30 60 60 121 Education < High School 241 0 0 0 0 2 4 10 20 30 110 121 121 Education High School Graduate 935 0 0 0 0 2 5 10 20 30 60 121 121 Education <College 680 0 0 0 1 2 5 10 20 30 60 120 121 Education College Graduate 445 0 0 0 0 2 5 10 20 30 60 60 121 Education Post Graduate 381 0 0 0 1 2 5 10 15 25 30 120 121 Census Region Northeast 680 0 0 0 0 2 5 10 15 30 60 90 121 Census Region Midwest 763 0 0 0 1 2 5 10 15 30 60 120 121 Census Region .South 1149 0 0 0 0 2 4 10 20 30 60 90 121 Census Region West 711 0 0 0 0 2 5 10 20 30 60 120 121 Day of Week Weekday 2209 0 0 0 0 2 5 10 20 30 60 120 121 Day of Week Weekend 1094 0 0 0 0 2 5 10 20 30 60 120 121 Season Winter 855 0 0 0 0 1 4 10 15 30 30 100 121 Season Spring 890 0 0 0 0 2 5 10 20 30 100 120 121 Season Summer 903 0 0 0 0 2 4 10 20 30 60 60 121 Season Fall 655 0 0 0 1 2 5 10 15 30 45 110 121 Asthma No 3063 0 0 0 0 2 5 10 20 30 60 120 121 Asthma Yes 234 0 0 0 1 2 5 10 15 30 120 121 121 Angina No 3219 0 0 0 0 2 5 10 20 30 60 120 121 Angina Yes 72 0 0 0 0 2 5 10 15 30 45 110 110 Bronchitis/Emphysema No 3132 0 0 0 0 2 5 10 20 30 60 120 121 Bronchitis/Emphysema Yes 162 0 0 0 0 2 5 10 20 30 110 121 121 NOTE: A value of "121" for number of minutes signifies that more than 120 minutes were spent. N = doer sample size. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996 Table 15-47. Number of Minutes Spent Runnini:i or Walkini:i Outside Other Than to the Car (minutes/day) Percentiles Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 1273 1 1 3 5 15 45 120 121 121 121 121 121 Gender Male 605 2 2 5 10 20 60 121 121 121 121 121 121 Gender Female 668 0 1 2 5 15 30 116 121 121 121 121 121 Age (years) 1-4 82 3 3 5 10 30 120 121 121 121 121 121 21 Age (yeaars) 5-11 149 4 5 5 10 30 120 121 121 121 121 121 21 Age (years) 12-17 110 5 5 5 10 15 60 121 121 121 121 121 121 Age (years) 18-64 772 0 1 2 5 15 30 120 121 121 121 121 121 Age (years) 5:>64 143 1 1 2 5 15 30 60 121 121 121 121 121 Race White 1051 1 1 3 5 15 45 121 121 121 121 121 121 Race Black 111 0 1 3 5 15 35 120 121 121 121 121 121 Race Asian 21 2 2 10 10 15 30 70 120 121 121 121 121 Race Some Others 23 5 5 10 15 20 60 121 121 121 121 121 121 Race 5:hispanic 55 2 3 8 10 20 40 90 121 121 121 121 121 Hispanic* No 1156 1 1 3 5 15 45 120 121 121 121 121 121 Hispanic Yes 99 1 2 2 10 20 60 121 121 121 121 121 121 Employment Full Time 517 0 1 2 5 15 30 120 121 121 121 121 121 Employment Part Time 112 1 2 2 5 15 30 90 121 121 121 121 121 Employment Not Employed 300 1 1 3 5 15 30 120 121 121 121 121 121 Education < High School 97 0 1 3 5 15 30 90 121 121 121 121 121 Education High School Graduate 287 0 0 2 5 15 30 120 121 121 121 121 121 Education <College 234 1 1 2 5 15 30 120 121 121 121 121 121 Education College Graduate 153 1 2 5 10 20 45 120 121 121 121 121 121 Education Post Graduate 138 1 1 3 5 15 37.5 90 121 121 121 121 121 Census Region Northeast 265 1 1 3 5 20 45 120 121 121 121 121 121 Census Region Midwest 286 1 2 5 5 15 40 121 121 121 121 121 121 Census .Region South 412 1 1 3 5 15 45 121 121 121 121 121 121 Census Region West 310 1 1 3 5.5 15 45 120 121 121 121 121 121 Day of Week Weekday 843 1 1 3 5 15 40 120 121 121 121 121 121 Day of Week Weekend 430 1 2 4 5 20 60 121 121 121 121 121 21 Season Winter 312 0 2 2 5 10 42.5 90 121 121 121 121 21 Season Spring 403 1 2 4 10 20 60 121 121 121 121 121 121 Season Summer 396 1 1 3 10 20 55 121 121 121 121 121 21 Season Fall 162 1 1 2 5 15 30 120 121 121 121 121 121 Asthma No 1162 1 1 3 5 15 45 120 121 121 121 121 21 Asthma Yes 105 2 4 5 6 15 45 121 121 121 121 121 21 Angina No 1240 1 1 3 5 15 45 120 121 121 121 121 121 Angina Yes 25 1 1 5 5 15 45 121 121 121 121 121 121 Bronchitis/Emphysema No 1204 1 1 3 5 15 45 120 121 121 121 121 121 Bronchitis/Emphysema Yes 62 1 2 4 5 15 30 120 121 121 121 121 121 NOTE: A value of "121" for number of minutes signifies that more than 120 minutes were spent. N = doer sample size. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsano and Kleoeis 1996 Table 15-48. Number of Hours Spent Workina for Pav (hours/week\ Percentiles Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 4896 0 0 0 12 33 40 50 60 61 61 61 61 Gender Male 2466 0 0 0 18 40 40 53 61 61 61 61 61 Gender Female 2430 0 0 0 6 28 40 43 55 60 61 61. 61 Age (years) 1-4 0 . . . . . . . . * . . . Age (years) 5-11 0 . . . . . . . * * . . . Age (years) 12-17 14 0 0 0 1 9 18.5 24 26 31 31 31 31 Age (years) 18-64 4625 0 0 0 15 35 40 50 60 61 61 61 61 Age (years) >64 181 0 0 0 0 5 21 40 50 61 61 61 61 Race White 3990 0 0 0 10 32 40 50 60 61 61 61 61 Race Black 499 0 0 0 18 35 40 46 60 61 61 61 61 Race Asian 76 0 0 0 7 36.5 40 50 61 61 61 61 61 Race Others 87 0 0 0 0 30 40 50 60 61 61 61 61 Race Hispanic 194 0 0 0 15 32 40 48 60 60 61 61 61 Hispanic No 4494 0 0 0 12 33 40 50 60 61 61 61 61 Hispanic Yes 341 0 0 0 8 32 40 50 60 61 61 61 61 Employment Full Time 4094 0 0 0 30 40 40 50 60 61 61 61 61 Employment Part Time 802 0 0 0 0 10 20 30 38 40 61 61 61 Employment Not Employed 0 . . . . . . . . * * . . Education < High School 308 0 0 0 1 21 40 48 61 61 61 61 61 Education High School Graduate 1598 0 0 0 12 32 40 48 60 61 61 61 61 Education <College 1251 0 0 0 15 30 40 50 60 61 61 61 61 Education College Graduate 954 0 0 0 16 40 40 50 60 61 61 61 61 Education Post Graduate 716 0 0 0 10 35 40. 50 60 61 61 61 61 Census Region Northeast 1096 0 0 0 14 32 40 50 60 61 61 61 61 Census Region Midwest 1118 0 0 0 12 32 40 50 60 61 61 61 61 Census Region South 1675 0 0 0 12 35 40 50 60 61 61 61 61 Census Region West 1007 0 0 0 9 30 40 50 60 61 61 61 61 Day of Week Weekday 3306 0 0 0 10 33 40 50 60 61 61 61 61 Day of Week Weekend 1590 0 0 0 12 33 40 48 60 61 61 61 61 Season Winter 1306 0 0 0 10 32 40 50 60 61 61 61 61 Season Spring 1197 0 0 0 15 35 40 50 60 61 61 61 61 Season Summer 1343 0 0 0 3 33 40 48 60 61 61 61 61 Season Fall 1050 0 0 0 14.5 32 40 50 60 61 61 61 61 Asthma No 4579 0 0 0 12 34 40 50 60 61 61 61. 61 Asthma Yes 302 0 0 0 9 30 40 48 60 61 61 61 61 Angina No 4811 0 0 0 12 34 40 50 60 61 61 61 61 Angina Yes 66 0 0 0 0 . 20 40 44 60 61 61 61 61 Bronchitis/Emphysema No 4699 0 0 0 12 33 40 50 6 61 61 61 61 Bronchitis/Emohvsema Yes 182 0 0 0 6 30 40 48 60 61 61 61 61 Note:
Signifies missing data. A value of "61" for number of hours signifies that more than 60 hours were spent. N = doer sample size. Percentiles are the Jercentage of doers below or equal to a given number of hours. *

Source: Tsana an Kleoeis 1996. . . .
Table 15-49. Number of Hours Spent Workinq for Pav Between 6PM and 6AM (hours/week) Percentiles Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 4894 0 0 0 0 0 0 8 30 45 61 61 61 Gender Male 2465 0 0 0 0 0 0 10 35 50 61 61 61 Gender Female 2429 0 0 0 0 0 0 5 20 39 61 61 61 Age (years) 1-4 0 0 0 0 0 0 0 0 0 0 0 0 0 Age (years) 5-11 0 0 0 0 0 0 0 0 0 0 0 0 0 Age (years) 12-17 14 0 0 0 0 0 4.5 20 24 25 25 25 25 Age (years) 18-64 4623 0 0 0 0 0 0 8 30 42 61 61 61 Age (years) >64 181 0 0 0 0 0 0 0 20 61 61 61 61 Race White 3989 0 0 0 .0 0 0 8 25 40 61 61 61 Race Black 499 0 0 0 0 0 0 10 40 61 61 61 61 Race Asian 75 0 0 0 0 0 0 12 30 61 61 61 61 Race Some Others 87 0 0 0 0 0 0 7 25 45 61 61 61 Race Hispanic 194 0 0 0 0 0 0 15 35 48 61 61 61 Hispanic No 4492 0 0 0 0 0 0 8 27 40 61 61 61 Hispanic Yes 341 0 0 , 0 0 0 0 13 35 50 61 61 61 Employment Full Time 4092 0 0 0 0 0 0 8 30 45 61 61 61 Employment Part Time 802 0 0 0 0 0 0 6 20 35 61 61 61 Employment Not Employed 0 0 0 0 0 0 0 0 0 0 0 0 0 Education < High School 308 0 0 0 0 0 0 11 50 61 61 61 61 Education High School Graduate 1597 0 0 0 0 0 0 8 35 50 61 61 61 Education <College 1251 0 0 0 0 0 0 9 26 40 60 61 61 Education College Graduate 953 0 0 0 0 0 0 8 20 40 61 61 61 Education Post Graduate 716 0 0 0 0 0 0 7 20 30 61 61 61 Census Region Northeast 1096 0 0 0 0 0 0 7 24 40 61 61 61 Census Region Midwest 1118 0 0 0 0 0 0 10 30 42 61 61 61 Census Region South 1674 0 0 0 0 *o 0 7 30 48 61 61 61 Census Region West 1006 0 0 0 0 0 0 10 30 47 61 61 61 Day of Week Weekday 3306 0 0 0 0 0 0 8 30 48 61 61 61 Day of Week Weekend 1588 0 0 0 0 0 0 7 28 40 61 61 61 Season Winter 1305 0 0 0 0 0 0 8 28 40 61: 61 61 Season Spring 1197 0 0 0 0 0 0 8* 30 48 61 61 61 Season Summer 1342 0 0 0 0 0 0 9 30 48 61 61 61 Season Fall 1050 0 0 0 0 0 0 7 25 40 61 61 61 Asthma No 4578 0 0 0 0 0 0 8 30 45 61 61 61 Asthma Yes 301 0 0 0 0 0 0 8 28 36 61 61 61 Angina No 4809 0 0 0 0 0 0 8 30 44 61 61 61 Angina Yes 66 0 0 0 0 0 0 7 36 40 61 61 61 Bronchitis/Emphysema No 4697 0* 0 0 0 0 0 8 30 43 61 61 61 Bronchitis/Emphysema Yes 182 0 0 0 0 0 0 10 40 50 61 61 61 Note: A Value of "61" for number of hours signifies that more than 60 hours were spent. N = doer sample size. Percentiles are the of doers below or equal to a given number of hours. Source: sanq and Kleoeis 1996. Table 15-50. Number of Hours Worked in a Week That Was Outdoors (hours/week) Percentiles Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 4891 0 0 0 0 0 0 1 30 50 61 61 61 Gender Male 2463 0 0 0 0 0 0 16 42 60 61 61 61 Gender Female 2428 0 0 0 0 0 0 0 2 12 55 61 61 Age (years) 1-4 0 0 0 0 0 0 0 0 0 0 0 0 0 Age (years) 5-11 0 0 0 0 0 0 0 0 0 0 0 0 0 Age (years) 12-17 14 0 0 0 0 0 0 0 0 0 0 0 0 Age (years) 18-64 4621 0 0 0 0 0 0 1 30 50 61 61 61 Age (years) >64 181 0 0 0 0 0 0 2 29 60 61 61 61 Race White 3986 0 0 0 0 0 0 2 30 50 61 61 61 Race Black 499 0 0 0 0 0 0 0 25 48 61 61 61 Race Asian 75 0 0 0 0 0 0 0 3 30 40 61 61 Race Some Others 87 0 0 0 0 0 0 1 17 40 48 61 61 Race Hispanic 194 0 0 0 0 0 0 2 30 50 61 61 61 Hispanic No 4489 0 0 0 0 0 0 1 30 48 61 61 61 Hispanic Yes 341 0 0 0 0 0 0 2 35 60 61 61 61 Employment Full Time 4090 0 0 0 0 0 0 2 35 50 61 61 61 Employment Part Time 801 *o 0 0 0 0 0 0 15 30 61 61 61 Employment Not Employed -0 0 0 0 0 0 0 0 0 0 0 0 0 Education < High School 308 0 0 0 0 0 0 16.5 55 61 61 61 61 Education High School Graduate 1594 0 0 0 0 0 0 6 40 60 61 61 61 Education <College 1251 0 0 0 0 0 0 1 30 46 61 61 61 Education College Graduate 953 0 0 0 0 0 0 0 20 35 50 61 61 Education Post Graduate 716 0 0 0 0 0 0 0 4 15 60 61 61 Census Region Northeast 1094 0 0 0 0 0 0 0 25 40 61 61 *61 Census Region Midwest 1117 0 0 0 0 0 0 0 30 50 61 61 61 Census Region South 1674 0 0 0 0 0 0 2 32 55 61 61 61 Census Region West 1006 0 0 0 0 0 0 *2 33 50 61 61 61 Day of Week Weekday 3305 0 0 0 0 0 0 1 32 50 61 61 61 Day of Week Weekend 1586 0 0 0 0 0 0 1 30 48 61 61 61 Season Winter 1305 0 0 0 0 0 0 0 25 50 61 61 61 Season Spring 1195 0 0 0 0 0 0 2 30 50 61 61 61 Season Summer 1341 0 0 0 0 0 0 2 36. 50 61 61 61 Season Fall 1050 0 0 0 0 0 0 0 30 45 61 61 61 Asthma No 4576 0 0 0 0 0 0 1 30 50 61 61 61 Asthma Yes 300 0 0 0 0 0 0 0 31 50 61 61 61 Angina No 4806 0 0 0 0 0 0 1 30 50 61 61 61 Angina Yes 66 0 0 0 0 0 0 4 35 50 61 61 61 Bronchitis/Emphysema No 4694 0 0 0 0 0 0 1 30 50 61 61 61 Bronchitis/Emphysema Yes 182 0 0 0 0 0 0 2 30 60 61 61 61 NOTE: A value of "61" for number of hours signifies that more than 60 hours were spent. N = doer sample size. Percentiles are the of doers below or equal to a given number of hours. Source: sano and Kleoeis 1996 Table 15-51. Number of Times Floors Were Swept or Vacuumed at Specified Frequencies by the Number of Respondents Number of Times TotalN Almost Every Day 3-5/week 1-2/week 1-2/month <Often Never DK Overall 4663 921 1108 2178 373 48 10 25 2163 415 520 976 201 27 5 19 Female 2498 505 588 1201 172 21 5 6 Refused 2 1 0 1 0 0 0 Age (years) 84 16 11 41 12 3 0 1 1-4 263 96 74 88 4 0 0 1 *115 107 165 8 8 82 83 18-64 2972. 524 723 1420 252 34 6 13 > 64 670 88 110 365 84 9 4 10 Race White 3774 641 879 1868 324 36 8 18 Black 463 167 115 150 19 5 2 5 Asian 77 3 8 1 Some Others 96 1 0 His/i'..anic 193 68 61 55 7 2 0 0 Re sed 60 8 9 34 7 1 0 1 Hispanic No 4244 799 988 2035 345 43 9 25 Yes 347 106 107 110 21 3 0 0 130 11 2 l 1 8 22 5 0 Erpployment 267 342 f84ii 2 1 Full Time 486 1018 27 9 Part Time 379 82 82 177 34 1 0 3 Not EmP,loyed 1309 256 263 626 127 18 8 11 Refusei:l 32 2 10 15 4 0 0 1 Equcation 1021 314 285 384 31 4 0 3 < High 1329593 3901 2 8 Hi81i Sc oo Graduate 3 7 < ollege 895 130 223 438 93 8 2 1 Graduate 650 64 132 346 93 9 3 3 Post. raduate 445 34 75 257 67 9 0 3 Census Region Northeast 1048 236 230 484 83 8 2 5 Mid:t"fiest 527 w 2 Sout 03 707 2 West 978 153 226 460 111 19 4 5 eekdaY. 3156 631 765 1458 248 33 5 16 Weekena 1507 290 343 720 125 15 5 9 Season Winter 1264 268 309 557 105 15 2 8 Spring 1181 217 286 560 96 12 3 7 Summer 1275 251 312 596 94 13 1 8 Fall 943 185 201 465 78 8 4 2 Asthma No 4287 821 1013 2030 351 39 10 23 Yes 341 95 88 133 17 7 0 1 DK 35 5 7 15 5 2 0 1 4500 892 352 44 10 24 es 125 21 16 2 0 0 DK 38 8 5 17 5 2 0 1 4424 871 1064 2063 349 44 9 24 Yes 203 45 39 99 17 2 1 0 DK 36 5 5 16 7 2 0 1 Note:
missing data; DK= respondent answered don't know; N = sample size; Refused = respondent refused to answer. Source: sano and Klepeis, 1996

Table 15-52. Number of Days Since the Floor Area in the Home Was Swept or Vacuumed by the Number of Respondents Number of Days since That Area Was Swept-vacuumed Swept->2 Total 0 Vacuumed 1 2 3 4 5 6 7 8 10 14 Weeks Dk N

Yes'day Overall 9386 8112 550 278 189 85 63 31 17 26 2 1 5 16 11 Gender Male 4294 3688 245 136 100 35 37 19 8 10 1 0 3 7 5 Female 5088 4421 304 142 89 50 26 12 .9 16 1 1 2 9 6 Refused 4 3 1 0 0 0 0 0 0 0 0 0 0 0 0 !\ge (years) 187 180 1 0 3 1 0 0 0 0 0 0 0 1 1 1-4 499 67 199 93 54 24 19 17 9 7 0 1 2 6 1 5-11 703 393 121 70 50 23 22 8 2 4 1 0 2 2 5 12-17 589 533 30 12 6 3 0 0 1 2 0 0 0 2 0 18-64 6059 5592 198 102 76 34 22 6 5 13 1 0 1 5 4 > 64 1349 1347 1 1 0 0 0 0 0 0 0 0 0 0 0 Race White 7591 6586 398 232 152 72 55 29 14 24 2 1 5 13 8 Black 945 825 72 18 17 7 3 1 2 0 0 0 0 0 0 Asian 157 138 5 6 2 2 1 0 0 1 0 0 0 1 1 Some Others 182 141 21 7 9 2 1 0 0 0 0 0 0 1 0 HisiEanic 385 300 52 15 9 2 2 0 1 1 . 0 0 0 1 2 Re sed 126 122 2 0 0 0 1 1 0 0 0 0 0 0 0 Hispanic 8534 7421 .460 248 170 80 57 29 15 24 2 1 5 14 8 No Yes 702 549 88 29 17 5 4 2 2 2 0 0 0 1 3 Dk 47 42 1 1 1 0 1 0 0 0 0 0 0 1 0 Refused 103 100 1 0 1 0 1 0 0 0 0 0 0 0 0 fmployment 1773 974 349 175 112 50 41 25 12 13 1 1 4 9 7 Full Time 4096 3826 96 64 50 21 18 6 4 6 1 0 0 4 0 Part Time 802 741 28 10 8 6 2 0 0 4 0 0 1 1 1 Not Employed 2644 2502 77 29 18 8 2 0 1 3 0 0 0 1 3 Refused 71 69 0 0 1 0 0 0 0 0 0 0 0 1 0 fducation 1968 1162 353 175 114 50 41 25 12 13 1 1 4 10 7 < High School 834 793 24 13 2 1 0 0 0 0 0 0 0 0 1 Hi81i School Graduate 2612 2447 76 39 26 9 7 1 2 0 1 0 0 2 2 < ollege 1801 1681 55 25 18 10 6 0 1 3 0 0 0 2 0 Graduate 1247 1155 28 19 17 10 5 3 1 7 0 0 0 1 1 Post raduate 924 874 14 7 12 5 4 2 1 3 0 0 1 1 0 Census Region Northeast 2075 1793 129 65 35 18 4 9 9 6 0 0 0 5 2 Midwest 2102 1826 108 59 47 21 17 7 2 6 2 1 2 2 2 South 3243 2805 193 87 75 26 27 8 3 8 0 0 2 5 4 West 1966 1688 120 67 32 20 15 7 3 6 0 0 1 4 3 Day of Week 6316 5487 366 160 125 57 51 18 13 15 2 1 4 11 6 Weekday Weekeni:l 3070 2625 184 118 64 28 12 13 4 11 0 0 1 5 5 Season Winter 2524 2144 162 79 61 27 . 17 7 3 13 0 0 1 5 5 Spring 2438 2112 121 90 48 19 19 9 7 4 0 0 2 5 2 Summer 2536 2187 167 68 41 26 19 12 3 3 0 1 2 4 3 Fall 1888 1669 100 41 39 13 8 3 4 6 2 0 0 2 1 Asthma No 8629 7455 502 262 171 80 59 30 13 22 2 1 5 16 11 Yes 694 596 *48 15 17 5 4 1 4 4 0 0 0 0 0 Dk 63 61 0 1 1 0 0 0 0 0 *o 0 0 0 0 Angina No 9061 7793 547 277 189 83 63 31 17 26 2 1 5 16 11 Yes 250 246 2 1 0 1 0 0 0 0 0 0 0 0 0 Dk 75 73 1 0 0 1 0 0 0 0 0 0 0 0 0 Bronchitis/emphysema No 8882 7645 536 268 182 84 61 31 17 25 2 1 5 15 10 Yes 433 397 13 10 7 1 2 0 0 1 0 0 0 1 1 Dk 71 70 1 0 0 0 0 0 0 0 0 0 0 0 0 Note:

Signifies missing DK = respondents answered don't know; N= sample size; Refused = respondent refused to answer. Source: Tsanq and Kleoeis 1 96 Table 15-53. Number of Loads of Laundry Washed in a Washing Machine at Home by the Number of Respondents Total N Number of Loads/Day 1 2 3 4 5 6 7 8 9 10 >10 DK Overall 1762 582 604 303 123 55 27 11 12 1 5 1 38 Gender *

1

Male 678 219 241 120 41 17 8 1 30 Female 1083 3§3 3§3 1§3 BJ 38 19 10 \2 1 1 § Refused 1 *

1

Ag,e (years) 30 9 14 2 3 1 * * * * *

1 1-4 109 29 36 24 12 5 2 ** *

1

5-11 141 38 55 28 8 6 2 1

1 1

1 12-17 127 39 52 22 10 1 1 1 *

1 18-64 1161 385 376 209 80 35 2J 9 \1

1 30 >64 194 82 71 18 10 7 1

5 Race

White 1511 513 519 254 101 48 23 \1 \2 1 3 26 Black 112 27 41 23 11 1 1 1

4 Asian 22 7 4 3 5 * * * *

3 Some Others 31 8 12 5 1 1 1 * * * *

3 HisRianic. 68 18 24 15 § ? ? * *

1

1 Re sed 18 9 4 3 * *

1 1 1615 536 556 271 115 50 24 1) \2 1 4

35 Yes 126 38 42 26

1

DK 6

2 4 * * *

Refused 15 8 4 2 * * * * * *

1

En:Jployment 369 102 143 71 29 12 5 1 1 1 2

2 Full Time 734 259 244 128 42 20 10 5 4 ?

20 Part Time 160 58 53 23 10 8 3

1 *

4 Not EmP,loyed 482 158 158 79 41 \5 8 §

1 1 10 Refusea 17 5 6 2 1 1

2 Ed,!Jcation 413 118 160 77 32 12 6 1 1 1 ?

3 < High School 133 44 44 22 10 4 3 2

4 Hi8ti School Graduate 508 175 166 85 35 18 8 3 4 * *

14 < allege 321 105 101 61 25 9 3 ? 5 * ? 1 7 Collee:,e Graduate 212 83 68 32 11 8 4 1

5 Post raduate 175 57 65 26 10 4 3 3 1

1

5 Census * *

Northeas 367 111 146 57 23 13 7 2 1 7 Midwest 406 125 123 76 42 14 5 3 6 1

1 10 South 628 205 228 110 39 17 6 § 4 3 10 West 361 141 107 60 19 11 9 1

2

11 DawofWeek eekday 1172 418 409 194 62 29 17 7 7 1 1 1 26 Weekena 590 164 195 109 61 26 10 4 5 4 12 Season 1 Winter 458 154 159 73 31 14 6 3 4 1 3 9 Spring 465 154 159 87 28 10 10 3 2 1 11 Summer 482 158 166 85 38 11 8 4 3

1

8 Fall 357 116 120 58 26 20 3 1 3 *

10 Asthma No 1615 548 545 274 105 50 2J . \1 12 1 1 36 Yes 140 31 56 28 \8 * * ? DK 7 3 3 1 * * * * *

1710 564 592 294 113 54 26 1) 12 1 l 37 Yes 40 14 9 7 8 1 1 *

DK 12 4 3 2 2 * * * * *

1 Bronchitis/Emphysema 1658 544 572 285 112 53 26 10 12 1 1 37 No Yes 96 36 28 16 \1 ? 1 1

l DK 8 2 4 2 * * * *

Note:

Sfsnifies missing data1 "DK" = respondent answered don't know; N= sample size; Refused = respondent refused to answer. Source: sana And Klebeis 996 Table 15-54. Number of Times Using a Dishwasher at Specified Frequencies by the Number of Respondents Number of Times/Week Total N

Almost Every Day 3-5/Week 1-2/Week <1-2/Week DK Overall 2635 1 557 678 529 824 46 Gender Male 1235

259 282 247 417 30 Female 1399 1 406 113 Refused 1

1 Ag,e (years) 35

4 13 11 6 1 1-4 145

9 4 3 118 11 5-11 211

14 8 15 157 17 12-17 206

27 33 31 113 2 18-64 1718

438 512 397 360 11 > 64 320 1 65 108 72 70 4 Race White 2267. 1 504 603 487 637 35 Black 163

19 32 19 90 3 Asian 54

7 8 7 31 1 Some Others 45

9 8 1 24 3 84

13 15 12 40 1 Re used 22

5 12 3 2 HiiP0anic 2444 l 524 635 504 739 41 Yes 164 27 32 21 79 DK 11

2 2 2 5 Refused 16

4 9 2 1

552

49 45 46 382 30 Full Time 1191

276 359 298 249 9 Part Time 204

48 70 46 38 2 Not EmP.loyed 678 l 181 200 136 Refusea 10 3 4 3 Ed,µcation 593

55 51 55 400 3.2 < High School 124 l 29 27 26 41 Hi8ti School Graduate 582 153 173 114 132 10 < allege 560

144 181 117 117 1 Graduate 446

105 134 126 80 1 Post raduate 330

71 112 91 54 2 Census Repion

Northeas 538 133 144 95 159 7 Midwest 514

116 130 110 152 6 South 953

200 251 169 312 21 West 630 1 108 153 155 201 12 oawofweek eekday 1768 l 378 466 341 549 33 Weekena 867 179 212 188 275 13 Season Winter 711

144 175 149 223 20 Spring . 664 l 122 181 132 214 14 Summer 721 157 185 134 239 6 Fall 539

134 137 114 148 6 Asthma No 2439. 1 521 622 492 765 38 Yes 189 35 54 35 58 7 DK 7

1 2 2 1 1 2570 l 538 664 512 809 4.6 Yes 60 19 11 16 14 DK 5 * * . 3 1 1

Bronchitis/Emphysema 2533 1 540 646 504 796 4.6 No Yes 93

16 27 23 27 DK 9 .

1 5 2 1

Note:

Sfsnifies missing datai "DK" = respondent answered don't know; Source: sane And Kleoeis 996

N= sample size; Refused = respondent refused to answer.
~~Table 15-55. Number of Times Washing Dishes by Hand at Specified Frequencies by the Number of Respondents Number of Times/Week Total N~~
Almost Every 3-5/Week 1-2/Week <1-2/Week DK Day Overall 3_626 1 2600 490 326 197 12 Gender

Male 1554 982 264 183 117 8 Female 2071 1 16)8 225 113 a.a 1 Refused 1 1 Aae (years) 65

5)" 2

1-4 1

1

5-11 103

12 14 33 44

12-17 228

57 45 69 56 1 18-64 2642 1 1979 379 201 76 6 > 64 587 501 46 20 15 5 Race White 2928 1 2114 391 257 157 8 Black 385 261 61 40 21 f Asian 61

48 6 3 4 Some Others 67

44 9 9 5

HisRianic 147

108 17 12 8 f Re sed 38

25 6 5 2 3322 1 2383 454 296 178 10 Yes 258 185 3.2 25 14 f DK 21

16 3 2 Refused 25

16 4 2 3

E11Jployment 328

71 57 102 97 1 Full Time 1765

1282 284 145 50 4 Part Time 349

270 44 17 15 3 Not EmP,loyed 1165 1 965 104 60 31 4 Refusea 19 12 1 2 4

Education

386

101 65 107 112 1 < High School 354

298 26 15 12 3 Hi81i School Graduate 1106 1 856 140 74 30 5 < allege 796 606 116 57 16 1 Collee,,e Graduate 591

445 86 47 13

Post raduate 393

294 57 26 14 2 Census Re@ion

Northeas 832 636 90 60 43 3 Midwest 811

569 114 81 45 2 South 1214 1 840 175 124 70 4 West 769 555 111 61 39 3 oawotweek

eekdaY. 2474 1759 335 236 136 8 Weekena 1152 1 841 155 90 61 4 Season

Winter 985 691 138 90 63 3 Spring 902 1 648 117 85 46 5 Summer 987 705 132 92 55 3 Fall 752

556 103 59 33 1 Asthma No 3345 1 2407 455 290 183 9 Yes 263

179 33 34 1.4 DK 18

14 2. 2 3501

2499 475 321 194 12 Yes 105 1 86 11 2

DK 20 15 4 1

Bronchitis/Emphysema 3438 1 2459 460 314 192 12 No Yes 169 126 27 11

DK 19

15 3 1

Note:

missing data1 '*'DK" = respondent answered don't know; N= sample size; Refused = respondent refused to answer. Source: sano And Klebeis 996 Table 15-56. Number of Times for Washing Clothes in a Washing Machine at Specified Frequencies by the Number of Respondents Number of Times/Week Total N

Almost Every 3-5 /Day 1-2/week <1/week Never DK Day Overall 4663 404 566 1033 1827 331 465 37 Gender Male 2163 212 211 458 811 154 300 17 Female 2498 191 355 575 1015 177 165 20 Refused 2 1 *

1 * *

A9e (years) 84 3 1.1 4J 2 12 1-4 263 261 1 1 5-11 348 101 2 4 16 15 206 4 12-17 326 1 22 29 83 67 124

18-64 2972 31 489 832 1328 197 83 12 > 64 670 7 47 157 353 49 49 8 Race White 3774 316 499 883 1445 246 370 15 Black 463 39 33 72 207 52 55 t Asian 77 4 1 12 39 13 8 Some Others 96 16 10 15 36 8 11

His/Ganie 193 29 19 41 77 10 17

Re sed 60

4 10 23 2 4 17 Hispanic 4244 342 528 950 1674 307 424 1.9 No Yes 347 59 31 69 130 20 38 DK 26 2 3 6 10 3 2

Refused 46 1 4 8 13 1 1 18 Erpployment 926 366 23 32 97 76 327 5 Full Time 2017 21 305 569 929 119 66 8 Part Time 379 6 64 101 166 29 13

Not Employed 1309 10 170 326 628 105 58 12 Refusei:I 32 1 4 5 7 2 1 12 Education

1021 367 33 37 129 89 343 23 < High School 399 3 61 88 178 40 27 2 Hi8h School Graduate 1253 14 218 367 548 55 47 4 < allege 895 3 126 261 432 51 19 3 Graduate 650 12 78 171 321 57 9 2 Post raduate 445 5 50 109 219 39 20 3 Census Region Northeast 1048 84 119 216 454 81 87 7 Midwest 1036 88 108 229 408 78 121 4 South 1601 147 229 376 557 97 182 13 West 978 85 110 212 408 75 75 13

eekday 3156 257 407 697 1217 232 320 26 Weekend 1507 147 159 336 610 99 145 11 Season* Winter 1264 121 157 273 472 101 129 11 Spring 1181 122 135 259 464 82 113 6 Summer 1275 102 163 280 484 88 142 16 Fall 943 59 111 221 407 60 81 4 Asthma No 4287 371 522 951 1700 303 421 19 Yes 341 32 42 79 118 26 43 1 DK 35 1 2 3 9 2 1 17 4500 493 555 993 1759 321 451 18 Yes 125 8 37 58 7 13 2 DK 38 1 3 . 3 10 3 1 17 Bronchitis/emphysema No 4424 397 549 979 1724 315 441 19 Yes 203 7 15 51 92 14 23 1 DK 36

2 3 11 2 1 17 Note:

Sfsnifies missing data; "DK" = respondent answered don't know; N= sample size; Refused = respondent refused to answer. Source: sanq And Kleoeis 1996 Table 15-57. Number of Minutes Spent Plaving on Sand or Gravel in a Dav bv the Number of Respondents Minutes/Dav Total N *

0-0 0-10 10-20 20-30 30-40 40-50 50-60 70-80 80-90 90-100 110-120 121 Overall 700 41 348 42 34 57 4 12 66 2 9 2 27 .56 Gender Male 352 18 189 20 13 25

7 32

7 1 10 30 Female 347 2.3 158 2.2 2.1 32 1 34 2 ? 1 17 2.6 Refusedused 1 1 * * *

Agi,; (years) 3 1 * . 1 * * * * * * *

1 1-4 216 13 115 15 9 15 ? 3 15 1 5

7 16 5-11 200 7 96 11 12 14 5 25 1 ? 1 6 20 12-17 41 1 23 1 2 4 *

3

1 3 3 18-64 237 18 112 1.5 10 2.4 2 1 2.3 * ? 11 1.6 > 64 3 1 2 * * * *

Race White 568 34 274 37 30 49 ? 9 57 1 8 ? 21 44 Black 68 1 42 2 1 4

4 Asian 5 2 1

1 * *

1 Some Others 16 ? 9 *

2

1 * * *

3 His/Ganie 41 19

1 * ? 3 1 1

1 Re sed 2 2 * * * * . 619 36 309 41 29 49 4 10 59 1 7 2 23 49 Yes 77 5 36 1 4 8

2 r 1 2

1 r DK 3

2

1 * * * *

Refused 1

1 * * * * * * * * *

Employment 461 22 234 27 24 33 2 8 43 ? 7 ? 16 41 Full Time 149 9 73 7 7 16 1 17 2 6 8 Part Time 29 2 10 4 1 2 1 4 * *

2 3 Not Employed 60 7 3.1 4 ? 6 1 ? * *

1 Refused 1 1 * * * * * *

Education

461 22 234 2.7 24 33 ? 43 ? r ? 16 41 < High School 22 5 9

3 1 2 2 Hi81i School Graduate 73 .4 39 4 1 8 1

6

1

2 7 < ollege 66 2 34 6 2 6 2 6 *

1 4* Graduate 54 4 26 3 3 6 1 ? 7 * *

2 Post raduate 24 4 6 2 4 1 3

1

3

Census Northeas 124 8 60 8 5 7

4 16

1

6 9 Midwest 128 6 69 8 6 14

2 11

2

3 7 South 273 17 133 18 12 25 3 3 30

3 ? 6 21 West 175 10 86 8 11 11 1 3 9 2 3 12 19 Week eekday 445 35 216 27 22 40 3 10 . 37 2 6 2 17 28 Weekena 255 6 132 15 12 17 1 2 29

3 . 10 28 Season Winter 107 10 44 9 6 11 1 2 8 ? 1

4 9 Spring 240 8 113 21 14 22 1 3 25 2

12 19 Summer 262 12 146 5* 9 20 2 5 25

5 2 9 22 Fall 91 11 45 7 5 4

2 8

1

2 6 Asthma No 638 38 319 39 3.4 51 4 10 57 2 2 22 51 Yes 61 28 3

2 *

5 DK 1 1 * * * * * * *

699 40 348 42 57 1 12 6.6 2 9 2 27 56 DK 1 1 * * * * . * * * *

Bronchitis/Emphysema 679 11 339 41 3.4 54 4 \2 62 9 26 No ? ? 53 Yes 21 9 1 3

4

1 3 Note: "*" = Signifies missing data. "DK" = Don't know. Refused = refused to answer. N = Doer sample size in specified range of number of minutes A value of "121" for number of minutes signifies that more than 120 minutes were spent. Source: Tsana and leoeis. 1996.
Table 15-58. Number of.Minutes Spent Plavinr:i in Sand or Grav.el (minutes/day) Percentiles Cater:iory Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 659 0 0 0 0 0 0 45 120 121 121 121 121 Gender Male 334 0 0 0 0 0 0 45 120 121 121 121 121 Gender Female 324 0 0 0 0 0 1 60 120 121 121 121 121 Age (years) 1-4 203 0 0 0 0 0 0 30 120 121 121 121 121 Age (years) 5-11 193 0 0 0 0 0 3 60 121 121 121 121 121 Age (years) 12-17 40 0 0 0 0 0 0 45 120 121 121 121 121 Age (years) 18-64 219 0 0 0 0 0 0 45 120 121 121 121 121 Age (years) > 64 2 0 0 0 0 0 0 0 0 0 0 0 0 Race White 534 0 0 0 0 0 0 50 120 121 121 121 121 Race Black 64 0 0 0 0 0 0 15 120 121 121 121 121 Race Asian 5 0 0 0 0 0 30 60 121 121 121 121 121 Race Some Others 15 0 0 0 0 0 0 60 121 121 121 121 121 Race Hispanic 39 0 0 0 0 0 15 60 121 121 121 121 121 . Hispanic No 583 0 0 0 0 0 0 45 120 121 121 121 121 Hispanic Yes 72 0 0 0 0 0 1.5 60 120 121 121 121 121 Employment Full Time 140 0 0 0 0 0 0 45 105 121 121 121 121 Employment Part Time 27 0 0 0 0 0 10 60 121 121 121 121 121 Employment Not Employed 53 0 0 0 0 0 0 30 120 121 121 121 121 Education < High School 17 0 0 0 0 0 0 60 121 121 121 121 121 Education High School Graduate 69 0 0 0 0 0 0 30 121 121 121 121 121 Education <College 64 0 0 0 0 0 0 37.5 120 121 121 121 121 Education College Graduate 50 0 0 0 0 0 0 30 60 60 121 121 121 Education Post Graduate 20 0 0 0 0 0 15 60 120 120 120 120 120 Census Region Northeast 116 0 0 0 0 0 0 60 120 121 121 121 121 Census Region Midwest 122 0 0 0 0 0 0 30 60 121 121 121 121 Census Region South 256 0 0 0 0 0 0 45 120 121 121 121 121 Census Region West 165 0 0 0 0 0 0 60 121 121 121 121 121 Day of Week Weekday 410 0 0 0 0 0 0 40 120 121 121 121 121 Day of Week Weekend 249 0 0 0 0 0 0 60 121 121 121 121 121 Season Winter 97 0 0 0 0 *o 5 45 120 121 121 121 121 Season Spring 232 0 0 0 0 0 1 52.5 120 121 121 121 121 Season Summer 250 0 0 0 0 0 0 60 120 121 121 121 121 Season Fall 80 0 0 0 0 0 0 30 105 121 121 121 121 Asthma No 600 0 0 0 0 0 0 45 120 121 121 121 121 Asthma Yes 58 0 0 0 0 0 3 60 120 121 121 121 121 Angina No 659 0 0 0 0 0 0 45 120 121 121 121 121 Bronchitis/emphysema No 638 0 0 0 0 0 0 45 120 121 121 121 121 Bronchitis/emphysema Yes 21 0 0 0 0 0 30 60 121 121 121 121 121 NOTE: A value of "121" for number of minutes signifies that more than 120 minutes were spent. are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996 N = doer sample size. Percentiles Table 15-59. Number of Minutes Spent Playing in Outdoors on Sand, Gravel, Dirt, or Grass When Fill Dirt Was Present bv the Number of Resoondents Minutes/Dav Total N *
0-0 0-10 10-20 20-30 30-40 40-50 50-60 70-80 80-90 110-120 121 Overall 700 53 380 51 29 48 1 6 60 7 1 21 43 Gender

Male 352 26 183 22 18 33 3 24 5 1 16 21 Female 347 27 196 29 .1 1_5 1 3.6 ? § 2.2 Refused 1 1 *

Agt; (years) 3 *

1 * * *

1 * *

1 1-4 216 11 118 14 10 13 1 4 18 4

7 16 5-11 200 15 103 14 8 15 1 17 1

9 v 12-17 41 3 19 3 2 7

4 1

2 18-64 237 23 138 \9 \3

1 2.0 1 1 >64 3 1 2

Race

White 568 40 317 40 21 38 5 48 5 1 15 38 Black 68 33 § t 6

J 7 1 2 Asian 5 2 2 * *

1 Some Others 16

10 1 2 1 1

1 * * *

HisRianic 41 § 17 5 1

1 1 * ? Re sed 2 1

1 * *

619 45 345 42 21 44 1 6 54 5 1 17 38 Yes 77 32 * \? 2

1 § DK 3 * * *

Refused 1 * *

1 * * * * * *

Employment 461 29 240 32 20 35 1 5 40 6

18 35 yrne 1f 11 91 1 12 1 1 5 art 1me 4 17

2 1 Not EmP.loyed 60 8 3.2 1 * * \? * * * ? Refusea 1 1 * * * *

Edycation 461 29 240 3.2 20 35 1 40 \?

18 35 < High School 22 5 9

3 2 * .1 2 Hi81i School Graduate 6 44 7 2 *

7 1 1 1 1 < ollege

4 38 7 3

1 7 3 Colle?,;e Graduate 54 3 35 3 1 1 *

3 * *

t Post raduate 24 6 14 2 *

1 *

1 Census * *

Northeas 124 6 70 13 3 5 18 1 2 6 Midwest 128 12 77 6 7 10

1 7 2

2 4 w,uth tH 153 17 12 tg

1

11 est 80 15 7 1 1 6 oawofWeek eekdaY, 445 235 21 li 1 2 1 10 Weekena 255 145 8 4 11 Season *

Winter 107 14 153\ 6 160 5 2 7 2 2 12 Spring 240 10 17 20 1 2 21 2

10 13 Summer 262 17 143 19 12 19 1 25 2 1 8 15 Fall 91 12 52 9 1 4

1 7 1 1 3 Asthma No 638 48 354 47 25 41 1 5 50 I 1 19 40 Yes 61 § 25 1 4 I 1 \0 t DK 1 1 * * *

699 5.3 5.1 2.9 4.8 1 \? 6.0 6 . 1 2.1 4.3 DK 1 1

Bronchitis/Emphysema 679 52 368 5.1 28 46 1 5 57 I 1 2.1 42 No Yes 21 1 12 1 2 1 3

1 Note: "*" Signifies missing data. "DK"k = Respondents answered don't know. Refused = Respondents refused to answer. N = Doer sample size in specified range of number of minutes spent. A value of "121" for number of minutes signifies that more than 120 minutes were spent. Source: Tsana and Kleoeis 1996.

Table 15-60. Number of Minutes Soent Plavino on Sand, Gravel, Dirt, or Grass When Fill Dirt Was Present (minutes/day) Percentiles Cateaorv Pooulation Groun N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 647 0 0 0 0 0 0 30 100 121 121 121 121 Gender Male 326 0 0 0 0 0 0 30 120 121 121 121 121 Gender Female 320 0 0 0 0 0 0 30 60 121 121 121 121 Age (years) 1-4 205 0 0 0 0 0 0 30 120 121 121 121 121 Age (years) 5-11 185 0 0 0 0 0 0 30 120 121 121 121 121 Age (years) 12-17 38 0 0 0 0 0 0.5 30 60 120 120 120 120 Age (years) 18-64 214 0 0 0 0 0 0 15 60 120 121 121 121 Age (years) > 64 2 0 0 0 0 0 0 0 0 0 0 0 0 Race White 528 0 0 0 0 0 0 30 120 121 121 121 121 Race Black 60 0 0 0 0 0 0 30 74 120 121 121 121 Race Asian 5 0 0 0 0 0 30 30 121 121 121 121 121 Race Some Others 16 0 0 *O 0 0 0 20 40 60 60 60 60 Race Hispanic 36 0 0 0 0 0 1 60 120 121 121 121 121 Hispanic. No 574 0 0 0 0 0 0 30 90 121 121 121 121 Hispanic Yes 69 0 0 0 0 0 1 30 120 121 121 121 121 Employment Full Time 138 0 0 0 0 0 0 15 60 120 121 121 121 Employment Part Time 25 0 0 0 0 0 0 10 60 60 121 121 121 Employment Not Employed 52 0 0 0 0 0 0 10 60 60 121 121 121 Education < High School 17 0 0 0 0 0 0 60 121 121 121 121 121 Education High School Graduate 67 0 0 0 0 0 0 10 60 88 120 121 121 Education <College 62 0 0 0 0 0 0 15 60 60 121 121 121 Education College Graduate 51 0 0 0 0 0 0 15 30 60 121 121 121 Education Post Graduate 18 0 0 0 0 0 0 0 60 120 120 120 120 Census Region Northeast 118 0 0 0 o. 0 0 30 60 121 121 121 121 Census Region Midwest 116 0 0 0 0 0 0 20 60 120 121 121 121 Census Region South 250 0 0 0, 0 0 0 30* 90 121 121 121-121 Census Region West 163 0 0 0 0 0 1 60 121 121 121 121 121 Day of Week Weekday 406 0 0 0 0 0 0 30 88 121 121 121 121 Day of Week Weekend 241 0 0 0 0 0 0 30 120 121 121 121 121 Season Winter 93 0 0 0 0 0 0 45 121 121 121 121 121 Season Spring 230 0 0 0 0 0 0 30 105 121 121 121 121 Season Summer 245 0 0 0 0 0 0 30 90 121 121 121 121 Season Fall 79 0 0 0 0 0 0 10 60 120 121 121 121 Asthma No 590 0 0 0 0 0 0 30 110 121 121 121 121 Asthma Yes 56 0 0 0 0 0 10 60 60 121 121 121 121 Angina No 646 0 0 0 0 0 0 30 100 121 121 121 121 Bronchitis/Emphysema No 627 0 0 0 0 0 0 30 120 121 121 121 121 Bronchitis/Emphysema Yes 20 0 0 0 0 0 0 37.5 60 90.5 121 121 121 NOTE: A value of "121" for number of minutes signifies that more than 120 minutes were spent. are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996 N = doer sample size. Percentiles Table .15-61. Range of the Time Spent Working in a Garden or Other Circumstances in a Month by the Number of Respondents Hours/Month Total N *

0-0 0-24 24-48 48-72 72-96 96-120 120-144-168-192-216-240-264-312-144 168 192 216 240 264 288 312 336 Overall 4663 91 2928 1312 145 81 28 23 1 10 5 12 8 3 1 1 14 Gender

Male 2163 38 1309 628 77 41 16 9 1 8 4 10 § 2 1 11 Female 2498 5.3 1618 683 40 1.2 \4 ? 1 ? 1 1 Refused 2 1 1 * * * *

Ag!? (years) 84 11 51 17

2 2 1 * * * * * * * *

1-4 263 7 189 55 4 3 ? ?

1 * * * * * *

5-11 348 7 225 100 9 4

1 * *

1

1 12-17 326 5 236 75 6 1

1 *

1 1 * *

18-64 2972 37 1813 900 97 52 16 16 1 7 1 8 § * * \3 >64 670 24 414 165 29 19 8 3 2 2 3

1 Race White 3774 59 2303. 1128 127 69 22 2.1 1 7 4 11 7 1 1 10 Black 463 9 351 77 9 § ? 1

1 ? Asian 77 1 50 25 1 * * * * * *

Some Others 96 2 64 23 2 2 1 *

1

1 * * * *

HisJEanic 193 6 126 50 5 1 ? 1 * * * * * * * ? Re sed 60 14 34 9 1 1 1 * * * * * * * * / 4244 65 2669 1206 135 73 25 20 1 8 1.2 § 1 1 12 Yes 347 11 218 94 6 1 ? DK 26 1 18 5 1

1 * * * * *

Refused 46 14 23 7 1 1 * * * * * * * * *

Employment 926 19 638 230 20 8 2 3 . 1 2 1 *

1

1 Full Time 2017 18 1235 600 68 35 12 9 1 7 1 10 § 2

11 Part Time 379 4 234 120 9 3 2 4 ? * * * *

1 Not EmP.loyed 1309 39 808 354 4,.8 3.5 1J I * ? 1

1

1 1 Refusea 32 11 13 8 * * *

Edl}cation 1021 34 699 246 22 8 3 3

1 ? 1 *

1

1 < High School 399 18 263 86 11 9 4 4

1 1 * *

2 Higti School 1253 25 770 355 41 22 9 7

5 ? 8 4 *

1 4 Graduate 895 11 545 265 33 18 6 3

1 ? 1 *

4 <College 650 1 406 200 19 12 3 5

1 1 *

2 Colle?,;e Graduate 445 2 245 160 19 12 3 1 1 1 * * * * *

1 Post raduate Census * *

Northeas 1048 17 714 259 24 12 4 8 2 1 1

3 Midwest 1036 23 687 273 19 18 5 3 *

3 *

2 South 1601 35 989 446 64 26 11 7 1 4 4 3 6

1 4 West 978 16 538 334 38 25 8 5

3 1 4 1 *

5 oawotweek eekday 3156 62 1982 890 96 54 18 15 1 8 3 6 7 2

1 11 Weekena 1507 29 946 422 49 27 10 8 2 2 6 1 1 1 3 Season * *

Winter 1264 9 1038 171 20 9 5 3 2 2 2

1 2 Spring 1181 29 614 434 50 20 8 7

4 1 4 5 2

3 Summer 1275 39 690 421 56 33 12 9 1 2 1 3 3 1 *

4 Fall 943 14 586 286 19 19 3 4 2 1 3 *

1 .

5 Asthma No 4287 70 2697 1206 135 77 27 2.3 1 10 1J 6 1 1 13 Yes 341 6 216 101 10 1 1 * ? 1 DK 35 15 15 5 * * * * * * . * *

4500 74 2825 1277 143 77 2.8 21 1 1.0 1.2 § 1 1 14 Yes 125 4 86 29 1 3 ? * *

DK 38 13 17 6 1 1 * * * * * * * * *

Bronchitis/emphysema 4424 72 2766 1265 140 77 27 22 1 1.0 \2 § 1 1 1.4 No Yes 203 5 146 43 5 2 1 1

DK 36 14 16 4

2 * * * * * * * * *

Note:

Signifies missing data. DK = respondents answered don't know. Refused = respondents refused to answer. N = doer sample size in range of number of minutes spent. ource: Tsariq and Kleoeis,1996 Table 15-62. Number of Hours Spent Working with Soil in a Garden or Other Circumstances Workini::i (hours/month) Percentiles Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 4572 0 0 0 0 0 -0 3 15 40 88 160 320 Gender Male 2125 0 0 0 0 0 0 3 20 50 150 230 320 Gender Female 2445 0 0 0 0 0 0 2 12 30 60 90 320 Age (years) 1-4 256 0. 0 0 0 0 0 1 7 20 60 120 150 Age (years) 5-11 341 0 0 0 0 0 0 2 10 20 50 60 320 Age (years) 12-17 321 0 0 0 0 0 0 1 5 10 40 60 200 Age (years) 18-64 2935 0 0 0 0 0 0 3 16 40 90 200 320 Age (years) >64 646 0 0 0 0 0 0 3 25 60 90 160 300 Race White 3715 0 0 0 0 0 0 3 16 40 88 160 320 Race Black 454 0 0 0 0 0 0 0 8 30 60 160 320 Race Asian 76 0 0. 0 0 0 0 1.5 6 15 24 40 40 Race Some Others 94 0 0 0 0 0 0 2 15 60 150 200 200 Race Hispanic 187 0 0 0 0 0 0 2 12 25 90 320 320 Hispanic No 4179 0 0 0 0 0 0 3 15 40 80 180 320 Hispanic Yes 336 0 0 0 0 0 0 2 15 32 90 120 320 Employment Full Time 1999 0 0 0 0 0 0 4 20 45 144 240 320 Employment Part Time. 375 0 0 0 0 0 0 3. 12 32 90 120 320 Employment Not Employed 1270 0 0 0 0 0 0 3 20 45 64 100 320 Education < High School 381 0 0 0 0 0 0 2 16 60 120 160 320 Education High School Grad 1228 0 0 0 0 0 0 3.5 20 50 120 200 320 Education <College 884 0 0 0 0 0 0 4 20 40 90 240 320 Education College Grad. 649 0 0 0 0 0 0 3 16 40 70 *100 320 Education Post Grad. 443 0 0 0 0 0 0 5 20 40 61 90 320 Census Region Northeast 1031 0 0 0 0 0 0 1 10 30 90 120 320 Census Region Midwest 1013 0 0 0 0 0 0 2 10 30 60 120 320 Census Region South 1566 0 0 0 0 0 0 3 18 40 90 180 320 Census Region West 962 0 0 0 0 0 0 5 20 50 90 200 320 Day of Week Weekday . 3094 0 0 0 0 0 0 3 15 40 80 160 320 Day of Week Weekend 1478 0 0 0 0 0 0 3 15 40 90 150 320 Season Winter 1255 0 0 0 0 0 0 0 4 12 50 90 320 Season Spring 1152 0 0 0 0 0 0 5 20 45 110 200 320 Season Summer 1236 0 0 0 0 0 0 5 25 50 96 160 320 Season Fall 929 0 0 0 0 0 0 3 10 30 88 180 320 Asthma No 4217 0 0 0 0 0 0 3 15 40 90 160 320 Asthma Yes 335 0 0 0 0 0 0 2 12 30 60 80 320 Angina No 4426 0 0 0 0 0 0 3 15 40 88 160 320 Angina Yes 121 0 0 0 0 0 0 2 7 24 60 110 120 Bronchitis/Emphysema No 4352 0 0 0 0 0 0 3 15 40 88 180 320 Bronchitis/Emphysema Yes 198 0 0 0 0 0 0 1 7 24 60 80 100 Note:

Signifies missing data. DK = respondents answered don't know. Refused = respondents refused to answer. N = doer sample size. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996.
Table 15-63. Range of Number of Minutes Spent Playing on Grass in a Day by the Number of Respondents Minutes/Day Total *-* 0-0 0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100-110-121-N 100 110 120 121 Overall 700 43 79 49 49 85 7 11 125 1 1 21 1 2 66 160 Gender . . . Male 352 25 35 23 25 41 3 5 64 1 12 1 33 84 Female 347 1_8 4.4 2.6 24 4.4 4 6.1 1 . 1 1 33 75 Refused 1 . . . . 1 Ag-; (years) 3 . . 1 1 . . . . . . . * . . 1 1-4 216 10 24 19 21 25 1 4 35 . 1 8 . 1 18 49 5-11 200 15 24 10 10 19 ? 3 38 1 8 1 20 49 12-17 41 2 5 1 2 8 1 8 . 1 . 8 5 18-64 237 16 2.6 18 \5 32 1 4.4 * . 1 . 1 z.o 54 > 64 3 . . 1 * . . 2 Race White 568 36 65 40 39 58 ? 9 98 1 1 17 1 1 56 139 Black 68 4 6 ? 14 1 15 ? 11 Asian 5 . 1 3 . . . . . . 1 Some Others 16 . 4 . 1 1 * . 4 * . 1 . . 2 3 41 4 5 f ? . * . . 1 . 1 Re sed 2 . 1 . 1 . . . . 619 38 65 44 42 73 6 1.1 110 1 1 18 1 1 62 146 Yes 77 1.3 7 11 1 14 . . 1 4 13 DK 3 . 1 . 1 * . * . 1 Refused 1 . 1 * . * * . . . * . * .
Employment 461 27 54 31 34 52 3 8 81 1 1 17 1 1 46 104 Full Time 149 8 16 12 10 21 25 2 13 36 Part Time 29 2 5 1 1 6 4 . . ? . . 3 5 Not EmP,loyed 60 5 1 1 1 . 1.5 * . . 1 4 1.5 Refuse a 1 1 . . . . *

461 27 54 31 34 52 81 1 1 17 1 1 46 104 < High School 22 2 2 1 1 4 3 . 1 3 5 Hi8ti School Graduate 73 4 8 9 4 6 1 1 9 * . . . 6 . 22 < allege 66 2 7 4 6 13 2 . 20 * . * . 3 9 Collee,e Graduate 54 3 5 3 1 6 1 1 10 . * . .

6 15 Post raduate 24 5 3 1 4 1 2 .

1 . . 2 5 Census Northeas 124 5 14 10 4 13 . 3 26 . . 2 1 . 10 36 Midwest 128 8 7 10 10 15 1 3 23 . 1 4 . . 15 31 South 273 21 22 20 25 30 5 4 52 1 11 . ? 23 57 West 175 9 36 9 10 27 1 1 24 . 4

18 36 oawofweek . eekdaY. 445 33 55 35 32 55 3 7 82 1 15 1 1 38 87 Weekena 255 10 24 14 17 30 4 4 43 1 6 1 28 73 Season . . . . . Winter 107 12 22 6 6 15 2 15 5 5 19 Spring 240 9 23 16 13 28 1 5 49 . . 7 1 1 26 61 Summer 262 12 20 20 18 36 2 5 48 1 . 7 . 1 29 63 Fall 91 10 14 7 12 6 2 1 13 1 2 . 6 17 Asthma No 638 38 73 46 44 78 ? 9 114 1 1 18 1 2 60 146 Yes 61 5 l ? 10 . . . 1.4 DK 1 .

1 * . .

699 4.3 7.9 49 48 8.5 7 11 1?5 1 1 2.1 1 ? DK 1 . 1 . . . Bronchitis/emphysema 679 4.3 76 4.9 47 83 l 1.1 120 1 1 20 1 ? 65 153 No Yes 21 3 2 2 5 1 1 7 NOTE: A value of "121" for number of minutes signifies that more than 120 minutes were spent. N =doer sample size. Percentiles are the percentage of doers below or equal to a given number of minutes. Refused = respondent refused to answer. Source: Tsano and Kleoeis 1996.

Table 15-64. Number of Minutes Spent Playing on Grass (minutes/day) Percentiles Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 657 0 0 0 0 20 60 120 121 121 121 121 121 Gender Male 327 0 0 0 0 20 60 121 121 121 121 121 121 Gender Female 329 0 0 0 0 15 60 120 121 121 121 121 121 Age (years) 1-4 206 0 0 0 0 15 60 120 121 121 121 121 121 Age (years) 5-11 185 0 0 0 0 30 60 121 121 121 121 121 121 Age (years) 12-17 39 0 0 0 0 30 60 120 121 121 121 121 121 Age (years) 18-64 221 0 0 0 0 20 60 120 121 121 121 121 121 Age (years) >64 3 30 30 30 30 30 121 121 121 121 121 121 121 Race White 532 0 0 0 0 20 60 121 121 121 121 121 121 Race "Black 65 0 0 0 3 20 58 90 121 121 121 121 121 Race Asian 5 10 10 10 10 30 30 30 121 121 121 121 121 Race Some Others 16 0 0 0 0 10 60 120 121 121 121 121 121 Race Hispanic 37 0 0 0 0 30 60 110 121 121 121 121 121 Hispanic No 581 0 0 0 0 20 60 121 121 121 121 121 121 Hispanic Yes 72 0 0 0 0 10 35 100 121 121 121 121 121 Employment Full Time 141 0 0 0 0 20 60 121 121 121 121 121 121 Employment Part Time 27 0 0 0 0 15 60 120 121 121 121 121 121 Employment Not Employed 55 0 0 0 5 23 60 121 121 121 121 121 121 Education < High School 26 0 0 0 5 30 60 120.5 121 121 121 121 121 Education High School Graduate 69 0 0 0 0 15 60 121 121 121 121 121 121 Education <College 64 0 0 0 0 17.5 46.5 60 121 121 121 121 121 Education College Graduate 51 0 0 0 1 30 60 121 121 121 121 121 121 Education Post Graduate 19 0 0 0 0 25 60 121 121 121 121 121 121 Census Region Northeast 119 0 0 0 0 30 60 121 121 121 121 121 121 Census Region Midwest 120 0 0 0 7.5 30 60 121 121 121 121 121 121 Census Region South 252 0 0 0 1 20 60 120 121 121 121 121 121 Census Region West 166 0 0 0 0 10 45 120 121 121 121 121 121 Day of Week Weekday 412 0 0 0 0 15 60 120 121 121 121 121 121 Day of Week Weekend 245 0 0 0 1 30 60 121 121 121 121 121 121 Season Winter 95 0 0 0 0 4 30 120 121 121 121 121 121 Season. Spring 231 0 0 0 1 30 60 121 121 121 121 121 121 Season Summer 250 0 0 0 1.5 30 60 121 121 121 121 121 121 Season Fall 81 0 0 0 0 10 35 120 121 121 121 121 121 Asthma No 600 0 0 0 0 20 60 120 121 121 121 121 121 Asthma Yes 56 0 0 0 0 22.5 60 120.5 121 121 121 121 121 Angina No 656 0 0 0 0 20 60 120 121 121 121 121 121 Bronchitis/Emphysema No 636 0 0 0 0 20 60 120 121 121 121 121 121 Bronchitis/Emphvsema Yes 21 0 0 0 0 30 60 121 121 121 121 121 121 NOTE: A value of "121" for number of minutes signifies that more than 120 minutes were spent. N = doer sample size. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996 -
Table 15-65. Number of Times Swimming in a Month in Freshwater Swimming Pool by the Number of Respondents Times/Month Total N 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Overall 653 147 94 73 47 42 26 11 26 2 38 3 27 *2 2 27 2 Gender 17
Male 300 62 47 37 20 16 5 9 ? 16 2 . 13 1 16 1 Female 352 8.5 17 3.6 2/ 2;,6 § 1/ 2.2 1 1.4 1 1 1.1 1 Refused 1

1 Agi; (years) 8 2 2 1 1 1 1 * * * * * * * * *

1-4 63 11 14 7 3 3 4 1 3 1 4

2 1 1 2

5-11 100 16 15 7 9 6 4 2 4 7

5 11 ? 12-17 84 21 13 7 4 8 4 2 3 1 8

1 *

2 18-64 360 86 48 50 27 22 . 11 5 14 18 15 1 1 10 * >64 38 11 2 1 3 2 2 1 2

1 4 2

Race White 555 126 74 64 14 32 2.5 1.0 23 ? 3.6 1 2 ? 21 1 Black 30 8 7 1 2 1 ? * ? 1 Asian 13 3 ? 2

1

1 1

1 1 *

Some Others 12 2 2 2 1 * * * *

4

His/i'..anic 35 5 8 1 § 1

l

1 * * * *

Re sed 8 3 3 * * * . * * * * *

591 135 81 68 44 35 25 10 25 ? 36 24 1 ? 24 ? Yes 55. 1.0 1) 9 2 6 1 1 1 ? 1 DK 2 1 1 . * *

Refused 5 2 2 * * * * * . * * * * * *

Employment 243. 47 41 21 17 15 12 5 10 .2 18

8 1 1 15 ? Full Time 240 56 38 38 15 13 \0 3 8

10 1 8 1 1 6 Part Time 43 13 2 4 3 8 1 1

4 ? 2 1

No} EmP,loyed 122 30 12 1.0 1.2 § 3 ? ? ** § *

9

Re usea 5 1 1 1 * * * *

Education *

215J 5;;' 43 231 1.8 v 1.f \1 ? 1.9 1 1 1.5 ? < High School 2 1 School Graduate 112 28 15 16 11 6 5 1 1

5 1 5

1 3 * < allege 104 29 11 11 2 9 2 7

4 1 7

3

Collee:,e Graduate 93 22 H 14 10 2 3 2

5 6 *

4

Post raduate 71 15 8 6 5 3 1 4

5

1 1

2

Census * *

H8 19 16 4 1 i 1 8 J ? 4 1dwest 7 2

4

South 235 46 36 29 13 15 1l 7 10 ? 10 ? 8 * ? West 152 34 22 17 10 12 1 8 6 7 *

8 oawofWeek eekday 445 97 67 52 36 25 15 9 14 1 24 2 18 ? ? 21 1 Weekena 208 50 27 21 11 17 11 2 12 1 14 1 9 6 1 Season * * * * *

Winter 62 19 12 5 3 1 2 .5 2 1 3 Spring 174 55 25 19 13 9 7 3 7

8

7 *

2 1 356.( 41 21 266 1.f ? 2l ? \4 ? ? 214 1 8 Asthma No 590 81 67 43 38 25 . 10 24 ? y 25 ? ? 22 ? Yes 56 11 5 3 1 1 ? ? DK 7 1 2 1 1 ** * * * * *

639 143 90 7.3 17 41 2.6 10 2.6 2 3/ 2/ ? 2 26 ? Yes 8 3 1 1 1 * .. 1 DK 6 1 3 * * * *

1 * * * *

Bronchitis/Emphysema 621 138 91 71 45 40 215 10 24 ? 3.8 2 27 ? ? 25 ? No Yes 26 8 1 ? 1 ? 1 1 1 * ? DK 6 1 2 1 1 * * * * ..

Table 15-65. Number of Times Swimming in a Month in Freshwater Swimming Pool by the Number of Respondents (continued) Times/Month 18 20 23 24 25 26 28 29 30 31 32 40 42 45 50 60 DK Overall 2 25 1 1 9 2 1 1 26 2 1 2 2 1 1 2 5 Gender . . . . . . Male 10 4 ? 1 10 ? 1 1 1 . 4 Female ? 1.5 1 1 § 1 1.6 . 1 1 1 1 ? 1 Refused . . . . . Ag\1 (years) . . . . . . . . . . ** . . . . . . 1-t . 2 . . . . . 1 2 . 1 . . . . . . 5-1 . 3 . 1 ? . . 5 . . *. . 1 . . 12-17 1 4 . 1 . . 2 . . . . . 1 1 18-64 15 1 . I 1 1 . 15 ? . ? 1 1 . . 3 >64 1 1 . . 2 . 1 . 1 1 Race . . White ? 19 1 1 ? 1 1 19 ? 1 ? ? ? § Black 3 . . . Asian . 1 . . . . . . . . . . . . . . Some Others . . . . . . . . . . . . . 1 . . His/Ganie . 1 . . . . . . 3 . . . . 1 . . Re .sed . 1 . . . . . . 1 . . . . . . . ? 23 1 1 9 ? 1 1 20 ? 1 ? ? . 1 ? 4 6f<S 1 . . . 1 1 . . . . . . . . . . . . . Refused . 1 . . . . . . . . . . . . . . . Employment 1 9 . 1 2 1 . 1 9 . 1 . . . 1 1 1 Full Time . 5 1 10 ? ?* 1 1 ? Part Time . . . 1 . . 1 . . . 1 7 1 . 1 1 . . . . . 1 . . 1 1 1 . . . . . . . . 1 Ed\,!cation 1 11 . 1 ? ? . 1 9 . 1 . . . 1 1 1 < High School 1 . . 1 . . . . Hi8ti School Graduate . 6 . . 1 . . . 4 . . . 1 . . 1 1 < allege . 3 1 . 4 . . . 4 . . . 1 . 2 Graduate . 2 . ? . . . 3 ? . 1 . . 1 est raduate 1 2 . . . 1 . 5 . . . . Census . . . . . . . . . . Northeas 7 *2 1 2 1 1 1 1 Midwest . 4 . . 1 . . 4 . 1 . . . South ? 7 1 1 4 . 1 1 9 1 . 1 . 1 1 1 West 7 2 1 . 11 1 . 1 . 1 oawofWeek . . . eekday 1 18 1 1 7 1 1 19 1 1 1 1 2 4 Weekena 1 *7 . 2 1 . 1 7 2 1 2 . 1 Season . . . . . . . . . . . Winter 1 3 1 1 1 1 Spring 8 . . 2 . 3 . . 1 . 1 1 2 1 10 1 1 I 1 . 1 21 1 1 ? 1 1 all 4 . .2 . . Asthma . ? 21 1 1 1 1 1 23 ? 1 ? ? 1 ? § 3 2 1 DK . 1 . . . . . 1 . . . . . . . ? 24 1 1 ? 1 1 2.6 ? 1 ? 1 1 1 ? § Yes . . . 1 DK . 1 . . . . . . . . . . . . . . Bronchitis/Emphysema ? 22 1 1 ? 1 1 23 ? 1 ? ? 1 1 ? 4 No Yes 2 . 1 DK . 1 . . . . . . . . . . . . . Note:

Sfsnifies missing "DK" = respondent answered don't know; Source: sana And Klebeis 996 N= sample size; Refused = respondent refused to answer.
Table 15-66. Range of the Average Amount of Time Actually Spent in the Water by Swimmers by the Number of Respondents Minutes/Month Total 0-10-20-30-40-50-60-70-80-90-110-150-180-181-N *-* 10 20 30 40 50 60 70 80 90 100 120 150 180 181 Overall 653 13 62 75 120 20 39 131 *8 2 31 2 68 10 32 40 Gender Male 300 5 31 38 60 6 17 55 3 . 18 1 28 6 17 15 Female 352 7 31 37 60 14 22 76 5 2 13 1 40 4 15 25 Refused 1 1 . . . . . . . . . . . . . . Ag<<; (years) 8 1 2 1 2 . . . . . . . 2 . . . 1-4 63 3 5 12 12 . 1 4 8 . . 2 . 7 1 3 5 5-11 100 5 3 2 12 5 4 25 . . 7
16 2 11 8 12-17 84 1 3 7 10 2 6 15 . 1 8 1 14 4 6 6 18-64 360 3 45 50 75 8 22 74 8

13 1 26 3 12 20 >64 38

4 3 9 4 3 9 . 1 1 . 3 *

1 Race White 555 7 53 67 105 18 3.6 109 8 2 24 2 59 9 26 30 Black 30 3 1 1 4

8 *

5

1 1 1 5 Asian 13 . 1 1 3 1

4 .

1 .. 1 *

1 Some Others 12 . 1 2 1 *

3 * * *

2 *

1 2 35 1 5 4 4 1 2 7 *

1

4

4 2 Re used 8 2 1

3

1 . * * * . 1 . *

591 11 57 67 108 19 35 120 8 2 29 2 62 9 28 34 Yes 55 1 5 8 10 1 3 10 .

2 . 5 1 4 5 DK 2 . . * * * . 1 * * * * * .

1 Refused 5 1 *

2

1. * * * .

1 * * . Employment 243 9 11 20 34 8 13 48

1 16 1 37 7 19 19 Full Time 240 3 31 29 51 4 14 51 3

8 . 21 3 10 12 Part Time 43 . 3 10 12 1 3 2 1

5

2 .

4 Not Employed 122 1 16 1.6 21 7 8 30 4 1 2 1 7

3 5 Refused 5

1 2

1 * * * .

1 * *

Education

257 9 13 22 35 8 1.5 50

1 17 1 39 7 20 20 < High School 16

4 2 3

3 1

1 * * *

2 Hi8h School Graduate 112 1 12 10 16 5 8 26 1 1 5 1 11 . 5 10 < allege 104 2 15 16 27 2 4 20 3

4 6 1 2 2 Graduate 93 1 8 15 21 2 6 17 1

1

10 2 4 5 Post raduate 71

10 10 18 3 6 15 2

3

2

1 1 Census Northeas 136 2 12 17 28 5 9 20 3 1 4

13 3 9 10 Midwest 130 3 10 17 27 4 8 24 1

6

17 1 7 5 South 235 20 19 37 6 15 56

13 1 26 4 12 18 West 152 20 22 28 5 7 31 4 1 8 1 12 2 4 7 DawofWeek eekday 445 11 45 52 82 14 23 87 7 2 19

46 8 22 27 Weekena 208 2 17 23 38 6 16 44 1

12 2 22 2 10 13 Season Winter 62 2 6 6 10 5 3 14 .

3 1 7 1 1 3 Spring 174 3 21 24 37 7 12 32

2 6 1 13 3 6 7 Summer 363 7 29 36 64 6 20 77 6

20

44 6 23 25 -Fall 54 1 6 9 9 2 4 8 2

2

4

2 5 Asthma No 590 12 52 71 114 \9 33 117 2 26 ? 64 9 26 35 Yes 56 1 9 3 4 5 14

5 3 1 6 5 DK 7

1 1 2 1 1 . * * *

1 * *

639 13 6.o .73 118 19 37 130 2 30 ? 66 10 32 39 Yes 8 * ? 1 1 1 1

1 1 * *

DK 6

2 1 1 * * * *

1 *

1 Bronchitis/emphysema 621 13 56 72 115 19 37 123 r 2 31 2 67 .. 10 30 37 No Yes 26

5 4 1 1 7 * * . * . 2 3 DK 6

1 1 1 . 1 1 * .

1 * *

Note:

Signifies data. DK = respondents answered don't know. Ref= respondents refused to answer. N = doer sample size in range of num er of minutes spent. Values of 120 , 150 , and 180 for number of minutes signify that 2 hours, 2.5 hours, an 3 hours, respectively, were sJ'ent. Source: Tsana and Klepeis 199 .
Table 15-67. Number of Minutes Spent Swimming in a Month in Freshwater Swimming Pool (minutes/month) Percentiles Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 640 2 3 10 15 30 60 90 180 181 181 181 181 Gender Male 295 3 4 8 10 30 45 90 180 181 181 181 181 Gender Female 345 2 3 10 15 30 60 90 180 181 181 181 181 Age (years) 1-4 60 3 3 7.5 15 20 42.5 120 180 181 181 181 181 Age (years) 5-11 95 2 3 20 30 45 60 120 180 181 181 181 181 Age (years) 12-17 83 4 5 15 20 40 60 120 180 181 181 181 181 Age (years) 18-64 357 2 3 5 10 20 45 60 120 181 181 181 181 Age (years) >64 38 5 5 8 10 30 40" 60 120 120 181 181 181 Race White 548 2 3 10 15 30 45 90 180 181 181 181 181 Race Black 27 10 10 15 30 60 60 150 181 181 181 181 181 Race Asian 13 4 4 4 20 30 60 60 120 181 181 181 181 Race Some Others 12 2 2 2 15 25 60 150 181 181 181 181 181 Race Hispanic 34 3 3 5 10 20 60 120 180 181 181 181 181 Hispanic No 580 2 3 10 15 30 60 90 180 181 181 181 181 Hispanic Yes 54 3 5 5 15 30 52.5 120 180 181 181 181 181 Employment Full Time 237 3 4 5 10 20 45 60 150 181 181 181 181 Employment Part Time 43 2 2 5 15 20 30 90 120 181 181 181 181 Employment Not Employed 121 2 2 8 10 20 45 60 120 180 181 181 181 Education < High School 16 1 1 1 2 12.5 30 60.5 181 181 181 181 181 Education High School Graduate 111 3 5 8 10 30 60 90 180 181 181 181 181 Education <College 102 3 3 5 10 20 30 60 120 120 180 181 181 Education College Graduate 92 2 3 10 15 22.5 42.5 60.5 150 181 181 181 181 Education Post Graduate 71 5 10 10 10 20 30 60 70 120 180 181 181 Census Region Northeast 134 4 8 10 15 30 45 120 180 181 181 181 181 Census Region Midwest 127 5 5 10 15 30 45 90 150 180 181 181 181 Census Region South 227 2 3 5 15 30 60 120 180 181 181 181 181 Census Region West 152 2 3 5 10 20 45 61 120 180 181 181 181 Day of Week Weekday 434 2 3 8 10 30 60 90 180 181 181 181 181 Day of Week Weekend 206 4 5 10 15 30 60 90 180 181 181 181 181 Season Winter 60 2 3 5 12.5 30 52.5 90 120 180.5 181 181 181 Season Spring 171 2 4 5 10 20 40 60 120 180 181 181 181 Season Summer 356 3 3 10 15 30 60 120 180 181 181 181 181 Season Fall 53 2 10 10 10 20 45 70 180 181 181 181 181 Asthma No 578 2 3 10 15 30 55 90 180 181 181 181 181 Asthma Yes 55 2 3 4 10 30 60 120 180 181 181 181 181 Angina No 626 2 3 10 15 30 60 90 180 181 181 181 181 Angina Yes 8 15 15 15 15 25 42.5 75 120 120 120 120 120 Bronchitis/Emphysema No 608 3 3 10 15 30 60 90 180 181 181 181 181 Bronchitis/Emphysema Yes 26 2 2 5 5 15 42.5 60 181 181 181 181 181 Note: A Value of 181 for number of minutes signifies that more than 180 minutes were spent. the percentage of doers below or equal to a given number of minutes. N = doer sample size. Percentiles are Source: Tsana and Kleoeis 1996. Table 15-68. Statistics for 24-Hour Cumulative Number of Minutes Spent Workina in a Main Job Percentiles Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 All 3259 475.909 179.067 3.1367 1 1440 120 395 500 570 660 740 840 930 Gender Male 1733 492.305 186.996 4.4919 1 1440 120 417 510 595 690 770 890 955 Gender Female 1526 457.288 167.74 4.294 2 1440 120 390 485 543 620 690 785 850 Age (years) . 80 472.375 183.298 20.4933 5 940 117.5 377.5 482.5 560 672.5 850 900 940 Age (years) 1-4 3 16.667 11.547 6.6667 10 30 10 10 10 30 30 30 30 30 Age (years) 5-11 10 150.4 185.796 58.754 2 550 2 10 67.5 264 447.5 550 550 550 Age (years) 12-17 38 293.158 180.681 29.3103 5 840 15 185 269 390 510 675 840 840 Age (years) 18-64 2993 484.822 173.083 3.1638 1 1440 140 420 505 570 660 745 840 930 Age (years) > 64 135 366.148 208.656 17.9582 5 990 30 185 395 500 600 660 840 940 Race . White 2630 477.536 179.01 3.4906 1 1440 120 400 500 570 660 735 845 933 Race Black 343 466.551 175.989 9.5025 5 1037 105 390 490 550 655 735 880 990 Race Asian 57 464.053 177.305 23.4846 5 870 45 390 493 553 660 750 780 870 Race Some Others 56 477.411 181.661 24.2754 45 855 75 415 510 570 680 765 780 855 Race Hispanic 125 465.88 185.322 16.5757 2 840 95 360 485 580 720 750 825 840 Race Refused 48 492.083 191.623 27.6584 50 957 120 410 507.5 575 810 840 957 957 Hispanic No 2980 475.393 179.214 3.2829 1 1440 120 395 500 570 660 740 850 940 Hispanic Yes 221 481.493 174.32 11.726 2 1106 150 405 505 580 670 740 825 840 Hispanic DK 12 529.583 146.226 42.2117 295 757 295 425 554 610 710 757 757 757 Hispanic Refused 46 468.522 201.347 29.687 10 860 115 350 497.5 585 780 818 860 860 Employment . 47 257.915 202.833 29.5863 2 840 5 65 245 390 540 625 840 840 Employment Full Time 2679 504.35 164.818 3.1843 1 1440 180 450 510 582 675 750 855 950 Employment Part Time 395 364.587 159.361 8.0183 5 945 80 250 365 480 540 600 675 795 Employment Not Employed 112 270.946 216.024 20.4123 4 990 9 82.5 245 377.5 600 675 795 870 Employment Refused 26 513.577 155.456 30.4875 170 840 225 440 510 570 778 790 840 840 Education . 108 343.037 211.879 20.3881 2 860 10 176.5 342.5 510 610 675 840 840 Education < High School 217 473.502 216.729 14.7125 4 1440 85 360 485 568 710 795 940 1080 Education High School Graduate 1045 482.03 180.638 5.5879 1 1440 120 405 500 565 670 765 890 979 Education <College 795 475.585 174.025 6.172 2 1440 140 409 495 563 648 750 825 905 Education College Graduate 627 484.526 159.816 6.3824 5 1005 120 424 510 570 645 720 765 815 Education Post Graduate 467 483.041 169.574 7.847 1 945 125 400 510 590 660 730 810 860 Census Region Northeast 721 475.964 180.84 6.7348 1 1440 120 405 495 570 669 740 890 950 Census Region Midwest 755 477.008 182.167 6.6297 2 1440 120 395 495 570 660 750 825 940 Census Region South 1142 478.231 176.739 5.23 1 1440 105 405 505 570 660 735 840 900 Census Region West 641 470.415 177.801 7.0227 5 1080 120 390 500 570 657 730 850 880 Day Of Week Weekday 2788 487.858 166.167 3.147 1 1440 155 425 505 570 660 740 840 930 Day Of Week Weekend 471 405.18 229.526 10.576 2 1440. 30 245 415 555 670 770 870 960 Season Winter 864 475.784 172.828 5.8797 5 1440 150 390 495 570 660 735 835 900 Season Spring 791 472.972 195.425 6.9485 1 1440 75 390 495 570 670 765 850 915 Season Summer 910 477.185 179.907 5.9639 1 1215 120 400 500 565 670 750 890 979 Season Fall 694 477.739 165.961 6.2998 2 1005 130 405 510 570 645 720 780 840 Asthma No 3042 477.013 176.967 3.2086 1 1440 120 400 500 570 660 740 840 930 Asthma Yes 195 453.354 204.227 14.625 5 1440 45 345 480 550 668 793 855 979 Asthma DK 22 523.182 216.952 46.2542 170 1215 225 430 500 565 780 860 1215 1215 Angina No 3192 475.735 178.389 3.1574 1 1440 120 395 500 570 660 740 840 930 Angina Yes 44 472.068 200.68 30.2536 10 990 60 386 500 572.5 679 730 990 990 Angina DK 23 507.391 230.296 48.02 80 1215 170 430 500 565 780 860 1215 1215 Bronchitis/Emphysema No 3120 476.547 178.194 3.1902 1 1440 120 400 500 570 660 740 840 930 Bronchitis/Emphysema Yes 116 446.991 189.381 17.5836 5 985 30 367.5 480 557.5 644 720 800 855 Bronchitis/Emphysema DK 23 535.217 226.256 47.1777 170 1215 225 430 500 600 860 875 1215 1215 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused= Refused data. N =doer sample size. Mean= Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Stderr = standard error. Min = minimum number of minutes. Max= maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsann and Kleneis 1996. Table 15-69. Statistics for 24-Hour Cumulative Number of Minutes Spent in Food Preparation Percentiles Category Population Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 4278 52.35 52.877 0.8084 1 555 5 20 35 65 115 150 210 265 Gender Male 1342 37.77 42.133 1.1501 1 480 5 13 30 50 80 105 150 210 Gender Female 2936 59.02 55.872 1.0311 1 555 5 25 45 75 120 155 224 272 Age (years) . 94 52 43.217 4.4575 5 215 5 20 40 60 110 150 195 215 Age (years) 1-4 24 56.46 60.37 12.3229 5 240 5 22.5 30 75 150 180 240 240 Age (years) 5-11 60 25.17 29.688 3.8327 1 120 2 5 11 30 60 107 120 120 Age (years) 12-17 131 21.7 37.69 3.293 1 385 2 5 10 30 55 70 90 90 Age (years) 18-64 '3173 52.07 52.872 0.9386 1 555 5 20 35 65 110 145 210 265 Age (years) > 64 796 60.5 54.669 1.9377 1 525 5 25 45 80 120 150 240 270 Race White 3584 51.62 53.259 0.8896 1 555 5 19 .35 65 110 145 210 265 Race Black 377 57.03 52.289 2.693 1 390 5 20 40 75 120 150 210 240 Race Asian 62 54 41.822 5.3115 2 210 5 20 50 70 105 130 175 210 Race Some Others 66 50.59 53.237 6.553 1 295 5 15 33.5 70 115 150 210 295 Race Hispanic 132 58.76 49.73 4.3285 2 315 5 23.5 52.5 79.5 110 135 225 285 Race Refused 57 53.14 49.297 6.5295 2 210 5 20 40 60 120 180 195 21.0 Hispanic No 3960 51.84 52.603 0.8359 1 555 5 20 35 65 111 145 205 255 Hispanic Yes 254 58.99 56.694 3.5573 2 420 5 20 45 75 120 155 *240 315 Hispanic DK 20 54.95 53.2 11.8959 6 240 8 25 45 60 112.5 180 240 240 Hispanic Refused 44 58.61 53.296 8.0346 2 210 5 27.5 37.5 80 150 180 210 210 Employment . 210 27.17 40.549 2.7981 1 385 2 5 15 30 60 90 120 180 Employment Full Time 1988 45.46 46.66 1.0465 1 480 5 15 30 60 90 130 180 240 Employment Part Time 419 53.85 55.413 2.7071 2 520 5 20 40 65 105 125 205 255 Employment Not Employed 1626 63.62 57.743 1.432 1 555 5 29 45 90 . 125 170 240 275 Employment Refused 35 53.54 66.78 11.2879 2 340 2 20 30 60 120 195 340 340 Education . . 291 31.71 42.621 2.4985 1 385 2 5 15 37 75 120 155 195 Education < High School 450 61.26 53.232 2.5094 1 555 5 30 45 90 120 150 197 225 Education High School Graduate 1449 58.84 56.665 1.4886 1 520 5 22 45 75 120 155 240 310 Education <College 954 51.99 52.238 1.6913 1 525 5 20 34.5 65 110 150 210 245 Education College Graduate 659 46.2 48.078 1.8728 1 515 5 15 30 60 100 125 180 224 Education Post Graduate 475 46.04 48.686 2.2339 1 375 5 15 30 60 95 135 200 270 Census Region Northeast 953 52.3 53.178 1.7226 1 480 5 20 40 60 110 140 205 255 Census Region Midwest 956 53.23 51.814 1.6758 1 520 5 20 35 65 120 150 210 265 Census Region South 1452 53.35 53.471 1.4032 1 555 5 15.5 35 70 120 150 195 245 Census Region West 917 49.91 52.72 1.741 1 515 5 15 31 60 105 135 225 265 Day Of Week Weekday 2995 50.05 49.979 0.9132 1 555 5 19 35 60 105 132 180 240 Day Of Week Weekend 1283 57.72 58.762 1.6405 1 420 5 20 40 75 130 180 240 300 Season Winter 1174 50.62 48.626 1.4192 1 480 5 18 35 65 110 135 195 240 Season Spring 1038 54.39 54.484 1.6911 1 525 5 20 38.5 70 120 150 224 265 Season Summer 1147 51.34 54.194 1.6002 1 555 5 20 35 60 110 137 208 300 Season Fall 919 53.54 54.535 1.7989 1 520 5 20 37 67 120 155 200 265 Asthma No 3948 52.02 53.176 0.8463 1 555 5 20 35 65 110 145 210 265 Asthma Yes 300 57.14 49.443 2.8546 1 272 5 20.5 45 75 120 160 199 240 Asthma DK 30 47.63 44.812 8.1815 2 195 5 10 32.5 60 117.5 120 195 195 Angina No 4091 52.18 52.97 0.8282 1 555 5 20 35 65 115 150 210 265 Angina Yes 149 56.81 48.238 3.9518 1 340 5 25 45 80 120 135 180 210 Angina DK 38 53.97 60.417 9.8009 2 240 2 10 32.5 60 120 240 240 240 Bronchitis/Emphysema No 4024 52.01 53.092 0.837 1 555 5 20 35 65 110 145 210 265 Bronchitis/Emphysema Yes 216 56.91 46.683 3.1764 3 240 5 20 45 85 120 150 198 210 Bronchitis/Emphysema DK 38 62.39 61.703 10.0096 2 240 2 20 42.5 90 150 240 240 240 Note: A"*" Signifies missing data. "DK" =The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsann and Kleneis 1996. Table 15-70. Statistics for 24-Hour Cumulative Number of Minutes Spent in Food Cleanup Percentiles Group Name Group Code N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 1143 32.9948 40.379 1.1944 1 825 8 15 30 35 60 85 120 135 Gender Male 204 27.4951 20.398 1.4282 1 180 10 15 25 30 50 60 80 85 Gender Female 939 34.1896 43.44 1.4176 1 825 5 15 30 35 60 90 120 150 Age (years} . 24 31.0417 28.013 5.7182 10 120 10 15 30 30 60 105 120 120 Age (years} 1-4 5 41.6 48.04 21.4839 3 120 3 15 15 55 120 120 120 120 Age (years} 5-11 9 28.4444 21.634 7.2113 1 75 1 15 30 30 75 75 75 75 Age (years} 12-17 28 26.75 20.573 3.8879 2 90 5 12.5 20 30 60 65 90 90 Age (years} 18-64 808 31.3317 27.053 0.9517 1 330 10 15 30 30 60 80* 120 120 Age (years} > 64 269 38.8067 67.357 4.1068 1 0825 5 15 30 40 60 105 130 270 Race White 976 32.9652 41.685 1.3343 1 825 8 15 30 35 60 84 120 130 Race Black 82 33.2805 28.602 3.1585 5 180 10 15 30 30 65 90 120 180 Race Asian 11 27.0909 22.047 6.6476 3 75 3 15 15 30 60 75 75 75 Race Some Others 17 29.7059 34.797 8.4396 5 150 5 10 15 30 60 150 150 150 Race Hispanic 42 35.6429 39.899 6.1565 3 255 10 15 30 40 50 60 255 255 Race Refused 15 34 28.234 7.2899 5 90 5 10 30 60 90 90 90 90 Hispanic No 1057 32.7351 40.353 1.2412 1 825 5 15 30 35 60 85 120 130 Hispanic Yes 68 38.9265 44.877 5.4422 3 270 10 15 30 40 60 120 255 270 Hispanic DK 6 24.1667 9.704 3.9616 10 35 10 15 27.5 30 35 35 35 35 Hispanic Refused 12 26.6667 18.257 5.2705 5 60 5 12.5 25 32.5 60 60 60 60 Employment . 39 28.1538 25.77 4.1265 1 120 2 15 15 30 65 90 120 120 Employment Full Time 432 28.4236 22.686 1.0915 2 255 8 15 25 30 50 60 90 120 Employment Part Time 134 28.903 21.322 1.842 3 150 10 15 25 30 60 60 95 100 Employment Not Employed 528 38.2254 53.763 2.3398 1 825 5 15 30 45 60 105 120 250 Employment Refused 10 28 21.884 6.9202 10 60 10 10 17.5 55 60 60 60 60 Education . 59 27.2542 22.695 2.9546 1 120 3 10 20 30 60 75 90 120 Education < High School 135 41.8593 58.603 5.0437 2 570 5 15 30 45 85 120 180 270 Education High School Graduate 445 33.3483 45.827 2.1724 1 825 10 15 30 30 60 90 120 120 Education <College 259 33.5907 30.026 1.8657 5 255 10 15 30 45 60 85 105 150 Education College Graduate 142 27.7254 21.846 1.8333 1 180 10 15 22.5 30 50 60 90 120 Education Post Graduate 103 28.9029 34.476 3.397 3 330 5 15 25 30 50 60 60 120 Census Region Northeast 295 32.6169 28.347 1.6504 3 270 5 15 30 40 60 90 120 120 Census Region Midwest 252 28.4643 22.677 1.4285 1 210 5 15 30 30 50 60 85 120 Census Region South 343 35.9242 52.496 2.8345 1 825 10 15 30 40 65 90 120 180 Census Region West 253 33.9763 46.539 2.9259 3 570 10 15 27 30 60 75 120 255 Day Of Week Weekday 782 32.1957 43.579 1.5584 1 825 8 15 30 30 60 75 120 120 Day Of Week Weekend 361 34.7258 32.371 1.7037 5 270 8 15 30 40 60 90 120 180 Season Winter 303 33.1188 51.809 2.9763 1 825 8 15 30 30 60 85 120 120 Season Spring 245 30.2939 26.108 1.668 2 250 10 15 30 30 60 65 105 120 Season Summer 293 33.157 29.932 1.7487 2 270 5 15 30 40 60 90 120 135 Season Fall 302 34.904 45.406 2.6128 1 570 8 15 30 40 60 90 120 180 Asthma No . 1047 32.7708 40.408 1.2488 1 825 6 15 30 35 60 85 120 120 Asthma Yes 91 35.956 40.996 4.2975 2 255 8 15 30 40 60 90 250 255 Asthma DK 5 26 20.736 9.2736 10 60 10 10 20 30 60 60 60 60 Angina No 1092 32.9661 40.95 1.2392 1 825 8 15 30 35 60 85 120 150 Angina Yes 45 32.3111 22.926 3.4175 5 120 5 15 30 45 60 60 120 120 Angina DK 6 43.3333 41.793 17.062 10 120 10 10 30 60 120 120 120 120 Bronchitis/Emphysema No 1065 31.77 28.195 0.864 1 330 8 15 .30 35 60 80 120 120 Bronchitis/Emphysema Yes 71 50.8592 118.417 14.0535 3 825 5 15 29 35 70 105 570 825 Bronchitis/Emphysema DK 7 38.1429 41.119 15.5417 2 120 2 10 30 60 120 120 120 120 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused= Refused data. N =doer sample size. Mean= Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Std err= standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleneis 1996. Table 15-71. Statistics for 24-Hour Cumulative Number of Minutes Soent Cleanina Hause Percentiles Category* Population Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 1910 114.798 111.683 2.5555 1 810 10 30 80 150 255 335 465 525 Gender Male 351 100.353 110.445 5.8951 1 810 10 30 60 120 240 310 400 495 Gender Female 1559 118.051 111.737 2.8299 1 790 15 40 90 160 255 340 465 540 Age (years) . 45 136.2 114.124 17.0127 10 480 10 55 105 180 297 320 480 480 Age (years) 1-4 11 74.091 69.42 20.9308 10 270 10 40 60 90 90 270 270 270 Age (years) 5-11 49 42.633 35.19 5.0271 1 180 5 20 30 53 90 120 180 180 Age (years) 12-17 67 78.746 79.357 9.695 1 300 5 20 55 105 240 240 285 300 Age (years) 18-64 1307 115.55 111.597 3.0868 1 810 15 30 85 150 270 350 435 510 Age (years) > 64 431 125.132 118.341 5.7003 3 790 10 45 90 170 250 340 540 570 Race White 1614 115.85 111.348 2.7716 1 790 10 35 85 155 255 330 435 540 Race Black 139 108.712 106.826 9.0609 1 490 5 30 80 135 270 358 480 484 Race Asian 32 97.656 101.091 17.8705 15 425 15 30 60 127.5 265 345 425 425 Race Some Others 26 80.5 58.059 11.3864 5 210 10 35 60 115 185 190 210 210 Race Hispanic 73 99.781 110.669 12.9528 5 548 10 30 60 120 210 345 470 548 Race Refused 26 179.615 176.878 34.6886 10 810 20 30 135 240 390 465 810 810 Hispanic No 1740 114.153 109.99 2.6368 1 790 10 30 80 150 255 330 435 525 Hispanic Yes 134 110.134 115.754 9.9996 5 658 10 34 60 135 240 360 480 548 Hispanic DK 14 136.071 131.591 35.1691 10 510 10 30 92.5 210 240 .510 510 510 Hispanic Refused 22 180.682 177 .33 37 .8069 10 810 20 45 138 240 340 390 810 810 Employment . 128 64.453 66.811 5.9053 1 300 5 22.5 45 77.5 180 240 270 285 Employment Full Time 673 100.944 99.87 3.8497 1 655 10 30 60 120 240 310 410 480 Employment Part Time 195 119.415 115.568 8.276 1 660 15 45 85 175 265 390 480 540 Employment Not Employed 901 129.566 118.009 3.9314 3 790 15 50 95 180 285 360 480 570 Employment Refused 13 235 218.908 60.7142 10 810 10 120 180 255 450 810 810 810 Education . 161 81.379 98.129 7.7337 1 810 5 28 45 100 225 265 300 375 Education < High School 234 135.731 121.618 7.9504 3 715 10 50 115 180 297 390 . 540 560 Education High School Graduate 665 121.899 118.814 4.6074 2 790 15 40 90 160 270 360 484 610 Education <College 432 108.343 100.456 4.8332 1 570 10 30 85 149 240 315 420 470 Education College Graduate 247 101.097 96.605 6.1468 1 525 15 30 60 127 240 315 390 465 Education Post Graduate 171 126.105 118.897 9.0923 5 655 15 45 90 180 280 390 495 540 Census Region Northeast 454 116.969 117.268 5.5037 2 790 10 30 90 164 240 330 480 655 Census Region Midwest 406 114.086 111.049 5.5113 1 720 10 30 80 150 240 325 475 495 Census Region South 636 114.36 112.921 4.4776 1 810 10 30 80 150 270 360 435 525 Census Region West 414 113.79 5.1228 5 720 .15 40 82.5 160 240 330 400 470 Day Of Week Weekday 1287 108.319 108.542 3.0256 1 790 10 30 70 150 240 315 465 540 Day Of Week Weekend 623 128.185 116.861 4.682 1 810 15 45 90 180 290 370 435 525 Season Winter 464 105.554 98.348 4.5657 1 810 10 30 75 150 240 285 360 465 Season Spring 445 114.202 109.757 5.203 3 720 15 30 75 165 240 340 465 525 Season Summer 546 109.908 113.686 4.8653 1 690 10 30 71 135 245 365 465 548 Season Fall 455 130.677 122.137 5.7259 1 790 15 45 90 180 300 390 480 560 Asthma No 1764 114.32 110.119 2.6219 1 790 10 30 82.5 150 255 330 450 525 Asthma Yes 133 114.699 117.523 10.1905 5 690 10 33 64 150 270 390 470 480 Asthma DK 13 180.769 214.533 59.5007 10 810 10 45 120 240 340 810 810 810 Angina No 1826 113.702 110.563 2.5874 1 790 14 30 80 150 255 330 465 525 Angina Yes 70 120.371 103.11 12.324 5 394 5 30 90 190 262.5 320 370 394 Angina DK 14 230 210.868 56.3569 10 810 10 120 210 255 480 810 810 810 Bronchitis/Emphysema No 1791 113.894 111.025 2.6234 1 790 10 30 80 150 255 340 450 540 Bronchitis/Emphysema Yes 100* 118.11 104.363 10.4363 5 480 7.5 32.5 90 180 262.5 297.5 467.5 475 Bronchitis/Emphysema DK 19 182.632 179.253 41.1234 5 810 5 50 150 240 340 810 810 810 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused= Refused data. N =doer sample size. Mean= Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Std err= standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleneis 1996. I I_ Table 15-72. Statistics for 24-Hour Cumulative Number of Minutes Soent in Outdoor Cleanina Percentiles Category Population Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 692 145.9 121.42 4.616 2 720 25 60 120 180 300 405 510 570 Gender Male 417 160.8 131.68 6.448 10 720 30 60 120 200 345 480 533 600 Gender Female 275 123.2 99.98 6.029 2 635 10 60 90 160 268 330 390 465 Age (years) . 13 210.5 157.91 43.796 30 600 30 112 140 250 395 600 600 600 Age (years) 1-4 4 138.3 116.84 . 58.421 30 285 30 45 119 231.5 285 285 285 285 Age (years) 5-11 12 104.6 62.921 18.164 30 210 30 58 80 165 190 210 210 210 Age (years) 12-17 20 142.3 96.274 21.527 30 385 32.5 75 127 157.5 300 372.5 385 385 Age (years) 18-64 479 147.4 125.22 5.721 2 690 15 60 120 180 310 435 520 570 Age (years) > 64 164 139.9 112.13 8.756 2 720 30 60 120 172.5 300 350 480 510 Race White 621 146.4 122.18 4.903 2 720 25 60 120 180 305 410 510 560 Race Black 30 134.2 99.049 18.084 2 405 10 60 117.5 190 262.5 330 405 405 Race Asian 6 65 27.568 11.255 30 90 30 30 77.5 85 90 90 90 90 Race Some Others 12 163.5 97.091 28.028 39 380 39 90 157.5 187.5 290 380 380 380 Race Hispanic 14 128.2 82.593 22.074 30 300 30 65 105 180 255 300 300 300 Race ' Refused 9 206.7 213.95 71.317 30 600 30 60 120 300 600 600 600 600 Hispanic No 652 145.6 121.19 4.746 2 720 25 60 120 180 300 405 510 560 Hispanic Yes 26 115.3 76.402 14.984 10 300 25 60 116.5 145 240 255 300 300 Hispanic DK 5 218 103.05 46.087 120 380 120 140 210 240 380 380 380 380 Hispanic Refused 9 216.7 206.64 68.88 60 600 60 60 120 300 600 600 600 600 Employment . 38 132.1 88.152 14.3 30 385 30 60 115 165 255 360 385 385 Employment Full Time 315 147.7 123.2 6.942 4 690 30 60 120 180 300 435 530 560 Employment Part Time 52 135.1 103.74 14.387 2 470 15 60 112.5 180 300 325 325 470 Employme*nt Not Employed 280 145.1 122.82 7.34 2 720 20 60 120 180 310 412.5 480 655 Employment Refused 7 252.9 216.41 81.794 15 600 15 120 120 465 600 600 600 600 Education . 46 136.8 115.99 17.101 2 600 30 60 112.5 165 285 360 600 600 Education < High School 96 146 124.59 12.716 2 510 10 60 119.5 180 330 465 480 510 Education High School Graduate 237 154.2 126.38 8.209 5 720 30 60 120 180 310 415 520 660 Education <College 142 146.7 119.87 10.059 4 655 30 60 120 185 270 375 560 570 Education College Graduate 99 137.3 124.43 12.505 10 555 15 60 95 175 325 475 533 555 Education Post Graduate 72 134.3 103.25 12.168 10 495 30 60 120 165 290 345 465 495 Census Region Northeast 144 135.2 113.42 9.451 5 600 15 60 110 185 300 330 510 555 Census Region Midwest 155 131 111.34 8.943 4 *555 15 60 95 150 270 360 510 560 Census Region South 218 158.7 117.58 7.964 2 635 30 70 120 195 330 415 510 520 Census Region West 175 151.8 138.65 10.481 2 720 25 60 . 120 180 355 ' 475 530 690 Day Of Week Weekday 420 132.5 109.32 5.334 4 660 20 60 105 175 285 360 475 530 Day Of Week Weekend 272 166.6 135.66 8.225 2 720 30 60 120 227.5 345 495 533 635 Season Winter 128 149.5 135.12 11.943 4 600 15 59.5 102.5 225 345 465 510 520 Season Spring 252 151.3 116.12 7.315 5 690 30 70 120 180 300 410 510 530 Season Summer 205 133 104.23 7.28 5 635 20 60 120 180 270 325 475 555 Season Fall 107 153.4 144.65 13.984 2 720 15 60 120 180 360 480 655 660 Asthma No 640 147.3 121.44 4.8 2 720 27.5 60 120 180 307.5 400 510 560 Asthma Yes 47 109.1 87.096 12.704 5 510 15 60 90 135 210 240 510 510 Asthma DK 5 312 230.04 102.879 60 600 60 120 300 480 600 600 600 600 Angina No 665 143.6 118.92 4.611 2 720 25 60 120 180 300 385 510 560 Angina Yes 18 144.7 96.703 22.793 30 330 30 60 135 165 330 330 330 330 Angina DK 9 318.9 213.67 71.223 10 600 10 120 325 480 600 600 600 600 Bronchitis/emphysema No 661 146.2 120.68 4.694 2 720 30 60 120 180 300 395 510 560 Bronchitis/emphysema Yes 26 104.8 85.282 16.725 5 375 10 60 90 135 225 300 375 375 Bronchitis/emphysema DK 5* 312 230.04 102.879 60 600 60 120 300 480 600 600. 600 600 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused= Refused data. N =doer sample size. Mean= Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Std err= standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given .number of minutes. Source: Tsana and Kleneis 1996. Table 15-73. Statistics for 24-Hour Cumulative Number of Minutes Soent in Clothes Care Percentiles Category Population Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 893 79.479 73.355 2.455 2 535 10 30 60 118 175 210 300 375 Gender Male 117 72.248 67.028 6.197 5 360 7 20 60 90 150 210 300 335 Gender Female 776 80.57 74.241 2.665 2 535 10 30 . 60 120 180 225 300 375 Age (years)
10 59.5 34.757 10.991 15 120 15 25 60 90 105 120 120 120 Age (years) 1-4 4 70 94.251 47.126 5 210 5 17.5 32.5 122.5 210 210 210 210 Age (years) 5-11 11 39 33.856 10.208 2 92 2 5 30 60 90 92 92 92 Age (years) 12-17 21 37.476 39.447 . 8.608 3 150 5 10 20 60 80 120 150 150 Age (years) 18-64 702 80.474 74.354 2.806 2 535 10 28 60 120 180 210 300 360 Age (years) > 64 145 85.455 73.545 6.108 2 375 10 30 60 120 180 245 300 375 Race White 737 80.096 73.392 2.703 2 535 10 30 60 118 175 223 300 375 Race Black 99 68.636 65.289 6.562 5 300 5 15 45 110 165 210 240 300 Race Asian 7 107.857 48.807 18.447 60 210 60 80 90 ' 120 210 210 210 210 Race Some Others 10 62.4 39.09 12.361 18 120 18 21 65 90 120 120 120 120 Race Hispanic 33 92.879 78.01 13.58 5 265 5 20 90 150 210 225 265 265 Race Refused 7 100.714 166.018 62.749 15 475 15 20 45 60 475 475 475 475 Hispanic *No 836 78.248 72.306 2.501 2 535 10 30 60 115 165 210 300 360 Hispanic Yes 51 91.176 71.178 9.967 5 265 5 20 90 150 190 225 225 265 Hispanic DK 3 118.333 62.517 36.094 55 180 55 55 120 180 180 180 180 180 Hispanic Refused 3 185 251.942 145.459 20 475 20 20 60 475 475 475 475 475 Employment

34 43.412 46.313 7.943 2 210 3 10 30 60 92 150 210 210 Employment Full Time 402 73.443 73.706 3.676 2 535 5 20 60 100 155 223 300 360 Employment Part Time 116 80.724 68.545 6.364 2 335 10 30 67.5 117.5 180 225 240 330 Employment Not Employed 336 89.804 75.166 4.101 2 475 10 35 60 120 185 235 300 375 Employment Refused 5 87.4 74.725 33.418 2 180 2 45 60 150 180 180 180 180 Education

43 47.488 48.217 7.353 2 210 5 10 30 60 92 150 210 210 Education < High School 102 86.51 60.048 5.946 10 265 15 38 65 120 175 210 240 245 Education High School Graduate 337 85.19 82.249 4.48 2 535 10 30 60 120 180 240 375 445 Education <College 193 85.87 78.466 5.648 2 475 5 21 60 120 190 240 300 375 Education College Graduate 127 67.756 56.995 5.058 5 260 10 20 60 90 150 190. 225 225 Education Post Graduate 91 68.374 64.714 6.784 5 360 5 20 60 90 145 210 245 360 Census Region Northeast 222 76.905 67.875 4.555 2 535 10 30 60 120 150 200 245 300 Census Region Midwest 201 78.448 75.998 5.36 2 475 5 20 60 115 170 210 265 420 Census Region South 304 81.839 75.654 4.339 5 450 10 30 60 115 170 235 330 375 Census Region West 166 79.849 73.398 5.697 2 405 5 20 . 60 120 180 223 300 360 Day Of Week Weekday 607 75.853 72.909 2.959 2 475 5 25 60 105 160 210 300 375 Day Of Week Weekend 286 87.175 73.832 4.366 5 535 10 30 65 120 180 223 300 335 Season Winter 254 82.291 80.245 5.035 2 475 7 23 60 120 190 225 330 445 Season Spring 213 86.103 79.325 5.435 2 450 10 30 60 120 180 240 335 375 Season Summer 259 76.722 68.328 4.246 2 535 8 30 60 115 154 190 240 360 Season Fall 167 71.03 60.463 4.679 3 300 5 25 60 105 150 195 240 300 Asthma No 829 79.534 74.024 2.571 2 535 10 30 60 118 180 225 300 360 Asthma Yes 62 79.855 65.269 8.289 5 375 10 30 66.5 120 154 180 200 375 Asthma DK 2 45 21.213 15 30 60 30 30 45 60 60 60 60 60 Angina No 867 79.516 73.48 2.496 2 535 10 30 60 120 178 210 300 375 Angina Yes 22 81.591 75.756 16.151 5 335 10 30 60 120 155 195 335 335 Angina DK 4 60 24.495 12.247 30 90 30 45 60 75 90 90 90 90 Bronchitis/emphysema No 834 78.45 73.617 2.549 2 535 8 25 60 115 170 210 300* 375 Bronchitis/emphysema Yes 58 94.621 68.927 9.051 5 335 15 60 77.5 120 190 240 300 335 Bronchitis/emphysema DK 1 60 0 0 60 60 60 60 60 60 60 60 60 60 Note: A "*" Signifies missing data. "DK"= The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean->= Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleneis 1996.
Table 15-74. Statistics for 24-Hour Cumulative Number of Minutes Spent in Car Repair/Maintenance Percentiles Cateqorv Pooulation Grouo N Mean* Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 145 123.407 147.198 12.224 5 700 5 30 60 150 300 495 670 690 Gender Male 110 135.582 152.737 14.563 5 700 5 30 85 170 300 505 600 670 Gender Female .35 85.143 122.441 20.696 5 690 5 15 45 120 180 270 690 690 Age (years) . 1 60 . . 60 60 60 60 60 60 60 60 60 60 Age (years) 1-4 1 150 . . 150 150 150 150 150 150 150 150 150 150 Age (years) 5-11 1 300 . . 300 300 300 300 300 300 300 300 300 300 Age (years) 12-17 8 106.875 163.837 57.925 20 505 20 30 45 90 505 505 505 505 Age (years) 18-64 114 130.342 156.511 14.659 5 700 5 30 77.5 165 300 520 670 690 Age (years) > 64 20 83.5 68.347 15.283 10 300 12.5 30 70 120 150 240 300 300 Race White 112 139.607 158.66 14.992 5 700 10 30 90 175 300 520 670 690 Race Black 19 85.789 93.516 21.454 5 300 5 20 60 95 300 300 300 300 Race Asian* 2 10 7.071 5 5 15 5 5 10 15 15 15 15 15 Race Some Others 6 43.333 42.387 17.304 5 120 5 10 32.5 60 120 120 120 120 Race Hispanic 6 58 51.595 21.063 5 120 5 13 45 120 120 120 120 120 Hispanic No 133 123.617 144.993 12.573 5 700 5 30 80 150 300 495 670 690 Hispanic Yes 10 98.8 153.362 48.497 5 520 5 30 45 120 320 520 520 520 Hispanic DK 2 232.5 321.734 227.5 5 460 5 5 233 460 460 460 460 460 Employment . 10 130.5 156.87 49.607 20 505 20 30 52.5 150 402.5 505 505 505 Employment Full Time 77 122.091 150.192 17.116 5 700 5 30 60 165 300 520 670 700 Employment Part Time 12 123.167 138.769 40.059 8 495 8 40 72.5 150 270 495 495 495 Employment Not Employed 46 124.13 146.952 21.667 5 690 10 30 90 120 300 480 690 690 Education . 13 120 139.523 38.697 15 505 15 30 60 120 300 505 505 505 Education < High School 17 185.882 224.418 54.429 5 670 5 30 90 220 555 670 670 670 Education High School Graduate 50 111.52 128.261 18.139 5 690 5 30 67.5 120 270 350 585 690 Education <College 31 138.226 169.231 30.395 5 700 10 30 85 180 280 600 700. 700 Education College Graduate 20 93.25 99.344 22.214 10 300 10 15 45 135 285 300 300 300 Education Post Graduate 14 '103.429 97.566 26.076 5 300 5 30 75 120 300 300 300 300 Census Region Northeast 28 130.75 163.729 30.942 8 690 10 30 60 200 300 520 690 690 Census Region Midwest 31 149.839 173.193 31.106 10 670 10 45 90 120 350 600 670 670 Census Region South -45 106.778 131.409 19.589 5 700 5 30 60 120 240 300 700 700 Census Region West 41 116.659 132.206 20.647 5 505 5 30 60 120 300 460 505 505 Day Of Week Weekday 79 108.519 125.914 14.166 5 690 5 15 60 150 280 350 480 690 Day Of Week Weekend 66 141.227 168.477 20.738 5 700 10 45 82.5 150 495 555 670 700 Season Winter 49 130.673 167.715 23.959 5 690 5 30 60 165 350 600 690 690 Season Spring 39 136.667 156.042 24.987 5 700 5 45 85 150 300 555 700 700 Season Summer 35 121.514 137.704 23.276 5 505 5 30 60 150 300 480 505 505 Season Fall 22 86.727 87.502 18.655 5 300 8 10 70 120 240 270 300 300 Asthma No 137 117.657 139.579 11.925 5 700 5 30 60 120 300 495 600 690 Asthma Yes 8 221.875 235.553 83.281 15 670 15 30 150 365 670 670 670 670 Angina No 139 125.712 149.156 12.651 5 700 5 30 75 150 300 505 670 690 Angina Yes 5 51 72.921 32.611 5 180 5 15 20 35 180 180 180 180 Angina DK 1 165 . . 165 165 165 165 165 165 165 165 165 165 Bronchitis/Emphysema No 140 122.279 145.67 12.311 5 700 5 30 67.5 135 300 500 670 690 Bronchitis/Emphysema Yes 5 155 203.347 90.94 5 460 5 10 30 270 460 460 460 460 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". N =doer sample size. Mean= Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max =maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleneis 1996. Table 15-75. Statitstics for 24-Hour Cumulative Number of Minutes Snent in Other Renairs Percentiles Group Name Group Code N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 All 288 184.816 184.111 10.849 2 1080 10 36.5 120 300 425. 525 690 840 Gender Male 200 205.045 187.704 13.273 2 1080 10 60 150 327.5 460 555 680 810 Gender Female 88 138.841 167.784 17.886 3 900 5 17.5 72.5 192.5 360 425 750 900 Age (years) . 1 540 . . 540 540 540 540 540 540 540 540 540 540 Age (years) 5-11 3 66.667 55.076 31.798 10 120 10 10 70 120 120 120 120 120 Age (years) 12-17 14 119.5 103.383 27.63 15 345 15 30 90 180 285 345 345 345 Age (years) 18-64 221 198.471 192.928 12.978 2 1080 10 45 120 325 434 570 750 840 Age (years) > 64 49 141.878 146.868 20.981 2 526 10 30 75 209 390 480 526 526 Race White 264 186.367 184.944 11.382 2 1080 10 36.5 120 300 430 525 670 840 Race Black 13 150.385 207.961 57.678 10 750 10 30 90 120 390 750 750 750 Race Asian 3 321.667 89.489 51.667 270 425 270 270 270 425 425 425 425 425 Race Some Otliers 3 173.667 165.228 95.395 45 360 45 45 116 360 360 360 360 360 Race Hispanic 4 127.5 122.848 61.424 10 290 10 35 105 220 290 290 290 290 Race Refused 1 75 . . 75 75 75 75 75 75 75 75 75 75 Hispanic No 278 184.917 184.467 11.064 2 1080 10 35 120 300 425 525 690 840 Hispanic Yes 9 160.556 180.666 60.222 10 575 10 60 60 210 575 575 575 575 Hispanic DK 1 375 . . 375 375 375 375 375 375 375 375 375 375 Employment . 17 110.176 97.439 23.632 10 345 10 30 90 180 285 345 345 345 Employment Full Time 140 199.993 206.025 17.412 5 1080 8.5 60 120 297.5 470 600 840 900 Employment Part Time 27 167.963 153.74 29.587 5 490 10 25 120 302 390 434 490 490 Employment Not Employed 102 183.314 169.14 16.747 2 670 10 30 120 315 420 480 526 600 Employment Refused 2 61 83.439 59 2 120 2 2 61 120 120 120 120 120 Education . 18 110.722 94.558 22.287 10 345 10 30 90 180 285 345 345 345 Education < High School 23 214.348 215.017 44.834 15 900 30 45 120 360 480 490 900 900 Education High School Graduate 90 194.4 196.472 20.71 3 840 5 30 132.5 300 447 575 780 840 Education <College 64 202.156 200.764 25.095 2 1080 10 32.5 130 355 420 480 600 1080 Education College Graduate 54 169 154.537 21.03 5 525 10 60 97.5 270 425 490 510 525 Education Post Graduate 39 172.923 174.213 27.896 2 690 7 38 120 270 420 600 690 690 Census Region Northeast 55 166.164 181.344 24.452 3 840 5 30 75 210 415 525 600 840 Census Region Midwest 77 188.909 170.219 19.398 10 780 15 60 120 315 420 460 670 780 Census Region South 89 202.281 212.332 22.507 2 1080 10 30 120 315 480 570 900 1080 Census Region West 67 172.224 161.66 19.75 2 750 7 60 120 243 340 526 690 750 Day Of Week Weekday 188 178.213 171.94 12.54 2 780 10 42.5 110 300 430 490 600 750 Day Of Week Weekend 100 197.23 205.392 20.539 3 1080 5 32.5 145 296.5 420 585 870 990 Season Winter 62 167.097 172.076 21.854 3 600 5 15 90 300 445 490 540 600 Season Spring 65 203.123 216.629 26.87 5 900 10 45 120 300 480 670 840 900 Season Summer 95 180.442 182.013 18.674 2 1080 10 60 120 290 390 510 750 1080 Season Fall 66 189.727 164.551 20.255 2 600 10 55 120 330 420 435 600 600 Asthma No 264 180.33 183.699 11.306 2 1080 10 36.5 120 288.5 420 525 690 840 Asthma Yes 24 234.167 185.283 37.821 5 670 10 45 210 352.5 480 510 670 670 Angina No 281 179.687 175.258 10.455 2 900 10 30 120 295 420 490 670 780 Angina Yes 6 448.333 369.995 151.05 90 1080 90 100 410 600 1080 1080 1080 1080 Angina DK 1 45 . . 45 45 45 45 45 45 45 45 45 45 Bronchitis/emphysema No 276 184.681 185.591 11.171 2 1080 10 36.5 120 299 430 526 690 840 Bronchitis/emphysema Yes 12 187.917 152.591 44.049 5 405 5 45 165 350 360 405 405 405 Note: A.""*" Signifies data. "DK"= The respondent repljeq "don't know". Refused= Refus.ed dat.a .. N =doer sample Mean= Mean.24-hour cumulative number of minutes for doers.* Stdev =standard dev1at1on. Stderr =standard error. Mm= m1rnmum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleneis 1996. Table 15-76. Statistics for 24-Hour Cumulative Number of Minutes Spent in Plant Care Percentiles Category Population Group N Mean .Stdev Stderr Min Max 5 25 50 75 90 95 98 99 All 254 103.602 108.761 6.824 3 630 10 30 60 130 225 300 480 570 Gender Male 84 146.274 145.969 15.926 10 630 15 32.5 105 195 380 480 570 630 Gender Female 170 82.518 76.759 5.887 3 630 10 30 60 120 180 210 270 325 Age (years) . 4 51.25 24.622 12.311 15 70 15 37.5 60 65 70 70 70 70 Age (years) 5-11 5 121 120.955 54.093 35 330 35 60 60 120 330 330 330 330 Age (years) 12-17 3 51 61.262 35.369 3 120 3 3 30 120 120 120 . 120. 120 Age (years) 18-64 157 100.49 104.921 8.374 5 570 10 30 60 135 225 300 475 565 Age (years) > 64 85 112.647 118.439 12.846 5 630 10 35 75 135 240 280 630 630 Race White 233 102.124 106.695 6.99 3 630 10 30 60 120 225 300 480 570 Race Black 8 81.25 90.149 31.872 15 280 15 15 50 112.5 280 280 280 280 Race Asian 3 140 45.826 26.458 90 180 90 90 150 180 180 180 180 180 Race Some Others 2 137.5 187.383 132.5 5 270 5 5 138 270 270 270 270 270 Race Hispanic 6 164.167 209.796 85.649 15 565 15 15 90 210 565 565 565 565 Race Refused 2 95 49.497 35 60 130 60 60 95 130 130 130 130 130 Hispanic No 244 102.971 106.161 6.796 3 630 10 30 60 132.5 225 280 480 570 Hispanic Yes 7 149.286 195.521 73.9 15 565 15 15 60 210 565 565 565 565 Hispanic DK 1 60 . . 60 60 60 60 60 60 60 60 60 60 Hispanic Refused 2 42.5 24.749 17.5 25 60 25 25 42.5 60 60 60 60 60 Employment . 8 94.75 103.657 36.648 3 330 3 32.5 60 120 330 330 330 330 Employment Full Time 94 94.436 111.848 11.536 5 630 10 30 60 120 195 325 570 630 Employment Part Time 25 112.2 104.812 20.962 15 485 15 30 90 150 210 270 485 485 Employment Not Employed 124 108.387 108.655 9.758 5 630 10 40 72.5 127.5 240 270 480 565 Employment Refused 3 145 99.875 57.663 60 255 60 60 120 255 255 255 255 255 Education . 9 86.444 100.113 33.371 3 330 3 30 60 120 330 330 330 330 Education < High School 30 92.333 108.753 19.855 10 475 10 15 60 120 170 420 475 475 Education High School Graduate 93 87.656 95.248 . 9.877 5 565 10 30 60 120 180 255 480 565 Education <College 47 118.298 112.855 16.462 5 630 10 50 90 150 240 240 630 630 Ed.ucation College Graduate 35 139 107.818 18.225 15 485 15 55 120 195 280 325 485 485 Education Post Graduate 40 104.75 131.036 20.719 15 630 15 30 60 120 217.5 420 630 630 Census Region Northeast 55 116.055 116.677 15.733 3 485 10 30 70 150 250 420 480 485 Census Region Midwest 41 101.659 109.248 17.062 5 630 30 30 60 120 195 270 630 630 Census Region South 77 82.078 76.081 8.67 5 475 10 30 60 120 175 225 300 475 Census Region West 81 116.593 126.602 14.067 10 630 14 30 75 150 240 330 570 630 Day Of Week Weekday 170 104.559 105.561 8.096 3 630 14 30 60 130 225 280 480 565 Day Of Week Weekend 84 101.667 115.595 12.612 5 630 10 30 60 127.5 240 325 570 630 Season Winter 15 135.333 170.592 44.047 5 565 5 30 60 175 485 565 565 565 Season Spring 96 124.323 108.656 11.09 5 570 15 45 90 150 270 330 475 570 Season Summer 111 89.82 100.882 9.575 3 630 10 30 60 120 190 225 420 630 Season Fall 32 74.375 87.894 15.538 5 480 10 25 47.5 102.5 135 195 480 480 Asthma No 239 105 108.541 7.021 3 630 10 30 60 135 235 300 485 570 Asthma Yes 15 81.333 113.68 29.352 5 450 5 15 55 90 175 450 450 450 Angina No 240 103.083 107.762 6.956 3 630 10 30 60 125 225 290 480 570 Angina Yes 13 120.769 130.286 36.135 15 485 15 55 60 135 270 485 485 485 Angina DK 1 5 . . 5 5 5 5 5 5 5 5 5 5 Bronchitis/emphysema No 248 105.202 109.525 6.955 3 630 10 30 60 135 235 300 485 570 Bronchitis/emphysema Yes 6 37.5 24.238 9.895 5 60 5 15 42.5 60 60 60 60 60 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused= Refused data. N =doer sample size. Mean= Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleneis 1996. Table 15-77. Statistics for 24-Hour Cumulative Number of Minutes Spent in Animal Care Percentiles Category Population Group N Mean Stdev Stderr Min Ma.x 5 25 50 75 90 95 98 99 All 764 48.168 65.029 2.3527 1 760 5 10 30 60 120 155 230 312 Gender Male 282 57.291 81.786 4.8703 1 760 5 15. 30 65 120 180 308 340 Gender Female 482 42.83 52.182 2.3768 1 450 3 10 28.5 60 105 140 187 273 Age (years) . 13 37.462 38.606 10.7074 2 135 2 5 30 55 80 135 135 135 Age (years) 1-4 9 59.222 44.291 14.7637 3 140 3 30 60 90 140 140 140 140 Age (years) 5-11 27 47.296 43.1 8.2946 2 179 8 15 38 65 120 150 179 179 Age (years) 12-17 49 55.204 68.276 9.7537 3 308 5 10 25 90 175 180 308 308 Age (years) 18-64 530 45.928 66.581 2.8921 1 760 3 10 30 60 109 150 230 280 Age (years) > 64 136 54.824 64.527 5.5331 1 383 5 15 30 60 135 180 340 340 Race White 696 47.757 62.011 2c3505 1 760 4 10 30 60 120 155 240 312 Race Black 26 37.577 39.832 7.8117 1 145 1 10 25 45 120 120 145 145 Race Asian 5 30.4 21.87 9.7806 10 60 10 15 20 47 60 60 60 60 Race Some Others 12 100 193.567 55.878 5 690 5 17.5 30 65 205 690 690 690 Race Hispanic 17 37.765 44.992 10.9123 5 180 5 15 30 35 120 180 180 180 Race Refused 8 73.75 58.478 20.675 5 180 5 32.5 55 115 180 180 180 180 Hispanic No 712 47.81 61.479 2.304 1 760 4 10 30 60 120 151 230 308 Hispanic Yes 39 50.872 112.78 18.0593 2 690 3 10 20 35 120 180 690 690 Hispanic DK 6 50 77.071 31.4643 10 205 10 10 15 45 205 205 205 205 Hispanic Refused 7 67.857 62.039 23.4485 5 180 5 20 60 120 180 180 180 180 Employment . 86 51.221 56.803 .6.1252 2 308 5 15 30 70 120 175 240 308 Employment Full Time 376 44.918 71.458 3.6852 1 760 3 10 25 60 90 145 240 340 Employment Part Time 60 48.883 56.285 7.2664 3 230 5 12.5 20 60 152.5 176.5 205 230 Employment Not Employed 233 52.459 59.357 3.8886 1 383 5 15 30 60 120 180 273 330 Employment Refused 9 38.889 53.897 17.9656 5 180 5 20 30 30 180 180 180 180 Education . 98 52.347 57.02 5.7599 2 308 5 15 30 70 140 180 240 308 Education < High School 63 51.492 68.122 8.5825 1 383 5 15 30 60 120 225 273 383 Education High School Graduate 231 52.913 75.819 4.9885 1 760 5 10 30 70 120 165 245 330 Education <College 150 40.593 49.247 4.021 1 280 4 10 20 55 97.5 155 205 230 Education College Graduate 121 51.273 79.213 7.2012 1 690 3 15 30 60 110 135 340 340 Education Post Graduate 101 38.713 40.069 3.987 1 240 5 12 30 57 80 105 150 185 Census Region Northeast 171 39.789 44.88 3.432 1 273 3 10 25 60 90 120 205 245 Census Region Midwest 181 49.773 58.716 4.3644 1 330 4 14 30 60 120 180 240 312 Census Region South 247 51.389 75.022 4.7736 1 760 5 15 30 60 120 165 308 383 Census Region West 165 50.267 72.551 5.6481 1 690 3 10 30 60 120 155 210 340 Day Of Week Weekday 527 46.602 66.468 2.8954 1 760 4 10 30 60 115 155 195 280 Day Of Week Weekend 237 51.65 61.703 . 4.0081 . 1 383 5 15 30 60 120 180 273 330 Season Winter 221 44.62 66.372 4.4647 1 690 4 10 25 55 95 160 225 245 Season Spring 201 52.99 60.351 4.2568 1 340 5 15 30 60 120 175 240 330 Season Summer 216 51.426 76.405 5.1987 1 760 5 15 30 64 120 165 240 383 Season Fall 126 41.111 45.413 4.0457 1 280 3 10 25 60 110 135 180 180 Asthma No 705 48.401 65.505 2.4671 1 760 4 10 30 60 120 155 225 308 Asthma Yes 57 45.386 60.468 8.0091 1 330 5 10 30 55 105 195 240 330 Asthma DK 2 45 21.213 15 30 60 30 30 45 60 60 60 60 60 Angina No 734 47.834 64.308 2.3737 1 760 5 10 30 60 120 155 225 280 Angina Yes 27 58.704 85.601 16.474 2 340 3 15 30 60 135 330 340 340 Angina DK 3 35 22.913 13.2288 15 60 15 15 30 60 60 60 60 60 Bronchitis/emphysema No 718 48.357 65.56 2.4467 1 760 4 10 30 60 120 160 230 308 Bronchitis/emphysema Yes 43 45.395 58.522 8.9245 2 330 5 10 30 55 90 150 330 330 Bronchtis/emphysema DK 3 42.667 15.535 8.9691 30 60 30 30 38 60 60 60 60 60 Note: A "*" Signifies missing data. "DK" =The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min= minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996. Table 15-78. Statistics for 24-Hour Cumulative Number of Minutes Soent in Other Household Work Percentiles Group Name Grouo Code N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 1322 68.6354 98.697 2.7145 1 905 5 15 30 75 195 255 360 480 Gender Male 478 70.3661 101.833 4.6577 1 905 5 10 30 90 195 265 375 480 Gender Female 844 67.6552 96.923 3.3362 1 720 5 15 30 75 190 255 360 496 Age (years) . 21 93.4286 113.994 24.8756 4 403 5 15 30 180 225 300 403 403 Age (years) 1-4 15 57.1333 85.7 22.1277 1 290 1 6 25 60 230 290 290 290 Age (years) 5-11 56 24.9464 30.134 4.0269 1 150 2 5 12.5 30 60 90 120 150 Age (years) 12-17 84 39.4762 51.785 5.6502 1 230 2 5 16.5 50 120 150 210 230 Age (years) 18-64 918 71.2353 101.54 3.3513 1 905 5 15 30 90 195 265 375 540 Age (years) > 64 228 78.114 106.158 7.0305 1 665 5 14.5 30 90 225 295 420 480 Race White 1118 70.6977 98.015 2.9314 1 720 5 15 30 80 195 265 375 480 Race Black 102 46.1176 65.201 6.4558 1 300 3 1o 15 50 120 210 255 260 Race Asian 20 71.9 76.619 17.1324 1 315 1.5 22.5 60 105 162.5 260 315 315 Race Some Others 22 67.7727 190.288 40.5695 1 905 2 10 15 30 . 90 155 905 905 Race Hispanic 43 65.6512 118.419 18.0587 5 660 5 10 20 60 155 270 660 660 Race Refused 17 72.9412 108.744 26.3742 5 420 5 15 20 75 210 420 420 420 Hispanic No 1218 67.8342 93.324 2.674 1 720 5 15 30 75 195 255 358 420 Hispanic Yes 81 80.5185 159.202 17.6891 1 905 5 10 20 60 155 360 665 905 Hispanic DK 7 54.1429 74.627 28.2062 1 210 1 10 25 90 210 210 210 210 Hispanic Refused 16 75.8125 113.469 28.3673 5 420 5 15 25 82.5 233 420 420 420 Employment . 153 37.0196 52.694 4.2601 1 290 2 5 15 45 90 150 225 230 Employment Full Time 555 70.0342 103.005 4.3723 1 905 5 15 30 85 195 265 375 540 Employment Part Time 124 62.0726 86.315 7.7513 2 420 5 15 30 65 190 240 400 403 Employment Not Employed 482 78.3008 105.529 4.8067 1 685 5 15 30 100 224 270 420 575 Employment Refused 8 95.625 110.014 38.8959 5 300 5 17.5 32.5 180 300 300 300 300 Education . 175 42.7086 64.901 4.906 1 450 2 5 15 45 120 192 233 300 Education < High School 96 82.5313 114.62 11.6983 1 660 5 15 30 117.5 240 328 420 660 Education High School Graduate 418 75.5574 105.946 5.182 1 720 5 15 30 90 215 270 420 540 Education <College 290 71.3724 100.836 5.9213 1 905 5 15 30 100 192.5 270 330 375 Education College Graduate 196 73.6173 104.18 7.4414 1 600 5 15 30 85 190 330 400 585 Education Post Graduate 147 58.7007 81.662 6.7354 1 570 4 10 30 65 150 210 315 420 Census Region Northeast 307 62.8632 91.306 5.2111 1 665 5 15 30 63 180 255 360 400 Census Region Midwest 318 70.8679 98.179 5.5056 1 590 5 15 30 90 180 270 375 570 Census Region South 394 74.7056 106.703 5.3756 1 720 5 10 30 85 215 296 380 600 Census Region West 303 64.2475 95.504 5.4866 1 905 5 13 30 75 180 240 330 420 Day Of Week Weekday 857 71.5496 106.351 3.6329 1 905 5 10 30 85 210 295 380 570 Day Of Week Weekend 465 63.2645 82.596 3.8303 1 600 5 15 30 75 170 225 296 403 Season Winter 353 64.1558 91.547 4.8726 1 590 5 15 30 65 195 240 345 480 Season Spring 327 82.844 118.992 6.5803 1 905 5 15 30 115 240 305 420 585 Season Summer 391 62.1125 97.341 4.9227 1 685 5 10 30 60 160 255 400 570 Season Fall 251 66.5857 77.867 4.9149 1 480 *5 15 35 90 180 230 292 345 Asthma No 1211 67.8423 98.123 2.8197 1 905 5 15 30 75 190 255 360 480 Asthma Yes 103 75.6893 104.033 10.2507 1 575 5 15 30 100 210 240 400 480 Asthma DK 8 97.875 120.21 42.5006 5 300 5 15 17.5 206.5 300 300 300 300 Angina No 1269 68.2041 99.025 2.7798 1 905 5 15 30 75 190 255 375 496 Angina Yes 44 77.1364 86.104 12.9807 5 300 5 10 30 132.5 220 240 300 300 Angina DK 9 87.8889 116.368 38.7895 5 300 5 15 15 180 300 300 300 300 Bronchitis/Emphysema No 1247 67.8043* 97.936 2.7734 1 905 5 15 30 75 190 255 360 480 Bronchitis/Emphysema Yes 64 83.4844 111.726 13.9658 1 575 5 15 32.5 117.5 220 265 480 575 Bronchitis/Emphysema DK 11 76.4545 107.17 32.3131 5 300 5 15 20 180 233 300 300 300 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused= Refused data. N =doer sample size. Mean= Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max= maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleneis 1996. Table 15-79. Statistics for 24-Hour Cumulative Number of Minutes Spent in Indoor Playina Percentiles Category Population Group N Mean Stdev Stderr Min *Max 5 25 50 75 90 95 98 99 All 188 105 82.7 6.03 2 510 20 55 90 127.5 190 270 390 435 Gender Male 65 117 97.1 12 10 510 20 60 90 135 255 3a°O 435 510 Gender Female 123 99.5 73.8 6.65 2 420 20 55 76 120 190 225 340 375 Age (years) . 3 127 47.3 27.3 90 180 90 90 110 180 180 180 180 180 Age (years) 1-4 11 130 80.2 24.2 15 270 15 60 115 180 255 270 270 270 Age (years) 5-11 11 93.6 64.3 19.4 30 195 30 30 60 175 180 195 195 195 Age (years) 12-17 4 82.5 45 22.5 30 120 30 45 90 120 120 120 120 120 Age (years) 149 103 86 7.05 2 510 20 55 76 120 190 292 420 435 Age (years) >64 10 124 76.4 24.2 20 270 20 75 100 150 248 270 270 270 Race White 153 110 84.3 6.82 2 510 20 60 90 130 190 270 390 435 Race Black 13 95 84.8 23.5 15 255 15 30 60 180 220 255 255 255 Race Asian 5 71 56.8 25.4 10 150 10 30 60 105 150 150 150 150 Race Same Others 7 108 96.5 36.5 30 300 30 55 60 175 300 300 300 300 Race Hispanic 8 68.4 46.4 16.4 42 180 42 45 50 67.5 180 180 180 180 Race Refused 2 64 65.1 46 18 110 18 18 64 110 110 110 110 110 Hispanic No 172 107 83.9 6.4 2 510 20 60 90 132.5 190 270 390 435 Hispanic Yes 15 88.1 71.4 18.4 42 300 42 45 60 100 180 300 300 300 Hispanic Refused 1 110 .
110 110 110 110 110 110 110 110 110 110 Employment

26 108 69.9 13.7 15 270 30 55 105 160 195 255 270 270 Employment Full Time 74 102 95 11 2 510 15 45 70 125 195 300 435 510 Employment Part Time 20 124 74 16.6 30 340 36 60 120 165 200 280 340 340 Employment Not Employed 68 102 76 9.21 15 420 30 60 85 120 180 245 390 420 Education . 27 108 68.6 13.2 15 270 30 55 110 160 195 255 270 270 Education < High School 16 89.4 58.8 14.7 20 220 20 52.5 60 125 180 220 220 220 Education High School Graduate 59 102 83.6 10.9 2 435 20 55 75 135 180 340 375 435 Education <College 33 112 97.7 17 10 510 20 55 90 120 190 300 510 510 Education College Graduate 37 125 96.1 15.8 15 420 15 60 105 155 270 390 420 420 Education Post Graduate 16 72.5 40.4 10.1 10 150 10 37.5 65 102.5 120 150 150 150 Census Region Northeast 46 110 94.4 13.9 2 420 20 60 75 120 245 375 420 420 Census Region Midwest 40 111 75.8 12 15 340 17.5 50 95 175 193 256 340 340 Census Region South 64 100 73 9.13 10 435 30 52.5 87.5 127.5 180 225 270 435 Census Region West 38 102 92.2 15* 10 510 18 60 60 120 180 300 510 510 Day Of Week Weekday 128 99.4 71 6.27 2 435 20 55 90 120 180 245 300 340 Day Of Week Weekend 60 118 13 13.3 15 510 30 60 90 150 245 382.5 420 510 Season Winter 49 130 99.2 14.2 18 420 20 60 105 180 300 375 420 420 Season Spring 36 85.7 55.7 9.28 2 270 20 45 77.5 112.5 155 180 270 270 Season Summer 47 92.7 77 11.2 10 435 30 45 60 120 180 195 435 435 Season Fall 56 107 82.7 11 10 510 15 60 90 127.5 195 255 270 510 Asthma Na 174 107 84.1 6.38 2 510 20 55 90 130 190 270 390 435 Asthma* Yes 13 88.5 66.4 18.4 20 245 20 30 75 120 180 245 245 245 Asthma DK 1 110 *

110 110 110 110 110 110 110 110 110 110 Angina Na 184 104 80.7 5.95 2 510 20 55 90 122.5 190 270 375 435 Angina Yes 3 210 167 96.4 60 390 60 60 180 390 390 390 390 390 Angina DK 1 110 *

110 110 110 110 110 110 110 110 110 110 Bronchitis/emphysema No 177 107 83.5 6.27 2 510 20 60 90 130 190 270 390 435 Bronchitis/emphysema Yes 10 80.1 72.5 22.9 10 245 10 30 60 76 208 245 245 245 Bronchitis/emphysema DK 1 110 .

110 110 110 110 110 110 110 110 110 110 Note: A"*" Signifies missing data. "DK" =The respondent replied "don't know". Refused= Refused data. N =doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996.
Table 15-80. Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor Plavinq Percentiles Cateqory Population Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 59 97.373 95.372 12.416 5 435 15 45 60 110 210 360 420 435 Gender Male 26 108.192 94.783 18.588 15 360 15 60 75 135 280 345 360 360 Gender Female 33 88.848 96.425 16.785 5 435 5 45 60 100 150 420 435 435 Age (years) . 1 170 . . 170 170 170 170 170 170 170 170 170 170 Age (years) 1-4 4 83.25 89.66 44.83 15 210 15 20 54 146.5 210 210 210 210 Age (years) 5-11 9 148.333 144.265 48.088 5 360 5 55 60 280 360 360 360 360 Age (years) 12-17 1 15 . . 15 15 15 15 . 15 15 15 15 15 15 Age (years) 18-64 40 92.05 86.358 13.654 20 435 27.5 52.5 65 102.5 142.5 307 435 435 Age (years) > 64 4 52.5 15 7.5 30 60 30 45 60 60 60 60 60 60 Race White 50 93.94 90.208 12.757 5 420 15 45 60 100 202 345 390 420 Race Black 2 86.5 37.477 26.5 60 113 *60 60 86.5 113 113 113 113 113 Race Asian 1 100 . . 100 100 100 100 100 100 100 100 100 100 Race Some Others 1 30 . . 30 30 3Q 30 30 30 30 30 30 30 Race Hispanic 5 149 164.864 73.729 20 435 20 60 110 120 435 435 435 435 Hispanic No 51 93.333 89.747 12.567 5 420 15 45 60 100 194 345 360 420 Hispanic Yes 8 123.125 130.218 46.039 20 435 20 60 90 115 435 435 435 435 Employment . 15 123.533 124.379 32.115 5 360 5 15 60 210 345 360 360 360 Employment Full Time 15 67.2 30.887 7.975 20 135 20 45 60 85 113 135 135 135 Employment Part Time 7 87.714 54.129 20.459 30 194 30 60 60 110 194 194 194 194 Employment Not Employed 22 103.182 110.136 23.481 25 435 30 45 60 105 150 420 435 435 Education . 15 123.533 124.379 32.115 5 360 5 15 60 210 345 360 360 360 Education < High School 5 57 6.708 3 45 60 45 60 60 60 60 60 60 60 Education High School Graduate 10 148.5 150.482 47.586 30 435 30 60 95 135 427.5 435 435 435 Education <College 18 74.667 45.169 10.646 20 194 20 45 60 95 150 194 194 194 Education College Graduate 8 75.375 35.492 12.548 30 120 30 45 75 106.5 120 120 120 120 Education Post Graduate 3 58.333 24.664 14.24 30 75 30 30 70 75 75 75 75 75 Census Region Northeast 17 114.059 103.26 25.044 15 360 15 60 70 120 345 360 360 360 Census Region Midwest 12 78.583 32.354 9.34 30 150 30 60 65 97.5 113 150 150 150 Census Region South 15 109.667 109.536 28.282 30 420 30 30 60 135 280 420 420 420 Census Region West 15 81.2 107.674 27.801 5 '435 5 20 60 105 165 435 435 435 Day Of Week Weekday 42 86.81 79.211 . 12.223 5 360 15 30 60 100 165 280 360 360 Day Of Week Weekend 17 123.471 126.007 30.561 25 435 25 45 60 120 420 435 435 435 Season Winter 10 66.5 46.251 14.626 5 150 5 30 60 105 135 150 150 150 Season Spring 10 135.3 114.735 36.283 45 435 45 60 108 165 302.5 435 435 435 Season Summer 31 92.355 94.966 17.056 5 420 15 45 60 100 210 345 420 420 Season Fall 8 1oa 115.681 40.899 25 360 25 30 67.5 142 360 360 360 360 Asthma No 56 94.821 91.447 1i22 5 435 15 45 60 107.5 194 360 420 435 Asthma Yes 3 145 173.853 100.374 30 345 30 30 60 345 345 345 345 345 Angina No 58 96.983 96.158 12.626 5 435 15 45 60 105 210 360 420 435 Angina Yes 1 120 . . 120 120 120 120 120 120 120 120 120 120 Bronchitis/Emphysema No 55 90.018 87.056 11.739 5 435 15 45 60 100 170 345 360 435 Bronchitis/Emphysema Yes 4 198.5 157.509 78.754 60 420 60 90 157 307 420 420 420 420 Note: A ..... Signifies missing data. "DK"= The respondent replied "don't know". N =doer sample size. Mean= Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max= maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleneis 1996.

Table 15-81. Statistics for 24-Hour Cumulative Number of Minutes Spent for Car Repair Services Percentiles Cateqorv Population Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 . 99 All 259 33.7876 53.772 3.3413 1 358 5 5 10 30 90 180 195 270 Gender Male 128 41.6953 65.45 5.7851 1 358 4 5 15 45 120 180 270 280 Gender Female 131 26.0611 37.84 3.3061 2 180 5 5 10 30 65 105' 180 180 Age (years) . *2 88 2.828 2 86 90 86 86 88 90 90 90 90 90 Age (years) 1-4 8 33.125 43.666 15.438 5 115 5 5 12.;i 55 115 115 115 115 Age (years) 5-11 6 18.3333 20.897 8.531 5 60 5 5 12.5 15 60 60 60 60 Age (years) 12-17 13 31.3077 32.638 9.0521 3 95 3 5 10 55 79 95 95 95 Age (years) 18-64 204 32.4853 52.731 3.6919 1 280 5 5 10 30 85 180 195 265 Age (years) > 64 26 44.8462 75.446 14.796 1 358 2 10 15 50 105 180 358 358 Race White 226 33.8451 51.028 3.3943 1 280 5 5 10 35 90 175 195 265 Race Black 19 49.3158 90.675 20.802 1 358 1 5 10 44 180 358 358 358 Race Asian 3 11.6667 11.547 6.6667 5 25 5 5 5 25 25 25 25 25 Race Some Others 5 11 8.944 4 5 25 5 5 5 15 25 25 25 25 Race Hispanic 6 12.5 6.124 2.5 5 20 5 5. 15 15 20 20 20 20 Hispanic No 247 34.6154 54.728 3.4822 1 358 5 5 10 35 90 180 245 270 Hispanic Yes 12 16.75 22.471 6.4867 5 86 5 5 12.5 15 20 86 86 86 Employment . 26 27.7692 33.586 6.5868 3 115 5 5 10 50 90 95 115 115 Employment Full Time 137 31.8759 52.912 4.5206 1 280 4 5 10 30 85 175 265 270 Employment Part Time 25 32.96 49.672 9.9344 5 180 5 7 15 30 105 180 180 180 Employment Not Employed 70 40.4714 62.833 7.51 1 358 4 10 15 35 103 180 245 358 Employment Refused 1 5 . . 5 5 5 5 5 5 5 5 5 5 Education . 28 28.4643 32.992 6.2349 3 115 5 5 12.5 52.5 90 95 115 115 Education < High School 20 36.15 51.714 11.564 5 180 5 10 15 45 117.5 177.5 180 180 Education High School Graduate 64 41.0781 62.959 7.8698 2 280" 5 5 15 47.5 105 180 265 280 Education <College 68 36.2206 59.709 7.2407 1 358 2 5 15 37.5 90 180 180 358 Education College Graduate 41 29.6829 54.536 8.5171 1 270 4 5 10 25 60 160 270 270 Education Post Graduate 38 24.2632 36.541 5.9277 5 195 5 5 10 20 70 95 195 195 Census Region Northeast 45 40.4889 58.498 8.7204 2 270 5 5 15 60 105 180 270 270 Census Region Midwest 66 34.6364 56.367 6.9383 2 280 5 5 10 35 70 180 265 280 Census Region South 88 34.8182 60.547 6.4543 1 358 3 5 10 30 95 180 245 358 Census Region West 60 26.3167 33.054 4.2673 4 175 5 5 12.5 30 80 95.5 115 175 Day Of Week Weekday 176 36.0227 57.142 4.3072 1 358 5 5 15 30 101 180 265 280 Day Of Week Weekend 83 29.0482 45.78 5.025 1 245 3 5 10 30 79 95 195 245 Season Winter 70 19.4857 27.784 3.3208 1 180 2 5 10 20 60 60 90 180 Season Spring 70 36.5286 48.821 5.8352 2 245 5 5 15 50 105 150 180 245 Season Summer 79 41.5316 66.665 7.5004 2 358 5 5 15 30 160 180 270 358 Season Fall 40 38.725 64.266 10.161 2 280 5 5 12.5 39.5 90.5 222.5 280 280 Asthma No 238 34.7731 55.08 3.5703 1 358 4 5* 10 35 90 180 245 270 Asthma Yes 21 22.619 34.735 7.5799 5 150 5 5 15 15 35 90 150 150 Angina No 253 32.6324 51.888 3.2622 1 358 5 5 10 30 90 160 180 270 Angina Yes 6 82.5 102.896 42.007 10 245 10 15 22.5 180 245 245 245 245 Bronchitis/emphysema No 247 33.0607 52.903 3.3661 1 358 5 5 10 30 90 175 195 270 Bronchitis/emphysema Yes 12 48.75 70.522 20.358 5 245 5 5 15 77.5 95 245 245 245 Note: A"*" Signifies missina data. "DK"= The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minu es for doers. Stdev =standard deviation. Stderr =standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996.

Table 15-82. Statistics for 24-Hour Cumulative Number of Minutes Soent Washina, etc. Percentiles Cateciorv Population Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 6029 23.9338 25.5661 0.3293 1 705 5 10 20 30 45 60 75 90 Gender Male 2785 23.4154 28.8168 0.5461 1 705 5 10 15 30 45 55 65 90 Gender Female 3242 24.3816 22.4026 0.3935 1 555 5 10 20 30 45 60 80 90 Gender Refused 2 20 14.1421 10 10 30 10' 10 20 30 30 30 30 30 Age (years) . 110 25.9182 30.4752 2.9057 3 300 5 10 20 30 41.5 60 60 80 Age (years) 1-4 318 29.2673 16.5524 0.9282 5 125 10 15 30 30 50 60 75 85 Age (years) 5-11 407 26.5184 35.9626 1.7826 2 690 7 15 20 30 45 60 60 75 Age (years) 12-17 411 22.4088 14.6309 0.7217 1 90 5 10 18 30 . 42 50 60 60 Age (years) 18-64 4154 22.7939 21.6279 0.3356 1 555 5 10 15 30 45 60 75 90 Age (years) > 64 629 27.7424 43.1415 1.7202 1 705 5 12 20 30 45 65 90 120 Race White 4794 23.1558 26.1288 0.3774 1 705 5 10 15 30 45 60 70 90 Race Black 664 28.7816 24.2016 0.9392 3 270 5 15 20 35 60 65 90 105 Race Asian 110 24.4727 17.5493 1.6733 5 90 5 15 20 30 47.5' 60 85 90 Race Some Others 119 28.6471 27.4768 2.5188 3 240 8 15 25 30 50 60 100 150 Race Hispanic 269 23.8364 19.8318 1.2092 1 210 5 10 20 30 45 60 75 90 Race Refused 73 22.7945 20.46 2.3947 3 105 5 10 15 30 60 75 90 105 Hispanic No 5476 23.8088 25.0872 0.339 1 705 5 10 20 30 45 60 75 90 Hispanic Yes 465 25.7312 31.6942 1.4698 1 570 5 15 20 30 45 60 75 90 Hispanic DK. 30 23.8 15.0319 2.7444 5 60 10 15 17.5 30 50 60 60 60 Hispanic Refused 58 21.3966 18.5708 2.4385 5 105 5 10 15 25 30 60 80 105 Employment . 1116 25.9758 ' 25.169 0.7534 1 690 7 15 20 30 45 60 60 75 Employment Full Time 2975 22.0733 21.4639 '0.3935 1 555 5 10 15 30 45 60 65 85 Employment . Part Time 518 22.3996 17.1137 0.7519 1 135 5 10 15 30 45 60 70 90 Employment Not Employed 1378 26.9354 34.8572 0.939 1 705 5 10 20 30 50 60 90 120 Employment Refused 42 21.9048 15.8865 2.4513 5 90 5 10 15 30 30 45 90 90 Education . 1245 25.3888 24.2988 0.6887 1 690 6 15 20 30 45 60 60 80 Education < High School 440 30.6 46.38 2.2111 1 570 5 15 20 30 50 60 90 240 Education High School Graduate 1634 23:7699 20.0081 0.495 1 270 5 10 20 30 45 60 75 90 Education <College 1228 22.8575 19.6959 0.5621 1 255 5 10 15 30 45 60 75 90 Education College Graduate 844 22.5936 32.3617 1.1139 1 705 5 10 15 30 40 60 75 110 Education Post Graduate 638 20.7618 18.4597 0.7308 2 240 5 10 15 30 45 60 65 85 Census Region Northeast 1356 23.3274 21.7583 0.5909 1 360 5 10 15 30 45 60 75 90 Census Region Midwest 1303 22.9294 27.432 0.76 1 570 5 10 15 30 45. 60 70 85 Census Region South 2136 25.2116 21.6627 0.4687 1 300 5 15 20 30 45 60 85 105 Census Region West 1234 23.4489 32.6116 0.9284 1 705 5 10 15 30 45 60 65 85 Day Of Week Weekday 4184 22.9441 25.7284 0.3978 1 705 5 10 15 30 45 60 65 90 Day Of Week Weekend 1845 26.1783 25.0567 0.5833 1 555 5 15 20. 30 50 60 90 100 Season Winter 1688 24.6226 20.295 0.494 1 300 5 10 20 30 45 60 75 90 Season Spring 1584 26.3295 38.468 0.9665 1 705 5 13 20 30 45 60 90 125 Season Summer 1636 21.8264 15.5411 0.3842 1 150 5 10 15 30 40 55 60 75 Season Fall 1121 22.587 20.8871 0.6238 1 340 5 10 15 30 45 60 75 90 Asthma No 5559 23.9538 26.1095 0.3502 1 705 5 10 20 30 45 60 75 90 Asthma Yes 437 24.2288 18.3575 0.8782 1 145 5 15 20 30 45 60 90 95 Asthma DK 33 16.6667 8.7202 1.518 5 30 5 10 15 25 30 30 30 30 Angina No 5866 23.9529 25.8029 0.3369 1 705 5 10 20 30 45 60 75 90 Angina Yes 125 25.176 15.6613 1.4008 3 100 6 15 25 30 45 60 60 75 Angina DK 38 16.8947 8.5481 1.3867 5 35 5 10 15 25 30 30 35 35 Bronchitis/Emphysema No 5749 23.8629 25.8064 0.3404 1 705 5 10 20 30 45 60 75 90 Bronchitis/Emphysema Yes 249 26.49 20.7475 1.3148 1 150 5 15 20 30 60 60 95 105 Bronchitis/Emphysema DK 31 16.5484 8.0616 1.4479 5 30 5 10 15 25 30 30 30 30 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused= Refused data. N =doer sample size. Mean= Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Std err= standard error. Min= minimum number of minutes. Max= maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996. Table 15-83. Statistics for 24-Hour Cumulative Number of Minutes Spent Sleeoino/Naooino Percentiles Cateqory Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 All 9362 526.287 134.435 1.3894 30 1430 345 445 510 600 690. 760 850 925 Gender Male 4283 523.333 135.183 2.0656 30 1295 330 435 510 600 690 765 860 925 Gender Female 5075 528.685 133.743 1.8774 30 1430 350 450 510 600 690 750 840. 925 Gender Refused 4 645 123.693 61.8466 540 780 540 540 630 750 780 780 780 780 Age (years) . 185 502.281 125.424 9.2214 195 908 330 420 480 555 655 745 865 900 Age (years) 1-4 499 732.363 124.328 5.5657 270 *1320 540 655 720 810 90.0 930 1005 1110 Age (years) 5-11 702 625.058 100.656 3.799 120 1110 480 570 630 680 725 780 840 875 Age (years) 12-17 588 563.719 110.83 4.5706 150 1015 395 484 550 630 705 750 810 900 Age (years) 18-64 6041 496.93 123.019 1.5828 30 1420 330 420 480 555 630 705 780 868 Age (years) > 64 1347 517.084 117.477 3.2009 30 1430 345 450 510 570 660 720 780 860 Race White 7576 523.598 129.545 1.4883 30 1430 350 445 510 600 690 750 840 900 Race Black 940 541.303 162.726 5.3076 60 1415 315 424 530 630 737 .5 822.5 940 1020 Race Asian 156 537.09 118.072 9.4533 300 920 345 467.5 540 600 690 735 840 870 Race Some Others 181 528.823 142.25 10.5734 60 905 300 420 525 630 720 769 810 842 Race Hispanic 383 537.966 148.886 7.6077 60 1125 315 450 540 630 720 765 870 930 Race Refused 126 523.421 143.695 12.8014 180 1140 330 420 510 600 720 780 870 930 Hispanic No 8514 525.205 133.218 1.4438 30 1430 345 445 510 600 690 750 855 925 Hispanic Yes 700 540.053 147.143 5.5615 60 1125 320 450 540 630 720 777.5 842.5 915 Hispanic DK 45 527.467 139.269 20.7609 195 842 345 420 515 659 690 710 842 842 Hispanic Refused 103 521.592 138.874 13.6837 240 930 330 420 510 590 720 780 865 870 Employment . 1771 636.604 128.545 3.0545 120 1320 440 555 630 705 802 860 930 975 Employment Full Time 4085 487.152 118.9 1.8603 30 1420 325 420 480 540 628 685 770 840 Employment Part Time 798 502.764 117.416 4.1565 60 1005 330 435 495 570 545. 720 780 860 Employment Not Employed 2638 520.277 125.549 2.4444 30 1430 345 450 510. 590 660 720 800 885 Employment Refused 70 513.671 136.491 16.3138 210 930 320 420 490 570 696.5 780 900 930 Education . 1966 625.586 133.976 3.0216 120 1420 420 540 628 699 790 855 926 975 Education < High School 832 515.445 135.697 4.7045 30 1317 300 435 510 585 670 750 860 900 Education High School Graduate 2604 505.367 123.006 2.4105 30 1430 330 420 495 570 659 720 780 840 Education < Colleg_e 1791 496.616 119.862 2.8323 60 1350 315 420 480 565 630 690 779 845 Education College Graduate 1245 492.516 117.558 3.3317 75 1404 330 420 480 540 629 690 775 900 Education Post Graduate 924 486.737 110.394 3.6317 105 1295 345 420 480 540 615 660 725 800 Census Region Northeast 2068 523.129 133.703 2.9401 55 1420 345 435 510 600 690 760 860 930 Census Region Midwest 2096 520.846 127.642 2.788 30 1215 330 440 510 598 690 745 840 870 Census Region South 3234 529.019 135.651 2.3854 30 1430 345 450 510 600 699 765 855 925 Census Region West 1964 530.918 139.966 3.1583 60 1404 345 449.5 510 600 690 769 862 940 Day OfWe"ek Weekday 6303 511.13 131.826 1.6605 30 1430 330 420 495 570 670 745 840 920 Day Of Week Weekend 3059 557.517 134.392 2.4299 30 1420 360 480 540 630 720 780 870 925 Season Winter 2514 534.911 134.719 2.6869 55 1404 355 450 520 600 700 780 870 930 Season Spring 2431 526.839 130.49 2.6466 30 1175 345 445 510 600 690 750 840 900 Season Summer 2533 527.653 139.46 2.771 30 1430 330 435 510 600 699 765 840 930 Season Fall 1884 512.228 131.14 3.0213 60 1420 330 430 505 570 660 735 840 900 Asthma No 8608 525.05 133.571 1.4397 30 1430 345 445 510 600 690 750 840 915 Asthma Yes 692 540.061 143.571 5.4577 30 1404 330 450 537.5 617.5 715 780 900 945 Asthma DK 62 544.194 140.992 17.906 300 1035 330 465 535 600 720 780 930 1035 Angina No 9039 526.754 134.235 1.4119 30 1420 345 445 510 600 690 760 855 925 Angina Yes 249 513.743 137.698 8.7263 60 1430 300 445 510 595 660 735 795 845 Angina DK 74 511.392 146.297 17.0067 30 930 300 420 510 600 720 780 840 930 Bronchitis/Emphysema No 8860 526.549 134.267 1.4264 30 1430 345 445 510 600 690 760 850 924 Bronchitis/Emphysema Yes 432 521.713 138.459 6.6616 80 1110 300 420 510 600 705 765 840 930 Bronchitis/Emphysema DK 70 521.243 131.857 15.7599 210 930 300 450 510 600 690 745 840 930 Note: A "*"Signifies missing data. "DK" =The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Std err= standard error. Min= minimum number of minutes. Max= maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996. Table 15-84. Statistics for 24-Hour Cumulative Number of Minutes Spent Attendinq Full Time School Percentiles Cateaorv Pooulation Grouo N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 884 358.537 130.347 4.384 1 840 95 300 390 435 483 550 600 640 Gender Male 468 369.301 123.186 5.6943 20 840 120 320 390 435 485 555 595 645 Gender Female 416 346.428 137.1 6.7219 1 710 75 262.5 385 430 480 535 600 628 Age (years) . 7 232.143 148.123 55.9853 10 495 10 180 210 320 495 495 495 495 Age (years) 1-4 56 365.036 199.152 26.6128 20 710 30 172.5 427.5 530 595 628 665 710 Age (years) 5-11 297 387.811 98.013 5.6873 60 645 170 360 390 435 485 555 600 630 Age (years) 12-17 271 392.28 84.986 5.1625 10 605 200 375 405 435 460 485 510 555 Age (years) 18-64 247 292.194 154.58 9.8357 1 840 60 180 289 400 480 535 645 785 Age (years) > 64 6 203.333 147.366 60.1618 75 480 75 120 152.5 240 480 480 480 480 Race White 665 362.913 128.548 4.9849 1 825 107 310 392 435 485 550 600 630 Race Black 92 351.793 129.647 13.5166 40 710 70 286.5 387.5 432.5 465 526 645 710 Race Asian 33 346.303 156.009 24.1576 90 840 120 225 365 435 500 565 840 840 Race Some Others 29 337 .828 148.115 27 .5043 58 553 70 212 360 445 502 540 553 553 Race Hispanic 58 345.259 124.048 16.2883 30 565 85 260 377.5 430 480 510 510 565 Race Refused 7 285 157.03 59.3517 60 440 60 150 290 440 440 440 440 440 Hispanic No 771 359.565 130.825 4.7116 1 840 100 300 390 435 483 550 600 645 Hispanic Yes 103 353.107 126.354 12.4501 30 630 85 269 385 425 483 510 595 600 Hispanic DK 4 315.5 167. 773 83.8863 65 416 65 221 391 410 415 415 415 415 Hispanic Refused 6 348.333 140.594 57.3973 150 445 150 185 435 440 445 .445 445 445 Employment . 608 386.497 107.308 4.3519 10 710 165 361 4.00 440 485 550 595 625 Employment Full Time 49 206.551 133.583 19.0833 5 502 15 115 180 305 430 461 502 502 Employment Part Time 89 304.652 134.791 14.2879 25 695 90 210 295 395 480 500 585 695 Employment Not Employed 135 325.274 161.049 13.8609 1 840 60 215 340 420 500 605 785 825 Employment Refused 3 270 147.224 85 185 440 185 185 440 440 440 440 440 440 Education . 666 384.985 107 .925 4.182 10 710 160 360 400 440 485 550 595 625 Education < High School 14 267.071 129.31 34.5595 5 415 5 175 310 357 385 415 415 415 Education High School Graduate 54 238.481 141.148 19.2079 58 785 60 125 212 330 400 480 480 785 Education <College 100 303.35 170.598 17.0598 1 840 60 185 272.5 415 525.5 613.5 760 832.5 Education College Graduate 24 238.417 145.897 29.781 25 565 30 135 200 360 430 460 565 565 Education Post Graduate 26 302.808 144.149 2.8.2699 10 535 95 210 300 461 500 502 535 535 Census Region Northeast 186 351.597 127.019 9.3135 60 825 120 268 375 420 483 520 600 785 Ce.nsus Region Midwest 200 358.07 123.934 8.7634 5 645 87.5 307.5 392.5 425 470 527.5 577.5 602 Census Region South 322 373.879 139.7 7.7852 10 840 60 330 405 450 500 565 625 645 Census Region West 176 338.335 120.469 9.0807 1 630 120 262.5 375 410 465 540 555 600 Day Of Week Weekday 858 363.66 126.018 4.3022 1 840 120 310 390 435 485 550 600 640 Day Of Week Weekend 26 189.5 158.415 31.0677 15 465 20 60 120 300 460 465 465 465 Season Winter 302 375.113 118.518 6.8199 5 695 150 330 395 440 495 550 612 640 Season Spring 287 353.359 133.705 7.8924 10 840 90 290 390 430 . 475 500 570 710 Season Summer 125 332.448 142.088 12.7088 40 630 70 217 375 425 470 550 600 600 Season Fall 170 357.018 132.833 10.1878 1 785 120 285 380 430 510 565 605 645 Asthma No 784 357.969 130.658 4.6663 1 840 95 295 390 435 485 550 595 630 Asthma Yes 96 362.958 127.895 13.0533 20 695 95 334 390 427.5 475 540 645 695 Asthma DK 4 363.75 162.551 81.2756 120 450 120 280 442.5 447.5 450 450 450 450 Angina No 875 358.57 130.546 4.4133 1 840 95 300 390 435 483 550 600 640 Angina Yes 4 382.5 87.702 43.8511 255 455 255 330 410 435 455 455 455 455 Angina DK 5 333.6 140.481 62.8248 120 460 120 270 378 440 460 460 460 460 Bronchitis/Emphysema No 851 359.132 130.435 4.4713 1 840 95 300 390 435 485 550 600 640 Bronchitis/Emphysema Yes 27 340.111 132.683 25.5349 30 605 60 305 365 435 450 460 605 605 Bronchitis/Emphysema DK 6 357.167 121.491 49.5987 120 440 120 350 396.5 440 440 440 440 440 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Stderr = standard error. Min = minimum number of minutes. Max= maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleceis 1996. Table 15-85. Statistics for 24-Hour Cumulative Number of Minutes Spent in Active Sports Percentiles Category Population Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 1384 123.994 112.825 3.0328 1 1130 15 50 90 165 267 330 435 525 Gender Male 753 136.781 120.777 4.4014 1 1130 20 60 105 180 285 375 500 558 Gender Female 629 108.628 100.648 4.0131 1 1065 15 38 75 150 240 300 370 435 Gender Refused 2 142.5 38.891 27.5 115 170 115 115 142.5 170 170 170 170 170 Age (years) . 23 108.696 78.628 16.395 5 290 30 40 90 155 220 225 290 290 Age (years) 1-4 105 115.848 98.855 9.6472 10 630 30 45 90 159 250 330 345 390 Age (years) 5-11 247 148.87 126.627 8.0571 2 975 20 60 120 188 320 390 '510 558 Age (years) 12-17 215 137.46 124.516 8.4919 5 1065 15 60 110 180 265 375 470 520 Age (years) 18-64 642 120.315 110.376 4.3562 1 1130 15 45 90 160 250 330 450 525 Age (years) > 64 152 88.007 80.207 6.5056 1 380 15 30 60 120 220 285 315 330 Race White 1139 125.994 116.168 3.4421 1 1130 15 50 90 165 270 340 452 530 Race Black 109 113.431 96.788 9.2706 5 440 10 45 86 150 240 332 430 435 Race Asian 30 89.933 79.214 14.4625 5 310 10 30 60 145 215 235 310 310 Race Some Others 35 135.371 112.206 18.9663 15 553 20 60 105 195 270 330 553 553 Race Hispanic 59 116.288 91.326 11.8897 1 520 15 45 115 145 240 305 345 520 Race Refused 12 120 86.576 24.9924 40 300 40 60 95 130 290 300 300 300 Hispanic No 1250 124.471 113.469 3.2094 1 1130 15 45 90 165 270 330 435 515 Hispanic Yes 120 121.2 110.791 10.1138 1 630 15 50 90 147.5 240 335 520 553 Hispanic DK 4 113.75 57.5 28.75 60 185 60 67.5 105 160 185 185 185 185 Hispanic Refused 10 102 72.119 22.8059 40 290 40 60 82.5 105 215 290 290 290 Employment . 561 137.073 120.838 5.1018 2 1065 20 60 1.10 180 285 370 452 558 Employment Full Time 375 117.579 107.304 5.5412 5 1130 20 45 90 155 240 305 380 525 Employment Part Time 87 116.207 87.553 9.3867 1 450 15 60 95 160 235 285 355 450 Employment Not Employed 352 112.537 109.99 5.8625 1 600 10 30 70 150 270 330 475 520 Employment Refused 9 99.444 77.235 25.7451 30 280 30 45 90 120 280 280 280 280 Education . 610 137.702 121.227 4.9083 2 1065 20 60 110 180 285 370 470 558 Education < High School 86 101.047 99.745 10.7558 10 570 15 30 60 135 225 270 510 570 Education High School Graduate 233 116.794 116.802 7.652 1 1130 20 45 85 150 240 300 420 530 Education <College . 178 115.781 100.276 7.516 1 525 15 45 90 160 270 340 418 475 Education College Graduate 165 116.218 97.925 7.6235 1 600 15 50 90 150 250 310 380 450 Education Post Graduate 112 106.446 97.879 9.2487 5 375 10 40 60 142.5 270 330 360 375 Census Region Northeast 333 131.967 129.1 7.0746 "1 1130 15 60 100 170 275 345 485 558 Census Region Midwest 254 116.882 101.859 6.3912 5 570 18 45 90 150 255 315 430 440 Census Region South 479 119.476 108.664 4.965 1 975 15 45 90 160 265 330 410 462 Census Region West 318 128.132 108.811 6.1018 1 625 25 55 92.5 175 295 330 500 525 Day Of Week Weekday 902 115.47 97.84 3.2577 1 650 15 45 90 150 240 300 395 485 Day Of Week Weekend 482 139.946 135.196 6.158 1 1130 20 59 100 180 300 380 500 565 Season Winter 316 115.589 115.201 6.4806 1 1065 15 45 85 155 240 305 370 475 Season Spring 423 130.775 105.017 5.1061 5 650 30 60 105 175 270 330 435 515 Season Summer 425 129.541 115.123 5.5843 1 625 15 45 95 178 290 375 462 530 Season Fall 220 112.314 118.325 7.9775 1 1130 15 43 77.5 143.5 240 290 460 565 Asthma No 1266 122.461 109.594 3.0801 1 1130 15 45 90 162 266 330 430 515 Asthma Yes 105 144.829 145.828 14.2314 1 1065 15 60 110 180 300 390 553 565 Asthma DK 13 105 110.416 30.6239 30 450 30 60 60 90 165 450 450 450 Angina No 1343 125.491 113.589 3.0995 1 1130 15 50 90 165 270 332 440 525 Angina Yes 33 72.091 73.998 12.8815 5 330 5 30 50 60 180 275 330 330 Angina DK 8 86.875 41.139 14.5448 40 155 40 60 75 115 155 155 155 155 Bronchitis/Emphysema No 1331 124.101 113.19 3.1026 1 1130 15 50 90 165 267 330 435 520 Bronchitis/Emphysema Yes 43 130 112.663 17.181 10 553 30 45 110 165 270 340 553 553 Bronchitis/Emphysema DK 10 84 39.847 12.6007 40 155 40 60 75 105 147.5 155. 155 155 Note: A"*" Siflnifies missing data. "DK"= The replied "don't know". Refused= Refused data. N =doer sample size. Mean= Mean 24-hour cumu alive number of minutes for doers. tdev =standard deviation. Stderr = standard error. Min = minimum number of minutes. Max= maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsann and Kleneis 1996. Table 15-86. Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor Recreation Percentiles Category Population Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 253 211.23 185.48 11.661 5 1440 20 60 165 300 480 574 670 690 Gender Male 140 231.78 207.41 17.529 5 1440 17.5 67.5 177 330 502.5 600 690 735 Gender Female 112 183.67 150.15 14.188 5 645 20 60 150 255 380 525 585 630 Gender Refused 1 420 . . 420 420 420 420 420 420 420 420 420 420 Age (years) . 2 337.5 201.53 142.5 195 480 195 195 337.5 480 480 480 480 480 Age (years) 1-4 13 166.54 177.06 49.109 15 630 15 30 130 180 370 630 630 630 Age (years) 5-11 21 206.14 156.17 34.078 30 585 60 90 165 245 360 574 585 585 Age (years) 12-17 27 155.07 128.28 24.687 5 465 5 60 135 225 420 420 465 465 Age (years) 18-64 158 223.61 192.97 15.352 5 1440 30 80 172.5 310 505 585 690 690 Age (years) > 64 32 211.06 206.59 36.521 5 735 5 30 171 375 495 600 735 735 Race White 225 209.77 182.74 12.183 5 1440 20 60 165 300 460 570 670 690 Race Black 16 233.88 231.3 57.825 5 690 5 42.5 150 450 585 690 690 690 *Race Asian 3 203.33 262.22 151.39 30 505 30 30 75 505 505 505 505 505 Race Some Others 2 327.5 130.82 92.5 235 420 235 235 327.5 420 420 420 420 420 Race Hispanic 4 77.5 53.929 26.964 20 150 20 42.5 70 112.5 150 150 150 150 Race Refused 3 308.33 209.42 120.91 180 550 180 180 195 550 550 550 550 550 Hispanic No 238 211.8 187.07 12.126 5 1440 20 60 165 300 480 585 690 690 Hispanic Yes 12 175.5 149.06 43.029 15 511 15 70 150 255 340 511 511 511 Hispanic Refused 3 308.33 209.42 120.91 180 550 180 180 195 550 550 550 550 550 Employment . 60 177.1 150.02 19.368 5 630 12.5 60 147.5 230 395 519.5 585 630 Employment Full Time 104 210.74 153.37 15.039 5 670 30 82.5 180 294 419 511 600 645 Employment Part Time 19 205.26 204.04 46.81 30 690 30 60 150 180 570 690 690 690 Employment Not Employed 68 244.44 245.03 29.715 5 1440 15 60 179.5 375 525 690 735 1440 Employment Refused 2 187.5 10.607 7.5 180 195 180 180 187.5 195 195 195 195 195 Education . 64 176.73 145.32 18.165 5 630 15 60 152.5 225 .370 465 585 630 Education < High School 22 259.41 177.97 37.943 5 600 30 105 247.5 380 525 600 600 600 Education High School Graduate 59 238.2 228.99 29.812 15 1440 20 90 175 310 511 670 690 1440 Education <College 54 218.09 172.21 23.434 5 690 25 65 172.5 345 460 550 570 690 Education College Graduate 31 224.71 193.06 34.675 20 690 30 60 150 325 505 645 690 690 Education Post Graduate 23 157.61 178.18 37.153 5 735 10 50 80 200 370 480 735 735 Census Region Northeast 52 189.6 160.88 22 .. 31 5 690 30 60 162.5 231.5 370 574 670 690 Census Region Midwest 54 212.09 228.41 31.083 5 1440 20 60 177.5 280 419 600 735 1440 Census Region South 84 217.26 175.27 19.123 5 645 15 62.5 150 347.5 495 525 600 645 Census Region West 63 220.29 179.71 22.642 10 690 30 75 165 280 545 585 690 690 Day Of Week Weekday 129 197.21 195.32 17.197 5 1440 15 60 150 275 465 525 670 735 Day Of Week Weekend 124 225.81 174.26 15.649 5 690 20 85 180 310 480 600 690 690 Season Winter 31 196.61 165.52 29.728 5 585 5 60 165 280 440 550 585 585 Season Spring 75 198.85 161.67 18.668 5 690 25 75 180 270 465 545 670 690 Season Summer 102 228.16 204.18 20.217 5 1440 30 75 179.5 325 459 585 690 690 Season Fall 45 203.53 193.83 28.895 5 735 20 60 120 330 505 574 735 735 No 232 208.24 187.69 12.323 5 1440 20 60 159 294 480 585 690 690 Asthma Yes 19 250.21 166.64 38.23 15 570. 15 80 255 350 525 570 570 570 Asthma DK 2 187.5 10.607 7.5 180 195 180 180 187.5 19!l 195 195 195 195 Angina No 245 206.82 184.85 11.81 5 1440 20 60 160 288 480 570 670 690 Angina Yes 6 399.17 151.21 61.731 285 690 285 310 345 420 690 690 690 690 Angina DK 2 187.5 10.607 7.5 180 195 180 180 187.5 195 195 195 195 195 Bronchitis/Emphysema No 238 212.24 189.23 12.266 5 1440 20 60 165 300 495 585 690 690 Bronchitis/Emphysema Yes 13 196.31 122.22 33.896 5 370 5 117 160 310 340 370 370 370 Bronchitis/Emphysema DK 2 187.5 10.607 7.5 180 195 180 180 187.5 195 195 195 195 195 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused= Refused data. N =doer sample size. Mean= Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Std err= standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsann and Kleneis 1996. Table 15-87. Statistics for 24-Hour Cumulative Number of Minutes Spent in Exercise Percentiles Category Population Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 564 77.429 70.438 2.966 4 670 15 30 60 100 150 195 275 420 Gender Male 262 84.676 75.778 4.6816 5 670 20 30 60 117 . 165 205 285 450 Gender Female 302 71.142 64.927 3.7361 4 525 15 30 60 90 125 175 265 360 Age (years) . 10 76.5 74.014 23.405 15 270 15 30 60 90 187.5 270 270 270 Age (years) 1-4 11 127.273 187.18 56.437 15 670 15 30 60 150 160 670 670 670 Age (years) 5-11 26 132.5 126.31 24.772 15 525 25 60 90 180 275 450 525 525 Age (years) 12-17 35 67.829 41.589 7.0298 15 180 20 30 60 100 120 150 180 180 Age (years) 18-64 407 77.572 63.597 3.1524 4 480 20 30 60 100 145 185 265 300 Age (years) > 64 75 54.853 44.455 5.1332 6 195 . 10 25 40 70 120 150 193 195 Race White 480 78.015 71.517 3.2643 4 670 15 30 60 100 150 194 285 450 Race Black 34 74.706 44.67 7.6608 15 250 15 45 60 105 120 130 250 250 Race Asian 16 46.3 25.038 7.9177 15 95 15 30 41.5 60 82.5 95 95 95 Race Some Others 14 80.214 73.944 19.762 30 275 30 30 47.5 90 179 275 275 275 Race Hispanic 19 63 60.658 13.916 15 265 15 30 45 60 ' 160 265 265 265 Race Refused 7 128.571 130.47 49.313 30 360 30 55 60 270 . 360 360 360 360 Hispanic No 516 76.872 70.111 3.0865 4 670 15 30 60 99 145 193 275 420 Hispanic Yes 38 76.553 59.516 9.6548 15 265 20 30 60 110 160 250 265 265 Hispanic DK 3 65 69.462 40.104 20 145 20 20 30 145 145 145 145 145 Hispanic Refused 7 128.571 130.47 49.313 30 360 30 55 60 270 360 360 360 360 Employment . 72 99.014 111.6 13.153 15 670 20 30' 60 120 180 275 525 670 Employment Full Time 300 72.663 55.618 3.2111 5 460 20 30 60 90 130 179.5 240 291 Employment Part Time 50 85.98 83.568 11.818 10 420 20 30 60 92 167.5 300 390 420 Employment Not Employed 139 72.683 63.36 5.3742 4 480 10 30 60 90 135 195 240 265 Employment Refused 3 113.333 135.77 78.387 30 270 30 30 40 270 270 270 270 270 Education . 83 101.976 110.97 12.18 15 670 25 30 60 120 205 275 525 670 Education < High School 21 58.238 66.062 14.416 10 300 10 28 30 60 90 165 300 300 Education High School Graduate 124 81.048 63.037 5.6609 4 298 15 30 60 115 179 205 250 265 Education <College 104 80.856 70.181 6.8818 15 480 20 30 60 112.5 150 170 240 420 Education College Graduate 110 62.548 5.9637 5 460 20 30 60 98 130 180 285 297 Education Post Graduate 122 60.861 38.368 3.4737 5 240 15 30 60 80 110 127 165 185 Census Region Northeast 130 88.423 77.649 6.8102 10 450 15 30 60 120 200 240 297 420 Census Region Midwest 101 63.564 44.33 4.411 10 300 15 30 60 89 115 120 170 215 Census Region South 177 75.311 71.62 5.3833 5 525 15 30 60 90 150 185 298 480 Census Region West 156 79.647 75.331 6.0313 4 670 20 30 60 104 130 183 270 460 Day Of Week Weekday 426 73.096 63.872 3.0946 4 670 15 30 60 90 130 180 240 298 Day Of Week Weekend 138 90.804 86.574 7.3697 6 525 15 30 60 120 200 265 420 460 Season Winter 150 67.387 49.859 4.071 8 285 15 30 60 90 127.5 175 212.5 240 -Season Spring 140 74.871 55.395 4.6817 10 360 17.5 30 60 90 147.5 181 220 298 Season Summer 192 93.188 91.294 6.5886 5 670 20 30 62.5 120 180 250 450 525 Season Fall 82 63.268 63.277 6.9878 4 460 15 30 45 75 120 135 300 460 Asthma No 523 76.625 70.247 3.0717 4 670 15 30 60 100 150 185 . 265 420 Asthma Yes 37 78.243 51.454 8.459 20 275 20 45 65 100 120 200 275 275 Asthma DK 4 175 167.03 83.517 10 360 10 35 165 315 360 360 360 360 Angina No 553 77.259 69.366 2.9497 4 670 15 30 60 100 145 193 265 420 Angina Yes 7 27.286 19.576 7.3992 6 60 6 10 25 45 60 60 60 60 Angina DK 4 188.75 150.35 75.177 60 360 60 62.5 167.5 315 360 360 360 360 Bronchitis/Emphysema No 542 77.098 69.465 2.9838 4 670 15 30 60 100 145 185 265 420 Bronchitis/Emphysema Yes 17 64.588 60.635 14.706 10 275 10 30 50 63 120 275 275 275 Bronchitis/EMphysema DK 5 157 1.49.57 66.888 15 360 15 60 80 270 360 360 360 360 Note: A ..... Signifies missing data. "DK" =The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Std err= standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996. Table 15-88. Statistics for 24-Hour Cumulative Number of Minutes Spent in Food Preparation' Percentiles Category Population Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 4278 52.37 52.8802 0.8085 1 555 5 20 35 65 115 150 210 265 Gender Male 1341 37.8106 42.1779 1.1518 1 480 5 13 30 50 80 105 150 210 Gender Female 2937 59.0177 55.862 1.0308 1 555 5 25 45 75 120 155 224 272 Age (years) . 94 52 43.2171 4.4575 5 215 5 20 40 60 110 150 195 215 Age (years) 1-4 24 56.4583 60.3699 12.3229 5 240 5 22.5 30 75 150 180 240 240 Age (years) 5-11 60 25.1667 29.6877 3.8327 1 120 2 5 11 30 60 107 120 120 Age (years) 12-17 131 21.7023 37.6902 3.293 1 385 2 5 10 30 55 70 90 90 Age (years) 18-64 3173 52.0905 52.8766 0.9387 1 555 5 2.0 35 65 110 145 210 265 Age (years) >64 796 60.5025 54.669 1.9377 1 525 5 25 45 80 120 . 150 240 270 Race White 3584 51.6205 53.2589 o.8896 1 555 5 19 35 65 110 145 210 265 Race Black 377 57.0265 52.2893 2.693 1 390 5 20 40 75 120 150 210 240 Race Asian 62 54 41.8224 5.3115 2 210 5 20 50 70 105 130 175 210 Race Some Others 66 50.5909 53.2368 6.553 1 295 5 15 33.5 70 115 150 210 295 Race Hispanic 132 59.2121 49.7947 4.3341 2 315 5 23.5 55 80 110 135 225 285 Race 57 53.1404 49.297 6.5295 2 210 5 20 40 60 120 180 195 210 Hispanic No 3960 51.848 52.6035 0.8359 1 555 5 20 35 65 111 145 205 255 Hispanic Yes 254 59.2244 56.7225 3.5591 2 420 5 20 45 75 120 155 240 . 315 Hispanic DK 20 54.95 53.2002 11.8959 6 240 8 25 45 60 112.5 180 240 240 Hispanic Refused 44 58.6136 53.2957 8.0346 2 210 5 27.5 37.5 80 150 180 210 210 Employment . 210 27.1667 40.5487 2.7981 1 385 2 5 15 . 30 60 90 120 180 Employment Full Time 1988 45.4874 46.6734 1.0468 1 480 5 15 30 60 90 130 180 240 Employment Part Time 420 53.8643 55.3474 2.7007 2 520 5 20 40 65 105 125 205 255 Employment Not Employed 1625 63.6357 57.7587 1.4328 1 555 5 29 45 90 125 170 240 275 Employment Refused 35 53.5429 66.7803 11.2879 2 340 2 20 30 60 120 195 340 340 Education . 291 31.7079 42.6211 2.4985 1 385 2 5 15 37 75 120 155 195 Education < High School 450 61.2556 53.2321 2.5094 1 555 5 30 45 90 120 150 197 225 Education High School Graduate 1449 58.8392 56.6653 1.4886 1 520 5 22. 45 75 120 155 240 310 Education <College 954 52.0073 52.2377 1.6913 1 525 5 20 34.5 65 110 150 210 245 Education College Graduate 659 46.2018 48.0775 1.8728 1 515 5 15 30 60 100 125 180 224 Education Post Graduate 475 46.1621 48.7374 2.2362 1 375 5 15 30 60 96 135 200 270 Census Region Northeast 952 52.312 53.2054 1.7244 1 480 5 20 40 61 110 140 205 255 Census Region Midwest 956 53.2333 51.8139 1.6758 1 520 5 20 35 65 120 150 210 265 Census Region South 1453 53.3944 53.4621 1.4025 1 555 5 16 35 70 120 150 195 245 Census Region West 917 49.9073 52.7204 1.741 1 515 5 15 31 60 105 135 225 265 Day Of Week Weekday 2995 50.0571 49.979 0.9132 1 555 5 19 35 60 105 132 180 240 Day Of Week Weekend 1283 57.7693 58.7687 1.6407 1 420 5 20 40 75 130 180 240 300 Season Winter 1173 50.6206 48.6464 1.4204
1 480 5 18 35 65 110 135 195 240 Season Spring 1038 54.3892 54.484 1.6911 1 525 5 20 38.5 70 120 150 224 265 Season Summer 1148 51.3972 54.1854 1.5992 1 555 5 20 35 60 110 137 208 300 Season Fall 919 53.5375 54.5349 1.7989 1 520 5 20 37 67 120 155 200 265 Asthma No 3948 52.0433 53.1805 0.8464 1 555 5 20 35 65 110 145 210 265 Asthma Yes 300 57.1433 49.4425 2.8546 1 272 5 20.5 45 75 120 160 199 240 Asthma DK 30 47.6333 44.8119 8.1815 2 195 5 10 32.5 60 117.5 120 195 195 Angina No 4091 52.1936 52.9733 0.8282 1 555 5 20 35 65 115 150 210 265 Angina Yes 149 56.8054 48.2377 3.9518 1 340 5 25 45 80 120 135 180 210 Angina DK 38 53.9737 60.4168 9.8009 2 240 2 10 32.5 60 120 240 240 240 Bronchitis/Emphysema No 4024 52.0318 53.0963 0.837 1 555 5 20 35 65 110 145 210 265 Bronchitis/Emphysema Yes 216 56.9074 46.6833 3.1764 3 240 5 20 45 85 120 150 198 210 Bronchitis/Emphysema DK 38 62.3947 61.7031 10.0096 2 240 2 20 42.5 90 150 240 240 240 Note: A"*" Signifies missing data. "DK"= The replied "don't know". Refused= Refused data. N =doer sample size. Mean= Mean 24-hour cumulative number of minutes for doers. tdev =standard deviation. Stderr =standard error. Min = minimum number of minutes. Max= maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsano and Kle,,eis 1996.
Table 15-89. Statistics for 24-Hour Cumulative Number of Minutes Scent Daina Dishes/Laundrv" Percentiles Cateaorv Peculation Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 1865 61.7882 68.894 1.5953 1 825 10 20 30 80 150 190 255 335 Gender Male 324 46.1142 50.179 2.7877 1 360 10 15 30 60 120 135 210 260 Gender Female 1541 65.0837 71.793 1.8289 1 825 10 20 35 90 150 200 270 340 Age (years} . 32 43.75 46.49 8.2183 10 225 10 15 30 55 90 150 225 225 Age (years} 1-4 10 49.3 66.545 21.0434 3 210 3 5 22.5 55 165 210 210 210 Age (years} 5-11 20 34.25 28.799 6.4395 1 92 1.5 15 30 58 82.5 91 92 92 Age (years} 12-17 47 32.6809 30.603 4.4639 2 150 5 10 20 45 65 90 150 150 Age (years} 18-64 1371 63.2356 67.104 1.8123 1 565 10 20 30 90 150 198 245 335 Age (years} > 64 385 63.4416 79.738 4.0638 1 825 9 20 35 80 135 195 285 375 Race White 1560 62.2173 69.493 1.7595 1 825 10 20 30 85 147.5 190 270 335 Race Black 170 57.8471 60.026 4.6038 5 390 5 17 30 75 150 180 235 240 Race Asian 19 56.7368 51.705 11.862 3 210 3 15 30 90 120 210 210 210 Race Some Others 25 45.96 41.361 8.2721 5 150 10 15 30 80 120 120 150 150 Race Hispanic 71 69.0141 75.626 8.9752 3 325 5 20 35 105 200 225 275 325 Race Refused 20 60.75 104.217 23.3037 5 475 7.5 15 30 60 127.5 305 475 475 Hispanic No 1732 61.3077 68.206 1.6389 1 825 10 20 30 80 140 180 250 335 Hispanic Yes 112 68.2589 71.468 6.7531 3 325 5 20 30 103 180 225 270 275 Hispanic DK 7 75.7143 66.548 25.1526 10 180 10 15 55 150 180 180 180 180 Hispanic Refused 14 62.5 122.266 32.677 5 475 5 15 25 35 120 475 475 475 Employment . 73 35.3288 37.364 4.3732 1 210 3 15 20 50 80 120 150 210 Employment Full Time 776 56.9549 63.42 2.2766 2 565 10 20 30 70 125 180 240 335 Employment Part Time 214 63.7243 64.791 4.429 2 340 10 15 30 90 151 205 240 275 Employment Not Employed 789 68.5234 76.296 2.7162 1 825 10 25 40 90 158 210 285 375 Employment Refused 13 58.2308 59.448 16.4878 10 180 10 10 30 100 150 180 180 180 Education . 99 37.5253 38.655 3.885 1 210 3 10 30 55 90 120 180 210 Education < High School 216 69.7824 69.956 4.7599 2 . 570 10 26.5 45 90 151 195 245 315 Education High School Graduate 683 67.3616 76.746 2.9366 1 825 10 20 40 90 1_50 205 285 405 Education <College 422 64.3033 72.277 3.5184 2 475 10 20 30 85 155 210 285 360 Education College Graduate 262 51.4466 49.386 3.0511 1 260 10 -15 30 70 120 158 200 225 Education Post Graduate 1.83 53.6831 60.208 4.4507 3 360 5 15 30 60 120 190 245 330 Census Region Northeast 471 59.5223 60.067 2.7677 2 565 10 20 35 75 135 180 210 285 Census Region Midwest 405 60.3235 68.244 3.3911 . 1 480 5 15 30 75 150 198 240 285 Census Region South 602 65.8156 75.076 3.0599 1 825 10 20 35 90 150 210 270 360 Census Region West 387 59.814 69.562 3.536 2 570 10 15 30 70 150 210 270 345 Day Of Week Weekday 1270 59.5402 68.798 1.9305 1 825 9 20 30 75 137.5 190 245 330 Day Of Week Weekend 595 66.5866 68.909 2.825 5 565 10 20 40 90 150 210 275 340 Season Winter 503 65.3479 79.461 3.543 1 825 10 20 30 90 150 210 300 360 Season Spring 438 62 .. 7763 67.751 3.2373 2 450 10 20 35 75 150 190 285 335 Season Summer 510 61.7294 62.801 2.7809 2 565 10 20 40 90 140 180 240 270 Season Fall 414 56.4903 63.125 3.1024 1 570 8 15 30 65 130 195 230 270 Asthma No 1712 61.9533 69.64 1.6831 1 825 10 20 30 85 150 195 270 335 Asthma Yes 147 60.8912 60.62 4.9999 2 375 10 20 30 76 151 180 250 255 Asthma DK 6 36.6667 41.793 17.062 10 120 10 10 25 30 120 120 120 120 Angina No 1790 62.0788 69.212 1.6359 1 825 10 20 30 85 150 190 255 335 Angina Yes 66 54.7576 62.985 7.7529 5 335 9 25 30 60 120 200 315 335 Angina DK 9 55.5556 44.19 14.7301 10 120 10 30 30 90 120 120 120 120 Bronchitis/Emphysema No 1746 60.5063 65.326 1.5634 1 565 10 20 30 80 140 190 250 325 Bronchitis/Emphysema Yes 112 82.7143 109.505 10.3473 3 825 5 20 57.5 103 170 240 360 570 Bronchitis/Emphysema DK 7 46.7143 51.403 19.4284 2 120 2 10 30 120 120 120 120 120 Note: A"*" missing data. "DK"= The replied "don't know". Refused= Refused data. N =doer sample size. Mean= Mean 24-hour cumu alive number of minutes for doers. tdev =standard deviation. Stderr =standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. a Includes food cleanup, clothes care. Source: Tsann and Kleneis 1996. Table 15-90. Statistics for 24-Hour Cumulative Number of Minutes Spent in Housekeeping" Percentiles Category Population Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 1943 118.833 113.369 2.5719 1 810 10 40 90 165 270 345 465 540 Gender Male 370 109.419 116.541 6.0587 1 810 10 30 60 150 270 360 425 560 Gender Female 1573 121.047 112.533 2.8374 1 790 15 45 90 165 270 345 465 540 Age (years) . 47 146.043 121.3 17.6935 10 480 10 45 115 240 300 375 480 480 Age (years) 1-4 11 74.091 69.42 20.9308 10 270 10 40 60 90 90 270 270 270 Age (years) 5-11 54 42.852 34.096 4.6399 1 180 5 20 30 53 80 120 150 180 Age (years) 12-17 72 78.111 75.546 8.9031 1 300 5 27.5 . 60 105 210 240 285 300 Age (years) 18-64 1316 120.422 113.654 3.133 1 810 15 40 90 165 270 360 465 525 Age > 64 443 128.217 118.925 5.6503 3 790 10 55 90 180. 270 345 540 570 Race White 1649 119.056 112.184 2.7626 1* 790 10 40 90 165 265 340 465 540 Race Black 137 116.555 109.394 9.3462 1 490 5 30 90 150 300 358 480 484 Race Asian 32 98.75 100.467 17.7602 15 425 15 30 60 127.5 265 345 425 425 Race Some Others 26 82.423 56.436 11.0681 5 210 15 40 60 115 185 190 210 210 Race Hispanic 71 112.648 129.335 15.3492 5 660 8 30 60 135 2"70 465 518 660 Race Refused 28 189.286 176.198 33.2983 10 810 20 52.5 147.5 247.5 420 465 810 810 Hispanic No 1771 117.443 110.586 2.6278 1 790 10 40 90 165 265 335 425 525 Hispanic Yes 134 121.657 129.578 11.1939 5 660 10 35 85 135 270 470 540 658 Hispanic DK 15 146.867 127.912 33.0268 10 510 10 30 120 210 240 510 510 510. Hispanic Refused 23 191.087 180.296 37.5944 10 810 20 45 150 255 390 420 810 810 Employment . 138 65.565 68.838 5.8599 1 375 5 25 45 80 180 240 285 300 Employment Full Time 673 106.579 102.376 3.9463 1 655 10 30 70 145 240 325 413 490 Employment Part Time 193 124.72 117.48 8.4564 1 660 15 45 90 180 270 390 480 540 Employment Not Employed 925 132.681 119.442 3.9272 3 790 -15 55 105 180 295 370 484 600 Employment Refused 14 236.786 208.221 55.6495 10 810 10 120 182.5 300 430 810 810 810 Education . 171 82.164 96.944 7.4135 1 810 5 30 45 105 220 270 300 375 Education < High School 246 140.736 125.356 7.9924 3 715 10 60 120 180 300 400 540 660 Education High School Graduate 677 125.078 120.495 4.631 2 790 15 45 90 175 270 375 490 610 Education <College 433 112.898 100.145 4.8127 1 570 10 40 90 150 240 320 420 470 Education College Graduate 245 107.302 102.244 6.5321 1 585 15 30 60 150 240 328 405 465 Education Post Graduate 171 130.813 117.998 9.0236 5 655 15 60 90 180 280 390 495 540 Census Region Northeast 464 119.235 116.368 5.4022 2 790 10 35 90 165 245 330 480 655 Census Region Midwest 413 117.855 112.595 5.5405 1 715 10 34 88 165 255 345 480 525 Census Region South 648 119.912 116.159 4.5631 1 810 10 40 90 165 285 370 435 540 Census Region West 418 117.679 106.559 5.212 5 720 15 40 90 165 255 340 420 470 Day Of Week Weekday 1316 113.21 111.913 3.085 1 790 10 30 75 150 255 330 470 550 Day Of Week Weekend 627 130.635 115.567 4.6153 1 810 15 55 90 180 290 370 435 525 Season Winter 470 111.4 100.617 4.6411 1 810 10 45 85 160 240 290 390 480 Season Spring 451 122.621 114.024 5.3692 3 720 15 40 90 180 270 360 465 540 Season Summer ' 563 111.803 114.5 4.8256 1 690 10 30 75 135 255 365 465 610 Season Fall 459 131.344 122.391 5.7127 1 790 15 45 90 180 300 390 480 560 Asthma No 1789 118.529 112.075 2.6497 1 790 10 40 90 165 270 345 465 540 Asthma Yes 140 115.664 115.811 9.7878 5 690 10 36.5 67 150 277.5 377.5 470 480 Asthma DK 14 189.286 208.565 55.7414 10 810 10 45 122.5 255 340 810 810 810 Angina No 1853 117.731 112.346 2.6099 1 790 13 40 90 160 265 345 465 540 Angina Yes 75 122.88 103.762 11.9814 5 394 5 30 90 210 270 320 370 394 Angina DK 15 234.667 204 52.6725 10 810 10 120 240 300 480 810 810 810 Bronchitis/Emphysema No 1816 118.073 112.929 2.65 1 790 10 40 90 160 270 355 465 540 Bronchitis/Emphysema Yes 107 118.701 102.942 9.9518 5 480 10 30 90 180 255 290 465 470 Bronchitis/Emphysema DK 20 188.5 176.435 39.452 5 810 7.5 85 155 240 320 575 810 810 Note: A """Signifies missing data. "DK"= The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Std err= standard error. Min = minimum number of minutes. Max= maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. a Includes cleaning house, other repairs, and household work. Source: Tsana ana Kleoeis 1996. Table 15-91. Statistics for 24-Hour Cumulative Number of Minutes Spent in Bathing (a) Percentiles Group Name Group Code N Mean Stdev Std err Min Max 5* 25 50 75 90 95 98 99 All 6416 26.0842 29.6711 0.3704 1 705 5 10 20 30 50 60 90 120 Gender Male 2930 24.2416 31.0251 0.5732 1 705 5 10 20 30 45 60 75 100 Gender Female 3484 27.6372 28.4021 0.4812 1 555 5 10 20 30 60 75 105 135 Gender Refused 2 20 14.1421 10 10 30 10 10 20 30 30 30 30 30 Age (years) . 114 29.0088 38.9855 3.6513 2 300 5 10 20 30 60 60 105 275 Age (years) 1-4 330 29.9727 19.4226 1.0692 1 170 10 15 30 31 54.5 60 85 90 Age (years) 5-11 438 25.7511 35.3164 1.6875 1 690 5 15 20 30 45 60 60 75 Age (years) 12-17 444 23.1216 18.7078 0.8878 1 210 5 10 18 30 45 60 65 90 Age (years) 18-64 4383 25.4312 27.1553 0.4102 1 555 5 10 20 30 50 60 90 120 Age (years) > 64 707 29.9123 44.502 1.6737 1 705 5 10 20 30 60 85 120 150 Race White 5117 25.0233 28.5494 0.3991 1 705 5 10. 20 30 45 60 90 115 Race Black 707 31.4851 31.5524 1.1866 1 295 5 15 22 40 60 80 120 170 Race Asian 112 28.1786 29.7661 2.8126 5 270 5 15 20 30 60 75 90 90 Race Some Others 122 30.2213 27.2726 2.4691 1 240 8 15 27.5 35 50 60 100 150 Race Hispanic 280 28.7786 39.2648 2.3465 2 546 5 15 20 31.5 54.5 62.5 90 155 Race Refused 78 27.5769 40.3235 4.5657 3 275 5 10 15 30 60 1.00 195 275 Hispanic No 5835 25.8833 28.5411 0.3736* 1 705 5 10 20 30 50 60 90 120 Hispanic Yes 486 28.751 40.5582 1.8398 2 570 5 15 20 30 50 60 90 140 Hispanic DK 33 25.7576 16.7724 2.9197 5 65 10 15 20 30 55 65 65 65 Hispanic Refused 62 24.2581 37.2268 4.7278 3 275 5 10 15 25 30 60 105 275 Employment . 1189 26.1329 26.4288 0.7665 1 690 5 15 20 30 45 60 75 90 Employment Full Time 3095 24.1499 25.0984 0.4511 1 555 5 10 15 30 45 60 85 110 Employment Part Time 558 24.7616 23.2468 0.9841 1 295 5 10 20 30 46 60 90 110 Employment Not Employed 1528 30.3161 39.9341 1.0216 1 705 5 10 20 30 60 85 120 155 Employment Refused 46 30.4348 45.176 6.6608 3 275 5 10 15 30 55 105 275 275 Education . 1330 25.6759 26.4094 0.7242 1 690 5 15 20 30 45 60 75 90 Education < Higl:t School 474 33.3122 53.0129 2.435 1 570 5 15 20.5 33 60 85 110 300 Education High School Graduate 1758 25.822 23.5699 0.5621 1 270 5 10 20 30 50 60 90 120 Education <College 1288 26.'4099 27.0338 0.7533 1 255 5 10 20 30 55 75 105 150 Education College Graduate 897 25.3813 34.8197 1.1626 1 705 5 10 15 30 50 65 105 135 Education Post Graduate 669 22.7788 23.0661 0.8918 1 257 5 10 15 30 45 60 85 100 Census Region Northeast 1444 25.0478 24.2512 0.6382 1 360 5 10 20 30 50 60 90 105 Census Region Midwest 1402 24.602 30.2958 0.8091 1 570 5 10 15 30 45 60 85 115 Census Region South 2266 27.4086 26.0895 0.5481 1 300 5 15 20 30 55 65 100 135 Census Region West 1304 26.5238 38.8092 1.0747 1 705 5 10 20 30 48 60 90 133 Day Of Week Weekday 4427 25.2896 30.2913 0.4553 1 705 5 10 20 30 45 60 90 115 Day Of Week Weekend 1989 27.8527 28.1689 0.6316 1 555 5 15 20 30 60 68 100 130 Season Winter 1796 26.858 26.9167 0.6351 1 546 5 11 20 30 50 60 90 110 Season Spring 1645 28.5854 41.0512 1.01:21 1 705 5 15 20 30 60 70 115 150 Season Summer 1744 23.9295 20.7343 0.4965 1 270 5 10 19.5 30 45 60 80 100 Season Fall* 1231 24.6653 25.5885 0.7293 1 340 5 10 17 30 50 60 95 120 Asthma No 5912 26.0658 30.0373 0.3907 1 705 5 10 20 30 50 60 9o 120 Asthma Yes 468 26.5427 22.9543 1.0611 1 210 5 15 20 30 46 60 100 120 Asthma DK 36 23.1389 44.0728 7.3455 3 275 5 10 15 25 30 30 275 275 Angina No 6243 26.0042 29.0175 0.3673 1 705 5 10 20 .30 50 60 90 120 Angina Yes 131 31.145 49.5427 4.3286 5 546 5 15 25 30 50 60 105 131 Angina DK 42 22.1905 40.9153 6.3134 3 275 5 10 15 25 30 30 275 275 Bronchitis/Emphysema No 6112 26.0545 29.857 0.3819 1 705 5 10 20 30 50 60 90 120 Bronchitis/Emphysema Yes 268 27.2463 22.162 1.3538 1 150 5 13 20 30 60 60 95 131 Bronchitis/Emphysema DK 36 22.4722 44.0859 7.3477 3 275 5 10 15 22.5 30 30 275 275 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused= Refused data. N =doer sample size. Mean= Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min= minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. a Includes baby and child care, care services, washing and personal hygiene (bathing, showering, etc.) Source: Tsana and Kleneis 19 6. Table 15-92. Statistics for 24-Hour Cumulative Number of Minutes Spent in Yardwork/Maintenance (a) Percentiles Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 All 1414 147.69 148.216 3.942 1 1080 5 45 100 205 360 470 570 655 Gender Male 804 174.84 160.191 5.649 2 1080 10 60 120 249.5 415 510 600 670 Gender Female 610 111.91 121.979 4.939. 1 900 5 30 75 145 277.5 360 465 510 Age (years) . 20 181.85 170.345 38.09 5 600 10 60 116 240 467.5 570 600 600 Age (years) 1-4 12 93.167 80.805 23.326 5 285 5 30 82.5 132.5 178 285 285 285 Age (years) 5-11 26 96.154 85.532 16.774 5 330 5 39 60 120 210 300 330 330 Age (years) 12-17 54 116 116.758 15.889 3 505 5 30 90 150 285 385 450 505 Age (years) 18-64 1015 .150.22 154.486 4.849 1 1080 5 35 100 210 360 480 585 670 Age (years) > 64 287 149.3 133.834 7.9 2 810 10 60 120 20.5 330 420 525 630 Race White 1249 151.52 150.205 4.25 1 1080 5 45 105 210 360 480 575 660 Race Black 77 114.53 127.124 14.487 2 750 5 20 65 165 285 355 405 750 Race Asian 13 140 150.111 41.633 5 425 5 15 85 210 360 425 425 425 Race Some Others 26 117.23 110.647 21.7 5 380 5 30 88 178 290 360 380 380 Race Hispanic 37 102.11 113.508 18.661 5 565 5 20 60 120 255 300 565 565 Race Refused 12 177.08 190.793 55.077 30 600 30 60 97.5 215 510 600 600 600 Hispanic No 1331 148.69 147.962 4.056 1 1080 5 45 105 209 360 465 570 660 Hispanic Yes 65 106.17 127.4 15.802 5 575 5 20 60 120 255 300 565 575 Hispanic DK 8 248.75 206.48 73.002 5 585 5 90 . 190 420 585 585 585 585 Hispanic Refused 10 203.5 200.056 63.263 60 600 60 60 120 300 555 600 600 600 Employment . 92 106.82 101.779 10.611 3 .505 5 31.5 77 147.5 240 330 450 505 Employment Full Time 664 146.73 155.488 6.034 1 1080 5 35 90 202.5 360 490 575 690. Employment Part Time 121 134.51 130.79 11.89 2 554 5 30 90 200 317 390 490 495 Employment Not Employed 526 157.76 147.022 6.41 2 810 10 60 120 220 370 480 595 655 Employment Refused 11 211.55 198.724 59.918 2 600 2 60 120 375 465 600 600 600 Education . 105 113.47 113.854 11.111 2 600 5 33 79 150 285 360 450 505 Education < High School 160 158.46 164.764 13.026 2 900 7.5 45 111 210 412.5 492.5 595 810 Education High School Graduate 465 .151.39 146.985 6.816 3 840 5 50 110 210 345 460 575 690 Education <College 305 152.84 157.011 8.99 2 1080 5 45 95 210 360 473 600 630 Education College Graduate 211 145.36 138.849 9.559 1 625 5 40 105 225 330 465 525 533 Education Post Graduate 168 142.2 147.773 11.401 2 690 5 30 90 180 340 470 570 630 Census Region Northeast 291 140.5 139.641 8.186 3 840 5 40 90 200 330 450 525 600 Census Region Midwest 314 145.1 143.219 8.082 2 780 10 55 95 195 360 445 560 655 Census Region . South 438 152.69 156.36 7.471 2 1080 5 45 111 205 375 480 585 635 Census Region West 371 149.63 149.345 7.754 1 750 5 40 104 210 350 480 575 690 Day Of Week Weekday 878 140.86 140.753 4.75 1 810 5 40 92.5 190 345 460 560 625 Day Of Week . Weekend 536 158.88 159.193 6.876 2 1080 5 50 116.5 225 380 510 600 690 Season Winter 289 139.35 151.711 8.924 1 690 5 30 75 195 360 480 565 600 Season Spring 438 162.23 150.477 7.19 3 900 10 60 120 220 360 480 570 700 Season Summer 458 137.92 140.291 6.555 2 1080 5 40 90 180 310 440 555 630 Season Fall 229 149.97 153.398 10.137 2 720 5 40 97 210 390 480 600 655 Asthma No 1311 146.95 147.084 4.062 1 1080 5 45 100 200 355 465 570 635 Asthma Yes 98 149.27 155.758 15.734 5 670 5 30 90 210 445 480 670 670 Asthma DK 5 312 230.043 102.879 60 600 60 120 300 480 600 600 600 600 Angina No 1360 145.34 145.05 3.933 1 900 5 45 100 200 355 465 570 655 Angina Yes 42 192.62 203.363 31.38 5 1080 15 60 142.5 255 465 485 1080 1080 Angina DK 12 257.08 216.716 62.56 5 600 .5 52.5 232.5 4 72.5 510 600 600 600 Bronchitis/Emphysema No 1352 148.48 148.534 4.04 1 1080 5 45 105 205 360 470 570 660 Bronchitis/Emphysema Yes 57 114.65 121.376 16.077 5 460 5 30 60 135 340 375 405 460 Bronchitis/Emphysema DK 5 312 230.043 102.879 60 600 60 120 300 480 600 600 600 600 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused= Refused data. N =doer sample size. Mean= Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Std err= standard error. Min = minimum number of minutes. Max= maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. a Includes car repair services, other repairs services, outdoor cleaning, car repair maintenance, other repairs, plant care, other household work, domestic crafts, domestic arts. Source: Tsana and Kleoeis 1996 .. Table 15-93. Statistics for 24-Hour Cumulative Number of Minutes Spent in Sports/Exercise (a) Percentiles Category Population Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 1852 116.322 107.947 2.5084 1 1130 17 45 85 150 253 316 420 515 Gender Male 958 130.669 117.216 3.7871 1 1130 20 55 97.5 175 270 355 475 558 Gender Female 892 100.854 94.795 3.174 1 1065 15 35 65 130 230 285 370 435 Gender Refused 2 142.5 38:891 27.5 115 170 115 115 143 170 170 170 170 170 Age (years) . 32 102.031 79.32 14.022 5 290 15 40 80 137.5 225 270 290 290 Age (years) 1-4 114 118.982 109.17 10.2247 10 670 25 45 90 159 250 330 390 630 Age (years) 5-11 262 153.496 130.58 8.0673 2 975 .20 60 120 200 330 415 525 580 Age (years) 12-17 237 134.717 122.228 7.9396 5 1065 15 60 110 179 265 360 470 520 Age (years) 18-64 992 109.692 100.801 3.2004 1 1130 20 45 75 145 240 300 405 510 Age (years) > 64 215 82.051 75.995 5.1828 1 380 10 30 60 110 195 270 310 316 Race White 1541 117.524 110.622 2.818 1 1130 20 45 85 150 255 320 435 525 Race Black 135 110.4 93.06 8.0094 5 440 15 45 85 150 220 340 430 435 Race Asian 37 85.432 73.897 12.1486 5 310 10 30 60 95 210 235 310 310 Race Some Others 47 124.702 106.397 15.5196 15 553 30 40 85 180 270 325 553 553 Race Hispanic 74 108.892 89.177 10.3667 1 520 15 45 90 145 225 270 345 520 Race Refused 18 130 111.698 26.3275 30 420 30 60 82.5 140 300 420 420 420 Hispanic No 1678 116.451 108.276 2.6432 1 1130 17 45 85 150 253 316 430 510 Hispanic Yes 151 115.583 106.428 8.661 1 630 15 45 90 145 240 325 415 553 Hispanic DK 7 92.857 62.773 23.726 20 185 20 30 75 145 185 185 185 185 Hispanic Refused 16 120 110 27.5 30 420 30 60 70 122.5 290 420 420 420 Employment . 606 138.658 123.665 5.0235 2 1065 20 60 110 180 285 375 470 580 Employment Full Time 644 102.315 94.146 3.7099 5 1130 20 45* 67.5 130 225 280 360 405 Employment Part Time 125 115.272 . 91.33 8.1688 1 450 15 45 90 160 220 300 420 420 Employment Not Employed 465 107.239 104.105 4.8277 1 600 10 31 70 135 250 310 462 515 Employment Refused 12 102.917 87.917 25.3794 30 280 30 40 75 130 270 280 280 280 Education . 663 139.46 123.813 4.8085 2 1065 20 60 110 180 285 383 510 580 Education < High School 103 96.243 97.046 9.5622 10 570 15 30 60 135 210 270 305 510 Education High School Graduate 341 109.276 106.483 5.7664 1 1130 15 40 75 150 235 285 405 485 Education <College 265 110.068 94.836 5.8257 1 525 17 45 80 145 240 305 418 475 Education College Graduate 258 105.717 92.204 5.7404 1 600 20 45 70 130 240 297 343 450 Education Post Graduate 222 87.149 79.704 5.3494 5 375 15 30 60 105 208 290 355 360 Census Region Northeast 437 126.865 122.905 5.8793 1 1130 15 50 95 165 270 338 470 558 Census Region Midwest 341 105.889 94.38 5.111 5 570 20 40 75 135 240 280 430 438 Census Region South 627 112.774 104.846 4.1872 1 975 15 45 80 150 250 313 410 462 Census Region West 447 118.951 105.629 4.9961 4 670 22 48 85 160 250 325 475 525 Day Of Week Weekday 1264 107.154 94.026 2.6447 1 670 15 45 75 140 235 285 375 485 Day Of Week Weekend 588 136.029 130.966 5.401 1 1130 20 51.5 90 180 297 380 462 558 Season Winter 448 104.094 104.108 4.9187 1 1065 15 40 70 130 230 280 360 420 Season Spring 533 123.452 100.904 4.3706 5 650 25 60 90 162 267 330 420 500 Season Summer 579 125.988 114.358 4.7525 1 670 15 45 90. 160 283 360 470 545 Season Fall 292 102.901 110.416 6.4616 4 1130 15 40 60 127.5 225 275 460 565 Asthma No 1699 114.927 105.239 2.5532 1 1130 17 45 85 150 250 310 420 510 Asthma Yes 137 132.131 134.238 11.4687 1 1065 15 60 90 165 265 390 553 565 Asthma DK 16 129.063 134.786 33.6966 10 450 10 60 60 152.5 420 450 450 450 Angina No 1801 117.3 108.373 2.5537 1 1130 20 45 89 150 254 316 430 515 Angina Yes 40 68 70.942 11.217 5 330 5.5 30 47.5 60 172.5 235 330 330 Angina DK 11 131.818 116.023 34.9823 40 420 40 60 90 155 270 420 420 420 Bronchitis/Emphysema No 1782 116.226 107.987 2.5581 1 1130 17 45 85 150 250 315 430 515 Bronchitis/Emphysema Yes 56 119.429 108.516 14.501 10 553 20 42.5 75 172.5 270 340 410 553 Bronchitis/Emphysema DK 14 116.071 108.187 28.9143 15 420 15 60 85 140 270 420 420 420 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Stderr =standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. a Includes active sports, exercise, hobbies. Source: Tsana and Kleoeis. 1996. Table 15-94. Statistics for 24-Hour Cumulative Number of Minutes Eatina or Drinkina Percentiles Cateaorv Population Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 8627 74.8821 54.8419 0.5904 1 900 15 35 60 96 140 175 215 270 Gender Male 3979 75.8316 56.2313 0.8914 1 900 15 39 60 96 140 180 210 270 Gender Female 4644 74.0814 53.6353 0.7871 2 640 15 34 60 98 140 170 225 270 Gender Refused 4 60 21.2132 10.6066 30 75 30 45 67.5 75 75 75 75 75 Age (years) . 157 75.3248 50.1255 4.0005 10 315 15 30 65 100 145 150 195 285 Age (years) 1-4 492 93.4837 52.8671 2.3834 2 345 20 60 90 120 160 190 225 270 Age (years) 5-11 680 68.5412 38.9518 1.4937 5 255 15 40 65 90 120 142.5 165 195 Age (years) 12-17 538 55.8587 34.9903 1.5085 2 210 10 30 50 75 105 125 150 170 Age (years) 18-64 5464 71.8673 55.1199 0.7457 1 900 15 30 60 90 135 170 220 270 Age (years) > 64 1296 91.7014 62.6665 1.7407 5 750 20 50 80 120 165 200 270 295 Race White 7049 77.0058 55.6564 0.6629 1 900 15 40 64 100 145 180 225 270 Race Black 808 59.9047 46.5954 1.6392 2 505 15 30 50 75 119 140 200 225 Race Asian 148 80.4054 47.8283 3.9315 2 305 15 45 72.5 106.5 150 160 200 200 Race Some others 168 66.0417 52.0928 4.019 7 525 15 30 59.5 83 120 135 190 200 Race Hispanic 345 68.7043 51.8926 2.7938 2 435 12 30 60 90 125 165 195 225 Race Refused 109 74.2477 60.8473 5.8281 8 410 20 30 60 90 130 180 290 315 Hispanic No 7861 75.5599 55.2306 0.6229 1 900 15 35 60 100 140 175 220 270 Hispanic Yes 639 68.2754 50.1994 1.9859 2 435 15 30 60 90 120 155 195 225 Hispanic DK 41 60.4146 37.1039 5.7947 5 150 15 30 55 90 120 130 150 150 Hispanic Refused 86 68.9186 55.4732 5.9818 8 410 15 30 60 90 115 155 210 410 Employment . 1695 72.2083 44.9086 1.0908 2 345 15 40 65 90 133 150 195 210 Employment Full Time 3684 70.6097 55.0998 0.9078 1 900 15 30 60 90 135 165 225 270 Employment Part Time 715 72.2112 55.4476 2.0736 2 509 15 30 60 90 135 170 230 260 Employment Not Empl.oyed 2472 83.9498 59.1281 1.1892 2 750 15 45 75 110 150 185 235 285 Employment Refused 61 71.0492 60.9843 7.8082 8 385 15 30 55 90 120 145 235 385 Education . 1867 70.85 45.3955 1.0506 2 375 15 38 60 90 130 150 190 210 Education < High School 758 72.3206 57.4352 2.0861 .2 460 15 30 60 90 135 180 230 315 Education High School Graduate 2363 74.8565 57.1005 1.1746 1 900 15 35 60 96 140 175 220 270 Education <College 1612 73.9237 56.5324 1.408 2 525 15 30 60 90 145 175 230 275 Education College Graduate 1160 78.4991 55.4196 1.6272 1 640 15 40 65 105 145 180 220 265 Education Post Graduate 867 82.8166 59.6871 2.0271 2 750 15 40 70 110 150 185 240 270 Census Region Northeast 1916 78.2766 59.1627 1.3516 1 750 15 37 65 102.5 145 180 240 285 Census Region Midwest 1928 75.8117 51.3702 1.1699 1 435 15 40 64 100 140 175 210 255 Census Region South 2960 71.3916 55.0903 1.0126 2 900 15 30 60 90 135 165 210 270 Census Region West 1823 75.9989 52.9755 1.2407 .2 500 15 35 60 100 150 180 210 240 Day Of Week Weekday 5813 71.2069 52.0446 0.6826 1 900 15 33 60 90 130 165 210 250 Day Of Week Weekend 2814 82.4741 59.5052 1.1217 2 630 15 40 70 110 150 190 240 297 Season Winter 2332 76.0931 56.4379 1.1687 2 640 15 38.5 65 95.5 140 . 175 240 275 Season Spring 2222 76.3096 55.207 1.1712 1 630 15 35 60 100 145 178 220 275 Season Summer 2352 73.4787 53.2506 1.098 1 750 15 35 60 95 135 170 210 260 Season Fall 1721 73.3161 54.2737 1.3083 2 900 15 30 60 95 140 175 210 232 Asthma No 7937 75.2016 54.8093 0.6152 1 900 15 35 60 100 140 175 215 270 Asthma Yes 635 71.3732 55.0353 2.184 2 460 15 30 60 90 133 170 225 285 Asthma DK 55 69.2909 56.5874 7.6302 8 335 15 30 60 90 120 210 215 335 Angina No 8318 74.5795 54.4372 0.5969 1 900 15 35 60 95 140 175 210 265 Angina Yes 243 85.0288 63.5335 4.0757 2 500 15 45 75 115 160 180 285 330 Angina DK 66 75.6667 67.304 8.2845 5 435 15 30 60 90 150 195 215 435 Bronchitis/Emphysema No 8169 74.6605 54.3234 0:601 1 900 15 35 60 95 140 170 210 260 Bronchitis/Emphysema Yes 397 80.6599 65.2442 3.2745 2 460 15 30 60 110 150 180 285 360 Bronchitis/Emphysema DK 61 66.9508 47.7188 6.1098 8 230 15 30 60 90 120 155 215 230 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused= Refused data. N =doer sample size. Mean= Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Std err= standard error. Min= minimum number of minutes. Max= maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleneis 1996. Table 15-95. Statistics for 24-Hour Cumulative Number of Minutes Scent Indoors at an Auto Reoair Shoo/Gas Station Percentiles Cateqorv Population Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 153 190.693 234.506 18.959 1 930 5 15 60 360 565 645 695 748 Gender Male 105 241.476 250.274 24.424 2 930 5 15 115 495 600 675 700 748 Gender Female 48 79.604 144.512 20.858 1 595 3 10 15 70 295 485 595 595 Age (years)
3 161.667 115.578 66.729 90 295 90 90 100 295 295 295 295 295 Age (years) 1-4 4 40 50.166 25.083 10 115 10 12.5 17.5 67.5 115 115 115 115 Age (years) 5-11 5 22 21.679 9.695 5 60 5 15 15 15 60 60 60 60 Age (years) . 12-17 7 153.857 205.069 77.509 3 505 3 5 55 390 505 505 505 505 Age (years) 18-64 118 223.847 249.335 22.953 1 930 5 15 75 480 600 675 700 748 Age (years) > 64 16 58.125 96.889 24.222 2 358 2 15 20 42.5 225 358 358 358 Race White 130 195.538 237.537 20.833 -1 930 5 15 60 390 587.5 645 700 748 Ra.ce Black 12 149.667 203.31 58.691 2 565 2 6.5 75 229 495 565 565 565 Race Asian 5 173 231.236 103.412 5 525 5 15 25 295 525 525 525 525 Race Some Others 3 15 10 5.774 5 25 5 5 15 25 25 25 25 25 Race Hispanic 3 350 330.114 190.591 15 675 15 15 360 675 675 675 675 675 Hispanic No 148 188.926 233.749 19.214 1 930 5 *15 60 369.5 565 630 700 748 Hispanic Yes 5 243 279.701 125.086 15 675 15 15 150 360 675 675 675 675 Employment

16 84.188 146.714 36.678 3 505 3 12.5 17.5 69.5 390 505 505 505 Employment Full Time 84 283.571 263.755 28.778 3 930 5 17.5 230 540 630 680 748 930 Employment Part Time 16 104.188 147.369 36.842 5 390 5 12.5. 17.5 187.5 359 390 390 390 Employment Not Employed 35 65.914 94.745 16.015 1 432 2 15 30 90 160 358 432 432 Employment Refused 2 17.5 17.678 12.5 5 30 5 5 17.5 30 30 30 30 30 Education

18 95.056 153.879 36.27 3 505 3 10 17.5 79 390 505 505 505 Education < High School 16 327.188 301.181 75.295 5 930 5 60 278 615 675 930 930 930 Education High School Graduate 51 233.353 243.089 34.039 2 748 5 20 120 480 565 675 695 748 Education <College 32 253.469 252.8 44.689 2 700 5 15 157 517.5 595 680 700 700 Education College Graduate 19 72.895 126.321 28.98 1 508 1 5 20 90 295 508 508 508 Education Post Graduate 17 49 73.388 17.799 5 235 5 10 15 35 225 235 235 235 Census Region Northeast 29 247.31 257.069 47.737 2 930 3 30 120 432 600 748 930 930 Census Region Midwest 48 230.896 251.622 36.318 1 700 5 17.5 74.5 510 600 680 700 700 Census Region South 43 165.721 211.591 32.267 3 675 5 15 50 358 555 595 675 675 Census Region West 33 115 198.907 34.625 5 675 5 10 15 100 505 645 675 675 Day Of Week Weekday 121 204.645 244.861 22.26 1 930 5 15 60 390 595 675 700 748 Day Of Week Weekend 32 137.938 184.175 32.558 2 540 3 15 40 200 505 510 540 540 Season Winter 28 177.143 258.088 48.774 2 930 5 15 30 355 595 700 930 930 Season Spring 44 189.636 223.267 33.659 2 645 5 15 79.5 384.5 565 600 645 645 Season Summer 52 171.692 223.809 31.037 1 680 3 10 30 347.5 540 675 675 680 Season Fall 29 239.448 251.391 46.682 5 748 8 35 95 445 605 695 748 748 Asthma No 145 191.29 235.288 19.54 1 930 5 15 60 360 565 645 700 748 Asthma Yes 8 179.875 234.838 83.028 5 600 5 5 37.5 374.5 600 600 600 600 Angina No 149 191.047 235.262 19.273 1 930 5 15 60 360 585 645 700 748 Angina Yes 4 177.5 235.744 117.872 5 510 5 10 97.5 345 510 510 510 510 Bronchitis/Emphysema No 146 189.048 234.959 19.445 1 930 5 15 57.5 360 585 645 700 748 Bronchitis/Emphysema Yes 7 225 239.948 90.692 5 555 5 5 95 510 555 555 555 555 Note: A"*" Signifies missing data. Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Stderr =standard error. Min= minimum number of minutes. Max= maximum number of minutes. *percentiles are the of doers below or to a given number of minutes. Source: sana and Kleoeis 19 6.
Table 15-96. Statistics for 24-Hour Cumulative Numbr of Minutes Spent Indoors at a Gym/Health Club Percentiles Cateaorv Population Grouo N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 364 129.651 104.343 5.4691 5 686 30 60 110 155 240 320 525 600 Gender Male 176 147.193 115.554 8.7102 5 686 30 77.5 120 175 285 360 533 660 Gender Female 188 113.229 89.876 6.5549 5 660 30 60 92.5 135 200 279 420 560 Age (years) . 6 202.5 227.854 93.0211 30 560 30 55 75 420 560 560 560 560 Age (years) 1-4 5 156 29.875 13.3604 105 180 105 160 160 175 180 180 180 180 Age (years) 5-11 28 105.286 69.537 13.1413 5 325 30 58 82.5 141 165 270 325 325 Age (years) 12-17 39 165.385 122.056 19.5447 15 660 30 90 138 206 330 440 660 660 Age (years) 18-64 254 123.134 98.827 6.2009 5 686 30 60 100 150 210 295 475 600 Age (years) > 64 32 141.375 114.216 20.1907 10 533 30 60 103 173 292 340 533 533 Race White 307 134.261 109.36 6.2415 5 686 30 65 110 164 255 330 533 600 Race Black 30 117.7 75.418 13.7693 5 320 10 60 115 145 235 285 320 320 Race Asian 10 75.2 36.484 11.5372 30 145 30 54 60 95 133 145 145 145 Race Some Others 11 112.909 69.077 20.8276 25 270 25 65 90 153 179 270 270 270 Race Hispanic 4 83.75 42.696 21.3478 40 140 40 52.5 77.5 115 140 140 140 140 Race Refused *2 57.5 3.536 2.5 55 60 55 55 57.5 60 60 60 60 60 Hispanic No 345 132.017 105.901 5.7015 5 686 30 65 110 160 240 325 533 600 Hispanic Yes 17 90.118 58.765 14.2527 5 255 5 60 90 115 140 255 255 255 Hispanic Refused 2 57.5 3.536 2.5 55 60 55 55 57.5 60 60 60 60 60 Employment . 72 139.625 103.274 12.171 5. 660 30 76 120 165 265 330 440 660 Employment Full Time 176 131.193 112.511 8.4808 5 686 30 60 110 150 240 330 560 660 Employment Part Time 40 129.25 92.836 14.6787 25 420 35 60 95 168 285 325 420 420 Employment Not Employed 75 117.867 91.345 10.5477 5 533 25 60 90 145 230 285 475 533 Employment Refused 1 40 . . 40 40 40 40 40 40 40 40 40 40 Education . 81 136.877 99.66 11.0733 5 660 30 75 120 164 215 325 440 660 Education < High School 9 110.556 97.706 32.5688 10 300 10 30 80 165 300 300 300 300 Education High School Graduate 61 128.475 110.005 14.0847 5 660 25 75 105 145 210 310 525 660 Education <College 71 145.634 129.073 15.3181 5 600 35 65 110 170 285 533 560 600 Education College Graduate 81 121.975 99.467 11.0519 15 686 30 60 98 135 220 285 420 686 Education Post Graduate 61 115.639 76.916 9.8481 10 415 40 60 90 145 225 265 320 415 Census Region Northeast 83 140.53 107.244 11.7716 20 660 40 70 120 170 240 330 600 660 Census Region Midwest 62 127 88.661 11.26 5 440 25 60 113 170 285 300 340 440 Census Region South 118 125.669 107.038 9.8537 5 660 15 60 105 150 240 330 533 540 Census Region West 101 126.99 108.452 10.7914 5 686 50 60 92 135 225 292 525 560 Day Of Week Weekday 281 121.26 96.577 5.7613 5 686 30 60 98 145 210 295 475 560 Day Of Week Weekend 83 158.06 123.652 13.5726 5 660 30 77 120 180 285 415 600 660 Season Winter 127 139.795 108.258 9.6063 5 686 25 75 120 177 240 330 533 660 Season Spring 85 141.459 115.229 12.4983 10 600 30 65 102 164 285 340 560 600 Season Summer 81 109.864 87.411 9.7123 5 525 30 60 90 130 160 310 440 525 Season Fall 71 119.944 98.963 11.7447 20 660 30 56 98 150 215 295 420 660 Asthma No 333 132.39 106.796 5.8524 5 686 30 62 110 160 255 325 533 600 Asthma Yes 28 100.071 69.387 13.113 5 330 25 60 86 118 210 230 330 330 Asthma DK 3 101.667 55.752 32.1887° 60 165 60 60 80 165 165 165 165 165 Angina No 357 130.499 104.98 5.5561 5 686 30 62 110 155 240 325 525 600 Angina Yes 4 90 47.61 23.8048 60 160 60 60 70 120 160 160 160 160 Angina DK 3 81.667 65.256 37.6755 30 155 30 30 60 155 155 155 155 155 Bronchitis/Emphysema No 352 130.696 104.843 5.5882 5 686 30 61 110 158 240 320 525 600 Bronchitis/Emphysema Yes 10 97.3 92.848 29.361 10 330 10 45 76.5 120 245 330 330 330 Bronchitis/Emphysema DK 2 107.5 67.175 47.5 60 155 60 60 108 155 155 155 155 155 Note: A "*" Signifies missing data. "DK"= The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Stderr =standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleneis. 1996. Table 15-97. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at the Laundromat Percentiles Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 All 40 99.275 85.209 13.4727 2 500 5 54.5 91 120 153 238 500 500 Gender Male 9 150.222 146.822 48.9407 2 500 2 115 120 150 500 500 500 500 Gender Female 31 84.484 51.822 9.3075 5 265 5 50 80 115 137 155 265 265 Age (years) 5-11 3 80.667 17.926 10.3494 60 92 60 60 90 92 92 92 92 92 Age (years) 18-6"4 33 101.182 91.724 15.967 2 500 5 50 90 120 155 265 500 500 Age (years) > 64 4 97.5 63.574 31.7871 5 150 5 60 118 135 150 150 150 150 Race White 31 102.161 93.832 16.8527 2 500 5 50 90 120 155 265 500 500 Race Black 6 75.667 50.306 20.5372 5 130 5 34 85 115 130 130 130 130 Race Hispanic 3 116.667 30.551 17.6383 90 150 90 90 110 150 150 150 150 150 Hispanic No 37 97.865 88.241 14.5068 2 500 5 50 90 120 155 265 500 500 Hispanic Yes 3 116.667 30.551 17.6383 90 150 90 90 110 150 150 150 150 150 Employment . 3 80.667 17.926 10.3494 60 92 60 60 90 92 92 92 92 92 Employment Full Time 20 97.6 104.739 23.4203 2 500 4 42 83.5 115 143 328 500 500 Employment Part Time 4 127.5 91.879 45.9393 75 265 75 77.5 85 178 265 265 265 265 Employment Not Employed 13 97.462 60.852 16.8772 5 210 5 45 115 137 150 210 210 210 Education . 3 80.667 17.926 10.3494 60 92 60 60 90 92 92 92 92 92 Education < High School 6 95 53.292 21.7562 5 150 5 60 113 130 150 150 150 150 Education High School Graduate 17 101.353 64.434 15.6275 5 265 5 59 90 120 210 265 265 265 Education <College 6 91.5 56.387 23.0199 10 155 10 34 115 120 155 155 155 155 Education College Graduate 7 126.429 168.219 63.5808 5 500 5 45. 70 110 500 500 500 500 Education Post Graduate 1 2 . . 2 2 2 2 2 2 2 2 2 2 Census Region Northeast 6 168.667 166.465 67.9591 45 500 45 75 126 140 500 500 500 500 Census Region Midwest 8 94 60.328 21.3291 5 210 5 57.5 93.5 118 210 210 210 210 Census Region South 18 85.944 61.82 14.5711 2 265 2 50 76 115 155 265 265 265 Census Region West 8 82.5 52.915 18.7083 5 150 5 35 100 118 150 150 150 150 Day Of Week Weekday 25 103.32 100.663 20.1326 2 500 5 50 90 115 155 265 500 500 Day Of Week Weekend 15 92.533 52.697 13.6063 10 210 10 60 92 130 150 210 210 210 Season Winter 11 86.455 57.98 17.4816 2 210 2 45 80 120 140 210 210 210 Season Spring 12 85.583 71.678 20.6916 5 265 5 35 73.5 120 130 265 265 265 Season Summer 12 118.667 125.78 36.3096 5 500 5 55 101 113 137 500. 500 500 Season Fall 5 113.8 48.422 21.655 34 155 34 115 115 150 155 155 155 155 Asthma No 37 95.459 83.88 13.7897 2 500 5 50 90 120 150 210 500 500 Asthma Yes 3 146.333 106.514 61.4962 59 265 59 59 115 265 265 265 265 265 Angina No 40 99.275 85.209 13.4727 2 500 5 54.5 91 120 153 238 500 500 Bronchitis/Emphysema No 35 92.314 84.343 14.2565 2 500 5 50 90 115 130 210 500 500 Bronchitis/Emphysema Yes 5 148 83.262 37.2357 30 265 30 140 150 155 265 265 265 265 Note: A "*"Signifies missing data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max= maximum number of minutes. Percentiles are the percentage of doers below or equal to a given numbefof minutes. Source: Tsana and Kleoeis, 1996. Table 15-98. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at Work (non-specific) Percentiles Cateqorv Pooulation Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 All 137 393.949 242.649 20.731 5 979 15 180 440 555 662 810 940 960 Gender Male 96 435.271 243.979 24.901 10 979 20 245 473 598 765 840 960 979 Gender Female 41 297.195 212.415 33.174 5 780 15 90 280 495 550 . 590 780 780 Age (years)
4 568.75 394.723 197.362 90 940 90 248 623 890 940 940 940 940 Age (years) 1-4 2 200 70.711 50 150 250 150 150 200 250 250 250 250 250 Age (years) 5-11 4 33.75 11.087 5.543 20 45 20 25 35 42.5 45 45 45 45 Age (years) 12-17 2 207.5 166.17 117.5 90 325 90 90 208 325 325 325 325 325 Age (years) 18-64 121 409.678 230.934 20.994 5 979 15 240 450 560 660 793 850 960 Age (years) > 64 4 293.75 289.464 144.732 10 610 10 50 278 538 610 610 610 610 Race White 113 397.903 235.199 22.126 5 979 15 210 450 555 660 780 940 960 Race Black 13 379.231 286.501 79.461 10 850 10 85 405 510 810 850 850 850 Race Some others 1 405 *

405 405 405 405 405 405 405 405 405 405 *Race Hispanic 9 314.778 266.161 . 88.72 30 793 30 95 245 440 793 *793 793 793 Race Refused 1 840 *

840 840 840 840 840 840 840 840 840 840 Hispanic No 121 388.702 242.092 22.008 5 979 15 180 405 550 660 795 940 960 Hispanic Yes 12 361.083 242.06 69.877 30 793 30 138 370 510 660 793 793 793 Hispanic DK 2 585 35.355 25 560 610 560 560 585 610 610 610 610 610 Hispanic Refused 2 717.5 173.241 122.5 595 840 595 595 718 840 840 840 840 840 Employment

8 118.75 113.916 40.275 20 325 20 35 67.5 200 325 325 325 325 Employment Full Time 97 440.732 237.56 24.121 10 979 15 300 480 585 690 815 960 979 Employment Part Time 21 341.19 188.235 41.076 30 795 115 240 330 435 590 610 795 795 Employment Not Employed 9 250.556 218.567 72.856 5 630 5 95 150 360 630 630 630 630 Employment Refused 2 425 586.899 415 10 840 10 10 425 840 840 840 840 840 Education

11 234.091 266.306 80.294 20 840 20 40 150 325 610 840 840 840 Education < High School 12 460.417 181.727 52.46 115 795 115 330 495 "558 615 795 795 795 Education High School Graduate 50 409.6 273.717 38.709 5 979 15 150 463 619 735 940 969.5 979 Education <College 29 368.897 237.58 44.117 10 850 10 160 405 510 660 765 850 850 Education College Graduate 22 405.682 184.225 39.277 90 815 150 240 375 540 595 645 815 815 Education Post Graduate 13 443.692 218.128 60.498 10 793 10 360 500 585 630 793 793 793 Census Region Northeast 22 405.545 193.817 41.322 15 765 90 320 398 540 660 662 765 765 Census Region* Midwest 26 418.577 250.898 49.205 10 940 13 180 473 610 690 780 940 940 Census Region South 58 379.707 233.179 30.618 5 979 10 150 420 540 619 810 815 979 Census Region West 31 391.71 289.538 52.003 10 960 20 90 405 630 795 850 960 960 Day Of Week Weekday 121 401.843 242.472 22.043 5 979 15 210 450 560 660 810 940 960 Day Of Week Weekend 16 334.25 243.28 60.82 13 795 13 97.5 340 495 690 795 795 795 Season Winter 42 390.81 241.456 37.257 10 960 30 175 405 550 660 765 960 960 Season Spring 34 361.324 236.996 40.644 10 840 30 150 360 525 660 815 840 840 Season Summer 41 400.902 262.9 41.058 5 979 13 210 450 570 690 810 979 979 Season Fall 20 441.75 219.411 49.062 10 793 12.5 285 490 620 661 727.5 793 793 Asthma No 124 393.218 237.29 21.309 5 960 20 180 440 553 660 795 850 940 Asthma Yes 13 400.923 300.15 83.247 10* 979 10 240 320 590 793 979 979 979 Angina No 133 397.677 243.291 21.096 5 979 15 190 440 555 662 810 940 960 Angina Yes 3 266.667 255.799 147.686 90 560 90 90 150 560 560 560 560 560 Angina DK 1 280 *

280 280 280 280 280 280 280 280 280 280 Bronchitis/Emphysema No 131 397.13 242.048 21.148 5 979 20 180 440 555 662 810 940 960 Bronchitis/Emphysema Yes 5 333.4 299.365 133.88 10 619 10 13 460 565 619 619 619 619 Bronchitis/Emphysema DK 1 280 *

280 280 280 280 280 280 280 280 280 280 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused= Refused data. N =doer sample size. Mean= Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Stderr = standard error. Min = minimum number of minutes. Max= maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996.

Table 15-99. Statistics for 24-Hour Cumulative Number of Minutes Soent Indoors at the Orv Cleaners Percentiles Cateoorv Pooulation Grouo N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 All 34 82.029 151.651 26.008 2 515 5 5 10 90 325 500 515 515 Gender Male 11 105.545 166.006 50.053 2 515 2 5 10 103 325 515 515 515 Gender Female 23 70.783 146.839 30.618 5 500 5 5 10 35 300 485 500 500 Age (years) . 1 485 . . 485 485 485 485 485 485 485 485 485 485 Age (years) 1-4 2 20 21.213 15 5 35 5 5 20 35 35 35 35 35 Age (years) 18-64 28 61.036 120.923 22.852 2 515 5 5 10 55 300 325 515 515 Age (years) > 64 3 185 273.359 157.824 10 500 10 10 45 500 500 500 500 500 Race White 25 70.72 143.744 28.749 2 515 5 5 10 35 300 485 515 515 Race Black 7 131.429 198.95 75.196 5 500 5 10 20 325 500 500 500 500 Race Some Others 1 10 . . 10 10 10 10 10 .10 10 10 10 10 Race Hispanic 1 91 . . 91 91 91 91 91 91 91 91 91 91 Hispanic No 31 83.806 158.483 28.464 2 515 5 5 10 45 325 500 515 515 Hispanic Yes 3 63.667 46.479 26.835 10 91 10 10 90 91 91 91 91 91 Employment . 2 20 21.213 15 5 35 5 5 20 35 35 35 35 35 Employment Full Time 25 83.12 151.81 30.362 2 515 5 5 10 90 325 485 515 515 Employment Part Time 1 500 . . 500 500 500 500 500 500 500 500 500 500 Employment Not Employed 6 28.5 33.934 13.853 5 91 5 10 10 45 91 91 91 91 Education . 2 20 21.213 15 5 35 5 5 20 35 35 35 35 35 Education < High School 4 234 209.191 . 104.595 45 500 45 68 196 400 500 500 500 500 Education High School Graduate 8 84.125 165.008 58.339 5 485 5 13 17.5 62 485 485 485 485 Education <College 6 146.333 220.347 89.956 5 515 5 10 11.5 325 515 515 515 515 Education College Graduate 12 13.5 24.247 6.999 2 90 2 5 5 10 10 90 90 90 Education Post Graduate 2* 50 63.64 45 5 95 5 5 50 95 95 95 95 95 Census Region Northeast 8 110 187.293 66.218 5 485 5 5 10 180 485 485 485 485 Census Region Midwest 10 19.1 30.101 9.519 5 103 5 5 7.5 20 61.5 103 103 103 Census Region South 8 197 211.975 74.945 15 515 15 30 93 400 515 515 515 515 I Census Region West 8 17.75 29.359 10.38 2 90 2 5 10 10 90 90 90 90 Day Of Week Weekday 23 93.957 172.77 36.025 2 515 5 5 10 90 485 500 515 515 Day Of Week Weekend 11 57.091 95.985 28.941 5 325 5 5 10 95 103 325 325 325 Season Winter 12 74.583 158.092 45.637 5 485 5 5 10 13 325 485 485 485 Season Spring 4 44.5 41.685 20.843 10 103 10 15 32.5 74 103 103 103 103 Season Summer 8 20.25 32.012 11.318 2 95 2 5 5 23 95 95 95 95 Season Fall 10 155.4 205.739 65.061 5 515 5 13 55 300 507.5 515 515 515 Asthma No 32 86.688 155.244 27.443 2 515 5 5 11.5 91 325 500 . 515 515 Asthma Yes 2 7.5 3.536 2.5 5 10 5 5 7.5 10 10 10 10 10 Angina No 33 83.909 153.599 26.738 2 515 5 5 10 90 325 500 515 515 Angina Yes 1 20 . . 20 20 20 20 20 20 20 20 20 20 Bronchitis/Emphysema No 33 84.061 . 153.532 26.726 2 515 5 5 10 90 325 500 515 515 Bronchitis/Emphysema Yes 1 15 . . 15 15 15 15 15 15 15 15 15 15 Note: A"*" missinfj data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Std err= stan ard error. Min = minimum number of minutes. Max= maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes.

Source: Tsann and Kleneis 1996.
Table 15-100. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at a Bar/Niqhtclub/Bowlina Allev Percentiles Cateqorv Pooulation Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 352 175.818 132.206 7.047 3 870 30 90 150 222.5 328 487 570 615 Gender Male 213 174.319 133.151 9.123 5 870 30 90 140 220 340 479 568 615 Gender Female 139 178.115 131.191 11.127 3 630 30 95 150 225 300 530 600 605 Age (years) . 4 158.75 98.011 49.006 75 300 75 98 130 220 300 300 300 300 Age (years) 5-11 4 9_8.75 57.5 28.75 45 170 45 53 90 145 170 170 170 170 Age (years) 12-17 8 151.25 77.678 27.463 50 270 50 80 160 205 270 270 270 270 Age (years) 18-64 313 180.192 136.706 7.727 3 870 30 90 150 225 370 498 590 615 Age (years) > 64 23 141.217 85.243 17.774 5 328 30 75 135 180 240 325 328 328 Race White 297 173.623 132.592 7.694 3 870 30 90 140 220 328 487 590 630 Race Black 25 205.44 126.551 25.31 50 540 60 120 180 240 417 498 540 540 Race Asian 8 169.875 153.311 54.204 5 479 5 38 175 225 479 479 479 479 Race Some Others 7. 197.286 187.607 70.909 *70 615 70 110 135 185 615 615 615 615 Race Hispanic 10 121.3 52.326 16.547 5 198 5 105 117.5 160 179 198 198 198 Race Refusetj 5 246.6 127.153 56.864 73 410 73 180 270 300 410 410 410 410 Hispanic No 327 177.131 134.457 7.435 3 870 30 90 150 225 340 489 590 615 Hispanic Yes 20 144.9 85.08 19.024 5 440 38 110 120 160 221.5 342.5 440 440 Hispanic DK 2 142.5 31.82 22.5 120 165 120 120 142.5 165 165 165 165 165 Hispanic Refused 3 261 171.852 99.219 73 410 73 73 300 410 410 410 410 410 Employment . 12 133.75 73.55 21.232 45 270 45 60 135 177.5 225 270 270 270 Employment Full Time 223 182.439 138.308 9.262 5 870 30 90 150 228 340 525 600 630 Employment Part Time 43 201.233 155.454 23.706 5 615 .---, 45 90 150 270 455 520 615 615 Employment Not Employed 70 146.3 97.375 11.639 3 479 . 30 73 122.5 180 255 328 462 479 Employment Refused 4 176.25 115.136 57.568 45 300 45 83 180 270 300 300 300 300 Education . 13 146.538 84.172 23.345 45 300 45 60 .150 185 270 300 300 300 Education < High School 28 218.036 170.225 32.17 60 870 75 120 174.5 235 420 568 870 870 Education High School Graduate 117 177.778 130.078 12.026 3 630 25 90 150 225 360 489 540 570 Education <College 95 205.274 152.829 15.68 5 650 30 105 180 240 462 590 615 650 Education College Graduate 55 141.764 92.766 12.509 10 417 20 75 120 205 265 340 410 417 Education Post Graduate 44 131.364 90.209 13.599 30 400 30 60 110 177.5 265 290 400 400 Census Region Northeast 83 179.337 137.039 15.042 5 650 45 89 140 240 328 489 630 650 Census Region Midwest 88 169.8'18 126.238 13.457 5 615 30 90 147.5 211.5 299 487 568 615 Census Region South 91 175.714 132.028 13.84 3 870 35 90 148 225 270 462 570 870 Census Region West 90 178.544 135.533 14.286 5 605 30 85 152.5 225 407 479 590 605 Day Of Week Weekday 192 167.458 133.473 9.633 5 650 30 80 120 210 340 520 590 605 Day Of Week Weekend 160 185.85 130.378 10.307 3 870 45 108 165 228 321.5 474.5 568 630 Season Winter 93 182.667 131.674 13.654 5 650 40 87 150 240 410 455 . 560 650 Season Spring 83 186.12 . 147.597 16.201 5 870 30 90 140 230 380 498 570 870 Season Summer 99 160.313 130.672 13.133 3 630 30 75 120 189 285 530 605 630 Season Fall 77 176.377 117.154 13.351 15 615 30 100 165 220 299 410 600 615 Asthma No 331 176.308 . 133.715 7.35 3 870 30 90 150 225 340 487 590 615 Asthma Yes 18 169.444 108.978 25.686 60 530 60 105 135 210 270 530 530 530 Asthma DK 3 160 124.9 72.111 60 300 60 60 120 300 300 300. 300 300 . Angina No 345 176.98 132.759 7.148 3 870 30 90 150 225 340 487 590 615 Angina Yes 5 82 47.249 21.131 5 120 5 75 90 120 120 120 120 120 Angina DK 2 210 127.279 90 120 300 120 120 210 300 300 300 300 300 Bronchitis/Emphysema No 333 177.273 133.27 7.303 3 870 30 90 150 225 340 487 590 615 Bronchitis/Emphysema Yes 17 148.588 108.499 26.315 50 530 50 110 120 175 210 530 530 530 Bronchitis/Emphysema DK 2 165 190.919 135 30 300 30 30 :165 300 300 300 300 300 Note: A"*" Signifies missing data. "DK":: The respondent replied "don't know". Refused= Refused data. N;, doer sample size. Mean= Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Stderr = standard error. Min= minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleneis 1996. Table 15-101. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at a Restaurant Percentiles Cateqory Pooulation Grouo N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 2059 94.539 119.93 2.643 1 925 10 30 60 95 185 351 548 660 Gender Male 986 87.498 114.17 3.6358 1 900 10 30 60 90 160 305 550 660 Gender Female 1073 10.1.01 124.69 3.8065 1 925 10 40 60 105 380 540 670 Age (years) . 30 126.13 138.22 25.2349 15 495 30 45 60 150 397.5 490 495 495 Age (years) 1-4 61 62.705 47.701 6.1075 4 330 10 35 55 85 115 120 130 330 Age (years) 5-11 84 56.69 38.144 4.1618 5 180 10 30 45 85 120 120 140 180 Age (years) 12-17 122 69.836 78.361 7.0945 2 455 10 30 45 65 165 250 325 360 Age (years) 18-64 1503 101.21 131.22 3.3846 1 925 10 30 60 105 211 400 570 675 Age (years) > 64 259 83.583 83.517 5.1895 3 750 19 45 60 90 150 215 315 520 Race White 1747 91.658 114.69 2.744 1 925 10 30 60 95 175 320 535 640 Race Black 148 102.82 141.28 11.613 3 805 5 30 60 95 295 430 555 735 Race Asian 37 81.297 78.948 12.979 15 480 18 30 60 90 135 200 480 480 Race Some Others 30 145.17 194.83 35.5705 5 765 10 45 82.5 120 432.5 750 765 765 Race Hispanic* 78 123 156.78 17.7518 10 700 15 40 60 110 375 585 660 700 Race Refused 19 123.84 127.64 29.2833 20 480 20 30 70 210 330 480 480 480 Hispanic No 1911 92.945 117.6 2.6901 1 925 10 30 60 95 180 330 542 645 Hispanic Yes 129 116.7 147.95 13.0261 1 765 15 40 60 115 360 435 660 700 Hispanic DK 5 76 134.32 60.0708 5 315 5 10 1.0 40 315 315 315 315 Hispanic Refused 14 114.5 134.74 36.0117 30 480 30 30 60 90 330 480 480 480 Employment . 263 62.251 57.907 3.5707 2 455 10 30 45 80 120 140 273 330 Employment Full Time 1063 105.48 142.37 4.3668 1 925 10 35 60 105 235 485 630 735 Employment Part Time 208 122.61 144.83 10.0423 1 805 5 32.5 65 122.5 320 441 595 660 Employment Not Employed 515 76.33 61.418 2.7064 3 490 15 40 60 90 145 195 260 315 Employment Refused 10 135 133.52 42.223 30 425 30 60 82.5 135 377.5 425 425 425 Education . 299 72.177 79.595 4.6031 1 548 10 30 50 85 130 250 360 480 Education < High School 132 134.77 171.84 14.9567 5 925 10 30 60 151.5 375 535 700 750 Education High School Graduate 590 99.439 136.32 5.612 3 910 10 35 60 90 202.5 435 645 680 Education <College 431 94.935 114.88 5.5338 1 770 10 35 60 105 180 340 550 640 Education College Graduate 359 89.515 104.13 5.4957 1 765 10 35 60 100 165 295 490 570 Education Post Graduate 248 95.012 109.37 6.9452 3 765 15 40 60 115 180 260 560 675 Census Region Northeast 409 94.379 113.64 5.619 2 765 15 35 60 100 210 330 507 585 Census Region Midwest 504 96.895 120.86 5.3833 1 805 10 30 60 105 190 340 560 675 Census Region South 680 92.666 125.1 4.7972 2 910 10 30 60 90 194.5 365 550 650 Census Region West 466 94.863 116.88 5.4145 1 925 10 30 60 110 175 375 535 640 Day Of Week Weekday 1291 97.338 128.83 3.5855 1 925 10 30 60 93 210 377 555 700 Day Of Week Weekend 768 89.833 103.16 3.7224 1 770 10 36 60 105 155 280 510 620 Season Winter 524 97.735 125.69 5.491 3 875 15 35 60 105 178 351 595 685 Season Spring 559 91.642 109.7 4.6399 2 925 10 35 60 95 180 360 505 555 Season Summer 556 95.121 123.03 5.2177 1 910 10 30 60 94 210 360 555 675 Season Fall 420 93.636 121.74 5.9401 1 900 10 30 60 95 185 325 540 653 Asthma No 1903 94.081 117.41 2.6915 1 910 10 35 60 100 180 330 545 653 Asthma Yes 150 96.267 143.56 11.7219 -4 925 10 30 45.5 90 237.5 485 590 670 Asthma DK 6 196.33 220.89 90.1782 30 480 30 30 79 480 480 480 480 480 Angina No 1998 94.926 120.73 2.701 1 925 10 30 60 100 190 355 550 660 Angina Yes 50 68.98 53.608 7.5813 3 340 15 45 60 90 105 120 286 340 Angina DK 11 140.27 171.27 51.6393 30 480 30 30 70 120 480 480 480 480 Bronchitis/Emphysema No 1945 93.746 117.67 2.668 1 910 10 30 60 97 180 335 548 653 Bronchitis/Emphysema Yes 104 96.077 130.13 12.7602 5 925 15 30 60 90 235 360 500 620 Bronchitis/Emphysema DK 10 232.8 288.24 91.1492 10 875
10 30 79 480 677.5 875 875 875 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Std err= standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996.
Table 15-102. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at School Percentiles Category Population Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 1224 343.35 179.099 5.119 1 995 10 210 395 454 540 585 660 723 Gender Male 581 358.599 167.7 6.957 1 995 30 255 400 450 540 600 690 -778 Gender Female 643 329.572 187.875 7.409 1 855 5 180 390 455 540 582 640 683 Age (years) . 18 314:056 230.927 54.43 5 713 5 165 247.5 520 625 713 713 713 Age (years) 1-4 43 288.465 217.621 33.187 5 665 10 60 269 500 580 595 665 665 Age (years) 5-11 302 396.308 109.216 6.285 5 665 170 365 403 445 535 565 625 640 Age (years) 12-17 287 402.551 125.512 7.409 15 . 855 120 383 420 450 500 565 710 778 Age (years) 18-64 550 295.422 207.294 8.839 1 995 5 104 300 460 552.5 612 683 785 Age (years) > 64 24 187.708 187.012 38.174 2 585 3 45 120 327.5 480 510 585 585 Race White 928 348.525 180.458 5.924 1 995 10 212.5 400 458 545 600 665 723 Race Black 131 339.809 169.282 14.79 2 855 15 230 390 445 510 580 624 645 Race Asian 39 332.385 179.918 28.81 5 840 20 190 365 450 560 580 840 840 Race Some Others 36 363.583 155.557 25.926 10 820 105 272.5 366 457.5 502 598 820 820 Race Hispanic 76 294.039 175.697 20.154 2 565 10 142.5 362.5 432 495 525 540 565 Race Refused 14 279.714 221.268 59.136 5 681 5 60 260 440 625 681 681 681 Hispanic No 1082 344.924 179.58 5.459 1 995 10 210 395 455 540 598 665 730 Hispanic Yes 127 333.016 173.803 15.423 2 820 15 200 390 445 500 565 600 630 Hispanic DK 5 293 244.672 109.42 3 562 3 65 415 420 562 562 562 562 Hispanic Refused 10 329.5 180.053 56.938 5 625 5 200 350 445 537.5 625 625 625 Employment . 616 390.294 130.206 5.246 5 855 115 365 410 450 525 570 640 665 Employment Full Time 275 331.269 222.021 13.388 1 995 5 115 405 510 575 625 690 755 Employment Part Time 138 280.891 174.844 14.884 1 800 10 160 285 412 480 537 660 683 Employment Not Employed 190 258.674 199.529 14.475 1 855 5 60 262.5 410 527.5 572 778 840 Employment Refused 5 166 179.074 80.084 5 440 5 5 180 200 440 440 440 440 Education . 679 388.943 132.842 5.098 5 855 100 360 410 450 525 580 640 710 Education < High School 24 233.333 179.648 36.67 1 540 2 30 297.5 373.5 460 465 540 540 Education High School Graduate 114 186.649 193.608 18.133 1 785 4 20 107.5 295 480 580 645 690 Education <College 173 281.41 209.872 15.956 1 995 5 120 255 425 550 640 820 855 Education College Graduate 93 300.43 208.704 21.642 1 755 5 115 320 470 540 580 730 755 Education Post Graduate 141 373.525 193.443 16.291 1 683 15 250. 442 510 575 615 655 680 Census Region Northeast 261 345.724 181:522 11.236 1 995 11 210 385 455 535 620 710 855 Census Region Midwest" 290 334.445 176.652 10.373 1 730 10 180 390 440 530 585 645 683 Census Region South 427 354.037 178.547 8.641 1 855 10 235 415 462 540 575 640 755 Census Region West 246 332.78 180.27.7 11.494 1 820 15 195 377.5 440 555 595 681 713 Day Of Week Weekday 1179 346.838 177.477 5.169 1 995 10 222 395 455 540 585 655 723 Day Of Week Weekend 45 251.978 198.543 29.597 20 820 40 105 180 360 555 632 820 820 Season Winter 392 369.298 164.363 8.302 1 855 20 285 405 457 545 600 680 710 Season Spring 353 355.057 165.488 8.808 1 855 12 250 400 455 535 575 636 713 Season Summer 207 316.763 196.364 13.648 2 995 10 125 365 445 557 585 640 723 Season Fall 272 310.996 195.332 11.844 1 855 5 120 365 445 540 595 660 778 Asthma No 1095 342. 779 179.195 5.415 1 995 10 200 390 455 540 585 660 723 Asthma Yes 124 350.669 178.785 16.055 1 855 10 250 401.5 445 535 605 645 800 Asthma DK 5 287 190.676 85.273 5 445 5 180 365 440 445 445 445 445 Angina No 1209 344.629 178.874 5.144 1 995 10 210 395 455 540 595 660 723 Angina Yes 9 205.778 169.545 56.515 15 510 15 90 180 275 510 510 510 510 Angina DK 6 292.167 178.908 73.039 5 480 5 180 324 440 480 480 480 480 Bronchitis/Emphysema No 1175 344.826 178.845 5.217 1 995 10 212 395 455 540 595 660 730 Bronchitis/Emphysema Yes 42 306.714 188.249 29.047 3 632 10 120 377.5 444 465 580 632 632 Bronchitis/Emphysema DK 7 315.429" 163.691 61.869 5 440 5 180 378 440 440 440 440 440 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Stderr =standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsano and Kleoeis, 1996.
Table 15-103. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at a Plant/Factorv/Warehouse Percentiles Cateaorv Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 All 383 450.896 204.367 10.443 2 997 30 350 510 568 670 705 770 855 Gender Male 271 460.458 205.102 12.459 2 997 30 365 515 575 675 720 780 870 Gender Female 112 427.759 201.609 19.05 5 820 15 314.5 510 555 600 675 705 720 Age (years) . 6 405.667 304.05 124.13 30 780 30 120 414.5 675 780 780 780 780 Age (years) 1-4 1 20 . . 20 20 20 20 20 20 20 20 20 20 Age (years) 5-11 2 107.5 123.744 87.5 20 195 20 20 107.5 195 195 195 195 195 Age (years) 12-17 4 108 136.404 68.202 10 307 10 20 57.5 196 307 307 307 307 Age (years) 18-64 353 463.683 196.321 10.449 5 997 30 385 520 570 670 705 770 855 Age (years) > 64 17 347.765 210.909 51.153 2 705 2 180 450 495 550 705 705 705 Race White 322 451.789 201.135 11.209 5 890 30 355 517.5 568 650 690 770 840 Race Black 32 466.438 172.559 30.504 2 750 30 382.5 497.5 550 675 720 750 750 Race Asian 3 263.333 378.462 218.51 30 700 30 30 60 700 700 700 700 700 Race Some Others 6 585.333 156.91 64.058 310 780 310 565 591 675 780 780 780 780 Race Hispanic 15 385.8 231.348 59.734 5 765 5 230 435 515 760 765 765 765 Race Refused 5 440.4 387.419 173.26 30 997 30 115 520 540 997 997 997 997 Hispanic No 350 454.137 202.78 10.839 2 997 30 365 512.5 570 666.5 700 770 855 Hispanic Yes 26 419.615 213.155 41.803 (i 765 15 240 482.5 550 675 760 765 765 Hispanic DK 2 425 162.635 115 310 540 310 310 425 540 540 540 540 540 Refused 5 397 3'14.833 140.8 30 780 30 115 520 540 780 780 780 780 Employment . 7 95.286 113.83 43.024 10 307 10 20 30 195 307 307 307 307 Employment Full Time 333 481.417 185.222 10.15 5 997 50 440 525 580 675 720 780 855 Employment Part Time 23 359.87 170.619 35.577 40 585 45 240 390 505 527 535 585 585

Employment Not Employed 19 179.316 221.341 50.779 2 705 2 25 60 295 640 705 705 705 Employment Refused 1 30 . . 30 30 30 30 30 30 30 30 30 30 Education . 13 184 234.182 . 64.95 10 780 10 20 85 270 510 780 780 780 Education < High School 38 491.237 195.919 31.782 2 855 5 435 525 600 (05 765 855 855 Education High School Graduate 190 465.374 188.699 13.69 5 997 30 380 520 565 667.5 705 760 890 Education <College 85 450.494 199.674 21.658 15 870 40 375 510 565 635 680 820 870 Education College Graduate 43 463.163 206.51 31.492 5 840 60 405 520 600 670 690 840 840 Education Post Graduate 14 357 .5 255. 702 68.339 10 700 10 90 355 550 675 700 700 700 Census Region Northeast 71 449.423 207.98 24.683 5 890 15 300 510 565 675 725 780 890 Census Region Midwest 113 462.035 196.506 18.486 2 997 30 405 520 570 640 700 770 820 Census Region South 136 465.912 199.315 17.091 .5 870 20 382 522.5 570 670 720 840 855 Census Region West 63 400.159 221.13 27.86 10 760 30 185 490 550 675 690 710 760 Day* Of Week Weekday 319 476.445 190.875 10.687 5 997 30 435 525 580 675 710 770 855 Day Of Week Weekend 64 323.547 222.63 27.829 2 820 10 107.5 357.5 507.5 560 620 780 820 Season Winter 89 468.157 188.472 19.978 10 997 30 360 520 565 660 690 780 997 se*ason Spring 91 445.198 212.648 22.292 10 870 30 270 505 570 675 760 840 870 Season Summer 127 440.646 210.285 18.66 2 890 15 . 370 510 560 645 700 765 855 Season Fall 76 454.632 204.721 23.483 5 760 30 352.5 520 591 675 690 720 760 Asthma No 364 452.948 203.838 10.684 2 997 30 355 512.5 570 675 705 770 855 Asthma Yes 17 412.353 187.025 45.36 20 580 20 340 495 540 550 580 580 580 Asthma DK 2 405 530.33 375 30 780 30 30 405 780 780 780 780 780 Angina No 375 453.928 202.31 10.447 2 997 30 360 515 570 670 705 770 855 Angina Yes 5 231 168.389 75.306 60 475 60 90 230 300 475 475 475 475 Angina DK 3 438.333 379.418 219.06 30 780 30 30 505 780 780 780 780 780 Bronchitis/Emphysema No 362 450.235 204.588 10.753 2 997 30 350 510 565 663 700 770 855 Bronchitis/Emphysema Yes 19 468.316 175.293 40.215 50 720 50 375 510 568 690 720 720 720 Bronchitis/Emphysema DK 2 405 530.33 375 30 780 30 30 405 780 780 780 780 780 Note: A "*"Signifies missing data. "DK" =The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Stderr =standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers *below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996.
Table 15-104. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors on a Sidewalk, Street, or in the Neiqhborhood Percentiles Cateoorv Population Graue N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 All 896 85.785 133.828 4.4709 1 1440 2 15 40 90 223 405 565 615 Gender Male 409 108.775 168.11 8.3125 1 1440 3 20. 45 120 330 525 615 710 Gender Female 487 66.476 91.863 4.1627 1 580 1 15 35 75 152 255 435 465 Age (years) . 15 72.533 69.418 17.9236 1 290 1 40 55 90 120 290 290 290 Age (years) 1-4 30 54.8 52.731 9.6274 1 235 2 10 42.5 78 125 158 235 235 Age (years) 5-11 75 110.813 116.76 13.4823 1 540 5 20 65 178 240 410 465 540 Age (years) 12-17 74 52.554 74.776 8.6925 1 435 2 15 30 60 125 200 338 435 Age (years) 18-64 580 94.279 153.933 6.3917 1 1440 2 15 40 82.5 277.5 480 600 690 Age (years) > 64 122 59.418 61.519 5.5696 1 380 2 20 40 75 120 190 235 270 Race White 727 85.735 136.504 5.0627 1 1440 2 15 41 90 215 405 570 675 Race Black 87 89.184 132.669 14.2236 1 565 2 10 35 120 324 426 540 565 Race Asian 11 88.727 114.01 34.3752 2 405 2 30 45 120 149 405 405 405 Race Some Others 18 80.556 105.981 24.98 10 420 10 20 40 75 240 420 420 420 Race Hispanic 42 71.357 110.769 17.092 1 525 1 20 40 75 135 290 525 525 Race Refused 11 122.909 117.699 35.4876 2 310 2 40 60 290 300 310 310 310 Hispanic No 807 87.482 136.129 4.792 1 1440 2 15 45 90 225 410 565 600 Hispanic Yes 79 67.797 110.301 12.4098 1 615 1 15 30 62 140 300 525 615 Hispanic DK 1 2 . . 2 2 2 2 2 2 2 2 2 2 Hispanic Refused 9 100.778 115.933 38.6443 2 310 2 40 60 90 310 310 310 310 Employment . 176 79.182 96.345 7.2622 1 540 2 15 45 110 200 260 435 465 Employment Full Time 384 102.221 169.534 8.6515 1 1440 3 15 40.5 75 330 525 600 710 Employment Part Time 74 74.446 113.86 13.2359 1 795 1 15 42.5 86 180 255 390 795 Employment Not Employed 255 69.996 94.045 5.8893 1 615 1 15 40 85 152 270 380 485 Employment Refused 7 45.143 36.64 13.8485 2 90 2 4 40 90 90 90 90 90 Education . 198 74.914 92.253 6.5561 1 540 2 15 40.5 90 185 240 435 465 Education < High School 56 131.232 247.289 33.0454 1 1440 1 15 40 118 465 710 735 1440 Education High School Graduate 223 100.233 146.92 9.8385 1 795 5 20 45 95 275 480 600 680 Education <College 172 77.186 128.752 9.8173 1 675 1 10 30 75 180 435 570 600 Education College Graduate 138 76.275. 106.589 9.0734 1 600 3 20 45 70 205 310 485 565 Education Post Graduate 109 78.229 121.311 11.6195 1 710 5 20 45 60 200 330 560 570 Census Region Northeast 202 89.134 132.343 9.3116 1 735 3 15 45 90 235 410 530 570 Census Region Midwest 193 87.855 153.329 11.0369 1 1440 2 15 30 85 240 355 565 600 Census Region South 298 79.943 125.46 7.2677 1 710 2 15 35 75 185 420 532 680 Census Region West 203 89.059 127.909 8.9775 1 795 1 20 45 105 210 300 570 615 Day Of Week Weekday 642 86.684 143.938 5.6808 1 1440 2 15 40 80 223 426 585 680 Day Of Week Weekend 254 83.512 104.207 6.5385 1 565 2 25 45 90 220 310 440 480 Season Winter 210 73.548 144.308 9.9582 1 1440 1 15 33 60 160 270 560 710 Season Spring 242 97.913 137.243 8.8223 1 795 4 25 45 120 240 435 570 675 Season Summer 276 83.989 123.086 7.4089 1 690 4 15 45 90 200 420 525 580 Season Fall 168 86.56 131.855 10.1729 1 710 2 15 40 90 240 405 600 615 Asthma No 832 86.108 129.455 4.488 1 795 2 15 40 90 225 418 565 600 Asthma Yes 57 85.596 193.133 25.5811 1 1440 1 15 35 90 180 235 260 1440 Asthma DK 7 48.857 27.973 10.5727 2 90 2 30 60 60 90 90 90 90 Angina No 857 86.177 134.897 4.608 1 1440 2 15 40 90 223 410 565 615 Angina Yes 33 81.727 117.393 20.4356 1 465 1 17 45 60 250 380 465 465 Angina DK 6 52 29.257 11.9443 2 90 2 40 60 60 90 90 90 90 Bronchitis/Emphysema No 855 84.837 132.316 4.5251 1 1440 2 15 40 85 225 405 560 600 Bronchitis/Emphysema Yes 34 117.735 176.429 30.2574 3 735 8 30 45 120 215 690 735 735 Bronchitis/Emphysema DK 7 46.286 27.482 10.3871 2 90 2 32 40 60 90 90 90 90 Note: A"'" Signifies missing data. "DK"= The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996. Table 15-105. Statistics for 24-Hour Cumulative Number of Minutes Soent Outdoors in a Parkinn Lot Percentiles Cateaorv Pooulation Grouo N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 All 226 70.721 126.651 8.425 1 910 2 10 20 60 190 309 510 580 Gender Male 106 100.34 167.159 16.236 1 910 5 15 30 110 315 495 580 720 Gender Female 120 44.558 64.826 5.918 1 295 1 5 20 46.5 167.5 187.5 248 285 Age (years)
3 135 195 112.58 15 360 15 15 30 360 360 360 360 360 Age (years) 1-4 11 39.818 38.449 11.593 5 110 5 10 20 90 90 110 110 110 Age (years) 5-11 5 62 63.699 28.487 5 170 5 30 45 60 170 170 170 170 Age (years) 12-17 12 93.75 90.81 26.214 5 248 5 17.5 52 163 238 248 248 248 Age (years) 18-64 182 69.984 132.655 9.833 1 910 2 10 20 60 190 309 550 720 Age (years) > 64 13 74.462 127.9 35.473 1 465 1 10 25 60 180 465 465 465 Race White 180 72.122 128.299 9.563 1 910 2 10 20.5 64 205 302 510 720 Race Black 18 102.444 167.776 39.545 2 580 2 6 27.5 130 495 580 580 580 Race Asian 3 21.667 7.638 4.41 15 30 15 15 20 30 30 30 30 30 Race Some Others 5 50 46.098 20.616 5 115 5 10 45 75 115 115 115 115 Race Hispanic 17 25.706 39.365 9.547 1 165 1 10 10 20 60 165 165 165 Race Refused 3 135 195 112.58 15 360 15 15 30 360 360 360 360 360 Hispanic No 196 69.26 114.078 8.148 1 720 . 2 10 24 67.5 190 295 495 580 Hispanic Yes 25 42.92 103.34 20.668 1 510 1 5 10 20 75 165 510 510 Hispanic DK 2 465 629.325 445 20 910 20 20 465 910 910 910 910 910 Hispanic Refused 3 135 195 112.58 15 360 15 15 30 360 360 360 360 360 Employment

26 55.577 59.88 11.743 5 238 5 15 30 90 145 170 238 238 Employment Full Time 117 83.325 155.119 14.341 1 910 2 10 20 60 240 495 580 720 Employment Part Time 37 75.378 114.734 18.862 1 465 1 5 21 90 180 450 465 465 Employment Not Employed 43 037.093 46.8 7.137 1 210 1 10 20 60 90 134 210 210 Employment Refused 3 135 195 112.58 15 360 15 15 30 360 360 360 360 360 Education

33 69.697 85.644 14.909 1 360 5 15 30 90 180 248 360 360 Education < High School 16 73.25 176.778 44.194 2 720 2 7.5 22.5 32.5 165 720 720 720 Education High School Graduate 83 83 124.358 13.65 1 580 5 10 25 90 215 315 495 580 Education <College 49 75.898 .162.674 23.239 1 910 2 10 20 60 210 450 910 910 Education College Graduate 23 48.783 107.169 22.346 1 510 2 5 *10 30 130 135 510 510 Education Post Graduate 22 35.5 54.472 11.613 1 185 1 5 15 30 115 180 185 185 Census Region Northeast 56 57.357 82.622 11.041 1 495 1 12.5 27.5 75 135 180 295 495 Census Region Midwest 48 73.438 118.574 17.115 1 550 5 10 25 62.5 248 315 550 550 Census Region South 75 57.92 106.421 12.288 1 720 2 7 20 50 185 238 360 720 Census Region West 47 104.298 189.916 27.702 3 910 5 10 20* 90 450 510 910 910 Day Of Week Weekday 154 64.851 136.686 11.014 1 910 2 7 20 43 180 450 550 720 Day Of Week Weekend 72 83.278 101.675 11.982 1 465 5 15 35 113 240 309 360 465 Season Winter 45 50.533 64.702 9.645 2 309 5 15 30 63 130 180 .309 309 Season Spring 57 82.912 131.245 17.384 1 495 1 10 20 90 240 465 495 495 Season Summer 75 72.027 146.21 16.883 1 910 2 10 20 60 205 315 580 910 Season Fall 49 73.082 133.165 19.024 1 720 1 10 20 75 205 295 720 720 Asthma No 204 62.98 109.369 7.657 1 720 2 10 20 60 180 248 495 510 Asthma Yes 18 149.722 238.456 56.205 1 910 1 15 45 145 580 910 910 910 Asthma DK 4 110 166.883 83.442 15 360 15 22.5 32.5 198 360 360 360 360 Angina No 217 69.263 127.076 8.626 1 910 2 10 20 60 185 309 510 580 Angina Yes 5 99.6 83.056 37.144 35 238 35 40 75 110 238 238 238 238 Angina DK 4 113.75 164.792 82.396 15 360 15 22.5 40 205 360 360 360 360 Bronchitis/Emphysema No 211 65.555 114.21 7.863 1 720 2 10 20 60 180 295 495 550 Bronchitis/Emphysema Yes 11 142.364 265.976 80.195 1 910 1 10 40 180 240 910 910 910 Bronchitis/Emphysema DK 4 146.25 160.799 80.399 15 360 15 22.5 105 270 360 360 360 360 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused= Refused data. N =doer sample size. Mean= Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Std err= standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996.
Table 15-106. Statistics for 24-Hour Cumulative Number of Minutes Soent Outdoors at a Service Station or Gas Station Percentiles Cateaorv Pooulation Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 191 50.597 125.489 9.0801 1 790 5 5 10 20 105 365 570 645 Gender Male 90 73.522 149.969 15.8082 1 645 5 5 10 30 325 495 600 645 Gender Female 101 30.168 94.915 9.4444 2 790 5 5 10 15 44 105 180 510 Age (years} . 1 86 . . 86 86 86 86 86 86 86 86 86 86 Age (years} 1-4 3 6.667 2.887 1.6667 5 10 5 5 5 10 10 10 10 10 Age (years} 5-11 3 66.667 98.277 56.7401 5 180 5 5 15 180 180 180 180 180 Age (years} 12-17 11 7.818 4.513 1.3606 1
15 1 5 5 10 15 15 15 15 Age (years} 18-64 157 54.185 135.636 10.8249 2 790 5 5 10 15 1_10 390 570 645 Age (years} > 64 16 47.813 69.497 17.3744 5 240 5 10 18 55 180 240 240 240 Race White 170 50.941 124.015 9.5115 2 790 5 5 10 20 107.5 365 520 600 Race Black 11 80.727 191.433 57.7192 4 645 4 5 5 44 140 645 645 645 Race Asian 1 5 . . 5 5 5 5 5 5 5 5 5 5 Race Some Others 3 16.667 20.207 11.6667 5 40 5 5 5 40 40 40 40 40 Race Hispanic 5 10.2 7.596 3.3971 1 20 1 5 10 15 20 20 20 20 Race Refused 1 10 . . 10 10 10 10 10 10 10 10 10 10 Hispanic No 179 . 53.056 129.15 9.6531 2 790 5 5 10 20 130 380 570 645 Hispanic Yes 12 13.917 23.008 6.6418 1 86 1 5 7.5 10 15 86 86 86 Employment . 16 18.813 43.196 10.799 1 180 1 5 7.5 12.5 15 180 180 180 Employment Full Time 110 55.827 136.782 13.0417 2 645 5 5 10 15 99 495 570 600 Employment Part Time 26° 34.731 71.829 14.0868 3 355 5 5 10 25 100 130 355 355 Employment Not Employed 38 40.237 76.973 12.4867 4 380 5 5 10 20 140 240 380 380 Employment Refused 1 790 . . 790 790 790 790 790 790 790 790 790 790 Education . 18 17.833 40.712 9.5958 1 180 1 5 7.5 15 15 180 180 180 Education < High School 16 103 164.12 41.03 5 520 5 10 15 140 365 520 520 520 Education High School Graduate 46

85.739 162.855 24.0116 3 645 5 5 10 85 380 495 645 645 Education <College 58 41.759 121.08 15.8986 2 790 4 5 13 20 .60 110 510 790 Education College Graduate 30 36.633 111.641 20.3828 2 570 4 5 6.5 15 30 270 570 570 Education Post Graduate 23 10 6.396 1.3337 5 30 5 5 10 10 20 20 30 30 Census Region Northeast 33 59.697 149.173 25.9677 2 600 3 5 10 20 105 570 600 600 Census Region Midwest 48 28.563 77.552 11.1936 2 510 5 5 10 15 60 110 510 510 Census Region South 68 49.882 133.967 16.2459 1 790 5 5 10 15 130 295 645 790 Census Region West 42 69.786 135.545 20.9151 4 520 5 5 13 40 270 390 520 520 Day Of Week Weekday 122 58.402 145.085 13.1354 2 790 5 5 10 20 130 495 600 645 Day Of Week Weekend 69 36.797 79.004 9.5109 1 390 4 5 10 . 15 88 240 380 390 Season Winter 56 37.536 100.602 13.4435 2 600 4 5 10 15 60 270 355 600 Season Spring 54 80.13 157.514 21.4349 1 645 5 5 10 60 380 510 570 645 Season S_ummer 51 46.51 137.689 19.2804 2 790 5 5 10 15 35 365 520 790 Season Fall 30 28.767 58.93 10.7591 3 295 5 5 8.5 15 93 130 295 295 Asthma No 174 53.517 130.777 9.9141 1 790 5 5 10 20 130 380 570 645 Asthma Yes 16 15.75 25.736 6.434 2 110 2 5 7.5 15 20 110 110 110 Asthma DK 1 100 . . 100 100 100 100 100 100 100 100 100 100 Angina No 184. 46.788 120.622 8.8923 1 790 5 5 10 15 88 295 570 645 Angina Yes 7 150.714 206.81 78.1667 10 510 10 15 20 380 510 510 510 510 Bronchitis/Emphysema No 181 47.122 123.971 9.2147 1 790 5 5 10 15 85 295 570 645 Bronchitis/Emphysema Yes 10 113.5 142.946 45.2036 5 380 5 10 58 140 367.5 380 380 380 Note: A"*" Sip,nifies missing data. "DK"= The replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cymu alive number of minutes for doers. tdev =standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsann and Kleneis 1996.
Table 15-107. Statistics for 24-Hour Cumulative Number of Minutes Soent Outdoors at a Construction Site Percentiles Grouo Name Grouo Code N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 143 437.098 242.073 20.243 1 1190 10 240 510 600 675 740 930 985 Gender Male 130 461.531 232.511 20.393 1 1190 10 300 522.5 600 688.5 745 930 985 Gender Female 13 192.769 202.794 56.245 5 630 5 60 135 165 535 630 630 630 Age (years) . 1 510 .
510 510 510 510 510 510 510 510 510 510 Age (years) 1-4 2 240 254.558 180 60 420 60 60 240 420 420 420 420 420 Age (years) 12-17 1 10 . . 10 10 10 10 10 10 10 10 10 10 Age (years) 18-64 133 444.549 243.017 21.072 1 1190 10 240 520 600 687 745 930 985 Age (years) > 64 6 396.667 188.75 77.057 60 560 60 300 460 540 560 560 560 560 Race White 125 430.872 247.432 22.131 5 1190 10 240 510' 600 687 740 930 985 Race Black 10 430.1 233.307 73.778 1 630 1 170 550 585 615 630 630 630 Race Some Others 2 492.5 60.104 42.5 450 535 450 450 492.5 535 535 535 535 535 Race Hispanic 3 501.667 170.318 98.333 305 600 305 305 600 60'0 600 600 600 600 Race Refused 3 618.333 166.458 96.105 510 810 510 510 535 810 810 810 810 810 Hispanic No 129 426.202 247.087 21.755 1 1190 10 180 510 600 665 735 930 985 Hispanic Yes 9 496.111 166.429 55.476 240 765 240 410 505 600 765 765 765 765 Hispanic DK 2 577*.5 180.312 127.5 450 705 450 450 577.5 705 705 705 705 705 Hispanic Refused 3 635 156.125 90.139 510 810 510 510 585 810 810 810 810 810 Employment . 3 163.333 223.681 129.142 10 420 10 10 60 420 420 420 420 420 Employment Full Time 127 456.803 236.198 20.959 1 1190 15 285 520 605 690 745 930 985 Employment Part Time 6 495.833 171.389 69.969 155 600 155 510 555 600 600 600 600 600 Employment Not Employed 7 146.571 162.79 61.529 5 430 5 6 60 300 430 430 430 430 Education . 4 250 251.794 125.897 10 510 10 35 240 465 510 510 510 510 Education < High School 12 500.833 227.035 65.539 60 930 60 375 525 592.5 735 930 930 930 Education High School Graduate 68 482.162 228.976 27.767 5 1190 20 395 522.5 592.5 720 780 985 1190 Education <College 41 417.683 241.023 37.641 1 745 10 170 520 615 645 687 745 745 Education College Graduate 14 372.357 247.278 66.088 15 660 15 120 440 585 643 660 660 660 Education Post Graduate 4 92.5 137.265 68.632 5 295 5 7.5 35 177.5 295 295 295 295 Census-Region Northeast 28 481.714 238.306 45.036 5 985 6 357.5 532.5 650 695 740 985 985 Census Region Midwest 30 343.967 231.025 42.179 5 810 10 120 342 525 637.5 660 810 810 Census Region South 57 474.018 248.301 32.888 1 1190 10 410 535 615 720 765 780 1190 Census Region West 28 417.107 226.287 42.764 15 930 60 235 500 570 630 656 930 930 Day Of Week Weekday 121 455.116 238.494 21.681 5 1190 15 285 525 600 687 745 930 985 Day Of Week Weekend 22 338 243.022 51.813 1 705 5 60 407.5 525 600 645 705 705 Season Winter 34 418.5 268.44 46.037 1 1190 5 155 505 570 645 695 1190 1190 Season Spring 33 412.242 223.533 38.912 10 810 60 230 490 570 635 740 810 810 Season Summer 46 477.739 221.422 32.647 10 985 60 325 515 630 705 745 985 985 Season Fall 30 423.2 264.183 48.233 5 930 6 135 532.5 585 700 780 930 930 Asthma No 137 437.161 243.531 20.806 1 1190 10 240 510 600 675 745 930 985 Asthma Yes 6 435.667 225.957 92.247 60 690 60 354 440 630 690 690 690 690 Angina No 139 439.108 242.331 20.554 1 1190 10 240 510 600 687 745 930 985 Angina Yes 4 367.25 256.288 128.144 10 570 10 182 444.5 552.5 570 570 570 570 Bronchitis/Emphysema No 140 433.257 240.003 20.284 1 1190 10 240 510 600 670 737.5 810 930 Bronchitis/Emphysema Yes 3 616.333 328.664 189.755 354 985 354 354 510 985 985 985 985 985 Note: A"*" Signifies missing data. "DK" =The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Std err= standard error. Min= minimum number of minutes. Max= maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996.

Table 15-108. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors on School Grounds/PlayQround Percentiles Cateaorv Population Grouo N Mean Stdev Stderr Min Max 5 25. 50 75 90 95 98 99 All 259 98.386 110.056 6.839 1 690 5 30 70 120 208 300 540 570 Gender Male 0.136 118.007 126.395 10.84 1 690 10 35 85 148.5 255 370 555 625 Gender Female 123 76.691 83.861 7.562 1 570 5 20 51 120 180 225 270 440 Age (years) . 2 275 374.767 265 10 540 10 10 275 540 540 540 540 540 Age (years) 1-4 9 85 61.084 20.36 10 175 10 30 65 140 175 175 175 175 Age (years) 5-11 64 88.016 95.638 11.96 5 625 10 30 60 120 170 220 315 625 Age (years) 12-17 76 78.658 88.179 10.12 3 570 5 25 55 105 165 225 370 570 Age (years) 18-64 101 119.812 127.563 12.69 1 690 5 30 85 165 240 360 540 555 Age (years) > 64 7 65 47.258 17.86 5 150 5 30 60 95 150 150 150 150 Race *White 208 98.212 106.512 7.385 1 690 9 30 70 125 190 281 510 555 Race Black 23 128.435 157.54 32.85 5 570 5 25 67 170 300 540 570 570 Race Asian 6 59 66.076 26.98 10 179 10 10 35 85 179 179 179 179 Race Some Others 7 70 59.652 22.55 10 180 10 10 60 105 180 180 180 180 Race Hispanic 15 83.733 102.972 26.59 1 370 1 10 30 120 228 370 370 370 Hispanic No 225 102.613 113.686 7.579 3 690 9 30 70 125 210 300 540 570 Hispanic Yes 32 71.219 79.899 14.12 1 370 1 12.5 32.5 110 . 150 228 370 370 Hispanic DK 2 57.5 31.82 22.5 35 80 35 35 57.5 80 80 80 80 80 Employment . 143 80.161 88.031 7.362 3 625 9 25 55 115 160 215 315 570 Employment Full Time 48 130.271 127.162 18.35 1 555 10 40 85 180 300 360 555 555 Employment Part Time 24 129.708 158.934 32.44 3 690 10 35 85 143.5 228 510 690 690 Employment Not Employed 42 95.429 94.776 14.62 1 440 5 30 80 120 180 235 440 440 Employment Refused .2 322.5 307.591 217.5 105 540 105 105 323 540 540 540 540" 540 Education . 162 86.593 94.!J53 7.429 3 625 10 27 60 120 170 220 370 570 Education < High School 11 124.818 171.918 51.84 1 540 1 5 45 180 345 540 540 540 Education High School Graduate 33 113.636 110.669 19.27 3 555 5 30 90 160 240 290 555 555 Education <College 19 129.842 147.389 33.81 5 510 5 33 70 210 440 510 510 510 Education College Graduate 19 122.105 149.938 34.4 5 690 5 50 85 125 235 690 690 690 Education Post Graduate 15 102.933 98.093 25.33 1 360 1 30 75 125 235 360 360 360 Census Region Northeast 66 105.955 115.248 14.19 5 690 10 30 85 150 190 281 540 690 Census Region Midwest 53 86.057 109.203 15 3 540 5 20 50 115 190 290 510 540 Census Region South 82 85.463 92.353 10.2 1 570 5 30 60 115 180 255 360 570 Census Region West 58 119.31 125.638 16.5 1 625 10 30 85 160 235 440 555 625 Day Of Week Weekday 205 87.02 105.524 7.37 1 625 5 25 55 115 180 240 540 555 Day Of Week Weekend 54 141.537 117.065 15.93 10 690 25 67 113 180 290 345 440 690 Season Winter 53 72.189 101.951 14 1 555 3 20 35 85 130 315 440 /555 Season Spring 88 108.614 96.502 10.29 5 540 10 45 85 147.5 215 255 510 540 Season Summer 65 116.446 137.897 17.1 5 690 10 30 75 135 270 360 625 690 Season Fall 53 85.453 96.241 13.22 5 540 5 20 55 120 180 235 345 540 Asthma No 237 100.941 113.236 7.355 1 690 5 30 70 120 215 315 540 570 Asthma Yes 22 70.864 61.977 13.21 5 179 10 15 45 145 160 165 179 179 Angina No 254 99.118 110.809 6.953 1 690 5 30 68.5 120 208 300 540 570 Angina Yes 5 61.2 53.383 23.87 1 130 1 15 70 90 130 130 130 130 Bronchitis/Emphysema No 248 100.565 111.621 7.088 1 690 5 30 71 125 210 300 540 570 Bronchitis/Emphysema Yes 10 52.7 45.363 14.35 9 160 9 22 44 60 125 160 160 160 Bronchitis/Emphysema DK 1 15 0 0 15 15 15 15 15 15 15 15 15 15 Note: A"*" missing data. "DK"= The replied "don't know". Refused= Refused data. N =doer sample size. Mean= Mean 24-hour cumu alive number of minutes for doers. tdev =standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996. *

Table 15-109. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a Park/Golf Course Percentiles Category Population Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 506 198.603 190.248 8.4575 1 1065 20 60 135 270 465 590 748 870 Gender Male 291 205.825 183.101 10.7336 1 1015 25 60 150 285 510 590 730 755 Gender Female 214 187.748 199.367 13.6284 5 1065 15 55 120 250 435 590 870 930 Gender Refused 1 420 . . 420 420 420 420 420 420 420 420 420 420 Age (years) . 10 122.4 60.183 19.0317 30 225 30 60 120 160 202 225 225 225 Age (years) 1-4 21 149.857 176.25 38.4609 21 755 25 50 85 150 360 425 755 755 Age (years) 5-11 54 207.556 184.496 25.1068 25 665 35 70 125 275 555 635 660 665 Age (years) 12-17 52 238.462 242.198 33.5869 15 1065 15 60 147.5 337.5 590 840 915 1065 Age (years) 18-64 314 197.838 185.939 10.4931 1 1015 20 60 150 270 440 580 748 870 Age (years) > 64 55 188.964 182.919 24.6648 10 735 20 30 120 300 510 570 590 735 Race White 441 205.338 195.266 9.2984 1 1065 20 60 150 275 480 605 795 915 Race Black 19 114.474 103.667 23.7829 15 425 15 30 90 155 240 425 425 425 Race Asian 8 185.625 233.398 82.5186 30 665 30 32.5 47.5 315 665 665 665 665 Race Some Others 16 171.25 154.229 38.5572 30 560 30 58 119.5 235 405 560 560 560 Race Hispanic 20 169.45 135.803 30.3664 30 555 32.5 77 145 205 372.5 495 555 555 Race Refused 2 75 63.64 45 30 120 30 30 75 120 120 120 120 120 Hispanic No 469 202.706 193.555 8.9376 1 1065 20 60 135 270 480 605 755 915 Hispanic Yes 34 154.824 135.043 23.1596 15 555 30 60 137.5 175 310 555 555 *555 Hispanic DK 1 10 . . 10 10 10 10 . 10 10 10 10 10 10 Hispanic Refused 2 75 63.64 45 '30 120 30 30 75 120 120 120 120 120 Employment . 128 208.242 209.644 18.5301 15 1065 25 60 120 275 555 645 840 915 Employment Full Time 201 195.831 188.984 13.3299 8 1015 25 60 135 270 450 570 748 930 Employment Part Time 41 213.488 215.602 33.6714 20 870 20 60 132 260 540 660 870 870 Employment Not Employed 132 190.932 166.019 14.4501 1 810 15 60 160 270 420 525 730 735 Employment Refused 4 130 106.771 53.3854 30 280 30 60 105 200 280 280 280 280 Education . 140 202.743 204.676 17.2983 15 1065 20.5 60 120 270 498.5 640 840 915 Education < High School 32 180.844 207.784 36.7315 30 995 30 30 110 245 385 570 995 995 Education High School Graduate 108 219.676 197.223 18.9778 10 1015 20 77.5 162.5 281 545 625 730 810 Education <College 93 191.57 171.177 17.7502 1 870 15 60 150 275 440 510 748 870 Education College Graduate 83 203.53 183.095 20.0973 5 930 23 60 145 270 450 590 795 930 Education Post Graduate 50 157.76 166.568 23.5562 10 735 20 45 75 255 337.5 555 703 735 Censµs Region Northeast 106 184.858 177.429 17.2334 1 1065 20 60 124 240 450 574 635 660 Census Region Midwest 124 194.629 188.667 16.9428 10 1015 30 60 135 255 420 590 735 995 Census Region South 136 218.846 211.474 18.1337 10 930 20 60 150 325 525 720 840 915 Census Region West 140 192.864* 179.421 15.1639 5 870 17.5 58 131 272.5 430 575 755 810 Day Of Week Weekday 276 195.996 189.287 11.3938 5 1015 20 60 145 252.5 510 625 748 840 Day Of Week Weekend 230 201.73 191.76 12.6443 1 1065 20 60 . 130 280 454.5 580 810 915 Season Winter 83 209.072 195.228 . 21.429 15 1065 30 60 165 275 440 660 795 1065 Season Spring 163 168.479 159.071 12.4594 8 930 20 50 120 235 360 510 570 755 Season Summer 192 219.615 199.872 14.4245 5 1015 20 65 155 290 535 630 840 915 Season Fall 68 198.706 217.911 26.4256 1 995 20 60 117.5 280 555 735 810 995 Asthma No 466 192.127 178.759 8.2808 1 1015 20 60 135 270 450 580 700 755 Asthma Yes 38 284.526 288.727 46.8377 30 1065 35 90 170 390 870 995 1065 1065 Asthma DK 2 75 63.64 45 30 120 30 30 75 120 120 120 120 120 Angina No 494 197.881 189.761 8.5378 1 1065 20 60 135 270 459 590 755 915 Angina Yes *9 247.778 235.267 78.4224 35 730 35 60 120 330 730 730 730 730 Angina DK 3 170 170.587 98.4886 30 360 30 30 120 360 360 360 360 360 Bronchitis/Emphysema No 490 196.978 184.633 8.3409 1 1065 20 60 145 270 454.5 585 735 840 Bronchitis/Emphysema Yes 14 273.143 339.073 90.6211 20 995 20 75 100 280 930 995 995 995 Bronchitis/Emphysema DK 2 75 63.64 45 30 120 30 30 75 120 120 120 120 120 Note: A"* Signifies missing data. "DK"= The respondent replied "don't know". Refused= Refused data. N =doer sample size. Mean= Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Std err= standard error. Min = minimum number of minutes. Max = maximum* number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Klepeis 1996.

Table 15-110. Statistics for 24-Hour Cumulative Number of Minutes Soent Outdoors at a Pool/River/Lake Percentiles Cateqorv Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 All 283 209.555 185.668 11.037 5 1440 25 60 150 296 480 570 670 690 Gender Male 152 229.829 202.702 16.441 10 1440 30 82.5 174 305 510 600 690 900 Gender Female 131 186.031 161.293 14.092 5 645 20 60 135 280 440 550 630 630 Age (years) . 6 175 156.971 64.083 60 480 60 85 115 195 480 480 480 480 Age (years) 1-4 14 250.571 177.508 47.441 90 630 90 130 167.5 370 560 630 630 630 Age (years) 5-11 29 175.448 117.875 21.889 25 390 30 60 145 293 365 375 390 390 Age (years) 12-17 22 128.318 94.389 20.124 40 420 58 60 82.5 210 225 235 420 420 Age (years) 18-64 187 224.492 203.822 14.905 5 1440 20 60 150 320 511 615 690 900 Age (years) > 64 25 194.2 161.757 32.351 20 525 30 60 115 277 480 510 525 525 Race White 246 201.565 182.298 11.623 5 1440 25 60 145 285 440 560 670 690 Race Black 12 380.583 231.89 66.941 20 690 20 177.5 450 562.5 615 690 690 690 Race Asian 4 265 247.083 123.54 30 505 30 52.5 262.5 477.5 505 505 505 505 Race Some Others 5 237 129.933 58.108 70 435 70 220 225 235 435 435 435 435 Race Hispanic 12 161 131.699 38.018 20 390 20 52.5 112.5 265 375 390 390 390 Race Refused 4 243.75 208.621 104.31 90 550 90 115 167.5 372.5 550 550 550 550 Hispanic No 259 208.923 187.792 11.669 5 1440 25 60 150 295 480 585 670 690 Hispanic Yes 20 210.9 160.142 35.809 20 540 28.5 87.5 155 337.5 450.5 525.5 540 540 Hispanic Refused 4 243.75 208.621 104.31 90 550 90 115 167.5 372.5 550 550 550 550 Employment . 66 176.879 131.256 16.156 25 630 40 70 142.5 235 370 420 560 630 Employment Full Time 119 210.748 176.089 16.142 10 900 20 65 150 298 510 600 645 670 Employment Part Time 26 217.038 199.926 39.209 20 670 30 60 120 320 570 580 670 670 Employment Not Employed 69 238.884 236.16 28.43 5 1440 20 65 145 370 510 630 690 1440 Employment Refused 3 141.667 52.52 30.322 90 195 90 90 140 195 195 195 195 195 Education . 73 172.932 129.988 15.214 20 630 30 70 140 225 370 420 560 630 Education < High School 18 267.611 159.382 37.567 40 600 40 145 247.5 375 525 600 600 600 Education High School Graduate 69 213.217 224.126 26.982 10 1440 20 60 145 285 511 670 690 1440 Education <College 62 233.258 192.408 24.436 5 690 30 65 150 360 550 580 615 690 Education College Graduate 37 230.919 187.271 30.787 14 645 20 70 173 400 505 630 645 645 Education Post Graduate 24 172.708 196.977 40.208 20 900 25 45 112.5 240 370 480 900 900 Census Region Northeast 61 220.689 172.373 22.07 30 900 30 60 180 325 390 510 670 900 Census Region Midwest 41 219.22 257.201 40.168 10 1440 20 60 120 280 480 600 1440 1440 Census Reg!on South 111 182.198 161.288 15.309 5 670 20 60 118 280 420 525 630 645 Census Region West 70 237.571 181.838 21.734 25 690 40 90 180 300 547.5 615 690. 690 Day Of Week Weekday 165 188.77 179.894 14.005 10 1440 30 60 125 255 420 511 615 670 Day Of Week Weekend 118 238.619 190.432 17.531 5 900 20 75 187.5 350 555 630 690 690 Season Winter 30 173.167 181.68 33.17 20 630 20 40 102.5 270 492.5 585 630 630 Season Spring 77 206.468 163.551 18.638 15 690 30 80 180 288 480 555 670 690 Season Summer 151 219.709 196.809 16.016 5 1440 26 65 155 300 445 580 630 900 Season Fall 25 201.4 189.663 37.933 20 670 45 70 105 310 510 510 670 670 Asthma No 262 209.004 188.208 11.628 5 1440 25 60 150 295 480 580 670 690 Asthma Yes 17 238.824 161.966 39.282 15 570 15 105 225 350 525 570 570 570 Asthma DK 4 121.25 59.214 29.607 60 195 60 75 115 167.5 195 195 195 195 Angina No 272 205.897 185.199 11.229 5 1440 25 60 145 290.5 480 570 645 690 Angina Yes 8 359.375 178.774 63.206 60 690 60 287.5 340 435 690 690 690 690 Angina DK 3 141.667 52.52 30.322 90 195 90 90 140 195 195 195 195 195 Bronchitis/Emphysema No 266 210.974 189.082 11.593 5 1440 25 60 150 296 480 580 670 690 Bronchitis/Emphysema Yes 14 197.143 131.54 35.156 15 440 . 15 90 172.5 300 370 440 440 440 Bronchitis/Emphysema DK 3 141.667 52.52 30.322 90 195 90 90 140 195 195 195 195 195 Note: A "*"Signifies missing data. "DK"= The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsann and Kleoeis 1996. Table 15-111. Statistics for 24-Hour Cumulative Number of Minutes Soent Outdoors at a Restaurant/Picnic Percentiles Catei:iorv Pooulation Grouo N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 All 64 81.016 114.7 14.337 3 540 5 12.5 30 107.5 165 270 540 540 Gender Male 31 111.839 148.921 26.747 5 540 5 20 60 150 270 540 540 540 Gender Female 33 52.061 57.66 10.037 3 210 3 8 30 80 135 180 210 210 Age (years) 1-4 6 57.5 61.38 25.058 5 160 5 15 30 105 160 160 160 160 Age (years) 5-11 5 112.8 202.59 90.601 5 473 5 6 20 60 473 473 473 473 Age (years) 12-17 6* 60 55.408 22.62 5 150 5 30 35 105 . 150 150 150 150 Age (years) 18-64 46 84.804 116.85 17.229 3 540 5 10 50 120 180 270 540 540 Age (years) > 64 1 15 *
15 15 15 15 15 15 15 15 15 15 Race White 54 76 105.032 14.293 3 540 5 15 30 105 165 270 473 540 Race Black 4 57.75 83.108 41.554 5 180 5 5.5 23 110 180 180 180 180 Race Asian 1 75 *

75 75 75 75 75 75 75 75 75 75 Race Some others 2 97.5 31.82 22.5 75 120 75 75 97.5 120 120 120 120 120 Race Hispanic 2 20 14.142 10 10 30 10 10 20 30 30 30 30 30 Race Refused 1 540 *

540 540 540 540 540 540 540 540 540 540 Hispanic No 60 81.833 117.521 15.172 3 540 5 12.5 30 107.5 172.5 371.5 540 540 Hispanic Yes 4 66.63 33.315 10 160 10 20 52.5 117.5 160 160 160 160 Employment

17 74.647 114.206 27.699 5 473 5 15 30 105 160 473 473 473 Employment Full Time 37 70.838 67.86 11.156 3 270 5 15 55 120 165 210 270 270 Employment Part Time 4 42 32.031 16.016 3 75 3 16.5 45 67.5 75 75 75 75 Employment Not Employed 6 187.833 272.841 111.387 5 540 5 7 17.5 540 540 540 540 540 Education

18 70:667 112.076 26.416 3 473 3 6 . 30 105 160 473 473 473 Education < High School 1 540 *

540 540 540 540 540 540 540 540 540 540 Education High School Graduate 11 56.182 84.536 . 25.489 3 270 3 10 20 60 165 270 270 270 Education <College 10 108.6 164.611 52.055 5 540 5 7 30 150 352.5 540 540 540 Education College Graduate 11 68.636 59.544 17.953 10 210 10 20 55 110 120 210 210 210 Education Post Graduate 13 70.308 53.494 14.836 6 180 6 15 75 80 140 180 180 180 Census Region Northeast 19 88.105 116.181 26.654 3 473 3 10 60 120 270 473 473 473 Census Region Midwest 15 102.6 140.685 36.325 3 540 3 15 45 165 210 540 540 540 Census Region South 16 48.563 47.25 11.812 5 140 5 8.5 30 92.5 120 140 140 140 Census Region \/Vest 14 85.357 138.737 37.079 10 540 10 15 30 75 160 540 540 540 Day Of Week Weekday 35 51.2 52.665 8.902 3 180 3 15 30 75 150 165 180 180 Day Of Week Weekend 29 117 154.21 28.636 5 540 5 10 60 135 473 540 540 540 Season Winter 8 79.375-75.187 26.583 10 210 10 20 52.5 135 210 210 210 210 Season Spring 14 138.429 172.811 46.186 5 540 5 30 65 180 473 540 540 540 Season Summer 28 71 105.063 19.855 3 540 3 7.5 35 100 150 160 540 540 Season Fall 14 44.571 52.2 13.951 5 165 5 10 20 60 150 165 165 165 Asthma No 61 82.131 117.182 15.004 3 540 5 10 30 110 165 270 540 540 Asthma Yes 3 58.333 40.723 23.511 30 105 30 30 40 105 105 105 105 105 Angina No 63 82.222 115.211 14.515 3 540 5 15 30 110 165 270 540 540 Angina Yes 1 5 *

5 5 5 5 5 5 5 5 5 5 Bronchitis/Emphysema No 63 81.667 115.502 14.552 3 540 5 10 30 110 165 270 540 540 Bronchitis/Emphysema Yes 1 40 *

40 40 40 40 40 40 40 40 40 40 Note: A"*" Signifies missing data. Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max= maximum number of minutes. Percentiles are the of doers below or to a given number of minutes. Source: sann and Kleneis 19 6.
Table 15-112. Statistics for 24-Hour Cumulative Number of Minutes Soent Outdoors at a Farm Percentiles Cateqorv Population Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 128 252.703 232.537 20.554 5 955 20 75 176.5 427.5 600 730 855 933 Gender Male 86 305.186 251.432 27.113 5 955 29 90 230 500 660 780 933 955 Gender Female 42 145.238 137.207 21.171 5 600 20 50 105 210 265 482 . 600 600 Age (years) . 1 510 . . 510 510 510 510 510 510 510 510 510 510 Age (years) 1-4 3 121.667 52.52 30.322 70 175 70 70 120 175 175 175 175 175 Age (years) 5-11 7 111.286 76.952 29.085 25 264 25 50 100 130 264 264 264 264 Age (years) 12-17 9 157.778 85.416 28.472 29 265 29 90 175 265 265 265 256 265 Age (years) 18-64 91 296.67 252.209 26.439 5 955 20 80 230 500 635 780 933 955 Age (years) > 64 17 133.824 134.182 32.544 5 495 5 50 85 160 360 495 495 495 Race White 120 260.217 236.226 21,554 5 955 20 75 180 472.5 607.5 745 855 933 Race Black 4 58.75 30.923 15.462 25 85 25 32.5 62.5 85 85 85 85 85 Race Some Others 2 165 21.213 15 150 180 150 150 165 180 180 180 180 180 Race Hispanic 2 277.5 222.739 157.5 120 435 120 120 277.5 435 435 435 435 435 Hispanic No 123 252.61 234.762 21.168 5 955 20 70 178 420 600 730 855 933 Hispanic Yes 4 297.5 189.143 94.571 120 485 120 135 292 .. 5 460 485 485 485 485 Hispanic Refused 1 85 . . 85 85 85 85 85 85 85 85 85 85 Employment . 19 134.947 77.658 17.816 25 265 25 86 120 180 264 265 265 265 Employment Full Time 73 314.781 258.07 30.205 5 955 20 85 240 525 660 780 933 955 Employment Part Time 11 283 183.589 55.354 45 525 45 150 230 490 495 525 525 525 Employment Not Employed 24 152.917 183.977 37.554 5 825 5 35 90 205 280 495 825 825 Employment Refused 1 20 . . 20 20 20 20 20 20 20 20 20 20 Education . 20 137.2 76.255 17.051 25 265 27 88 120 180 262 264.5 265 265 Education < High School 12 305 211.058 60.927 . 30 635 30 97.5 325 492.5 510 635 635 635 Education High School Graduate 50 314.54 280.31 39.642 5 955 20 85 215 525 745 855 944 955 Education <College 25 186.6 165.994 33.199 5 555 15 60 155 255 482 525 555 555 Education College Graduate 12 290.417 242.903 70.12 30 615 30 67.5 202.5 530 600 615 615 615 Education Post Graduate 9 229.444 246.062 82.021 5 780 5 80 150 210 780 780 780 780 Census Region Northeast 11 238.182 299.143 90.195 5 955 5 30 100 490 520 955 955 955 Census Region Midwest 42 202.31 196.644 30.343 15 780 20 654 125 265 510 635 780 780 Census Region South 57 279.702 239.345 31.702 5 933 25 85 195 482 635 760 825 933 Census Region West 18 293.667 242.324 57.116 5 855 5 120 220 525 615 855 855 855 Day Of Week Weekday 78 276.859 243.801 27.605 5 955 15 85 180 485 615 780 933 955 Day Of Week Weekend 50 215.02 210.635 29.788 5 855 25 60 120 290 525 700 792.5 855 Season Winter 32 205.25 207.666 36.711 5 955 22 77.5 120 245 495 540 955 955 Season Spring 40 224.4 213.304 33.726 5 825 25 60 152.5 342.5 525 625 825 825 Season Summer 43 276.093 247.758 37.783 5 933 20 70 230 435 660 760 933 933 Season Fall 13 379.231 264.904 73.471 15 780 15 200 280 600 730 780 780 780 Asthma No 120 256.983 235.209 21.472 5 955 21 75 180 427.5 607.5 745 855 933 Asthma Yes 8 188.5 188.481 66.638 5 .500 5 700 110 321.5 500 500 500 500 Angina No 127 253.039 233.426 20.713 5 955 20 75 175 435 600 730 855 933 Angina Yes 1 210 . . 210 210 210 210 210 210 210 210 210 210 Bronchitis/Emphysema No 125 256.208 233.892 20.92 5 955 22 75 178 435 600 730 855 933 Bronchitis/Emphysema Yes 3 106.667 95.699 55.252 5 195 5 5 120 195 195 195 195 195 Note: A "*"Signifies missing data. Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Std err= standard error. Min = minimum number of minutes. Max= maximum number of minutes. Percentiles are the of doers below or to a given number of minutes. Source: sana and Kleoeis 19 6. Table 15-113. Statistics for 24-Hour Cumulative Number of Minutes Scent at Home in the Kitchen Percentiles Cateoorv Pooulation Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 7063 92.646 *94.207 1.121 1 1320 10 30 60 120 205 270 365 460 Gender Male 2988 74.998 80.79 1.478 1 840 10 30 55 90 155 215 300 392 Gender Female 4072 105.636 101.03 1.5832 1 1320 10 35 75 145 230 295 395 475 Gender Refused 3 40 31.225 18.028 15 75 15 15 30 75 75 75 75 75 Age (years) . 144 102.688 110.82 9.235 5 840 15 30 70 130 215 260 485 540 Age (years) 1-4 335 73.719 54.382 2.9712 5 392 15 30 60 100 140 180 225 240 Age (years) 5-11 477 60.468 52.988 2.4262 1 690 10 30 50 75 120 150 180 235 Age (years) 12-17 396 55.02 58.111 2.9202 1 450 5 15 36 65 125 155 240 340 Age (years) 18-64 4531 90.313 90.893 1.3503 1 1320 10 30 60 120 200 260 345 420 Age (years) > 64 1180 131.388 119.55 3.4802 3 825 15 49 100 172 275 360 490 620 Race White 5827 95.076 95.151 1.2465 1 840 10 30 65 120 210 273 380 465 Race Black 641 79.376 91.989 3.6333 2 1320 10 30 60 100 175 230 275 380 Race Asian 113 89.363 95.45 8.9792 5 690 10 30 75 115 150 220 265 650 Race Some Others 119 69.059 60.786 5.5722 2 315 7 30 55 90 150 195 210 315 Race Hispanic 266 84.203 77.297 4.7394 1 585 10 30 60 110 190 240 305 360 Race Refused 97 90.33 113.55 11.53 5 880 7 30 60 90 190 275 480 880 Hispanic No 6458 . 93.422 94.778 1.1794 1 1320 10 30 60 120 210 270 370 460 Hispanic Yes 497 83.889 82.921 3.7195 1 675 10 30 60 110 180 240 315 415 Hispanic DK 32 82.25 71.901 12.71 5 300 10 35 60 112.5 185 240 300 300 Hispanic Refused 76 88.421 118.56 13.6 5 880 7 30 60 90 190 240 480 880 Employment . 1200 62.348. 55.431 1.6001 1 690 10 30 50 85 125 152.5 212.5 260 Employment Full Time 2965 77.748 77.466 1.4227 1 840 10 30 60 100 165 225 300 376 Employment Part Time 608 97.699 94.046 3.8141 1 755 10 30 70 133.5 213 270 405 445 Employment Not Employed 2239 126. 929 115.78 2.4468 1 1320 12 45 95 175 270 342 470 545 Employment Refused 51 106.373 168.46 23.589 2 880 5 30 48 130 210 250 840 880 Education . 1346 63.922 62.315 1.6985 1 880 10 30 50 85 130 165 235 285 Education < High School 678 108.114 102.88 3.9511 1 775 10 34 80 150 230 295 405 545 Education High School Graduate 2043 107 .208 102.33 2.264 1 840 10 35 75 150 235 300 415 500 Education <College 1348 94.359 101.17 2.7555 1 1320 10 30 60 120 210 280 380 450 Education College Graduate 933 91.874 92.098 3.0152 2 840 10 30 60 120 200 261 330 410 Education Post Graduate 715 88.227 87.661 3.2783 1 770 10 30 60 113 190 260 380 405 Census Region Northeast 1645 99.632 99.739 2.4591 1 840 10 30 70 130 210 300 390 465 Census Region Midwest 1601 96.066 93.567 2.3384 1 833 10 30 65 125 213 270 355 450 Census Region South 2383 86.253 87.055 1.7833 1 880 10 30 60 115 190 245 330 420 Census Region West 1434 91.441 99.061 2.6159 1 1320 10 30 60 119 195 255 380 480 Day Of Week Weekday 4849 90.068 92.218 1.3243 1 1320 10 30 60 119 195 255 360 450 Day Of Week Weekend 2214 98.294 98.207 2.0871 1 840 10 30 65.5 135 220 280 390 480 Season Winter 1938 96.575 100.32 2.2787 1 1320 10 30 65 120 210 285 390 485 Season Spring 1780 89.02 90.187 2.1376 1 840 10 30 60 120 195 255 350 420 Season Summer 1890 89.316 90.984 2.0928 1 880 10 30 60 120 195 255 362 430 Season Fall 1455 96.177 94.494 2.4773 1 770 10 30 65 125 210 275 375 470 Asthma No 6510 92.448 93.602 1.1601 1 1320 10 30 60 120 205 270 365 450 Asthma Yes 503 94.038 96.001 4.2805 1 785 10 30 60 120 210 270 345 450 Asthma DK 50 104.44 143.73 20.326 7 880 10 30 60 120 195 240 712.5 880 Angina No 6798 91.625 93.03 1.1283 1 1320 10 30 60 120 200 265 360 450 Angina Yes 207 122.469 111.41 7.7437 4 657 10 45 100 155 255 360 415 620 Angina DK 58 105.948 138.38 18.17 2 880 10 30 60 135 240 240 545 880 Bronchitis/Emphysema No 6671 91.827 92.587 1.1336 1 1320 10 30 60 120 200 265 360 445 Bronchitis/Emphysema Yes 338 104.784 113.39 6.1676 1 825 10 30 71 135 225 300 480 657 Bronchitis/Emphysema DK 54 117.889 142.41 19.38 2 880 10 30 76 160 240 275 545 880 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Stderr =standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsann and Kleneis 1996. Table 15-114. Statistics for 24-Hour Cumulative Number of Minutes Soent in the Bathroom Percentiles Cateqorv Pooulation Grouo N Mean Stdev Std err Min Mai< 5 25 50 75 90 95 98 99 All 6661 35.0237 48.796 0.5979 1 870 5 15 25 40 60 90 137 255 Gender Male 3006 32.689 50.366 0.9186 1 870 5 15 20.5 35 60 75 150 300 Gender Female 3653 36.9491 47.399 0.7842 *1 665 5 15 30 45 70 90 135 240 Gender Refused 2 27.5 3.536 2.5 25 30 25 25 27.5 30 30 30 30 30 Age (years) . 122 43.8689 67.007 6.0665 2 530 5* 15 30 45 85 120 300 360 (years) 1-4 328 35.939 46.499 2.5675 1 600 10 15 30 40 60 75 125 270 Age (years) 5-11 490 30.9673 38.609 1.7442 1 535 5 15 27 35 52.5 60 100 200 Age (years) 12-17 445 29.0517 32.934 1.5612 1 547 5 15 20 35 60 65 90 100 Age (years) 18-64 4486 34.4884 46.067 0.6878 1 665 5 15 25 40 60 90 135 250 Age (years) > 64 790 42.1975 69.431 2.4703 1 870 5 15 30 45 75 120 240 360 Race White 5338 34.3164 48.628 0.6656 1 870 5 15 25 40 60 85 135 255 Race Black 711 36.8678 39.559 1.4836 1 460 5 15 30 45 70 98 135 186 Race Asian 117 33.5556 41.449 3.8319 5 375 5 15 25 40 60 90 110 210 Race Some Others 134 47.306 69.649 6.0167 1 535 5 15 30 45 95 120 315 422 Race Hispanic 283 38.6396 61.494 3.6554 1 546 5 15 24 45 60 80 270 425 Race Refused 78 34.6026 49.182 5.5687 3 360 5 10 20 35 60 135 165 360 Hispanic No 6067 34.5332 45.887 0.5891 1 705 5 15 25 40 60 90 135 240 Hispanic Yes 498 39.2309 68.582 3.0733 1 870 5 15 25 45 60 90 270 425 Hispanic DK 33 44.4242 72.269 12.58 5 422 10 15 30 45 60 120 422 422 Hispanic Refused 63 44.0794 95.224 11.997 3 665 5 10 20 35 60 150 360 665 Employment . 1240 31.9645 39.652 1.1261 1 600 5 15 30 35 60 70 100 180 Employment Full Time 3130 33.4086 44.827 0.8012 1 595 5 15 25 40 60 80 123 240 Employment Part Time 583 35.5232 43.932 1.8195 1 430 5 15 29 45 60 90 140 270 Employment Not Employed 1661 40.1854 61.587 1.5111 1 870 5 15 30 45 75 110 210 340 Employment Refused 47 34.6809 54.835 7.9986 3 360 5 15 25 30 55 75 360 360 Education . 1386 32.1717 42.788 1.1493 1 665 5 15 25 35 60 70 110 200 Education < High School 522 40.8736 64.533 2.8245 1 870 5 15 30 45 70 100 240 350 Education High School Graduate 1857 35.832 50.155 1.1639 1 600 5 15 25 40 63 90 135 270 Education <College 1305 36.0797 44.121 1.2214 1 540 5 15 25 45 70 95 150 225 Education College Graduate 913 34.9912 54.071 1.7895 1 705 5 15 20 40 60 90 150 340 Education Post Graduate 678 32.1475 42.82 1.6445 1 460 5 15 22 40 60 75 110 300 Census Region Northeast 1497 34.3287 51.244 1.3244 1 600 5 15 25 40 60 80 140 335 Census Region Midwest 1465 35. 7802 54.521 1.4245 1 870 5 15 25 40 60 90 145 315 Census Region South 2340 35.0739 42.003 0.8683 1 510 5 15 30 40 60 90 135 214 Census Region West 1359 34.8874 50.399 1.3671 1 705 5 15 25 40 60 90 140 250 Day Of Week Weekday 4613 33.9035 46.663 0.687 1 870 5 15 25 40 60 85 135 240 Day Of Week Weekend 2048 37.5469 53.214 1.1759 1 600 5 15. 30 45 65 90 150 300 Season Winter . 1853 37.0232 50.658 1.1768 1 665 5 15 30 42 65 90 150 270 Season Spring 1747 36.6474 50.536 1.2091 1 870 5 15 30 . 45 60 90 135 240 Season Summer 1772 32. 7788 44.543 1.0582 1 570 5 15 25 38 60 80 135 210 Season Fall 1289 33.0349 49.108 1.3678 1 540 5 11 20 35 60 90 140 303 Asthma No 6132 34.9204 48.833 0.6236 1 870 5 15 25 40 60 90 135 255 Asthma Yes 493 35.2495 38.157 1.7185 1 410 5 15 30 45 65 90 140 220 Asthma DK 36 49.5278 121.114 20.186 3 665 5 10 17.5 30 60 360 665 665 Angina No 6473 34.5801 46.79 0.5816 1 870 5 15 25 40 60 90 135 240 Angina Yes 145 51.9103 88.284 7.3316 3 600 7 20 30 45 75 185 546 570 Angina DK 43 44.8605 111.216 16.96 3 665 5 10 15 30 50 110 665 665 Bronchitis/Emphysema No 6327 34.8211 48.073 0.6044 1 870 5 15 25 40 60 90 135 255 Bronchitis/Emphysema Yes . 296 36.8378 47.481 2.7598 1 600 5 15 30 43.5 60 90 180 250 Bronchitis/Emphysema DK 38 54.6316 122.723 19.908 3 665 5 10 17.5 30 110 360 665 665 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused= Refused data. N =doer sample size. Mean= Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Stderr =standard error. Min= minimum number of minutes. Max= maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleneis 1996. ------------- Table 15-115. Statistics for 24-Hour Cumulative Number of Minutes Scent at Home in the Bedroom Percentiles Cateqorv Population Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 9151 563.12 184.644 1.9302 3 1440 300 460 540 660 780 880 1005 1141 Gender Male 4157 549.648 182.976 2.8379 3 1440 285 450 540 640 780 860 980 1095 Gender Female 4990 574.274 185.332 2.6236 5 1440 312 470 555 660 790 900 1030 1185 Gender Refused 4 648.75 122.772 61.386 540 785 540 545 635 752.5 785 785 785 785 Age (years)
184 525.065 193.498 14.265 15 1440 195 420 513 600 720 860 950 1295 Age (years) 1-4 488 741.988 167.051 7.562 30 1440 489 635 740 840 930 990 1095 1200 Age (years) 5-11 689 669.144 162.888 6.2055 35 1440 435 600 665 740 840 915 1065 1140 Age (years) 12-17 577 636.189 8.7792 15 1375 165 542 645 750 875 970 1040 1210 Age (years) 18-64 5891 532.699 172.964 2.2535 3 1440 295 440 520 610 723 820 975 1110 Age (years) > 64 1322 550.8 171.997 4.7305 15 1440 315 475 540 610 735 . 840 1000 1140 Race White 7403 553.424 175.912 2.0445 3 1440 300 455 540 640 760 850 975 1105 Race Black 923 612.33 219.9 7.2381 15 1440 300 480 597 725 895 990 1160 1323 Race Asian 153 612.261 187.417 15.152 25 1285 345 510 600 705 830 950 1005 1245 Race Some Others 174 590.713 200.214 15.178 15 1405 300 464 580 700 830 960 1050 1152 Race Hispanic 378 602.577 214.353 11.025 25 1440 265 480 587.5 720 865 958 1095 1213 Race Refused 120 555.842 198.564 18.126 30 1405 285 440 534 630 762.5 875 1290 1295 Hispanic No 8326 560.878 182.574 2.0009 3 1440 300 460 540 650 780 870 1000 1140 Hispanic Yes 684 597.402 206.333 7.8893 15 1440 300 480 585 713 840 958 1095 1200 Hispanic DK 43* 542.279 169.881 25.907 135 1002 300 420 555 660 756 830 1002 1002 Hispanic Refused 98 523.439 180.194 18.202 30 1295 255 415 515 600 735 795 930 1295 Employment

1736 679.52 185.535 4.453 15 1440 390 590 675 785 892 960 1065 1170 Employment Full Time 3992 513.454 157.599 2.4943 3 1440 283 435 510 585 680 765 890 1000 Employment Part Time 777 551.613 169.425 6.0781 15 1335 330 455 540. 630 750 835 1005 1100 Employment Not Employed 2578 566.409 191.218 3.7661 5 1440 300 478 540 650 780 905 1095 1223 Employment Refused 68 513.971 209.558 25.413 30 1440 210 420 497.5 585 725 795 1200 1440 Education

1925 668.265 188.751 4.302 15 1440 360 575 663 780 885 960 1060 1170 Education < High School 807 554.809 180.581 6.3567 5 1440 300 450 540 630 775 860 1015 1160 Education High School Graduate 2549 534.057 176.208 3.4901 3 1440 285 447 520 607 720 835 975 1151 Education <College 1740 539.07 176.123 4.2222 5 1440 282 450 530 615 735 825 1005 1135 Education College Graduate 1223 526.025 164.899 4.7152 15 1404 300 445 515 600 713 785 965 1070 Education Post Graduate 907 525.192 160.567 5.3315 3 1355 315 445 510 600 690 780 950 1095 Census Region Northeast 2037 561.515 185.273 4.105 5 1440 300 457 540 655 781 885 1020 1139 Census Region Midwest 2045 552.402 179.232 3.9634 3 1440 280 450 540 643 765 860 965 1035 Census Region South 3156 570.023 186.38 3.3177 10 1440 300 465 552 660 790 900 1055 1155 Census Region West 1913 186.373 4.2611 5 1440 305 460 540 660 793 875 995 1152 Day Of Week Weekday 6169 552.611 174.489 2.2216 3 1440 325 450 539 635 760 855 975 1130 Day Of Week Weekend 2982 584.861

202.361 3.7057 3 1440 223 480 570 690 825 920 1055 1170 Season Winter 2475 576 183.782 3.6942 5 1440 305 475 555 660 805 900 1035 1148 Season Spring 2365 558.956 176.729 3.6341 15 1440 315 455 540 655 770 855 960 1095 Season Summer 2461 566.114 195.229 3.9354 3 1440 285 455 545 660 810 900 1030 1190 Season Fall 1850 547.23 179.924 4.1832 3 1440 270 450 537.5 630 750 850 960 1100 Asthma No 8420 560.814 182.769 1.9918 3 1440 300 460 540 655 780 870 1000 1140 Asthma Yes 671 593.846 201.517 7.7795 30 1440 300 475 580 690 835 946 1060 1327 Asthma DK 60 543.117 218.404 28.196 30 1295 223 423 540 605 760 982.5 1275 1295 Angina No 8836 564.211 183.935 1.9568 3 1440 300 460 540 660 785 880 1005 1140 Angina Yes 244 535.545 203.888 13.053 20 1440 215 450 522.5 612.5 770 840 1135 1230 Angina DK 71 522.113 193.937 23.016 30 1295 180 420 540 600 . 690 820 990 1295 Bronchitis/Emphysema No 8660 563.08 184.244 1.9799 3 1440 300 460 540 660 780 880 1005 1141 Bronchitis/Emphysema Yes 423 570.102 192.041 9.3373 15 1440 294 450 555 660 795 900 1055 1110 Bronchitis/Emphysema DK 68 524.765 186.701 22.641 30 1295 240 420 540 600 700 820 930 1295 Note: A "*" Signifies missing data. "DK"= The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Stderr =standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsann and Kleneis 1996.
Table 15-116. Statistics for 24-Hour Cumulative Number of Minutes Scent at Home in the Garaae Percentiles Cateaorv Population Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 193 117.782 144.451 10.398 1 790 5 20 60 150 296 480 665 690 Gender Male 120 144.058 162.612 14.844 2 790 10 30 93.5 182.5 315 518 675 690 Gender Female 73 74.589 94.322 11.04 1 530 5 15 30 120 180 240 450 530 Age (years) . 1 20 . . 20 20 20 20 20 20 20 20 20 20 Age (years) 1-4 4 83.5 47.459 23.729 15 120 15 52 99.5. 115 120 120 120 120 Age (years) 5-11 6 63.333 63.377 25.874 10 165 10 25 30 120 165 165 165 165 Age (years) 12-17 12 80.833 78.383 22.627 10 240 10 20 50.5 147.5* 185 240 240 240 Age (years) 18-64 130 134.508 165.117 14.482 1 790 5 20 67.5 180 360 526 675 690 Age (years) > 64 40 88.55 84.108 13.299 5 300 7.5 25 60 142.5 227.5 270 300 300 Race White 165 109.509 127.523 9.928 1 690 5 20 60 135 240 315 526 675 Race Black 12 205 219.483 63.359 5 570 5 37.5 90 405 530 570 570 570 Race Asian 1 5 . . 5 5 5 5 5 5 5 5 5 5 Race Some Others 6 186.333 308.416 125.91 10 790 10 18 30 240 790 790 790 790 Race Hispanic 8 120 164.859 58.287 15 510 15 22.5 60 135 510 510 510 510 Race Refused 1 120 . . 120 120 120 120 120 120 120 120 120 120 Hispanic No 174 116.615 138.452 10.496 1 690 5 20 60 155 296 460 570 675 Hispanic Yes 17 128.588 207.294 50.276 5 790 5 20 60 110 510 790 790 790 Hispanic Refused 2 127.5 10.607 7.5 120 135 120 120 127.5 135 135 135 135 135 Employment . 21 79.714 67.545 14.74 10 '240 15 25 51 120 165 185 240 240 Employment Full Time 85 145.259 175.17 19 1 790 5 20 65 180 405 530 675 790 Employment Part Time 17 50.118 51.967 12.604 5 194 5 15 30 60 135 194 194 194 Employment Not Employed 70 112.271 127.392 15.226 5 690 5 30 75 135 255 450 480 690 Education . 22 76.545 67.572 14.406 10 240 10 20 50.5 120 165 185 240 240 Education < High School 14 188.929 195.036 52.126 5 675 5 30 120 235 510 675 675 675 Education High School Graduate 63 127.286 159.283 20.068 2 690 5 25 60 165 300 530 665 690 Education <College 48 121.583 147.764 21.328 5 790 10 30 60 140 296 450 790 790 Education College Graduate 25 118.2 145.773 29.155 5 480 5 20 60 120 405 460 480 480 Education Post Graduate 21 75.857 88.067 19.218 1 300 2 10 30 120 195 260. 300 300 Census Region Northeast 23 137.174 159.451 33.248 5 510 15 30 60 195 460 510 510 510 Census Region Midwest 42 131.381 166.398 25.676 10 690 20 40 87.5 120 260 665 690 690 Census Region South 60 103.683 128.598 16.602 2 570 5 12.5 52.5 127.5 283 427.5 480 570 Census Region West 68 115.265 139.682 16.939 1 790 5 20 72.5 152.5 300 315 530 790 Day Of Week Weekday 116 128.664 158.968 14.76 1 790 5 25 60 165 315 510 665 690 Day Of Week Weekend 77 101.39 118.416 13.495 2 675 10 20 60 120 240 300 526 675 Season Winter 51 115.608 161.848 22.663 2 690 5 15 50 150 240 526 665 690 Season Spring 59 136.763 163.341 21.265 5 790 10 30 90 165 315 570 675 790 Season Summer 51 101.078 121.329 16.989 1 530 5 20 60 120 260 450 460 530 Season Fall 32 112.875 110.217 19.484 5 480 10 25 85 157.5 240 315 480 480 Asthma No 184 118.598 146.349 10.789 1 790 5 25 60 150 300 480 665 690 Asthma Yes 9 101.111 102.585 34.195 5 270 5 15 60 180 270 270 270 270 Angina No 187 118.219 146.174 10.689 1 790 5 20 60 150 300 480 665 690 Angina Yes 6 104.167 78.639 32.104 10 220 10 25 110 150 220 220 220 220 Bronchitis/Emphysema No 185 114.146 142.947 10.51 1 790 5 20 60 135 260 480 665 690 Bronchitis/Emphysema Yes 8 201.875 163.64 57.856 15 450 15 60 177.5 337.5 450 450 450 450 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsano and Kleoeis 1996. Table 15-117. Statistics for 24-Hour Cumulative Number of Minutes Spent in the Basement Percentiles Category Population Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 274 142.15 162.882 9.84 1 931 10 30 90 180 330 535 705 765 Gender Male 132 160.386 180.747 15.732 1 931 10 40 90 202.5 490 565 720 765 Gender Female 141 125.66 143.283 12.067 2 810 10 30 75 175 265 420 705 720 Gender Refused 1 60 . . 60 60 60 60 60 60 60 60 60 60 Age (years) . 3 171.667 122.712 70.848 30 245 30 30 240 245 245 245 245 245 Age (years) 1-4 8 94.75 55.695 19.691 28 180 28 47.5 90 137.5 180 180 180 180 Age (years) 5-11 25 135.4 145.945 29.189 15 705 15 60 105 140 270 420 705 705 Age (years) 12-17 26 97.462 113.063 22.173 1 515 10 30 60 150 240 275 515 515 Age (years) 18-64 170 151.271 .172.66 13.242 1 810 5 30 90 210 410 555 720 765 Age (years) > 64 42 143.833 173.502 26.772 5 931 10 40 90 170 330 455 931 931 Race White 248 133.75 154.08 9.784 1 810 10 30 90 167.5 315 510 705 720 Race Black 15 183.8 165.472 42.725 12 515 12 40 150 270 450 515 515 515 Race Asian 2 135 106.066 75 60 210 60 60 135 210 210 210 210 210 Race Some Others 3 468.667 455.654 263.072 20 931 20 20 455 931 931 931 931 931 Race Hispanic 1 30 . . 30 30 30 30 30 30 30 30 30 30 Race Refused 5 263.2 173.071 77.4 60 540 60 231 240. 245 540 540 540 540 Hispanic No 263 139.046 161.666 9.969 1 931 10 30 90 180 330 510 705 . 765 Hispanic Yes 6 185 197.332 80.561 15 555 15 30 150 210 555 555 555 555 Hispanic DK 1 185 . . 185 185 185 185 185 185. 185 185 185 185 Hispanic Refused 4 271.25 198.762 99.381 60 540 60 150 242.5 392.5 540 540 540 540 Employment . 57 115.561 124.205 16.451 1 705 12 40 90 150 240 420 515 705 Employment Full Time 107 149.075 178.633 17.269 1 810 5 30 75 210 450 540 720 765 Employment Part Time 22 115 114.808 24.477 10 535 25 60 77.5 150 185 290 535 535 Employment Not Employed 85 157.953 176.347 19.128 5 931 10 35 120 210 330 600 720 931 Employment Refused 3 151.667 110.265 63.661 30 245 30 30 180 245 245 245 245 245 Education . 65 129.492 133.447 16.552 1 705 15 45 90 160 270 420 535 705 Education < High School 15 169.867 203.464 52.534 5 605 5 30 90 255 565 605 605 605 Education High School Graduate 78 159.385 188.681 21.364 5 810 5 40 90 195 420 720 765 810 Education <College 48 160.583 184.204 26.588 2 931 10 25 120 202.5 400 600 931 931 Education College Graduate 39 146.744 150.808 24.149 10 555 10 30 70 210 450 510 555 555 Education Post Graduate 29 73.138 66.272 12.306 1 245 10 30 60 100 210 210 245 245 Census Region Northeast 90 115.611 118.744 12.517 5 555 10 40 72.5 150 250 400 540 555 Census Region Midwest 123 129.024 146.939 13.249 2 765 10 30 90 180 270 510 605 630 Census Region South 35 187.971 205.847 34.794 10 931 28 45 110 255 450 720 931 931 Census Region West 26 234.423 247.688 48.576 1 810 1 30 165 325 705 720 810 810 Day Of Week Weekday 178 135.331 159.404 11.948 1 810 10 30 82.5 180 315 535 720 765 Day Of Week Weekend 96 154.792 169.263 17.275 5 931 10 50 97.5 190 450 540 600 931 Season Winter 80 144.475 147.022 16.438 5 630 13.5 30 90 220.5 315 480 610 630 Season Spring 65 174.215 196.783 24.408 1 931 5 60 105 210 490 555 810 931 Season Summer 79 142.367 180.698 20.33 1 765 5 30 85 150 455 605 720 765 Season Fall 50 96.4 83.08 11.749 5 332 10 30 60 145 240 255 301 332 Asthma No 253 143.126 164.183 10.322 1 931 10 35 90 180 330 540 705 765 Asthma Yes 20 124.65 150.961 33.756 1 510 5.5 16 72.5 177.5 382.5 510 510 510 Asthma DK 1 245 . . 245 245 245 245 245 245 245 245 245 245 Angina No 269 "141.409 163.736 9.983 1 931 10 30 90 180 330 535 705 765 Angina Yes 3 201.667 122.1 70.494 65 300 65 65 240 300 300 300 300 300 Angina DK 2 152.5 130.815 92.5 60 245 60 60 152.5 245 245 245 245. 245 Bronchitis/Emphysema No 265 138.996 160.98 9.889 1 931 10 30 90 180 330 515 705 765 Bronchitis/Emphysema Yes 8 233.75 214.172 75.721 20 605 20 67.5 180 375 605 605 605 605 Bronchitis/Emphysema DK 1 245 . . 245 245 245 245 245 245 245 245 245 245 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused= Refused data. N =doer sample size. Mean= Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Std err= standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996. Table 15-118. Statistics for 24-Hour Cumulative Number* of Minutes Soent at Home in the Utilitv Room or Laundry Room Percentiles Group Name Grouo Code N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 458 73.218 71.872 3.358 1 510 5 25 60 100 150 200 300 360 Gender Male 70 78.443 95.687 11.437 1 510 5 20 60 90 167.5. 345 360 510 Gender Female 388 72.276 66.796 3.391 2 510 5 28 60 105 150 190 240 330 Age (years) . 6 65.833 34.412 14.049 25 120 25 40 60 90 120 120 120 120 Age (years) 1-4 3 75 116.94 67.515 5 210 5 5 10 210 210 210 210 210 Age (yeais) 5-11 3 105.667 168.423 97.239 2 300 2 2 15 300 300 300 300 300 Age (years) 12-17 8 55.5 77.107 27.261 1 240 1 17 33 52.5 240 240 240 240 Age (years) 18-64 362 73.58 73.87 3.882 2 510 5 20 60 105 150 195 325 405 Age (years) > 64 76 72.592 58.092 6.664 2 345 10 30 60 90 150 180 245 345 Race White 400 69.243 65.801 3.29 2 510 5 25 60 90 150 180 258 352.5 Race Black 35 100.514 103.238 17.45 1 510 5 20 60 135 240 300 510 510 Race Asian 4 82.5 37.749 18.875 30 120 30 60 90 105 120 120 120 120 Race Some Others 6 86.667 27.869 11.377 60 120 60 65 78 120 120 120 120 120 Race Hispanic . 10 95.9 78.827. 24.927 4 225 4 20 105 120 217.5 225 225 225 Race Refused 3 170 264.15 152.507 15 475 15 15 20 475 475 475 475 475 Hispanic No 435 72.069 69.87 3.35 1 510 5 25 60 90 150 190 300 360 Hispanic Yes 20 81.7 62.982 14.083 4 225 4.5 40 60 120 182.5 218 225 225 Hispanic DK 1 55 . . 55 55 55 55 55 55 55 55 55 55 Hispanic Refused 2 247.5 321.734 227.5 20 475 20 20 248 475 475 475 475 475 Employment . 12 76.75 107.831 31.128 1 300 1 4 23 135 240 300 300 300 Employment Full Time 206 69.184 78.438 5.465 2 510 5 20 60 90 135 203 360 405 Employment Part Time 51 72.216 62.506 8.753 2 225 5 15 55 120 150 180 225 225 Employment Not Employed 187 77.679 63.835 4.668 5 475 . 10 30 60 115 150 180 245 345 Employment Refused 2 76 104.652 74 2 150 2 2 76 150 150 150 150 150 Education . 17 72 90.881 22.042 1 300 1 10 35 90 240 300 300 300 Education < High School 51 71.765 49.445 6.924 15 245 20 30 60 90 120 180 195 245 Education High School Graduate 163 71.583 71.583 5.607 2 510 6 30 60 90 140 180 325 405 Education <College 107 77.234 71.721 6.934 2 475 5 20 60 120 155 200 225 240 Education College Gradutae 60 74.033 77.252 9.973 5 510 10 27 60 97.5 . 154 190 203 510 Education Post Graduate 60 71.267 79.857 10.31 5 360 5 18 60 90 155 263 360 360 Census Region Northeast 105 80.933 84.595 8.256 2 510 5 25 60 120 180 225 345 360 Census Region Midwest 116 64.948 63.307 5.878 2 475 5 15 60 90 135 155 215 240 Census Region South 151 72.695 69.541 5.659 1 510 10 30 60 90 150 210 245 330 Census Region West 86 75.872 69.9 7.537 4 405 5 30 60 115 150 180 360 405 Day or week Weekday 322 68.643 66.724 3.718 1 510 5 23 60 90 140 180 240 345 Day Of Week Weekend 136 84.051 82.05 7.036 5 510 10 30 60 120 180 240 360. 405 Season Winter 145 75.248 80.989 6.726 1 510 5 17 60 90 165 215 360 475 Season Spring 89 81.888 83.016 8.8 5 510 10 30 60 100 180 240 405 510 Season Summer 132 69.25 60.815 5.293 2 360 5 25 60 120 135 155 240 325 Season Fall 92 67.326 58.613 6.111 3 345 10 22 60 90 125 180 245 345 Asthma No 432 73.764 73.182 3.521 1 510 5 25 60 105 150 200 325 360 Asthma Yes 26 64.154 44.791 8.784 10 200 10 25 60 90 120 130 200 200 Angina No 440 72.134 70.217 3.347 1 510 5 25 60 100 150 185 270 360 Angina Yes 16 103.125 109.877 27.469 5 360 5 30 60 138 345 360 360 360 Angina DK 2 72.5 17.678 12.5 60 85 60. 60 73 85 85 85 85 85 Bronchitis/emphysema No 428 73.276 73.484 3.552 1 510 5 24 60 105 150 200 325 360 Bronchitis/emphysema Yes 30 72.4 43.498 7.942 10 200 15 45 60 90 125 150 200 200 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Std err= standard error. Min= minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996. Table 15-119. Statistics for 24-Hour Cumulative Number of Minutes Soent at Home in the Outdoor Pool or Soa Percentiles Cateqorv Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 All 85 115.318 103.713 11.249 1 450 15 34 90 150 255 360 450 450 Gender Male 34 113.676 106.758 18.309 5 450 10 45 75 150 258 360 450 450 Gender Female 51 116.412 102.691 14.38 1 450 15 30 90 178 240 360 390 450 Age (years) . 2 60 63.64 45 15 105 15 15 60 105 105 105 105 105 Age (years) 1-4 9 85.556 86.329 28.776 15 255 15 30 60 75 255 255 255 255 Age (years) 5-11 15 164.2 103.969 26.845 25 450 25 105 140 185 300 450 450 450 Age (years) 12-17 5 97 53.805 24.062 40 180 40 60 100 105 180 180 180 180 Agei (years) 18-64 44 117.614 112.718 16.993 4 450 15 32 82.5 155 297 360 450 450 Age (years) > 64 10 78.9 85.318 26.98 1 258 1 20 52.5 90 226.5 258 258 258 Race White 75 120.893 107.723 12.439 1 450 15 34 90 180 258 360 450 450 Race Black 5 66 59.729 26.711 10 150 10 20 45 105 150 150 150 150 Race Some Others 1 105 . . 105 105 105 105 105 105 105 105 105 105 Race Hispanic 2 112.5 53.033 37.5 75 150 75 75 112.5 150 150 150 150 150 Race Refused 2 37.5 31.82 22.5 15 60 15 15 37.5 60 60 60 60 60 Hispanic No 78 116.821 104.631 11.847 1 450 10 34 90 160 255 360 450 450 Hispanic Yes 5 123 108.374 48.466 30 300 30 60 75 150 300 300 300 300 Hispanic Refused 2 37.5 31.82 22.5 15 60 15 15 37.5 60 60 60 60 60 Employment . 29 128.207 96.956 18.004 15 450 20 60 105 178 255 300 450 450 Employment Full Time 27 111.889 102.499 19.726 4 390 10 30 90 150 297 360 390 390 Employment Part Time 2 237.5 300.52 212.5 25 450 25 25 237.5 450 450 450 450 450 Employment Not Employed 26 98.962 94.835 18.599 1 360 5 30 67.5 130 240 258 360 360 Employment . Refused 1 15 . . 15 15 15 15 15 15 15 15 15 15 Education . 30 124.433 97.486 17.798 15 450 15 60 105 178 250 300 450 450 Education < High School 8 109.375 155.367 54.93 5 450 5 15 37.5 157.5 450 450 450 450 Education High School Graduate 15 150 130.516 33.699 1 390 1 45 105 240 360 390 390 390 Education <College 17 80.529 66.66 16.167 4 240 4 30 75 90 225 240 240 240 Education College Graduate 9 120.556 107.308 35.769 15 297 15 30 85 180 297 297 297 297 Education Post Graduate *6 81.667 42.032 17.159 30 135 30 60 67.5 130 135 135 135 135 Census Region Northeast 23 135.348 113.518 23.67 1 450 10 40 100 225 245 297 450 450 Census Region Midwest 16 64.625 63.636 15.909 4 255 4 25 52.5 82.5 135 255 255 255 Census Region South 23 114.696 78.499 16.368 15 390 20 60 105 150 185 210 390 390 Census Region West 23 131.174 129.262 26.953 15 450 25 30 75 195 360 360 450 450 Day Of Week Weekday 56 114.464 106.726 14.262 1 450 5 30 90 155 255 390 450 450 Day Of Week Weekend 29 116.966 99.452 18.468 10 360 20 45 85 150 297 360 360 360 Season Winter 10 118.9 159.415 50.412 4 450 4 20 30 135 405 450 450 450 Season Spring 24 97.417 74.622 15.232 10 360 30 52.5 80 120 180 195 360 360 Season Summer 47 124.511 104.25 15.206 1 450 15 40 90 185 255 300 450 450 Season Fall 4 105.75 107.481 53.741 30 258 30 30 . 67.5 181.5 258 258 258 258 Asthma No 73 109.89 105.481 12.346 1 450 10 30 75 140 255 360 450 450 Asthma Yes 11 160.455 82.355 24.831 85 360 85. 90 150 225 225 360 360 360 Asthma DK 1 15 . . 15 15 15 15 15 15 15 15 15 15 Angina No 84 116.512 103.746 11.32 1 450 15 37 90 155 255 360 450 450 Angina DK 1 15 . . 15 15 15 15 15 15 15 15 15 15 Bronchitis/Emphysema No 78 115.731 101.786 11.525 1 450 10 40 90 150 255 360 450 450 Bronchitis/Emphysema Yes 6 126.667 137.792 56.253 15 360 15 25 67.5 225 360 360 360 360 Bronchitis/Emphysema DK 1 15 .
15 15 15 15 15 15 15 15 15 15 Note: A ..... Signifies missing data. "DK" =The respondent replied "don't know". Refused =Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Stderr =standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsann and Kleneis 1996.
Table 15-120. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Yard or Other Areas Outside the House Percentiles Category Population Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 2308 137.587 144.112 2.9997 1 1290 10 40 90 180 320 420 570 660 Gender Male 1198 158.448 160.016 4.6231 1 1290 10 60 120 198 360 500 627 730 Gender Female 1107 114.887 120.869 3.6328 1 1065 5 30 75 150 285 360 450 560 Gender Refused* 3 183.333 60.277 34.801 120 240 120 120 190 240 240 240 240 240 Age (years) . 27 167.37 164.484 31.6549 2 600 5 60 120 230 395 600 600 600 Age (years) 1-4 151 135.311 111.483 9.0723 5 630 25 60 90 180 305 345 450 480 Age (years) 5-11 271 150.594 135.111 8.2074 2 1250 20 60 120 190 310 405 553 570 Age (years) 12-17 157 113.153 117.746 9.3972 2 660 5 30 80 150 240 405 462 610 Age (years) 18-64 1301 136.382 147.923 4.1011 1 1080 5 30 90 180 330 435 570 715 Age (years) > 64 401 141.125 155.213 7.751 1 1290 10 45 90 180 302 465 598 660 Race White 1966 139.037 145.534 3.2823 1 1290 io 40 90 180 330 435 570 670 Race Black 173 128.416 144.607 10.9943 1 1250 5 30 95 180 270 390 462 745 Race Asian 21 101.19 88.485 19.3091 12 360 15 35 90 125 210 240 360 360 Race Some Others 37 183.541 161.858 26.6094 2 750 3 84 120 270 380 553 750 750 Race Hispanic 83 106.108 96.781 10.6231 2 610 5 35 75 145 240 270 330 610 Race Refused 28 152.321 151.049 28.5455 5 600 5 60 97.5 210 360 510 600 600 Hispanic No 2122 137.711 144.33 3.1332 1 1290 10* 40 90 180 320 420 570 670 Hispanic Yes 153 125 134.265 10.8547 1 750 5 30 85 150 270 435 575 630 Hispanic DK 10 213.8 192.232 60.7892 3 585 3 60 145 380 503 585 585 585 Hispanic Refused 23 176.739 156.551 32.6431 5 600 5 60 160 240 360 510 600 600 Employment . 581 137.501 125.562 5.2092 2 1250 15 60 110 180 300 370 480 570 Employment Full Time 807 131.087 150.703 5.305 f 1080 5 30 80 175 307 450 600 745 Employment Part Time 166 126.145 134.084 10.407 1 1080 10 30 77.5 180 300 360 450 485 Employment Not Employed 739 146.097 149.672 5.5058 1 1290 10 45 100 185 360 465 585 655 Employment Refused 15 198 239.029 61.7171 5 660 5 30 120 465 600 660 660 660 Education . 615 136.348 125.656 5.0669 2 1250 15 60 105 180 300 370 480 570 Education < High School 236 161.017 186.469 12.1381 2 1290 10 45 105 195 390 510 765 915 Education High School G_raduate 618 144.706 144.929 5.8299 1 840 5 40 100 195 360 479 555 660 Education <College 381 128.843 141.194 7.2336 1 1080 5 35 85 175 300 400 585 720 Education College Graduate 251 122.968 135.802 8.5717 1 750 10 30 75 160 300 390 575 690 Education Post Graduate 207 127.126 149.975 10.424 1 1065 5 30 78 150 320 435 570 630 Census Region Northeast 473 137.67 132.769 6.1047 1 750 10 45 90 185 317 420 532 600 Census Region Midwest 456 138.853 155.656 7.2893 2 1290 10 45 90 180 300 440 575 690 Census Region South ,832 136.472 146.655 5.0843 1 1080 10 35 90 180 310 420 570 730 Census Region West 547 138.155 139.946 5.9837 1 750 5 36 90 180 330 460 570 630 Day Of Week Weekday 1453 126.919 131.579 3.4519 1 1250 5 35 90 165 300 395 553 610 Day Of Week Weekend 855 155.716 161.693 5.5298 1 1290 10 45 110 210 360 475 630 745 Season Winter 399 112.19 135.967 6.8068 1 1080 5 30 60 140 300 380 540 690 Season Spring 787 149.738 139.245 4.9635 1 915 10 60 120 195 338 430 555 660 Season Summer 796 143.681 155.886 5.5252 1 1290* 10 45 *99 180 330 450 610 715 Season Fall 326 124.457 130.523 7.229 1 720 10 35 87.5 160 300 380 510 655 Asthma No 2129 137.746 144.41 3.1297 1 1290 10 40 90 180 315 420 570 690 Asthma Yes 166 131.566 136.006 10.5561 1 670 10 30 90 165 345 450 553 610 Asthma DK 13 188.462 192.141 53.2904 5 600 5 60 90 300 480 600 600 600 Angina No 2228 136.521 141.088 2.989 1 1290 10 41 90 180 315 420 570 660 Angina Yes 63 158.683 216.341 27.2564 2 *1080 5 30 75 180 420 485 1065 1080 Angina DK 17 199.118 191.305 46.3983 5 600 5 35 120 325 480 600 600 600 Bronchitis/Emphysema No 2191 138.793 144.994 3.0976 1 1290 10 45 90 180 320 430 570 690 Bronchitis/Emphysema Yes 105 104.438 111.282 10.86 1 553 5 30 60 145 270 360 415 475 Bronchitis/Emphysema DK 12 207.5 192.23 55.4919 5 600 5 60 140 330 480 600 600 600 Note: A ..... Signifies missing data. "DK"= The respondent replied "don't know". Refused= Refused data. N =doer sample size. Mean= Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Std err= standard error. Min= minimum number of minutes. Max= maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996. Table 15-121. Statistics for 24-Hour Cumulative Number of Minutes Spent TravelinQ in a Car Percentiles Cateaorv Population Grouo N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 6560 87.4261 88.186 1.0888 1 1280 10 34 63 110 175 240 345 450 Gender Male 2852 90.7398 97.337 1.8227 1 1280 10 30 63 115 185 254 360 526 Gender Female 3706 84.9069 80.374 1.3203 1 878 10 35 63.5 110 165 220 335 420 Gender Refused 2 30 14.142 10 20 40 20 20 30 40 40 40 40 40 Age (years) . 120 94.025 90.218 8.2358 7 593 10 37.5 71.5 120 180 222.5 435 450 Age (years) 1-4 297 63.0101 56.758 3.2934 2 390 10 25 45 80 135 180 235 270 Age (years) 5-11 449 64.6325 81.08 3.8264 1 900 5 20 40 85 145 175 310 345 Age (years) 12-17 393 64.8346 70.974 3.5802 1 630 9 20 41 80 136 185 300 380 Age (years) 18-64 4489 93.8278 92.302 1.3776 1 1280 13 40 70 120 184 250 360 495 Age (years) > 64 812 83.5283 79.436 2.7877 4 780 10 30 60 110 165 225 315 405 Race White 5337 87.6283 89.72 1.2281 1 1280 10 31 64 110 175 240 360 460 Race Black 640 86.8063 74.343 2.9387 1 690 10 35 65 115 180 240 305 330 Race Asian '117 78.7607 66.315 6.1309 5 360 20 35 60 95 135 225 320 330 Race Some Others 121 87.6942 84.48 7.68 3 540 10 30 60 120 180 250 330 345 Race Hispanic 265 90.0717 101.474 6.2335 2 825 15 35 65 100 165 235 465 620 Race Refused 80 82.4 73.314 8.1967 5 420 12 30 60 120 167.5 229.5 315 420 Hispanic No 5987 87.4657 87.603 1.1322 1 1280' 10 35 65 110 175 240 345 440 Hispanic Yes 477 88.543 97.206 4.4507 2 825 10 30 60 103 180 240 388 595 Hispanic DK 29 63.8966 73.131 13.5801 5 325 6 20 40 60 187 200 325 325 Hispanic Refused 67 86.1194 78.361 9.5733 5 420 14 30 60 120 180 239 315 420 Employment . 1124 64.2482 72.331 2.1575 1 900 5 20 45 81 136 180 270 345 Employment Full Time 3134 93.5568 92.167 1.6464 2 1280 15 40 70 120 180 242 360 490 Employment Part Time 632 90.0506 81.969 3.2605 2 878 10 40 70 116.5 175 230 330 384 Employment Not Employed 1629 90.3603 90.224 2.2354 1 780 10 35 60 115 195 250 365 465 Employment Refused 41 97.1707 83.994 13.1176 10 330 15 30 75 120 220 290 330 330 Education . 1260 66.531 72.305 2.0369. 1 900 6 21 45 85 145 186.5 270 350 Education < High School 434 86.0115 82.143 3.943 5 620 10 35 60 115 165 210 360 455 Education High School Graduate 1805 91.8476 91.088 2.144 1 870 10 38 65 115 190 255 385 465 Education <College 1335 93.2427 94.302 2.581 2 1280 10 36 70 120 180 250 380 460 Education College Graduate 992 95.6683 95.468 3.0311 4 840 14 40 73 120 185 250 370 580 Education Post Graduate 734 91.5395 82.009 3.027 4 905 20 40 75 115 175 235 330 380 Census Region Northeast 1412 85.8343 83.847 2.2314 1 780 10 33 60 110 170 240 330 410 Census Region Midwest 1492 89.0992 86.623 2.2426 4 825 10 35 65 112.5 180 250 360 465 Census Region South 2251 88.2625 89.347 1.8832 1 900 10 34 65 115 175 235 338 490 Census Region West 1405 85.9089 92.167 2.4589 2 1280 10 30 60 110 175 235 345 435 Day* Of Week Weekday 4427 83.9248 85.023 1.2779 1 905 10 30 60 105 165 225 330 440 Day Of Week Weekend 2133 94.6929 94.018 2.0357 1 1280 10 35 70 120 190 265 360 455 Season Winter 1703 83.4692 82.128 1.9902 1 870 10 30 60 105 165 230 350 425 Season Spring 1735 88.589 91.537 2.1976 1 905 10 30 60 110 180 250 380 480 Season Summer 1767 88.0266 86.471 2.0571 1 900 10 35 65 115 170 235 330 450 Season Fall 1355 90.1269 93.173 2.5312 1 1280 10 35 70 115 170 240 335 545 Asthma No 6063 87.4143 88.032 1.1306 1 1280 10 34 63 110 175 240 350 450 Asthma Yes 463 88.2419 92.088 4.2797 4 870 15 34 64 110 165 245 345 505 Asthma DK 34 78.4118 57.362 9.8376 10 239 10 30 71 100 160 220 239 239 Angina No 6368 87.54 88.695 1.1115 1 1280 10 34 63.5 110 175 240 350 450 Angina
Yes 154 82.1753 68.568 5.5254 8 365 10 30 60 115 162 214 285 320 Angina DK 38 89.6053 72.877 11.8221 10 360 10 35 73.5 120 180 239 360 360 Bronchitis/Emphysema No 6224 87.5517 88.855 1.1263 1 1280 10 34 62 110 175 240 350 450 Bronchitis/Emphysema Yes 300 85.5833 76.155 4.3968 1 505 10 35 68.5 109 185 237.5 305 435 Bronchitis/Emphysema DK 36 81.0556 63.142 10.5237 5 239 10 30 71 120 175 220 239 239 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused= Refused data. N =doer sample size. Mean= Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Std err= standard error. Min= minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996.
Table 15-122. Statistics for 24-Hour Cumulative Number of Minutes Soent Travelina in a Truck IPick-unNanl Percentiles Group Name Group Code N Mean Stdev Std err Min Max 5 25 50 75 90 95 . 98 99 All 1172 85.3 95.867 2.8003 1 955 10 30 60 110 180 240 395 478 Gender Male 760 91.097 105.368 3.8221 1 955 10 30 60 115 190 265 450 620 Gender Female 412 74.607 74.197 3.6554 1 510 10 25 55 95 165 220 300 355 Age (years) . 13 110.769 129.178 35.8274 10 450 10 35 60 90 300 450 450 450 Age (years) 1-4 41 80.829 154.295 24.0969 1 955 10 15 35 70 206 210 955 955 Age (years) 5-11 89 47.607 44.208 4.6861 1 240 7 15 30 65 110 130 180 240 Age (years) 12-17 80 66.763 71.084 7.9475 5 352 5.5 15 37 93.5 180 222.5 265 352 Age (years) 18-64 859 91.42 97.968 3.3426 2 750 10 30 60 115 189 260 440 555 Age (years) > 64 90 79 82.42 8.6878 10 453 12 30 48.5 105 185 265 390 453 Race White 1022 84.717 96.222 3.0099 1 955 10 30 60 110 180 235 390 510 Race Black 68 91.294 98.465 11.9406 6 453 14 27.5 62.5 105.5 220 295 450 453 Race Asian 3 '138.333 63.311 36.5529 90 210 90 90 115 210 210 210 210 210 Race Some Others . 20 67.2 48.46 10.836 5 165 7.5 25 62.5 102.5 137 154.5 165 165 Race Hispanic 48 92.792 99.31 14.3341 5 440 10 27.5 60 120 224 330 440 440 Race Refused 11 88.182 110.754 33.3935 10 390 10 30 60 '65 190 390 390 390 Hispanic No 1069 85.112 95.567 2.9229 1 955 10 30 60 110 180 240 390 478 Hispanic Yes 87 89.103 100.75 10.8015 5 630 5 29 60 115 210 230 440 630 Hispanic DK 5 *58 36.187 16.1833 20 97 20 20 68 85 97 97 97 97 Hispanic Refused 11 85.909 111.643 33.6615 10 390 10 30 35 65 190 390 390 390 Employment . 205 60.176 86.416 6.0355 1 955 7 15 30 75 146 185 240 265 Employment Full Time 642 93.288 101.354 4.0001 4 750 10 30 60 120 192 270 450 555 Employment Part Time 97 89.351 88.958 9.0323 2 460 6 30 . 60 120 190 270 450 460 Employment Not Employed 217 83.032 85.775 5.8228 5 655 10 30 60 110 180 235 300 355 Employment Refused 11 96.364 114.26 34.4508 10 390 10 30 35 170 190 390 390 390 Education . 230 64.043 86.936 5.7324 1 955 7 15 35 85 160 206 245 352 Education < High School 119 90.471 81.711 7.4904 5 453 14 35 60 120 195 280 295 450 Education High School Graduate 392 87.594 94.724 4.7843 2 675 10 30 60 115 185 255 450 510 Education <College 238 91.992 111.776 7.2454 4 750 10 30 60 110 190 290 555 655 Education College Graduate 127 85.228 74.586 6.6184 5 370 15 30 60 110 180 230 345 355 Education Post Graduate 66 112.439 117.975 14.5217 10 650 10 35 80 135 220 412 445 650 Census Region Northeast 170 85.365 104.161 7.9888 2 695 10 20 50 110 186 260 445 630 Census Regio'n Midwest 268 91.209 94.43 5.7682 1 750 10 30 . 60 118.5 205 245 390 460 Census Region South 491 87.279 100.099 4.5174 4 955 10 30 60 111 180 235 445 595 Census Region West 243 74.741 81.299 5.2153 5 478 10 23 52 90 160 235 395 440 Day Of Week Weekday 796 80.083 90.569 3.2101 1 750 10 30 55 101 170 230 375 510 Day Of Week Weekend 376 96.346 105.493 5.4404 *2 955 12 30 60.5 120 192 . 280 430 460 Season Winter 322 78.543 91.604 5.1049 1 955 10 29 51 95 170 220 355 445 Sea*son Spring 300 92.477 100.164 5.783 1 '695 10 30 60 120 208 267.5 442.5 549 Season Summer 323 86.133 99.255 5.5227 2 750 10 30 60 110 180 233 430 595 Season Fall 227 84.216 90.861 6.0306 5 675 10 30 60 105 165 265 395 465 Asthma No 1092 85.288 93.452 2.828 1 750 10 30 60 110 184 240 412 478 Asthma Yes 72 83.639 125.252 14.7611 5 955 10 20 46 115 170 . 235 395 955 Asthma DK 8 101.875 129.668 45.8446 10 390 10 20 60 127.5 390 390 390 390 Angina No 1142 84.868 95.219 2.8177 1 955 10 30 60 110 180 235 395 475 Angina Yes 20 93.4 116.003 25.939 5 555 7.5 37.5 70 103 140.5 350.5 555 555 Angina DK 10 118.5 128.583 40.6615 10 390 10 30 60 190 340 390 390 390 Bronchitis/Emphysema No 1128 85.469 96.579 2.8756 1 955 10 30 60 110 180 240 412 478 Bronchitis/Emphysema Yes 35 77.8 60.527 10.2308 5 240 5 30 60 120 165 220 240 240 Bronchitis/Emphysema DK 9 93.333 123.92 41.3068 10 390 10 20 60 65 390 390 390 390 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Std err= standard error. Min= minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsann and Kleneis 1996. Table 15-123. Statistics for 24-Hour Cumulative Number of Minutes Soent Travelinq on a Motorcvcle, Mooed, or Scooter Percentiles Cateqory Population Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 32 100.125 152.222 26.909 1 535 5 25 31 98 375 510 535 535 Gender Male 29 104.276 158.322 29.4 1 535 5 25 32 80 485 510 535 535 Gender Female 3 60 74.666 43.108 5 145 5 5 30 145 145 145 145 145 Age (years) 5-11 2 42.5 53.033 37.5 5 80 5 5 42.5 80 80 80 80 80 Age (years)
12-17 1 180 . . 180 180 180 180 180 180 180 180 180 180 Age (years) 18-64 28 103.893 160.69 30.367 1 535 5 25 31 90.5 485 510 535 535 Age (years) > 64 1 30 . . 30 30 30 30 30 30 30 30 30 30 Race White 31 101.516 154.532 27.755 1 535 5 25 30 116 375 510 535 535 Race Black 1 57 . . 57 57 57 57 57 57 57 57 57 57 Hispanic No 31 102.387 154.191 27.693 1 535 5 25 32 116 375 510 535 535 Hispanic Yes 1 30 . . 30 30 30 30 30 30 30 30 30 30 Employment . 3 88.333 87.797 50.69 5 180 5 5 80 180 180 180 180 180 Employment Full Time 23 62.783 100.105. 20.873 1 485 5 25 30 57 142 1_45 . 485 485 Employment Not Employed 6 249.167 251.663 102.741 10 535 10 30 205 510 535 535 535 535 Education . 3 88.333 87.797 50.69 5 180 5 5 80 180 180 180 180 180 Education < High School 3 305 247.538 142.916 30 510 30 30 375 510 510 510 510 510 Education High School Graduate 15 95.667 170.645 44.06 1 535 1 25 30 57 485 535 535 535 Education <College 6 45.833 49.54 20.224 10 145 10 20 32.5 35 145 145 145 145 Education College Graduate 4 70.5 51.423 25.712 20 142 20 37.5 60 103.5 142 142 142 142 Education Post Graduate 1 32 . . 32 32 32 32 32 32 32 32 32 32 Census Region Northeast 6 ;24.167 8.01 3.27 10 30 10 20 27.5 30 30 30 30 30 Census Region Midwest 12 191.583 216.501 62.499 1 535 1 28 68.5 430 510 535 535 535 Census Region South 6 67.167 66.764 27.256 5 180 5 32 35 116 180 180 180 180 Census Region West 8 44.625 44.654 15.788 5 142 5 15 30 60 142 142 142 142 Day Of Week Weekday 21 71.333 110.425 24.097 5 510 5 25 32 65 145 180 510 510 Day Of Week Weekend 11 155.091 205.865 62.071 1 535 1 20 30 375 485 535 535 535 Season Winter 5 124 230.011 102.864 5 535 5 20 25 35 535 535 535 535 Season Spring 12 121.833 153.631 44.349 1 485 1 28 43.5 143.5 375 485 485 485 Season Summer 8 55.875 52.267 18.479 20 180 20 30 33.5 60 180 180 180 180 Season Fall 7 96.429 184.249 69.639 5 510 5 5 30 80 510 510 510 510 Asthma No 30 85.1 134.187 24.499 1 510 5 25 30 65 277.5 485 510 510 Asthma Yes 2 325.5 296.278 209.5 116 535 116 116 325.5 535 535 535 535 535 Angina No 31 102.387 154.191 27.693 1 535 5 25 32 116 375 510 535 535 Angina Yes 1 30 . . 30 30 30 30 30 30 30 30 30 30 Bronchitis/Emphysema No 31 101.516 154.532 27.755 1 535 5 25 30 116 375 510 535 535 Bronchitis/Emphysema Yes -1 57 . . 57 57 57 57 57 57 57 57 57 57 Note: A"*" Signifies missing data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Stderr*= standard error. Min= minimum number of minutes. Max= maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleneis 1996.
Table 15-124. Statistics for 24-Hour Cumulative Number of Minutes Soent Traveling in Other Trucks Percentiles Cate!:forv Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 All 124 135.121 235.635 21.16 1 1440 5 25 48 107.5 270 690 960 1080 Gender. Male 80 174.888 283.085 31.65 1 1440 5 27 60 139 640 772.5 1080 1440 Gender Female 44 62.818 57.438 8.659 1 270 5 20 45 90 145 180 270 270 Age (years) . 1 35 . . 35 35 35 35 35 35 35 35 35 35 Age (years) 1-4 4 79 26.47 13.235 46 105 46 58 82.5 100 105 105 105 105 Age (years) 5-11 9 37.875 28.002 9.9 10 95 10 18.5 30 50.5 95 95 95 95 Age (years) 12-17 7 116.857 83.071 31.398 10 250 10 60 90 195 250 250 250 250 Age (years) 18-64 96 153.24 263.424 26.886 1 1440 5 22.5 45 117 600 750 1080 1440 Age (years) > 64 9 71.5 57.887 20.466 18 186 18 25 60 99 186 186 186 186 Race White 110 1440 242.807 23.151 1 1440 5 25 60 120 412.5 735 960 1080 Race Black 8 46.125 36.314 12.839 10 100 10 15 32.5 82 100 100 100 100 Race Asian 1 40 . . 40 40 40 40 40 40 40 40 40 40 Race Some Others 1 95 . . 9.5 95 95 95 95 95 95 95 95 95 Race Hispanic 3 246.333 366.947 211.86 29 670 29 29 40 670 670 670 670 670 Race Refused 1 35 . . 35 35 35 35 35 35 35 35 35 35 Hispanic No 113 133.673 240 .595 22.633 1 1440 5 20 45 100 270 735 960 1080 Hispanic Yes 9 170 200.709 66.903 29 670 29 41 105 180 670 670 670 670 Hispanic DK 1 85 . . 85 85 85 85 85 85 85 85 85 85 Hispanic Refused 1 35 . . 35 35 35 35 35 35 35 35 35 35 Employment . 18 79.278 63.15 14.885 10 250 10 35 65 95 195 250 250 250 Employment Full Time 79 168.468 286.399 32.222 1 1440 5 20 45 114 670 795 1080 1440 Employment Part Time 6 96 103.894 42.415 2 255 2 5 55 180 255 255 255 255 Employment Not Employed 19 75.105 57.278 13.14 10 186 10 25 75 120 180 186 186 186 Employment Refused 2 20 21.213 15 5 35 5 5 20 35 35 35 35 35 Education . 21 70.333 62.607 13.662 5 250 10 25 60 95 138 195 250 250 Education < High School 10 389 505.656 159.9 5 1440 5 25 45 750 1117.5 1440 1440 1440 Education High School Graduate 48 156.958 257.81 37.212 1 1080 5 19 52.5 130 610 690 1080 1080 Education <College 24 116.25 124.385 25.39 29 600 32 42.5 77.5 120 255 270 600 600 Education College Graduate 10 53 53.24 16.836 10 180 10 15 30 90 135 180 180 180 Education Post Graduate 11 48.545 55.111 16.617 1 186 1 15 30 78 103 186 186 186 Census Region Northeast 28 119.179 237 .794 44.939 2 1080 5 27.5 45.5 90 180 795 1080 1080 Census Region Midwest 36 189.194 318.577 53.096 1 1440 5 17 45 197.5 600 960 1440 1440 Census Region South 42 100.595 151.868 23.434 1 750 5 22 55 114 186 205 750 750 Census Region West 18 132.333 194.344 45.807 10 67Q. 10 35 67.5 105 610 670 670 670 Day Of Week Weekday 82 134.793 197.96 21.861 1 795 5 25 60 120 555 670 750 795 Day Of Week Weekend 42 135.762 298.573 46.071 1 1440 5 18 45 75 250 960 1440 1440 Season Winter 36 126.444 219.584 36.597 5 1080 10. 26 53 92.5 270 670 1080 1080 Season Spring 29 199.793 350.125 65.017 1 1440 5 15 35 180 795 960 1440 1440 Season Summer 38 87.447 125.316 20.329 2 750 5 32 60 95 195 255 750 750 Season Fall 21 146.952 213.871 46.67 1 735 15 30 74 120 600 600 735 735 Asthma No 116 133.69 238.543 22.148 1 1440 5 21 48 104 270 735 960 1080 Asthma Yes 7 210.169 79.436 32 610 32 35 60 250 610 610 610 610 Asthma DK 1 35 . . 35 35 35 35 35 35 35 35 35 35 Angina No 120 138.725 238.702 21.79 1 1440 5 25 60 112 412.5 712.5 960 1080 Angina Yes 3 24.333 13.65 7.881 15 40 15 15 18 40 40 40 40 40 Angina DK 1 35 . . 35 35 35 35 35 35 35 35 35 35 Bronchitis/Emphysema No 116 135.612 242.76 22.54 1 1440 5 23.5 45 101.5 555 735 960 1080 Bronchitis/Emphysema Yes 7 141.286 83.38 31.515 18 250 18 60 180 195 250 250 250 250 Bronchitis/Emphysema DK 1 35 . . 35 35 35 35 35 35 35 35 35 35 Note: A "*" Signifies missing data. "DK"= The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Std err= standard error. Min = minimum number of minutes. Max = maximum number of minute*s. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsann and Kleoeis 1996. Table 15-125. Statistics for 24-Hour Cumulative Number of Minutes Soent Travelina on a Bus Percentiles Cateaorv Pooulation Grouo N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 469 74.648 93.532 4.3189 2 945 10 30 55 90 125 180 435 570 Gender Male 219 77.251 104.119 7.0357 5 945 10 30 55 90 135 180 460 570 Gender Female 250 72.368 83.306 5.2688 2 640 15 30 55 90 120 175 420 501 Age (years) . 14 145 167.177 44.68 10 605 10 60 100 140 435 605 605 605 Age (years) 1-4 5 56 40.218 17.986 15 120 15 30 55 60 120 120 120 120 Age (years) 5-11 133 48.383 29.431 2.552 5 140 10 25 43 67 90 110 120 122 Age (years) 12-17 143 59.413 46.343 3.8754 7 370 10 30 54 75 110 135 179 225 Age (years) 18-64 147 96.639 128.354 10.587 2 945 10 30 60 110 180 405 640 690 Age (years) > 64 27 131.963 144.641 27.836 10 570 20 45 73 130 435 460 570 570 Race White 311 70.071 89.462 5.0729 2 945 10 30 54 80 120 147 405 501 Race Black 101 85.178 92.396 9.1937 5 570 15 35 60 110 140 185 460 468 Race Asian 15 58 58.487 15.101 5 175 5 20 20 120 155 175 175 175 Race Some Others 14 107.143 176.48 47.166 20 690 20 30 42.5 100 225 690 690 690 Race Hispanic 24 65.542 71.515 14.598 15 370 20 30 42.5 87 90 120 370 370 Race Refused 4 168 196.195 98.098 10 435 10 21 113.5 315 435 435 435 435 Hispanic No 415 72.839 86.077 4.2253 2 9.45 10 30 55 90 125 165 420 468 Hispanic Yes 46 83.913 138.922 20.483 7 690 15 . 30 37.5 85 145 370 690 690 Hispanic DK 2 47.5 10.607 7.5 40 55 40 40 47.5 55 55 55 55 55 Hispanic Refused 6 137.833 159.631 65.169 10 435 10 32 77.5 195 435 435 435 435 Employment . 274 54.018 39.364 2.3781 5 370 10 29 49.5 70 100 120 150 179 Employment Full Time 95 122.579 168.8 17.319 5 945 10 30 60 120 405 570 690 945 Employment Part Time 34 83.265 79.298 13.6 2 468 10 40 60 100 135 185 468 468 Employment Not Employed 61 80.262 69.212 8.8617 5 460 10 30 65 120 135 165 205 460 Employment Refused 5 167.4 169.916 75.989 10 435 10 32 165 195 435 435 435 435 Education . 295 55.302 44.964 2.6179 5 435 10 29 49 70 100 120 155 225 Education < High School 25 120.4 124.272 24.854 10 570 30 45 90 135 195 405 570 570 Education High School Graduate 57 111.579 116.718 15.46 10 501 20* 45 73 120 225 435 468 501 Education <College 38 108.842 133.431 21.645 10 640 20 40 75 120 195 605 640 640 Education College Graduate 30 84.633 128.087 23.385 2 690 5 30 60 90 130 300 690 690 Education Post Graduate 24 110.458 199.236 40.669 5 945 10 29 60 101.5 125 460 945 945 Census Region Northeast 145 77.062 75.41 6.2624 7 435 15 30 60 95 135 180 435 435 Census Region Midwest 102 69.676 103.283 10.227 2 945 10 30 55 85 120 125 175 468 Census Region South 142 71.718 82.846 6.9523 5 570 10 30 50 80 135 180 460 501 Census Region West 80 81.813 124.342 13.902 5 690 12.5 30 41.5 90 127.5 297.5 640 690 Day Of Week Weekday 426 70.61 84.646 4.1011 2 690 10 30 50 85 120 165 435 501 Day Of Week Weekend 43 114.651 152.229 23.215 10 945 20 45 90 120 180 300 945 94!\ Season Winter 158 78.285 98.116 7.8057 5 690 10 30 58 90 125 180 435 605 Season Spring 140 61.636 53.541 . 4.525 2 460 10 30 50 75 120 137.5 205 225 Season Summer 94 86.617 116.695 12.036 5 945 10 30 60 95 155 225 435 945 Season Fall 77 76.234 107.505 12.251 5 640 10 30 50 80 125 175 570 640 Asthma No 413 76.448 96. 792 4. 7628 2 945 10 30 55 90 125 180 435 570 Asthma Yes 50 55.36 39.329 5.562 5 195 10 30 47.5 71 115 135 165 195 Asthma DK 6 111.5 65.924 10 435 10 32 46 100 435 435 435 435 Angina No 459 73.373 91.312 4.2621 2 945 10 *30 55 90 125 179 420 570 Angina Yes 4 168. 75 182.683 91.341 20 435 20 60 110 277.5 435 435 435 435 Angina DK 6 109.q 162.362 66.284 10 435 10 30 41 100 435 435 435 435 Bronchitis/Emphysema No 442 74.814 94.281 4.4845 2 945 10 30 55 90 125 180 435 570 Bronchitis/Emphysema Yes 19 58.158 39.881 9.1493 10 155 10 30 55 65 125 155 155 155 Bronchitis/Emphysema DK 8 104.625 137.907 48.757 10 435 10 28.5 67.5 100 435 435 435 435 Note: A ..... Signifies missing data. "DK" =The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Stderr = standard error. Min = minimum number of minutes. Max= maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleneis 1996. Table 15-126. Statistics for 24-Hour Cumulative Number of Minutes Scent Walkinn Percentiles Cateaorv Poculation Graue N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 1639 29.6718 41.617 1.028 1 540 2 6 16 39 65 95 151 190 Gender Male 755 32.4781 48.2611 1.7564 1 540 2 7 20 40 70 100 170 270 Gender Female 883 27.2831 34.8259 1.172 1 360 2 6 15 35 60 94 140 171 Gender Refused 1 20 . . 20 20 20 20 20 20 20 20 20 20 Age (years) . 38 29.5263 23.7416 3.8514 1 100 2 10 25 40 60 80 100 100 Age (years) 1-4 58 24.3276 26.3268 3.4569 1 160 2 10 15 35 60 60 70 160 Age (years) 5-11 155 18.2129 21.0263 1.6889 1 170 1 5 10 25 40 60 65 100 Age (years) 12-17 223 25.8341 32.3753 2.168 1 190 2 6 15 30 60 100 135 151 Age (years) 18-64 944 31.8252 44.9705 1.4637 1 410 2 6 18.5 40 70 110 171 250 Age (years) > 64 221 33.81 49.3278 3.3181 1 540 2 10 20 45 73 95 155 180 Race White 1289 29.5912 43.6801 1.2166 1 540 2 6 15 35 65 100 160 225 Race Black 175 34.8114 39.7274 3.0031 1 250 2 10 20 50 75 125 160 194 Race Asian 36 26.5556 24.6535 4.1089 1 100 1 10 20 30 60 78 100 100 Race Some Others 30 23.7667 21.2192 3.8741 1 60 1 6 17 43 60 60 60 60 Race Hispanic 88 23.0795 21.1058 2.2499 1 100 2 5.5 15 37 50 60 92 100 Race Refused 21 33.1905 32.9555 7.1915 4 150 8 15 20 40 65 65 150 150 Hispanic No 1467 29.8118 41.0288 1.0712 1 410 2 6 16 40 65 100 155 194 Hispanic Yes 144 26.8403 48.7064 4.0589 1 540 2 5.5 15 35 60 70 100 135 Hispanic DK 10 30.2 28.8359 9.1187 2 80 2 10 17.5 55 77.5 80 80 80 Hispanic Refused 18 35.7222 34.7847 8.1988 8 150 8 15 25 55 65 150 150 150 Employment . 431 22.768 28.0141 1.3494 1 190 2 5 13 30 55 65 131 151 Employment Full Time 561 30.9519 43.7734 1.8481 1 365 2 7 16 40 70 100 180 250 Employment Part Time 153 26.8693 37.1231 3.0012 1 295 2 5 15 35 60 92 135 165 Employment Not Employed 482 35.5249 49.4109 2.2506 1 540 2 10 20 50 75 120 150 250 Employment Refused 12 18.4167 13.4601 3.8856 5 55 5 10 16.5 20 30 55 55 55 Education . 472 22.6737 27.6375 1.2721 1 190 2 5 13 30 55 65 130 151 Education < High School 138 42.7174 71.9429 6.1242 1 540 3 7 20 50 115 145 360 365 Education High School Graduate 366 29.2596 41.5618 2.1725 1 410 2 5 18 35 65 100 150 240 Education <College 288 32.5313 39.3063 2.3161 1 295 2 9.5 20 45 75 100 160 180 Education College Graduate 210 29.7667 38.813 2.6784 1 300 2 8 18.5 40 60 90 140 225 Education Post Graduate 165 34.5818 44.6107 3.4729 1 360 2 10 20 45 80 95 180 200 Census Region Northeast 507 34.9172 45.2549 2.0098 1 365 2 10 20 45 75 107 170 250 Census Region Midwest 321 29.271 46.8743 2.6163 1 540 2 6 15 31 60 105 160 180 Census Region South 423 24.9976 37.6654 1.8314 1 410 2 5 10 30 60 80 135 171 Census Region West 388 28.2448 35.029 1.7783 1 285 2 8 15 40 60 90 140 180 Day Of Week Weekday 1182 29.2902 39.1911 1.1399 1 540 2 7 18 40 65 92 145 180 Day Of Week Weekend 457 30.6586 47.3511 2.215 1 410 2 5 15 35 60 120 171 200 Season *Winter 412 32.3034 47.7062 2.3503 1 365 2 6 20 38.5 75 120 180 250 Season Spring 459 28.854 41.54 1.9389 1 540 2 6 16 35 60 90 146 180 Season Summer 475 26.6084 31.325 1.4373 1 270 2 6 15 35 60 85 123 160 Season Fall 293 32.2184 46.6936 2.7279 1 410 2 8 20 45 61 105 155 295 Asthma No 1504 29.6011 41.9939 1.0828 1 540 2 6 16 35.5 65 95 152 190 Asthma Yes 120 29.7417 38.3451 3.5004 1 250 2 5 15 40 70 117.5 135 150 Asthma DK 15 36.2 27.8162 7.1821 5 90 5 10 30 60 75 90 90 90 Angina No 1578 29.5076 41.4718 1.044 1 540 2 6 16 38 65 95 151 190 Angina Yes 44 29 36.0633 5.4367 2 150 4 6 14.5 36 60 115 150 150 Angina DK 17 46.6471 63.1456 15.3151 5 270 5 10 30 60 90 270 270 270 Bronchitis/Emphysema No 1553 29.7173 42.1023 1.0684 1 540 2 6 16 38 65 95 151 194 Bronchitis/Emphysema Yes 67 26.9851 31.8774 3.8944 1 165 2 5 16 40 60 90 130 165 Bronchitis/Emphysema DK 19 35.4211 31.3658 7.1958 3 11.0 3 10 30 '60 90 110 110 110 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused= Refused data. N =doer sample size. Mean= Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Stderr =standard error. Min= minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleneis 1996. Table 15-127. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on a Bicycle/Skateboard/Rollerskate Percentiles Group Name Group Code N Mean Stdev Std err Min Max 5 25 50 75 *90 95 98 99 All 115 45.1217 53.35 4.9749 1 400 5 11 30 60 102 151 195 205 Gender Male 82 43.2073 56.113 6.1966 1 400 5 10 27.5 50 90 120 195 400 Gender Female 33 49.8788 46.228 8.0472 5 205 5 15 45 60 105 165 205 205 Age (years) . 2 15 7.071 5 10 20 10 10 15 20 20 20 20 20 Age (years) 1-4 2 20 14.142 10 10 30 10 10 20 30 30 30 30 30 Age (years) 5-11 18 40.2778 52.985 12.4886 1 195 1 10 15 55 151 195 195 195 Age (years) 12-17 33 31.9697 27.929 4.8618 2 115 5 10 25 45 65 102 115 115 Age (years) 18-64 53 53.2264 62.916 8.6422 5 400 5 20 30 65 105 165 180 400 Age (years) > 64 7 74 67.295 25.4353 23 205 23 25 35 110 205 205 205 205 Race White 98 46.7245 56.914 5.7492 1 400 5 11 30 60 110 165 205 400 Race Black 7 41.1429 21.737 8.2156 5 65 5 25 50 60 65 65 65 65 Race Asian 2 6 1.414 1 5 7 5 5 6 7 . 7 7 7 7 Race Some Others 4 47.5 23.629 11.8145 30 80 30 30 40 65 80 80 80 80 Race Hispanic 3 33.3333 25.166 14.5297 10 60 10 10 30 60 60 60 60 60 Race Refused 1 20 . . 20 20 20 20 20 20 20 20 20 20 Hispanic .No 106 45.8679 55.172 5.3587 1 400 5 10 30 60 105 151 195 205 Hispanic Yes 8 38.375 23.323 8.2461 10 80 10 23.5 30 55 80 80 80 80 Hispanic Refused 1 20 . . 20 20 20 20 20 20 20 20 20 20 Employment . 52 33.8462 38.258 5.3054 1 195 2 10 20 47.5 65 115 151 195 Employment Full Time 27 56.8519 76.863 14.7923 5 400 5 15 30 60 115 120 400 400 Employment Part Time 7 40.8571 24.768 9.3616 10 90 10 30 35 46 90 90 90 90 Employment Not Employed 27 55.4815 54.258 10.442 5 *205 5 20 30 90 165 180 205 205 Employment Refused 2 55 49.497 35 20 90 20 20 55 90 90 90 90 90 Education . 56 33.3929 36.945 4.937 1 195 2 10 20 45 65 115 151 195 Education < High School 3 98.3333 77.835 44.9382 25 180 25 25 90 180 180 180 180 180 Education High School Graduate 18 41.5556 49.048 11.5606 5 205 5 15 30 46 100 205 205 205 Education <College 18 42.9444 35.049 8.261 5 120 5 20 30 60 115 120 120 120 Education College Graduate 11 89.8182 111.308 33.5605 15 400 15 25 53 90 165 400 400 400 Education Post Graduate 9 57.2222 38.415 12.8049 5 110 5 20 60 90 110 110 110 110 Census Region Northeast 20 42.05 35.057 7.839 5 102 5 10 32.5 77.5 95 101 102 102 Census Region Midwest 24 39.125 47.505 9.6969 2 180 5 10 18.5 57.5 90 165 180 180 Census Region South 26 64.6923 87.03 17.0681 1 400 2 15 32.5 75 195 205 400 400 Census Region West 45 38.3778 32.614 4.8619 5 151 5 18 30 50 80 115 151 151 Day Of Week Weekday 83 44.5783 56.02 6.149 5 400. 5 15 30 60 90 151 205 400 Day Of Week Weekend 32 46.5313 46.508 8.2215 1 195 2 10 32.5 75 110 120 195 195 Season Winter 20 38.6 44.951 10.0513 1 205 3.5 12.5 27.5 47.5 75 147.5 205 205 Season Spring 46 34.7826 35.036 5.1657 5 195 5 10 22.5 46 80 90 195 195 Season Summer 34 61.7059 72.243 12.3896 2 400 5 20 42.5 90 115 165 400 400 Season Fall 15 47.9333 55.663 14.3721 2 180 2 10 20 75 151 180 180 180 Asthma No 95 48.5368 57.246 5.8733 1 400 5 15 30 60 110 165 205 400 Asthma Yes 18 29.3333 24.22 5.7086 5 90 5 7 32.5 40 60 90 90 90 Asthma DK 2 25 7.071 5 20 30 20 20 25 30 30 30 30 30 Angina No 114 45.3421 53.533 5.0138 1 400 5 11 30 60 102 151 195 205 Angina DK 1 20 . . 20 20 20 20 20 20 20 20 20 20 Bronchitis/Emphysema No 109 45.1284 53.909 5.1636 1 400 5 15 30 60 102 151 195 205 Bronchitis/Emphysema Yes 5 50 49.624 22.1923 5 115 5 10 30 90 115 115 115 115 Bronchitis/Emphysema DK 1 20 . . 20 20 20 20 20 20 20 20 20 20 Note: A "'"Signifies missing data. "DK"= The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Stderr =standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996. Table 15-128. Statistics for 24-Hour Cumulative Number of Minutes Scent on a Bus, Train, etc. Stoo Percentiles Cateaorv Pooulation Grouo N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 All 151 18.702 18.7513 1.526 1 128 4 7 15 20 40 45 67 120 Gender Male 61 16.3443 17.9934 2.3038 1 120 4 5 11 20 30 . 45 65 120 Gender Female 90 20.3 19.1818 2.02319 1 128 4 10 15 30 42.5 60 75 128 Age (years) . 2 21 5.6569 4 17 25 17 17 21 25 25 25 25 25 Age (years) 1-4 2 8 9.8995 7 1 15 1 1 8 15 . 15 15 15 15 Age (ye?rS) 5-11 32 12.5 10.7283 1.8965 2 45 2 5 10' 15 20 43 45 45 Age (years)
12-17 50 13.78 11.4843 1.6241 1 74 3 5 10 20 23 30 52.5 75 Age (years) 18-64 54 25.5 25.616 3.4859 1 128 5 10 15 30 60 6.7 120 128 Age (years) > 64 11 27.2727 13.484 4.0656 5 45 5 20 30 40 45 45 45 45 Race White 115 18.2522 17.9501 1.6739 1 128 4 5 15 22 40 45 67 75 Race Black 21 17.4762 11.9901 2.6164 1 45 3 10 15 23 35 40 45 45 Race Asian 3 10 5 2.8868 5 15 5 5 10 15 15 15 15 15 Race Some Others 1 15 . . 15 15 15 15 15 15 15 15 15 15 Race Hispanic 10 29.8 35.8137 11.3253 5 120 5 10 16.5 20 92.5 120 120 120 Race Refused 1 15 . . 15 15 15 15 15 15 15 15 15 15 Hispanic No 136 18.0956 17.1036 1.4666 1 128 4 6 15 22.5 40 45 67 75 Hispanic Yes 13 25.2308 32.4427 8.998 1 120 1 10 15 20 65 120 120 120 Hispanic DK 1 20 . . . 20 20 20 20 20 20 20 20 20 20 Hispanic Refused 1 15 . . 15 15 15 15 15 15 15 15 15 15 Employment . 79 13.1646 11.3707 1.2793 1 75 2 5 10 15 23 35 45 75 Employment Full Time 31 24.9355 24.8125 4.4565 1 128 5 10 15 30 45 65 128 128 Employment Part Time 15 31.6667 31.5179 8.1379 5 120 5 10 17 45 67 120 120 120 Employment Not Employed 26 20.6154 12.7061 2.4919 5 45 5 10 20 30 40 45 45 45 Education . 87 12.931 10.9723 1.1763 1 75 3 5 10 15 23 30 45 75 Education < High School 6 32.5 11.726 4.7871 15 45 15 25 32.5 45 45 45 45 45 Education. High School Graduate 25 23.56 24.5749 4.915 5 120 5 10 15 30 45 67 120 120 Education <College 9 28.333 19.2029 6.401 10 60 10 10 20 45 60 60 60 60 Education College Graduate 16 33.8125 31.1239 7.781 5 128 5 10 30 37.5 65 128 128 128 Education Post Graduate 8 14.875 8.3741 2.9607 1 30 1 40.5 15 18.5 30 30 30 30 Census Region Northeast 63 20.4921 23.43 2.9519 1 128 3 6 15 22 40 65 120 128 Census Region Midwest 27 17.4074 13.1244 2.5258 3 60 4 5 15 20 35 35 60 60 Census Region South 39 19.8205 16.6684 2 .. 6691 4 75 5 10 15 28 45 65 75 75 Census Region West 22 13.1818 11.3458 2.4189 1 45 1 5 10 15 30 30 45 45 Day Of Week Weekday 128 17.7891 18.9656 1.6763 1 128 3 5.5 15 20 35 45 75 120 Day Of Week Weekend 23 23.7826 17.0026 3.5453 5 65 5 10 20 35 45 60 65 65 Season Winter 55 19.9273 15.5693 2.0994 1 75 2 10 15 25 . 43 60 65 75 Season Spring 43 17.186 20.6574 3.1502 1 120 4 5 10 20 33 45 120 120 Season Summer 28 24 25.4675 4.8129 5 128 5 10 15 32.5 45 67 128 128 Season Fall 25 12.68 9.8815 1.9763 1 45 4 5 10 15 20 35 45 45 Asthma No 139 18.7698 18.7788 1.5928 1 128 3 10 15 20 40 45 75 120 Asthma Yes 10 20 20.5372 6.4944 4 65 4 5 12 30 55 65 65 65 Asthma DK 2 7.5 3.5355 2.5 5 10 5 5 7.5 10 10 10 10 10 Angina No 151 18.702 18.7513 1.526 1 128 4 7 15 20 40 45 67 120 Bronchitis/Emphysema No 145 18.6552 18.969 1.5753 1 128 4 6 15 20 40 45 75 120 Bronchitis/Emphysema Yes 6 19.8333 13.5561 5.5342 9 45 9 10 16 23 45 45 45 45 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Stderr =standard error. Min= minimum number of minutes. Max= maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleneis 1996.
Table 15-129. Statistics for 24-Hour Cumulative Number of Minutes Spent Travelin!'.l on a Train/Subway/Rapid Transit Percentiles Group Name Group Code N Mean Stdev Std err Mi tylax 5 25 50 75 90 95 98 99 n All 116 97.767 136.346 12.659 1 810 5 27.5 60 120 189 415 690 720 Gender Male 62 91.613 119.437 15.168 5 720 10 24 60 120 180 240 480 720 Gender Female 54 104.833 154.349 21.004 1 810 2 30 60 120 195 480 690 810 Age (years) . 8 191.875 256.82 90.8 20 810 20 55 117.5 180 810 810 810 810 Age (years) 1-4 2 92.5 38.891 27.5 65 120 65 65 92.5 120 120 120 120 120 Age (years) 5-11 3 166.667 271.401 156.693 5 480 5 5 15 480 480 480 480 480 Age (years) 12-17 2 100 56.569 40 60 140 60 60 100 140 140 140 140 140 Age (years) 18-64 92 84.967 106.533 11.107 1 720 5 30 60 104.5 175 240 480 720 Age (years) > 64 9 122.667 219.531 73.177 10 690 10 10 24 120 690 690 690 690 Race White 64 89.5 139.691 17.461 1 720 5 22 55 74 195 380 690 720 Race Black 26 131.385 168.356 33.017 5 810 10 35 117.5 135 195 480 810 810 Race Asian 3 79.667 17.039 9.838 60 90 60 60 89 90 90 90 90 90 Race Some Others 4 71.25 47.675 23.838 30 140 30 42.5 57.5 100 140 140 140 140 Race Hispanic 16 88.625 98.922 24.731 5 415 5 20 70 112.5 165 415 415 415 Race Refused 3 85 56.347 32.532 20 120 20 20 115 120 120 120 120 120 Hispanic No 89 101.281 149.687 15.867 1 810 5 25 60 120 195 480 720 810 Hispanic Yes 22 86.955 85.561 18.242 5 415 10 40 70 120 130 165 415 415 Hispanic DK 2 79.5 34.648 24.5 55 104 55 55 79.5 104 104 104 104 104 Hispanic Refused 3 85 56.347 32.532 20 120 20 20 115 120 120 120 120 120 Employment . 7 126.429 163.598 61.834 5 480 5 15 65 140 480 480 480 480 Employment Full Time 76 98.526 128.056 14.689 1 720 5 30 60 120 189 380 690 720 Employment Part Time 10 61.7 46.375 14.665 5 160 5 15 57.5 89 125 160 160 160 Employment Not Employed 21 101.714 186.201 40.632 1 810 10 10 55 90 165 415 810 810 Employment Refused 2 107.5 123.744 87.5 20 195 20 20 107.5 195 195 195 195 195 Education . 10 122 140.024 44.279 5 480 5 20 92.5 140 337.5 480 480 480 Education < High School 6 181.833 311.76 127.275 1 810 1 5 70 135 810 810 810 810 Education High School Graduate 30 89.433 109.191 19.935 1 480 2 30 60 120 177.5 415 480 480 Education <College 26 125.692 189.64 37.192 10 720 10 20 60 120 380 690 720 720 Education College Graduate 24 66.5 50.332 10.274 5 180 10 24.5 55 102.5 125 175 180 180 Education Post Graduate 20 74.15 59.415 13.286 10 240 12.5 30 60 97 164.5 214.5 240 240 Census Region Northeast 72 111.847 134.554 15.857 10 810 20 49 62.5 122.5 189 415 690 810 Census Region Midwest 14 64.214 109.483 29.261 2 380 2 10 22.5 50 240 380 380 380 Census Region South 15 75.733 121.139 31.278 1 480 1 10 30 90 160 480 480 480 Census Region West 15 83.533 179.444 46.332 5 720 5 10 30 75 120 720 720 720 Day Of Week Weekday 96 101.604 127.189 12.981 1 720 10 30 60 120 195 415 690 720 Day Of Week Weekend 20 79.35 176.643 39.499 2 810 3.5 7.5 32.5 60 120 465 810 810 Season Winter 26 138.192 196.327 38.503 . 5 810 10 30 79.5 130 240 720 810 810 Season Spring 29 77.276 89.479 16.616 2 480 5 25 60 105 135 175 480 480 Season Summer 37 106.081 140.735 23.137 5 690 10 30 60 120 195 480 690 690 Season Fall 24 65.917 82.217 16.782 1 380 1 15 42.5 82.5 160 180 380 380 Asthma No 106 94.151 122.865 11.934 1 720 5 30 60 120 180 380 *480 690 Asthma Yes 7 146.571 294.036 111.135 1 810 1 10 30 90 810 810 810 810 Asthma DK 3 111.667 87.797 50.69 20 195 20 20 120 195 195 195 195 195 Angina No 112 96.527 137.946 13.035 1 810 5 27.5 60 117.5 175 415 690 720 Angina DK 4 132.5 82.916 41.458 20 195 20 70 157.5 195 195 195 195 195 Bronchitis/Emphysema No 112 98.179 138.009 13.041 1 810 5 30 60 120 180 415 690 720 Bronchitis/Emphysema Yes 1 10 * . 10 10 10 10 10 10 10 10 10 10 Bronchitis/Emphysema DK 3 111.667 87.797 50.69 20 195 20 20 120 195 195 195 195 195 Note: A ..... Signifies missing data. "DK"= The respondent replied "don't know". Refused= Refused data. N =doer sample size. Mean= Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Std err= standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsann and Kleneis 1996. Table 15-130. Statisti.cs for 24-Hour Cumulative Number of Minutes Spent Travelinq on an Airplane Group Name All Gender Gender Age (years) Age (years) Age (years) Age _(years) Race Race Race Race Hispanic Hispanic Employment Employment Employment Employment Employment Education Education Education Education Education Education Census Region Census Region Census Region Census Region Day Of Week Day Of Week Season Season Season Season Asthma Asthma Angina Angina Grouo Code Male Female 12-17 18-64 > 64 White Black Asian Hispanic No Yes Full Time Part Time Not Employed Refused < High School High School Graduate <College College Graduate Post Graduate Northeast Midwest South West Weekday Weekend Winter Spring Summer Fall No Yes No Yes No Bronchitis/Emohvsema Yes N 53 28 25 3 Mean Stdev 234 203.736 241.25 230.979 225.88 172.581 175 145.688 Std err 27.985 43.651 34.516 84.113 3 113.333 118.568 68.455 42 226.429 193.962 29.929 5 405.4 292;392 130.762 44 241.068 215.555 32.496 7 199.286 134.364 50.785 60 340 51 234.745 206.224 2 215 176.777 3 113.333 118.568 33 212.424 194.008 28.877 125 68.455 33.773 3 510 375.899 217.025 13 259.385 168.387 46.702 1 150 *
4 122.5 98.531 49.265 4 111.25 179.647 89.823 9 253.889 191.046 63.682 13 293.846 170.784 47.367 15 194.8 113.998 29.434 8 305 375.129 132.628 17 254.706 234.81 56.95 17 235.118 234.348 56.838 9 212. 778 103.565 34.522 10 216 181.702 57.459 37 258.919 192.755 16 176.375 222.825 17 216.294 172.818 14 191.786 160.547 31.689 55.706 41.914 42.908 17 230.882 222.171 53.884 5 423 294.398 131.659 51 224.843 201.484 28.213 2 467.5 123.744 87.5 51 233. 725 207.562 2 241 65.054 51 231.608 206.7 2 295 120.208 29.064 46 28.944 85 Percentiles Min Max 5 25 50 75 90 95 98 99 10 900 15 20 15 15 70 65 110 15 210 300 210 292.5 480 660 900 900 555 900 900 900 480 510 660 660 300 300 300 300 15 900 10 660 210 300 15 300 210 300 15 10 195 10 15 60 340 10 90 15 15 150 10 150 15 10 15 20 45 20 15 15 15 10 15 10 20 15 10 180 10 380 10 195 10 210 245 15 15 80 60 202.5 245 245 245 245 245 900 20 300 480 555 900 900 900 195 210 900 15 65 435 15 110 60 60 60 340 340 340 900 15 60 340 90 90 245 15 15 900 20 60 900 150 150 660 10 195 150 150 150 245 15 47.5 380 10 12.5 287 435 210 300 210 255 60 60 340 . 340 210 300 215 340 80 245 180 285 480 900 225 300 150 150 115 197.5 27.5 210 660 15 195 270 285 .555 20 180 300 435 480 45 90 210 255 900 20 45 137 .5 577.5 900 15 70 245 380 900 15 60 195 287 900 900 900 900 510 660 900 900 435 435 435 435 60 60 60 60 340 340 340 340 480 660 900 900 340 340 340 340 245 245 245 245 480 555 900 900 900 900 900 900 435 660 660 660 150 150 150 150 245 245 245 245 380 380 380 380 660 660 660 660 510 555 555 555 287 480 480 480 900 900 900 900 510 900 900 900 660 900 900 900 340 15 150 255 270 340 340 340 340 555 10 45 202.5 240 517.5 *555 .555. 555 900 15 150 230 305 510 660 900 900 900 10 37 .5 95 262.5 360 900 900 900 660 20 60 210 275 480 . 660 660 660 555 15 90 150 230 435 555 555 555 900 10 60 245 300 480 900 900 900 900 180 240 285 510 900 900 900 900 900 15 60 210 287 480 660 900 900 555 380 380 467 .5 555 555 555 555 555 900 15 60 210 300 480 660 900 900 287 195 195 241 287 287 287 287 287 900 15 60 210 300" 480 660 900 900 380 210 210 295 380 380 380 380 380 Note: A"*" Signifies missing data. Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min = minimum number of minutes. Max= maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleneis 1996.
Table 15-131. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors in a Residence (all rooms) Percentiles Category Population Group N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 All 9343 1001.39 275.143 2.8465 8 1440 575 795 985 1235 1395 1440 1440 1440 Gender Male 4269 945.9 273.498 4.1859 8 1440 540 750 900 1160 1350 1430 1440 1440 Gender Female 5070 1048.07 267.864 3.7619 30 1440 620 840 1050 1280 1420 1440 1440 1440 Gender Refused 4 1060 135.647 67.8233 900 1200 900 950 1070 1170 1200 1200 1200 1200 Age (years) . 187 1001.07 279.866 20.4658 265 1440 565 799 955 1230 1440 1440 1440 1440 Age (years) 1-4 498 1211.64 218.745 9.8022 270 1440 795 1065 1260 1410 1440 1440 1440 1440 Age (years) 5-11 700 1005.13 222.335 8.4035 190 1440 686 845 975 1165 1334 1412.5 1440 1440 Age (years) 12-17 588 969.5 241.776 9.9707 95 1440 585 811.5 950 1155 1310 1405 1440 1440 Age (years) 18-64 6022 947.91 273.033 3.5184 8 1440 540 750 900 1165 1350 1428 1440 1440 Age (years) > 64 1348 1174.64 229.344 6.2466 60 1440 760 1030 1210 1375 1440 1440 1440 1440 Race White 7556 999.36 275.678 3.1714 8 1440 570 795 980 1235 1395 1440 1440 1440 Race Black 941 1015.95 . 272.54 8.8845 190 1440 600 815 1000 1245 1410 1440 1440 1440 Race Asian 157 983.52 254.689 20.3264 30 1440 600 810 930 1180 1355 1420 1440 1440 Race Some Others 181 996.09 268.283 19.9413 10 1440 604 805 975 1198 1380 1440 1440 1440 Race Hispanic 382 1009.4 281.75 14.4156 55 1440 555 810 1004.5 125Q 1410 1440 1440 1440 Race Refused 126 1019.69 276.578 24.6396 270 1440 575 840 975 1255 1440 1440 1440 1440 Hispanic No 8498 1000.38 275.436 2.9879 8 1440 575 795 980 1235 1395 1440 1440 1440 Hispanic Yes 696 1009.84 270.816 10.2653 55 1440 585 810 1000 1230 1405 1440 1440 1440 Hispanic DK 46 1097.87 286.655 42.265 401 1440 645 835 1172.5 1355 1440 1440 1440 1440 Hispanic Refused 103 984.08 269.485 26.5531 270 1440 565 810 950 1200 1375 1440 1440 1440 Employment . 1768 1053.3 248.46 5.909 95 1440 675 870 1030 1255 1413 1440 1440 1440 Employment Full Time 4068 881.03 259.166 4.0634 8 1440 515 715 835 1045.5 1290 1385 1440 1440 Employment Part Time 797 982.44 243.085 8.6105 255 1440 600 820 970 1170 1320 1380 1440 1440 Employment Not Employed 2639 1158.03 233.775 4.5507 60 1440 735 1015 1190 1350 1440 1440 1440 1440 Employment Refused 71 995.08 268.059 31.8128 445 1440 575 810 940 1255 1440 1440 1440 1440 Education . 1963 1044.47 251.888 5.6852 95 1440 660 855 1020 1254 1410 1440 1440 1440 Education < High School 829 1093.37 278.592 9.6759 150 1440 630 870 1130 1345 1440 1440 1440 1440 Education High School Graduate 2602 1008.1 279.281 5.4751 30 1440 565 803 995 1245 1400 1440 1440 1440 Education <College 1788 974.34 272.599 6.4468 10 1440 570 775 930 1205 1371 1436 1440 1440 Education College Graduate 1240 939.49 275.004 7.8096 30 1440 528 745 885 1165 1335 1427.5 1440 1440 Education Post Graduate 921 943.67 274.27 9.0375 8 1440 540 750 900 1155 1350 1410 1440 1440 Census Region Northeast 2068 1003.4 278.441 6.1229 30 1440 570 795 980 1245 1405 1440 1440 1440 Census Region Midwest 2087 1001.73 280.646 6.1432 8 1440 565 790 989 1250 1390 1440 1440 1440 Census Region South 3230 999 270.19 4.7541 10 1440 585 800 970 1228 1'100 1440 1440 1440 Census Region West 1958 1002.84 273.992 6.192 30 1440 575 800 1000 1230 1390 1440 1440 1440 Day Of Week Weekday 6286 965.69 272.596 3.4382 30 1440 567 770 911 1190 1380 1440 1440 1440 Day Of Week Weekend 3057 1074.81 265.676 4.8051 8 1440 615 895 1105 1290 1420 1440 1440 1440 Season Winter 2513 1034.92 278.237 5.5503 30 1440 590 825 1015 1285 1432 1440 1440 1440 Season Spring 2424 977.88 267.177 5.4267 10 1440 580 780 955 1185 1370 1435 1440 1440 Season Summer 2522 980.52 273.962 5.4553 8 1440 555 785 960 1201 1365 1440 1440 1440 Season Fall . 1884 1014.84 277.47 6.3926 30 1440 589 805 997 1260 1405 1440 1440 1440 Asthma No 8591 999.12 274.377 2.9602 8 1440 576 795 980 1230 .1393 1440 1440 1440 Asthma Yes 689 1027.42 284.437 10.8362 190 1440 555 825 1025 1260 1430 1440 1440 1440 Asthma DK 63 1025.68 264.342 33.3039 445 1440 630 840 960 1315 1410 1440 1440 1440 Angina No 9019 997.77 274.112 2.8863 8 1440 575 795 975 1230 1391 1440 1440 1440 Angina Yes 249 1125.47 281.353 17.83 180 1440 660 925 1185 1380 1440 1440 1440 1440 Angina DK 75 1024.08 285.059 32.9158 150 1440 560 840 975 1305 1425 1440 1440 Bronchitis/Emphysema No 8840 997.66 274.78 2.9225 8 1440 575 795 975 1230 1395 1440 1440 1440 Bronchitis/Emphysema Yes 432 1070.48 273.759 13.1712 205 1440 585 867.5 1110 1292.5 1440 1440 1440 1440 Bronchitis/Emphysema DK 71 1045.48 273.047 32.4047 445 1440 565 845 975 1320 1440 1440 1440 1440 Note: A "*"Signifies missinfe data. "DK"= The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of mi nu es for doers. Stdev = standard deviation. Stderr =standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Klepeis 1996. Table 15-132. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors (outside the residence) Percentiles Group Name Group Code N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 All 3124 154.03 158.302 2.8322 1 1290 5 40 105 210 362 480 610 715 Gender Male 1533 174.908 173.671 4.4356 1 1290 1.0 60 120 240 420 540 680 745 Gender Female 1588 133.524 138.801 3.4831 1 1065 5 30 90 190 325 415 525 610 Gender Refused 3 340 140 80.829 240 500 240 240 280 500 500 500 500 500 Age (years) . 40 163.95 179.615 28.3996 2 720 3.5 40 107.5 212.5 430 600 720 720 Age (years) 1-4 201 195.652 163.732 11.5488 3 715 30 75 135 270 430 535 625 699 Age (years) 5-11 353 187.564 158.575 8.4401 4 1250 20 80 150 265 365 479 600 720 Age (years) 12-17 219 135.26 137.031 9.2597 1 720 5 35 100 190 300 452 545 610 Age (years) 18-64 1809 144.244 155.13 3.6473 1 1080 5 30 90 199 360 470 600 715 Age (years) > 64 502 156.448 168.259 7.5098 1 1290 5 36 110 210 375 485 645 735 Race White 2622 156.787 160.173 3.1281 1 1290 5 45 105 215 375 485 625 720 Race Black 255 141.557 153.169 9.5918 1 1250 5 30 95 195 330 420 535 645 Race Asian 34 115.765 135.554 23.2474 1 480 5 20 60 150 360 450 480 480 Race Some Others 53 167 149.049 20.4735 3 750 5 60 130 238 320 475 553 750 Race Hispanic 125 117.28 128.886 11.5279 1 720 5 30 70 150 270 355 590 610 Race Refused 35 187.143 163.771 27.6824 5 600 5 60 170 240 450 510 600 600 Hispanic No 2857 153.812 158.38 2.9631 1 1290 5 40 105 210 362 480 610 720 Hispanic
Yes 222 146.405 154.069 10.3405 1 750 5 30 112.5 200 345 480 640 690 Hispanic DK 15 191.533 178.278 46.0312 15 585 . 15 40 140 380 420 585 585 585 Hispanic Refused 30 212.5 165.335 30.186 5 600 5 60 180 345 457.5 510 600 600 Employment . 774 175.762 156.127 5.6119 1 1250 15 60 125 245 380 480 610 705 Employment Full Time 1110 141.308 159.947 4.8008 1 1080 5 30 85 195 358.5 490 660 745 Employment Part Time 240 134.663 140.78 9.0873 1 1080 5 30 90 182.5 332.5 422.5 485 525 Employment Not Employed 978 156.052 159.151 5.0891 1 1290 5 40 115 220 375 480 610 701 Employment Refused 22 152.727 209.828 44.7355 5 660 5 15 60 125 555 600 660 660 Education . 825 174.105 156.184 5.4376 1 1250 15 60 125 240 38q 480 610 699 Education <High School 306 171.941 188.396 10.7699 1 1290 7 45 120 240 405 510 765 855 Education High School Graduate 837 153.633 .* 154. 781 5.35 1 840 5 35 105 215 380 480 598 701 Education <College 527 143.362 157 .106 6.8436 1 1080 5 30 90 195 360 465 615 720 Education College Graduate 355 126.868 142.575 7.5671 1 750 5 30 80 170 300 415 615 690 Education Post Graduate 274 130.504 150.996 9.122 1 1065 5 30 75 180 325 465 570 660 Census Region Northeast 635 147.967 143.678 5.7017 1 750 5 35 105 215 345 450 575 610 Census Region Midwest 639 156.028 169.151 6.6915 1 1290 5 45 102 210 360 500 655 750 Census Region South 1120 158.577 165.201 4.9363 1 1080 5 40 110 210 390 495 640 745 Census Region West 730 150.579 149.63 5.5381" 1 855 5 36 105 213 360 465 575 660 Day Of Week Weekday 1933 141.157 148.958 3.388 1 1250 5 31 90 190 345 .452 598 698 Day Of Week Weekend 1191 174.924 170.399 4.9375 1 1290 10 50 120 260 400 500 660 745 Season Winter 548 113.96 138.121 5.9002 1 1080 5 25 60 150 280 380 540 690 se*ason Spring 1034 171.915 159.391 4.9568 1 990 10 60 120 240 390 495 645 730 Season Summer 1098 168.309 168.2 5.076 1 1290 5 50 120 235 400 510 630 715 Season Fall 444 126.525 140.747 6.6796 1 960 5 30 75 162.5 313 420 575 655 Asthma. No 2869 154.516 159.172 2.9717 1 1290 5 40 105 210 365 480 615 720 Asthma Yes 236 145.835 145.523 9.4727 1 885 5 45 105 190 360 450 575 610 Asthma DK 19 182.421 181.024 41.5298 1 600 1 60 120 300 480 600 600 600 Angina No 3023 153.218 156.257 2.842 1 1290 5 40 105 210 360 479 610 707 Angina Yes 76 172.855 222.319 25.5017 2 1080 5 30 68.5 252.5 465 660 1065 1080 Angina DK 25 195 170.434 34.0869 5 600 5 60 150 300 465 480 600 600 Bronchitis/Emphysema No 2968 154.884 158.787 2.9146 1 1290 5 40 105 210 367 480 615 715 Bronchitis/Emphysema Yes 139 129.353 142.494 12.0862 1 855 5 30 75 175 327 415 553 735 Bronchitis/Emphysema DK 17 206.765 179.765 43.5994 5 600 5 60 170 300 480 600 600 600 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused= Refused data. N =doer sample size. Mean= Mean 24-hour cumulative number cif minutes for doers. Stdev =standard deviation. Stderr = standard error. Min= minimum number of minutes. Max= maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsanq and Kleoeis, 1996.
Table 15-133. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling Inside a Vehicle Percentiles Category Population Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 7743 97.278 104.938 1.1926 1 1440 12 40 70 120 190 270 425 570 Gender Male 3603 103.696 119.736 1.9948 1 1440 10 40 70 120 205 295 478 655 Gender Female 4138 91.721 89.756 1.3953 1 995 12 40 70 115 180 240 385 465 Gender Refused 2 30 14.142 10 20 40 20 20 30 40 40 40 40 40 Age (years) . 144 117.035 129.103 10.7586 5 810 20 40 80 142.5 210 435 593 660 Age (years) 1-4 335 68.116 75.531 4.1267 1 955 10 30 47 85 150 200 245 270 Age (years) 5-11 571 71.033 77.62 3.2483 1 900 10 25 51 90 140 171 275 360 Age (years) 12-17 500 81.53 79.8 3.5687 1 790 10 30 60 100 165.5 232.5 345 405 Age (years) 18-64 5286 104.011 111.1 1.5281 1 1440 15 43 75 120 200 285 450 620 Age (years) > 64 907 90.87 93.881 3.1173 4 900 10 35 60 120 190 258 400 460 Race White 6288. 97.248 107.173 1.3515 1 1440 10 40 70 120 190 270 425 595 Race Black 766 98.723 91.337 3.3001 2 810 15 45 75 120 195 265 390 485 Race Asian 133 83.414 74.929 6.4972 5* 540 20 35 70 105 150 210 330 360 Race Some Others 144 96.181 93.965 7.8304 3 690 10 40 69.5 127.5 180 250 345 540 Race Hispanic 319 101.734 110.376 6.1799 2 825 20 41 70 120 190 335 465 620 Race Refused 93 93.591 90.073 9.3401 10 480 15 30 65 120 205 255 420 480 Hispanic No 7050 97.149 104.847 1.2487 1 1440 10 40 70 120 190 270 420 566 Hispanic Yes 578 100.043 109.048 4.5358 2 825 15 40 70 120 190 285 480 630 Hispanic DK 34 73 68.279 11.7098 5 325 6 25 60 97 175 200 325 325 Hispanic Refused 81 98.914 95.273 10.5859 10 480 15 30 65 130 220 255 420 480 Employment . 1388 73.609 77.782 2.0878 1 955 10 30 55 90 150 195 275 382 Employment Full Time 3732 105.816 116.18 1.9018 4 1440 16 45 75 124 198 290 475 660 Employment Part Time 720 98.763 94.999 3.5404 2 960 10 45 75 120 195 260 380 470 Employment Not Employed 1849 96.561 99.534 2.3147 1 995 10 37 65 120 200 275 420 526 Employment Refused 54 120.296 108.615 14.7807 10 480 20 35 88 190 290 330 390 480 Education . 1550 76.39 78.923 2.0047 1 955 10 30 60 95 155 201 302.5 385 Education < High School 561 100.822 120.246 5.0768 5 1440 15 40 70 120 180 265 460 620 Education High School Graduate 2166 101.605 107.594 2.3118 1 1210 12 40 70 120 210 286 445 570 Education <College 1556 103.215 110.128 2.7919 2 1280 15 40 75 120 195 285 460 630 Education College Graduate 1108 104.532 109.485 3.2891 4 1215 15 45 75 125 200 280 450 675 Education Post Graduate 802 101.938 108.688 3.8379 4 1357 20 45 75.5 120 195 270 365 480 Census Region Northeast 1662 98.585 106.64 2.6158 1 1215 15 40 70 120 190 275 425 570 Census Region
Midwest 1759 101.229 114.641 2.7334 1 1440 10 40 70 120 205 290 435 595 Census Region South 2704 96.051 97.72 1.8792 1 955 13 40 70 120 190 250 420 558 Census Region West 1618 93.689 103.717 2.5785 2 1280 10 35 65 115 180 260 420 540 Day Of Week Weekday 5289 94.437 101.435 1.3948 1 1215 10 40 66 115 180 260 435 575 Day Of Week Weekend 2454 103.399 111.892 2.2587 1 1440 13 40 75 125 205 280 420 540 Season Winter 2037 94.31 101.375 2.2461 1 1080 10 35 65 116 190 270 425 544 Season Spring 2032 99.612 110.464 2.4505 1 1440 12 40 70 120 200 275 440 546 Season Summer 2090 97.792 103.76 2.2696 1 1357 10 40 70 120 190 260 415 558 Season Fall 1584 97.419 103.714 2.6059 1 1280 14 40 70 . 120 180 265 420 620 Asthma No 7152 97.262 104.554 1.2363 1 1440 10 40 70 120 190 270 425 570 Asthma Yes 544 97.241 110.792 4.7502 4 955 17 40 65 116.5 180 255 460 705 Asthma DK 47 100 95.192 13.8852 10 480 10 30 75 120 220 239 480 480 Angina No 7516 97.288 105.235 1.2139 1 1440 11 40 70 120 190 270 425 570 Angina Yes 172 93.07 93.142 7.102 8 615 15 30 65 120 185 280 420 540 Angina DK 55 108.945 99.695 13.4429 10 480 20 35 75 150 235 360 390 480 Bronchitis/Emphysema No 7349 97.559 106.055 1.2371 1 1440 10 40 70 120 190 270 425 580 Bronchitis/Emphysema Yes 342 90.971 79.287 4.2873 2 505 15 40 70 115 195 240 325 460 Bronchitis/Emphysema DK . 52 98.942 93.767 13.0031 5 480 10 30 73.5 145 195 239 390 480 Note: A '"" Signifies missing data. "DK"= The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Stderr =standard error. Min= minimum number of minutes. Max= maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Klepeis. 1996.
Table 15-134. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors Near a Vehicle Percentiles Cateaorv Pooulation Grouo N Mean Stdev Stderr Min Max 5 25 50 75 90 95 98 99 All 2825 79.828 143.82 2.7059 1 1440 2 10 30 65 200 465 600 67.5 Gender Male 1388 111.21 184.96 4.9645 1 1440 3 11 30.5 90 430 570 675 735 Gender Female 1436 49.541 75.947 2.0042 1 790 2 10 25 60 120 180 290 420 Gender Refused 1 20 . . 20 20 20 20 20 20 20 20 20 20 Age (years) . 51 64.373 90.949 12.7354 1 510 4 20 40 65 125 290 360 510 Age (years) 1-4 102 45.99 59.489 5.8903 1 420 2 10 30 60 105 160 192 245 Age (years) 5-11 230 55.909 86.475 5.702 1 540 2 10 20 . 60 170 215 360 465 Age (years) 12-17 313 40.879 55.718 3.1494 1 435 3 10 21 45 100 160 220 260 Age (years) 18-64 1787 96.365 169.13 4.0009 1 1440 2 10 30 75 325 539 645 720 Age (years) > 64 342 57.55 85.255 4.61 1 560 4 10 30 60 120 205 450 510 Race White 2275 81.787 148.41 3.1116 1 1440 2 10 30 68 210 480 600 695 Race Black 278 78.374 130.69 7.838 1 645 2 10 30 70 190 435 580 600 Race Asian 51 42.431 61.693 8.6387 1 405 2 10 28 60 85 120 150 405 Race Some Others '50 73.06 113.02 15.9836 1 535 2 15 40 60 167.5 420 492.5 535 Race Hispanic 136 55.066 100.19 8.591 1 600 2 10 25 54.5 110 170 525 600 Race Refused 35 124.4 186.88 31.5887 4 810 10 20 40 120 360 565 810 810 Hispanic No 2552 79.761 142.98 2.8303 1 1440 2 10 30 65 200 457 600 665 Hispanic Yes 230 68.091 125.96 8.3058 1 765 2 10 30 60 147.5 410 565 615 Hispanic DK 13 185.31 321.29 89.*1098 *2 985 2 10 25 100 705 985 985 985 Hispanic Refused 30 129.83 198.28 36.2 10 810 10 20 40 98 435 585 810 810 Employment . 632 46.989 68.827 2.7378 1 540 2 10 23 55 120 180 265 360 Employment Full Time 1169 114.86 193.04 5.646 1 1440 2 10 30 90 485 570 690 740 Employment Part Time 254 67.118 114.34 7.174 1 795 2 10 30 63 165 280 510 600 Employment Not Employed 751 56.792 84.927 3.099 1 690 2 10 30 60 130 210 360 465 Employment Refused 19 96.947 185.76 42.616 5 790 5 20 30 90 360 790 790 790 Education . 702 47.098 70.151 2.6477 1 540 2 10 24 55 120 180 265 360 Education < High School 222 105.76 193.65 12.9967 1 1440 4 10 30 90 365 540 720 735 Education High School Graduate 702 113.18 185.75 7.0107 1 1410 2 10 35 90 455 555 665 740 Education <College 537 87.927 157.3 6.7878 1 985 2 10 30 70 240 540 635 705 Education College Graduate 367 70.905 117.85 6.1515 1 660 2 10 30 68 170 325 565 600 Education Post Graduate 295 55.186 86.872 5.0579 1 710 3 10 30 60 120 200 362 560 Census Region Northeast 749 75.734 130.56 4.7705 1 985 3 10 30 70 179 375 570 665 Census Region Midwest 586 77.445 141.21 5.8332 1 1440 2 10 30 60 210 390 560 645 Census Region South 836 86.447 160.31 5.5443 1 1410 2 10 30 61.5 210 525 643 710 Census Region West 654 78.19 138.28 5.4072 1 985 2 10 30 65 180 435 570 615 Day Of Week Weekday 2018 84.241 155.61 3.4639 1 1440 2 10 30 65 215 515 625 705 Day Of Week Weekend 807 68.793 108.2 3.8088 1 705 2 10 30 65 180 310 465 540 Season Winter 703 70.91 141.83 5.3492 1 1440 2 10 26 60 160 365 570 643 Season Spring 791 80.542 135.48 4.817 1 810 2 10 30 74 215 435 570 645 Season Summer 819 84.178 150.3 5.2519 1 985 2 10 30 70 210 510 615 705 Season Fall 512 84.01 148.27 6.5525 1 930 2 10 30 70 225 510 600 690 Asthma No 2596 80.366 143.21 2.8107 1 1410 2 10 30 65 205 475 600 675 Asthma Yes 205 75.088 157.15 10.9756 1 1440 2 10 30 65 160 309 580 690 Asthma DK 24 62.083 78.548 16.0335 5 360 5 17.5 35 67.5 98 225 360 360 Angina No 2726 79.57 144.32 2.7642 1 1440 2 10 30 65 196 465 600 687 Angina Yes 76 92.434 139.38 15.9879 1 570 3 10 35 91 354 465 535 570 Angina bK 23 68.696 91.209 19.0183 5 360 10 20 40 75 98 330 360 360 Bronchitis/Emphysema No 2684 79.404 142.84 2.7572 1 1440 2 10 30 65 197 465 600 665 Bronchitis/Emphysema Yes 115 93.843 175.36 16.3523 1 985 2 10 30 90 225 465 735 985 Bronchitis/Emphysema DK 26 61.615 72.201 14.1598 5 360 7 27 40 75 110 180 360 360 Note: A ..... Signifies missing data. "DK"= The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Stderr =standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996. Table 15-135. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors Other Than Near a Residence or Vehicle Such as Parks, Golf Courses, or Farms Percentiles Group Name Group Code N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 1383 200.153 202.665 5.45 1 1440 10 60 130 276 510 600 748 915 Gender Male 789 223.482 208.727 7.431 1 1440 20 60 150 315 540 635 765 900 Gender Female 593 168.742 189.993 7.802 1 1440 10 40 105 238 420 540 700 930 Gender Refused 1 420 . . 420 420 420 420 420 420 420 420 420 420 Age (years) . 19 183.368 160.349 36.787 10 540 10 60 140 220 510 540 540 540 Age (years) 1-4 54 164.648 177.34 24.133 1 980 10 60 120 175 370 560 630 980 Age (years) 5-11 159 171.34 177.947 14.112 5 1210 15 55 115 221 405 574 660 725 Age (years) 12-17 175 156.903 174.411 13.184 5 1065 10 45 100 210 385 570 735 915 Age (years) 18-64 858 219.425 215.094 7.343 1 1440 10 60 150 310 540 635 780 933 Age (years) > 64 118 181.932 180.158 16.585 5 900 20 55 112.5 280 480 570 600 735 Race White 1186 202.615 203.396 5.906 1 1440 14 60 134.5 280 510 615 750 930. Race Black 81 185.84 195.119 21.68 1 765 5 40 108 240 540 585 690 765 Race Asian 20 169.45 189.122 42.289 10 665 10 32.5 95 230 477.5 585 665 665 Race Some Others 30 187.5 161.849 29.549 10 560 10 60 120 270 437.5 535 560 560 Race Hispanic 57 158.298 203.27 26.924 1 1305 5 30 110 228 370 435 555 1305 Race Refused 9 380 250.637 83.546 30 810 30 195 435 540 810 810 810 810 Hispanic No 1267 202.593 203.353 5.713 1 1440 10 60 130 280 510 615 748 915 Hispanic Yes 103 163.942 185.155 18.244 1 1305 10 30 115 228 400 511 555 555 Hispanic DK 4 67.5 59.231 29.616 10 145 10 22.5 57.5 112.5 145 145 145 145 Hispanic Refused* 9 330 259.459 86.486 30 810 30 140 210 510 810 810 810 810 Employment . 383 163.846 176.805 9.034 1 1210 10 51 110 215 385 560 665 915 Employment Full Time 555 228.526 219.372 9.312 1 1305 14 60 150 335 545 645 825 955 Employment Part Time 126 202.556 211.673 18.857 3 1440 10 60 125 280 510 580 690 700 Employment Not Employed 309 191.469 189.268 10.767 1 1440 10 50 125 275 480 565 690 735 Employment Refused 10 254 240.899 76.179 30 810 30 105 167.5 280 675 810 810 810 Education . 429 163.949 175.476 8.472 1 1210 10 55 115 210 385 560 665 840 Education < High School 83 264.482 255.463 28.041 1 1305 30 60 180 480 555 600 1100 1305 Education High School Graduate 313 228.613 228.235 12.901 3 1440 10 60 160 310 570 690 855 990 Education <College 250 217.984 202.991 12.838 1 1440 10 60 152.5 330 510 555 715 765 Education College Graduate 185 207.27 190.178 13.982 1 930 20 60 128 285 505 600 690 795 Education Post Graduate 123 163.642 173.04 15.603 1 900 10 45 90 240 385 480 735 780 Census Region Northeast 279 196.824 208.372 12.475 1 1305 10 60 130 265 480 590 900 1130 Census Region Midwest 309 196.702 211.59 12.037 1 1440 10 50 120 270 510 635 740 900 Census Region South 468 198.432 195.071 9.017 1 933 15 60 120 285 510 600 748 825 Census Region West 327 208.716 200.465 11.086 1 1440 15 60 150 285 525 580 725 855 Day Of Week Weekday 851 183.982 197.931 6.785 1 1440 10 45 119 240 490 585 735 900 Day Of Week Weekend 532 226.019 207.598 9 1 1440 20 68.5 155 320 525 630 810 915 Season Winter 241 175.676 192.682 12.412 1 1065 10 ' 35 93 253 450 585 750 810 Season Spring 412 185.806 174.522 8.598 5 980 15 60 130 240 473 555 665 740 Season Summer 508 224.996 220.748 9.794 1 1440 15 60 150 305 540 630 840 990 Season Fall 222 196.5 213.598 14.336 1 1130 10 35 120 280 540 600 780 900 Asthma No 1283 196.564 196.894 5.497 1 1440 10 60 125 270 495 600 730 855 Asthma Yes 93 244.344 263.314 27.304 5 1440 15 60 150 350 530 810 1100 1440 Asthma DK 7 270.714 274.415 103.719 30 810 30 60 195 450 810 810 810 810 Angina No 1352 199.038 202.274 5.501 1 1440 10 60 130 270 510 600 740 915 Angina Yes 25 238.64 205.994 41.199 1 730 5 .60 210 340 465 690 730 730 Angina DK 6 290.833 275.979 112.668 30 810 30 140 202.5 360 810 810 810 810 Bronchitis/Emphysema No 1326 199.761 200.843 5.516 1 1440 10 60 130 275 500 600 735 900 Bronchitis/Emphysema Yes 51 206.431 239.756 33.573 5 1100 10 50 110 305 540 700 930 1100 Bronchitis/Emphysema DK 6 233.333 294.035 120.039 15 810 15 30 167.5 210 810 810 810 810 Note: A ..... Signifies missing data. "DK"= The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Stderr = standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996. Table 15-136. Statistics for 24-Hour Cumulative Number of Minutes Spent in an Office or Factory Percentiles Cateaorv Peculation Grouo N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 1975 393.972 230.763 5.1926 1 1440 9 180 485 550 630 675 765 818 Gender Male 1012 410.816 233.454 7.3386 1 1440 10 225 495 565 645 710 780 855 Gender Female 963 376.271 226.676 7.3045 1 855 5 120 480 540 600 645 710 750 Age (years) . 49 438.918 232.58 33.2257 10 900 20 299 500 555 675 780 900 900 Age (years) 1-4 12 31.583 25.639 7.4013 5 90 5 12.5 25 44.5 60 90 90 90 Age (years) 5-11 14 100.929 155.126 41.4593 2 580 2 10 32.5 178 195 580 580 580 Age (years) 12-17 19 145.421 181.118 41.5512 1 625 1 10 50 240 510 625 625 625 Age (years)* 18-64 1749 418.971 218.445 5.2233 1 1440 10 273 500 555 630 680 765 818 Age (years) >64 132 145.848 193.973 16.8832 1 705 3 10 40 205 495 540 640 675 Race White 1612 387.646 231.968 5.7776 1 1440 6 150 480 550 628 675 750 800 Race Black 191 413.911 218 15.7739 1 1037 10 268 485 540 635 720 803 900 Race Asian 42 428.024 .216.759 33.4466 10 780 30 285 491.5 553 660 745 780 780 Race Some Others 28 480.893 200.859 37.9588 40 795 75 347.5 540 582.5 715 780 795 795 Race Hispanic 74 394.459 237.847 27.6492 1 840 5 230 492.5 560 645 720 765 840 Race Refused 28 482.893 246.079 46.5046 30 997 30 373 532.5 607.5 818 860 997 997 Hispanic No 1805 393.453 229.593 5.404 1 1440 10 180 483 550 630 675 755 810 Hispanic Yes 138 393.645 238.608 20.3116 1 840 5 180 497.5 560 644 675 765 795 Hispanic DK 7 262.571 242.131 91.5168 1 610 1 12 245 540 610 610 610 610 Hispanic Refused 25 470.04 258.753 51.7505 17 860 30 311 525 615 810 818 860 860 Employment . 43 121.279 177.984 27.1423 1 685 2 10 40 178 307 580 685 685 Employment Full Time 1535 455.571 200.299 5.1124 1 1440 15 400 510 570 644 700 775 837 Employment Part Time 164 293.03 196.95 15.3792 1 750 10 95 342.5 480 525 555 585 615 Employment Not Employed 213 77.643 122.957 8.4249 1 705 3 10 30 90 215 305 570 640 Employment Refused 20 449.15 184.813 41.3256 30 675 60 334 522.5 550 645 675 675. 675 Education . 80 225.1 248.547 27.7884 1 860 3 15 105 470 607.5 675 780 860 Education < High School 104 329.548 264.402 25.9267 2 930 5 50.5 388.5 552.5 640 705 765 855 Education High School Graduate 631 396.876 228.074 9.0795 1 997 10 210 492 550 615 675 760 800 Education <College 462 393.108 228.826 10.6459 1 '1440 5 210 480 540 615 660 770 820 Education College Graduate 415 437.231 205.198 10.0728 1 900 10 325 510 570 640 690 750 800 Education Post Graduate 283 396.883 232.151 13.7999 2 860 5 175 480 565 640 675 780 818 Census Region Northeast 465 399.075 226.243 10.4918 1 930 10 215 485 550 625 675 765 840 Census Region Midwest 439 389.31 229.075 10.9331 1 997 8 180 480 550 630 670 750 800 Census Region South 666 408.637 228.181 8.8418 1 1440 10 225 497.5 555 630 675 760 840 Census Region West 405 369.052 240.375 11.9443 1 900 5 95 470 550 630 675 760 800 Day Of Week Weekday 1759 406.795 225.173 5.3689 1 997 10 237 495 555 630 675 755 810 Day Of Week Weekend 216 289.551 249.076 16.9475 1 1440 3 30 282.5 495 600 670 800 900 Season Winter 531 390.716 231.677 10.0539 1 997 10 180 480 550 625 675 755 835 Season Spring 470 385.198 240.678 11.1016 1 1440 5 120 480 553 630 695 775 837 Season Summer 550 393.524 224.454 9.5708 1 1037 9 200 482.5 540 613.5 675 753 810 Season Fall 424 408.358 226.578 11.0036 1 840 10 238.5 500 566.5 640 675 750 770 Asthma No 1845 394.976 230.383 5.3635 1 1440 8 185 490 550 630 675 760 810 Asthma Yes 114 371.693 231.336 21.6666 3 840 10 120 462.5 540 630 675 800 837 Asthma DK 16 437 272.067 68.0168 5 860 5 232.5 520 587.5 780 860 860 860 Angina No 1931 395.718 229.668 5.2265 1 1440 10 195 490 550 630 675 760 811 Angina Yes 26 265.462 246.766 48.3947 5 650 9 15 175 490 630 645 650 650 Angina DK 18 392.333 282.64 66.619 5 860 5 30 490 550 780 860 860 860 Bronchitis/Emphysema No 1873 395.611 229.961 5.3135 1 1440 8 195 490 550 630 675 760 818 Bronchitis/Emphysema Yes 86 356.43 236.119 25.4614 5 800 10 75 427.5 540 620 660 720 800 Bronchitis/Emphysema DK 16 403.875 289.456 72.3641 5 860 5 30 490 582.5 780 860 860 860 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused= Refused data. N =doer sample size. Mean= Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Std err= standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsann and Kleoeis 1996. Table 15-137. Statistics for 24-Hour Cumulative Number of Minutes Spent in Malls, Grocerv Stores, or Other Stores Percentiles Group Name Group Code N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 2697 114.975 140.961 2.7143 1 1080 10 30 60 135 285 482 570 640 Gender Male 1020 120.159 157.143 4.9203 1 840 5 30 60 130 375 530 609 658 Gender Female 1677 111.822 130.088 3.1766 1 1080 10 30 60 135 255 400 550 600 Age (years) . 50 139.44 137.586 19.4576 15 660 20 45 92.5 180 338.5 420 565 660 Age (years) 1-4 110 90.036 77.887 7.4263 5 420 10 40 -65 105 210 250 359 360 Age (years) 5-11 129 77.674 68.035 5.9901 3 320 5 30 60 110 180 225 255 280 Age (years) 12-17 140 88.714 101.361 8.5666 . 1 530 5 20 45 123.5 222.5 317.5 384 413 Age (years) 18-64 1871 125.927 156.815 3.6253 1 1080 10 30 60 150 360 525 600 658 Age (years) > 64 397 88.572 88.477 4.4405 1 655 10 30 60 120 180 255 400 470 Race White 2234 111.563 139.443 2.9502 1 1080 10 30 60 130 265 495 570 640 Race Black 237 123 152.318 9.8941 2 800 10 25 60 135 370 480 600 613 Race Asian 37 158.892 151.725 24.9434 2 600 14 50 105 220 410 480 600 600 Race Some Others 52 150.231 146.737 20.3488 5 660 14 65 102.5 180 280 588 600 660 Race Hispanic 110 133.145 138.309 13.1872 1 720 10 35 90 195 310 450 535 540 Race Refused 27 124.741 131.136 25.2372 10 515 10 30 60 207 300 380 515 515 Hispanic No 2476 114.387 141.819 2.8501 1 1080 10 30 60 131.5 285 495 570 640 Hispanic Yes 188 126.074 133.15 9.711 1 720 10 30 90 172.5 270 450 540 610 Hispanic DK 12 49.417 37.689 10.8798 2 122 2 17.5 47.5 69.5 105 122 122 122 Hispanic Refused 21 122.429 138.488 30.2206 10 515 20 33 60 180 290 380 515 515 Employment . 372 86.946 86.322 4.4756 1 660 5 30 60 120 206 255 360 384 Employment Full Tinie 1170 136.797 176.691 5.1656 1 1080 10 30 60 150 480 562 640 690 Employment Part Time 285 134.123 147.732 8.7509 2 540 6 30 65 186 400 480 520 540 Employment Not Employed 854 91.198 87.218 2.9846 1 585 10 30 60 120 195 255 360 420 Employment Refused 16 98.938 110.033 27.5083 10 357 10 31.5 52.5 115 290 357 357 357 Education . 420 88.262 91.922 4.4853 1 660 5 29 60 120 210 262.5 384 420 Education < High School 206 128.937 155.722 10.8497 2 1080 10 30 75 150 330 500 570 605 Education High School Graduate 792 126.295 158.884 5.6457 1 960 5 30 60 150 365 524 600 660 Education <College 583 129.849 149.53 6.1929 1 800 10 30 70 165 345 510 563 651 Education College Graduate 411 117.876 144.142 7.11 1 720 10 30 60 135 290 515 600 640 Education Post Graduate 285 78.182 95.665 5.6667 1 630 10 25 50 90 160 250 450 555 Census Region Northeast 622 110.201 134.942 5.4107 1 755 5 30 60 130 280 465 563 600 Census Region Midwest 601 108.243 133.098 5.4292 2 840 10 30 60 130 250 440 560 645 Census Region South .871 127.922 155.825 5.2799 1 1080 10 30 60 155 320 520 600 660 Census Region West 603 107.909 130.742 5.3242 1 840 10 30 60 120 255 430 550 600 Day Of Week Weekday 1721 117.451 148.879 3.5887 1 1080 10 30 60 135 320 510 586 650 Day Of Week Weekend 976 110.61 125.747 . 4.0251 1 840 5 30 65 135 255 380 560 608 Season Winter 683 111.71 134 5.1274 2 840 10 30 60 135 255 420 568 660 Season Spring 679 115.844 142.21 5.4575 1 720 10 30 60 130" 300 500 588 645 Season Summer 759 113.138 147.47 5.3528 1 1080 5 30 60 125 300 510 570 610 Season Fall 576 120.243 138.948 5.7895 1 840 10 30 60 160 295 480 550 640. Asthma No 2480 116.246 142.351 2.8585 1 1080 10 30 60 135 287.5 495 575 640 Asthma Yes 208 101.111 124.977 8.6656 1 600 5 30 60 120 245 420 545 550 Asthma DK 9 85.111 79.634 26.5447 33 290 33 55 58 60 290 290 290 290 Angina No 2607 115.981 142.101 2.7831 1 1080 10 30 60 135 290 495 570 640 Angina Yes 74 90.838 103.912 12.0795 2 630 15 37 64 105 150 190 510 630 Angina DK 16 62.688 68.084 17.021 2 290 2 30 55 60 110 290 290 290 Bronchitis/Emphysema No 2553 115.736 141.704 2.8045 1 1080 10 30 60 135 285 481 570 640 Bronchitis/Emphysema Yes 130 104.754 131.336 11.5189 5 613 10 25 60 135 192.5 505 575 609 Bronchitis/Emphysema DK 14 71.143 66.864 17.8701 20 290 20 35 56.5 70 110 290 290 290 Note: A"*" Signifies missing data. "DK" =The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Std err= standard error. Min= minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsann and Kleneis 1996. Table 15-138. Statistics for 24-Hour Cumulative Number of Minutes Scent in Schools, Churches, Hospitals. and Public BuildinQs Percentile Cateaorv Population Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 2932 274.332 205.942 3.8033 1 1440 20 95 221 430 540 615 725 805 Gender Male 1234 285.147 206.713 5.8845 1 1440 30 110 255 425 540 620 745 840 Gender Female 1698 266.472 205.082 4.9769 1 1440 20 90 200 430 540 610 713 800 Age (years) . 50 268.96 221.042 31.2601 5 1030 30 100 192.5 400 590 625 871.5 1030 Age (years) 1-4 98 233 235.787 23.8181 1 1440 5 60 150 390 545 595 900 1440 Age (years) 5-11 391 351.202 149.578 7.5645 5 665 70 245 389 440 535 562 625 645 . Age (years) 12-17 355 366.338 161.247 8.5581 1 935 60 260 415 446 502 605 710 805 Age (years) 18-64 1653 267.707 221.203 5.4407 1 1440 15 87 190 450 570 655 760 855 Age (years) > 64 385 151.091 128.639 6.556 5 710 21 60 115 195 340 435 525 615 Race White 2310 268.239 204.323 4.2512 1 1440 20 90 210 429 540 612 705 765 Race Black 332 303.473 207 .071 11.3645 1 1440 35 135 285 440 540 630 775 1000 Race Asian 61 295 199.398 25.5302 5 900 30 135 240 425 535 565 840 900 Race Some Others 57 314.684 203.549 26.9607 10 967 30 135 360 455 525 598 820 967 .Race Hispanic 141 283.936 229.828 19.355 2 1440 11 100 237 430 525 630 840 940 Race Refused 31 257.774 192.517 34.5771 5 681 5 .120 240 430 495 625 681 681 Hispanic No 2654 271.293 203.551 3.9511 1 1440 20 94 215 425 540 612 712 800 Hispanic Yes 240 306.388 230.835 14.9003 1 1440 20 110 287.5 444.5 567.5 695 840 940 Hispanic DK 13 279.385 230.736 63.9946 35 760 35 65 235 420 562 760 760 760 Hispanic Refused 25 286.6 175.367 35.0734 5 625 55 145 255 440 495 565 625 625 Employment . 821 343.484 171.113 5.9719 1 1440 55 190 393 441 520 570 645 713 Employment Full Time 1029 300.3 239.785 7.4751 1 1440 15 90 215 510 610 685 775 900 Employment Part Time 293 251.324 199.326 11.6447 1 1030 20 85 200 387 525 610 800 880 Employment Not Employed 775 176.406 148.414 5.3312 1 855 15 60 121 250 400 475 570 641 Employment Refused 14 212.857 147.736 39.484 5 440 5 120 190 305 430 440 440 440 Education . 917 340.328 172.613 5.7002 1 1440 45 190 390 440 525 580 645 713 Education < High School 166 172.602 138.026 10.7129 1 735 27 70 123.5 235 375 465 525 640 Education High School Graduate 617 207.29 199.027 8.0125 1 1440 15 60 135 295 510 585 690 785 Education <College 520 247.492 213.609 9.3674 1 1000 15 85 165 420 552.5 640 760 855 Education College Graduate 351 261.581 214.287 11.4378 1 1005 15 85 180 450 560 625 750 800 Education Post Graduate
361 319.114 236.166 12.4298 1 1440 30 110 290 510 615 683 765 900 Census Region Northeast 645 272.747 211.594 8.3315 1 1440 25 90 215 420 545 630 735 855 Census Region Midwest 686 275.394 207 .157 7.9093 1 1440 30 88 239 425 540 615 745 850 Census Region South 1036 278.387 201.004 6.2449 1 1440 20 110 230 440 535 600 690 778 Census Region West 565 267.418 207.214 8.7176 1 1440 15 100 200 420 555 620 712 820 Day Of Week Weekday 2091 309.844 212.577 4.6488 1 1440 15 115 340 460 565 632 750 855 Day Of Week Weekend 841 186.039 156.873 5.4094 1 1440 40 85 140 230 385 525 640 735 Season Winter 847 296.587 201.244 6.9148 1 1440 30 120 285 444 545 615 710 770 Season *Spring 805 276.761 204.618 7.2118 1 1440 30 110 220 420 535 600 725 840 Season Summer 667 254.115 209.724 8.1205 1 1015 20 80 180 420 550 630 738 890 Season Fall 613 262.39 207.33 8.374 1 1005 14 75 210 425 540 615 712 778 Asthma No 2689 273.193 207.301 3.9977 1 1440 20 94 217 430 540 615 725 820 Asthma Yes 229 287.974 191.578 12.6598 1 855 25 120 275 435 533 605 645 800 Asthma DK 14 270 171.24 45.7658 5 565 5 145 280 430 445 565 565 565 Angina No 2836 277.127 206.396 3.8757 1 1440 20 100 230 430 540 615 725 805 Angina Yes 78 176.423 172.803 19.5661 5 890 28 60 120 195 480 575 625 890 Angina DK 18 258.278 . 165.599 39.0321 3 565 3 145 270 378 480 565 565 565 Bronchitis/Emphysema No 2794 276.999 207.348 3.9227 1 1440 20 95 228 430 540 615 726 840 Bronchitis/Emphysema Yes 121 212.562 166.349 15.1226 10 662 30 90 145 375 445 490 605 630 Bronchitis/Emphysema DK 17 275.765 163.401 39.6306 5 565 5 145 305 415 440 565 565 565 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused = Refused data. N =doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min= minimum number of minutes. Max= maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsann and Kleneis 1996.
Table 15-139. Statistics for 24-Hour Cumulative Number of Minutes Spent in Bars/Niohtclubs, Bowlinii Allevs, and Restaurants Percentiles Cateaorv Pooulation Grouo N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 2296 111.735 131.368 2.7416 1 925 10 40 60 120 255 405 568 660 Gender Male 1127 109.497 129.654 3.8621 1 900 10 35 60 120 240 377 560 660 Gender Female 1169 113.892 133.019 3.8905 2 925 10 45 60 120 270 424 570 645 Age (years) . 32 138.094 151.816 26.8376 15 610 30 47.5 65 150 315 495 610 610 Age (years) 1-4 61 62.705 47.701 6.1075 4 330 10 35 55 85 115 120 130 330 Age (years) 5-11 88 58.602 39.746 4.2369 5 180 10 30 45 85 120 137 170 180 Age (years) 12-17 127 76.614 82.038 7.2797 2 455 10 30 50 90 220 270 325 360 Age (years) 18-64 1718 121.371 142.223 3.4313 1 925 10 40 65 135 285 462 600 680 Age (years) > 64 270 92.207 90.483 5.5066 3 750 20 45 62.5 100 177.5 255 358 520 Race White 1945 108.84 127.174 2.8836 1 925 10 40 60 120 240 388 560 645 Race Black 167 121.88 147.847 11.4408 5 805 10 30 60 153 300 490 555 735 Race Asian 42 103.976 104.151 16.0709 5 497 30 40 62.5 120 200 240 497 497 Race Some Others 36 159.333 196.721 32.7868 5 765 10 52.5 90 137.5 495 750 765 765 Race Hispanic 83 130.205 161.594 17.7373 5 813 15 40 65 143 360 485 700 813 Race Refused 23 155.913 135.696 28.2945 20 480 30 60 88 270 330 410 480 480 Hispanic No 2131 110.53 129.679 2.8092 1 925 10 40 60 120 245 395 560 650 Hispanic Yes 141 127.319 153.659 12.9404 1 813 15 40 70 120 360 440 700 765 Hispanic DK 7 95 115.109 43.507 5 315 5 10 40 165 315 315 315 315 Hispani_c Refused 17 140.353 147.503 35.7748 30 480 30 40 70 210 410 480 480 480 Employment . 273 65.85 61.078 3.6966 2 455 10 30 50 85 120 182 273 330 Employment Full Time 1215 125.765 151.364 4.3424 1 925 10 40 63 135 300 500 640 735 Employment Part Time 236 144.729 157.886 10.2775 1 813 10 47.5 80 180 385 520 615 745 Employment Not Employed 559 88.642 77.231 3.2665 3 610 15 45 60 115 180 240 315 388 Employment Refused 13 158.077 127.157 35.267 30 425 30 70 105 240 330 425 425 425 Education . 309 76.006 81.68 4.6466 1 548 10 30 55 90 165 255 330 455 Education < High School 155 154.155 175.537. 14.0995 5 925 15 40 90 209 388 545 700 870 Education High Schciol Graduate 665 119.502 145.414 5.6389 3 910 10 45 60 120 290 485 630 680 Education <College 498 121.321 137.839 6.1767 2 775 10 40 75 135 270 440 610 675 Education College Graduate 395 101.096 109.709 5.5201 1 765 15 40 60 120 225 330 507 570 Education Post Graduate 274 107.091 117.52 7.0997 3 765 15 40 65 120 220 330 560 675 Census Region Northeast 462 115.771 127.168 5.9164 2 765 15 45 70 120 270 380 560 650 Census Region Midwest 561 113.688 132.476 5.5932 1 813 10 40 65 120 250 410 570 675 Census Region South 748 105.619 133.036 4.8643 2 910 13 35 60 110 240 390 555 650 Census Region West 525 114.81 131.486 5.7385 1 925 10 37 70 130 245 417 590 640 Day Of Week Weekday 1407 112.164 138.508 3.6926 1 925 10 35 60 120 270 430 595 675 Day Of Week Weekend 889 111.055 119.269 4.0001 2 870 10 45 70 120 235 351 535 630 Season Winter 584 116.783 135.982 5.627 3 875 15 40 68.5 120 265 440 595 735 Season Spring 615 108.416 124.727 5.0295 2 925 15 41 65 120 240 395 542 585 Season Summer 622 110.543 132.965 5.3314 1 910 10 35 60 120 260 390 605 660 Season Fall 475 111.385 132.104 6.0614 1 900 10 35 60 125 265 355 550 770 Asthma No 2124 111.768 129.918 2.819 1 910 10 40 60 120 255 390 568 660 Asthma Yes 163 107.301 145.813 11.4209 4 925 10 30 57 118 265 485 560 670 Asthma DK 9 184.222 186.348 62.1159 30 480 30 60 88 300 480 480 480 480 Angina No 2229 112.481 132.361 2.8035 1 925 10 40 60 120 260 410 570 660 Angina Yes 54 71.463 52.513 7.1461 3 340 15 45 60 90 120 120 232 340 Angina DK 13 151 162.726 . 45.132 30 480 30 35 88 120 480 480 480 480 Bronchitis/Emphysema No 2171 111.178 129.886 2.7876 1 910 10 40 60 120 255 400 560 660 Bronchitis/Emphysema Yes 114 109.807 134.998 12.6437 5 925 15 43 65 120 235 375 530 620 Bronchitis/Emphysema DK 11 241.636 274.085 82.6397 10 875 10 30 88 480 480 875 875 875 Note: A"*" Signifies missing data. "DK" =The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Std err= standard error. Min= minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsann and Kleoeis 1996.
Table 15-140. Statistics for 24-Hour Cumulative Number of Minutes in Other Outdoors Such as Auto Reoair Shops, Laundromats, Gvms, and at Wor (non-soecificl Percentiles Group Name Group Code N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 1214 225.747 231.111 6.633 1 1440 10 56 120 370 568 670 800 910 Gender Male 612 260.322 239.586 9.685 1 1040 10 60 160 460 605 695 815 930 Gender Female 602 190.598 216.774 8.835 1 1440 10 45 105 260 535 600 720 855 Age (years) . 21 264.524 273.733 59.733 15 940 30 75 100 420 560 840 940 940 Age (years) 1-4 27 92.296 74.852 14.405 10 270 15 25 65 160 180 250 270 270 Age (years) 5-11 59 134.678 186.691 24.305 5 910 5 30 80 145 325 720 855 910 Age (years) 12-17 76 164.368 159.542 18.301 1 660 5 45 130 208 450 550 600 660 Age (years) 18-64 903 250.29 243.45 8.101 1 1440 10 60 135 450 600 690 815 945 Age (years) > 64 128 152.813 159.777 14.122 2 770 12 45 95 202.5 420 510 600 610 Race White 996 226.348 228.881 7.252 1 1440 10 58.5 120 370 580 665 780 910 Race Black 118 228.102 256.391 23.603 2 1430 5 45 120 358 525 720 990 1150 Race Asian 25 194.68 196.484 39.297 5 600 25 58 90 300 525 530 600 600 Race Some Others 23 211.217 236.332 49.279 5 800 10 25 115 405 515 680 800 800 Race Hispanic 42 250.19 229.16 35.36 5 793 15 60 165 420 600 675 793 793 Race ' Refused 10 146.5 246.555 77.967 15 840 15 55 67.5 105 495 840 840 840 Hispanic No 1133 224.325 231.063 6.865 1 1440 10 55 120 360 565 670 810 930 Hispanic Yes 68 230.088 215.421 26.124 5 793 15 61.5 127.5 398 545 660 790 793 Hispanic DK 5 483.2 240.867 107.719 55 623 55 560 568 610 623 623 623 623 Hispanic Refused 8 229.375 310.592 109.811 30 840 30 42.5 67.5 372.5 840 840 840 840 Employment . 162 140.031 158.915 12.486 1 910 10 30 103.5 170 325 505 660 855 Employment Full Time 652 276.345 250.945 9.828 2 1430 10 60 162.5 508 619 700 815 945 Employment Part Time 132 240.909 227.902 19.836 5 1440 15 67.5 170 360 510 620 815 1005 Employment Not Employed 259 145.347 173.086 10.755 1 1150 5 40 90 160 432 540 704 770 Employment Refused 9 194.444 278.752 92.917 15 840 15 40 75 150 840 840 840 840 Education . 186 148.097 168.067 12.323 1 910 5'. 30 109.5 177 330 520 720 855 Education < High School 88 301.966 251.244 26.783 5 930 15 60 265 487.5 670 780 815 930 Education High School Graduate 324 249.086 243.136 13.508 2 1150 10 53.5 126 435 595 690 815 979 Education <College 251 266.996 256.435 16.186 2 1440 10 60 155 480 600 710 800 990 Education College Graduate 217 202.014 217.284 14.75 1 1005 5 55 110 295 570 645 760 855 Education Post Graduate 148 191.764 198.819 16.343 2 870 10 60 105 262.5 535 590 700 793 Census Region Northeast 275 218.171 216.166 13.035 2 990 10 60 120 360 544 660 765 855 Census Region Midwest 254 250.689 241.492 15.153 1 1005 10 55 150 460 600 695 815 940 Census Region South 401 223.691 239.929 11.981 1 1440 10 47 120 360 560 635 815 979 Census Region West 284 213.68 222.324 13.193 2 960 10 60 120* 305 585 675 793 850 Day Of Week Weekday 900 224.954 232.145 7.738 1 1430 10 58.5 120 367.5 565 672.5 815 942.5 Day Of Week Weekend 314 228.019 228.476 12.894 2 1440 8 52 120 376 580 665 720 815 Season Winter 347 241.715 239.749 12.87 2 1440 10 60 155 390 585 660 897 960 Season Spring 321 220.343 220.658 12.316 1 1005 10 54 115 390 550 630 730 815 Season Summer 294 224.418 244.957 14.286 1 1040 5 45 115 360 595 760 855 979 Season Fall 252 212.194 214.928 13.539 1 990 15 55.5 120 327.5 540 660 710 793 Asthma No 1123 225.742 229.228 6.84 1 1440 10 55 125 370 565 660 780 897 Asthma Yes 84 228.5 259.329 28.295 1 979 10 59.5 100 351 660 793 910 979 Asthma DK 7 193.571 201.406 76.124 15 510 15 60 80 450 510 510 510 510 Angina No 1178 225.259 231.28 6.739 1 1440 10 55 120 360 570 670 810 930 Angina Yes 28 227.75 218.573 41.306 5 770 12 62.5 135 425 560 600 770 770 Angina DK 8 290.625 269.171 95.166 15 780 15 67.5 217.5 480 780 780 780 780 Bronchitis/Emphysema No 1166 226.724 232.003 6.794 1 1440 10 58 120 370 570 670 810 930 Bronchitis/Emphysema Yes 41 198.829 213.198 33.296 5 780 10 45 95 330 550 565 780 780 Bronchitis/Emphysema DK 7 220.714 197.261 74.558 15 510 15 60 155 450 510 510 510 510 Note: A,,.,, Signifies missing data. "DK"= The respondent replied "don't know". Refused= Refused data. N =doer sample size. Mean= Mean 24-hour cumulative number of minutes for doers. Stdev = standard deviation. Stderr = standard error. Min= minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleneis 1996.
Table 15-141. Statistics for 24-Hour Cumulative Number of Minutes Spent with Smokers Present Percentiles Category Population Group N Mean Stdev Std err Min Max 5 25 50 75 90 95 98 99 All 4005 381.494 300.479 4.748 1 1440 30 120 319 595 815 925 1060 1170 Gender Male 1967 411.359 313 7.057 1 1440 30 135 355 638 855 965 1105 1217 Gender Female 2035 352. 771 285.139 6.321 1 1440 29 105 285 545 780 870 995 1110 Gender Refused 3 283.333 188.171 108.641 105 480 105 105 265 480 480 480 480 480 Age (years) . 54 386.259 305.371 41.556 5 1440 25 105 370 555 780 995 995 1440 Age (years) 1-4 155 366.561 324.464 26.062 5 1440 30 90 273 570 825 1010 1140 1305 Age (years) 5-11 224 318.071 314.016 20.981 1 1440 25 105 190 475 775 1050 1210 1250 Age (years) 12-17 256 245.77 243.61 15.226 1 1260 10 60 165 360 595 774 864 1020 Age (years) 18-64 2976 403.067 299.434 5.489 2 1440 30 134.5 355 625 830 930 1047 1150 Age (years) > 64 340 342.694 292.209 15.847 5 1440 30 100 240 540 797.5 880 1015 1205 Race White 3279 389.219 303.032 5.292 1 1440 30 120 330 610 825 930 1060 1190 Race Black 395 359.977 287.96 14.489 2 1440 22 118 300 538 775 905 1080 1160 Race Asian 48 262.063 209.928 30.3 5 800 10 64 212.5 412.5 560 630 800 800 Race Some Others 79 420.671 339.247 38.168 10 1328 30 135 310 655 885 1140 1305 1328 Race Hispanic 165 292.624 250.208 19.479 5 1095 15 75 220 475 660 800 845 945 Race Refused 39 393.538 325.254 52.082 25 1110 30 115 290 655 865 1040 1110 1110 Hispanic No 3666 384.913 301.22 4.975 1 1440 30 120 324 600 822 930 1060 1170 Hispanic Yes 288 336.191 280.874 16.551 1 1440 20 115 252 512 760 850 1010 1260 Hispanic DK 18 369.833 371.484 87.56 15 1440 15 90 220 600 760 1440 1440 1440 Hispanic Refused 33 403.364 322.819 56.195 25 1110 30 120 325 655 840 1040 1110 1110 Employment . 624 301.723 295.529 11.831 1 1440 15 75 190 450 735 900 1140 1230 Employment Full Time 2042 405.894 296.349 6.558 2 1440 30 135 364.5 625 835 925 1005 1110 Employment Part Time 381 378.013 291.098 14.913 5 1440 30 135 325 585 805 915 1080 1245 Employment Not Employed 935 383.833 308.691 10.095 3 1440 30 120 310 600 825 930 1110 1290 Employment Refused 23 341.957 254.245 53.014 25 925 30 120 325 450 715 885 925 925 Education . 704 308.635 292.801 11.035 1 1440 15 87.5 205 465 741 900 1095 1217 Education < High School 377 497.719 317.756 16.365 2 1440 40 225 465 775 905 990 1120 1369 Education High School Graduate 1315 425.682 301.711 8.32 3 1440 30 155 390 650 840 928 1060 1202 Education <College 829 388.807 295.753 10.272 5 1435 30 135 330 600 810 930 1050 1155 Education College Graduate 473 325.871 272.694 12.538 2 1140 30 90 240 499* 735 860 990 1035 Education Post Graduate 307 282.518 257.117 14.674 3 1205 20 60 200 430 665 810 900 983 Census Region Northeast 932 369.46 287.677 9.423 2 1440 30 120 314 565 800 892 990 1095 Census Region Midwest 938 384.067 304.829 9.9;i3 2 1440 29 120 319.5 600 825 930 1080 1140 Census Region South 1409 404.028 308.501 8.219 1 1440 30 130 345 630 840 943 1090 1205 Census Region West 726 349.883 291.992 10.837 1 1440 30 110 274 541 800 900 1045 1180 Day Of Week Weekday 2661 374.746 296.185 5.742 1 1440 30 120 315 578 810 915 1045 1150 Day Of Week Weekend 1344 394.854 308.482 8.415 1 1440 30 120 321.5 625 833 940 1110 1260 Season Winter 1046 374.159 304.183 9.4.05 1 1440 25 115 295 590 815 925 1080 1170 Season Spring 1034 384.762 301.561 9.378 2 1440 30 120 320 610 810 900 1105 1215 Season Summer 1059 385.134 300.394 9.231 2 1440 30 120 330 591 840 940 1040 1130 Season Fall 866 381.999 295.104 10.028 2 1440 30 120 324 590 810 915 1030 1150 Asthma No 3687 378.806 298.378 4.914 1 1440 30 120 315 591 810 915 1050 1170 Asthma Yes 298 416.862 323.967 18.767 5. 1440 20 135 342.5 652 870 1015 1202 1335 Asthma DK 20 350 304.324 68.049 25 995 27.5 60 290 540 795 902.5 995 995 Angina No 3892 380.923 299.475 4.8 1 1440 30 120 320 595 815 920 1060 1170 Angina Yes 87 404.31 345.105 36.999 2 1380 30 120 270 703 910 1015 1320 1380 Angina DK 26 390.577 300.394 58.912 25 995 30 115 342.5 670 780 790 995 995 Bronchitis/Emphysema No 3749 378.662 298.576 4.876 1 1440 30 120 315 590 810 915 1060 1170 Bronchitis/Emphysema Yes 236 431.157 326.848 21.276 5 1380 30 150 362.5 680 892 980 1205 1260 Bronchitis/Emphysema DK 20 326.25 291.068 65.085 10 995 17.5 85 222.5 540 755 887.5 995 995 Note: A"*" Signifies missing data. "DK"= The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour cumulative number of minutes for doers. Stdev =standard deviation. Std err= standard error. Min = minimum number of minutes. Max = maximum number of minutes. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996. fable 15-142 Range of Time (minutes) Spent Smoking Based on the Number of Respondents Total N *-* 0-60-120-Number of Minutes 180-240-300-360-420-480-540-600-60 120 180 240 300 360 420 480 540 600 660 Overall 9386 5381 628 444 338 285 258 242 236 192 228 186 185 Gender .Male 4294 2327 280 184 167 141 119 114 128 92 101 92 89 Female 5088 3053 348 259 1?1 114 138 108 99 94 96 Refused 4 1
1 1

1 *

Ag_e (years) 187 133 10 6 2 3 2 4 3 6 4 3 3 1-4 499 344 29 23 14 8 10 7 8 7 8 7 5 5-11 703 479 40 38 32 23 10 9 6 12 6 11 6 12-17 589 333 75 31 30 20 22 15 13 7 13 5 3 18-64 6059 3083 412 305 225 196 195 187 192 143 184 148 154 > 64 1349 1009 62 41 35 35 19 20 14 17 13 12 14 Race White 7591 4312 496 368 261 233 208 208 186 154 173 160 149 Black 945 550 66 41 37 26 29 18 31 23 33 15 22 Asian 157 109 12 3 7 5 3 2 5 3 3 2 1 Some Others 182 103 10 8 9 5 7 3 2 3 5 4 4 His/Ganie 385 220 39 17 21 13 9 9 10 8 12 6 Re sed 126 87 5 7 3 3 2 2 2 1 2 3 8534 4868 573 396 295 267 238 226 213 181 202 173 168 Yes 702 414 48 38 38 16 18 \4 21 \0 23 11 13 DK 47 29 3 4 2

1 1 1 1 Refused 103 70 4 6 3 2 1 2 1 1 2 3 E"]ployment 1773 1149 143 91 74 50 39 29 26 28 27 22 14 Full Time 4096 2054 286 203 140 141 124 126 134 96 134 109 110 Part Time 802 421 51 42 36 25 32 27 17 23 28 12 16 Not Employed 2644 1709 145 105 87 67 61 56 58 43 38 43 44 Refused 71 48 3 3 1 2 2 4 1 2 1

1 Ed}lcation 1968 1264 153 98 81 56 49 38 30 31 30 27 18 * < High School 834 457 34 28 23 16 15 23 38 15 20 26 12 High School Graduate 2612 1297 160 115 94 86 92 84 69 71 93 64 76 < allege 1801 972 114 87 76 62 50. 56 49 44 52 35 44 Graduate

1247 774 88 70 42 38 32 24 32 23 20 22 21 Post raduate 924 617 79 46 22 27 20 17 18 8 13 12 14 Census Repion Northeas 2075 1143 150 108 66 73 61 63 54 52 56 40 38 Midwest 2102 1164 145 110 75 65 69 37 63 42 55 51 41 South 3243 1834 206 137 116 106 76 92 85 58 87 60 76 West 1966 1240 127 89 81 41 52 50 34 40 30 35 30 eekday 6316 3655 430 301 227 188 164 146 171 127 169 128 116 Weekena 3070 1726 198 143 111 97 94 96 65 65 59 58 69 Season Winter 2524 1478 180 113 91 81 65 68 53 39 60 48 41 Spring 2438 1404 154 120 82 73 73 61 61 50 58 40 61 Summer 2536 1477 165 116 88 71 64 64 68 61 52 57 45 Fall 1888 1022 129 95 77 60 56 49 54 42 58 41 38 Asthma No 8629 4942 580 419 308 264 237 223 216 175 213 172 173 Yes 694 396 42 24 29 20 20 17 2.0 16 13 13 12 DK 63 43 6 1* 1 1 1 2 1 2 1

9061 5169 610 430 331 273 252 235 233 187 223 181 Yes 250 63 13 11 5 11 5 *5 2 5 4 4 DK 75 49 5 3 2 1 1 2 1

1 2

Bronchitis/emphysema No 8882 5133 593 423 311 267 246 224 219 182 215 177 174 Yes 433 197 30 20 24 17 11 16 1.7 \0 11 7 11 DK 71 51 5 1 3 1 1 2 2 2

Table 15-142 Range of Time (minutes) Spent Smoking Based on the Number of Respondents (continued) Number of Minutes 660-720-780-840-900-960-1020-1080-1140-1200-1260-1320-1380-720 780 840 900 960 1020 1080 1140 1200 1260 1320 1380 1440 Overall 149 135 162 105 83 53 27 21 12 12 3 6 15 Gender Male 84 76 87 66 48 37 18 14 9 6 3 10 Female 6.5 5.9 7.5 3.9 3.5 1.7 ? Refused

Ag_e (years) 2 1 1 1

2 * * * * *

1 1-4 3 5 6 3 f 3 2 2 1

1

1 5-11 7 2 5 2 1 5 2 2 3

2 12-17 7 3 5 3 1 1 * *

2 * *

18-64 119 114 129 91 72 44 18 1.7 5 2 5 10 > 64 11 10 16 5 8 2 2 2

1 1 Race White 135 118 139 90 74 49 21 16 11 11 2 3 14. Black 7 10 8 9 6 3 5 2 1 *

f 1 Asian *

2 * * * * * * *

Some Others 3 2 6 2 2 *

1

1 1 1

3 3 6 2 1 *

1 * * *

Re sed 1 2 1 2

1 1 1 * * * *

141 127 149 96 81 52 25 19 12 11 2 6 13 Yes 5 6 11 8 2 1 1 1

1 1

1 DK 1 1 * * * * * * * * *

1 Refused 2 1 2 1 *

1 1 * * *

E11Jployment 16 10 16 8 3 5 7 4 3 5 1

3 Full Time 83 82 82 72 50 34 10 11 2 2 6 Part Time 18 11 16 6 10 2 2 3 2

1 1 Not Employed 31 32 48 18 19 12 8 3 4 3 2 3 5 Refused 1 *

1 1 * * * * * * *

Education

19 12 18 10 3 7 8 4 3 5 1

3 < High School 15 24 34 16 16 7 6 2 '1 1 .

2 3 Hi8h School Graduate 60 64 62 45 33 17 6 5 5 3 1 2 8 < ollege 36 22 29 18 23 12 5 6 3 2 1 2 1 Graduate 11 9 12 10 6 8 1 4 * * *

Post raduate 8 4 7 6 2 2 1 *

1 * *

Census Repion Northeas 37 34 34 23 20 10 2 4 2 2

1 2 Midwest 36 28 36 29 15 13 11 8 1 2 1 1 4 South 52 63 60 37 37 21 11 6 7 5 4 7 West 24 10 32 16 11 9 3 3 2 3 2

2 Daw of Week* eekday 95 84 103 63 55 38 17 12 8 8 2* 1 8 Weekena 54 51 59 42 28 15 10 9 4 4 1 5 7 Season Winter 30 47 46 26 21 11 7 6 4 1 2 1 5 Spring 41 36 44 29 10 14 5 5 4 5 1 2 5 Summer 38 23 45 31 33 13 11 5 2 3 2 2 Fall 40 29 27 19 19 15 4 5 2 3

1 3 Asthma No 134 124 150 92' 77 47 24 20 9 9 5 13 Yes 15 9 11 13 6 5 3 1 3 3 1 2 DK

2 1 * .

1 * * * * * *

141 130 157 103 82 48 26 20 12 12 2 5 1.5 Yes 4 3 4 2 1 4 1 1 *

1 1 DK 4 2 1 *

1 * * * * * *

Bronchitis/emphysema No 139 128 150 . 91 75 48 25 20 11 9 3 4 15 Yes 10 5 12 14 8 4 2 1 1 3

2

DK

2 * *

1 * * * * * *

Note: * = Missing Data; DK =Don't know; N = Number of Respondents; Refused = Respondent Refused to Answer. Source: Tsang And Klepeis, 1996.
Table 15-143 Number of Minutes Spent Smoking (minutes/day) Percentiles Category Population Grouo N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 9386 0 0 0 0 0 0 240 615 795 930 1035 1440 Gender Male 4294 0 0 0 0 0 0 310 685 840 983 1095 1440 Gender Female 5088 0 0 0 0 0 0 180 545 725 870 960 1440 Age (years) 1-4 499 0 0 0 0 0 0 75 455 735 975 1095 1440 Age (years) 5-11 703 0 0 0 0 0 0 82 370 625 975 1140 1440 Age (years) 12-17 589 0 0 0 0 0 0 130 377 542 810 864 1260 Age (years) 18-64 6059 0 0 0 0 0 0 345 675 830 950 1045 1440 Age (years) > 64 1349 0 0 0 0 0 0 10 340 622 825 910 1440 Race White 7591 0 0 0 0 0 0 250 630 805 940 1035 1440 Race Black 945 0 0 0 0 0 0 225 540 715 910 1071 1440 Race Asian 157 0 0 0 0 0 0 60 375 494 565 790 800 Race Some Others 182 0 0 0 0 0 0 255 680 815 1140 1305 1328 Race Hispanic 385 0 0 0 0 0 0 175 481 652 813 845 1095 Hispanic No 8534 0 0 0 0 0 0 243 625 800 940 1035 1440 Hispanic Yes 702 0 0 0 0 0 0 175 518 680 850 920 1440 Employment Full Time 4096 0 0 0 0 0 0 360 687 835 945 1005 1440 Employment Part Time 802 0 0 0 0 0 0 295 630 793 930 1054 1440 Employment Not Employed 2644 0 0 0 0 0 0 144.5 555 768 915 1045 1440 Education < High School 834 0 0 0 0 0 0 420 790 880 1004 1105 1440 Education High School Graduate 2612 0 0 0 0 0 5 390 710 840 956 1060 1440 Education <College 1801 0 0 0 0 0 0 288 630 805 945 1045 1435 Education College Graduate 1247 0 0 0 0 0 0 135 480 660 860 970 1140 Education Post Graduate 924 0 0 0 0 0 0 60 380 595 795 860 1205 Census Region Northeast 2075 0 0 0 0 0 0 259 610 775 915 990 1440 Census Region Midwest 2102 0 0 0 0 0 0 255 630 .810 945 1054 1440 Census Region South 3243 0 0 0 0 0 0 275 655 810 950 1060 1440 Census Region West 1966 0 0 0 0 0 0 140 510 710 885 990 1440 Day of Week Weekday 6316 0 0 0 0 0 0 225 595 780 925 1015 1440 Day of Week Weekend 3070 0 0 0 0 0 0 260 651 810 950 1080 1440 Season Winter 2524 0 0 0 0 0 0 210 600 790 930 1034 1440 Season Spring 2438 0 0 0 0 0 0 240 626 785 920 1060 1440 Season Summer 2536 0 0 0 0 0 0 235 600 810 940 1020 1440 Season Fall 1888 0 0 0 0 0 0 285 630 791 945 1020 1440 Asthma No 8629 0 0 0 0 0 0 240 610 790 928 1020 1440 Asthma* Yes 694 0 0 0 0 0 0 270 668 855 1020 1170 1440 Angina No 9061 0 0 0 0 0 0 240 615 795 930 1034 1440 Angina Yes 250 0 0 0 0 0 0 125 615 835 1007.5 1125 1380 Bronchitis/emphysema No 8882 0 0 0 0 0 0 235 605 785 928 1020 1440 Bronchitis/emphvsema Yes 433 0 0 0 0 0 50 405 810 900 1040 1205 1380 Note: N = Doer Sample Size; Percentiles are the Percentage of Doers below or Equal to a Given Number of Minutes. Source: Tsana and Kleneis 1996. Table 15-144 Range of Time Spent Smoking Cigars or Pipe Tobacco by the Number of Respondents Total N Number of Minutes oer Dav *-* 0-3 3-6 6-9 9-12 12-15 15-18 18-61 Overall 62 5 10 8 6 1 2. 9 21 Gender Male 58 5 8 7 6 1 2 9 20 Female 4
2 1 * * *

1 Age (years) 5-11 1 *

1 * * * *

12-17 1 1 * * * * * *

18-64 46 3 10 4 6 1 1 5 16 > 64 14 1

3 *

1 4 5 Race White 53 3 8 7 4 1 1 9 20 Black 5 1 2 1 1 . * * *

Some Others 1 1 * * * * * *

Hispanic 3 * *

1

1

1 Hispanic No 57 5 9 8 5

1 9 20 Yes 5

1

1 1 1

1 Employment

2 1

1 * * * *

Full Time 39 2 7 4 5 1 1 4 15 Part Time 3

3 * * * * *

Not Employed 17 1

3 1

1 5 6 Refused 1 1 * * * * * *

Education

2 1

1 * * * * * < High School 2 * * * *

1

1 High School Graduate 24 2 4 4 3 *

3 8 <College 18 2 4 *

1

4 7 College Graduate 10

2 2 2 *

1 3 Post Graduate 6 *

1 1

1 1 2 Census Region Northeast 20 3 1 4

1

1 10 Midwest 19

4 4 2

1 4 4 South 12 1 3

2

1 1 4 West 11 1 2

2 *

3 3 Day of Week Weekday 40 3 7 5 2 1

7 15 Weekend 22 2 3 3 4

2 2 6 Season Winter 16

3 5 1

1 3 3 Spring 19 3 4 1 1 *

2 8 Summer 19 1 1 1 4 1 1 2 8 Fall 8 1 2 1 * *

2 2 Asthma No 59 5 8 8 6 1 2 8 21 Yes 3

2 * * *

1

Angina No 60 5 10 8 6 1 2 8 20 Yes 2 * * * * *

1 1 Bronchitis/emphysema No 60 4 10 8 6 1 2 8 21 Yes 2 1 * * * *

1

Note:

Signifies missing data; Refused = respondents refused to answer; N = doer sample size in specified range of number of minutes spent. A value of "61" for number of minutes signifies that more than 60 minutes were spent. Source: Tsana and Kleoeis 1996. I I I Table 15-145 Number of Minutes Spent Smoking CiQars or Pipe* Tobacco (minutes/day) Percentiles Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 57 2 3 3 10 20 60 61 61 61 61 61 61 Gender Male 53 .3 5 10 10 20 60 61 61 61 61 61 61 Gender Female 4 2 2 2 2 2.5 9 38 61 61 61 61 61 Age (years) 5-11 1 15 15 15 15 15 15 15 15 15 15 15 15 Age (years) 12-17 0 0 0 0 0 0 0 0 0 0 0 0 0 Age (years) 18-64 43 2 2 3 10 15 45 61 61 61 61 61 61 Age (years) > 64 13 15 15 15 20 45 60 61 61 61 61 61 61 Race White 50 2 2.5 3 }O 20 60 61 61 61 61 61 61 Race Black 4 10 10 10 10 10 15 25 30 30 30 30 30 Race Some Others 0 0 0 0 0 0 0 0 0 0 0 0 0 Race Hispanic 3 30 30 30 30 30 45 61 61 61 61 61 61 Hispanic No 52 2 3 3 10 20 60 61 61 61 61 61 61 Hispanic Yes 5 10 10 10 10 30 40 45 61 61 61 61 61 Employment Full Time 37 2 2 3 10 20 60 61 61 61 61 61 61 Employment Part Time 3 3 3 3 3 3 10 10 10 10 10 10 10 Employment Not Employed 16 15 15 15 20 37.5 60 61 61 61 61 61 61 Education < High School 2 45 45 45 45 45 53 61 61 61 61 61 61 Education High School Graduate 22 2 2 10 10 15 45 61 61 61 61 61 61 Education <College 16 3 3 3 3 25 60 61 61 61 61 61 61 Education College Graduate 10 5 5 5 7.5 20 30 61 61 61 61 61 61 Education Post Graduate 6 20 20 20 20 30 52.5 61 61 61 61 61 61 Census Region Northeast 17 10 10 10 20 20 61 61 61 61 61 61 61 Census Region Midwest 19 2 2 2 3 15 30 60 61 61 61 61 61 Census Region South 11 10 10 10 10 10 45 61 61 61 61 61 61 Census Region West 10 10 10 10 10 30 60 61 61 61 61 61 61 Day of Week Weekday 37 2 2 3 10 20 60 61 61 61 61 61 61 Day of Week Weekend 20 3 3 6.5 10 20 37.5 61 61 61 61 61 61 Season Winter 16 3 3 3 10 15 25 60 61 61 61 61 61 Season Spring 16 2 2 2 5 15 60.5 61 61 61 61 61 61 Season Summer 18 10 10 10 20 30 60 61 61 61 61 61 61 Season Fall 7 3 3 3 3 10 60 61 61 61 61 61 61 Asthma No 54 2 3 10 10 20 60 61 61 61 . 61 61 61 Asthma Yes 3 3 3 3 3 3 5 60 60 60 60 60 60 Angina No 55 2 3 3 10 20 60 61 61 61 61 61 61 Angina Yes 2 60 60 60 60 60 60.5 61 61 61 61 61 61 Bronchitis/emphysema No 56 2 3 3 10 20 60 61 61 61 61 61 61 Bronchitis/emphysema Yes 1 60 60 60 60 60 60 60 60 60 60 60 60 Note: A value of "61" for number of minutes signifies that more than 60 minutes were spent; N = doer sample size. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis 1996.
Table 15-146 Range of Numbers of Cigarettes Smoked Based on the Number of Respondents Total N Number of Ciqarettes Smoked bv Resoondent on the Dav Before the Survev . None 1-2 3-5 6-9 10-14 15-24 25-35 36+ DK Overall 4663 530 3288 45 92 88 182 315 56 57 10 Gender Male 2163 278 1467 24 38 32 81 167 30 43 3 Female 2498 251 1820 21 54 56 101 148 26 14 7 Refused 2 1 1 . . . . . . . . Ag.e (years) 84 2 72 1 1 . 2 3 1 1 1 1-4 263 263 . . . . . . . . . 5-11 348 258 88 . 1 . . 1 .. . . 12-17 326 1 315 . 1 3 2 3 . . 1 18-64 2972 5 2232 42 76 75 156 276 54 51 5 >64 670 1 581 2 13 10 22 32 1 5 3 Race White 3774 413 2664 30 63 63 156 272 54 52 7 Black 463 53 319 7 18 22 17 22 1 1 3 Aian 77 5 71 . . . . 1 . . . Some Others 96 22 55 1 4 1 5 6 1 1 . Hisfuanic 193 37 133 7 5 2 2 7 . . . Re sed 60 . 46 . 2 . 2 7 . 3 . 4244 452 3010 33 79 79 173 297 56 55 10 Yes 347 75 225 11 10 7 7 12 . . . DK 26 2 18 . 2 2 1 1 . . . Refused 46 1 35 1 1 . 1 5 . 2 . E",?ployment 926 526 388 ** 2 3 2 3 . . 2 Full Time 2017 1 1510 34 55 51 100 193 37 34 2 Part Time 379 . 307 5 7 6 23 22 4 3 2 Not Employed 1309 3 1058 6 28 28 57 92 14 20 3 Refused 32 . 25 . . . . 5 1 . 1 Education . 1021 526 473 . 4 3 4 8 . 1 2 < High School 399 3 279 1 9 12 27 42 8 16 2 High School Graduate 1253 1 899 16 44 35 73 138 23 23 1 <College
895 . 696 11 19 20 44 75 18 9 3 College Graduate 650 . 547 11 10 13 26 32 5 *5 1 Post Graduate 445 . 394 6 6 5 8 20 2 3 1 Census Region Northeast 1048 112 747 4 12 19 49 78 10 16 1 Midwest 1036 110 746 11 25 19 29 73 13 8 2 South 1601 193 1079 17 31 34 76 108 29 24 4 West 978 115 716 13 18 16 28 56 4 9 3 oarvotweek eekday

3156 341 2239 28 66 61 116 217 38 43 7 Weekend 1507 189 1049 17 26 27 66 98 18 14 3 Season Winter 1264 163 883 16 23 21 50 71 18 14 5 Spring 1181 148 819 13 22 14 45 94 14 10 2 Summer 1275 142 906 7 20 32 47 89 12 17 3 Fall 943 77 680 9 27 21 40 61 12 16 . Asthma No 4287 480 3023 40 85 80 171 292 51 56 .9 Yes 341 48 239 5 6 8 10 18 5 1 1 DK . 35 2 26 . 1 . 1 5 . .. . 4500 526 3161 45 88 85 175 304 52 54 10 Yes 125 2 99 . 3 3 5 8 3 2 . DK 38 2 28 . 1 . 2 3 1 1 .. Bronchitis/emphysema No 4424 519 3138 43 80 81 170 284 48 52 9 Yes 203 11 120 2 11 6 11 28 8 5 1 DK 36 . 30 . 1 1 1 3 . . . Note: * = Missing Data; DK = Don't Know; N:... Number of Respndents; Refused = Respondent Refused to Answer Source: Tsang and Klepeis, 1996.
Table 15-147 Range of Number of Cigarettes Smoked by Other People Based on Number of Respondents Total N Number of Cigarettes Smoked By Others . None 1-2 3-5 6-9 10-14 15-24 25-35 36+ DK Overall 4723 898 3209 55 108 78 122 121 19 28 85 Gender Male 2131 468 1403 21 35 39 61 46 11 12 35 Female 2590 428 1806 34 73 39 61 75 8 16 50 Refused 2* 2 . . * . . . . . . Ag.e (years) 103 11 82 . 2 .
3 . 1 4 1-4 236 236 * . * . . . . . . 5-11 355 355 . . . . . . . . . 12-17 263 263 . . . . . . . . . 18-64 3087 32 2506 46 97 74 116 109 16 24 67 >64 679 1 621 9 9 4 6 9 3 3 14 Race White 3817 675 2616 42 89 70 106 107 18 24 70 Black 482 119 309 7 8 6 9 9 1 2 12 Asian 80 21 57 1 . . 1 . . . . Some Others 86 29 51 . . 1 3 1 . 1 . Hispanic 192 50 120 5 9 1 3 1 . 1 2 Refused 66 4 56 . 2 . . 3 . . 1 4290 796 2928 49 91 73 114 118 19 25 77 Yes 355 95 223 5 15 3 7 1 . 1 5 DK 21 4 11 1

1 1 . . 2 1 Refused 57 3 47 . 2 1 . 2 . . 2 E11Jployment 847 845 2 . . . * . . . . Full Time 2079 . 1740 28 64 50 73 59 9 10 46 Part Time 423 21 336 6 15 4 14 11 1 3 12 Not Employed 1335 30 1098 21 28 24 35 48 9 15 27 Refused 39 2 33

1 . . 3 * *

Education . 947 897 44 . 1 . . 4 . . 1 < High School 435 . 336 6 18 9 17 16 4 10 19 High School Graduate 1359 . 1097 25 38 40 47 62 9 9 32 <College 906 1 748 10 29 22 36 22 5 9 24 College Graduate 597 . 536 9 15 5 17 11 . . 4 Post Graduate 479 . 448 5 7 2 5 6 1 . 5 Census Region Northeast 1027 201 690 14 29 18 14 32 3 4 22 Midwest 1066 196 726 15 28 13 27 25 4 7 25 South 1642 320 1090 17 36 33 58 44 7 15 22 West 988 181 703 9 15 14 23 20 5 2 16 eekday 3160 596 2178 33 76 54 77 69 12 14 51 Weekend 1563 302 1031 22 32 24 45 52 7 14 34 Season Winter 1260 266 841 17 . 23 19 29 34 7 -6 18 Spring 1257 270 821 14 35 22 27 32 4 10 22 Summer 1261 240 863 13 25 18 35 30 3 6 28 Fall 945 122 684 11 25 19 31 25 5 6 17 Asthma No 4342 802 2989 52 97 69 117 104 15 22 75 Yes 353 95 196 3 10 9 5 16 4 6 9 DK 28 1 24 . 1 . . 1 . . 1 4561 894 3068 53 104 78 121 116 19 26 82 Yes 125 1 110 2 3

1 4

2 2 DK 37 3 31 . 1 * . 1 . . 1 Bronchitis/emphysema No . 4458 875 3016 53 99 75 115 108 17 23 77 Yes 230 21 163 2 8 3 7 12 2 5 7 DK 35 2 30 . 1 . . 1 . . 1 Note: * = Missing Data; DK =Don't know; N = Number of Respondents; Refused = Respondent Refused to Answer. Source: Tsang And Klepeis, 1996.
Table 15-148 Range of the Number of Cigarettes Smoked While at Home Based on the Number of Respondents Total N Number of Cigarettes Smoked by Respondent at Home . None 1-2 3-5 6-9 10-14 15-24 25-35 36+ DK Overall 4723 516 3358 51 193 126 224 180 23 29 23 Gender Male 2131 277 1463 24 86 53 91 98 11 17 11 Female 2590 237 1895 27 107 73 133 82 12 12 12 Refused 2 2 * * * * * * * *
Ag.e (years) 103 8 83

2 4 1 2 1

2 1-4 236 236 * * * * * * * *

5-11 355 268 86 * *

1 * * *

12-17 263 2 248

6 2 3 1 1 *

18-64 3087 1 2352 . 47 170 110 193 150 21 26 17 > 64 679 1 589 4 15 10 26 27 0 3 4 Race White 3817 391 2700 30 152 103 208 164 22 28 19 Black 482 61 345 10 27 20 9 6 1

3 Asian 80 13 65

2 * * * * *

Some Others 86 17 58 1 3 1 2 3

1 * 'Hispanic 192 32 140 8 3 2 3 4 * *

Refused 66 2 50 2 6

2 3 *

1 Hispanic No 4290 451 3Q45 41 182 121 210 167 23 29 21 Yes 355 64 252 8 4 5 10 11 *

1 DK 21

18

1

2 . * *

Refused 57 1 43 2 6 . 2 2 * . 1 E":!ployment 847 514 322

5 1 3 1 1 . . Full Time 2079 1 1598 33 122 88 117 87 11 10 12 Part Time 423

346 4 17 10 27 12 3 3 1 Not Employed 1335 1 1060 14 47 27 76 78 7 16 9 Refused 39 . 32

2 . 1 2 1 . 1 Education . 947 514 406 1 9 3 6 4 2 . 2 < High School 435

309 5 20 17* 32 26 7 12 7 High School Graduate 1359

989 21 78 64 98 84 7 11 7 <College 906 2 701 17 51 25 56 39 4 5 6 College Graduate 597 . 524 6 20 11 19 13 2 1 1 Post Graduate 479

429 1 15 6 13 14 1 *

Census Region Northeast 1027 121 721 11 39 22 50 46 8 5 4 Midwest 1066 102 764 12 52 32 53 33 5 7 6 South 1642 177 1159 16 62 51 81 63 8 14 11 West . 988 116 714 12 40 21 40 38 2 3 2 Day of Week Weekday 3160 336 2277 32 129 87 134 118 14 18 15 Weekend 1563 180 1081. 19 64 39 90 62 9 11 8 Season Winter 1260 153 873 18 53 39 59 42 10 6 7 Spring 1257 152 901 7 51 22 55 54 1 6 8 Summer 1261 139 896 10 44 33 64 53 7 10 5 Fall 945 72 688 16 45 32 46 31 5 7 3 Asthma No 4342 470 3100 45 176 112 208 165 20 25 21 Yes 353 46 234 5 15 14 16 15 3 4 1 DK 28 . 24 1 2 . . * . . 1 Angina No 4561 515 3225 49 188 123 217 173 23 26 22 Yes 125

104 1 2 3 5 7

3

DK 37 1 29 1 3

2 * *

1 No 4458 501 3179 46 179 121 210 159 21 20 22 Yes 230 15 149 4 12 5 14 20 2 9 * ' DK 35

30 1 2 *

1 *

1 Note: * = Missing Data; DK =Don't Know; N= Number of Respondents; Refused = Respondent Refused to Answer Source: Tsang and Klepeis, 1996.
Table 15-149. Differences in Time Use (hours/week)* Grouped by Sex, Employment Status, and Marital Status for the Surveys Conducted in 1965 and 1975 Employed Men Employed Women Housewives Total Urban Data Married Single Married Single Married Single 1965 (N=448) (N=73) (N=190) (N=152) (N=341) (N=14) (N=1218) Sleep 53.1 50.6 53.8 52.6 53.9 58.8 53.3 Work for Pay 51.3 51.4 38.4 39.8 0.5 1.6 33.0 Family Care 9.0 7.7 28.8 20.6 50.0 45.7 25.4 Personal Care 20.9 22.2 20.3 21.7 22.6 23.0 21.5 Free Time 33.7 36.1 26.7 33.3 41.0 38.9 34.8 Organizations 2.6 3.6 1.4 3.7 3.4 3.4 2.8 Media 17.1 13.9 10.7 11.1 15.3 19.1 14.7 Social Life 7.2 10.4 7.9 9.6 12.6 10.2 9.4 Recreation 1.4 1.3 0.6 0.5 0.6 1.1 0.9 Other Leisure 5.4 6.9 6.1 8.4 9.1 5.1 7.0 Total Time 168.0 168.0 168.0 168.0 168.0 168.0 168.0 (Free) (33.7) (36.1) (26.7) (33.3) (41.0) (38.9) (34.8) 1975 (N=245) (N=87) (N=117) (N=108) (N=141) (N=28) (N=726) Sleep 53.4 54.1 55.1 54.3 56.8 58.6 54.7 Work for Pay 47.4 40.0 30.1 38.8 1.1 0.0 32.5 Family Care 9.7 9.0 24.9 16.6 44.3 42.8 20.5 Personal Care 21.4 20.0 26.2 21.9 21.4 19.2 21.8 Free Time 36.1 44.9 31.7 36.4 44.4 47.4 38.5 Organizations 3.7 4.8 1.1 4.4 4.8 3.0 3.8 Media 18.9 18.5 15.6 14.5 20.4 27.2 18.2 Social Life 6.4 8.9 6.6 8.9 10.1 9.1 7.8 Recreation 1.3 4.1 0.8 0.5 0.7 0.4 1.3 Other Leisure 5.8 8.6 6.5 8.1 8.4 7.7 7.4 Total Time 168.0 168.0 168.0 168.0 168.0 168.0 168.0 (Free) (36.1) (44.9) (31.7) (36.4) (44.4) (!J-7.4) (38.5) a Data weighted to ensure equal days of the week. Source: Robinson, 1977. Table 15-150. Time Use (hours/week)" Differences by Age for the Surveys Conducted in 1965 and 1975 Mean Duration lhrs/wk) , Age Group (years) . 18-25 25-35 36-45 46-55 '56-65 1965 1975 1965 1975 1965 1975 1965 1975 1965 1975 Activity IN=200l IN=149\ IN=321\ IN=234\ IN=306) IN=150l IN=252\ IN=141) IN=156) IN=111) Sleep 54.2. 55.4 52.5 53.9 53.1 54.7 53.9 55.4 53.6 56.0 Work for Pay 32.6 27.0 29.2 33.4 33.1 34.4 33.4 31.0 35.9 20.4 Family Care 21.2 15.3 30.4 21.6 25.4 20.4 24.9 23.2 20.4 23.2 Personal Care 20.9 20.3 20.3 20.8 22.5 21.1 22.4 23.1 20.9 26.6 Free Time 39.1 50.0 35.6 38.4 33.8 37.3 33.4 35.2 37.1 41.8 Organizations 4.8 8.4 3.0 4.2 3.0 3.3 2.0 3.1 2.9 3.2 Media 13.8 18.5 14.6 17.2 14.5 18.3 15.3 18.8 17.4 22.6 Social Life 11.3 10.7 10.3 8.7 8.4 7.8 8.6 5.4 8.1 6.2 Recreation 0.9 2.6 1.2 1.3 0.8. 1.0 0.6 1.3 1.1 1.3 Other Leisure 8.3 9.8 6.5 7.0 7.1 6.9 6.9 6.6 7.6 8.5 Total Time Free 168.0 168.0 168.0 168.0 168.0 168.0 168.0 168.0 168.0 168.0 Time (39.1) (50.0) (35.6) (38.4) (33.8) (37.3) (33.4) (35.2) (37.1) *(41.8)
~~Data weighted to ensure equal days of the week. Source: Robinson, 1977.~~
Table 15-151. Time Use (hours/week)* Differences by Education for the Surveys Conducted in 1965 and 1975 Mean duration (hours/week) Age Group (in years) 0-8 9-11 12 13-15 16+ 1965 1975 1965 1975 1965 1975 1965 1975 1965 1975 Activity <N=171l (N=75) (N=220l (N=114l (N=452l (N=319l (N=195) (N=137) (N=191) (N=144) Sleep 54.9 57.0 52.3 53.7 53.0 55.5 53.6 53.6 53.6 54.8 Work for Pay 31.6 30.0 33.1 32.0 30.9 26.9 34.4 27.5 34.5 38.0 Family Care 24.7 18.7 25.4 21.7 28.9 n5 21.7 18.9 21.2 16.8 Personal Care 20.8 22.9 20.9 22.0 21.1 22.1 21.7 10.5 22.7 22.3 Free Time 35.9 39.4 36.1 38.6 34.1 40.0 36.5 47.5 35.9 36.1 Organizations 1.8 3.0 1.5 2.2 2.5 3.7 5.8 9.1 4.7 4.1 Media 19.3 18.0 16.5 20.7 14.2 19.0 13.3 19.7 12.5 16.2 Social Life 7.7 8.4 9.8 7.9 9.5 8.5 9.0 7.7 10.2 8.1 Recreation 0.9 1.3 1.4 0.7 0.7 1.3 1.1 2.0 0.9 1.3 other Leisure 6.3 8.7 7.0 7.1 7.2 7.5 7.4 9.0 7.7 6.4 Total Time 168.0 168.0 168.0 (36.2) 168.0 168.0 168.0 168.0 (36.6) 168.0 168.0 (36.0) 168.0 (36.1) Free Time (36.0) (39.4) (38.6) (34.1) (40.0l (47.5) a Data weighted to ensure equal days of the week. Source: Robinson, 1977. Table 15-152. Time Use (hours/week)* Differences by Race for the Surveys Conducted in 1965 and 1975 Mean duration (hours/week) White Black 1965 1975 1965 1975 <N = 1030\ (N = 680). (N = 103) (N=77) Activity Category Sleep 53.4 54.5 50.9 54.8 Work for Pay 31.9 30.0 36.6 30.0 Family Care 26.0 21.1 23.6 17.6 Personal Care 21.8 22.1 20.0 21.0 Free Time 34.9 40.3 36.9 44.6 Organizations 2.8 4.4 3.0 4.9 Media 14.8 18.7 15.7 19.6 Social Life 9.3 8.2 9.1 9.8 Recreation 1.1 1.5 0.6 0.4 Other Leisure . 6.9 7.5 8.4 9.9 Total Time
~~168.0 168.0 168.0 168.0 Free Time (34.9) (40.3\ (36.8) (44.6) a Data weighted to ensure equal days of the week. Source: Robinson 1977.~~
Table 15-153. Mean Time Spent (hours/week)' in Ten Major Activity Categories Grouped by Regions Totalb N=975 Activity West North Central Northeast South Mean S.D.' N=200 N=304 N=185 N=286 Activity Actegtory Market Work 23.44 29.02 27.34 24.21 26.15 23.83 House/yard work 14.64 14.17 14.29 15.44 14.66 . 12.09 Child care 2.50 2.82 2.32 2.66 2.62 5.14 Services/shop 5.22 5.64 4.92 4.72 5.15 5.40 Personal care 79.23 76.62 78.11 79.38 78.24 12.70 Education 2.94 1.43 0.95 1.45 1.65 6.34 Organizations 3.42 2.97 2.45 2.68 2.88 5.40 Social 8.26 8.42 8.98 8.22 8.43 8.17 entertainment Active leisure 5.94 5.28 4.77 5.86 5.49 7.81 Passive leisure 22.47 21.71 23.94 23.47 22.80 13.35 Total Time 168.00 168.00 168.00 168.00 168.00 0.09 a Weighted for day of week, panel loss (not defined in report), and correspondence to Census. Data may not"add to totals shown due to rounding. b N =surveyed population. ' S.D. = standard deviation. Source: Hill 1985. Table 15-154. Total Mean Time Spent (minutes/day) in Ten Major Activity Categories Grouped by Type of Day Time Duration (mins/day) Weekday Saturday Sunday [N" = 8311 fN = 8311 fN = 8311 Activity Category Market Work 288.0 (257.7)b 97.9 (211.9) 58.0 (164.8) House/Y ardwork 126.3 (119.3) 160.5 (157.2) 124.5 (133.3) Child Care 26.6 (50.9) 19.4 (51.5) 24.8 (61.9) Services/Shopping 48.7 (58.7) 64.4 (92.5) 21.6 (49.9) Personal Care 639.2 (114.8) 706.8 (169.8) 734.3 (156.5) Education 16.4 (64.4) 5.4 (38.1) 7.3 (48.0) Organizations 21.1 (49.7) 18.4 (75.2) 58.5 (104.5) Social Entertainment 54.9 (69.2) 1,114.1 (156.0) 110.0 (151.2) *Active Leisure 37.9 (71.11) 61.4 (126.5) 64.5 (120.6) Passive Leisure 181.1 (121.9) 191.8 (161.6) 236.5 (167.1) Total Time 1,440 1,440 1,440 a N = Number of respondents. b () = Numbers in parentheses are standard deviations. Source: Hill, 1985. Table 15-155. Mean Time Spent (minutes/dav) in Ten Maior Activity Categories Durinq Four Waves of Interviews* Fall Winter Spring Summer Range of (Nov. 1, 1975)b (Feb. 28, 1976)' (June 1, 1976)' (Sept. 21, 1976)b Standard N=861 N=861 N=861 Deviations Activity Category Wave 1 Wave2 Wave3 Wave4 Market work 222.94 226.53 210.44 230.92 272-287 House/yard work 133.16 135.58 143.10 119.95 129-156 Child care 25.50 22.44 25.51 21.07 49-58 Services/shop 48.98 44.09 44.61 47.75 76-79 Personal care 652.95 678.14 688.27 674.85 Education 22.79 12.57 2.87 10.76 32-93 Organizations 25.30 22.55 23.21 29.91 68-87 Social entertainment 63.87 67.11 83.90 72.24 102-127 Active leisure 42.71 47.46 46.19 42.30 96-105 Passive leisure 210.75 183.48 171.85 190.19 144-162 Total Time 1440.00 1440.00 1440.00 1440.00 --a Weighted for day of week, panel loss (not defined in report), and correspondence to Census. b Dates by which 50% ofthe interviews for each wave were taken. Source: Hill 1985. Table 15-156. Mean Time Spent (hours/week) inTen Major Activity Categories Grouped by Gender" Time duration (hours/week) Men Women Men and Women n = 140 n = 561 n = 971 . Activity Category Market work 35.8 (23.6)b 17.9 (20.7) 26.2 (23.8) House/yard 8.5 (9.0) 20.0 (11.9) 14.7 (12.1) Child care 1.2 (2.5) 3.9 (6.4) 2.6 (5.2) Services/shop 3:9 (4.5) 6.3 (5.9) 5.2 (5.4) Personal care 77.3 (13.0) 79.0 (12.4) 78.2 (12.7) Education 2.3 (7.7) 1.1 (4.8) 1.7 (6.4) Organizations 2.5 (5.5) 3.2 (5.3) 2.9 (5.4) Social entertainment 7.9 (8.3) 8.9 (8.0) 8.4 (8.2) Active leisure 5.9 (8.2) 5.2 (7.4) 5.5 (7.8) Passive 22.8 (14.1) 22.7 (12.7) 22.8 (13.3) Total time 168.1 168.1 168.1
~~Detailed components of activities (87) are presented in Table 1A-4. b ( ) = Numbers in are standard deviations. Source: Hill, 1985.~~
Table 15-157. Percent Responses of Children's "Play" (activities) Locations in Maryvale, Arizona* Location Percent Responses Ranking of Children's "Play" Locations' Preschool Primary Grades (K-3) lntennediate Grades n = 211 n =45 (4-6) n =66 Residential Yards 143b 124b 132b Residential (Own and Others) School Playgrounds 0 53 52 Parks and Recreation Areas Parks and Recreation Areas 42 53 33 Street/Path/Alley Commercial 2 24 27 NaturalNacant Areas Industrial 0 0 2 School Institutional 1 2 0 Institutional Streets 3 24 41 Commercial Alleys 1 2 9 Parking Lots Parking Lots 0 9 9 Child Built Places Vacant Lots/Canals/Fields 1 7 8 Water Industrial a Survey was conducted in Maryvale (West Central Phoenix), Arizona. b Percentages greater than 100, because many children played in more than one location. ' Ranking of children's activity locations were obtained from other literature sources. Source: Sell, 1989. Table 15-158. Occupational Tenure of Employed lndividuals8 by Age and Sex Median Tenure (years) Aae Group (vears) All Workers Men Women 16-24 1.9 2.0 1.9 25-29 4.4 4.6 4.1 30-34 6.9 7*.6 6.0 35-39 9.0 10.4 7.0 40-44 10.7 13.8 8.0 45-49 13.3 17.5 10.0 50-54 15.2 20.0 10.8 55-59 17.7 21.9 12.4 60-64 19.4 23.9 14.5 65-69 20.1 26.9 15.6 70 and older 21.9 30.5 18.8 Total 6.6 7.9 5.4 a Working population = 109.1 million persons Source: Carev 1988. Table 15-159. Occu ational Tenure for Emplo ed Individuals" Grau ed by Sex and Race White Black His anic Race All Individuals 6.7 5.8 4.5 a Working population = 109.1 million persons. Source: Care 1988. Median Tenure (Years) Men 8.3 5.8 5.1 Women 5.4 5.8 3.7 Table 15-160. Occupational Tenure for Employed lndividuals8 Grouped by Sex and Employment Status Median Tenure (Years) Emolovment Status All Individuals Men Women Full-Time 7.2 8.4 5.9 Part-Time 3.1 2.4 3.6 a Working population = million persons. Source: Carev. 1988. Table 15-161. Occupational Tenure of Employed lndividualsa Grouped by Maior Occupational Groups and Aqe Median Tenure-(years) Occupational Group Age Group Totalb 16-24 25-34 35-44 45-54 . 55-64 65+ Executive, Administrative, and Managerial 8.4 2.4 5.6 10.1 15.1 17.9 26.3 Professional Specialty 9.6 2.0 5.7 12.0 18.2 25.6 36.2 Technicians and Related Support 6.9 2.2 5.7 10.9 17.7 20.8 22.2 Sales Occupations 5.1 1.7 4.7 7.7 10.5 15.5 21.6 Administrative Support, including Clerical 5.4 2.1 5.0 7.6 '10.9 14.6 15.4 Service Occupations 4.1 1.7 4.4 6.9 9.0 10.6 10.4 Precision Production, Craft, and Repair
9.3 2.6 7.1 13.5 19.9 25.7 30.1 Operators, Fabricators, and Laborers 5.5 1.7 4.6 9.1 13.7 18.1 14.7 Farminq, Forestry, and Fishing 10.4 2.9 7.9 13.5 20.7 30.5 39.8 a Working population = 109.1 million persons. b Includes all workers 16 years and older Source: Carey, 1988.
Table 15-162. Voluntary Occupational Mobility Rates for Workers8 Age 16 Years and Older Age Group (years) Occupational Mobility Rateb (Percent) 16-24 12.7 25-34 6.6 35-44 4.0 45-54 1.9 55-64 1.0 64 and older 0.3 Total, aQe 16 and older 5.3 a Working population = 109.1 million persons. b Occupational mobility rate = percentage of persons employed in an occupation who had voluntarily entered it from another occupation. Source: Carev, 1990. Table 15-163. Values and Their Standard Errors for Average Total Residence Time, T, for Each Group in Survey8 Average total Households (percent) . residence time S.D.ST Average current Households T (years) residence 1985 1987 TcR (years) All households 4.55 +/- 0.60 8.68 10.56+/-0.10 100.0 100.0 Renters 2.35+/-0.14 4.02 4.62+/-0.08 36.5 36.0 Owners 11.36+/-3.87 13.72 13.96+/-0.12 63.5 64.0 Farms 17.31+/-13.81 18.69 18.75+/-0.38 2.1 1.9 Urban 4.19+/-0.53 8.17 10.07+/-0.10 74.9 74.5 Rural 7.80+/-1.17 11.28 12.06+/-0.23 25.1 25.5 Northeast region 7.37+/-0.88 11.48 12.64+/-0.12 21.2 20.9 Midwest region 5.11+/-0.68 9.37 11.15+/-0.10 25.0 24.5 South region 3.96+/-0.47 8.03 10.12+/-0.08 34.0 34.4 West region 3.49+/-0.57 6.84 8.44+/-0.11 19.8 20.2 8Values of the average current residence time, TcR* are given for comparison. Source: Israeli and Nelson, 1992. Table 15-164. Total Residence Time, t (years), Corresponding to Selected Values of R(t)" by Housing Category R(t) = 0.05 0.1 0.25 0.5 0.75 All households 23.1 12.9 3.7 1.4 0.5 Renters 8.0 5.2 2.6 1.2 0.5 Owners -41.4 32.0 17.1 5.2 1.4 Farms 58.4 48.3 26.7 10.0 2.4 Urban 21.7 10.9 3.4 1.4 0.5 Rural 32.3 21.7 9.1 3.3 1.2 Northeast region 34.4 22.3 7.5. 2.8 1.0 Midwest region 25.7 15.0 . 4.3 1.6 0.6 South region 20.7 10.8 3.0 1.2 0.4 West region 17.1 8.9 2.9 1.2 0.4 a R(t) =fraction of households living in the same residence fort years or more. Source: Israeli and Nelson, 1992. Table 15-165. Residence Time of Owner/Renter Occupied Units Year household moved into unit Total occupied units (numbers in thousands) 1990-1994 24,534 1985-1989 27,054 1980-1984 10,613 1975-1979 9,369 1970-1974 6,233 1960-1969 7,933 1950-1959 4,754 1940-1949 1,772 1939 or earlier 885 Total 93,147 Source: U.S. Bureau of the Census, 1993b. Table 15-166. Percent of Householders Living in Houses for Specified Ranges of Time Years lived in current home Percent of total households 0-4 26.34 5-9 29.04 10-14 11.39 15-1.9 10.06 20-24 6.69 25-34 8.52 35-44 5.1 54 1.9 > 55 0.95 Totala 99.99 a Total does not equal 100 due to rounding errors. Source: Adapted from U.S. Bureau of the Census, 1993b. Table 15-167. Descriptive Statistics for Residential Occupancy Period Residential occupancy period (years) Both genders Males only Females only N" = 500,000 N = 244,274 N = 255,726 Statistic 11.7 11.1 12.3 Mean 2 2 2 5th percentile 2 2 2 1 Oth percentile 3 4 5 25th percentile 9 8 9 5oth percentile 16 15 17 75th percentile 26 24 28 90th percentile 33 31 35 95th percentile 41 39 43 98th percentile 47 44 49 99th percentile 51 48 53 99.5th percentile 55 53 58 99.8th percentile 59 56 61 99.9th percentile 75 73 75 Second largest value 87 73 87 Largest value a = Number of simulated persons Source: Johnson and Caoel, 1992. Table* 15-168. Descriptive Statistics for Both Genders by Current Age Residential occupancy period (years) Current Percentile age, years Mean 25 50 75 90 95 99 3 6.5 3 5 8 13 17 22 6 8.0 4 7 10 15 18 22 9 8.9 5 8 12 16 18 22 12 9.3 5 9 13 16 18 23 15 9.1 5 8 12 16 18 23 18 8.2 4 7 11 16 19 23 21 6.0 2 4 8 13 17 23 24 5.2 2 4 6 11 15 25 27 6.0 3 5 8 12 16 27 30 7.3 3 6 9 14 19 32 33 8.7 4 7 11 17 23 39 36 10.4 5 8 13 21 28 47 39 12.0 5 9 15 24 31 48 42 13.5 6 11 18 27 35 49 45 15.3 7 13 20 31 38 52 48 16.6 8 14 22 32' 39 52 51 17.4 9 15 24 33 39 50 54 18.3 9 16 25 34 40 50 57 19.1 10 17 26 35 41 51 60 19.7 11 18 27 35 40 51 63 20.2 11 19 27 36 41 51 66 20.7 12 20 28 36 41 50 69 21.2 12 20 29 37 42 50 72 21.6 13 20 29 37 43 53 75 21.5 13 20 29 38 43 53 78 21.4 12 19 29 38 44 53 81 21.2 11 20 29 39 45 55 84 20.3 11 19 28 37 44 56 87 20.6 10 18 29 39 46 57 90 18.9 8 15 27 40 47 56 All aaes 11.7 4 9 16 26 33 47 Source: Johnson and Caoel 1992. Table 15-169. Summary of Residence Time of Recent Home Buyers (1993) Number of years lived in prev_ious house Percent of Respondents 1 *year or less 2 2-3 16 4-7 40 8-9 10 10 years or* more 32 Source: NAR, 1993 Table 15-170. Tenure in Previous Home (Percentage Distribution) Percent 1987 1989 1991 1993 One year or less 5 8 4 2 2-3 Years 25 15 21 16 4-7 Years 36 22 37 40 8-9 Years 10 11 9 10 10 or More Years 24 34 29 32 Total 100 100 100 100 Median* 6 6 6 6 Source*: NAR, 1993 Table 15-171. Number of Miles Moved (Percentage Distribution) First-Time Repeat Buyer New Home Existing Home All Bu ers Bu er Bu er Bu er Miles Percent Less than 5 miles 29 33 27 23 31 5 to 9 miles 20 25 16 18 20 1 0 to 19 miles 18 20 17 20 17 20 to 34 miles 9 11 8 12 9 35 to 50 miles
2 2 2 2 3 51 to 100 miles 5 2 6 6 4 Over 100 miles 17 6 24 19 16 Total 100 100 100 100 100 Median 9 8 11 11 8 Mean 200 110 270 230 190 Source: NAR, 1993 Table 15-172. Confidence in Activity Patterns Recommendations Considerations Rationale RatinQ TIME SPENT INDOORS VS. OUTDOORS Study Elements . Level of peer review The studies received high level of peer review. High . Accessibility The studies are widely available to the public. High . Reproducibility The reproducibility of these studies is left to question. Evidence has shown Medium that activities have tended to shift over the past decade since the studies were published, due to economic conditions and technological developments, etc. Thus, it is assumed there would be differences in reproducing these results. However; if data were reanalyzed in the same manner the results are expected to be the same. . Focus on factor of The study focused on general activity patterns. One study delineated High interest between indoor and outdoor use of time but in many cases the locations were specified. Thus, any assumptions were made about the indoor or outdoor location where event took place. . Data pertinent to US The studies focused on the U.S. population and California. High . Primary data One study analyzed data from a two primary studies. Data from the High remaining study was collected to via questionnaires and interviews. . Currency The studies were published in 1985 (data was collected 1981-1982), 1987, Medium 1991 (data was collected 1987-1990) and 1992. . Adequacy of data In one study, households were sampled 4 times during 3 month intervals from High collection period February to December, 1981. Robinson's data was based on 1) the CARB Study where data was collected October 1987 to August 1988; and 2) the National Study where data was collected January through December 1985. . Validity of approach The approach used to collect data was direct and included questionnaires or High interviews. Responses where based on diaries and 'mailback' surveys based on what the person planned to do the following day (the "tomorrow approach"). A 24 hour diary was used in another study. . Study size The study sizes ranged from 922 to 5,000 depending on the sub-group High considered. . Representativeness of Timmer focused on activities of children. Robinson studies activities of both High the population children and adults. The studies are representative of the US population and California State. . Characterization of Variability was characterized by age, gender, and day of the week; location of Medium variability activities and various age categories for children. There was no mention of race and no socio-economic characterizations made. . Lack of bias in study Biases noted were sampled during time when children were in school Medium design (high rating is (activities during vacation time are not represented); activities in the 1980's desirable) may different than they are now; . Measurement error Measurement or recording error may occur since the diaries were based on Medium recall (in most cases a 24 hour recall). Other Elements . Number of studies Two High . Agreement between Difficult to compare due to varying categories of activities and the unique age Not researchers distributions found within each study. Ranked Overall Ratina Medium Table 15-172. Confidence in Activity Patterns Recommendations (continued) Considerations Rationale Ratina TIME SPENT IN A VEHICLE Elements . Level of peer review The study received high level of peer review. High . Accessibility The study is widely available to the public. High . Reproducibility The reproducibility of these studies is left to question. Evidence has shown Medium that activities have tended to shift over the past decade since the studies were published, due to economic conditions, technological developments, etc. Thus, it is assumed there would be differences in reproducing these results. . Focus on factor of The study focused specifically focused on time spent in vehicle. High interest . Data pertinent to US The studies focused on the U.S. population and California. High . Primary data Robinson's study analyzed data from two primary studies, thus it secondary High data. . Currency The studies were published in 1985 (data was collected 1981-1982), 1987, Medium 1991 (data was collected 1987-1990) and 1992. . Adequacy of data In one study, households were scimpled 4 times during 3 month intervals from High collection period February to December, 1981. Robinson's data was based on 1) the Wiley et al. (1991) Study where data was collected October 1987 to August 1988; and 2) the National Study where data was collected January through December 1985. . Validity of approach The approach used to collect primary data was based on diary entries High recorded the previous day with follow-up telephone interviews. Another study collected time diary data via mailback of questionnaires, telephone interviews. 'Mailback' surveys were based on the "tomorrow approach" where person knew they were to record in diaries in advance. . Study size The study sizes ranged from 922 to 5,000 depending on the sub-group High considered. . Representativeness of The studies are representative of the US population and California State. High the population . Characterization of Variability was characterized by age, gender, and day of the week. There was Medium variability no mention of race and no socio-economic characterizations made. . Lack of bias in study Both studies lacked time distributions and were based on short-term data. Medium design (high rating is Wiley et al. (1991) data was based recall, is limited to California's population, desirable) and only considered English speaking households. . Measurement error Measurement or recording error may occur when diaries were based on 24 Medium hr recall. Other Elements . Number of studies One secondary study analyzing two primary studies Medium . Agreement between Similar activity patterns were found in both studies. High researchers Overall Medium Table 15-172. Confidence in Activity Patterns Recommendations (continued) Considerations TIME SPENT SHOWERING Study Elements

Level of peer review

Accessibility

Reproducibility

Focus on factor of

interest Rationale The study received high level of peer review. Currently, raw data are available to on'ly EPA. It is not known when data will be publicly available. Results are reproducible. The study focused specifically focused on time spent showering. Ratin!:l High Low High High

Data pertinent to US The study focused on the U.S. general population. High

Primary data The study was based on primary data. High

Currency The study was published in 1996. High '

Adequacy of data The data were collected between October 1992 and September 1994. High collection period

Validity of approach The study used a valid methodology and approach which, in addition to 24-High hour diaries, collected information on temporal conditions and demographic data such as geographic location and socioeconomic status for various U.S. subgroups.

Study size Study consisted of 9,386 total participants.. High

Representativeness of The data were representative of the U.S. population. the population

Characterization of variability

Lack of bias in study design (high rating is desirable)

Measurement error Other Elements

Number of studies

Agreement between researchers Overall Ratinci The study provides a distribution on showering duration. The study includes distributions for showering duration. Study is based on short-term data. Measurement or recording error may occur because diaries are based on 24-hour recall. One; the study was a national study. Recommendation is based on only one study but it is a widely accepted study and average value is comparable to a second key study. High High High Medium Low High Hicih Table 15-172. Confidence in Activity Patterns Recommendations (continued) Considerations Rationale Ratina TIME SPENT BATHING Study Elements

Level of peer review The study received high level of peer review. High

Accessibility Currently, raw data are available to only EPA. It is not known when data will Low be publicly available.

Reproducibility Results can be reproduced or methodology can be followed and evaluated High provided comparable economic and social conditions exists.

Focus on factor of The survey collected information on duration and frequency of selected High interest . activities and time spent in selected micro-environments.

Data pertinent to US The data represents the U.S. population. High

Primary data The study was based on primary data. High

Currency The study was published in 1996. High

Adequacy of data Tlie data were collected between October 1992 and September 1994. High collection period

Validity of approach The study used a valid methodology and approach which, in addition to 24-High hour diaries, collected fnformation on temporal conditions and demographic data such as geographic location and socioeconomic status for various U.S. subgroups. Responses were weighted according to this demographic data.

Study size The study consisted of 9,386 total participants. High

Representativeness of The studies were based on the U.S. population. the population

Characterization of variability

Lack of bias in study design (high rating is desirable)

Measurement error Other Elements

Number of studies

Agreement between researchers Overall Ratina The study provided data that varied across geographic region, race, gender, employment status, educational level, day of the week, seasonal conditions, and medical conditions of respondent.. The study includes distributions for bathing duration. Study is based on short-term data. Measurement or recording error may occur because diaries were based on 24-hour recall. One; the study was based on one, primary, national study. Recommendation was based on only one study. High High Medium Medium Low Not Ranked Hiah Table 15-172. Confidence in Activity Patterns Recommendations (continued) Considerations Rationale Ratinq SHOWER AND BATHING FREQUENCY Study Elements . Level of peer review The study received high level of peer review. High . Accessibility

Currently, raw data is available to only EPA. It is not known when data will be Low publicly available. . Reproducibility Results can be reproduced or methodology can be followed and evaluated High provided comparable economic and social conditions exists. . Focus on factor of The survey collected information on duration and frequency of selected High interest activities and time spent in selected micro-environments. . Data pertinent to US The data represents the U.S. population High . Primary data The study was based on primary data . High . Currency The study was published in 1996. High . Adequacy of data The data were collected between October 1992 and September 1994. High collection period . Validity of approach The study used a valid methodology and approach which, in addition to 24-High hour diaries, collected information on temporal conditions and demographic data such as geographic location and socioeconomic status for various U.S. subgroups. Responses were weighted according to this demographic data. . Study size The study consisted of 9,386 total participants High . Representativeness of Studies were based on the U.S. population. High the population . Characterization of The study provided data that varied across geographic region, race, gender, High variability employment status, educational level, day of the week, seasonal conditions, and medical conditions of respondent.. . Lack of bias in study Study is based on short term data .. Medium design (high rating is desirable) . Measurement error Measurement or recording error may occur because diaries were based on Medium 24-hour recall. Other Elements . Number of studies One; the study was based on one, primary, national study. Low . Agreement between Recommendation was based on only one study. Not researchers Ranked Overall Ratinq High Table 15-172. Confidence in Activity Patterns Recommendations (continued) Considerations TIME SPENT SWIMMING Study Elements

Level of peer review

Accessibility

Reproducibility

Focus on factor of interest

Data pertinent to US

Primary data

Currency

Adequacy of data collection period

Validity of approach

Study size Rationale Study*received high level of peer review. Currently, raw data is available to only EPA. It is not known when data will be publicly available. Results can be reproduced or methodology can be followed and evaluated provided comparable economic and social conditions exists. The survey collected information on duration and frequency of selected activities and time spent in selected micro-environments. The data represents the U.S. population The study was based on primary data. The study was published in 1996. The data were collected between October 1992 and September 1994. The study used a valid methodology and approach which, in addition to 24-hour diaries, collected information on temporal conditions and demographic data such as geographic location and socioeconomic status for various U.S. subgroups. Responses were weighted according to this demographic data. The study consisted of 9,386 total participants

Representativeness of Studies were based on the U.S. population. the population

Characterization of variability

Lack of bias in study design (high rating is desirable)

Measurement error Other Elements The study provided data that varied across geographic region, race, gender, employment status, educational level, day of the week, seasonal conditions, and medical conditions of respondent.. The study includes distributions for swimming duration. Study is based on short term data. Measurement or recording error may occur because diaries were based on 24-hour recall.

Number of studies One; the study was based on one, primary, national study.

Agreement between

Recomrnendation was based on only one study. researchers Overall Rating Ratinq High Low High High High High High High High High High High Medium Medium Low Not Ranked High Table 15-172. Confidence in Activity Patterns Recommendations (continued) Considerations Rationale Ratinq RESIDENTIAL TIME SPENT INDOORS AND OUTDOORS Study Elements . Level of peer review The study received high level of peer review. High . Accessibility Currently, raw data is available to only EPA. It is not known when data will be Low publicly available. . Reproducibility Results can be reproduced or methodology can be followed and evaluated High provided comparable economic and social conditions exists. . Focus on factor of The survey collected information on duration and frequency of selected High interest activities and time spent in selected micro-environments. . Data pertinent to US The data represents the U.S. population High . Primary data The study was based on primary data. High . Currency The study was published in 1996. High . Adequacy of data Data were collected between October 1992 and September 1994. High collection period . Validity of approach The study used a valid methodology and approach which, in addition to 24-High hour diaries, collected information on temporal conditions and demographic data such as geographic location and socioeconomic status for various U.S. subgroups. Responses were weighted according to this demographic data. . Study size The study consisted of 9,386 total participants High . Representativeness of The studies were based on the U.S. population. High the population . Characterization of The study provided data that varied across geographic region, race, gender, High variability employment status, educational level, day of the week, seasonal conditions, and medical conditions of respondent.. . Lack of bias in study The study includes distribitions for time spent indoors and outdoors at ones Medium design (high rating is residence. Study is based on short term data. desirable) . Measurement error Measurement or recording error may occur because diaries were based on Medium 24-hour recall. Other Elements . Number of studies One; the study was based on one, primary, national study. Low . Agreement between Recommendation was based on only one study. Not researchers Ranked Overall Ratina Hi ah Table 15-173. Confidence in Occupational Mobility Recommendations Considerations Rationale Ratinq Study Elements . Level of peer review The studies received high level of peer review . High . Accessibility The studies are widely available to the public. High . Reproducibility If the data were re-collected in the same fashion, it is questionable whether Medium the results would be the same based on changes in the economy that have occurred since study was conducted (more than 10 years ago). If the same data were analyzed according to the design of the study then it is expected the results would be the same. . Focus on factor of Occupational tenure was the focus of both key studies. High interest . Data pertinent to US The data represents the U.S. population. High . Primary data The two studies are secondary data sources since they are based on Medium supplemental data to the January 1987 Current Population Study (a U.S. Census publication). . Currency The studies were published in 1988 (data was collection in 1987) and 1990 Medium (data collected from 1986-1987). . Adequacy of data The studies are based on census data, which is collected over a period of High collection period years. One study analyzed data for January 1987. The remaining study based data between a January 1986 and January 1987 time frame. . Validity of approach The studies used a valid methodologies and approaches. High . Study size The study size for one is 109 Million; the remaining study's sample size was High 100.1 Million. . Representativeness of The data are representative of the U.S. population. High the population . Characterization of The studies provided averaged data according to gender, race, and High variability education; age averages and percentiles were provided. . Lack of bias in study Much of the original study data is not available. Only median values are Medium design (high rating is reported. desirable) . Measurement error There is no apparent error in measurement High Other Elements . Number of studies Two Medium . Agreement between Difficult to compare between the number of years worked on a job and entry Not researchers verses exit rate of various occupations. One set of data was recorded in Ranked number of years. The other set of data was recorded as a percent motility rate and grouped by age. Overall Ratinq HiQh Table 15-174. Recommendations for Population Mobility Study Value Method Israeli and Nelson, 1992 4.6 yr (averge) Average of current and total 1/6 a person's lifetime residence times (70 yr)= 11.7 (modeled) US Bureau of the Census, 1993 9 yr (50th percentile) Current residence time 33 yr (9oth percentile) Johnson and Capel, 1992 26 yr (9oth percentile) Residential occupancy period 33 yr (95th percentile) 47 yr (99th percentile) 12 vr (mean)
~~Table 15-175. Confidence in Population Mobility Recommendations Considerations Study Elements~~
Level of peer review ** Accessibility

Reproducibility

Focus on factor of interest

Data pertinent to US

Primary data

Currency

Adequacy of data collection period

Validity of approach

Study size Rationale Rating The studies receiv.ed high levels of peer review and appear in publications. High The studies are widely available to the public. High Results can be reproduced or methodology can be followed and evaluated. High The Census data provided length of time at current. Two of the studies used Medium modeling to estimate total time. The data is based on the U.S. population High Two studies based results on modeled data and one based results on Medium interviews. The reports were published in 1992 (based on data collected in 1985-1987) Medium and 1993 (based on data collected from 1939 and 1994 (projected) . The collection period was based on data collected over several years. High There are some concerns regarding the validity of approach. Data does not Medium account for each member of the household, values are more realistic estimates for the individual's total residence time, than the average time a household has been living at its current residence. The moving process was modeled. In another study data was assumed to have an even distribution within the different ranges which may bias the 50th and ,9oth percentiles. The study size ranged from 15,000 to 500, 000. High

Representativeness of Studies were based on the U.S. population. the population High

Characterization of variability

Lack of bias in study design (high rating is *desirable)

Measurement error Other Elements

Number of studies

Agreement between researchers Overall Rating Variability across several geographic regions was noted. Type of ownership Medium was also addressed. One study provided data grouped by race. Mentioned above in validity of approach section. Not Ranked There is no apparent error in measurement. High Three High The studies produced very similar results. High Medium

~~Table 1 s-*1 fo: Summary Recommended Values for A2tivity Factors lndobr*Activities .~~

Outdoor Activities Time Vehicle _ -I ', 1'aking*Baths Taking Showers dccup*atidnal Tenure -Population *Mobilify ; Swimming * <\ }< Residential -**indoors .-Outdpors-. Value Children (ages'3:11). 19 hr/day (weekdays) -:.17* t1r/day*(weekends)* Adults (ages 12 and older) 21 .hr/day* -" children 5 hr/day (weekdays}. * ----7-hr/tlay* (weekends)* Adults-. -**1 ;-5 llr/day:* Adults*

1.3 -20111inutes/event <.* _10 min/day _shower durcition . .,: .';/. 1 shower event/day 6.6 years older) -Averi:lge: 9 yr -* 95th percentile: 30 yr * ',, ' ' 1 event/month -5ff 16.4 hr/day *study

Timmer et al., 1985 -Key study ,*' ei>?I., 1985 -}<:ey :study' " ._,. ;Robinson:andl;'hom,as; 19,91 'study' -Timmer et al.,. 1985 -Key study -.':Timmer ef'al., 1985:'-Key study ;-Robinson and Th.omas, 19g1 -*Key .study

Robil)scm 1 gg'1 study _ . , _ _ _ .--ahd Klepeis, 1996'-Key study* Tsang and-Klepeis, -1996-,.. !Key* study* Ts_ang andl:<lepeis, 1996 -*Key.study '. <"'._' "< , ' , . ,l '". ,'/" Tsang and Klepe_is, 1996 -l}ey study > ':' * > ' ,,f ' 'I ' .! < * : '" *' ' ' Carey, 1988 -Key study * :us Bureau of th"e Cer;fous, ;1993;' " * -Israeli and Nelson, 1992; Johnson ---* .:and Capel;'-1992 ,.. study __ Tsang and.Klepeis,. 1996 ,.Key .. study, ,, . ' . ' ' ,, c lf *t, ' ---' --_Tsang and'Klepeis,-1996 "iKey study.-, -,,, -.,, ' ,>
Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries WORK AND OTHER INCOME-PRODUCING ACTIVITIES Paid Work 01 Normal work: activities at the main job including work brought home, travel that is part of the job, and overtime; "working," "at work" Work at home; work activities for pay done in the home when home is the main workplace (include travel as above) 02 Job search; lookin9 for work, including visits to employment agencies, phone calls to prospective employers, answering want ads Unemployment benefits; applying for or collecting unemployment compensation Welfare, food stamps; applying for or collecting welfare, food stamps 05 Second job; paid work activities that are not part of the main job (use this code only when R* clearly indicates a second job or "other" job); paid work for those not having main job; garage sales, rental property 06 Lunch at the workplace; lunch eaten at work, cafeteria, lunchroom when "where" = work (lunch at a restaurant, code 44; lunch at home, code 43) Eating, smoking, drinking coffee as a secondary activity while working (at workplace) 07 Before and/or after work at the workplace; activities at the workplace before starting or after stopping work; include "conversations," other work. Do not code secondary activities with this primary activity Other work-related 08 Coffee breaks and other breaks at the workplace; unscheduled breaks and other nonwork during work hours at the workplace; "took a break"; "had coffee" (as a primary activity). Do not code secondary activities with this primary activity 09 Travel; to and from the workplace when R's travel to and from work were both interrupted by stops; waiting for related travel
Travel to and from the workplace, including time spent awaiting transportation HOUSEHOLD ACTIVITIES 10 Meal preparation: cooking, fixing lunches Serving food, setting table, putting groceries away. unloading car after grocery shopping 11 Doing dishes, rinsing dishes, loading dishwasher Meal cleanup, clearing table, unloading dishwasher (continued on the following page)
Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries (continued) HOUSEHOLD ACTIVITIES (continued) Indoor (continued) 12 Miscellaneous, "worked around house." NA if indoqr or outdoor -Routine indoor cleaning and chores, picking up, dusting, making beds, washing windows, vacuuming, "cleaning," "fall/spring cleaning," "housework" 14 Laundry and clothes care -wash Laundry and clothes care -iron, fold, mending, putting away clothes ("Sewing" code 84) 16 Repairs indoors; fixing, repairing appliances Repairs indoors; fixing, repairing furniture Repairs indoors; fixing, repairing furnace, plumbing, painting a room 17 Care of houseplants 19 Other indoor, NA whether cleaning or repair; "did things in house" Outdoor 13 Routine outdoor cleaning and chores; yard work, raking leaves, mowing grass, garbage removal, snow shoveling, putting on storm windows, cleaning garage, cutting wood 16. Repair, maintenance, exterior; fixing repairs outdoors, painting the house, fixing the roof, repairing the driveway (patching) Home improvements: additions to and remodeling done to the house, garage; new roof Improvement to grounds around house; repaved driveway 17 Gardening; flower or vegetable gardening; spading, weeding, composting, picking, worked in garden" 19 Other outdoor; "worked outside," "puttering in garage MISCELLANEOUS HOUSEHOLD CHORES 16 Car care; necessary repairs and routine care to cars; tune up Car maintenance; changed oil, changed tires, washed cars; "worked on car" except when clearly as a hobby -(code 83) 17 Pet care; care of household pets including activities with pets; playing with the dog; walking the dog; (caring for pets of relatives, friends, code 42) (continued on the following page) j Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries (continued) MISCELLANEOUS HOUSEHOLD CHORES (continued) 19 Household paperwork; paying bills, balancing the checkbook, making lists, getting the mail, working on the budget Other household chores; (no travel), picking up things at home, e.g., "picked up deposit slips" (relate travel to purpose) CHILD CARE Child Care for Children of Household 20 Baby care; care to children aged 4 and under 21 Child care; care to children aged 5*-17 Child care; mixed ages or NA ages of children 22 Helping/teaching children learn, fix, make things; helping son bake cookies; helping daughter fix bike Help with homework or supervising homework 23 Giving children orders or instructions; asking them to help; telling the*i*n to behave Disciplining child; yelling at kids, spanking children; correcting children's behavior Reading to child Conversations with household children only; listening to children 24 Indoor playing; other indoor activities with children (including games ("playing") unless obviously outdoor games) 25 Outdoor playing; outdoor activities with children including sports, walks, biking with, other outdoor games Coaching/leading outdoor, nonorganizational activities 26 Medical care at home or outside home; activities associated with children's health; "took son to doctor," "gave daughter medicine" Other Child Care 27 Babysitting (unpaid) or child care outside R's home or for children not residing in HH Coordinating or facilitating child's social or instructional nonschool activities; (travel related, code 29) Other child care, including phone conversations relating to child care other than medical 29 Travel related to child's social and instructional nonschool activities Other travel related to child care activities; waiting for related travel (continued on the following page) r Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries (continued) OBTAINING GOODS AND SERVICES Goods (include phone calls to obtain goods) 30 Groceries; supermarket, shopping for food All other shopping for goods; including for clothing, small appliances; at drugstores, hardware stores, department stores, "downtown" or "uptown," "shopping," "shopping center," buying gas, "window shopping" 31 Durable household goods; shopping for large appliances, cars, furniture House, apartment: activities connected to buying, selling, renting, looking for house, apartment, including phone calls; showing house, including traveling around looking at real estate property (for own use) Services (include phone conversations to obtain services) 32 Personal care; beauty, barber shop; hairdressers 33 Medical care for self; visits to doctor, dentist, optometrist, including making appointments 34 Financial services; activities related to taking care of financial business; going to the bank, paying utility bills (not by mail), going to accountant, tax office, loan agency, insurance office Other government services: post office, driver's license, sporting licenses, marriage licenses, police station 35 Auto services; repair and other auto services including waiting for such services Clothes repair and cleaning; cleaners, laundromat, tailor Appliance repair: including furnace, water heater, electric.or battery operated appliances; including watching repair person Household repair services: including furniture; other repair services NA type; including watching repair person 37 Other professional services; lawyer, counseling (therapy) Picking up food at a takeout place -no travel Other services, "going to the dump" 38 Errands; "running errands," NA whether for goods or services; borrowing goods 39 Related travel; travel related to obtaining goods and services and/or household activities except 31; waiting for related travel (continued on the following page) Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries (continued) PERSONAL NEEDS AND CARE Care to Self 40 Washing, showering, bathing Dressing; getting ready, packing and unpacking clothes, personal hygiene, going to the bathroom 41 Medical care at home to self 43 Meals at home; including coffee, drinking, smoking, food from a restaurant eaten at home, "breakfast," "lunch" 44 Meals away from home; eaten at a friend's home (including coffee, drinking, smoking) Meals away from home, except at workplace (06) or at friend's home ( 44 ); eating at restaurants, out for coffee 45 Night sleep; longest sleep for day; (may occur during day for night shift workers) including "in bed," but not asleep
46 Naps and resting; rest periods, "dozing," "laying down" (relaxing code 98) 48 Sex, making out Personal, private; "none of your business" Affection between household members; giving and getting hugs, kisses, sitting on laps Help and Care to Others 41 Medical care to adults in household (HH) 42 Nonmedical care to adults in HH; routine nonmedical care to adults in household; "got my wife up," "ran a bath for my husband" Help and care to relatives not living in HH; helping care for, providing for needs of relatives; (except travel) helping move, bringing food, assisting in emergencies, doing housework for relatives;* visiting when sick Help and care to neighbors, friends Help and care to others, NA relationship to respondent Other Personal and Helping 48 Other personal; watching personal care activities 49 Travel (helping); travel related to code 42, including travel that is the helping activity; waiting for related travel Other personal travel; travel related to other personal care activities; waiting for related travel; travel, NA purpose of trip -e.g., "went to Memphis" (no further explanation given) (continued on the following page)
Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries (continued) EDUCATION AND PROFESSIONAL TRAINING 50 Student (full-time); attending classes, school if full-time student; includes daycare, nursery school for children not in school 51 Other classes, courses, lectures, academic or professional; R not a full-time student or NA whether a student; being tutored 54 Homework, studying, research, reading, related to classes or profession, except for current job (code 07); "went to the library" 56 Other education 59 Other school-related travel; travel related to education coded above; waiting fonelated travel; travel to school not originating from home ORGANIZATIONAL ACTIVITIES Volunteer, Helping Organizations: hospital volunteer group, United Fund, Red Cross, Big Brother/Sister 63 Attending meetings of volunteer, helping organizations 65 Officer work; work as an officer of volunteer, helping organizations; R must indicate he/she is an officer to be coded here Fund raising activities as a member of volunteer helping organization, collecting money, planning a collection drive Direct help to individuals or groups as a member of volunteer helping organizations; visiting, bringing food, driving Other activities as a member of volunteer helping organizations, including social events and meals Religious Practice Attending services of a church or synagogue, including participating in the service; ushering, singing in choir, leading youth group, going to church, funerals Individual practice; religious practice carried out as an individual or in a small group; praying, meditating, Bible study group (not a church), visiting graves Religious Groups 64 Meetings: religious helping groups; attending meetings of helping -oriented church groups -ladies aid circle, missionary society, Knights of Columbus
~~Other activities; religious helping groups; other activities as a member of groups listed above, ineluding social activities and meals (continued on the following page) )~~
Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries (continued) ORGANIZATIONAL ACTIVITIES (continued) Religious Groups (continued) Meetings: other church groups; attending meetings of church group, not primarily helping-oriented, or NA if helping-oriented Other activities, other church groups; other activities as a member of church groups that are not helping-oriented or NA if helping, including social activities and meals; choir practice; Bible class Professional/Union Organizations: State Education Association; AFL-CIO; Teamsters 60 Meetings; professional/union; attending meetings of professional or union groups Other activities, professional/union; other activities as a member of professional or union group including social activities and meals Child/Youth/Family Organizations: PTA, PTO; Boy/Girl Scouts; Little Leagues; YMCA/YWCA; school volunteer 67 Meetings, family organizations; attending meetings of child/youth/family*-oriented organizations Other activities, family organizations; other activities as a member of child/youth/family-oriented organizations including social activities and meals Fraternal Organizations: Moose, VFW, Kiwanis, Lions, Civitan, Chamber of Commerce, Shriners, American Legion 66 Meetings, fraternal organizations; attending meetings of fraternal organizations Other activities, fraternal organizations; other activities as a member of fraternal organizations including social activities and helping activities and meals Political Party and Civic Participation: Citizens' groups, Young Democrats, Young Republicans, radical political groups, civic duties 62 Meetings, political/citizen organizations; attending meetings of a political party or citizen group, including city council Other activities, political/citizen organizations; other participation in political party and citizens' groups, including social activities, voting, jury duty, helping with elections, and meals Special Interest/Identity Organizations (including groups based on sex, race, national origin); NOW; NAACP; Polish-American Society; neighborhood, block organizations; CR groups; senior citizens; Weight Watchers 61 Meetings: identify organizations; attending meetings of special interest, identity organizations Other activities, identity organizations; other activities as a member of a special interest, identity organization, including social activities and meals (continued on the following page) Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries (continued) ORGANIZATIONAL ACTIVITIES (continued) 9ther Miscellaneous Organizations, do not fit above 68 Other organizations; any activities as a member of an organization not fitting into above categories; (meetings and other activities included here) Travel Related to Organizational Activities 69 Travel related to organizational activities as a member of a volunteer (helping) organization (code 63); including travel that is the helping activity, waiting for related travel Travel (other organization-related); travel related to all other organization activities; waiting for related travel ENTERTAINMENT/SOCIAL ACTIVITIES Attending Spectacles, Events 70 Sports; attending sports events -football, basketball, hockey, etc. 71 Miscellaneous spectacles, events: circus, fairs, rock concerts, accidents 72 Movies; "went to the show" 73 Theater, opera, concert, ballet 7 4 Museums, art galleries, exhibitions, zoos Socializing 75 Visiting with others; socializing with people other than R's own HH members either at R's home or another home (visiting on the phone, code 96); talking/chatting in the context of receiving a visit or paying a visit 76 Party; reception, weddings 77 At bar; cocktail lounge, nightclub; socializing or hoping to socialize at bar, lounge Dancing 78
~~Other events; other events or socializing, do not fit above 79 Related travel; waiting for related travel (continued on the following page)~~
Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries (continued) SPORTS AND ACTIVE LEISURE Active Sports 80 Football, basketball, baseball, volleyball, hockey. soccer, field hockey Tennis, squash, racquetball, paddleball Golf, miniature golf Swimming, waterskiing Skiing, ice skating, sledding, roller skating Bowling; pool, ping-pong, pinball Frisbee, catch Exercises, yoga (gymnastics -code 86) Judo, boxing, wrestling Out of Doors 81 Hunting Fishing Boating, sailing, canoeing Camping, at the beach
Snowmobiling, dune-buggies Gliding, ballooning, flying Excursions, pleasure drives (no destination), rides with the family Picnicking Walking. Biking 82 Walking for pleasure Hiking Jogging, running Bicycling Motorcycling Horseback riding Hobbies 83 Photography Working on cars -not necessarily related to their running; customizing, painting Working on or repairing leisure time equipment the boat, "sorting out fishing tackle") Collections, scrapbooks Carpentry and woodworking (as a hobby) (continued on the following page)
Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries (continued) SPORTS AND ACTIVE LEISURE (continued) Domestic Crafts 84 Preserving foodstuffs (canning, pickling) Knitting, needlework, weaving, crocheting (including classes), crewel, embroidery, quilting, quilling, macrame Sewing Care of animals/livestock when R is not a farmer (pets, code 17; "farmer", code 01, work) Art and Literature 85 Sculpture, painting, potting, drawing Literature, poetry, writing (not letters), writing a diary Music/Theater/Dance 86 Playing a musical instrument (include practicing), whistling Singing Acting (rehearsal for play) Nonsocialdancing (ballet, modern dance, body movement) Gymnastics (lessons -code 88) 87 Playing card games (bridge, poker) Playing board games (Monopoly, Yahtzee, etc.), bingo, dominoes Playing social games (scavenger hunts), "played games" -NA kind Puzzles Classes/Lessons for Active Leisure Activity 88 Lessons in sports activities: swimming, golf, tennis. skating, roller skating Lessons in gymnastics, dance, judo, body movement Lessons in music, singing, instruments Other lessons, not listed above 89 Related travel; travel related to sports and active leisure; waiting for related travel: vacation travel (continued on the following page) Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries (continued) PASSIVE LEISURE 90 Radio 91 TV 92 Records, tapes, "listening to music," listening to others playing a musical instrument 93 Reading books (current job related, code 07; professionally or class related, code 54) 94 Reading magazines, reviews, pamphlets Reading NA what; or other 95 Reading newspapers 96 Phone conversations -not coded elsewhere, including all visiting by phone Other talking/conversations; face-to-face conversations, not coded elsewhere (if children in HH only, code 23); visiting other than 75 Conversations with HH members only -adults only or children and adults Arguing or fighting with people other than HH members only, household and nonhousehold members, or NA Arguing or fighting with HH members only 97 Letters (reading or writing); reading mail 98 Relaxing Thinking, planning; reflecting "doing nothing," "sat"; just sat; Other passive leisure, smoking dope, pestering, teasing, joking around, messing around; laughing 99 Related travel: waiting for related travel MISSING DATA CODES Activities of others *reported -R's activity not specified NA activities; a time gap of greater than 10 minutes. EXAMPLES OF ACTIVITIES IN "OTHER" CATEGORIES Other Work Related 07 Foster parent activities (continued on the following page) Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries (continued) EXAMPLES OF ACTIVITIES IN "OTHER" CATEGORIES (continued) Other Household 19 Typing Wrapping presents Checked refrigerator for shopping list Unpacked gifts from shower Packing/unpacking car "Settled in" after trip Hooked up boat to car Showed wife car (R was fixing) Packing to f\lOVe Moved boxes Looking/searching for things at home (inside or out) Other Child Care 27 Waited for son to get hair cut Picked up nephew at sister's house "Played with kids" (R's children from previous marriage not living with R) Called babysitter Other Services 37 Left clothing at Goodwill Unloaded furniture Uust purchased) Returned books (at library) Brought clothes in from car (after laundromat) Delivered some stuff to a friend Waited for father to pick up meat Waited for stores to open Put away things from swap meet Sat in car waiting for rain to stop before shopping Waiting for others while they are shopping Showing mom what I bought Other Personal 48 Waiting to hear from daughter Stopped at home, NA what for Getting hysterical Breaking up a fight (not child care related) Waited for wife to get up (continued on the following page) Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries (continued) EXAMPLES OF ACTIVITIES IN "OTHER" CATEGORIES (continued) Other Personal (continued) Waiting for dinner at brother's house Waiting for plane (meeting someone at airport) Laughing Crying Moaning -head hurt Watching personal care activities ("watched dad shave") Other Education 56 Watched a film In discussion group Other Organization
68 Attending "Club House coffee klatch" Waited for church activities to begin "Meeting" NA kind Cleanup after banquet Checked into swap meet -selling and looking Other Social, Entertainment 78 Waiting for movies, other events Opening presents (at a party) Looking at gifts Decorating for party Tour of a home (friends or otherwise) Waiting for date Preparing for a shower (baby shower) Unloaded uniforms (for parade) Other Active Leisure 88 Fed birds, bird watching Astrology Swinging At park Showing slides Showing sketches (continued on the following page)
Table 15A-1. Activity Codes and Descriptors Used for Adult Time Diaries (continued) EXAMPLES OF ACTIVITIES IN "OTHER" CATEGORIES (continued) Other Active Leisure (continued) Recording music Hung around airport (NA reason) Picked up fishing gear Inspecting motorcycle Arranging flowers Work on model airplane Picked asparagus Picked up softball equipment Registered to play golf Toured a village or lodge (coded 81) Other Passive Leisure 98 . Lying in sun Listening to birds Looking at slides Stopped at excavating place Looking at pictures Walked around outside Waiting for a call Watched plane leave Girl watching/boy watching Watching boats Wasted time In and out of house Home movies
~~R = Respondent HH =Household. *source: Juster et al., 1983.~~
Table 15A-2. Differences in Average Time Spent in Different Activities Between California and National Studies (minutes per day for age 18-64 years) California National California National 00-49 NON-FREE TIME 1987-88 1985 50-59 Free Time 1987-88 1985 11359\ 11980\ -11359) 11980) 00-09 PAID WORK 50-99 EDUCATION AND TRAINING 00 (not used) -50 Students' Classes 9 5 01 Main Job 224 211 51 Other Classes 1 3 02 Unemployment 1 1 52 (not used) --03 Travel during work 8 NR 53 (not used) --04 (not used) --54 Homework 8 7 05 Second job 3 3 55 Library
1 06 Eating 6 8 56 Other Education 1 1 07 Before/after work 1 2 57 (notused) --08 Breaks 2 2 58 (not used) --09 Travel to/from work 28 25 59 Travel Education 3 2 10-19 HOUSEHOLD WORK 60-69 ORGANIZATIONAL ACTIVITIES 10 Fo.od Preparation 29 36 60 Professional/Union 0 1 11 Meal Cleanup 10 11 61 Special Interest

1 12 Cleaning House 21 24 62 Political/Civic 0 . 13 Outdoor Cleaning 9 7 63 Volunteer/Helping 1 1 14 Clothes Care 7 11 64 Religious Groups 1 2 15 Car Repair/Maintenance (by 5 5 65 Religious Practice 5 7 R) 16 Other Repairs (by R) 8 6 66 Fraternal 0

17 Plant Care 3 5 67 Child/Y outh/Farnily 1

18 Animal Care 3 5 68 Other Organizations 2 1 19 Other Household 7 8 69 Travel Oraanizations 2 4 20-29 CHILD CARE 70-79 ENTERTAINMENT/ SOCIAL ACTIVITIES 20 Baby Care 3 8 70 Sports Events 2 2 21 Child Care 7 5 71 Entertainment Events 5 1 22 Helping/Teaching 2 1 72 Movies 2 3 23 Talking/Reading 1 1 73 Theatre 1 1 ' 24 Indoor Playing 2 3 74 Museums 1 . 25 Outdoor Playing 2 1 75 Visiting 26 25 26 Medical care -Care

1 76 Parties 6 7 27 Other Child Care 2 1 77 Bars/Lounges 4 6 28 (At Dry Cleaners)

NR 78 Other Social . 1 29 Travel Child care 4 4 79 Travel Events/Social 13 16 Table 15A-2. Differences in Average Time Spent in Different Activities Between California and National Studies (minutes per da1 for age 18-64 years) (continued) California National California National 00-49 NON-FREE TIME 1987-88 1985 50-59 Free Time 1987-88 1985 11359) 11980l 11359) 11980) 30-39 OBTAINING GOODS AND 80-89 RECREATION SERVICES 30 Everyday Shopping 8 5 80 Active Sports 15 13 31 Durable/House Shop 19 20 81 Outdoor 3 7 32 Personal Services 1 1 82 Walking/Hiking 5 4 33 Medical Appointments 2 2 83 Hobbies 1 1 34 Gov't/Financial Service 3 2 84 Domestic Crafts 3 6 35 Car Repair services 2 1 85 Art

1 36. Other Repair services

1 86 Music/Drama/Dance 3 2 37 Other Services 2 2 87 Games 5 7 38 Errands

1 88 Computer Use/Other 3 3 39 Travel Goods and Services 24 20 89 Travel Recreation 5 6 40-49 PERSONAL NEEDS AND 90-99 COMMUNICATION CARE 40 Washing, Etc. 21 25 90 Radio 1 3 41 Medical Care 3 1 91 TV 130 126 42 Help and Care 3 4 92 Records/Tapes 3 1 43 Meals At Home 44 50 93 Read Books 4 7 44 Meals Out 27 20 94 Reading Magazines/Other 16 10 45 Night Sleep . 480 469 95 Reading Newspaper 11 9 46 Naps/Day Sleep 16 16 96 Conversations 15 25 47 Dressing, Etc. 24 32 97 Writing 8 9 48 NA Activity 2 12 98 Think, Relax 9 6 49 Travel Personal Care/NA 22 13 99 Travel Communication 5

NR= Not Recorded in National Total Travel 108 90 Survey *= Less than 0.5 Min. per day (Codes 09, 29, 39, 49, 59, 69 79 89 99l Source: Robinson and Thomas 1991.
Table 15A-3. Time Spent in Various Microenvironments Mean duration Men Women Total* Code Description N =639 N = 914 N = 720 N = 1059 N = 1980 N = 1359 California National California National California National AT HOME Kitchen 46 56 98 135 72 104 Living Room 181 136 98 180 189 158 Dining Room 18 10 22 18 19 15 Bathroom 27 27 38 43 33 38 Bedroom 481 478 534 531 508 521 Study 8 10 6 7 7 8 Garage 14 5 6 1 19 2 Basement <0.5 4 <0.5 6 <0.5 5 Utility Room 1 0 3 5 2 4 Pool, Si:>a 1 NR 1 NRb 1 NRb Yard 33 21 27 37 Room to Room 9 160' 34 116 21 40 Other NR Room 3 .4 3 22 Total at home 822 888 963 1022 892 954 AWAY FROM HOME Office 78 261 94 155 86 193 Plant 73 12 42 Grocery Store 12 18 14 33 13 30 Shopping Mall 30 40 35 School 25 13 29 11 27 15 Other Public Places 18 10 14 12 Hospital 9 NR 24 NR 17 3 Restaurant 35 22 25 18 30 23 Bar-Night Club 15 5 10 Church 7 8 5 11 6 10 Indoor Gym 4 NR 4 NR 4 NR Other's Home 60 42 61 45 61 43 Auto Repair 18 NR 4 NR 11 NR Playground 16 27 .8 16 12 NR Hotel-Motel 7 . NR 8 NR 8 NR Dry Cleaners <0.5 NR 1 NR 1 NR Beauty Parlor <0.5 NR 4 NR 2 NR Other Locations 3 NR 1 NR 2 NR Other Indoor 17 41 7 24 12 24 Other Outdoor 60 NR 13 NR 37 6 Total awa':f. from home 487 445 371 324 430 383 Table 15A-3. Time Spent in Various Microenvironments {continued) Mean duration Men Women Total' Code Description N =639 N = 914 N = 720 N = 1059 N = 1980 N = 1359 California National California National California National TRAVEL Car 76 77 76 Van!Truck 30 86 11 77 20 88 Walking 10 8 9 2 Bus Stop <0.5 1 1 Bus 6 2 4 3 Rapid Train 1 1 1 Other Travel 2 1 <0.5 Airplane 1 15 <0.5 10 1 1 Bicycle 1 <0.5 1 NR Motorcycle 2 <0.5 1 NR Other or Missing 1 <0.5 1 NR Total travel 130 101 102 87 116 94 Not ascertained 8 4 7 2 9 Total Time Outdoors 88 70 Totals do not necessarily reflect exact averages presented for each gender. Totals were revised, but revisions for each gender were not provided. NR = Not Reported Is total mean duration for those categories; breakdowns per category were not reported. Source: Robinson and Thomas, 1991. National California . Note: Percent at home men 62 men 57 women 71 women 67 total 67 total 62 Percent away from home men 31 men 34 women 23 women 26 total 27 total 30 Percent in travel men 7 men 9 women 6 women 7 total 7 total 8 Table 15A-4. Major Time Use Activity Categoriesa Activity code Activity 01-09 Market work 10-19 House/yard work 20-29 Child care 30-39 Services/shopping 40-49 Personal care 50-59 Education 60-69 Organizations 70-79 Social entertainment 80-89 Active leisure 90-99 Passive leisure a Appendix Table 15A-5 presents a detailed explanation of the coding and activities. Source: Hill, 1985. Table 15A-5. Mean Time Spent (minutes/day) for 87 Activities Grouped by Dav of the Week Weekday Saturday Sunday N=831 N=831 N=831 Activitv Mean Std. Dev. Mean Std. Dev. Mean Std. Dev. 01-Normal Work 240.54 219.10 82.43 184.41 46.74 139.71 02-Unemployment Acts 0.98 9.43 0.00 0.00 0.00 0.00 05-Second Job 3.76 25.04 2.84 32.64 2.65 27.30 06-Lunch At Work 10.00 15.81 1.82 7.88 1.43 8.29 07-Before/After Work 3.51 10.05 1.45 9.79 1.66 13.76 08-Goffee Breaks 5.05 11.53 1.59 7.32 0.93 8.52 09-Travel: To/From Work 24.03 30.37 7.74 22.00 4.60 17.55 10-Meal Preparation 42.18 46.59 40.37 59.82 42.38 57.42 11-Meal Cleanup 12.48 19.25 12.07 22.96 13.97 25.85 12-lndoor Cleaning 26.37 43.84 38.88 80.39 21.73 48.70 13-0utdoor Cleaning 7.48 25.45 15.71 58.00 9.01 39.39 14-Laundry 13.35 30.39 11.48 31.04 7.79 25.43 16-Repairs/Maintenance . 9.61 35.43 17.36 72.50 13.56 62.12 17-Garden/Pet Care 8.52 25.15 14.75 49.17 8.47 37.54 19-0ther Household 6.26 20.62 9.82 37.58 7.60 32.17 20-Baby Care 6.29 22.91 5.89 30.72 6.26 33.78 21-Child Care 6.26 16.34 5.38 21.58 7.09 23.15 22-Helping/Teaching 1.36 "8.28 0.23 3.64 0.76 6.52 23-Reading/T al king 2.47 8.65 1.71 10.84 1.53 9.97 24-lndoor Playing 1.75 8.72. 0.90 7.82 2.45 15.11 25-0utdoor Playing 0.73 6.33 1.23 13.03 0.91 10.30 26-Medical Care-Child 0.64 7.42 0.16 2.79 0.44 7.20 27-Babysitting/Other 2.93 14.56 2.16 19.11 3.28 24.89 29-Travel: Child Care 4.18 10.97 1.71 8.72 2.08 10.56 30-Everyday Shopping 19.73 30.28 33.52 61.38 10.13 30.18 31-Durable/House Shop 0.58 4.83 1.46 14.04 1.65 17.92 32-Personal Care Services 1.93 10.04 3.42 18.94 0.02 0.69 33-Medical Appointments 3.43 14.49 0.60 6.63 0.00 0.00 34-Gov't/Financial Services 1.90 6.07 0.66 4.34 0.03 0.43 35-Repair Services 1.33 7.14 1.25 10.24 0.52 5.61 37-0ther Services 1.13 7.17 1.55 9.57 0.72 4.34 38-Errands 0.74 8.03 0.35 5.27 0.04 1.04 39-Travel: Goods/Services 17.93 23.58 21.61 36.35 8.45 21.64 40-Washing/Dressing 44.03 29.82 44.25 41.20 47.54 40.15 41-Medical Care R/HH Adults 0.77 6.19 1.29 15.90 1.45 29.18 42-Help & Care 8.43 28.17 12.19 52.58 14.32 55.13 43-Meals At Home 53.45 35.57 57.86 49.25 61.84 49.27 44-Meals Out 19.55 31.20 31.13 56.03 25.95 47.60 45-Night Sleep 468.49 79.42 498.40 115.55 528.86 115.84 46-Naps/Resting 22.07 43.92 30.67 74.98 27.56 66.01 48-N.A. Activities 7.52 22.32 11.72 41.61 8.18 35.79 . 49-Travel: Personal 14.87 27.76 19.33 50.42 18.58 46.36 50-Students' Classes 6.33 33.79 0.96 18.17 0.96 20.07 51-0ther Classes 2.65 17.92 0.40 11.52 0.27 5.63 Table 15A-5. Mean Time Spent (minutes/dav\ for 87 Activities Grouped by Day of the Week (continued) Weekday Saturday Sunday N=831 N=831 N=831 Activitv Mean Std. Dev. Mean Std. Dev. Mean Std. Dev. 54-Homework 4.56 24.35 3.48 27.98 5.40 38.68 56-0ther Education 0.53 5.91 0.15 2.75 0.45 9.85 59-Travel: Education 2.29 10.36 0.35 4.26 0.21 3.14 60-Professional/Union Orgs. 0.51 7.27 0.13 3.64 0.44 8.34 61-ldentity Organizations 1.53 11.19 1.24 35.63 0.48 7.58 62-Political/Citizen Orgs 0.14 1.25 0.07 1.91 0.19 5.55 63-Volunteer/Helping Orgs 1.08 10.08 0.02 0.45 0.41 7.09 64-Religious Groups 2.96 17.33 3.05 27.73 8.59 33.31 65-Religious Practice 4.98 19.92 7.13 30: 12 34.05 62.06 66-Fratemal Organizations 0.85 9.28 1.73 27.71 0.31 6.67 67-Child/Family Organizations 1.70 11.69 1.04 17.83 0.26 7.63. 68-0ther Organizations 3.91 22.85 1.31 20.28 1.71 17.52 69-Traves: Organizations 3.41 9.83 2.66 12.22 12.07 37.64 70-Sport Events 2.22 13.45 6.29 42.05 3.44 27.78 71-Miscellaneous Events 0.32 4.89 1.94 19.90 1.96 19.75 72-Movies 1.65 11.03 4.74 27.04 3.35 22.65 73-Theater 0.69 7.13 2.66 27.79 0.77 10.37 74-Museums 0.19 3.32 0.90 13.62 0.72 11.17 75-Visiting w/Others 33.14 51.69 56.78 95.61 69.65 114.58 76-Parties 2.81 16.49 12.63 56.11 7.16 39.02 77-Bars/Lounges 3.62 18.07 7.23 35.09 3.91 26.95 78-0ther Events 1.39 11.55 1.33 15.52 1.00 10.80 79-Travel: Events/Social 8.90 16.19 19.55 43.38 18.02 34.45 80-Active Sports 5.30 19.60 9.23 43.69 11.39 48.66 81-0utdoors 5.11 33.00 11.58 55.07 15.52 62.68 82-Walking/Biking 2.08 9.70 5.87 36.38 5.92 32.28 83-Hobbies 1.78 11.73 3.20 32.43 4.10 31.55 84-Domestic Crafts 11.18 37.03 8.67 40.49 6.41 34.82 85-Art/Literature 0.99 10.84 0.86 13.59 1.13 15.07 86-Music/Drama/Dance 0.45 4.91 0.83 8.83 0.63 8.32 87-Games 5.06 22.91 10.14 45.11 7.89 40.45 88-Classes/Other 2.65 15.83 2.56 29.92 3.37 23.60 89-Travel: Active Leisure 3.31 14.77 8.50 48.72 . 8.19 38.11 90-Radio 2.89 12.19 3.53 23.42 2.88 18.50 91-TV 113.01 103.89 118.99 131.24 149.67 141.43 92-Records/Tapes 2.58 20.26 2.40 16.09 2.03 16.08 93-Reading Books 4.41 18.09 2.76 17.85 5.23 30.13 94-Reading Magazines/NA 13.72 31.73 16.33 46.24 17.18 51.01 95-Reading Newspapers 12.03 22.65 12.19 34.96 26.01 44.47 96-Conversations 18.68 28.59 15.45 35.27 14.57 34.60 97-Letters 2.83 12.23 1.61 10.80 1.96 12.59 98-0ther Passive Leisure 9.72 25.02 17.24 57.21 15.28 47.86 99-Travel: Passive Leisure 1.26 5.44 1.32 6.80 1.72 9.87 Source: Hill, 1985. Table 15A-6. Weighted Mean Hours Per Week by Gender: 87 Activities and 10 Subtotals Men Women Men.and women N=410 N=561 N=971 Activity Mean Std. dev. Mean Std. dev. Mean Std. dev. 01 -Normal work 29.78 20.41 14.99 17.62 21.82 20.33 02 -Unemployment acts 0.14 1.06 0.08 0.75 0.11 0.90 05 -Second job 0.73 3.20 0.17 1.62 0.43 2.49 06 -Lunch at work 1.08 . 1.43 0.65 1.21 0.85 1.33 07 -Before/after work 0.51 1.27 0.23 0.69 0.36 1.01 08 -Coffee breaks 0.57 1.05 0.36 1.03 0.46 1.04 09 -Travel: to/from work 2.98 2.87 1.45 2.17 2.16 2.63 10 -Meal preparation 1.57 2.61 7.25 5.04 4.63 4.98 11 -Meal cleanup 0.33 0.83 2.30 2.19 1.39 1.97 12 -Indoor cleaning 0.85 2.01 5.03 5.05 3.10 4.46 13 -Outdoor cleaning 1.59 3.59 0.56 1.59 1.03 2.75 14 -Laundry 0.13 0.72 2.44 3.34 1.38 2.75 16 -Repairs/maintenance 2.14 4.29 0.68 3.43 1.35 3.92 17 -Gardening/pet care 0.94 2.78 1.00 2.19 0.97 2.48 19 -Other household 0.92 2.42 0.72 1.84 0.81 2.13 20 -Baby care 0.24 1.20 0.90 3.04 0.60 2.40 21 -Child care 0.24 0.78 0.99 2.11 0.64 1.68 22 -Helping/teaching 0.07 0.61 0.15 0.76 0.11 0.70 23 -Reading/talking 0.07 0.35 0.30 0.86 0.19 0.68 24 -Indoor playing 0.13 0.69 0.18 0.82 0.16 0.76 25 -Outdoor playing 0.06 0.37 0.12 0.72 0.09 0.58 26 -Medical care -child 0.01 0.09 0.09 0.67 0.05 0.50 27 -Babysitting/other 0.14 0.78 0.64 2.58 0.41 1.98 29 -Travel: child care 0.23 0.67 0.50 1.21 0.38 1.00 30 -Everyday shopping 1.45 2.18 2.78 3.25 2.17 2.89 31 -Durables/house shopping 0.19 1.39 0.08 0.51 0.13 1.01 32 -Personal care services 0.06 0.42 0.35 1.14 0.22 0.90 33 -Medical appointments 0.15 0.75 0.37 1.63 0.27 1.31 34 -Govt/financial services 0.15 0.44 0.19 0.61 0.17 0.54 35 -Repair services 0.11 0.45 0.17 0.78 0.14 0.65 37 -Other services 0.11 0.61 0.13 0.61 0.12 0.61 38 -Errands 0.04 0.41 0.06 0.68 0.05 0.57 39 -Travel: goods/services 1.60 2.02 2.14 2.17 1.89 2.12 (Continued on the following page) Table 15A-6. Weighted Mean Hours Per Week by Gender: 87 Activities and 10 Subtotals (continued) Men Women Men and women N=410 N=561 N=971 Activi!l'. Mean *Std. dev. Mean Std. dev. Mean Std. dev. 40 -Washing/dressing 4.33 2.39 5.43 3.24 4.92 2.93 41 -Medical care -adults 0.09 0.67 0.18 1.00 0.14 0.86 42 -Help and care 1.02 2.84 1.30 3.04 1.17 2.95 43 -Meals at home 6.59 3.87 6.32 3.53 6.44 3.69 44 -Meals out 2.72 3.48 2.24 2.73 2.46 3.10 45 -Night sleep 55.76 8.43 56.74 8.49 56.29 8.47 46 -Naps/resting 2.94 5.18 3.19 4.70 3.08 4.93 48 -N.A. activities 1.77 6.12 1.99 5.70 1.89 5.89 49 -Travel: personal 2.06 2.59 1.61 2.51 1.82 2.56 50 -Students' classes 0.92 4.00 0.38 2.51 0.63 3.29 51 -Other classes 0.23 1.68 0.15 1.05 0.18 1.38 54 -Homework 0.76 3.48 0.38 1.87 0.56 2.74 56 -Other education 0.11 0.86 0.02 o*.22 0.06 0.61 59 -Travel: education 0.29 1.07 0.16 1.06 0.22 1.07 60 -Professional/union organizations 0.04 0.46 0.04 0.62 0.04 0.55 61 -Identity organizations 0.14 0.97 0.18 1.55 0.16 1.31 62 -Political/citizen organizations 0.01 0.08 0.02 0.15 0.01 0.12 63 -Volunteer/helping organizations 0.02 0.32 0.14 1.05 0.09 0.80 64 -Religious groups 0.38 1.82 0.41 1.61 0.40 1.71 65 -Religious practice 0.89 2.05 1.31 2.97 1.12 1.60 66 -Fraternal organizations 0.16 1.17 0.05 0.66 0.10 0.93 67 -Child/family organizations 0.10 0.88 0.21 1.33 0.16 1.15 68 -Other organizations 0.34 2.40 0.32 1.53 0.32 1.98 69 -Travel: organizations 0.43 1.04 0.52 1.02 0.48 1.03 70 -Sports events 0.30 1.31 0.26 1.28 0.28 1.29 71 -Miscellaneous events 0.07 0.52 0.08 0.59 0.07 0.56 72-Movies 0.31 1.25 0.26 1.13 0.28 1.19 73-Theatre 0.13 0.93 0.06 0.48 0.09 0.72 74-Museums 0.04 0.37 0.03 0.35 0.03 0.36 75 -Visiting with others 4.24 5.72 5.84 6.42 5.10 6.16 76 -Parties 0.64 2.05 0.44 1.65 0.53 1.84 77 -Bars/lounges 0.71 2.21 0.46 2.09 0.57 2.15 78 -Other events 0.12 0.72 0.18 1.18 0.15 0.99 79 -Travel: events/social 1.40 1.82 1.26 1.67 1.32 1.74 (Continued on the following page) Table 15A-6. Weighted Mean Hours Per Week by Gender: 87 Activities and 10 Subtotals (continued) Men Women Men and women N=410 N=561 N=971 Activity Mean Std. dev. Mean Std. dev. Mean Std. dev. 80 -Active sports 1.05 2.62 0.50 1.68 0.76 2.18
81 -Outdoors 1.49 4.59 0.48 1.67 0.94 3.39 82 -Walking/biking 0.52 1.31 0.23 0.98 0.36 1.16 83-Hobbies 0.69 3.88 0.06 0.43 0.35 2.67 84 -Domestic crafts 0.30 1.59 2.00 4.72 1.21 3.93 85 -Art/literature 0.05 0.45 0.13 1.03 0.09 0.81 86 -Music/drama/dance 0.06 0.49 0.07 0.47 0.07 0.48 87-Games 0.60 2.00 0.99 3.16 0.81 2.69 88 -Classes/other 0.41 1.75 0.28 1.50 0.34 1.62 89 -Travel: active leisure 0.76 1.91 0.43 1.43 0.58 1.68 90-Radio 0.39 1.40 0.39 1.55 0.39 1.49 91 -TV 14.75 12.14 13.95 10.67

14.32 11.38 92 -Records/tapes 0.46 2.35 0.33 2.13 0.39 2.23 93 -Reading books 0.37 1.52 0.56 1.83 0.47 1.70 94 -Reading m?gazines/N.A. 1.32 2.81 1.97 3.67 1.67 3.32 95 -Reading newspapers 1.86 2.72 1.47 2.27 1.65 2.49 96 -Conversations 1.61 2.19 2.18 2.74 1.91 2.52 97 -Letters 0.20 1.06 0.31 1.12 0.26 1.10 98 -Other passive leisure 1.68 3.53 1.41 3.32 1.53 3.42 99 -Travel: passive leisure 0.18 0.49 0.13 0.49 0.15 0.49 Source: Hill, 1985.
Table 15A-7. Ranking of Occupations by Median Years of Occupational Tenure Barbers Farmers, except horticultural Railroad conductors and yardmasters Clergy Dentists Telephone line installers and repairers Millwrights Locomotive operating occupations Managers; farmers, except horticultural Telephone installers and repairers Airplane pilots and navigators Supervisors: police and detectives Grader, dozer, and scraper operators Tailors Civil engineers Crane and tower operators Supervisors, n.e.c. Teachers, secondary school Teachers, elementary school Occupation Dental laboratory and medical applicance technicians Separating, filtering, and clarifying machine oeprators Tool and die makers Lathe and turning machine operators Machinists
Pharmacists Stationary engineers Mechanical engineers Chemists, except biochemists Inspectors, testers, and graders Electricians Operating engineers Radiologic technicians Electrical power installers and repairers Supervisors; mechanics and repairers Heavy equipment mechanics Bus, truck, and stationary engine mechanics Physicians Construction inspectors Cabinet makers and bench carpenters Industrial machinery repairers Automobile body and related repairers Median years of occupational tenure 24.8 21.1 18.4 15.8 15.7 15.0 14.8 14.8 14.4 14.3 14.0 13.8 13.3 13.3 13.0 12.9 12.9 12.5 12.4 12.3 12.1 12.0 11.9 11.9 11.8 11.7 11.4 11.1 11.0 11.0 11.0 10.9 10.8 10.7 10.7 10.7 10.7 10.7 10.6 . 10.6 10.4 (Continued on the following page)
Table 15A-7. Ranking of Occupations by Median Years of Occupational Tenure (continued) Occupation Electrical and electronic engineers Plumbers, pipefitters, and steamfitters Licensed practical nurses Brickmasons and stonemasons Truck drivers, heavy Tile setters, hard and soft Lawyers Supervisors: production occupations Administrators, education and related fields Engineers, n.e.c. Excavating and loading machine operators Firefighting occupations Aircraft engine mechanics Police and detectives, public service Counselors, educational and vocational Architects Stuctural metal workers Aerospace engineers Miscellaneous aterial moving equipment operators Dental hygienists Automobile mechanics Registered nurses Speech therapists Binding and twisting machine operators Managers and administrators, n.e.c. Personnel and labor relations managers Office machine repairer Electronic repairers, commercial and industrial equipment Welders and cutters Punching and stamping press machine operators Sheet metal workers Administrators and officials, public administraion Hairdressers and cosmetologists Industrial engineers Librarians Inspectors and compliance officers, except construction Upholsterers Payroll and timekeeping clerks Furnace, kiln, and oven operators, except food Surveying and mapping technicians Chemical engineers Median years of occupational tenure 10.4 10.4 10.3 10.2 10.1 10.1 10.1 10.1 10.1 10.0 10.0 10.0 10.0 9.7 9.7 9.6 9.6 9.6 9.4 9.4 9.3 9.3 9.3 9.3 9.1 9.0 9.0 9.0 9.0 9.0 8.9 8.9 8.9 8.9 8.8 8.8 8.6 8.6 8.6 8.6 8.6 (continued on the following page) Table 15A-7. Ranking of Occupations by Median Years of Occupational Tenure (continued) Occupation Sheriffs, bailiffs, and other law enforcement officers Concrete and terrazzo finishers Sales representatives, mining, manufacturing, and wholesale Supervisors: general office Specified mechanics and repairers, n.e.c. Stenographers Typesetters and compositors Financial managers Psychologists Teachers: special education Statistical clerks Designers Water and Sewage Treatment plant operators Printing machine operators Heating, air conditioning, and refrigeration mechanics Supervisors; distribution, scheduling, and adjusting clerks Insurance sales occupations Carpenters Public transportation attendants Drafting occupations Butchers and meatcutters Miscellaneous electrical and electronic equipment repairers Dressmakers Musicians and composers Supervisors and proprietors; sales occupations Painters, Sculptors, craft-artists, and artist printmakers Mechanics and repairers, not specified Engineering technicians, n.e.c. Clinical laboratory technologists and technicians Purchasing managers Purchasing agents and buyers, n.e.c. Photographers Chemical technicians Managers; properties and real estate Accountants and auditors Religious workers, n.e.c. Secretaries Social workers Operations and systems researchers and analysts Postal clerks, except mail carriers Managers; marketing, advertising, and public relations Median years of occupational tenure 8.6 8.6 8.6 8.6 8.5 8.5 8.5 8.4 8.4 8.4 8.3 8.3 8.3 8.2 8.1 8.1 8.1 8.0 8.0 8.0 8.0' 7.9 7.9 7.9 7.9 7.9 7.7 7.7 7.7 7.7 7.7 7.6 7.6 7.6 7.6 7.6 7.5 7.5 7.4 7.4 7.3 (continued on the following page) Table 15A-7. Ranking of Occupations by Median Years of Occupational Tenure (continued) Occupation Farm workers Managers; medicine and health Data processing equipment repairers Bookkeepers, accounting and auditing clerks Grinding, abrading, buffing, and polishing machine operators Management related occupations, n.e.c. Supervisiors; cleaning and building service workers Management analysts Science technicians, n.e.c. Mail carriers, postal service Knitting, looping, taping, and weaving machine operators Electrical and electronic technicians Painting and paint spraying machine operators Postsecondary teachers, subject not specified Crossing guards Inhalation therapists Carpet installers Computer systems analysts and scientists Other financial officers Industrial truck and tractor equipment operators Textile sewing machine operators Correctional institution officers Teachers, prekindergarten and kindergarten Supervisors; financial records processing Miscellaneous Textile machine operators Production inspectors, checkers, and examiners Actors and directors Health technologists and technicians, n.e.c. Miscellaneous machine operators, n.e.c. Private household cleaners, and servants Buyers, wholesale and retail trade, excluding farm products Real estate sales occupations Electrical and electronic equipment assemblers Bus drivers Editors and reporters Laundering and dry cleaning machine operators Meter readers Painters, construction and maintenance Driver-sales workers Teachers, n.e.c. Order clerks Physicians' assistants Median years of occupational tenure 7.3 7.2 7.2 7.1 7.0 7.0 7.0 7.0 7.0 7.0 6.9 6.9 6.9 6.8 6.8 6.7 6.7 6.6 6.6 6.6 6.6 6.5 6.4 6.4 6.4 6.3 6.3 6.3 6.2 6.2 6.0 6.0 6.0 6.0 6.0 6.0 5.9 5.9 5.9 5.9 5.8 5.8 (continued on the following page) Table 15A-7. Ranking cif Occupations by Median Years of Occupational Tenure (continued) Occupation Billing clerks Drywall installers Construction trades, n.e.c. Telephone operators Authors Nursing aides, orderlies, and attendants Dental assistants Timber cutting and logging occupations Molding and casting machine operators Miscellaneous hand-working occupations Production coordinators Public relations specialists Personnel clerks, except payroll and bookkeeping Assemblers Securities. and financial services sales occupations Salesworkers, furniture and home furnishings Insurance adjusters, examiners, and investigators Pressing machine operators Roofers Graders and sorters, except agricultural Supervisors; related agricultural occupations Typists Supervisors; motor vehicle operators Personnel, training, and labor relations specialists Legal assistants Physical therapists Advertising and related sales occupations Records clerks Economists Technicians, n.e.c. Expediters Sales occupations, other business services Computer operators Computer programmers Investigators and adjusters, except insurance Underwriters Salesworkers, parts Artists, performers, and related workers, n.e.c. Teachers' aides Maids and housemen Sawing machine operators Machine operators, not specified Weighers, measurers, and checkers Median years of occupational tenure 5.8 5.7 5.7 5.7 5.6 5.6 5.6 5.5 5.5 5.5 5.5 5.5 5.4 5.4 5.4 5.4 5.3 5.3 5.3 5.3 5.2 5.2 5.2 5.2 5.2 5.2 5.1 5.1 5.1 5.0 5.0 4.9 4.8 4.8 4.8 4.8 4.8 4.8 4.6 4.6 4.6 4.5 4.5 (continued on the following page) Table 15A-7. Ranking of Occupations by Median Years of Occupational Tenure (continued) Occupation Traffic, shipping, and receiving clerks Salesworkers, hardware and building supplies Biological technicians Athletes Bill and account collectors Taxicab drivers and chauffeurs Slicing and cutting machine operators Administrative support occupations, n.e.c. Mixing and blending machine operators Waiters and waitresses
Janitors and cleaners Production helpers General office clerks Machine feeders and offbearers Interviewers Bartenders Eligibility clerks, social welfare Bank tellers Cooks, except short-order Health aides, except nursing Laborers, except construction Welfare service aides Salesworkers, motor vehicles and boats Cost and rate clerks Construction laborers Hand packers and packagers Transportation ticket and reservation agents Animal caretakers, except farm Photographic process machine operators Freight, stock, and material movers, hand, n.e.c. Data-entry keyers Bakers Dispatchers Guards and police, except public service Packaging and filling machine operators Receptionists Library clerks Truckdrivers, light Salesworkers, radio, television, hi-ti, and appliances Salesworkers, apparel Sales counter clerks Salesworkers, other commodities Median years of occupational tenure 4.5 4.5 4.4 4.4 4.4 4.4 4.3 4.3 4.3 4.2 4.2 4.1 4.0 3.9 3.9 3.9 3.9 3.8 3.8 3.7 3.7 3.7 3.7 3.6 3.6 3.5 3.5 3.5 3.5 3.4 3.4 3.4 3.3 3.3 3.3 3.3 3.3 3.2 3.2 3.1 3.1 3.1 (continued on the following page)
Table 15A-7. Ranking of Occupations by Median Years of Occupational Tenure (continued} Occupation Small engine repairers Supervisors, food preparation and service occupations Health record technologists and technicians Helpers, construction trades Attendants, amusement and recreation facilities Street and door-to-door salesworkers Child-care workers, private household Child-care workers, except private household Information clerks, n.e.c. Hotel clerks Personal service occupations, n.e.c. Salesworkers, shoes Garage and service station related occupations Short-order cooks File clerks Cashiers Mail clerks, except postal service Misce.llaneous food preparation occupations News vendors Vehicle washers and equipment cleaners Messengers Kitchen workers, food preparation Stock handlers and baggers Waiters and waitresses assistants Food counter, fountain, ;;ind related occupations
n.e.c. -not elsewhere classified Source: Carey, 1988. Median years of occupational tenure 3.1 3.0 2.9 2.9 2.8 2.7 2.7 2.7 2.7 2.7 2.7 2.6 2.6 2.5 2.5 2.4 2.3 2.3 2.3 2.3 2.3 2.1 1.9 1.7 1.5 Table 15B-1. Annual Geographical Mobility Rates, by Type of Movement for Selected 1-Year Periods: 1960-1992 (numbers in thousands) Residing in the United States at beginning of period Residing outside the Different Different County United States house, at the Mobility Total same Same Different Different beginning of period movers Total county Total State State Region period NUMBER 1991-92 42,800 41,545 26,587 14,957 7,853 7,105 3,285 1,255 1990-91 41,539 40,154 25,151 15,003 7,881 7,122 3,384 1,385 1989-90 43,381 41,821 25,726 16,094 8,061 . 8,033 3,761 1,560 1988-89 42,620 41, 153 26,123 15,030 7,949 7,081 3,258 1,467 1987-88 42,174 40,974 26,201 14,772 7,727 7,046 3,098 1,200 1986-87 43,693 42,551 27,196 15,355 8,762 6,593 3,546 1,142 1985-86 43,237 42,037 26,401 15,636 8,665 6,791 3,778 1,200 1984-85 46,470 45,043 30,126 14,917 7,995 6,921 3,647 1,427 1983-84 39,379 38,300 23,659 14,641 8,198 6,444 3,540 1,079 1982-83 37,408 36,430 22,858 13,572 7,403 6,169 3,192 978 1981-82 38,127 37,039 23,081 13,959 7,330 6,628 3,679 1,088 1980-81 38,200 36,887 23,097 13,789 7,614 6,175 3,363 1,313 1970-71 37,705 36,161 23,018 13,143 6,197 6,946 3,936 1,544 1960-61 36,533 35,535 24,289 11,246 5,493 5,753 3,097 988 PERCENT 1991-92 17.3 16.8 10.7 6.0 3.2 2.9 1.3 0.5 1990-91 17.0 16.4 10.3 6.1 3.2 2.9 1.4 0.6 1989-90 17.9 17.3 10.6 6.6 3.3 3.3 1.p 0.6 1988-89 17.8 17.2 10.9 6.3 3.3 3.0 1.4 0.6 1987-88 17.8 17.3 11.0 6.2 3.3 3.0 1.3 0.5 1986-87 18.6 18.1 11.6 6.5 3.7 2.8 1.5 0.5 1985-86 18.6 18.0 11.3 6.7 3.7 3.0 1.6 0.5 1984-85 20.2 19.6 13.1 6.5 3.5 3.0 1.6 0.6 1983-84 17.3 16.8 10.4 6.4 3.6 2.8 1.6 0.5 1982-83 16.6 16.1 10.1 6.0 3.3 2.7 1.4 0.4 1981-82 17.0 16.6 10.3 6.2 3.3 3.0 1.6 0.5 1980-81 17.2 16.6 10.4 6.2 3.4 2.8 1.5 0.6 1970-71 18.7 17.9 11.4 6.5 3.1 3.4 2.0 0.8 1960-61 20.6 20.0 13.7 6.3 3.1 3.2 1.7 0.6 Source: U.S. Bureau of Census, 1993.
Table 158-2. Mobility of the Resident Population by State: 1980 Percent distribution -residence in 1975" Persons Same 5 years house old, and in Different Different Different over" 1980 house, county, county, Region, division, 1980 as same same different and state (1,000) 1975 county state state United States 210,323 53.6 25.1 9.8 9.7 Northeast 46,052 61.7 22.3 8.0 6.1 New England 11,594 59.1 23.4 6.7 9.2 Maine 1,047 56.9 24.0 7.5 10.8 New Hampshire 857 51.6 22.8 6.2 18.5 Vermont 476 54.4 23.9 6.5 14.3 Massachusetts 5,398 61.0 22.7 7.6 7.0 Rhode Island 891 60.5 23.9 5.0 8.7 Connecticut 2,925 59.0 24.4 5.5 9.3 Middle Atlantic 34,458 62.6 21.9 8.4 5.0 New York 16,432 61.5 22.6 9.3 3.8 New Jersey 6,904 61.5 20.0 8.6 7.8 Pennsylvania 11,122 65.0 22.0 7.1 5.2 Midwest 54,513 55.4 26.4 10.2 7.0 East North Central 38,623 56.0 27.4 9.6 6.0 Ohio 10,015 56.7 27.9 9.0 5.7 Indiana 5,074 54.8 27.5 9.6 7.6 Illinois 10,593 55.5 28.5 8.1 6.1 Michigan 8,582 56.4 26.2 11.3 5.1 Wisconsin 4,360 56.2 25.5 11.0 6.7 West North Central 15,890 53.9 24.0 11.8 9.4 Minnesota 3,770 55.6 22.8 13.3 7.3 Iowa 2,693 55.6 25.0 10.9 7.9 Missouri 4,564 54.0 24.1 11.8 9.4 North Dakota 598 51.7 23.1 11.4 12.7 South Dakota 633 52.9 23.2 12.1 11.1 Nebraska 1,448 53.1 24.4 11.0 10.5 Kansas 2,184 50.2 25.1 10.7 12.6 (Continued on the following page) Table 158-2. Mobility of the Resident Population by State: 1980 (continued) Percent distribution -residence in 1975* Persons Same 5 years house old, and in Different Different Different over" 1980 house, county, county, Region, division, 1980 as same same different and state (1,000) 1975 county state state South 69,880 52.4 24.1 10.0 12.0 South Atlantic 34,498 52.7 22.4 9.7 13.6 Delaware 555 57.0 26.3 2.0 13.3 Maryland 3,947 55.5 21.9 10.3 10.4 District of Columbia 603 58.2 22.7 NA 16.3 . Virginia 4,99i 51.0 17.9 15.0 13.9 West Virginia 1,806 60.9 23.4 6.6 8.6 North Carolina 5,476 56.9 23.5 8.9 9.8 South Carolina 2,884 57.5 22.3 7.7 11.5 Georgia 5,052 52.5 22.8 12.2 11.5. Florida 9,183 46.2 23.7 . 7.8 19.6 East South Central 13,556 56.0 25.9 7.9 9.5 Kentucky 3,379 54.4 27.2 8.6 9.0 Tennessee 4,269 54.2 27.2 7.4 10.6 Alabama 3,601 57.6 25.3 7.4 8.9 Mississippi 2,307 59.0 22.5 8.6 9.2 West South Central 21,826 49.6 25.6 11.8 11.0 Arkansas 2,113 53.1 24.8 9.1 12.4 Louisiana 3,847 57.0 *24.3 9.2 8.4 Oklahoma 2,793 47.6 24.9 12.3 13.7 Texas 13,074 47.3 26.2 12.9 11.0 West 39,879 43.8 28.3 11.0 13.4 Mountain 10,386 42.7 25.1 9.1 21.1 Montana 722 47.3 24.5 12.3 15.0 Idaho 852 44.4 24.7 9.5 20.0 Wyoming 425 38.4 23.6 8.6 28.3 Colorado 2,676 39.8 22.7 14.8 20.6 New Mexico 1,188 50.3 23.2 7.2 17.4 Arizona 2,506 41.9 27.1 5.0 23.9 Utah 1,272 45.8 27.8 8.4 16.0 Nevada 745 34.8 27.4 3.6 31.5 (continued on the following page) Table 158-2. Mobility of the Resident Population by State: 1980 (continued} Persons 5 years old, and over" Region, division, 1980 and state (1,000) Pacific 29,493 Washington 3,825 Oregon 2,437 California 21,980 Alaska 363 Hawaii 888 *Survey assessed changes in residence between 1975 and 1980. b Includes persons residing abroad in 1975. NA = not applicable. Source: U.S. Bureau of the Census, Statistical Abstract, 1984. Percent distribution -residence in 1975* Same house in Different Different 1980 house, county, as same same 1975 county state 44.2 29.4 11.6 43.7 27.7 10.1 41.4 26.6 13.4 44.6 30.2 12.1 32.2 27.6 8.7 49.3 25.2 2.8 Different county, different state 10.7 16.2 16.9 8.5 29.1 16.9 Different County Same State 18.5% Local Movers, Within Same County 61.95% Different State Abroad 2.9% Figure 15-1. Distribution of Individuals Moving by Type of Move: 1991-92
Source: U.S. Bureau of the Census, 1993a REFERENCES FOR CHAPTER 15 AIHC. (1994) Exposure factors sourcebook. Washington, DC. American Industrial Health Council. . Bureau of Labor Statistics. (1987) Most occupational exposures .are voluntary. Washington, DC: U.S. Department of Labor. Carey, M. (1988) Occupational tenure in 1987: Many workers have remained in their fields. Monthly Labor Review. October 1988. 3-12. Carey, M. (1990) Occupational tenure-; employer tenure, and occupational mobility. Occupational Outlook Quarterly. Summer 1990: 55-60. Hill, M.S. (1985) Patterns of time use. In: Juster, F.T.; Stafford, F.P., Eds. Time, goods, and well-being. Ann Arbor, Ml: University of Michigan, Survey Research Center, Institute for Social Research; pp. 133-166. Israeli, M; Nelson, C.B. (1992) Distribution and expected time of residence for U.S. households. Risk Anal. 12(1):65-72. James, l.R.; Knuiman, M.W. (1987) An application of Bayes methodology to the analysis of diary records from a water use study. J. Am. Sta. Assoc. 82(399):705-711. Johnson, T. and Capel, J. (1992) A monte carlo approach to simulating residential occupancy periods and its application to the general U.S. population. Research Triangle Park, NC: U.S. Environmental Protection Agency, Office of Air Quality and Standards. Juster, F.T.; Hill, M.S.; Stafford, F.P.; Parsons, J.E. (1983) Study description. 1975-1981 time use longitudinal panel study. Ann Arbor, Ml: The University of Michigan, Survey Research Center, Institute for Social Research. Lehman, H.J. (1994) Homeowners relocating at faster pace. Virginia Homes Newspaper, Saturday, June 15, P. E1. National Association of Realtors (NAR). (1993) The homebuying and selling process: 1993. The Real Estate-Business Series. Washington, DC.: NAR. Palisade. (1992) @Risk users guide. Newfield, NY: Palisade Corporation. Robinson, J.P. (1977) Changes in Americans' use of time: 1965-1975. A progress report. Cleveland, OH: Cleveland State University, Communication Research Center.
Robinson, J.P; Thomas, J. (1991) Time spent in activities, locations, and microenvironments: a California-National Comparison Project report. Las Vegas, NV: U.S. Environmental Protection Agency, Environmental Monitoring Systems . Laboratory. Sell, J. (1989) The use of children's activity patterns in the development of a strategy for soil sampling in West Central Phoenix. The Arizona Department of Environmental Quality, Phoenix, Arizona. Sexton, K; Ryan, P.B. (1987) Assessment of human exposure to air pollution: methods, measurements, and models. In: Watson, A.; Bates, R.R.; Kennedy, D., eds. Air pollution, the automobile and public health: research opportunities for quantifying risk. Washington, DC: National Academy of Sciences Press. Tarshis, B. (1981) The "Average American" book. New York, NY: New American Library, p. 191. Timmer, S.G.; Eccles, J.; O'Brien, K. (1985) How children use time. In: Juster, F.T.; Stafford, F.P.; eds. Time, goods, and well-being. Ann Arbor, Ml: University of Michigan, Survey Research Center, Institute for Social Research, pp. 353-380. Tsang, A.M.; Klepeis, N.E. (1996) Results tables from a detailed analysis of the National Human Activity Pattern Survey (NHAPS) response. Draft Report prepared for the U.S. Environmental Protection Agency by Lockheed Martin, Contract No. 68-W6-001; Delivery Order No. 13. U.S. Bureau of the Census. (1993a) Geographical mobility: March 1991 to March 1992. Current population reports P.20-473. U.S. Bureau of the Census. (1993b)American Housing Survey for the United States in 1991. Washington, DC: U.S. Government Printing Office. U.S. EPA. (1989) Exposure factors handbook. Washington, DC: Office of Health and Environmental Assessment. EPA/600/08-89/043. U.S. EPA. (1992) Dermal exposure assessment: principles and applications. Washington, DC: Office of Health and Environmental Assessment. EPA No. 600/8-91-011 B. Interim Report. Wiley, J.A.; Robinson, J.P.; Cheng, Y.; Piazza, T.; Stork, L.; Plasden, K. (1991) Study of children's activity patterns. California Environmental Protection Agency, Air Resources Board Research Division. Sacramento, CA. . DOWNLOADABLE TABLES FOR CHAPTER 15 The following selected tables are available for download as Lotus 1-2-3 worksheets. Table 15-18. Range of Recommended Defaults for Dermal Exposure Factors [WK1, 1 kb] Table 15-19. Number of Times Taking a Shower at Specified Daily Frequencies by the Number of Respondents [WK1, 8 kb] Table 15-20. Times (minutes) Spent Taking Showers by the Number of Respondents [WK1, 7 kb] Table 15-21. Number of Minutes Spent Taking a Shower (minutes/shower) [WK1, 7 kb] Table 15-22. Time (minutes) Spent in the Shower Room Immediately After Showering by the Number of Respondents [WK1, 8 kb]
Table 15-23. Number of Minutes Spent in the Shower Room Immediately After (minutes/shower) [WK1, 7 kb] Table 15-24. Number of Baths Given or Taken in One Day by Number of Respondents [WK1, 8 kb] Table 15-25. Total Time Spent Taking or Giving a Bath by the Number of Respondents [WK1, 7 kb] . . . . Table 15-26. Number of Minutes Spent Giving and Taking the Bath(s) (minute.s/bath) [WK1, 7 kb] Table 15-27. Time Spent in the Bathroom Immediately After the Bath(s) by the Number of Respondents [WK1, 8 kb] Table 15-28. Number of Minutes Spent in the Bathroom Immediately After the Bath(s) (minutes/bath) [WK1, 7 kb] Table 15-29. Total Time Spent Altogether in the Shower or Bathtub by the Number of Respondents [WK1, 11 kb] Table 15-30. Total Number of Minutes Spent Altogether in the Shower or Bathtub . (minutes/bath) [WK1, 7 kb] Table 15-31. Time Spent in the Bathroom Immediately Following a Shower or Bath by the Number of Respondents [WK1, 10 kb] Table 15-32. Number of Minutes Spent in the Bathroom Immediately Following a *Shower or Bath (minutes/bath) [WK1, 7 kb] Table 15-33. Range of Number of Times Washing the Hands at Specified Daily Frequencies by the Number of Respondents [WK1, 7 kb]
Table 15-50. Number of Hours Worked in a Week That Was Outdoors (hours/week) [WK1, 7 kb] Table 15-57. Number of Minutes Spent Playing on Sand or Gravel in a Day by the Number of Respondents [WK1, 10 kb] Table 15-58. Number of Minutes Spent Playing in Sand or Gravel (minutes/day) [WK1, 7 kb] Table 15-59. Number of Minutes Spent Playing in Outdoors on Sand, Gravel, Dirt, or Grass When Fill Dirt Was Present by the Number of Respondents [WK1, 10 kb] Table 15-60. Number of Minutes Spent Playing on Sand, Gravel, Dirt, or Grass When Fi.II Dirt Was Present (minutes/day) [WK1, 7 kb] Table 15-61. Range of the Time Spent Working in a Garden or Other Circumstances in a Month by the Number of Respondents [WK1, 11 kb] Table 15-62. Number of Hours Spent Working with Soil in a Garden or Other Circumstances Working (hours/month) [WK1, 7 kb] Table 15-63. Range of Number of Minutes Spent Playing on Grass in a Day by the Number of Respondents [WK1, 11 kb] Table 15-64. Number of Minutes Spent Playing on Grass (minutes/day) [WK1, 7 kb] Table 15-65. Number of Times Swimming in a Month in Freshwater Swimming Pool by the Number of Respondents [WK1, 21 kb] Table 15-66. Range of the Average Amount of Time Actually Spent in the Water by Swimmers by the Number of Respondents [WK1, 12 kb] Table 15-67. Number of Minutes. Spent Swimming in a Month in Freshwater Swimming Pool (minutes/month) [WK1, 8 kb] Table 15-79. Statistics for 24-Hour Cumulative Number of Minutes Spent in Indoor Playing [WK1, 11 kb] Table 15-80. Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor Playing [WK1, 10 kb] Table 15-85. Statistics for 24-Hour Cumulative Number of Minutes Spent in Active Sports [WK1, 12 kb] Table 15-86. Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor Recreation [WK1, 12 kb] Table 15-87. Statistics for 24-Hour Cumulative Number of Minutes Spent in Exercise [WK1, 12 kb] Table 15-91. Statistics for 24-Hour Cumulative Number of Minutes Spent in Bathing [WK1, 12 kb] Table 15-92. Statistics for 24-Hour Cumulative Number of Minutes Spent in Yardwork/Maintenance [WK 1, 12 kb] Table 15-93. Statistics for 24-Hour Cumulative Number of Minutes Spent in Sports/Exercise [WK1, 12 kb]
Table 15-102. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at School [WK1, 12 kb] Table 15-108. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors on School Grounds/Playground [WK1, 11 kb] Table 15-110. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a Pool/River/Lake [WK1, 12 kb] Table 15-113. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Kitchen [WK1, 12 kb]

Table 15-114. Statistics for 24-Hour Cumulative Number of Minutes Spent in the Bathroom [WK1, 12 kb] Table 15-115. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Bedroom [WK1, 12 kb] Table 15-116. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Garage [WK1, 11 kb] Table 15-117. Statistics for 24-Hour Cumulative Number of Minutes Spent in the Basement [WK 1 , 12 kb] ; *Table 15-118 .. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Utility Room or Laundry Room [WK1, 11 kb] Table 15-121. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling in a Car [WK1, 12 kb] Table 15-122. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling in a Truck (Pick-upNan) [WK1, 12 kb] Table 15-123. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on a Motorcycle, Moped, or Scooter [WK1, 9 kb] Table 15-124. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling in Other Trucks [WK1, 12 kb] Table 15-125. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on a Bus [WK1, 12 kb] Table 15-126. Statistics for 24-Hour Cumulative Number of Minutes Spent Walking [WK1, 12 kb] Table 15-127. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on

a Bicycle/Skateboard/ Rollerskate [WK 1, 11 kb] Table 15-128. Statistics for 24-Hour Cumulative Number of Minutes Spent Waiting on a Bus, Train etc., Stop [WK1, 11 kb] Table 15-129. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on a Train/Subway/Rapid Transit [WK1, 12 kb]
Table 15-130. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on .an Airplane [WK1, 10 kb] Table 15-131. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors in a Residence (all rooms) [WK1, 12 kb] Table 15-132. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors (outside the residence) [WK 1 , 12 kb] Table 15-133. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling Inside a Vehicle [WK1, 12 kb] Table 15-135. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors Other Than Near a Residence or Vehicle Such as Parks, Golf Courses, or Farms [WK1, 12 kb] Table 15-166. Percent of Householders Living in Houses for Specified Ranges of Time [WK1, 1 kb] Table 15-167. Descriptive Statistics for Residential Occupancy Period [WK1, 1 kb] Table 15-168. Descriptive Statistics for Both Genders by Current Age [WK1, 3 kb] Volume III -Activity Factors Chapter 16 -Consumer Products 16. CONSUMER PRODUCTS 16.1. BACKGROUND 16.2. KEY CONSUMER PRODUCTS USE STUDIES 16.3. RELEVANT CONSUMER PRODUCTS USE STUDY 16.4. RECOMMENDATIONS REFERENCES FOR CHAPTER 16 APPENDIX 16A Table 16-1. Consumer Products Found in the Typical U.S. Household Table 16-2. Frequency of Use for Household Solvent Products (users-only) Table 16-3. Exposure Time of Use for Household Solvent Products (users-only) Table 16-4. Amount of Products Used for Household Solvent Products (users-only) Table 16-5. Time Exposed After Duration of Use for Household Solvent Products (users-only) Table 16-6. Frequency of Use and Amount of Product Used for Adhesive Removers Table 16-7. Adhesive Remover Usage by Gender
Table 16-8. Frequency of Use and Amount of Product Used for Spray Paint Table 16-9. Spray Paint Usage by Gender Table 16-10. Frequency of Use and Amount of Product Used for Paint Removers/Strippers Table *16-11. Paint Stripper Usage by Gender Table 16-12. Total Exposure Time of Performing Task and Product Type Used by Task for Household Cleaning Products* Table 16-13. Percentile Rankings for Total Exposure Time in Performing Household Tasks Table 16-14. Mean Percentile Rankings for Frequency of Performing Household Tasks Table 16-15. Mean and Percentile Rankings for Exposure Time Per Event of Performing Household Tasks Table 16-16. Total Exposure Time for Ten Product Groups Most Frequently Used for Household Cleaning Table 16-17. Total Exposure Time of Painting Activity of Interior Painters (hours) Table 16-18. Exposure Time of Interior Painting Activity/Occasion (hours) and Frequency of Occasions Spent Painting Per Year Table 16-19. Amount of Paint Used by Interior Painters Table 16-20. Number of Respondents Using Cologne, Perfume, Aftershave or Other Fragrances at Specified Daily Frequencies Table 16-21. Number of Respondents Using Any Aerosol Spray Product for Personal Care Item Such as Deodorant or Hair Spray at Specified Daily Frequencies Table 16-22. Number of Minutes Spent in Activities Working with or Being Near Freshly Applied Paints (minutes/day) Table 16-23. Number of Minutes Spent in Activities Working with or Near Household Cleaning Agents Such as Scouring Powders or Ammonia (minutes/day) Exposure Factors Handbook August 1997

Volume III -Activity Factors Chapter 16 -Consumer Products Table 16-24. Number of Minutes Spent in Activities (at home or elsewhere) Working with* or Near Floorwax, Furniture Wax or Shoe Polish (minutes/day) Table 16-25. Number of Minutes Spent in Activities Working with or Being Near Glue Table 16-26. Number of Minutes Spent in Activities Working with or Near Solvents, Fumes or Strong Smelling Chemicals (minutes/day) Table 16-27. Number of Minutes Spent in Activities Working with or Near Stain or Spot Removers (minutes/day) Table 16-28. Number of Minutes Spent in Activities Working with or Near Gasoline or Diesel-powered Equipment, Besides Automobiles (minutes/day) Table 16-29. Number of Minutes Spent Using Any Microwave Oven (minutes/day) Table 16-30. Number of Respondents Using a Humidifier at Home Table 16-31. Number of Respondents Indicating that Pesticides Were Applied by the Professional at Home to Eradicate Insects, Rodents, or Other Pests at Specified Frequencies Table 16-32. Number of Respondents Reporting Pesticides Applied by the Consumer at Home to Eradicate Insects, Rodents, or Other Pests at Specified Frequencies Table 16-33. Number of Minutes Spent in Activities Working with or Near Pesticides, Including Bug Sprays or Bug Strips (minutes/day) Table 16-34. Amount and Frequency of Use of Various Cosmetic and Baby Products Table 16-35. Summary of Consumer Products Use Studies Table 16A-1. Volumes Included in 1992 Simmons Study Exposure Factors Handbook August 1997 I -______ ____J Volume III -Activity Factors Chapter 16 -Consumer Products 16. CONSUMER PRODUCTS BACKGROUND Consumer products may contain toxic or potentially toxic chemical constituents to which humans may be exposed as a result of their use. For example, methylene chloride and other solvents and carriers are common in consumer products and may have human health concerns. Potential pathways of exposure to consumer products or chemicals released from consumer products during use occur via ingestion, inhalation, and dermal contact. Exposure assessments that address consumer products involve characterization of these potential exposure pathways and calculating exposure or dose (based on exposure pathway) of chemical substances released during use of consumer products. In order to estimate specific-pathway exposure for consumer products or their components, the following information is needed: amount of product used; concentration of product in each type of activity; percent weight of chemical present in product; duration and frequency of use or activity; and for dermal exposure, the amount of solution on skin after exposure (Hakkinen et al., 1991; U.S. EPA, 1987). This chapter presents information on the.amount of product used, frequency of use, and duration of use for various consumer products typically found in consumer households. All tables that present information for these consumer products are located at the end of this chapter. U.S. EPA (1987) has complied a comprehensive list of consumer . products found in typical American households. This list of consumer products is presented in Table 16-1. It should be noted that this chapter does not provide an exhaustive treatment .of all consumer products, but rather provides some background and data that can be utilized in an exposure assessment. Also, the data presented may not capture information needed to assess the highly exposed population (e.g., consumers who use commercial/ industrial strength products at home). The studies presented in the following sections represent readily available surveys for which data were collected on the frequency duration of use and amount of use of cleaning products, painting products, household solvent products, cosmetic and other personal care products, household equipment, pesticides, and tobacco. The studies have been classified as either key or relevant based on their applicability to exposure assessment needs. The reader is also referred to a document developed by the U.S. EPA, Office of Toxic Substances: Standard Scenarios for Estimating Exposure to Chemical Substances During Use of Consumer Products -Volumes I and II (U.S. EPA, 1986). This document presents data and supporting information required to assess consumer exposure to constituents in household cleaners and components of adhesives. Information presented includes a description of standard scenarios selected to represent upper bound exposures for each Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 16 -Consumer Products product. Values are also presented for parameters,that are needed to estimate exposure for defined exposure routes and pathways assumed for each scenario. An additional reference is the Simmons Market Research Bureau (SMRB), "Simmons Study of Media and Markets." This document provides an example of marketing data that are available that may be useful in assessing exposure to selected products. The reports are published annually. Data are collected on the buying habits of the U.S. populations over the past 12 months. This information is collected for over 1,000 consumer products. Data are presented on frequency of use, total number of buyers in each use category, and selected demographics. The consumer product data are presented according to the "buyer" and not necessarily according to the "user" (actively exposed person). It may be necessary to adjust the data to reflect potential uses in a household. The reports are available for purchase from the Simmons Market Research Bureau, (212) 916-8970. Appendix Table 16A-1 presents a list of product categories in SMRB for which information is available. 16.2. KEY CONSUMER PRODUCTS USE STUDIES Westat (1987a) -Household Solvent Products: A National Usage Survey-Westat (1987a) conducted a nationwide survey to determine consumer exposure to common household products believed to contain methylene chloride or its substitutes (trichloroethane, . trichloroethylene, carbon tetrachloride, perchloroethylene, . and 1, 1, 1,2,2,2-trichlorotrifluoroethane). The survey methodology was comprised of three phases. In the first phase, the sample population was generated by using a random digit dialing (ROD) procedure. Using this procedure, telephone numbers of households were randomly selected by utilizing an unbiased, equal probability of selection method, known as the "Waksberg Method" (Westat,. 1987a). After the respondents in the selected households (18 years and older) agreed to participate in the survey, the second phase was initiated. It involved a mailout of questionnaires and product pictures to each respondent. In the third phase, a telephone follow-up call was made to those respondents who did not respond to the mailed questionnaire within a 4-week period. The same questionnaire was administered over the telephone to participants who did not respond to the mailed questionnaire. Of the 6,700 individuals contacted for the survey, 4,920 individuals either responded to the mailed questionnaire or to. a telephone interview (a response rate of 73 percent). Survey questions included how often the products were used in the last 12 months; when they were last used; how much time was spent using a product (per occasion or year), and the time the respondent remained in the room after use; how much of a product was used per occasion or year; and what protective measures were used (Westat, 1987a).

Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 16 -Consumer Products Thirty-two categories of common household products were included in the survey and are presented in Table 16-2. Tables 16-2, 16-3, 16-4, and 16-5 provide means, medians, and percentile rankings for the following variables: frequency of use, exposure time, amount of use, and time exposed after use. An advantage of this study is that the random digit dialing procedure (Waksberg Method) used in identifying participants for this survey enabled a diverse selection of a representative, unbiased, sample of the U.S. population (Westat 1987a). Also, empirical data generated from this study will provide more accurate calculations of human exposure to consumer household products than estimates previously used. However, a limitation associated with this study is that the data generated were based on recall behavior. Another limitation is that extrapolation of these data to long-term use patterns may be difficult. Abt (1992) -Methylene Chloride Consumer Use Study Survey Findings -As part of a plan to assess the effectiveness of labeling of consumer products containing methylene chloride, Abt conducted a telephone survey of nearly five thousand households (Abt, 1992). The survey was conducted in April and May of 1991. Three classes of products were of concern: paint strippers, non-automotive spray paint, and adhesive removers. The survey paralleled a 1986 consumer use survey sponsored jointly by Abt and the U.S. EPA. Results of the survey were the following (Abt, 1992):

Compared to the 1986 findings, a significantly smaller proportion of current survey respondents used a paint stripper, spray paint, or adhesive remover.

The proportion of the population who used the three products recently (within the past year) decreased

Those who used the products reported a significantly longer time since. their last use.

For all three products, the reported amount used per year was significantly higher in the current survey. The survey was conducted to estimate the percent of the U.S. adult population using paint remover, adhesive remover, ar1d non-automotive spray paint. In addition, . an estimate of the population using these products containing methylene chloride was determined. A survey question-naire was developed to collect product usage data and demographic data. The survey sample was generated using a ROD technique. Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 16 -Consumer Products A total of 4,997 product screener interviews were conducted for the product interview sections; the number of respondents were: 381 for paint strippers, 58 for adhesive removers, and 791 for non-automotive spray paint. Survey responses were weighted to allow estimation at the level of the total U.S. population (Abt, 1992). A follow-up mail survey was also conducted using a short questionnaire. Respondents who had used the product in the past year or had purchased the product in the past 2 years and still had the container were asked to respond to the questionnaire (Abt, 1992). Of the mail questionnaires (527) sent out, 259 were returned. The questionnaire responses included 67 on paint strippers, 6 on adhesive removers, and 186 on non-automotive spray paint. Results of the survey are presented in Tables 16-6 through 16-11 (N's are unweighted). Data are presented for recent users. Recent users were defined as persons who have used the product within the last year of the survey or who have purchased the product in the past 2 years. *An advantage of this survey is that the survey population was large and the survey responses were weighted to represent the U.S. population. In addition, the survey was

designed to collect data for frequency of product use and amount of product used by gender. A limitation of the survey is that the data were generated based on recall behavior. Extrapolation of these data to accurately reflect long-term use patterns may be difficult. Westat (1987b) -National Usage Survey of Household Cleaning Products -Westat (1987b)-collected usage data from a nationwide survey to assess the magnitude of exposure of consumers to various products used when performing certain household cleaning tasks. The survey was conducted between the middle of November, 1985 to the middle of January, 1986. Telephone interviews were conducted with 193 households. According to Westat (1987b), the resulting response rate for this survey was 78 percent. The Waksberg method discussed previously in the Westat (1987a) study was also used in randomly selecting telephone numbers employed in the Westat (1987b) survey. The survey was designed to obtain information on cleaning activities performed in the interior of the home during the previous year. The person who did the majority of the cleaning in the kitchen and bathroom areas of each household was interviewed. Of those respondents, the primary cleaner was female in* 160 households (83 percent) and male in 30 households (16 percent); the sex of the respondents in three remaining households was not ascertained (Westat, 1987b ). Data obtained from the survey included the frequency of performing 14 different cleaning tasks; the amount of time (duration) spent at each task; the cleaning product most frequently used; the type of product (liquid, powder, aerosol or spray pump) used; and the protective measures taken during cleaning such as wearing rubber gloves or having a window open or an exhaust fan on (Westat, 1987b ). Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 16 -Consumer Products The survey data are presented in Tables 16-12 through 16-16. Table 16-12 pres*ents the mean and median total exposure time of use for each cleaning task and the product type preferred for each task. The percentile rankings for the total time exposed to the products used for 14 cleaning tasks are presented in Table 16-13. The mean and percentile rankings of the frequency in performing each task are presented in Table 16-14. Table 16-15 shows the mean and percentile rankings for exposure time per event of performing household tasks. The mean and percentile rankings for total number of hours spent per year using the top 10 product groups are presented in Table 16-16. Westat (1987b) randomly selected a subset of 30 respondents from the original survey and reinterviewed them during the first two weeks of March, 1986 as a reliability check on the recall data obtained from the original phone survey. *Frequency and duration data for 3 of the original 14 cleaning tasks were obtained from the reinterviews. In a second effort to validate the phone survey, 50 respondents of the original phone survey participated in a four-week diary study (between February and March, 1986) of 8 of the 14 cleaning tasks originally studied. The diary approach assessed the validity of using a time telephone survey to determine usual cleaning behavior (Westat, 1987b ). The data (i.e., frequency and duration) obtained from the reinterviews and the diary approach were , lower than the data from the original telephone survey. The data from the reinterviews and the diary approach were more consistent with each other. Westat (1987b) attributed the significant differences in the data obtained from these surveys to seasonal changes rather than methodological. problems.

A limitation of this survey is evident from the reliability and validity check of the data conduded by Westat ( 1987b ). The data obtained from the telephone survey may reflect heavier seasonal cleaning because the survey was conducted during the holidays (November through January). Therefore, usage data obtained in this study may be biased and may represent upper bound estimates. Another limitation of this study is the small size of the sample population. An advantage of this survey is that the ROD procedure (Waksberg Method) used provides unbiased results of sample selection and reduces the number of unproductive calls. Another advantage of this study is that it provides empirical data on frequency and duration of consumer use, thereby eliminating best judgment or guesswork. Westat (1987c) -National Househ.old Survey of Interior Painters -Westat (1987c) conducted a study between November, 1985 and January, 1986 to obtain usage information to estimate the magnitude of exposure of consumers to different types of painting and painting related products used while painting the interior of the home. hundred and seventy-seven households were sampled to determine whether any household member had painted the interior of the home during the last 12 months prior to the survey date. Of the sampled households, 208 households (27 percent) had a Exposure Factors Handbook August 1997

...,.----------------------Volume III -Activity Factors Chapter 16 -Consumer Products household member who had painted during the last 12 months. Based on the households with primary painters, the response rate was 90 percent (Westat; 1987c). The person in each household who did most of the interior painting during the last 12 months was interviewed over the telephone. The ROD procedure (Waksberg Method) previously described in Westat (1987a) was used to generate sample blocks of telephone numbers in this survey. Questions were asked ori frequency and time spent for interior painting activities; the amount of paint used; and protective measures used (i.e., wearing gloves, hats, and masks or keeping a window open) (Westat, 1987c). Fifty-three percent ofthe primary painters in the households interviewed were male, 46 percent were female, and the sex of the remaining 1 percent was not ascertained. Three types of painting products were used in this study; latex paint, oil-based paint, and wood stains and varnishes. Of the respondents, 94. 7 percent used latex paint, 16.8 percent used oil-based paint, and 20.2 percent used wood stains and varnishes. Data generated from this survey are summarized in Tables 16-17, 16-18, and 16-19. Table 16-17 presents the mean, standard duration, and percentile rankings for the total exposure time for painting activity by paint type. Table 16-18 presents the mean and standard exposure time for the painting activity per occasion for each paint type. A "painting occasion" is defined as a time period from start to cleanup (Westat 1987c) .. Table 16-18 also presents the frequency and percentile rankings of painting occasions per . year. Table 16-19 presents the total amount of paint used by interior painters. In addition, 30 respondents from the original survey were reinterviewed in April 1986, as a reliability check on the recall data obtained from the original painting survey. There were no significant differences between the data obtained from the reinterviews and the original painting survey (Westat, 1987c). An advantage of this survey, based on the reliability check conducted by Westat (1987c), is the stability in the painting data obtained. Another advantage of this survey is that the response rate was high (90 percent), therefore, minimizing non-response bias. Also, the Waksberg Method employed provides an unbiased equal probability method of ROD. A limitation of the survey is the data are based on 12-month recall and may not accurately reflect long-term use patterns; Tsang and Klepeis {1996) -National Human Activity Pattern Survey (NHAPS)-The U.S. EPA collected information for the general population on the duration and frequency of selected activities and the time spent in selected microenvironments via *24-hour diaries. Over 9000 individuals from 48 contiguous states participated in NHAPS. The survey was conducted between October 1992 and September 1994. Individuals were interviewed to categorize their 24-hour routines (diaries) and/or answer follow-up exposure questions that were related to exposure events. Data were collected based on selected socioeconomic Exposure Factors Handbook August 1997 . I Volume Ill -Activity Factors Chapter 16 -Consumer Products (gender, age, race, education, etc.) and geographic (census region, state, etc.) factors and time/season (day of week, month) (Tsang and Klepeis, 1996). Data were collected for a maximum of 82 possible microenvironments and 91 different activities (Tsang and Klepeis, 1996). Respondents were also asked exposure-rE!lated follow. up questions, mostly on air and water exposure pathways, on specific pollutant

sources (paint, glue, etc.), or prolonged background activities (tobacco smoke, gas heaters, etc.) (Tsang and Klepeis, 1996). As part of the survey, data were also collected on duration and frequency of use of selected consumer products. These data are presented in Tables 16-20 through 16-34. Distribution data are presented for selected percentiles (where possible). Other data are presented in ranges of time spent in an activity (e.g., working with or near a product being used) or ranges for the number of times an activity involving a consumer product was performed. Tables 16-20 through 16-34 provide duration and/or frequency data for the following categories: selected cosmetics and personal care items; household cleaners and other household products; household equipment; pesticides; and tobacco products. . . The advantages of NHAPS is that the data were collected for a large number of individuals and are representative of the U.S. general population. In addition, frequency distributions of time spent and frequency of occurrence data for activities and locations are provided, when possible. Also, d<;lta on 9,386 different respondents are grouped by various socioeconomic, geographic, time/seasonal factors. A disadvantage of NHAPS is that means cannot be calculated for consumers who spent more than 60 or 120 minutes (depending on the activity) in an activity using a consumer product. Therefore, a good estimate of the high consumer activities cannot be captured. 16.3. RELEVANT CONSUMER PRODUCTS USE STUDY CTFA (1983) -Cosmetic, Toiletry, and Fragrance Association, Inc. -Summary of Results of Surveys of the Amount and Frequency of Use of Cosmetic Products by Women The Cosmetic, Toiletry, and Fragrance Association Inc. (CTFA, 1983), a major manufacturer and a market research bureau, conducted surveys to obtain information on frequency of use of various cosmetic products. Three surveys were conducted to collect data on the frequency of use of various cosmetic products and selected baby products. In the first of these three surveys CTFA (1983) conducted a one-week prospective survey of 47 female employees and relatives of employees between the ages of 13 and 61 years. In the second survey, a cosmetic manufacturer conducted a retrospective survey of 1, 129 ' of its customers. The third survey was conducted by a market research bureau which sampled 19,035 female consumers nationwide over a 9-1/2 month period. Of the 19,035 females interviewed, responses from only 9,684 females were tabulated (CTFA, 1983). Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 16 -Consumer Products The third survey was designed to reflect the sociodemographic (i.e., age, income, etc) characteristics of the entire U.S. population. The respondents in all three surveys were asked to record the number of times they used the various products in a given time period, i.e., a week, a day, a month, or a year (CTFA, 1983). To obtain the average frequency of use for each cosmetic product, responses were averaged for each product in each survey. Thus, the averages were calculated by adding the reported number of uses per given time period for each product, dividing by the total number of respondents in the survey, and then dividing again by the number of days in the given time period (CTFA, 1983). The average frequency of use of cosmetic products was determined for both "users" a*nd "non-users." The frequency of use of baby products was determined among "users" only. The upper 90th percentile frequency of use values were determined by eliminating the top ten percent most extreme frequencies of use. Therefore, the highest remaining frequency of use was recorded as the upper 90th percentile value (CTFA, 1983). Table 16-34 presents the amount of product used per application (grams) and the average and 90th ,percentile frequency of use per day for baby products and various cosmetic products for all the surveys. An advantage of the frequency data obtained from the third survey (market research bureau) is that the sample population was more likely to be representative of the U.S. population. Another advantage of the third dataset is that the survey was conducted over a longer period of time when compared with the other two frequency datasets. Also, the study provided empirical data which will be useful in generating more accurate estimates of consumer exposure to cosmetic products. In contrast to the large market research bureau survey, the CTFA employee survey is very small and both that survey and the cosmetic company survey are likely to be biased toward high end users. Therefore, data from these two surveys should be used with caution. 16.4. RECOMMENDATIONS Due to the large range and variation among consumer products and their exposure pathways, it is not feasible to specify recommended exposure values as has been done in other chapters of this handbook. The user is referred to the contents and references in the chapter to derive appropriate exposure factors. Table 16-35 summarizes the key and relevant studies in this chapter. In order to estimate consumer exposure to household products, several types of information are needed for the exposure equation. The information needed includes frequency and duration of use, amount of product used, percent weight of the chemical of concern found in the product, and for dermal exposure, the amount of the solution on the skin after exposure. The studies of Westat (1987a, b, and c), (Abt, 1992), and Tsang and Klepeis (1996) provide information on amount, duration, and frequency of use of household products. The frequency and duration of use Exposure Factors Handbook August 1997 -, . ' ' I I Volume III -Activity Factors Chapter 16 -Consumer Products and amount of product used for some household and other consumer products can be obtained from Tables 16-2 through 16-34. Exposure to chemicals present in common household products can be estimated by utilizing data presented in these tables and the appropriate exposure equation. It should be noted thatif these data are used to model indoor air concentrations, the values for time of use, time exposed after use, and frequency in the indoor air, should be the same values used in the dose equation for frequency and contact time for a given individual. Exposure Factors Handbook August 1997 Table 16-1. Consumer Products Found in the Typical U.S. Household' Consumer Product Cateaorv Consumer Product Cosmetics Hygiene Products Adhesive bandages Bath additives (liquid) Bath additives (powder) Cologne/perfume/aftershave Contact lens solutions Deodorant/antiperspirant (aerosol) Deodorant/antiperspirant (wax and liquid) Depilatories Facial makeup Fingernail cosmetics Hair coloring/tinting products Hair conditioning products Hairsprays (aerosol) Lip products Mouthwash/breath freshener Sanitary napkins and pads Shampoo Shaving creams (aerosols) Skin creams (non-drug) Skin oils (non-drug) Soap (toilet bar) Sunscreen/suntan products Talc/body powder (non-drug) Toothpaste Waterless skin cleaners Household Furnishings Carpeting Draperies/curtains Rugs (area) Shower curtains Vinyl upholstery, furniture Garment Conditioning Products Anti-static spray (aerosol) Leather treatment (liquid and wax) Shoe polish Spray starch (aerosol) Suede cleaner/polish (liquid and aerosol) Textile water-proofing (aerosol) Household Maintenance Products Adhesive (general) (liquid) Bleach (household) (liquid) Bleach (see laundry) Candles Cat box litter Charcoal briquets Charcoal lighter fluid Drain cleaner (liquid and powder) Dishwasher detergent (powder) Dishwashing liquid Fabric dye (DIY)b Fabric rinse/softener lliauid\
Table 16-1. Consumer Products Found in the Typical U.S. Household' (continued) Consumer Product Cateaorv Consumer Product Household Maintenance Products Fabric rinse/softener (powder) (continued) Fertilizer (garden) (liquid) Fertilizer (garden) (powder) Fire extinguishers (aerosol) Floor polish/wax (liquid) Food packaging and packaged food Furniture polish (liquid) Furniture polish (aerosol) General cleaner/disinfectant (liquid) General cleaner (powder) General cleaner/disinfectant (aerosol and pump) General spot/stain remover (liquid) General spot/stain remover (aerosol and pump) Herbicide (garden-patio) (Liquid and aerosol) Insecticide (home and garden) (powder) Insecticide (home and garden) (aerosol and purnp) I Insect repellent (liquid and aerosol) Laundry detergent/bleach (liquid) Laundry detergent (powder) Laundry pre-wash/soak (powder) Laundry pre-wash/soak (liquid) Laundry pre-wash/soak (aerosol and pump) Lubricant oil (liquid) Lubricant (aerosol) Matches Metal polish Oven cleaner (aerosol) Pesticide (home) (solid) Pesticide (pet dip) (liquid) ' Pesticide (pet) (powder) Pesticide (pet) (aerosol) Pesticide (pet) (collar) Petroleum fuels (home( (liquid and aerosol) Rug cleaner/shampoo (liquid and aerosol) Rug deodorizer/freshener (powder) Room deodorizer (solid) Room deodorizer (aerosol) Scouring pad Toilet bowl cleaner Toiler bowl deodorant (solid) Water-treating chemicals (swimming pools) Home Building/Improvement Products (DIY)b Adhesives, specialty (liquid) Ceiling tile Caulks/sealers/fillers Dry wall/wall board Flooring (vinyl) House Paint (interior) (liquid) House Paint and Stain (exterior) (liquid) Insulation (solid) Insulation (foaml Table 16-1. Consumer ProduCts Found in the Typical U.S. Household* (continued) Consumer Product Cateoorv Consumer Product Home Building/Improvement Products (DIY)b Paint/varnish removers (Continued) Paint thinner/brush cleaners Patching/ceiling plaster Roofing Refinishing products (polyurethane, varnishes, etc.) Spray paints (home) (aerosol) Wall paneling Wall paper Wall paper glue Automobile-related Products Antifreeze Car poli?hlwax Fuel/lubricant additives Gasoline/diesel fuel Interior upholstery/components, synthetic Motor oil Radiator flush/cleaner Automotive touch-up paint (aerosol) Windshield washer solvents Personal Materials Clothes/shoes Diapers/vinyl pants Jewelry Printed material (colorprint, newsprint, photographs) Sheets/towels Toys (intended to be placed in mouths) a A subjective listing based on consumer use profiles. b DIY =Do It Yourself. Source: U.S. EPA, 1987. Table 16-2. Frequencv of Use for Household Solvent Products (users-onlvl Percentile Rankings for Frequency of Use/Year Products Mean Std. dev. Min. 1 5 10 25 50 75 90 95 99 Max. Spray Shoe Polish 10.28 20.10 1.00 1.00 1.00 1.00 2.00 4.00 8.00 24.30 52.00 111.26 156.00 Water Repellents/Protectors 3.50 11.70 1.00 1.00 1.00 1.00 1.00 2.00 3.00 6.00 10.00 35.70 300.00 Spot Removers 15.59 43.34 1.00 1.00 1.00 1.00 2.00 3.00 10.00 40.00 52.00 300.00 365.00 Solvent-Type Cleaning Fluids or Degreasers 16.46 44.12 1.00 1.00 1.00 1.00 2.00 4.00 12.00 46.00 52.00 300.00 365.00 Wood Floor and Paneling Cleaners 8.48 20.89 1.00 1.00 1.00 1.00 NA 2.00 6.00 24.00 50.00 56.00 350.00 TypeWriter Correction Fluid 40.00 74.78 1.00 1.00 1.00 2.00 4.00 12.00 40.00 100.00 200.00 365.00 520.00 Adhesives 8.89 26.20 1.00 1.00 1.00 1.00 2.00 3.00 6.00 15.00 28.00 100.00 500.00 Adhesive Removers 4.22 12.30 1.00 1.00 1.00 1.00 1.00 1.00 3.00 6.00 16.80 100.00 100.00 Silicone Lubricants 10:32 25.44 1.00 1.00 1.00 1.00 2.00 3.00 10.00 20.00 46.35 15.0.00 300.00 Other Lubricants (excluding Automotive) 10.66 25.46 1.00 1.00 1.00 1.00 2.00 4.00 10.00 20.00 50.00 100.00 420.00 Specialized Electronic Cleaners (for 1Vs, Etc.) 13.41 38.16 1.00 1.00 1.00 1.00 2.00 3.00 10.00 24.00 52.00 224.50 400.00 Latex Paint 3.93 20.81 1.00 1.00 1.00 1.00 1.00 2.00 4.00 6.00 10.00 30.00 800.00 Oil Paint 5.66 23.10 1.00 1.00 1.00 1.00 1.00 1.00 3.00 6.00 12.00 139.20 300.00 Wood Stains, Varnishes, and Finishes 4.21 12.19 1.00 1.00 1.00 1.00 1.00 2.00 4.00 7.00 12.00 50.80 250.00 Paint Removers/Strippers 3.68 9.10 1.00 1.00 1.00 1.00 4.00 2.00 3.00 6.00 11.80 44.56 100.00 Paint Thinners 6.78 22.10 0.03 0.03 0.10 0.23 1.00 2.00 4.00 12.00 23.00 100.00 352.00 Aerosol Spray Paint 4.22 15.59 1.00 1.00 1.00 1.00 1.00 2.00 4.00 6.10 12.00 31.05 365.00 Primers and Special Primers 3.43 8.76 1.00 1.00 1.00 1.00 1.00 1.00 3.00 6.00 10.00 50.06 104.00 Aerosol Rust Removers 6.17 9.82 1.00 1.00 1.00 1.00 1.00 2.00 6.00 15.00 24.45 50.90 80.00 Outdoor Water Repellents (for Wood or Cement) 2.07 3.71 1.00 1.00 1.00 1.00 1.00 2.00 2.00 3.00 5.90 12.00 52.00 Glass Frostings, Window Tints, and Artificial 2.78 21.96 1.00 1.00 1.00 1.00 1.00 1.00 1.00 2.00 2.00 27.20 365.00 Snow Engine Degreasers 4.18 13.72 1.00 1.°oo 1.00 1.00 1.00 2.00 3.25 6.70 12.00 41.70 300.00 Carburetor Cleaners 3.77 . 7.10 1.00 1.00 1.00 1.00 1.00 2.00 3.00 6.00 12.00 47.28 100.00 Aerosol Spray Paints for Cars 4.50 9.71 1.00 1.00 1.00 1.00 1.00 2.00 4.00 10.00 15.00 60.00 100.00 Auto Spray Primers 6.42 33.89 1.00 1.00 1.00 1.00 1.00 2.00 3.75 10.00 15.00 139.00 500.00 Spray Lubricant for Cars 10.31 30.71 1.00 1.00 1.00 1.00 2.00 3.00 6.00 20.00 40.00 105.60 365.00 Transmission Cleaners 2.28 3.55 1.00 NA 1.00 1.00 1.00 1.00 2.00 3.00 9.00 NA 26.00 Battery Terminal Protectors 3.95 24.33 1.00 1.00 1.00 1.00 1.00 2.00 2.00 4.00 6.55 41.30 365.00 Brake Quieters Cleaners 3.00 6.06 1.00 NA 1.00 1.00 1.00 2.00 2.00 6.00 10.40 NA 52.00 Gasket Remover 2.50 4.39 1.00 NA 1.00 1.00 1.00 1.00 2.00 5.00 6.50 NA 30.00 Tire/Hubcap Cleaners 11.18 18.67 1.00 1.00 1.00 1.00 2.00 4.00 12.00 30.00 50.00 77.00. 200.00 lanition and Wire Drvers 3.01 5.71 1.00 1.00 *1.00 1.00 1.00 2.00 3.00 5.00 9.70 44.52 60.00 NA= Not Available Source: Westat 1987a Table 16-3. Exoosure Time of Use for Household Solvent Products (users-onlvl Percentile Rankings for Duration of Use (minutes) Mean Std. Products (mins) dev. Min. 1 5 10 25 50 75 90 95 99 Max. Spray Shoe Polish 7.49 9.60 0.02 0.03 0.25 0.50 2.00 5.00 10.00 18.00 30.00 60.00 60.00 Water Repellents/Protectors 14.46 24.10 0.02 0.08 0.50 1.40 3.00 10.00 1.5.00 30.00 60.00 120.00 480.00 Spot Removers 10.68 22.36 0.02 0.03 0.08 0.25 2.00 5.00 10.00 30.00 30.00 120.00 360.00 Solvent-Type Cleaning Fluids or 29.48 97.49 0.02 0.03 1.00 2.00 5.00 15.00 30.00 60.00 120.00 300.00 1800.00 Degreasers Wood Floor and Paneling Cleaners 74.04 128.43 0.02 1.00 5.00 10.00 20.00 30.00 90.00 147.00 240.00 480.00 2700.00 TypeWriter Correction Fluid 7.62 29.66 0.02 0.02 0.03 0.03 0.17 1.00 2.00 10.00 32.00 120.00 480.00 Adhesives 15.58 81.80 0.02 0.03 0.08 0.33 1.00 4.25 10.00 30.00 60.00 180.00 2880.00 Adhesive Removers 121.20 171.63 0.03 0.03 1.45 3.00 15.00 60.00 120.00 246.00 480.00 960.00 960.00 Silicone Lubricants 10.42 29.47 0.02 0.03 0.08 0.17 0.50 2.00 10.00 20.00 45.00 180.00 360.00 Other Lubricants (excluding 8.12 32.20 0.02 0.03 0.05 0.08 0.50 2.00 5.00 15.00 30.00 90.00 900.00 Automotive) Specialized Electronic Cleaners 9.47 45.35 0.02 0.03 0.08 0.17 0.50 2.00 5.00 20.00 30.00 93.60 900.00 (for TVs. Etc.) Latex Paint 295.08 476.11 0.02 1.00 22.50 30.00 90.00 180.00 360.00 480.00 810.00 2880.00 5760.00 Oil Paint 194.12 345.68 0.02 0.51 15.00 30.00 60.00 12.00 240.00 480.00 579.00 1702.80 5760.00 Wood Stains. Varnishes. and Finishes 117.17 193.05 0.02 0.74 5.00 10.00 30.00 60.00 120.00 140.00 360.00 720.00 280.00 Paint Removers/Strippers 125.27 286.59 0.02 0.38 5.00 5.00 20.00 60.00 120.00 240.00 420.00 1200.00 4320.00 Paint Thinners 39.43 114.85 0.02 0.08 1.00 2.00 5.00 10.00 30.00 60.00 180.00 480.00 2400.00 Aerosol Spray Paint 39.54 87.79 0.02 0.17 2.00 5.00 10.00 20.00 45.00 60.00 120.00 300.00 1800.00 Primers and Special Primers 91.29 175.05 0.05 0.24 3.00 5.00 15.00 30.00 140.00 240.00 360.00 981.60 1920.00 Aerosol Rust Removers 18.57 48.54 0.02 0.05 0.17 0.25 2.00 5.00 20.00 60.00 60.00 130.20 720.00 Outdoor Water Repellents 104.94 115.36 0.02 0.05 5.00 15.00 30.00 60.00 120.00 240.00 300.00 480.00 960.00 (for Wood or Cement) 29.45 48.16 0.03 0.14 2.00 3.00 5.00 15.00 30.00 60.00 96.00 268.80 360.00 Glass Frostings, Window Tints, and 29.29 48.14 0.02 0.95 2.00 5.00 10.00 15.00 30.00 60.00 120.00 180.00 900.00 Artificial Snow Engine Degreasers, 13.57 23.00 0.02 0.08 0.33 1.00 3.00 7.00 15.00 30.00 45.00 120.00 300.00 Carburetor Cleaners Aerosol Spray Paints for Cars 42.77 71.39 0.03 0.19 1.00 3.00 10.00 20.00 60.00 120.00 145.00 360.00 900.00 Auto Spray Primers 51.45 86.11 0.05 0.22 2.00 5.00 10.00 27.50 60.00 120.00 180.00 529.20 600.00 Spray Lubricant for Cars 9.90 35.62 0.02 0.03 0.08 0.17 1.00 5.00 10.00 15.00 30.00 120.00 720.00 Transmission Cleaners 27.90 61.44 0.17 NA 0.35 1.80 5.00 15.00 30.00 60.00 60.00 NA 450.00 Battery Terminal Protectors 9.61 18.15 0.03 0.04 0.08 0.23 1.00 5.00 10.00 20.00 30.00 120.00 180.00 Brake Quieters/Cleaners 23.38 36.32 0.07 NA 0.50 1.00 5.00 15.00 30.00 49.50 120.00 NA 240.00 Gasket Remover 23.57 27.18 0.33 NA 0.50 2.00 6.25 15.00 30.00 60.00 60.00 NA 180.00 Tire/Hubcap Cleaners 22.66 23.94 0.08 0.71 3.00 5.00 10.00 15.00 30.00 60.00 60.00 120.00 240.00 lanition and Wire Drvers 7.24 8.48 0.02 0.02 0.08 0.47 1.50 5.00 10.00 15.00. 25.50 48.60 60.00 NA= Not Available Source: Westat 1987a I Table 16-4. Amount of Products Used for Household Solvent Products (users-onlvl Percentile Rankings for Amount of Products Used (ounces/yr) Mean Std. Products (ounces/yr) dev Min. 1 5 10 25 50 75 90 95 99 Max. Spray Shoe Polish 9.90 17.90 0.04 0.20 0.63 1.00 2.00 4.50 10.00 24.00 36.00 99.36 180.00 Water Repellents/Protectors 11.38 22.00 0.04 0.47 0.98 1.43 2.75 6.00 12.00 24.00 33.00 121.84 450.00 Spot Removers 26.32 90.10 0.01 0.24 0.60 1.00 2.00 5.50 16.00 48.00 119.20 384.00 1600.00 Solvent-Type Cleaning Fluids or 58.30 226.97 0.04 0.50 2.00 3.00 6.50 16.00 32.00 96.00 192.00 845.00 5120.00 Degreasers Wood Floor and Paneling Cleaners 28.41 57.23 0.03 0.80 2.45 3.50 7.00 14.00 30.00 64.00 96.00 204.40 1144.00 TypeWriter Correction Fluid 4.14 13.72 0.01 0.02 0.06 0.12 0.30 0.94 2.40 8.00 18.00 67.44 181.80 Adhesives
7.49 55.90 0.01 0.02 0.05 0.12 0.35 1.00 3.00 8.00 20.00 128.00 1280.00 Adhesive Removers 34.46 96.60 0.25 0.29 1.22 2.80 6.00 10.88 32.00 64.00 138.70 665.60 1024.00 Silicone Lubricants* 12.50 27.85 0.02 0.20 0.69 1.00 2.25 4.50 12.00 24.00 41.20 192.00 312.00 Other Lubricants (excluding 9.93 44.18 0.01 0.18 0.30 0.52 1.00 2.25 8.00 18.00 32.00 128.00 1280.00 Automotive) Specialized Electronic Cleaners 9.48 55.26 0.01 0.05 0.13 0.25 0.52 2.00 6.00 12.65 24.00 109.84 1024.00 (for TVs, Etc.) Latex Paint 371.27 543.86 0.03 4.00 12.92 32.00 64.00 256.00 384.00 857.60 1280.00 2560.00 6400.00 Oil Paint 168.92 367.82 0.02 0.33 4.00 8.00 25.20 64.00 148.48 384.00 640.00 1532.16 5120.00 Wood Stains, Varnishes, and 65.06 174.01 0.12 1.09. 4.00 4.00 8.00 16.00 64.00 128.00 256.00 768.00 3840.00 Finishes Paint Removers/Strippers 63.73 144.33 0.64 1.50 4.00 8.00 16.00 32.00 64.00 128.00 256.00 512.00 2560.00 Paint Thinners 69.45 190.55 0.03 0.45 3.10 4.00 8.00 20.48 64.00 128.00 256.00 640.00 3200.00 Aerosol Spray Paint 30.75 52.84 0.02 0.75 2.01 3.25 7.00 13.00 32.00 65.00 104.00 240.00 1053.00 Primers and Special Primers 68.39 171.21 0.01 0.09 1.30 3.23 8.00 16.00 60.00 128.00 256.00 867.75 1920.00 Aerosol Rust Removers 18.21 81.37 0.09 0.25 1.00 1.43 2.75 8.00 13.00 32.00 42.60 199.80 1280.00 Outdoor Water Repellents 148.71 280.65 0.01 0.37 3.63 8.00 16.00 64.00 128.00 448.00 640.00 979.20 3200.00 (for Wood or Cement) Glass Frostings, Window Tints, and 13.82 14.91 1.00 1.40 2.38 3.25 6.00 12.00 14.00 28.00 33.00 98.40 120.00 Artificial Snow Engine Degreasers 46.95 135.17 0.04 1.56 4.00 6.00 12.00 16.00 36.00 80.00 160.00 480.00 2560.00 Carburetor Cleaners 22.00 50.60 0.10 0.50 1.50 3.00 5.22 12.00 16.00 39.00 75.00 212.00 672.00 Aerosol Spray Paints for Cars 44.9.5 89.78 0.04 0.14 1.50 3.00 6.12 16.00 48.00 100.80 156.00 557.76 900.00 Auto Spray Primers 70.37 274.56 0.12 0.77 3.00. 4.00 9.00 16.00 48.00 128.00 222.00 1167.36 3840.00 Spray Lubricant for Cars 18.63 54.74 0.08 0.40 0.96 1.00 2.75 6.00 15.50 36.00 64.00 240.00 864.00 Transmission Cleaners 35.71 62.93 2.00 NA 3.75 4.00 . 8.00 15.00 32.00 77.00 140.00 NA 360.00 Battery Terminal Protectors 16.49 87.84 0.12 0.13 0.58 1.00 2.00 4.00 8.00 15.00 24.60 627.00 1050.00 Brake Quieters/Cleaners 11.72 13.25 0.50 NA 1.00 2.00 3.02 8.00 14.25 32.00 38.60 NA 78.00 Gasket Remover 13.25 22.35 0.50 NA 1.00 1.00 3.75 7.75 16.00 24.00 58.40 NA 160.00. -Tire/Hubcap Cleaners 31.58 80.39 0.12 0.50 1.82 3.00 6.00 12.00 28.00 64.00 96.00 443.52 960.00 lanition and Wire Drvers 9.02 14.59 0.13 0.32 1.09. 1.50 3.00 6.00 10.75 16.00 20.55 "113.04 120.00 NA= Not Available Source: Westat 1987a Table 16-5. Time Exposed After Duration of Use for Household Solvent Products (users-only) Percentile Rankings for Time Exposed After Duration of Use (minutes) Products Mean Std. (mins) dev. Min. 1* 5 10 25 50 75 90 95 99 Max. Spray Shoe Polish 31.40 80.50 0.00 0.00 0.00 0.00 0.00 5.00 20.00 120.00 120.00 480.00 720.00 Water Repellents/Protectors 37.95 111.40 0.00 0.00 0.00 0.00 0.00 3.00 20.00 120.00 240.00 480.00 1800.00 Spot Removers 43.65 106.97 0.00 0.00 0.00 0.00 1.00 5,.00 30.00 120.00 240.00 480.00 1440.00 Solvent-Type Cleaning Fluids or Degreasers 33.29 90.39 0.00 0.00 0.00 0.00 0.00 3.00 28.75 60.00 180.00 "480.00 1440.00 Wood Floor and Paneling Cleaners 96.75 192.88 0.00 0.00 0.00 0.00 5.00 30.00 120.00 240.00 480.00 1062.00 1440.00 TypeWriter Correction Fluid 124.70 153.46 0.00 0.00 1.00 5.00 30.00 60.00 180.00 360.00 480.00 600.00 1800.00 Adhesives 68.88 163.72 0.00 0.00 0.00 0.00 1.00 10.00 60.00 180.00 360.00 720.00 2100.00 Adhesive Removers 94.12 157.69 0.00 0.00 0.00 0.00 1.75 20.00 120.00 360.00 480.00 720.00 720.00 Silicone Lubricants 30.77 107.39 0.00 0.00 0.00 0.00 0.00 0.00 10.00 60.00 180.00 480.00 1440.00 Other Lubricants (excluding Automotive) 47.45 127.11 0.00 0.00 0.00 0.00 0.00 2.00 30.00 120.00 240.00 485.40 1440.00 Specialized Electronic Cleaners 117.24 154.38 0.00 0.00 0.00 1.00 10.00 60.00 180.00 300.00 480.00 720.00 1440.00 (for TVs, Etc.) Latex Paint 91.38 254.61 0.00 0.00 0.00 0.00 0.00 5.00 60.00 240.00 480.00 1440.00 2880.00 Oil Paint 44.56 155.19 0.00 0.00 0.00 0.00 0.00 0.00 30.00 120.00 240.00 480.00 2880.00 Wood Stains, Varnishes, and Finishes 48.33 156.44 0.00 0.00 0.00 0.00 0.00 1.00 30.00 120.00 240.00 694.00 2880.00 Paint Removers/Strippers 31.38 103.07 0.00 0.00 0.00 0.00 0.00 0.00 20.00 60.00 180.00 541.20 1440.00 Paint Thinners 32.86 105.62' 0.00 0.00 0.00 0.00 0.00 0.00 15.00 60.00 180.00 480.00 1440.00 Aerosol Spray Paint 12.70 62.80 0.00 0.00 0.00 0.00 0.00 0.00 1.00 30.00 60.00 260.50 1440.00 Primers and Special Primers 22.28 65.57 0.00 0.00 0.00 0.00 0.00 0.00 10.00 60.00 120.00 319.20 720.00 Aerosol Rust Removers 15.06 47.58 0.00 0.00 0.00 0.00 0.00 0.00 5.00 60.00 60.00 190.20 600.00 Outdoor Water Repellents 8.33 43.25 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.00 58.50 309.60 420.00 (for Wood or Cement) Glass FrostinQs, Window Tints, and Artificial 137.87 243.21 0.00 0.00 0.00 0.00 3.00 60.00 180.00 360.00 480.00 1440.00 1800.00 Snow Engine Degreasers 4.52 24.39 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 15.50 120.00 360.00 Carliuretor Cleaners 7.51 68.50 0.00 0.00 0.00 0.00 0.00 0.00 0."00 0.10 30.00 120.60 1800.00 Aerosol Spray Paints for Cars 10.71 45.53 0.00 0.00 0.00 0.00 0.00 0.00 0.00 17.50 60.00 282.00 480.00 Auto Spray Primers 11.37 45.08 0.00 0.00 0.00 0.00 0.00 0.00 0.00 20.00 77.25 360.00 360.00 Spray Lubricant for Cars 4.54 30.67 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.00 15.00 70.20 420.00 Transmission Cleaners 5.29 29.50 0.00 NA 0.00 0.00 0.00 0.00 0.00 5.00 22.50 NA 240.00 Battery Terminal Protectors 3.25 17.27 0.00 NA 0.00 0.00 0.00 0.00 0.00 2.90 15.00 120.00 180.00 Brake Quieters/Cleaners 10.27 30.02 0.00 NA 0.00 0.00 0.00 0.00 0.00 30.00 120.00 NA 120.00 Gasket Remover 27.56 58.54 0.00 NA 0.00 0.00 0.00 0.00 12.50 120.00 180.00 NA 240.00 Tire/Hubcap Cleaners 1.51 20.43 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 30.00 480.00 lanition and Wire Drvers 6.39 31.63 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 30.00 216.60 240.00 NA= Not Available Source: Wes tat 1987a Table 16-6. Frequency of Use and Amount of Product Used for Adhesive Removers No. of Times Minutes in Amount Used in Used Within the Minutes Minutes in Room Room After Past Year (Fluid Amount per Last 12 Months Using After Using' Usingb oz.) Use (Fluid oz.) N=58 N=52 N=51 N=5 N=51 N=51 Mean 1.66 172.87 13.79 143.37 96.95 81.84 Standard deviation 1.67 304.50 67.40 169.31 213.20 210.44 Minimum* Value 1.00 5.00 0.00 5.00 13.00 5.20 1st Percentile 1.00 5.00 0.00 5.00 13.00 5.20 5th Percentile 1.00 10.00 0.00 5.00 13.00 6.50 10th Percentile 1.00 15.00 0.00 5.00 16.00 10.67 25th Percentile 1.00 29.50 0.00 20.00 16.00 16.00 Median Value 1.00 120.00 0.00 120.00 32.00 26.00 ?5th Percentile 2.00 240.00 0.00 420.00 96.00 (;)4.00 90th Percentile 3.00 480.00 0.00 420.00 128.00 128.00 95th Percentile 5.00 1440.00 120.00 420.00 384.00 192.00 99th Percentile 12.00 1440.00 420.00 420.00 1280.00 1280.00 Maximum Value 12.00 1440.00 420.00 1440.00 1280.00 1280.00 ' Includes those who did not spend anytime in the room after use. b Includes only those who spent time in the room. Source: Abt, 1992.
Table 16-7. Adhesive Remover Usaae bv Gender Gender Male Female N=25 N=33 Mean number of months since last time adhesive remover was used -includes fill 35.33 43.89 respondents. (Unweighted N=240) Mean number of uses of product in the past year. 1.94 1.30 Mean number of minutes spent with the product during last use. 127.95 233.43 Mean number of minutes spent in the room after last use of product. (Includes all 19.76 0 recent users) Mean riumber of minutes spent in the room after last use of product. (Includes only 143.37 0 those who did not leave immediately) Mean ounces of prqduct used in the past year. 70.48 139.71 Mean ounces of oroduct used oer use in the oast vear. 48.70 130.36 Source: Abt, 1992. Table 16-8. Frequency of Use and Amount of Product Used for Sorav Paint No. ofTimes Minutes in Amount Used in Used Within the Minutes Minutes in Room Room After Past Year Amount per Last 12 Months Using After Using' Usingb (Fluid oz.) Use (Fluid oz.) N=775 N=786 N=791 N=35 N=778 N=778 Mean 8.23 40.87 3.55 65.06 83.92 19.04 Sta'ndard deviation 31.98 71.71 22.03 70.02 175.32 25.34 Minimum Value 1.00 1.00 0.00 1.00 13.00 0.36 1st Percentile 1.00 1.00 0.00 1.00 13.00 0.36 5th Percentile 1.00 3.00 0.00 1.00 13.00 3.47 1 oth Percentile 1.00 5.00 0.00 10.00 13.00 6.50 25th Percentile 1.00 10.00 0.00 15.00 13.00 9.75 Median Value 2.00 20.00 0.00 30.00 26.00 13.00 75th Percentile 4.00 45.00 0.00 60.00 65.00 21.67 9oth Percentile 11.00 90.00 0.00 120.00 156.00 36.11 95th Percentile 20.00 120.00 0.00 120.00 260.00 52.00 99th Percentile 104.00 360.00 120.00 300.00 1170.00 104.00 Maximum Value 365.00 960.00 300.00 300.00 1664.00 312.00 ' Includes those who did not spend anytime in the room after use. b Includes only those who spent time in the room. Source: Abt, 1992. Table 16-9. Sprav Paint Usaqe by Gender Gender Male Female N=405 N=386 Mean number of monttis since last time spray paint was used -includes .fill 17.39 26.46 respondents. (Unweighted N=1724) Mean number of uses of product in the past year. 10.45 4.63 Mean number of minutes spent with the product during last use. 40.87 40.88 Mean number of minutes spent in the room after last use of product. (Includes all 5.49 0.40 recent users) Mean number of minutes spent in the room after last use of product. (Includes only 67.76 34.69 those who did ncit leave immediately) Mean ounces of product used in the past year. 103.07 59.99 Mean ounces of product used oer use in the oast vear. 18.50 19.92 Source: Abt, 1992. Table 16-10. Frequency of Use and Amount of Product Used for Paint Removers/Strippers No. of Times Amount Used in Used Within the Minutes Minutes in Minutes in Past Year Amount per Last 12 Months Using Room After Room After (Fluid oz.) Use (Fluid oz.) N=316 N=390 Using* Usingb N=307 N=307 N=390 N=39 Mean 3.54 144.59 12.96 93.88 142.05 64.84 Standard deviation 7.32 175.54 85.07 211.71 321.73 157.50 Minimum Value 1.00 2.00 0.00 1.00 15.00 0.35 1st Percentile 1.00 5.00 0.00 1.00 15.00 2.67 5th Percentile 1.00 15.00 0.00 1.00 16.00 8.00 1 oth Percentile 1.00 20.00 0.00 3.00 16.00 10.67 25th Percentile 1.00 45.00 0.00 10.00 32.00 16.00 Median Value 2.00 120.00 0.00 60.00 64.00 32.00 75th Percentile 3.00 180.00 0.00 120.00 128.00 64.00 9oth Percentile 6.00 360.00 10.00 180.00 256.00 128.00 95th Percentile 12.00 480.00 60.00 420.00 384.00 192.00 99th Percentile 50.00 720.00 180.00 1440.00 1920.00 320.00 Maximum Value 70.00 1440.00 1440.00 1440.00 3200.00 2560.00
~~Includes those who did not spend anytime in the room after use. b Includes only those who spent Ume in the room. Source: Abt, 1992.~~
Table 16-11. Paint Stripper Usage by Gender Gender Male Female N=156 N=162 Mean number of months since last time paint stripper was used -includes fill 32.07 47.63 respondents. (Unweighted N=1724) Mean number of uses of product in the past year. 3.88 3.01 Mean number of minutes spent with the product during last use. 136.70 156.85 Mean number of minutes spent in the room after last use of product. (Includes all 15.07 9.80 recent users) Mean number of minutes spent in the room after last use of product. (Includes only 101.42 80.15 those who did not leave immediately) Mean o,unces of product used in the past year. 160.27 114.05 Mean ounces of product used per use in the past vear. 74.32 50.29 Source: Abt, 1992. - Table 16-12. Total Exposure Time of Performing Task and Product Type Used by Task for Household Cleaning Products Mean Median Product Type Percent of Tasks lhrs/vearl lhrs/vear\ Used Preference Clean Bathroom Sinks and Tubs 44 26 Liquid 29% Powder 44% Aerosol 16% ' Spray pump 10% Other 1% Clean Kitchen Sinks 41 18 Liquid 31% Powder 61% Aerosol 2% Spray pump 4% Other 2% Clean Inside of Cabinets 12 5 Liquid 68% (such as kitchen) Powder 12% Aerosol 2% Spray pump 16% Other 2% Clean Outside of Cabinets 21 6 Liquid 61% Powder 8% Aerosol 16% Spray pump 13% Other 2% Wipe Off Kitchen Counters 92 55 Liquid 67% Powder 13% Aerosol 2% Spray pump 15% Other 3% Thoroughly Clean Counters 24 13 Liquid 56% Powder 21% Aerosol 5% Spray pump 17% Other 1% Clean Bathroom Floors 20 9 Liquid 70% Powder 21% Aerosol 2% Spray pump 4% Other 3% Clean Kitchen Floors 31 14 Liquid 70% Powder 27% Aerosol 2% Spray pump 1% Other --Clean Bathroom or Other Tilted or Ceramic Walls 16 9 Liquiq 37% Powder 18% Aerosol 17% Spray pump 25% Other 3% Table 16-12. Total Exposure Time of Performing Task and Product Type Used by Task for Household Cleaninq Products (continued) Mean Median . Product Type Percent of Tasks lhrs/vear\ lhrs/vear\ Used Preference Clean Outside of Windows 13 6 Liquid 27% Powder 2% Aerosol 6% Spray pump 65% Other --Clean Inside of Windows 18 6 Liquid 24% Powder 1% Aerosol 8% Spray pump 66% Other 2% Clean Glass Surfaces Such as Mirrors & Tables 34 13 Liquid 13% Powder 1% Aerosol 8% Spray pump 76% Other 2% Clean Outside of Refrigerator and Other Appliances 27 13 Liquid 48% Powder 3% Aerosol 7% Spray pump 38% Other 4%. Clean Spots or Dirt on Walls or Doors 19 8 Liquid 46% Finishes Powder 15% Aerosol 4% Spray pump 30% Other 4% Source: Westat 1987b. Table 16-13. Percentile Rankings for Total Exposure Time in Performing Household Tasks Percentile Rankings for Total Exposure Exposure Time Performing Task (hrs/yr) Tasks 100th 95th 90th 75th 50th 25th 10th 0th Clean Bathroom Sinks and Tubs 365 121.67 91.25 52 26 13 5.2 0.4 Clean Kitchen Sinks 547.5 121.67 97.6 60.83 18.25 8.67 3.47 0.33 Clean Inside of Kitchen Cabinets 208 48 32.48 12 4.75 '2 1 0.17 Clean Outside of Cabinets 780 78.66 36 17.33 6 2 0.967 0.07 Wipe Off Kitchen Counters 912.5 456.25 231..16 91.25 54.75 24.33 12.17 1.2 Thoroughly Clean Counters 547.5 94.43 52. 26 13 6 1.75 0.17 Clean Bathroom Floors
365 71.49 36.83 26 8.67 4.33 2 0.1 Clean Kitchen Floors 730 96.98 52 26 14 8.67 4.33 0.5 Clean Bathroom or Other Tilted or Ceramic 208 52 36 26 8.67 3 1 0.17 Walls Clean Outside of Windows 468 32.6 24 11.5 6 2 1.5 0.07 Clean Inside of Windows 273 72 36 19.5 6 3 1.15 0.07 Clean Glass Surfaces Such as Mirrors & Tables 1460 104 60.83 26 13 6 1.73 0.17 Clean Outside Refrigerator and Other 365 95.29 91.25 30.42 13 4.33 1.81 0.1 Appliances Clean Spots or Dirt on Walls or Doors 312 78 52 24 8 2 0.568 0.07 Source: Westat, 1987b. *.
Table 16-14. Mean Percentile Rankinas for Freauencv of Performina Household Tasks Percentile Rankings Tasks Mean Oth 1oth 25th 5oth 75th 90th 95th 10oth Clean bathroom sinks and tubs 3 x/week 0.2 x/week 1 x/week 1 x/week 2 x/week 3.5 x/week 7 x/week 7 x/week 42 x/week Clean kitchen sinks 7 x/week 0 x/week 1 x/week 2 x/week 7 x/week 7 x/week 15 x/week 21 x/week 28 x/week *clean inside of cabinets such as those in the 9 x/year 1 x/year 1 x/year 1 x/year 2 x/year 12 x/year 12 x/year 52 x/year 156 x/year kitchen Clean outside of cabinets 3 x/month 0.1 x/month 0.1 x/month 0.3 x/month 1 x/month 4 x/month 4 x/month 22 x/month 30 x/month Wipe off counters such as those in the 2 x/day Ox/day 0.4 x/day 1 x/day 1 x/day 3 x/day 4 x/day 6 x/day 16 x/day kitchen Thoroughly clean counters 8 x/month 0.1 x/month 0.8 x/month 1 x/month 4 x/month 4 x/month 30 x/month 30 x/month 183 x/month Clean bathroom floors 6 x/month 0.2 x/month 1 x/month 2 x/month 4 x/month 4 x/month 13 x/month 30 x/month 30 x/month Clean kitchen floors 6 x/month 0.1 x/month 1 x/month 2 x/month 4 x/month 4 x/month 13 x/month 30 x/month 30 x/month Clean bathroom or other tiled or ceramic 4 x/month 0.1 x/month 0.2 x/month 1 x/month 2 x/month 4 x/month 9 x/month 13 x/month 30 x/month walls Clean outside of windows 5 x/year 1 x/year 1 x/year 1 x/year 2 x/year 4 x/year 12 x/year 12 x/year 156 x/year Clean inside of windows 10 x/year 1 x/year 1 x/year 2 x/year 4 x/year 12 x/year 24 x/year 52 x/year 156 x/year Clean other glass surfaces such as mirrors 7 x/month 0.1 x/month 1 x/month 2 x/month 4 x/month 4 x/month 17 x/month 30 x/month 61 x/month and tables Clean outside of refrigerator and other 10 x/month 0.2 x/month 1 x/month 2 x/month 4 x/month 13 x/month 30 x/month 30 x/month 61 x/month appliances Clean spots or dirt on walls or doors 6 x/month 0.1 x/month 0.2 x/month 0.3 x/month 1 x/month 4 x/month 13 x/month 30 x/month 152 x/month Source: Westat, 1987b. 16-15. Mean and Percentile Rankings for Exposure Time Per Event of Performing Household Tasks Percentile Rankings (minutes/event) Mean Tasks (minutes/event) Oth 1oth 25th 5oth 75th 90th 95th 100th Clean bathroom sinks and tubs 20 1 5 10 15 30 45 60 90 Clean kitchen sinks 10 1 2 3 5 10 15 20 480 Clean inside of cabinets such as those in the 137 5 24 44 120 180 240 360 2,880 kitchen Clean outside of cabinets 52 1 5 15 30 60 120 180 330 Wipe off counters such as those in the kitchen 9 1 2 3 5 10 15 30 120 Thoroughly clean counters 25 1 5 10 15 30 60 90 180 Clean bathroom floors 16 1 5 10 15 20 30 38 60 Clean kitchen floors 30 2 10 15 20 30 60 60 180 Clean bathroom or other tiled or ceramic walls 34 1 5 15 30 45 60 120 240 Clean outside of windows 180 4 30 60 120 240 420 480 1,200 Clean inside of windows 127 4 20 45 90 158 300 381 1,200 Clean other glass surfaces such as mirrors and 24 1 5 10 15 30 60 60 180 tables Clean outside of refrigerator and other 19 1 4 5 10 20 30 45 240 appliances Clean spots or dirt on walls or doors 50 1 5 10 20 60 120 216 960 Source: Westat, 1 987b. Table 16-16. Total Exposure Time for Ten Product Groups Most Frequently Used for Household Cleaning" Percentile Rankings of Total Exposure Time Mean (hrs/vrl Products (hrs/yr) Oth 1oth 25th SO th 75th 90th 95th 10oth Dish Detergents 107 0.2 6 24 56 :134 274 486 941 Glass Cleaners 67 0.4 3 12 29 62 139 260 1,508 Floor Cleaners 52 0.7 4 7 22 52 102 414 449 Furniture Polish 32 0.1 0.3 1 12 36 101 215 243 Bathroom Tile Cleaners 47 0.5 2 8 17 48 115 287 369 Liquid Cleansers 68 0.2 2 9 22 52 122 215 2,381 Scouring Powders 78 0.3 9 17 35 92 165 281 747 Laundry Detergents 66 0.6 8 14 48 103 174 202 202 Rug Cleaners/Shampoos 12 0.3 0.3 0.3 9 26 26 26 26 All Puroose Cleaners 64 0.3 4 9 26 77 174 262 677 a The data in Table 16-15 above reflect for only the 14 tasks included in the survey. Therefore, many of the durations reported in the table underestimate the hours of the use of the product group. For example, use of dish detergents to wash dishes is not included. Source: Westat 1987b. Table 16-17. Total Exposure Time of Painting Activity of Interior Painters (hours\ Percentile Rankings for Duration of Painting Activity Mean (hrs) Types of Paint . (hrs) Std. dev. Min. 10 25 50 75 90 95 Max. Latex 12.2 11.28 1 3 4 9 15 24 40 248 Oil-based 10.68 15.56 1 1.6 3 6 10 21.6 65.6 72 Wood Stains and Varnishes 8.57 10.85 1 1 2 4 9.3 24 40 42 Source: Westat, 1987c. L_ __ Table 16-18. Exoosure Time of Interior Painting Activity/Occasion (hours) and Frequency of Oci:asions Spent Painting Per Year Types of Paint Duration of Frequency of Painting/Occasion . Occasions Spent (hrs) Painting/Year Percentile Rankings for Frequency of Occasions Spent Painting Mean Median Mean Std. dev. Min 10 25 50 75 90 95 Max. Latex 2.97 3 4.16 5.54 1 1 2 3 4 9 10 62 Oil-based 2.14 3 5.06 11.98 1 1 1 2 4 8 26 .72 Wood Stains and 2.15 2 4.02 4.89 1 1 1 2 4 9 20 20 Varnishes Source: Westat, 1987c. Table 16-19. Amount of Paint Used by Interior Painters Percentile Rankings for Amount of Paint Used Median Mean Std. (gallons) Types of Paint (gallons) (gallons) dev. Min 10 25 50 75 90 95 Max. Latex 3.0 3.89 4.56 0.13 1 2 3 5 8 10 50 Oil-based 2.0 2.55 3.03 0.13 0.25 0.5 2 3 7 12 12 Wood Stains and 0.75 0.88 0.81 0.13 0.14 0.25 0.75 1 2 2 4.25 Vamislies Source: Westat, 1987c. Table 16-20. Number of Respondents Using Perfume, Aftershave or Other Fraarances at Specified Dailv Frequencies Number of Times Used in a Dav Population Group TotalN 1-2 3-5 6-9 10+ DK Overall 2223 2100 113 4 2 4 Gender Male 912 868 44 * * * ' Female 1311 1232 69 4 2 4 Age .(Years) 33 31 1 1 *
5-11 26 24 2 * *

12-17 144 133 9 1 1 18-64 1735 1635 93 3 1 3 > 64 285 277 8 * *

Race White 1781 1684 91 4

2 Black 242 233 7

1 1 Asian 30 30 * * *

Some Others 38 35 3 * *

Hispanic 111 98 11

1 1 Refused 21 20 1 * *

Hispanic No 2012 1909 95 4 1 3 Yes 182 165 15

1 1 DK 11 9 2 * "'----*

Refused 18 17 1 * *

Employment c '

157 145 10

1 1 Full Time 1195 1125 67 2

1 Part Time 240 228 11

1

Not Employed 618 591 23 2

2 Refused 13 11 2 * * . Education . 208 194 12 . 1 1 < High School 190 177 13 . * . High School Graduate 739 704 32 2 . 1 <College 504 480 21 . 1 2 College Graduate 331 308 21 2 * . Post Graduate 251 237 14 . . . Census Region Northeast 459 434 21 3

1 Midwest 530 502 25 1 . 2* South 813 766 46 . 1 . West 421 398 21 . 1 1 Day of Week Weekday 1480 1402 71 3 . 4 Weekend 743 698 42 1 2

Season I Winter 604 574 26 1 1 2 Spring 588 549 36 1 1 1 Summer 568 535 31 2 . . Fall 463 442 20 . . 1 Asthma No 2075 1959 106 4 2 4 Yes 143 136 7 . . . DK 5 5 * * . . Angina No 2161 2043 108 4 2 4 Yes 52 47 5 . . . DK 10 10 . * ' . Bronchitis/emphysema '* No 2112 1994 108 4 2 4 Yes 103 98 5 . l . . DK 8 8 * . . . Note: * -Data; DK -Don't Know; Refused -Respondents Refused to Answer; N -Number of Respondents. Source: Tsana and Kleoeis 1996.
Table 16-21. Number of Respondents Using Any Aerosol Spray Product for Personal Care Item Such as Deodorant or Hair Spray at Specified Daily Frequencies Number of Times Used in a Dav Population Group Total N 1 2 3 4 5 6 7 10 10+ DK Overall 1491 1019 352 57 22 17 2 1 3 10 8 Gender Male 528 375 125 14 4 3 2 0 0 2 3 Female 962 644 226 43 18 14 0 1 3 8 5 Refused 1 0 1 0 0 0 0 0 0 0 0 Age (years) 0 27 14 . 8 1 2 1 0 0 0 0 1 1-4 40 30 9 0 0 1 0 0 0 0 0 5-11 75 57 14 1 1 1 1 0 0 0 0 12-17 103 53 31 12 4 1 0 0 1 1 0 18-64 1071 724 263 39 15 13 1 1 2 8 5 > 64 175 141 27 4 0 0 0 0 0 1 2 Race White 1232 855 285 47 17 8 2 0 3 10 5 Black 131 84 32 5 3 5 0 0 0 0 2 Asian 24 18 5 0 0 0 0 0 0 0 1 Some Others 22 12 8 1 0 0 0 1 0 0 0 Hispanic 73 45 19 4 1 4 0 0 0 0 0 Refused 9 5 3 0 1 0 0 0 0 0 0 Hispanic No 1359 937 316 49 20 13 2 1 3 10 8 Yes 119 74 32 7 2 4 0 0 0 0 0 DK 6 3 2 1 0 0 0 0 0 0 0 Refused 7 5 2 0 0 0 0 0 0 0 0 Emgloyment 210 137 52 11 4 3 1 0 1 1 0 Full Time 714 492 171 24 11 5 1 1 1 4 4 Part Time 152 99 35 7 0 5 0 0 0 4 2 Not Employed 404 284 92 14 6 4 0 0 1 1 2 Refused 11 7 2 1 1 0 0 0 0 0 0 Education 0 240 151 61 14 6 4 1 0 1 2 0 < High School 128 83 37 2 1 1 0 0 0 2 2 High School Graduate 528 365 121 23 7 5 1 0 2 1 3 <College 311 212 77 7 3 6 0 1 0 4 1 College Graduate 161 115 34 8 1 1 0 0 0 1 1 Post Graduate 123 93 22 3 4 0 0 0 0 0 1 Census Northeas 292 201 70 8 8 1 0 0 0 1 3 Midwest 340 227 85 14 4 3 1 0 1 3 2 South 585 388 148 23 8 8 0 1 2 4 3 West 274 203 49 12 2 5 1 0 0 2 0 eekday 994 695 220 35 17 12 1 0 1 7 6 Weekend 497 324 132 22 5 5. 1 1 2 3 2 Season Winter 381 264 86 15 5 4 0 0 0 4 3 Spring 408 269 104 12 9 9 0 1 1 1 2 Summer 400 282 86 21 5 2 1 0 0 1 2 Fall 302 204 76 9 3 2 1 0 2 4 1 Asthma No 1387 950 327 53 20 15 2 1 1 10 8 Yes 100 66 24 4 2 2 0 0 2 0 0 DK 4 3 1 0 0 0 0 0 0 0 0 ' 1451 990 344 55 22 17 2 1 3 9 8 Yes 35 26 7 1 0 0 0 0 0 1 0 DK 5 3 1 1 0 0 0 0 0 0 0 Bronchitis/emphysema No 1411 972 322 55 22 17 2 1 3 9 8 Yes* 74 44 29 1 0 0 0 0 0 0 0 DK 6 3 1 1 0 0 0 0 0 1 0 Note: *=Missing Data; "DK"= Don't Know; Refused = Respondents Refused To Answer; N= Sample Size Source: Tsanq And Klepeis 1996. Table 16-22. Number of Minutes Spent in Activities Working with or Being Near Freshly Applied Paints (minutes/day) Percentiles Category Population Group N 1 2 5 10 25 50 75 90 95 . 98 99 100 Overall 276 O* 0 1 2 15 60 121 121 121 121 121 121 Gen.der Male 145 0 0 1 2 10 48 121 121 121 121 121 121 Gender Female 131 0 0 1 3 15 120 121 121 121 121 121 121 Age (years) 1-4 7 3 3 3 3 5 15 121 121 121 121 121 121 Age (years) 5-11 12 5 5 5 15 20 45 120 120 121 121 121 121 Age (years) 12-17 20 0 0 0.5 3 8 45 75 121. 121 121 121 121 Age (years) 18-64 212 0 0 1 2 11 60 121 121 121 121 121 121 Age (years) >64 20 0 0 0 2.5 17.5 90 121 121. 121 121 121 121 Race White 241 0 0 2 4 15 60 121 121 121 121 121 121 Race Black 16 0 0 0 1 2.5 10 90 121 121 121 121 121 Race Asian 3 20 20 20 20 20 30 60 60 60 60 60 60 Race Some Others 2 10 10 10 10 10 20 30 30 30 30 30 30 Race Hispanic 12 0 0 0 1 3.5 27.5 120.5 121 121 121 121 121 Hispanic No 257 0 0 1 3 15 60 121 121 121 121 ' 121 121 Hispanic Yes 17 0 0 0 1 6 45 121 121 121 121 121 121 Employment Full Time 145 *o 1 2 3 10 60 121 121 121 121 121 121 Employment Part Time 31 0 0 0 1 30 60 121 121 121. 121 121 . 121 Employment Not Employed 61 0 0 0 2 30 120 121 121 121 121 121 121 Education < High School 13 0 0 0 1 5 45 121 121 121 121 121 121 Education High School Graduate 74 0 1 1 5 20 120 121 121 121 121 121 121 Education <College 72 0 0 2 2 12.5 105 121 121 121 121 121 121 Education College Graduate 42 0. 0 0 1 6 60 121 121 121 121 121 121 Education Post Graduate 30 2 2 3 4.5 15 30 121 121 121 121 121 121 Census Region Northeast 60 0 0 2 5 25 120 121 121 121 121 121 121 Census Region Midwest 70 0 0 0 2 10 55 121 121 121 121 121 121 Census Region South 90 0 0 1 2 10 47.5' 121 121 121 121 121 121 Census Region West 56 1 1 1 3 12.5 75 121 121 121 121 121 121 Day of Week Weekday 222 0 0 1 2 15 60 121 121 121 121 121 121 Day of Week Weekend 54 0 0 0 5 15 45 121 121 121 121 121 121 Season Winter 67 0 1 2 3 15 60 121 121 121 121 121 121 Season Spring 74 0 0 1 2 10 30 121 121 121 121 121 121 Season Summer 76 0 0 0 2 13.5 90 121 121' 121 121 121 121 Season Fall 59 .0 1 2 5 20 120 121 121 121 121 121 121 Asthma* No *257 0 0 1 2 15 60 121 121 121 121 121
121 Asthma Yes 19 1 1 1 2 10 45 121 121 121 121 121 121 Angina No 270 0 0 1 2 12 60 121 121 121 121 121 121 Angina Yes 6 45 45 45 45 60 121 121 121 121 121 121 121 Bronchitis/emphysema No 265 0 0 1 3 15 60 121 121 121 121 121 121 Bronchitis/emphysema Yes 11 0 0 0 2 5 45 121 121 121 121 121 121 Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent; n =doer sample size; percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis, 1996. \ \
Table 16-23. Number of Minutes Spent in Activities Working with or Near Household Cleaning Agents Such as Scouring Powders or Ammonia (minutes/day) Percentiles Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 905 0 0 0 1 4 10 20 60 121 121 121 121 Gender Male 278 0 0 1 2 3 10 20 60 121 121 121 121 Gender .Female 627 0 0 0 1 4 10 20 60 120 121 121 121 Age (years) 1-4 21 0 0 0 0 5 10 15 20 30 121 121 121 Age (years) 5-11 26 1 1 2 2 3 5 15 30 30 30 30 30 Age (years) 12-17 41 0 .0 0 0 2 5 10 40 60 60 60 60 Age (years) 18-64 672 0 0 1 2 5 10 20 60 121 121 121 121 Age (years) > 64 127 *O 0 0 1 3 5 15 30 60 120 121 121 Race White 721 0 0 1 1 4 10 20 60 121 121 121 121 Race Black 112 0 0 0 1 2 *5 12 30 90 121 121 121 Race Asian 16 0 0 0 5 5 10 15 20 30 30 30 30 Race Some Others 19 2 2 2 3 5 10 20 30 60 60 60 60 Race Hispanic 30 0 0 1 2.5 10 15 30 60 90 121 121 121 Hispanic No 838 0 0 0 1 3 10 20 60 121 121 121 121 Hispanic Yes 58 0 0 1 2 5 12.5 30 60 120 121 121 121 Employment Full Time 422 0 0 1 1 4 10 30 60 121 121 121 121 Employment Part Time 98 0 0 1 2 5 10 20. 60 121 121 121 121 Employment Not Employed 296 0 0 0 2 3 10 15 60 120 121 121 121 Education < High School 76 0 0 1 2 2 12.5 30 120 121 121 121 121 Education High School Graduate 304 0 0 0 2 5 10 20 60 120 121 121 121 Education <College 204 0 0 0 1 4.5 10 30 120 121 121 121 121 Education College Graduate 114 0 1 1 2 5 10 20 60 90 121 121 121 Education Post Graduate 109 0 0 1 1 3 5 15 30 60 121 121 121 Census Region Northeast 207 0 0 0 1 3 5 15 45 120 121 121 121 Census Region Midwest 180 0 0 0 . 1 5 10 30 75 121 121 121 121 Census Region South 309 0 0 1 2 4 10 20 60 120. 121 121 121 Census Region West 209 0 0 1 1 4 10 20 60 121 121 121 121 Day of Week Weekday 580 0 0 0 1 3 10 20 60 121 121 121 121 Day of Week Weekend 325 0 0 1 2 5 10 20 60 90 121 121 121 Season Winter 240 0 0 0 2 3 10 20 75 121 121 121 121 Season Spring 220 0 0 0 1 3 10 17.5 52.5 104 121 121 121 Season Summer 244 0 0 0 2 4 10 20 30 60 121 121 121 Season Fall 201 0 0 1 2 5 10 30 90 121 121 121 121 Asthma No 826 0 0 0 1 3 10 20 60 120 121 121 121 Asthma Yes 79 0 0 1 2 5 10 30 120 121 121 121 121 Angina No 868 0 0 0 1 4 10 20 60 121 121 121 121 Angina Yes 33 0 0 2 2 5 5 3p 120 121 121 121 121 Bronchitis/emphysema No 843 0 0 0 1 4 10 20 60 120 121 121 121 Bronchitis/emphysema Yes 60 0 0 1 2 3.5 10 32.5 120.5 121 121 121 121 Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent; n =doer sample size; percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis, 1996. Table 16-24. Number of Minutes Spent in Activities (at home or elsewhere) Working with or Near Floorwax, Furniture Wax or Shoe Polish (minutes/day) Percentiles Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 325 0 0 2 2 5 10 30 60 121 121 121 121 Gender Male 96 0 0 1 2 5 11 30 121 121 121 121 121 Gender Female 229 0 0 2 3 5 10 30 60 121 121 121 121 Age (years) 1-4 13 0 0 0 5 10 15 20 60 121 121 121 121 Age (years) 5-11 21 0 0 2 2 3 5 10 35 60 120 120 120 Age (years) 12-17 15 0 0 0 1 2 10 25 45 121 121 121 121 Age (years) 18-64 238 0 0 2 3 5 15 30 120 121 121 121 121 Age (years) > 64 34 0 0 0 2 5 10 20 35 121 121 121 121 Race White 267 0 0 2 2 5 10 30 60 121 121 121 121 Race Black 32 2 2 2 5 5 15 30 60 121 121 121 121 Race Asian 1 4 4 4 4 4 4 4 4 4 4 4 4 Race Some Others 6 0 0 0 0 2 22.5 60 121 121 121 121 121 Race Hispanic 18 1 1 1 4 5 12.5 30 120 121 121 121 121 Hispanic No 291 0 0 2 2 5 10 30 60 121 121 121 121 Hispanic Yes 31 1 1 4 5 5 10 30 90 120 121 121 121 Employment Full Time 150 0 0.5 2 3 5 15 30 121 121 121 121 121 Employment Part Time 32 3 3 5 5 10 15 30 60 121 121 121 121 Employment Not Employed 92 0 0 1 2 5 10 20 60 120 121 121 121 Education < High School 26 2 2 3 5 5 10 15 60 60 60 60 60 Education High School Graduate 115 0 0 2 3 5 12 30 120 121 121 121 121 Education <College 70 0 1 2 3 10 15 30 75 121 121 121 121 Education College Graduate 29 2 2 3 5 7 30 60 121 121 121 121 121 Education Post Graduate 31 0 0 0 2 4 10 30 60 121 121 121 121 Census Region Northeast 77 0 0 2 3 5 10 30 60 121 121 121 121 Census Region Midwest 70 0 0 1 2 5 10 25 90 121 121 121 121 Census Region South 125 0 0 2 2 5 10 30 120 121 121 121 121 \:ensus Region West 53 0 0 1 3 5 15 30 120 121 121 121 121 Day of Week Weekday 210 0 0 2 2 5 10 30 120 121 121 121 121 Day of Week Weekend 115 0 0 2 3 5 10 *30 60 120 121 121 121 Season Winter 92 0 1 2 4 7 13.5 30 121 121 121 121 121 Season Spring 78 0 0 1 2 5 15 30 60 121 121 121 121 Season Summer 81 0 0 2 2 5 15 30 120 121 121 121 121 Season Fall 74 0 0 0 2 5 10 15 60 121 121 121 121 Asthma No 296 0 0 2 2 5 10 30 60 121 121 121 121 Asthma Yes 29 0 0 0 2 5 15 30 121 121 121 121 121 Angina No 312 0 0 2 2 5 10 30 60 121 121 121 121 Angina Yes 12 0 0 0 2 4 10 12.5 30 121 121 121 121 Bronchitis/emphysema No 302 0 0 2 2 5 10 30 90 121 121 121 121 Bronchitis/emphysema Yes 22 0 0 2 2 5 10 15 20 20 121 121 121 Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent; n =doer sample size; percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsano and Kleoeis; 1996. Table 16-25. Number of Minutes Spent in Activities Working with or Being Near Glue (minutes/day) Percentiles Category Population Group N 1 2 5 10 25 50 75 90, 95 98 99 100 Overall 294 0 0 0 1 5 15 60 121 121 121 121 121 Gender Male 151 0 0 0 2 5 15 70 121 121 121 121 121 Gender Female 143 0 0 0 1 5 15 30 121 121 121 121 121 Age (years) 1-4 6 0 0 0 0 30 30 30 50 50 50 50 50 Age (years) 5-11 36 2 2 3 5 5 12.5 25 30 60 120 120 120 Age (years) 12-17 34 0 0 1 2 5 10 30 30 60 120 120 120 Age (years) 18-64 207 0 0 0 1 5 20 90 121 121 121 121 121 Age (years) > 64 10 0 0 0 0 0 3.5 60 120.5 121 121 121 121 Race White 241 0 0 0 1 5 15 60 121 121 121 121 121 Race Black 28 0 0 0 2 5 12.5 45 121 121 121 121 121 Race Asian 4 10 10 10 10 12.5 17.5 40 60 60 60' 60 60 Race Some Others 7 1 1 1 1 3 30 90 120 120 120 120 120 Race Hispanic 12 5 5 5 5 5 27.5 90 121 121 121 121 121 Hispanic No 260 0 0 0 1 5 15 60 121 121 121 121 121 Hispanic Yes 27 3 3 5 5 5 30 120 121 121 121 121 121 Employment Full Time 150 0 0 0 1 5 20 120 121 121 121 121 121 Employment Part Time 24 1 1 2 3 10 27.5 90 121 121 121 121 121 Employment Not Employed 46 0 0 0 0 2 10 30 121 121 121 121 121 Education < High School 11 0 0 0 0 1 5 10 60 121 121 121 121 Education High School Graduate 69 0 0 0 1 5 20 90 121 121 121 121 121 Education <College 66' 0 0 0 1 5 27.5 121 121 121 121 121 121 Education College Graduate 37 0 0 0 1 5 15 30 121 121 121 121 121 Education Post Graduate 32 0 0 0. 1 5 15 60 121 121 121 121 121 Census Region Northeast 55 0 0 0 1 5 20 60 121 121 121 121 121 Census Region Midwest 71 0 0 1 2 5 15 60 121 121 121 121 121 Census Region South 98 0 0 0 1 5 15 60 121 121 121 121 121 Census Region West 70 0 0 0 1 5 15 60 121 121 121 121 121 Day of Week Weekday 228 0 0 0 1 5 15 60 121 121 121 121 121 Day of Week Weekend 66 0 0 0 1 5 15 60 121 121 121 121 121 Season Winter 85 0 0 0 2 5 15 45 121 121 121 121 121 Season Spring 74 0 0 0 2 5 10 30 121 121 121 121 121 Season Summer 66 0 0 0 1 10 20 121 121 121 121 121 121 Season Fall 69 0 0 0 1 5 15 60 121 121 121 121 121 Asthma No 266 0 0 0 1 5 15 60 121 121 121 121 121 Asthma Yes 28 0 0 0 1 5 17.5 40 121 121 121 121 121 Angina No 290 0 0 0 1 5 15 60 121 121 121 121 121 Angina Yes 3 1 1 1 1 1 121 121 121 121 121 121 121 Bronchitis/emphysema No 283 0 0 0 1 5 15 60 121 121 121 121 121 Bronchitis/emphysema Yes 11 1 1 1 1 2 30 121 121 121 121 121 121 Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent; n = doer sample size; percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsano and Kleoeis 1996. Table 16-26. Number of Minutes Spent in Activities Working with or Near Solvents, Fumes or Strong Smelling Chemicals (minutes/day) Percentiles Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 495 0 0 0 2 5 20 121 121 121 121 121 121 Gender Male 258 0 0 1 2 5 30 121 121 121 121 121 121 Gender Female 237 0 0 0 1 5 15 90 121 121 121 121 121 Age (years) 1-4 7 0 0 0 0 1 5 60 121 121 121 121 121 Age (years) 5-11 16 0 0 0 2 5 5 17.5 45 70 70 70 70 Age (years) 12-17 38 0 0 0 0 5 10 60 121 121 121 121 121 Age (years) 18-64 407 0 0 1 2 5 30 121 121 121 121 121 121 Age (years) > 64 21 0 0 0 0 2 5 15 121 121 121 121 121 Race White 413 0 0 0 2 5 20 121 121 121 121 121 121 Race Black _40 0 0 1 3.5 9 60 121 121 121 121 121 121 Race Asian 8 5 5 5 5 10 37.5 120.5 121 121 121 121 121 Race Some Others 8 2 2 2 2 2.5 5 60 121 121 121 121 121 Race Hispanic 23 0 0 0 0 5 30 121 121 121 121 121 121 Hispanic No 449 0 0 0 2 5 20 121 121 121 121 121 121 Hispanic Yes 41 0 0 0 0 5 20 121 121 121 121 121 121 Employment Full Time 299 0 0 1 2 10 30 121 121 121 121 121 121 Employment Part Time 44 0 0 2 2 5 22.5 121 121 121 121 121 121 Employment Not Employed 91 0 0 0 0 2 10 60 121 121 121 121 121 Education < High School 35 0 0 1 2 5 15 121 121 121 121 121 121 Education High School Graduate 138 0 0 1 2 5 30 121 121 121 121 121 121 Education <College 128 0 0 1 2 5 30 121 121 121 121 121 121 Education College Graduate 69 0 0 0 1 5 30 121 121 121 121 121 121 Education Post Graduate 60 0 0 0 1.5 5 27.5 121 121 121 121 121 121 Census* Region Northeast 101 0 0 2 2 5 20 121 121 121 121 121 121 Census Region Midwest 122 0 0 0 2 5 30 121 121 121 121 121 121 Census Region South 165 0 0 0 2 5 20 121 121 121 121 121 121 Census Region West 107 0 0 0 2 5 20 121 121 121 121 121 121. Day of Week Weekday 362 0 0 0 2 5 30 121 121 121 121 121 121 Day of Week Weekend 133 0 0 0 2 5 15 90 121 121 121 121 121 Season Winter 128 0 0 0 2 5 20 95 121 121 121 121 121 Season Spring 127 0 0 0 1 5 20 121 121 121 121 121 121 Season Summer 149 0 0 1 2 5 21 121 121 121 121 121 121 Season Fall 91 0 0 . 1 2 5 30 121 121 121 121 121 121 Asthma No 445 0 0 0 2 5 20 121 121 121 121 121 121 Asthma Yes 50 0 0 1 1 5 15 121 121 121 121 121 121 Angina No 489 0 0 0 2 5 20 121 121 121 121 121 121 Angina Yes 6 0 0 0 0 2 15 121 121 121 121 121 121 Bronchitis/emphysema No 469 0 0 0 2 5 20 121 121 121 121 121 121 Bronchitis/emphysema Yes 26 2 2 2 2 5 17.5 60 121 121 121 121 121 Note: A Value of "121" for Number of Minutes Signifies That More than 120 Minutes Were Spent; N = Doer Sample Size; Percentiles Are the Percentage of Doers below or Equal to a Given Number of Minutes. Source: Tsana and Kleoeis, 1996. Table 16-27. Number of Minutes Spent in Activities Working with or Near Stain or Spot Removers (minutes/day) Percentiles Category Pop.ulation Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 109 0 0 0 0 2 5 15 60 121 121 121 121 Gender Male 42 0 0 0 0 3 5 60 121 121 121 121 121 Gender Female 67 0 0 0 0 2 5 10 20 30 60 120 120 Age (years) 1-4 3 0 0 0 0 0 0 3 3 3 3 3 3 Age (years) 5-11 3 3 3 3 3 3 5 5 5 5 5 5 5 Age (years) 12-17 7 0 0 0 0 5 15 35 60 60 60 60 60 Age (years) 18-64 87 0 0 0 0 2 5 15 60 121 121 121 121 . Age (years) > 64 9 0 0 0 0 2 3 15 121 121 121 121 121 Race White 88 0 0 0 0 2 5 15 60 121 121 121 121 Race Black 9 0 0 0 0 5 5 6 121 121 121 121 121 Race Asian 2 5 5 5 5 5 7.5 10 10 10 10 10 10 Race Some Others 3 0 0 0 0 0 2 3 3 3 3 3 3 Race Hispanic 7 1 1 1 1 2 5 30 35 35 35 35 35 Hispanic No 97 0 0 0 0 2 5 15 60 121 121 121 121 Hispanic Yes 12 0 0 0 1 2 3 22.5 35 121 121 121 121 Employment Full Time 62 0 0 0 0 2 5 15 120 121 121 121 121 Employment Part Time 8 0 0 0 0 3 5 12.5 20 20 20 20 20 Employment Not Employed 25 0 0 0 0 2 4 15 60 121 121 121 121 Education < High School 6 3 3 3 3 3 20 30 60 60 60 60 60 Education High School Graduate 34 0 0 0 0 1 4 10 120 121 121 121 121 Education <College 22 0 0 0 1 3 5 15 20 121 121 121 121 Education College Graduate 16 0 0 0 1 3 5 12.5 60 121 121 121 121 Education Post Graduate 16 0 0 0 0 1 5 15 20 121 121 121 121 Census Region Northeast 21 0 0 1 1 3 5 10 121 121 121 121 121 . Census Region Midwest 25 0 0 0 0 2 5 15 60 60 121 121 121 Census Region South 38 0 0 0 0 2 5 15 60 120 121 121 121 Census Region West 25 0 0 0 0 2 5 25 60 60 121 121 121 Day of Week Weekday 75 0 0 0 0 2 5 15 120 121 121 121 121 Day of Week Weekend 34 0 0 0 0 2 5 15 60 60 120 120 120 Season Winter 26 0 0 0 0 2 5 15 60 120 120 120 120 Season Spring 30 0 0 0 0.5 2 5 15 32.5 121 .121 121 121 Season Summer 37 0 0 0 0 2 5 20 121 121 121 121 121 Season Fall 16 0 0 0 1 5 5 15 60 121 121 121 121 Asthma No 100 0 0 0 0 2 5 15 60 120.5 121 121 121 Asthma Yes 9 0 0 0 0 2 5 6 121 121 121 121 121 Angina No 109 0 0 0 0 2 5 15 60 121 121 121 121 Bronchitis/emphysema No 105 0 0 0 0 2 5 15 60 121 121 121 121 Bronchitis/emphysema Yes 4 0 0 0 0 0.5 1.5 8.5 15 15 15 15 15 Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent; n =doer sample size; percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsanq and Klepeis 1996. Table 16-28. Number of Minutes Spent in Activities Working with or Near Gasoline or Diesel-powered Equipment, Besides Automobiles (minutes/day) Percentiles Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 390 0 0 1 3 10 60 121 121 121 121 121 121 Gender Male 271 0 0 1 3 15 60 121 121 121 121 121 121 Gender Female 119 1 1 1 2 8 30 120 121 121 121 121 121 Age (years) 1-4 14 0 0 0 1 5 22.5 120 121 121 121 121 121 Age (years) 5-11 12 1 1 1 3 7.5 25 50 60 60 60 60 60 Age (years) 12-17 25 2 2 5 5 13 35 120 121 121 121 121 121 Age (years) 18-64 312 0 0 1 3 15 60 121 121 121 121 121 121 Age (years) > 64 26 2 2 2 3 10 25 90 121 121 121 121 121 Race White 355 0 1 1 3 15 60 121 121 121 121 121 121 Race Black 15 1 1 1 1 2 15 121 121 121 121 121 121 Race Asian 8 0 0 0 0 5 11.5 17.5 90 90 90 90 90 Race Some Others 2 1 1 1 1 1 23 45 45 45 45 45 45 Race Hispanic 8 3 3 3 3 10 105.5 121 121 121 . 121 121 121 Hispanic No 367 0 0 1 3 10 60 121 121 121 121 121 121 Hispanic Yes 19 1 1 1 2 5 30 121 121 121 121 121 121 Employment Full Time 237 0 0 1 2 20 90 121 121 121 121 121 121 Employment Part Time 33 1 1 2 2 10 45 121 121 121 121 121 121 Employment Not Employed 66 0 0 *2 4 10 30 121 121 121 121 121 121 Education < High School 33 0 0 1 2 6 60 121 121 121 121" 121 121 Education High School Graduate 135 1 1 2 5 20 90 121 121 121 121 121 121 Education <College 89 0 1 2 3 15 60 121 121 121 121 121 121 Education College Graduate 48 0 0 0 1 10 60 120 121 121 121 121 121 Education Post Graduate 30 0 0 1 1.5 10 30 120 121 121 121 121 121 Census Region Northeast 57 0 1 1 1 10 60 121 121 121 121 121 121 Census Region Midwest 117 0 0 1 5 15 90 121 121 121 121 121 121 Census Region South 151 0 1 2 3 10 60 121 121 121 121 121 121 Census Region West 65 0 0 1 3 10 45 121 121 121 121 121 121 Day of Week Weekday 278 0 0 1 2 10 60 121 121 121 121 121 121 Day of Week Weekend 112 1 . 1 2 5 15 45 120 121 121 121 121 121 Season Winter 97 0 0 1 2 10 60 121 121 121 121 121 121 Season Spring 110 0 1 1 3 10 60 121 121 121 121 121 121 Season Summer 119 0 1 2 5 15 60 121 121 121 121 121 121 Season Fall 64 0 1 1 2 5 30 121 121 121 121 121 121 Asthma No 361 0 0 1 3 10 60 121 121 121 121 121 121 Asthma Yes 28 2 2 3 3 30 120.5 121 121 121 121 121 121 Angina No 381 0 0 1 3 10 60 121 121 121 121 121 121 Angina Yes 7 15 15 15 15 20 45 121 121 121 121 121 121 Bronchitis/emphysema No 368 0 0 1 3 15 60 121 121 121 121 121 121 Bronchitis/emphysema Yes 21 2 2 3 3 5 45 121 121 121 121 121 121 Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent; n =doer sample size; percentiles are the percer:itage of doers below or equal to a given number of minutes. Source: Tsanq and Kleoeis, 1996. Table 16-29. Number of Minutes Spent Using Any Microwave Oven (minutes/day) Percentiles Cateaorv Pooulation Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 2298 0 0 1 1 3 5 10 15 30 40 60 121 Gender Male 948 0 0 1 1 2 5 10 15 30 40 67 121 Gender Female* 1350 0 0 1 1.5 3 5 10 20 30 42.5 60 121 Age (years) 5-11 62 0 0 0 1 1 2 5 10 15 20 30 30 Age (years) 12-17 141 0 0 0 1 2 3 5 10 15 30 30 60 Age (years) . 18-64 1686 0 0 1 2 3 5 10 15 25 45 60 121 Age (years) >64 375 0 0 1 2 3 5 10 20 30 60 60 70 Race White 1953 0 0 1 2 3 5 10 16 30 40 60 121 Race Black 182 0 0 1 1 2 3 6 15 20 30 30 121 Race Asian 38 0 0 1 1 3 5 10 20 30 60 60 60 Race Some Others 29 0 0 2 2 3 5 10 30 30 50 50 50 Race Hispanic 74 0 0 0 1 2 3 10 15 45 120 121 121 Hispanic No 2128 0 0 1 1 3 5 10 15 30 35 60 121 Hispanic Yes 139 0 0 0 1 2 5 10 20 30 120 120 121 Employment Full Time 1114 0 0 1 1 3 5 10 15 30 34 60 121 Employment Part Time 237 0 0 1 1 3 5 10 20 30 60 120 121 Employment Not Employed 734 0 0 1 2 3 5 10 20 30 45 60 120 Education < High School 190 0 0 0 1.5 3 5 10 33 60 121 121 Education High School Graduate 717 0 0 1 2 3 5 10 20 30 45 60 121 Education <College 518 o* 0 1 2 3 5 10 18 30 60 120 121 *Education College Graduate 347 0 0 1 2 3 5 10 15 25 30 60 70 Education Post Graduate 288 0 0 1 1 3 5 10 15 20 30 30 90 Census Region Northeast 420 0 0 1 2 2 5 10 20 30 60 60 121 Census Region Midwest 545 0 0 1 1 3 5 10 15 30 35 60 121 Census Region South 831 0 0 1 2 3 5 10 16 30 45 60 121 Census Region West 502 0 0 1 1 2 5 10 15 20 30 60 121 Day of Week Weekday 1567 o. 0 1 1 3 5 10 15 25 30 60 121 Day of Week Weekend 731 0 0 1 1 2 5 10 20 30 50 120 121 Season Winter 657 0 0 1 2 2 5 10 15 30 40 67 121 Season Spring 577 0 0 1 2 3 5 10 20 30 45 60 120 Season Summer 565 0 0 0 1 2 5 10 15 20 30 60 120 Season Fall 499 0 0 1 1 2 5 10 20 30 45 120 121 Asthma No 2109 0 0 1 1 2 5 10 15 30 40 60 121 Asthma Yes 180 0 0 1 2 3 5 10 19 30 45 60 121 Angina No 2212 0 0 1 1 2 5 10 15 30 40 60 121 Angina Yes 72 0 0 1 2 3 6 10 15 30 45 60 60 Bronchitis/emphysema No 2164 0 0 1 1 2 5 10 15 30 40 60 121 Bronchitis/emphysema Yes 124 0 0 1 1 3 5 10 30 30 60 120 121 Note: A Value of "121" for number of minutes signifies that more than 120 minutes were spent; n =doer sample size; percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsana and Kleoeis, 1996. Table 16-30. Number of Respondents Using a Humidifier at Home Frequency Almost Total N Every 3-5 Times a 1-2 Times a 1-2 Times a DK Day Week Week Month Overall 1047 . 300 121 107 495 24 Gender Male 455 135 53 48 208 11 Female 591 165 68 59 286 13 Refused 1 * *
1 * (years) 16 3 1 3 7 2 1-4 111 33 16 7 53 2 5-11 88 18 10 12 46 2 12-17 83 21 7 5 49 1 18-64 629 183 77 70 287 12 > 64 120 42 10 10 53 5 Race White 879 268 98 79 414 20 Black 93 24 10 15 42 2 Asian 18 3 2 1 11 1 Some Others 20 1 3 4 12

Hispanic 30 2 7 8 13

Refused 7 2 1

3 1 978 286 109 95 466 22 Yes 60 11 11 12 25 1 DK 5 3 *

2

Refused 4

1 0 2 1 Employment 279 70 32 25 147 5 Full Time 416 124 43 44 194 11 Part Time 88 22 14 9 43

Not Employed 256 82 29 29 109 7 Refused 8 2 3

2 1 Education

303 74 36 27 160 6 < High School 86 27 15 14 29 1 High School Graduate 251 85 27 28 104 7 <College 188 53 16 17 97 5 College Graduate 119 32 17 13 56 1 Post Graduate 100 29 10 8 49 4 Census Northeas 273 84 26 28 132 3 Midwest 326 102 37 32 142 13 South 302 83 42 31 141 5 West 146 31 16 16 80 3 eekday 698 196 83 70 335 14 Weekend 349 104 38 37 160 10 Season Winter 320 135-46 34 98 7 *Spring 257 58 23 29 144 3 Summer 269 56 27 20 155 11 Fall 201 51 25 24 98 3 Asthma No 948 272 110 95 448 23 Yes 92 27 9 10 45 1 DK 7 1 2 2 2

1015 290 116 103 482 24 Yes 24 8 4 3 9

DK 8 2 1 1 4

Bronchitis/emphysema No 994 278 117 102 473 24 Yes 48 21 3 4 20

DK 5 .1 1 1 2

Note: * = Missing Data; DK= Don't Know; Refused = Respondent Refused to Answer; N = Number of Respondents Source: Tsano and Kleoeis, 1996.
Table 16-31. Number of Respondents Indicating that Pesticides Were Applied by the Professional at Home to Eradicate Insects, Rodents, or Other Pests at Specified Frequencies Total N Number of Times Over a 6-month Period Pesticides Were Aoolied bv Professionals None 1-2 3-5 6-9 10+ DK Overall 1946 1057 562 134 150 20 23 Gender Male 897 498 248 64 64 11 12 Female 1048 558 314 70 86 9* 11 Refused 1 1 * * * *
Ag.e (years 33 17 8 4 4 *

1-4 113 60 35 11 6 1

5-11 150 84 37 10 18 1

12-17 143 90 40 5 6

2 18-64 1264 660 387 89 97 15 16 ;> 64 243 146 55 15 19 3 5 Race White 1532 856 429 98 117 14 18 Black 231 107 78 20 17 4 5 Asian 24 13 10 1 * *

Some Others 38 24 8 4 2 *

Hispanic 100 45 33 10 11 1

Refused 21 12 4 1 3 1

1750 960 499 121 130 19 21 Yes 172 83 56 12 18 1 2 DK 8 5 3 * * *

Refused :16 9 4 1 2 *

E":!ployment 398 229 111 24 30 2 2 Full Time 855 463 252 59 60 11 10 Part Time 163 84 50 14 12 2 1 Not Employed 512 272 145 35 46 5 9 Refused 18 9 4 2 2

1 Education

436 246 122 27 35 2 4 < High School 137 80 31 11 10 1 4 High School Graduate 483 265 140 26 38 9 5 <College 416 218 131 28 29 4 6 College Graduate 272 137 87 25 20 2 1 Post Graduate 202 111 51 17 18 2 3 Census Region Northeast 335 201 85 2 22 3 4 Midwest 318 202 84 17 13

2 South 875 404 298 63 86 11 13 West 418 250 95 34 29 6 4 Day of Week Weekday 1303 702 374 91 105 16 15 Weekend 64.3 355 188 43 45 4 8 Season Winter 466 247 129 29 46 9 6 Spring 449 240 128 30 43 3 5 Summer 584 324 172 40 34 6 8 Fall 447 246 133 35 27 2* 4 Asthma No 1766 969 509 121 129 16 22 Yes 167 80 50 13 19 4 1 DK 13 8 3

2 *

1880 1019 549 131 141 19 21 Yes 53 30 10 3 7 1 2 DK 13 8 3

2 *

Bronchitis/emphysema No 1833 1004 524 127 140 18 20 Yes 101 46 36 7 8 1 3 DK 12 7 2

2 1

Note: * = Missing Data; DK= Don't know; Refused = Respondent Refused to Answer; N = Number of Respondents Source: Tsana and Kleoeis, 1996.
Table 16-32. Number of Respondents Reporting Pesticides Applied by the Consumer at Home . To Eradicate Insects, Rodents, or Other Pests at Specified Frequencies Total N Number of Times a 6-month Period Pesticides Aoolied bv Resident None 1-2 3-5 6-9 10+ DK Overall 1946 . 721 754 286 73 83 29 Gender Male 897 318 367 135 31 35 11 Female 1048 403 386 151 42 48 18 Refused 1
1 * * *

Ag.e (years) . 33 13 12 3 1 4

1-4 113 46 46 15 3 3

5-11 150 50 70 24 1 4 1 12-17 143 45 64 21 5 . 8

18-64 1264 473 477 192 48 55 19 > 64 243 94 85 31 15 9 9 Race White 1532 574 600 227 55 50 26 Black 231 81 77 36 10 25 2 Asian 24 4 15 3 1 1

Some Others 38 11 12 11 1 2 1 Hispanic 100 41 42 9 5 3

Refused 21 10 8

1 2

1750 647 677 258 63 76 29 Yes 172 66 67 26 10 3

DK 8 2 3 1

2

Refused 16 6 7 1

2

E"1ployment 398 139 176 59 9 14 1 Full Time 855 298 342 131 37 35 12 Part Time 163 67 66 20 4 5 1 Not Employed 512 209 163 76 23 27 14 Refused 18 8 7 *

2 1 Education

436 157 189 62 10 17 1 < High School 137 44 50 19 4 14 6 High School Graduate 483 184 196 53 21 18 11 <College 416 157 158 63 18 16 4 College Graduate 272 97 97 53 9 12 4 Post Graduate 202 82 64 36 11 6 3 Census Region Northeast 335 112 131 56 12 19 5 Midwest 318 108 145 35 12 12 6 South 875 363 316 119 30 37 10 West 418 138 162 . 76 19 15 8 eekday 1303 485 503 186 44 66 19 Weekend 643 236 251 100 29 17 10 Season Winter 466 190 153 75 18 21 9 Spring 449 170 192 51 15 16 5 Summer 584 204 233 89 21 27 10 Fall 447 157 176 71 19 19 5 Asthma No 1766 643 695 261 70 70 27 Yes 167 73 54 25 3 11 1 DK 13 5 5 *

2 1 1880 696 731 276 70 80 27 Yes 53 21 19 8 3 1 1 DK 13 4 4 2 0 2 1 Bronchitis/emphysema No 1833 675 715 272 72 71 28 Yes 101 41 35 14 1 10

DK 12 5 4 *

2 1 Note: * = Missing Data; DK= Don't know; Refused = Respondent Refused to Answer; N = Number of Respondents Source: Tsanq and Kleoeis 1996.
Table 16-33. Number of Minutes Spent in Activities Working with or Near Pesticides, Including Bug Sprays or Bug Strips (minutes/day) Percentiles Category Population Group N 1 2 5 10 25 50 75 90 95 98 99 100 Overall 257 0 0 0 0 2 10 60 121 121 121 121 121 Gender Male 121 0 0 1 1 2 10 90 121 121 121 121 121 Gender Female 136 0 0 0 2 0 35 121 121 121 121 121 Age (years) 1-4 6 1 1 1 1 3 10 15 20 20 20 20 20 Age (years) 5-11 16 0 0 0 0 1.5 7.5 30 121 121 121 121 121 Age (years) 12-17 10 0 0 0 0 2 2.5 40 121 121 121 121 121 Age (years) 18-64 190 0 0 0 1 2 10 88 121 121 121 121 121 Age (years) >64 31 0 0 0 0 2 5 15 60 121 121 121 121 Race White 199 0 0 0 1 2 10 60 121 121. 121 121 121 Race Black 36 0 0 0 0 1 3 20 121 121 121 121 121 Race Asian 2 5 5 5 5 5 7.5 10 10 10 10 10 10 Race Some Others 4 0 0 0 0 1.5 6.5 10 10 10 10 10 10 Race Hispanic 15 0 0 0 0 2 20 121 121 121 121 121 121 Hispanic No 231 0 0 0 0 2 10 60 121 121 121 121 121 Hispanic Yes 25 0 0 0 1 5 20 121 121 121 121 121 121 Employment Full Time 124 0 0 0 1 2 10 120.5 121 121 121 121 121 Employment Part Time 26 0 0 0 1 2 5 60 121 121 121 121 121 Employment Not Employed 75 0 0 0 0 2 5 30 121 121 121 121 Education < High School 20 1 1 1 1 2.5 22.5 105.5 121 121 121 121 121 Education High School Graduate 87 0 0 0 0 2 10 45 121 121 121 121 121 Education <College 56 0 0 0 1 2 10 89 121 121 121 121 121 Education College Graduate 29 0 0 0 0 1 10 90 121 121 121 121 121 Education Post Graduate 29 0 0 0 0 3 10 30 121 121 121 121 121 Census Region Northeast 45 0 0 1 2 5 10 88 121 121 121 121 121 Census Region Midwest 51 0 0 0 . 0 2 10 121 121 121 121 121 121 Census Region South 106 0 0 0 0 2 5 30 121 121 121 121 121 Census Region West 55 0 0 0 1 2 10 45 121 121 121 121 121 Day of Week Weekday 183 0 0 0 0 2 10 60 121 121 121 121 121 Day of Week Weekend 74 0 0 0 1 3 10 30 121 121 121 121 121 Season Winter 39 0 0 0 0 2 5 90 121 121 121 121 121 Season Spring 78 .o 0 0 0 2 10 60 121 121 121 121 121 Season Summer 105 0 0 0 1 2 10 60 121 121 121 121 121 Season Fall 35 0 0 0 0 1 10 60 121 121 121 121 121 Asthma No 231 0 0 0 1 2 10 60 121 121 121 121 121 Asthma Yes 24 0 0 0 0 1 5 90.5 121 121 121 121 121 Angina No 244 0 0 0 0 2 10 60 121 121 121 121 121 Angina Yes 8 1 1 1 1 2 5 75.5 121 121 121 121 121 Bronchitis/emphysema No 240 0 0 0 0 2 10 60 121 121 121 121 121 Bronchitis/emphysema Yes 14 1 1 1 2 2 5 30 121 121 121 121 121 Note: A value of "121" for number of minutes signifies that more than 120 minutes were spent; n = doer sample size. Percentiles are the percentage of doers below or equal to a given number of minutes. Source: Tsano and Kleoeis 1996. Table 16-34. Amount and Frequency of Use of Various Cosmetic and Baby Products Average Frequency of Use Upper 9oth Percentile Frequency of Use Amount of (per day) (per day) Product Type Product Pe£ Survey Type Survey Type Applic9tion (grams) Market0 Market Cosmetic Research Cosmetic .Research CTFA Co. Bureau CTFA Co. Bureau Baby Lotion -baby use c 1.4 0.38 1.0 0.57 2.0 ----Baby Lotion -adult use 1.0 0.22 0.19 0.24d 0.86 1.0 1.0d Baby Oil -baby use c 1.3 0.14 1.2 0.14 3.0 ---Baby Oil -adult use 5.0 0.06 0.13 --0.29 0.57 --Baby Powder -baby use c 0.8 5.36 1.5 0.35d 8.43 3.0 1.0d . Baby Powder -adult use 0.8 0.13 0.22 --0.57 1.0 --Baby Cream -baby use c 0.43 1.3 0.43 3.0 ------. Baby Cream -adult use --0.07 0.10 --0.14 0.148 --Baby Shampoo -baby use c 0.5 0.14 0.11 f 0.14 0.43f ----Baby Shampoo -adult use 5.0 0.02 --0.868 ----Bath Oils 14.7 0.08 0.19 0.229 0.29 0.86 1.09 Bath Tablets --0.003 0.008 --0.14e 0.14e --Bath Salts 18.9 0.006 0.013 --0.14e 0.14e -Bubble Baths 11.8 . 0.088 0.13 --0.43 0.57 --Bath Capsules --0.018 0.019 --0.298 0.148 -Bath Crystals -0.006 ----0.298 0.148 --Eyebrow Pencil --0.27 0.49 --1.0 1.0 --Eyeliner --0.42 0.68 0.27 1.43 1.0 1.0 Eye Shadow --0.69 0.78 0.40 1.43 1.0 1.0 Eye Lotion --0.094 0.34 -0.43 1.0 --Eye Makeup Remover --. 0.29 0.45 --1.0 1.0 --Mascara --0.79 0.87 0.46 1.29 1.0 1.5 Under Eye Cover -0.79 ----0.29 ----Blusher & Rouge 0.011 1.18 1.24 0.55 2.0 1.43 1.5 Face Powders 0.085 0.35 0.67 0.33 1.29 1.0 1.0 Foundations 0.265 0.46 0.78 0.47 1.0 1.0 1.5 Leg and Body Paints .. --0.003 0.011 --0.148 0.148 --Lipstick & Lip Gloss --1.73 1.23 2.62 4.0 2.86 6.0 Makeup Bases 0.13 0.24 0.64 --0.86 1.0 --Makeup Fixatives --0.052 0.12 -0.14 1.0 -Sunscreen 3.18 0.003 --0.002 0.14e --0.005 Colognes & Toilet Water 0.65 0.68 0.85 0.56 1.71 1.43 1.5 Perfumes 0.23 0.29 0.26 0.38 0.86 1.0 1.5

Table 16-34. Amount and Frequency of Use of Various Cosmetic and Baby Products (continued) Average Frequency of Use Upper 90th Percentile Frequency of Use Amount of (per day) (per day) Product Type Product Pe£ Survey Type Survey Type Application (grams) Market0 Market Cosmetic Research Cosmetic Research CTFA Co. Bureau CTFA Co. Bureau Powders 2.01 0.18 0.39 --1.0 1.0 -Sachets 0.2 0.0061 0.034 --0.148 0.148 --Fragrance Lotion --0.0061 ---0.298 ----Hair Conditioners 12.4 0.4 0.40 0.27 1.0 1.0 0.86 Hair Sprays -0.25 0.55 0.32 1.0 1.0 1.0 Hair Rinses 12.7 0.064 0.18 --0.29 1.0 --Shampoos 16.4 0.82 0.59 0.48 1.0 1.0 1.0 Tonics and Dressings 2.85 0.073 0.021 --0.29 0.148 -Wave Sets 2.6 0.003h 0.040 h 0.14 ------Dentifrices --1.62 0.67 2.12 2.6 2.0 4.0 Mouthwashes --0.42 0.62 0.58 1.86 1.14 1.5 Breath Fresheners --0.052 0.43 0.46 0.14 1.0 0.57 Nail Basecoats 0.23 0.052 0.13 --*0.29 0.29 --Cuticle Softeners 0.66 0.040 0.10 -0.14; 0.29 -Nail Creams & Lotions 0.56 0.070 0.14 -0.29 0.43 --Nail Extenders --0.003 0.013 --0.148 0.148 --Nail Polish & Enamel 0.28 0.16 0.20 0.07 0.71 0.43 1.0 Nail Polish & Enamel 3.06 0.088 0.19 --o.'29 0.43 --Remover Nail Undercoats --0.049 0.12 -0.14 0.29 -Bath Soaps 2.6 1.53 0.95 --3.0 1.43 -Underarm Deodorants 0.52 1.01 0.80 1.10 1.29 1.29 2.0 Douches -0.013 0.089 0.085 0.148 0.29 0.29 Feminine Hygiene --0.021 0.084 0.05 1.0° 0.29 0.14 Deodorants Cleansing Products (cold 1.7 0.63 0.80 0.54 1.71 2.0 1.5 creams, cleansing lotions liquids & pads) Depilatories -0.0061 0.051 0.009 0.016 0.14 0.033 Face, Body & Hand Preps 3.5 0.65 --1.12 2.0 -2.14 (excluding shaving preps) Foot Powder & Sprays --0.061 0.079 --0.578 0.29 -Hormones -0.012 0.028 --0.578 0.148 --Moisturizers 0.53 0.98 0.88 0.63 2.0 1.71 1.5 Niqht Skin Care Products 1.33 0.18 0.50 -1.0 1.0 --

Table 16-34. Amount and Frequency of Use of Various Cosmetic and Baby Products (continued) Average Frequency of Use Upper 90th Percentile Frequency of Use Amount of (per day) (per day) Product Type Product Pe£ Survey Type Survey Type Application (g) Market0 Market Cosmetic Research Cosmetic Research CTFA Co. Bureau CTFA Co. Bureau Paste Masks (mud packs) 3.7 0.027 0.20 -0.14 0.43 --Skin Lighteners --0.024 ----d 0.14d --Skin Fresheners & Astringents 2.0 0.33 0.56 --1.0 1.43 -Wrinkle Smoothers (removers) 0.38 0.021 0.15 --1.0d 1.0 --Facial Gream 0.55 0.0061 ----0.0061 ----Permanent Wave 101 0.003 --0.001 0.0082 --0.005 Hair Straighteners 0.156 0.0007 ---0.005d ---Hair Dye --0.001 -0.005 0.004d -0.014 Hair Lighteners --0.0003 ---0.005d ----Hair Bleaches --0.0005 ----0.02d ---Hair Tints --0.0001 ----0.005d ----Hair Rinse (coloring) --0.0004 ----0.02d ----Shampoo (coloring) --0.0005 ----0.02d ---Hair Color Spray ----------d ----Shave Cream 1.73 ----0.082 ---0.36 a Values reported are the averages of the responses reported by the twenty companies interviewed. b (-'s) indicate no data available. The averages shown for the Market Research Bureau are not true averages -this is due to the fact that in many cases the class of most frequent users were indicated by "1 or more" also ranges were used in many cases, i.e., "10-12." The average, therefore, is underestimated slightly. The "1 or more" designation also skew the 9oth percentile figures in many instances. The 9oth percentile values may, in actuality, be somewhat higher for many products. c Average usage among users only for baby products. d Usage data reflected "entire household" use for both baby lotion and baby oil. . Fewer than 10% of individuals surveyed used these products. Value listed is lowest frequency among individuals reporting usage . In the case of wave sets, skin lighteners, and hair color spray, none of the individuals surveyed by the CTFA used this product during f the period of the study. Usage data reflected "entire household" use. g Usage data reflected total bath product usage. h None of the individuals surveyed reported using this product. Source: CTFA 1983. Table 16-35. Summary of Consumer Products Use Studies Study Study Size Approach Relevant Populati9n Comments KEY STUDIES Abt, 1992 4,997 product interviews; Direct -interviews and Adults Random digit dialing method used to select sample. 527 mailed questionnaires questionnaires Information on use of 3 products containing methyl chloride was requested. Westat, 1987a 4,920 individuals Direct -questionnaire 18+ yrs selected to be Waksberg Method (random digit dialing) used to select representative of US sample. Respondents asked to recall use in past 2 months of population 32 catagories of household products containing methyl chloride. Westat, 1987b 193 households Direct -telephone survey; 2 Adult household members Waksberg Method (random digit dialing) used to select post-survey validation efforts: 30 who do cleaning tasks in sample. Household use of cleaning products requested. reinterviewed, then another 50 household Phone survey during end of year holidays may reflect biased reeinterviewed usage data. Two validation resurveys conducted 3 months after survey. Westat, 1987c 777 households Direct -telephone survey; 1 Household members who do Waksberg Method (random digit dialing) used to select . post-survey validation effort painting tasks in household sample. Painting product use information in past 12 months conducted with 30 reinterviewed was requested. One validation resurvey conducted 3 months after survey. Tsang and Klepeis, 1996 9,386 individuals Direct -interviews and Representative of U.S. National Human Activity Patterns Survey (NHAPS). questionnaires general population Participants selected using random Dial Digit (ROD) and Computer Assisted Telephone Interviewing (CATI). 24-hour diary data, and follow-up questions; nationally representative; represent all seasons, age groups, and genders. RELEVANT STUDY CTFA, 1983 Survey 1: 47 women Survey 1: Direct -1 wk Survey 1: 16-61 yr old Interviewees asked to recall their use of cosmetics and some employees and relatives or prospective survey females baby products during a specific past time period. Surveys 1 employees Survey 2: Direct -prospective Survey 2: Customers of and 2 had small populations, but Survey 3 had large Survey 2: 1,129 cosmetics survey cosmetic manufacturer population selected to be representative of U.S. population purchasers Survey 3: Direct -9.5 months. Survey 3: Market research Survey 3: 19,035 females prospective survey company sampled female consumers nationwide Table 16A-1. Volumes Included in 1992 Simmons Study The volumes included in the Media series are as follows: M1 M2 M3 M4 M5 M6 M7 MB Publications: Total Audiences Publications: Qualitative Measurements And In-Home.Audiences Publications: Duplication Of Audiences Multi-Media Audiences: Adults Multi-Media Audiences: Males Multi-Media Audiences: Females and Mothers Business To Business Multi-Media Reach and Frequency and Television Attentiveness & Special Events The following volumes are included in the Product series: P1 P2 P3 P4 P5 P6 P7 PB pg P10 P11 P12 P13 P14 P15 P16 P17 P1B P19 P20 P21 P22 P23 P24 P25 P26 Automobiles, cycles, Trucks & Vans Automotive Products & Services Travel Banking, Investments, Insurance, Credit Cards & Contributions, Memberships & Public Activities Games & Toys, Children's & Babies' Apparel & Specialty Products *computers, Books, Discs, Records, Tapes, Stereo, Telephones, TV & Video Appliances, Garden Care, Sewing & Photography Home Furnishings & Home Improvements Sports & Leisure Restaurants, Stores & Grocery Shopping Direct Mail & Other In-Home Shopping, Yellow.Pages, Florist, Telegrams, Faxes & Greeting Cards Jewelry, Watches, Luggage, Writing Tools & Men's Apparel Women's Apparel Distilled Spirits, Mixed Drinks, Malt Beverages, Wine & Tobacco Products Coffee, Tea, Cocoa, Milk, Soft Drinks, Juices & Bottled Water Dairy Products, Desserts, Baking & Bread Products Cereals & Spreads, Rice, Pasta, Pizza, Mexican Foods, Fruits & Vegetables Soup, Meat, Fish, Poultry, Condiments & Dressings Chewing Gum, Candy, Cookies & Snacks Soap, Laundry, Paper Pro'ducts & Kitchen Wraps Household Cleaners, Room Deodorizers, Pest Controls & Pet Foods Health Care Products & Remedies Oral Hygiene Products, Skin Care, Deodorants & Drug Stores Hair Care, Shaving Products & Fragrances Women's Beauty Aids, Cosmetics & Personal Products Relative Volume of Consumotion REFERENCES FOR CHAPTER 16 Abt. (1992) Methylene chloride consumer products use survey findings. Prepared by Abt Associates, Inc. for the U.S. Consumer Product Safety Commission, Bethesda, MD. Cosmetic, Toiletry and Fragrance Association (CTFA). (1983). Summary of the results of surveys of the amount and frequency of use of cosmetic products by women. Prepared by Environ Corporation, Washington, DC for CFFA Inc., Washington, DC. Hakkinen, P.J.; Kelling, C.K.; Callender, J.C. (1991) Exposure assessment of consumer products: Human body weights and total body surface areas to use; and sources of data for specific products. Veterinary and Human Toxicology 1(33):61-65. Tsang, A.M.; Klepeis, N.E. (1996) Results tables from a detailed analysis of the National Human Activity Pattern Survey (NHAPS) response. Draft Report prepared for the U.S. Environmental Protection Agency by Lockheed Martin, Contract No. 68-W6-001, Delivery Order No. 13. U.S. EPA. (1986) Standard scenarios for estimatir:ig exposure to chemical substances during use of consumer products. Prepared by Versar, Inc. For the Office of Toxic Substances, Contract No. 68-02-3968. U.S. EPA. (1987) Methods for assessing exposure to chemical substances -Volume 7 -Methods for assessing consumer exposure to chemical substances. Washington, DC: Office of Toxic Substances. EPA Report No. 560/5-85-007. Westat. (1987a) Household solvent products -a national usage survey. Under Subcontract to Battelle Columbus Div., Washington DC. Prepared for U.S. Environmental Protection Agency, Washington, DC. Available from NTIS, Springfi.eld, .VA. PB88-132881. Westat. (1987b) National usage survey of household cleaning products. Prepared for U.S. Environmental Protection Agency, Office of Toxic Substances and Office of Pesticides and Toxic Substances, Washington, DC. Westat. (1987c) National household survey or interior painters. Prepared for U.S. Environmental Protection Agency, Office of Toxic Substances and Office of Pesticides and Toxic Substances, Washington DC. DOWNLOADABLE TABLES FOR CHAPTER 16 The following selected tables are available for download as Lotus 1-2-3 worksheets. Table 16-2. Frequency of Use for Household Solvent Products (users-only) [WK1, 6 kb] Table 16-3. Exposure Time of Use for Household Solvent Products (users-only) [WK1, 7 kb] Table 16-4. Amount of Products Used for Household Solvent Products (users-only) [WK1, 7 kb] Table 16-5. Time Exposed After Duration of Use for _Household Solvent Products (users-only) [WK1, 6 kb] Table 16-6, Frequency of Use and Amount of Product Used for Adhesive Removers [WK1, 2 kb] Table 16-8. Frequency of Use and Amount of Product Used for Spray Paint [WK1, 2 kb] Table 16-10. Frequency of Use and Amount of Product Used for Paint Removers/Strippers [WK1, 2 kb] Table 16-13. Percentile Rankings for Total Exposure Time in Performing Household Tasks [WK1, 2 kb] Table 16-14. Mean Percentile Rankings for Frequency of Performing Household Tasks [WK1, 3 kb] Table 16-15. Mean and Percentile Rankings for Exposure Time Per Event of Performing Household Tasks [WK1, 2 kb] Table 16-16. Total Exposure Time for Ten Product Groups Most Frequently Used for Household Cleaning [WK1, 2 kb] Table 16-17. Total Exposure Time of Painting Activity of Interior Painters (hours) [WK1, 1 kb] Table 16-18. Exposure Time of Interior Painting Activity/Occasion (hours) and Frequency of Occasions Spent Painting Per Year [WK1, 1 kb] Table 16-19. Amount of Paint Used by Interior Painters [WK1, 1 kb] Table 16-20. Number of Respondents Using Cologne, Perfume, Aftershave or Other Fragrances at Specified Daily Frequencies [WK1, 5 kb] Table 16-21. Number of Respondents Using Any Aerosol Spray Product for Personal Care Item Such as Deodorant or Hair Spray at Specified Daily Frequencies [WK1, 7 kb] Table 16-22. Number of Minutes Spent in Activities Working with or Being Near Freshly Applied Paints (minutes/day) [WK1, 8 kb] . Table 16-23. Number of Minutes Spent in Activities Working with or Near Household Cleaning Agents Such as Scouring Powders or Ammonia (minutes/day) [WK1, 8 kb] Table 16-24. Number of Minutes Spent in Activities (at home or elsewhere) Working with or Near Floorwax, Furniture Wax or Shoe Polish (minutes/day) [WK1, 8 kb] Table 16-25. Number of Minutes Spent in Activities Working with or Being Near Glue [WK1, 7 kb] Table 16-26. Number of Minutes Spent in Activities Working with or Near Solvents, Fumes or Strong Smelling Chemicals (minutes/day) [WK1, 8 kb] Table 16-27. Number of Minutes Spent in Activities Working with or Near Stain or Spot Removers (minutes/day) [WK1, 7 kb] Table 16-28. Number of Minutes Spent in Activities Working with or Near Gasoline or Diesel-powered Equipment, Besides Automobiles (minutes/day) [WK1, 8 kb] Table 16-29. Number of Minutes Spent Using Any Microwave Oven (minutes/day) [WK1, 7 kb] Table 16-30. Number of Respondents Using a Humidifier at Home [WK1, 5 kb] Table 16-31. Number of Respondents Indicating that Pesticides Were Applied by the .Professional at Home to Eradicate Insects, Rodents, or Other Pests at Specified Frequencies [WK1, 5 kb] Table 16-32. Number of Respondents Reporting Pesticides Applied by the Consumer at Home to Eradicate Insects, Rodents, or Other Pests at Specified Frequencies [WK1, 5 kb] Table 16-33. Number of Minutes Spent in Activities Working with or Near Pesticides, Including Bug Sprays or Bug Strips (minutes/day) [WK1, 8 kb] Volume III -Activity Factors Chapter 17 -Residential Building Characteristics 17. RESIDENTIAL BUILDING CHARACTERISTICS 17.1. INTRODUCTION 17.2. BUILDING CHARACTERISTICS 17 .2.1. Key Volu-mes of Residence Studies 17.2.2. Volumes and Surface Areas of Rooms 17.2.3. Mechanical System Configurations 17.2.4. Type of Foundation 17.3. TRANSPORT RATES 17.3.1. Background 17.3.2. Air Exchange Rates 17.3.3. Infiltration Models 17.3.4. Deposition and Filtration 17.3.5. lnterzonal Airflows 17.3.6. Water Uses 17.3.7. House Dust and Soil 17.4. SOURCES 17.4.1. Source Descriptions for Airborne .Contaminants 17.4.2. Source Descriptions for Waterborne Contaminants 17.4.3. Soil and House Dust Sources 17 .5. ADVANCED CONCEPTS 17 .5.1. Uniform Mixing Assumption 17.5.2. _ Reversible Sinks 17.6 RECOMMENDATIONS REFERENCES FOR CHAPTER 17 Table 17-1. Summary of Residential Volume Distributions Table 17-2. Average Estimated Volumes of U.S. Residences, by Housing Type and Ownership Table 17-3. Residential Volumes in Relation to Household Size and Year of Construction Table 17-4. Dimensional Quantities for Residential Rooms Table 17"."5. Examples of Products and Materials Associated with Floor and Wall Surfaces in Residences Table 17-£;). Percent of Residences with Basement, by Census Region and EPA Region Table 17-7. Percent of Residences with Certain Foundation Types by Census Region Table 17-8. States Associated with EPA Regions and Census Regions Table 17-9. Summary of Major Projects Providing Air Exchange Measurements in the PFT Database Table 17-10. Summary Statistics for Air Exchange Rates (air changes per hour-ACH), by Region Table 17-11. Distributions of Residential Air Exchange Rates by Climate Region and Season Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 17 -Residential Building Characteristics Table 17-12. Deposition Rates for Indoor Particles Table 17.,.13. Particle Deposition During Normal Activities Table 17-14. In-house Water Use Rates (gcd), by Study and Type of Use Table 17-15. Summary of Selected HUD and Power Authority Water Use Studies Table 17-16. Showering and Bathing Water Use-Characteristics Table 17-17. Showering Characteristics for Various Types of Shower Heads Table 17-18. Toilet Water Use Characteristics Table 17-19. Toilet Frequency Use Characteristics Table 17-20. Dishwasher Frequency Use Characteristics Table 17-21. Dishwasher Water Use Characteristics Table 17-22. Clothes Washer Frequency Use Characteristics Table 17-23. Clothes Washer Water Use Characteristics Table 17-24. Range of Water Uses for Clothes Washers Table 17-25. Total Dust Loading for Carpeted Areas Table 17-26. Particle Deposition and Resuspension During Normal Activities Table 17-27. Dust Mass Loading After One Week Without Vacuum Cleaning Table 17-28. Simplified Source Descriptions for Airborne Contaminants Table 17-29. Volume of Residence Surveys Table 17-30. Air Exchange Rates Surveys Table 17-31. Recommendations-Residential Parameters Table 17-32. Confidence in House Volume Recommendations Table 17-33. Confidence in Ai,r Exchange Rate Recommendations Figure 17-1. Elements of Residential Exposure Figure 17-2. *Cumulative Frequency Distributions for Residential Volumes from the PFT Data Base and the U.S. DOE's RECs Figure 17-3. Configuration for Residential Forced-air Systems Figure 17-A. Idealized Patterns of Particle Deposition Indoors Figure 17-5. Air Flows for Multiple-zone Systems Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 17 -Residential Building Characteristics 17. RESIDENTIAL BUILDING CHARACTERISTICS 17 .1. INTRODUCTION Unlike previous chapters in this handbook which focus on human behavior or characteristics that affect exposure, this chapter focuses *on residence characteristics. Assessment of exposure in residential settings requires information on the availability of the chemical(s) of concern at the point of exposure, characteristics of the structure and microenvironment that affect exposure, and human presence within the residence. The purpose of this chapter is to provide data that are available on residence characteristics that affect exposure in an indoor environment. Source-receptor relationships in* residential exposure scenarios can be complex due to interactions among sources, and transport/transformation processes that result from chemical-specific and building-specific factors. Figure 17-1 illustrates the complex f?ctors that must be considered when conducting exposure assessments in a residential setting. In addition to sources within the building, chemicals of concern may enter the indoor environment from outdoor air, soil, gas, water supply, tracked-in soil, and industrial work clothes worn by the residents. Indoor concentrations are affected by loss mechanisms, also illustrated in Figure 17-1, involving chemical reactions, deposition to and re-emission from surfaces, and transport out of the building. Particle-bouFld chemicals can enter indoor air through resuspension. Indoor air concentrations of gas-phase organic chemicals are affected by the presence of reversible sinks .formed by a wide range of indoor materials. In addition, the activity of human receptors greatly affects their exposure as they move from room to room, entering and leaving the exposure scene. Inhalation exposure assessments in residential and other indoor settings are modeled by considering the building as an assemblage of one or more well-mixed zones. A zone is defined as one room, a group of interconnected rooms, or an entire building. This macroscopic level, well-mixed perspective forms the basis for interpretation of measurement data as well as simulation of hypothetical scenarios. Exposure assessment models on a macroscopic level incorporate important physical factors and processes. These well-mixed, macroscopic models have been used to perform indoor air quality simulations (Axley, 1989), as well as indoor air exposure assessments (McKone, 1989; Ryan, 1991 ). Nazzaroff and Cass (1986) and Wilkes et al. (1992) have used intensive computer programs featuring finite difference or finite element numerical techniques to model mass balance. A simplified approach using desk top spreadsheet programs has been used by Jennings et al. (1985). In order to model mass balance of indoor contaminants, the indoor air volume is represented as a network of interconnected zones. Because conditions in a given zone *are determined by with other connecting zones, the multizone model is stated Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 17 -Residential Building Characteristics as a system of simultaneous equations. The mathematical framework for modeling indoor air has been reviewed by Sinden (1978) and Sandberg (1984). Indoor air quality models typically are not software products that can be purchased as "off-the-shelf' items. Most existing software models are research tools that have been developed for specific purposes and are being continuously refined by researchers. Leading examples of.indoor air models implemented as software products are as follows:
CONTAM --developed at the National Institute of Standards and Technology * (NIST) with support from U.S. EPA and the U.S. Department of Energy (DOE) (Axley, 1988; Grot, 1991; Walton, 1993);

EXPOSURE --developed at the Indoor Air Branch of U.S. EPA Air and Energy Engineering Research Lab.oratory (EPA/AEERL) (Sparks, 1988, 1991 );

MCCEM --the Multi-Chamber Consumer Exposure Model developed for U.S EPA Office of Pollution Prevention and Toxics (EPA/OPPT) (GEOMET, 1989; Koontz and Nagda, 1991 ); and *

THERdbASE --the Total Human Exposure Relational Data Base and Advanced Simulation Environment software developed by researchers at the Hcirry Reid Center for Environmental Studies at University Nevada, Las Vegas (UNLV) (Pandian et al., 1993). Section 17 .2 of this chapter summarizes existing data on building characteristics (volumes, surface areas, mechanical sy!:?tems, and types of foundations). Section 17.3 summarizes transport phenomena that affect chemical transport (airflow, chemical-specific deposition and filtration, and effects of water supply and soil tracking). Section 17.4 provides information on various types of indoor sources associated with *airborne exposure, waterborne sources, and soil/house dust sources. Section 17.5 summarizes advanced concepts. 17.2. BUILDING CHARACTERISTICS 17 .2.1. Key Volumes of Residence Studies Versar (1990) -Database on Perfluorocarbon Tracer (PFT) Ventilation Measurements -A database of time-averaged air exchange and interzonal airflow measurements in more than 4,000 residences has been compiled by Versar (1990) to allow researchers to access these data (see Section 17.3.2). These data were collected between 1982 and 1987. The residences that appear in this database are not a random sample of U.S. homes; however, Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 17 -Residential Building Characteristics they do represent a compilation of homes visited in about 100 different field studies, some of which involved random sampling. In each study, the house volumes were directly . measured or estimated. The collective homes visited in these field projects are not geographically balanced; a large fraction of these homes are located in southern California. Statistical weighting techniques were applied in developing estimates of nationwide distributions (see Section 17.3.2) to compensate for the geographic imbalance. U.S. DOE (1995) -Housing Characteristics 1993, Residential Energy Consumption Survey (RECS) -Measurement surveys have not been. conducted to directly characterize the range and distribution of volumes for a random sample of U.S. residences. Related data, however, are regularly collected through the U.S. DOE's RECS (U.S. DOE, 1995). In addition to collecting information on energy use, this triennial survey collects data on. housing characteristics including direct measurements of total and heated floor space for buildings visited by survey specialists. For the most recent survey (1993), a multistage probability sample of over 7,000 residences was surveyed, representing 96 million residences nationwide. The survey response rate was 81.2 percent. Volumes were estimated from the RECS measurements by multiplying the heated floor space area by an assumed ceiling height of 8 feet, recognizing that this assumed height may not apply universally to all homes.

Results for residential volume distributions from the RECS (Thompson, 1995) are presented in Table 17-1. Estimated parameters of residential volume distributions (in cubic meters) from the PFT database (Versar, 1990) are also summarized in Table 17-1, for comparison to the RECS data. The arithmetic means from the two. sources are identical (369 cubic meters). The medians (50th percentiles) are very similar: 310 cubic meters for the RECS data, and 321 cubic meters for the PFT database. Cumulative frequency distributions from the two sources (Figure 17-2) also are quite similar, especially between the 50th and 75th percentiles. The RECS also provides relationships between average residential floor areas and factors such as housing type, ownership, household size and structure age. The predominant housing type--single-family detached homes--also has the largest average volume (Table 17-2). Multifamily units and mobile homes have volumes averaging about half that of single-family detached homes, with single-family attached homes about halfway between these extremes. Within each category of housing type, owner-occupied

residences average about 50 percent greater volume than rental units. The relationship of residential volume to household size (Table 17-3) is of particular interest for purposes of exposure assessment. For example, one-person households would not include children, and the data in the table indicate that multi-person households occupy residences averaging about 50 percent greater volume than residencE?s occupied by person households. Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 17 :. Residential Building Characteristics Data on year of construction indicate a slight decrease in residential volumes between 1950 and 1984, followed by an increasing trend over the next decade. A ceiling height of 8 feet was assumed in estimating the average volumes, whereas there may have been some time-related trends in ceiling height. Murray (1996) -Analysis of RECS and PFT Databases. Using a database from the 1993 RECS and an assumed ceiling height of 8 feet, Murray (1996) estimated a mean residential volume of 38.2 m3 using RECS estimates of heated floor space. This estimate is slightly different from the mean of 369 m3 given in Table 17-1. Murray's (1996) sensitivity analysis indicated that when a fixed ceiling height of 8.feet was replaced with a randomly varying height with a mean of 8 feet, there was little effect on the sta.ndard deviation of the estimated distribution. From a separate analysis of the PFT database, based on 1,751 individual household measure-ments, Murray (1996) estimated an average volume of 369 m3, the same as previously given in Table 17-1. In performing this analysis, the author carefully reviewed the PFT database in an effort to use each residence only once, for those residences thought to have multiple PFT measurements. 17 .2.2. Volumes and Surface Areas of Rooms Room Volumes -Volumes of individual rooms are dependent on the building size and configuration, but summary data are not readily available. The exposure assessor is advised to define specific rooms, or assemplies of rooms, that best fit the scenario of interest. Most models for predicting indoor-air concentrations specify airflows in cubic meters per hour and, correspondingly, express volumes in cubic meters. A measurement in cubic feet can be converted to cubic meters by multiplying the value in cubic feet by 0.0283 m3/ft3. For example, a bedroom that is 9 feet wide by 12 feet long by 8 feet high has a volume of 864 cubic feet or 24.5 cubic meters. Similarly, a living room with dimensions of 12 feet wide by 20 feet long by 8 feet high has a volume of 1920 cubic feet or 54.3 cubic meters, and a bathroom with dimensions of 5 feet by 12 feet by 8 feet has a vofume of 480 cubic feet or 13.6 cubic meters. Murray (1996) analyzed the distribution of selected residential zones (i.e., a series of conn.ected rooms) using the PFT database. The author analyzed the "kitchen zone" and the "bedroom zone" for houses in the Los.Angeles area that were labeled in this manner

by field researchers, and "basement," "first floor," and "second floor" zones for houses outside of Los Angeles for which the researchers labeled individual floors as zones. The kitchen zone contained the kitchen in addition to any of the following associated spaces: utility room, dining room, living room and family room. The bedroom zone contained all the bedrooms plus any bathrooms and hallways associated with the bedrooms. The following summary statistics (mean+/- standard deviation) were reported by Murray (1996) for the volumes of the zones described above: 199 +/- 115 m3 for the kitchen zone, 128 +/- Exposure Factors Handbook August 1997 Volume III-Activity Factors Chapter 17 -Residential Building Characteristics 67 m3 for the bedroom zone, 205 +/- 64 m3 for the basement, 233 +/- 72 m3 for the first floor, and 233 +/- 111 m3 for the second floor. Surface Areas -The surface areas of floors are commonly considered in relation to the room or house volume, and their relative loadings are expressed as a surface volume, or loading ratio. Table 17-4 provides the basis for calculating loading ratios for typical-sized rooms. Constant features in the examples are: a room width of 12 feet and a ceiling height of 8 feet (typical for residential buildings), or a ceiling height 12 feet (typical for commercial buildings). The loading ratios for the 8-foot ceiling height range from 0.98 m2m-3 to 2.18 m2m-3 for wall area and from 0.36 m2m-3 to 0.44 m2m-3 for floor area. In comparison, ASTM Standard E 1333 (ASTM, 1990), for large-chamber testing of formaldehyde levels from wood products, specifies the following loading ratios: (1) 0.95 m2m-3 for testing plywood (assumes plywood or paneling on all four walls of a typical size room); and (2) 0.43 m2m-3 for testing particleboard (assumes that particleboard decking or underlayment would be used as a substrate for the entire floor of a structure). Products and Materials -Table 17-5 presents examples of assumed amounts of selected products and materials used in constructing or finishing residential surfaces (Tucker, 1991 ). Products used for floor surfaces include adhesive, varnish and wood stain; and materials used for walls include paneling, painted gypsum board, and wallpaper. Particleboard and chipboard are commonly used for interior furnishings such as shelves or cabinets, but could also be used for decking or underlayment. It should be noted that numbers presented in Table 17-5 for surface area are based on typical values for residences, and they are presented as examples. In contrast to the concept of loading ratios presented above (as a surface area), the numbers in Table 17-5 also are not scaled to any particular residential volume. In some cases, it may be preferable for the exposure assessor to use professional judgment in combination with the loading ratios given above. For example, if the exposure scenario involves residential carpeting, either as an indoor source or as an indoor sink, then the ASTM loading ratio of 0.43 m2m-3 for floor materials could be multiplied by an assumed residential volume and assumed fractional coverage of carpeting to derive an estimate of the surface area. More specifically, a residence with a volume of 300 m3, a loading ratio of 0.43 m2m-3 and coverage of 80% would have 103 m2 of carpeting. The estimates discussed here relate to macroscopic surfaces; the true surface area for carpeting, for example, would be considerably larger because of the nature of its fibrous material. Furnishings -Information on the relative abundance of specific types of indoor furnishings, such as draperies or upholstered furniture, was not readily available. The exposure assessor is advised to rely on common sense and *professional judgment. For example, the number of beds in a residence is usually related to household size, and Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapt.er 17 -Residential Building Characteristics information has been provided (Table 17-3) on average house volume in relation to household size. 17 .2.3. Mechanical System Configurations Mechanical systems for air movement in residences can affect the migration and mixing of pollutants released indoors and the rate of pollutant removal. Three types of mechanical systems are: (1) systems associated with heating and air conditioning (HAG); (2) systems whose primary function is providing localized exhaust; and (3) systems intended to increase the overall air exchange rate of the residence. Portable space heaters intended to serve a single room, or a series of adjacent rooms, may or may not be equipped with blowers that promote air movement and mixing. Without a blower, these heaters still have the ability to induce mixing through convective heat transfer. If the heater is a source of combustion pollutants, as with unvented gas or kerosene space heaters, then the combination of convective heat transfer and thermal buoyancy of combustion products will result in fairly rapid dispersal of such pollutants. The pollutants will disperse throughout the floor where the heater is located and to floors above the heater, but will not disperse to floors below. Central forced-air HAG systems are common in many residences. Such systems, through a network of supply/return ducts and registers, can achieve fairly complete mixing within 20 to 30 minutes (Koontz et al., 1988). The air handler for such systems is commonly equipped with a filter (see Figure 17-3) that can remove particle-phase contaminants. Further removal of particles, via deposition on various room surfaces (see Section 17.3.2), is acccimplished through increased air movement when the air handler is operating. Figure 17-3 also distinguishes forced-air HAG systems by the return layout in relation to supply registers. The return layout shown in the upper portion of the figure is the type most commonly found in residential settings. On any floor of the residence, it is typical to find one or more supply registers to individual rooms, with one or two centralized return registers. With this layout, supply/return imbalances can often occur in individual rooms, particularly if the interior doors to rooms are closed. In comparison, the supply/return layout shown in the lower portion of the figure by design tends to achieve a balance in individual rooms or zones. Airflow imbalances can also be caused by inadvertent duct

leakage to unconditioned spaces such as attics, basements, and crawl spaces. Such imbalances usually depressurize the h<?use, thereby increasing the likelihood of contaminant entry via soil-gas transport or through spillage of combustion products from vented fossil-fuel appliances such as fireplaces and gas/oil furnaces. Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 17 -Residential Building Characteristics Mechanical devices such as kitchen fans, bathroom fans, and clothes dryers are intended primarily to provide localized removal of unwanted heat, moisture, or odors. Operation of these devices tends to increase the air exchange rate between the indoors and outdoors.* Because local exhaust devices are designed to be near certain indoor sources, their effective removal rate for locally generated pollutants is greater than would be expected from the dilution effect .of increased air exchange. Operation of these devices also tends to depressurize the house, because replacement air usually is not provided to balance the exhausted air. An alternative approach to pollutant removal is one which relies on an increase in air exchange to dilute pollutants generated indoors. This approach can be accomplished using heat recovery ventilators (HRVs) or energy recovery ventilators (ERVs). Both types of ventilators are designed to provide balanced supply and exhaust airflows and are intended to recover most of the energy that normally is lost when additional outdoor air is introduced. Although ventilators can provide for more rapid dilution of internally generated pollutants, they also increase the rate at yvhich outdoor pollutants are brought into the house. A distinguishing feature of the two types is that ERVs provide for recovery of latent . . heat (moisture) in addition to sensible heat. Moreover, ERVs typically recover latent heat using a moisture-transfer device such as a desiccant wheel. It has been observed in some studies that the transfer of moisture between outbound and inbound air streams can result in some re-entrainment of indoor pollutants that otherwise would have been exhausted from the house (Andersson et al., 1993). Inadvertent air communication between the . supply and exhaust air streams can have a similar effect. Studies quantifying the effect of mechanical devices on air exchange using tracer-gas measurements are uncommon and typically provide only anecdotal data. The common approach is for the expected increment in the air exchange rate to be estimated from the. rated airflow capacity of the device(s). For example, if a device with a rated capacity of 100 cubic feet per minute (cfm), or 170 cubic meters per hour, is operated continuously in a house with a volume of 400 cubic meters, then the expected increment in the air exchange rate of the house would be 170 m3h-1I400 m3, or approximately 0.4 air changes per hour. 17.2.4. Type of Foundation The type of foundation of a residence is of interest in residential exposure assessment. It provides some indication of the number of stories and house configuration, and provides an indication of the relative potential for soil-gas transport. For example, such transport can occur readily in homes with enclosed crawl spaces. Homes with basements provide some resistance, but still have numerous pathways for soil-gas entry. Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 17 -Residential Building Characteristics By comparison, homes with crawl spaces open to the outside significant opportunities for dilution of soil gases prior to transport into the house. Lucas et al. (1992) -National Residential Radon Survey -The National Resdental Radon Survey, sponsored by the U.S. EPA, was conducted by Lucas et al. (1992) in abo.ut 5,700 households nationwide .. In addition to radon measurements, information on a number of housing characteristics was collected, including whether each house had a basement. The estimated percentage (45.2 percent) of homes in the U.S. having basements (Table 17-6) from this survey is the same as found by the RECS (Table 17-7). The National Residential Radon Survey provides data for more refined geographical areas, with a breakdown by the 10 EPA Regions. The New England region (i.e., EPA Region 1 ), which includes Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont, had the highest prevalence of basements (93 percent). The lowest prevalence (4 percent) was for the South Central region (i.e., EPA Region 6), which includes Arkansas, Louisiana, New Mexico, Oklahoma, and Texas. Table 17-8 presents the States associated with each Census Region and EPA Region. U.S. DOE (1995) -Housing Characteristics 1993 -Residential Energy Consumption Survey (RECS) -The most recent RECS (described in Section 17.2.1) was administered in 1993 to over 7,000 households (U.S. DOE, 1995). The type of information requested by the survey questionnaire included the type of -foundation for the residence (i.e., basement, enclosed crawl space, crawl space open to outside or concrete slab). This information was not obtained for multifamily structures with five or more dwelling units or for mobile homes. Table 17-7 presents estimates from the survey of the percentage of residences with each foundation type, by census region, and for the entire U.S. The percentages* can add to more than 100 percent because some residences have more than one type of foundation; for example, most split-level structures have a partial basement combined with some cravylspace that typically is enclosed. The data in Table 17-7 indicate *that close to half (45 percent) of residences nationwide have a basement, and that fewer than 10 percent have a crawl space that is open to outside. It also shows that a large fraction of homes have concrete slabs (31 percent). There are also variations by census region. For example, nearly 80 percent of the residences in the Northeast and Midwest regions have basements. In the South and West regions, the predominant foundation types are concrete slabs and enclosed crawl spaces. Table 17-8 illustrates the four Census Regions. Exposure Factors Handbook August 1997 Volume 111-Activity Factors Chapter 17 -Residential Building Characteristics 17 .3. TRANSPORT RATES 17 .3.1. Background ,Major air transport pathways for airborne substances in residences include the following:

Air exchange -Air leakage through windows, doorways, intakes and exhausts, and "adventitious openings" (i.e., cracks and seams) that combine to form the leakage configuration of the building envelope plus natural and mechanical ventilation;

lnterzonal airflows -Transport through* doorways, ductwork, and service chaseways that rooms or zones within a building; and

Local circulation -Convective and advective air circulation and mixing within a room or within a zone. The distribution of airflows across the building envelope that contribute to air exchange and the interzonal airflows along interior flowpaths is determined by the interior pressure distribution. The forces causing the airflows are temperature differences, the actions of wind, and mechanical ventilation systems. Basic concepts have been reviewed by ASHRAE (1993). Indoor-outdoor and room-to-room temperature differences create density differences that help determine basic patterns of air motion. During the heating season, Warmer indoor air tends to rise to exit the building at upper levels by stack action. Exiting air is replaced at lower levels by an influx of colder outdoor air. During the cooling season, this pattern is reversed: stack forces during the cooling season are generally not as strong as in the heating season because the indoor-outdoor temperature differences

are not pronounced. In examining a data base of air leakage measurements, Sherman and Dickerhoff (1996) observed that houses built prior to 1980 showed a clear increase in leakage with increasing age and were leakier, on average, than newer houses. They further observed that the* post-1980 houses did not show any trend in leakiness with age. The position of the neutral pressure level (i.e., the point where indoor-outdoor pressures are equal) depends on the leakage configuration of the building envelope. The stack effect arising from indoor-outdoor temperature differences is also influenced by the partitioning of the building interior. When there is free communication between floors or stories, the building behaves as a single volume affected by a generally rising current . the heating season and a generally falling current during the cooling season. When Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 17 -Residential Building Characteristics vertical communication is restricted, each level essentially becomes an independent zone. As the wind flows past a building, regions of positive and negative pressure (relative to indoors) are created within the building; positive pressures induce an influx of air, whereas negative pressures induce an outflow. Wind effects and stack effects combine to determine a net inflow or outflow.

The final element of indoor transport involves the actions of mechanical ventilation systems that circulate indoor air through the use of fans. Mechanical ventilation systems may be connected to heating/cooling systems that, depending on the type of building, recirculate thermally treated indoor air or a mixture of fresh air and recirculated air. Mechanical systems also may be solely dedicated to exhausting air from a designated area, as with some kitchen range hoods and bath exhausts, or to recirculating air in designated areas as with a room fan. Local air circulation also is influenced by the movement of people and the operation of local heat sources. 17.3.2. Air Exchange Rates Air exchange is the balanced flow into and out of a building, and is composed of three processes: (1) infiltration -air leakage through random cracks, interstices, and other unintentional openings in the building envelope; (2) natural ventilation -airflows through open windows, doors, and other designed openings in the building envelope; and (3) forced or mechanical ventilation -controlled air movement driven by fans. For nearly all indoor exposure scenarios, air exchange is treated as the principal means of diluting indoor concentrations. The* air exchange rate is generally expressed in terms of air changes per hour (ACH, with units of h-1 ), the ratio of the airflow (m3 h-1) to the volume (m3). No measurement surveys have been conducted to directly evaluate the range and distribution of residential air exchange rates. Although a significant number of air exchange measurements have been carried out over the years, there has been a diversity of protocols and study objectives. Since the early 1980s, however, an . inexpensive perfluorocarbon tracer (PFT) technique has been used to measure time-averaged air exchange and interzonal airflows in thousands of occupied residences using essentially similar protocols (Dietz et al., 1986). The PFT technique utilizes miniature permeation tubes as tracer emitters and passive samplers to collect the tracers. The passive samplers are returned to the laboratory for analysis by gas chromatography. These measurement results have been compiled to allow various researchers to access the data (Versar, 1990). Nazaroff et al. _(1988) -Prior to the Koontz and Rector (1995) study, Nazaroff et al. (1988) aggregated the data from two studies conducted earlier using tracer-gas decay. Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 17 -Residential Building Characteristics At the time these studies were conducted, they were the largest U.S. studies to include air exchange measurements. The first (Grot and Clark, 1981) was conducted in 255 dwellings occupied by low-income families in 14 different cities. The geometric mean +/- standard deviation for the air exchange measurements in these homes, with a median house age of 45 years, was 0.90 +/- 2.13 ACH. The second study (Grimsrud et al., 1983) involved 312 newer residences, with a median age of less than 10 years. Based on measurements taken during the heating season, the .geometric mean +/- standard deviation for these homes was 0.53 +/- 1.71 ACH. Based on an aggregation of the two distributions with proportional weighting by the respective number of houses studied, Nazaroff et al. (1988) developed an overall distribution with a geometric mean of 0.68 ACH and a geometric standard deviation of 2.01. Versar (1990) -Database of PFT Ventilation Measurements -The residences included in the PFT database do not constitute a random sample across the United States. They represent a compilation of homes visited in the course of about 100 separate research projects by various organizations, some of which involved random sampling and some of which involved judgmental or fortuitous sampling. The larger projects in the PFT database are summarized in Table 17-9; in terms of the number of measurements (samples), states where, and months when, samples were taken, and summary statistics for their respective distributions of measured air exchange rates. For selected projects (LBL, RTI, SOCAL), multiple measurements were taken for the same house, usually during different seasons. A large majority of the measurements are from the SOCAL project that was conducted in Southern California. The means of the respective studies generally range from 0.2 to 1.0 ACH, with .the exception of two California projects--RTl2 and SOCAL2. Both projects involved measurements in Southern California during a time of year (July) wh.en windows would likely be opened by many occupants. Koontz and Rector {1995) -Estimation of Distributions for Residential Air Exchange Rates -In analyzing the composite data from various projects (2,971 measurements), Koontz and Rector (1995) assigned weights to the results from each state to compensate for the geographic imbalance in locations where PFT measurements were taken. The results were weighted in .such a way that the resultant number of cases would represent each state in proportion to its share of occupied housing units, as determinea from the 1990 U.S. Census of Population and Housing. Summary statistics from the Koontz and Rector (1995) analysis are shown in Table 17-10, for the country as a whole and by census regions. Based on the statistics for all regions combined, the authors suggested that a 10th percentile value of 0.18 ACH would be appropriate as a conservative estimator for air exchange in residential settings, and that the 50th percentile value of 0.45 ACH would be appropriate as a typical air exchange rate. In applying conservative or typical values of air exchange rates, it is important to realize Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 17:.. Residential Building Characteristics the limitations of the u*nderlying data base. Although the estimates are based on thousands of measurements, the residences represented in the database are not a random sample of the United States housing stock. The sample population is not balanced in terms of geography or time of year. Statistical techniques were applied to compensate for some of these imbalances. In addition, PFT measurements of air exchange rates assume uniform mixing of the tracer within the building. This is not always so easily achieved. Furthermore, the degree of mixing can vary from day to day and house to house because of the nature of the factors* controlling mixing (e:g., convective air monitoring driven by weather, and type and operation of the heating system). The relative placement of the PFT source and the sampler can also cause variability and uncertainty. It should be noted that sampling is typically done in a single location in a house which may not represent the average from that house. In addition, very high and very low values of air exchange rates based on PFT measurements have greater uncertainties than those in the middle of the distribution. Despite such limitations, the estimates in Table 17-10 are believed to represent the best available information on the distribution of air exchange rates across United States residences throughout the year. Murray and Burmaster (1995) -Residential Air Exchange Rates in the United States: Empirical and Estimated Parametric Distributions by Season and Climatic Region -Murray and Burmaster (1995) analyzed the PFT database using-2,844 measurements (essentially the same cases as analyzed by Koontz and Rector (1995), but without the compensating weights). These authors summarized distributions for subsets of the data defined by climate region and season. The coldest region was defined as having 7,000 or more heating degree days, the colder region as 5,500-6,999 degree days, the warmer region as 2,500-5,499 degree days, and the warmest region as fewer than 2,500 degree days. The months of December, January and February were defined as winter, March, April and May were defined as spring, and so on. The results of Murray and Burmaster (1995) are summarized in Table 17-11. Neglecting the summer results in* the colder regions which have only a few observations, the results indicate that the highest air exchange rates occur in the warmest region during the summer. As noted earlier (Section 17 .32), many

of the me*asurements in the warmer climate region were from field studies conducted in Southern California during a time of year (July) when windows would tend to be open in that area. Data for this region in particular should be used with caution since other areas within this region tend to have very hot summers and residences .use air conditioners, resulting in lower air exchange rates. The lowest rates generally occur in the colder regions during the fall (Table 17-11 ). 17.3.3. Infiltration Models A variety of mathematical models exist for prediction of air infiltration rates in buildings. A number of these models have been reviewed, for example, by Exposure Factors Handbook August 1997

Volume III -Activity Factors ** Chapter 17 -Residential Building Characteristics Liddament and Allen (1983), and by Persily and Linteris (1984). Basic principles are concisely summarized in the ASHRAE Handbook of Fundamentals (ASHRAE, 1993). These models have a similar theoretical basis; all address indoor-outdoor pressure differences that are maintained by the actions of wind and stack (temperature difference) effects. The models generally incorporate a network of airflows where nodes representing regions of different pressure are interconnected by leakage paths. Individual models differ

in details such as the number of nodes they can treat or the specifics of leakage paths (e.g., individual components such as cracks around doors or windows versus a combination of components such as an entire section of a building). Such models are not easily applied by exposure assessors, however, because the required inputs (e.g., inferred leakage areas, crack lengths) for the model are not easy to gather. Another approach for estimating air infiltration rates is developing empirical models. Such models generally rely on collection of infiltration measurements in a specific building under a variety of weather conditions. The relationship between the infiltration rate and weather conditions can then be estimated through regression analysis, and is usually stated in the following form:

A ' a%b IT; & T 0 I% cU n (Eqn.17-1) where: A = air infiltration rate {h-1) T1 =. indoor temperature ( ° C) T0 * = outdoor temperature (°C) U = windspeed (ms-1) n is an exponent with a value typically between 1 and 2 a, b and c are parameters to be estimated Relatively good predictive accuracy usually can be obtained for individual buildings through this approach. However, exposure assessors often do not have the information resources required to develop parameter estimates for making such predictions. A reasonable compromise between the theoretical and empirical approaches has been developed in the model specified by Dietz et al. (1986). The model, drawn from correlation analysis of environmental measurements and air infiltration data, is formulated as follows: A ' L ( 0.006LlT % U 1*5} (Eqn. 17-2) where: A = L = c = LlT u = average air changes per hour or infiltration rate, h-1 generalized house leakiness factor (1 < L < 5) terrain sheltering factor (1 < C < 10) = indoor-outdoor temperature difference (C0) windspeed (ms-1) Exposure Factors Handbook August 1997 Volume Ill -Activity Factors Chapter 17 -Residential Building Characteristics The value of L is greater as house leakiness increases and the value of C is greater as terrain sheltering (reflects shielding of nearby wind barrier) increases. Although the above model has not been extensively validated, it has intuitive appeal and it is possible for the user to develop reasonable estimates for L and C with limited guidance. Historical data from various U.S. airports are available for estimation of the temperature and windspeed parameters. As an example application, consider a house that has central values of 3 and 5 for L and C, respectively. Under conditions where the indoor temperature is 20 °C (68 °F), the outdoor temperature is 0 °C (32 ° F) and the windspeed is 5 ms-1, the predicted infiltration rate for that house would be 3 (0.006 x 20 + 0.03/5 x 51.5), or 0.56 air changes per hour. This prediction applies under the condition that exterior doors and windows are closed, and does not include the contributions, if any, from mechanical systeins (see Section 17.2.3). Occupant behavior, such as opening* windows, can, of course, overwhelm the idealized effects of temperature and wind speed. 17.3.4. and Filtration Deposition refers to the removal of airborne substances to available surfaces that occurs as a result of gravitational settling and diffusion, as well as electrophoresis and thermophoresis. Filtration is driven by similar processes, but is confined to material through which air passes. Filtration is usually a matter of design, whereas deposition is a matter of fact. 17.3.4.1. Deposition The deposition of particulate matter and reactive gas-phase pollutants to indoor surfaces is often stated in terms of a characteristic deposition velocity (m h-1) allied to the surface-to-volume ratio (m2 m-3) of the building or room interior, forming a first order loss rate (h-1) similar to that of air exchange. Theoretical considerations specific to indoor . environments have been summarized in comprehensive reviews by Nazaroff and Cass (1989) and.Nazaroff et al. (1993). For airborne particles, deposition rates depend on aerosol properties (size, shape, density) as well as room factors (thermal gradients, turbulence, surface geometry). The motions of larger particles are dominated by gravitational settling; the motions of smaller particles are subject to convection and diffusion. Consequently, larger particles tend to accumulate more rapidly on floors and up-facing surfaces while smaller particles may accumulate on surfaces facing in any direction. Figure 17-4 illustrates the general trend for particle deposition across the size range of general concern for inhalation exposure (<10 µm). The current thought is that theoretical calculations of deposition rates are likely to provide unsatisfactory results due to knowledge gaps relating to near-surface air motions and other sources of inhomogeneity (Nazaroff et al., 1993). Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 17 -Residential Building Characteristics Wallace (1996} -Indoor Particles: A Review-In a major review of indoor particles, Wallace (1996) cited overall particle deposition rates for respirable (PM2.5), inhalable (PM10), and coarse (difference between PM10 and PM2.5) size fractions determined from EPA's PTEAM study. These values, listed in Table 17-12, were derived from measurements conducted in nearly 200 residences. Thatcher and Layton (1995) -Deposition, Resuspension, and Penetration of Particles Within a Residence -Thatcher and Layton (1995) evaluated removal rates for indoor particles in four size ranges (1-5, 5-10, 10-25, and >25 µm) in. a study of one house occupied by a family of four. These values are listed in Table 17-13. In a subsequent evaluation of data collected in 100 Dutch residences, Layton and Thatcher ( 1995) estimated settling velocities of 2.7 m h-1 for lead-bearing particles captured in total suspended particulate matter (TSP) samples. 17.3.4.2. Filtration A variety of air cleaning techniques have been applied to residential settings. Basic prtnciples related to residential-scale air cleaning technologies have been summarized in conjunction with reporting early test results (Offerman et al., 1984 ). General engineering principles are summarized in ASHRAE (1988). In addition to fibrous filters integrated into

central heating and air conditioning systems, extended surface filters and High Efficiency Particle Arrest (HEPA) filters as well as electrostatic systems are available to increase removal efficiency. Free-standing air cleaners (portable and/or console) are also being used. Product-by-product test results reported by Hanley et qi. (1994); Shaughnessy et al. (1994); and Offerman et al. (1984) exhibit considerable variability across systems, ranging from ineffectual ( < 1 % efficiency) to nearly complete removal. 17.3.5. lnterzonal Airflows Residential structures consist of a number of rooms that may be connected horizontally, vertically, or both horizontally and vertically. Before considering residential structures as a detailed network of rooms, it is convenient to divide them into one or more zones. At a minimum, each floor is typically defined as a separate zone. For indoor air exposure assessments, further divisions are sometimes made within a floor, depending on (1) locations of specific contaminant sources and (2) the presumed degree of air -communication among areas with and without sources. Defining the airflow balance for a multiple-zone exposure scenario rapidly increases the information requirements as rooms or zones are added. As shown in Figure 17-5, a single-zone system (considering the entire building as a single well-mixed volume) requires only two airflows to define air exchange. Further, because air exchange is Exposure Factors. Handbook August 1997 Volume III -Activity Factors Chapter 17 -Residential Building Characteristics balanced flow (air does not "pile up" in the building, nor is a vacuum formed), only one number (the air exchange rate) is needed. With two zones, six airflows are needed to accommodate interzonal airflows plus air exchange; with three zones, twelve airflows are required. In some cases, the complexity can be reduced using judicious (if hot convenient) assumptions. lhterzonal airflows connecting nonadjacent rooms can be set to zero, for example, if flow pathways do not exist. Symmetry also can be applied to the system by assuming that each flow pair is balanced. 17.3.6. Water Uses Among indoor water uses, showering, bathing and handwashing of dishes or clothes provide the primary opportunities for dermal exposure. Virtually all indoor water uses will result in some volatilization of chemic?ls, leading to inhalation exposure. The exposure potential for a given situation will depend on the source of water, the types and extents of water uses, and the extent of volatilization of specific chemicals. According to the results of the 1987 Annual Housing Survey (U.S. Bureau of the Census, 1992), 84.7 percent of all U.S. housing units receive water from a public system or private company (as opposed to a well). Across the four major regions defined by the U.S. Census Bureau (Northeast, South, Midwest, and West), the percentage varies from 82.5 in the Midwest region to 93.2 in the West region (the Northeast and South regions both are very close to .the national percentage). The primary types of water use indoors can be classified as showering/bathing, toilet use, clothes washing, dishwashing, and faucet use (e.g., for drinking, cooking, general cleaning, or washing hands). Substantial information on water use has been collected in California households by the Metrop*olitan Water District of Southern California (MWD, .

1991) and by the East Bay Municipal Utility District (EBMUD, 1992). An earlier study by the U.S'. Department of Housing and Urban Development (U.S. DHUD, 1984) monitored water use in 200 households over a 20-month period. The household selection process for this study was not random; it involved volunteers from water companies and engineering organizations, most of which were located in large metropolitan areas. Nazaroff .et al. (1988) also assembled the results of several smaller surveys, typically involving between 5 and 50 households each. A common feature of the various studies cited above is that the results were all . reported in gallons per capita per day (gcd), or in units that could be easily converted to gcd. Most studies also provided estimates by type of use--shower/bath, toilet, laundry, dishwashing, and other (e.g., faucets). A summary of the various study results is provided in Table 17-14. There is generally about a threefold variation across studies for total house water use as well as each type of use. Central values for total use, were obtained Exposure Factors Handbook August 1997 Volume Ill -Activity Factors Chapter 17 -Residential Building Characteristics by taking the mean and median across the studies for each type of water use and then summing these means/medians across uses. These central values are shown at the bottom of the table. The means and medians were summed across types of uses to obtain the mean for all uses combined because only a subset of the studies reported values for other uses.

The following sections provide a summary of the water use characteristics for the / primary types of water uses indoors. To the extent found in the literature, each water use is described in terms of the frequency of use; flowrate during the use; quantity of water used during each occurrence of the water use; and quantity used by an average person. Table 17-15 summarizes the studies of U.S. DHUD and the Power Authorities by locations and number of households. Caution should be exercised when using the data collected in these studies and shown here. The participants in these studies are not a representative sample of the general population. The participants consisted of volunteers, mostly from large metropolitan areas. Showering and Bathing Water Use Cryaracteristics -The HUD study (U.S. DHUD, 1984) monitored 162 households for shower duration. The individuals were also subdivided by people who only shower or only bath. The results are given in Table 17-16. The flowrates of various types of shower. heads were also evaluated in the study (Table 17-17).

Toilet Water Use Characteristics-The HUD study (U.S. DHUD, 1984) reported water volume per flush for various types of toilets and monitored 162 households for shower duration. The results of this study are shown in Table 17-18. Since the HUD study was conducted prior to 1984, the newer (post 1984) conserving toilets that are designed to use approximately 1.6 gallons per flush were not tested. The frequency of use for toilets in households was examined in several studies (U.S. DHUD, 1984; Ligman, et al., 1974; Siegrist, 1976). The ooserved mean frequencies in these studies are given in Table 17-19. Tables 11,..20 through 17-24 present indoor water use frequencies for dishwashers and clothes washers. 17.3.7. House Dust and'Soil House dust is a complex mixture of biologically-derived material (animal dander, fungal spores, etc.), particulate matter deposited from the indoor aerosol, and soil particles brought in by foot traffic. House dust may conta'in VOCs (see, for example, Wolkoff and Wilkins, 1994; Hirvonen et 1995), pesticides from imported soil particles as well as Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 17 -Residential Building Characteristics , from direct applications indoors (see, for example, Roberts et al., 1991 ), and trace metals derived from outdoor sources (see, for example, Layton and Thatcher, 1995). The indoor abundance of house dust depends on the interplay of deposition from the airborne state, resuspension due to various activities, direct accumulation, and infiltration. In the absence of indoor sources, indoor concentrations of particulate matter are significantly lower than outdoor levels. For some time, this observation supported the idea that a significant fraction of the outdoor aerosol is filtered out by the building envelope. More recent data, however, have shown that deposition (incompletely addressed in earlier studies) accounts for the indoor-outdoor contrast, and outdoor particles smaller than 10 µm aerodynamic diameter penetrate the building envelope as completely as nonreactive gases (Wallace, .1996). Roberts et al. {1991) -Development and Field Testing of a High Volume Sampler for Pesticides and Toxics in Dust-Dust loadings, reported by Roberts et al. (1991) were also measured in conjunction with the Non-Occupational Pesticide Exposure Study (NOPES). In this study house dust was sampled from a representative grid using a specially constructed high-volume surface sampler (HVS2); The surface sampler collection efficiency was verified in conformance with ASTM F608 (ASTM, 1989). The data summarized in Table 17-25 were collected from carpeted areas in volunteer households in Florida encountered during the course of NOPES. Seven of the nine sites were family detached homes, and two were mobile homes. The authors noted that the two houses exhibiting the highest dust loadings were only those homes where a vacuum cleaner was not used for housekeeping. Thatcher and Layton {1995) -Deposition, Resuspension and Penetration of Particles Within a Residence -Relatively few studies have been conducted at the level of detail *needed to clarify the dynamics of indoor aerosols. One intensive study of a California residence (Thatcher and Layton, 1995), however, provides instructive results. Using a model-based analysis for data collected under .controlled circumstances, the investigators verified penetration of the outdoor aerosol and estimated rates for particle deposition and resuspension (Table 17-26). The investigators stressed that normal household activities are a significant source of airborne particles larger than 5 µm. During the study, they observed that just walking into and out of a room could momentarily double the concentration. The airborne abundance of submicrometer particles, on the.other hand, was unaffected by either cleaning or walking. Mass loading of floor surfaces (Table 17-27) was measured in study 9f Thatcher and Layton (1995) by thoroughly cleaning the house and sampling accumulated dust, after one week of normal habitation. Methodology, validated under ASTM F608 (ASTM, 1989), showed fine dust recovery efficiencies of 50 percent with new carpet and 72. percent for Exposure Factors Handbook August 1997 Volume Ill -Activity Factors Chapter 17 -Residential Building Characteristics linoleum. Tracked areas showed consistently higher accumulations than untracked areas, confirming the importance of tracked-in material. Differences -between tracked areas upstairs and downstairs show that tracked-in material is not readily transported upstairs. The consistency of untracked carpeted areas throughout the house, suggests that, in the absence of tracking, particle transport processes are similar on both floors. 17.4. SOURCES Product-and chemical-specific mechanisms for indoor sources can be described using simple emission factors to represent instantaneous releases, as well as constant releases over defined time periods; more complex formulations may be required for varying sources. Guidance documents for characterizing indoor sources within the context of the exposure assessment process are limited (see, for example, Jennings et al., 1987; Wolk off, 1995). Fairly extensive guidance exists in the technical literature, however, provided that the exposure assessor has the means to define (or estimate) key mechanisms and chemical-specific parameters. Basic concepts are summarized below for the broad source categories that relate to airborne contaminants, waterborne contaminants, and for soil/house dust indoor sources. 17 .4.1. Source Descriptions for Airborne Contaminants Table 17-28 summarizes simplified indoor source descriptions for airborne chemicals for direct discharge sources (e.g., combustion, pressurized propellant products), as well as emanation sources (e.g., evaporation from "wet" films, diffusion from porous media), and transport-related sources (e.g., infiltration of outdoor air contaminants, soil gas entry). Direct-discharge sources can be approximated using simple formulas that relate pollutant mass released to characteristic process rates. Combustion sources, for example, may be stated in terms of an emission factor, fuel content (or heating value), and fuel consumption (or carrier delivery) rate. Emission factors for combustion products of general concern (e.g., CO, NOJ have measured for a number of combustion appliances using room-sized chambers (see, for example, Relwani et al., 1986). Other discharge sources would include volatiles released from water use and from pressurized consumer products. Resuspension of house dust (see Section 17 .3. 7) would take on a similar form by combining an activity-specific rate constant with an applicable dust mass. Diffusion-limited sources (e.g., carpet backing, furniture, flooring, dried paint) represent probably the greatest challenge in sourc_e characterization for indoor air quality. Vapor-phase organics dominate this group, offering great complexity because (1) there is a fairly long list of chemicals that could be of concern, (2) ubiquitous consumer products, building materials, coatings, and furnishings contain varying amounts of different Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 17 -Residential Building Characteristics chemicals, (3) source dynamics may include nonlinear mechanisms, and (4) for many of the chemicals, emitting as well as non-emitting materials evident in realistic settings may promote reversible and irreversible sink effects. Very detailed descriptions for limited sources can be constructed to link specific properties of the chemical, the source material, and the receiving environment to calculate expected behavior (see, for example, Schwope et al., 1992; Gussler, 1984 ). Validation to actual circumstances, however, suffers practical shortfalls' because many parameters simply cannot be measured directly. The exponential formulation listed in Table 17-28 was derived based on a series of papers generated during the development of chamber testing methodology by EPA (Dunn, 1987; Dunn and Tichenor, 1988; Dunn and Chen, 1993). This framework represents an empirical alternative that works best when the results of chamber tests are available. Estimates for the initial emission rate (Ea) and decay factor (ks) can be developed for hypothetical sources from information on pollutant mass available for release (M) and supporting assumptions. Assuming that a critical time period (tc) coincides with reduction of the emission rate to a critical level (Ee) or with the release of a critical fraction of the total mass (Mc), the decay factor can be estimated by solving either of these relationships: I"°' e"-" or M, '1&e" , Ea M (Eqn. 17-3) The critical time period can be derived from product-specific considerations (e.g., equating drying time for a paint to 90 percent emissions reduction). Given such an estimate for ks, the initial emission rate can be estimated by integrating the emission formula to infinite time under the assumption that all chemical mass is released: I E M " E e "'-'dt' --" m a ' k a s (Eqn. 17-4) The basis for the exponential source algorithm has also been extended to the description of more complex diffusion-limited sources. With these sources, diffusive or evaporative transport at the interface may be much more rapid than diffusive transport from within the source material, so that the abundance at the source/air interface becomes Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 17 -Residential Building Characteristics depleted, limiting the transfer rate to the air. Such effects can prevail with skin formation in "wet" sources like stains and paints (see, for example, Chang and Guo, 1992). Similar emission profiles have been observed with the emanation of formaldehyde from particleboard with "rapid" decline as formaldehyde evaporates from surface sites of the particleboard over the first few weeks. It is then followed by a much slower decline over ensuing years as formaldehyde diffuses from within the matrix to reach the surface (see, for example, Zinn et al., 1990).

Transport-based sources bring contaminated air from other areas into the airspace of concern. Examples include infiltration of outdoor contaminants, and soil gas entry. Soil gas entry is a particularly complex phenomenon, and is frequently treated as a separate modeling issue (Little et al., 1992; Sextro, 1994). Room-to-room migration of indoor contaminants would also fall under this category, but this concept is best considered using* the multiple-zone model. 17.4.2. Source Descriptions for Waterborne Contaminants Residential water supplies may convey chemicals to which occupants can be exposed through ingestion, dermal contact, or inhalation. These chemicals may appear in the form of contaminants (e.g., trichloroethylene) as well as naturally-occurring byproducts of water system history (e.g., chloroform, radon). Among indoor water uses, showering, bathing and handwashing of dishes or clothes provide the primary opportunities for dermal exposure. The escape of volatile chemicals to the gas phase associates water use with inhalation exposure. The exposure potential for a given situation will depend on the source of water, the types and extents of water uses, and the extent of volatilization of specific chemicals. Primary types of residential water use (summarized in Section 17.3) include showering/bathing, toilet use, clothes washing, dishwashing, and faucet use (e.g., for drinking, cooking, general Cleaning, or washing hands). Upper-bounding estimates of chemical release rates from water use can be formulated as simple emission factors by combining the concentration in the feed water (g m-3) with the flow rate for the water use (m 3 h-1), and assuming that the chemical escapes to the gas phase. For some chemicals, however, not all of the chemical escapes in realistic situations due to diffusion-limited transport and solubility factors. For inhalation exposure estimates, this may not pose a problem because the bounding estimate would overestimate emissions by no more than approximately a factor of two. For multiple exposure pathways, the chemical mass remaining in the water may be of importance. Refined estimates of volatile emissions are usually considered under two-resistance theory to accommodate mass transport aspects of the water-air syl?tem (see, for example, Little, 1992; Andelman, 1990; McKone, 1.987). Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 17 -Residential Building Characteristics Release rates are formulated as: s

K F [c & c.} . m w w H (Eqn. 17-5) where:* S = chemical release rate (g h-1) Km dimensionless mass-transfer coefficient F w water flow rate (m3 h-1) Cw concentration in feed water (g m-3) c. = concentration in air (g m-3) H dimensionless Henry's Law constant Because the emission rate is dependent on the air concentration, recursive techniques are required. The mass transfer coefficient is a function of water use characteristics (e.g., water droplet size spectrum, fall distance, water film) and chemical properties (diffusion in gas and liquid phases). Estimates of practical value are based on empirical tests to incorporate system characteristics into a single parameter (see, for example, Giardino et al., 1990). Once characteristics of one chemical-water use system are known (reference chemical, subscript r), the mass transfer coefficient for another chemical (index. chemical, subscript i) delivered by the same system can be estimated using formulations identified in the review by Little ( 1992): (Eqn. 17-6) where: DL liquid diffusivity (m2 s-1) DG gas diffusivity (m2 s-1) KL = liquid-phase mass transfer coefficient

KG gas-phase mass transfer coefficient H = dimensionless Henry's Law constant 17 .4.3. Soil and House Dust Sources The rate process descriptions compiled for soil and house dust in Section 17.3 provide inputs for estimating indoor emission rates (Sd, g h-1) in terms of dust mass loading (Md, g m-2) combined with resuspension rates (Rd, h-1) and floor area (At, m2): (Eqn. 17-7) Exposure Factors Handbook August 1997 Volume Ill -Activity Factors Chapter 17 -Residential Building Characteristics Because house dust is a complex mixture, transfer of particle-bound constituents to the gas phase may be of concern for some exposure assessments. For emission estimates, one would then need to consider particle mass residing in each reservoir (dust deposit, airborne). 17.5. ADVANCED CONCEPTS 17 .5.1. Uniform Mixing Assumption Many exposure measurements are predicated on the assumption of uniform mixing within a room or zone of a house. Mage and Ott ( 1-994) offers an extensive review of the history of use and misuse of the concept. Experimental work by Baughman et al. ( 1994) and Drescher et al. (1995) indicates that, for an instantaneous release from a point source in a room, fairly complete mixing is achieved within 10 minutes when convective flow is induced by solar radiation. However, up to 100 minutes may be required for complete mixing under quiescent (nearly isothermal) conditions. While these experiments were conducted at extremely low air exchange rates(< 0.1 ACH), based on the results, attention is focused on mixing within a room. The situation changes if a human invokes a point source for a longer period and remains in the immediate vicinity of that source. Personal exposure in the near vicinity of a source can be much higher than the well-mixed assumption would suggest. A series of experiments conducted by GEOMET (1989) for the U.S. EPA involved controlled source releases of carbon monoxide tracer (CO), each for 30 minutes. "Breathing-zone" measurements located within 0.4 m of the release point were ten times higher than for other locations in the room during early stages of mixing and transport. Similar investigations conducted by Furtaw et al. (1995) involved a series of experiments in a controlled-environment room-sized chamber. Furtaw et al. (1995) studied spatial concentration gradients around a continuous point source simulated by sulfur hexafluoride (SF6) tracer with a human moving about the room. Average breathing-zone concentrations when the subject was near the source exceeded those several meters away by a factor that varied inversely with the ventilation intensity in the room. At typical room ventilation rates, the ratio of source-proximate to slightly-removed concentration was on the order of2:1. 17 .5.2. Reversible Sinks For some chemicals, the actions of reversible sinks are of concern. For an initially "clean" condition in the sink material, sorption effects can greatly deplete indoor concentrations. However, once enough of the chemical has been adsorbed, the diffusion Exposure Factors Handbook August 1997 Volume 111 -Activity Factors Chapter 17 -Residential Building Characteristics gradient will reverse, allowing the chemical to escape. For persistent indoor such effects can serve to reduce indoor levels initially but once the system equilibrates, the net effect on the average concentration of the reversible sink is negligible. Over suitably short time frames, this can also affect integrated exposure. For indoor sources whose profile declines with time (or ends abruptly), reversible sinks can serve to extend the emissions period as the chemical desorbs long after direct emissions are finished. Reversible sink effects have been observed for a number of chemicals in the presence of carpeting, wall coverings, and other materials commonly found in residential environments. Interactive sinks (and models of the processes) are of a special importance; while sink effects can greatly reduce indoor air concentrations, re-emission at lower rates over longer time periods could greatly extend the exposure period of concern. For completely reversible sinks, the extended time could bring the cumulative exposure to levels approaching the sink-free case. Recent publications (Axley et al., 1993; Tichenor etal., 1991) show that first principles provide useful guidance in postulating models and setting assumptions for reversible/irreversible, sink models. Sorption/desorption can be described in terms of Langmuir (monolayer) as well as Brunauer-Emmet-Teller (BET, multilayer) adsorption. 17 .6 RECOMMENDATIONS Table 17-29 presents a summary of volume of residence surveys and Table 17-30 presents a summary of air exchange rates surveys. Table 17-31 presents the recommended values. Tables 17-32 and 17-33 provide the confidence in recommendations for house volume and air exchange rates, respectively. Key studies or analyses described in this chapter were used in selecting recommended values for residential volume. The air exchange rate data presented in the studies are extremely limited. Therefore, studies have not been classified as key or relevant studies. However, recommendations have been provided for air exchange rates and the confidence recommendation has been assigned a "low" overall rating. Therefore, these values should be used with caution. Both central and conservative values are provided. These two parameters --volume and air exchange rate --can be used by exposure assessors in modeling indoor-air concentrations as one of the inputs to exposure estimation. Other inputs to the modeling effort include rates of indoor pollutant generation and losses to (and, in some cases, re-emissions from) indoor sinks. Other things being equal (i.e., holding constant the pollutant generation rate and effect of indoor sinks), lower values for either the indoor volume or the air exchange rate will result in higher indoor-air concentrations. Thus, values near the lower end of the distribution (e.g., 10th percentile) for either parameter are appropriate in developing conservative estimates of exposure. Exposure Factors Handbook August 1997 Volume III -Activity Factors Chapter 17 -Residential Building Characteristics For the volume of a residence, both key studies (U.S. DOE (1995) and Versar (1990) PFT database) have the same mean value --369 m3 (see Table 17-1 ). This mean value is recommended as a central estimate residential volume. Intuitively, the 10th percentile of the distribution from either study --147 m3 for RECS survey or 167 m3 for the PFT database --is too conservative a value, as both these values are. lower than the mean volume for multifamily dwelling units (see_ Table 17-2). Instead, the 25th percentile --209 m3 for RECS survey or 225 m3 for PFT database, averaging 217 m3 across the two key studies --is recommended (Table 17-1 ). For the residential air exchange rate, the median value of 0.45 air changes per hour (ACH) from the PFT database (see Table 17-9) is recommended as a typical value (Koontz and Rector, 1995). This median value is very close to the geometric mean of the measurements in the PFT database analyzed by Koontz and Rector (1995). The arithmetic mean is not preferred because it is influenced fairly heavily by extreme values at the upper tail of the distribution. For a conservative value, the 10th percentile for the PFT database --0.18 ACH --is recommended (Table 17-10). There are some uncertainties in, or limitations on, the distribution for volumes and air exchange rates that are presented in this chapter. For example, the RECS used to infer volume distributions used a nationwide probability sample, but measured floor area rather than total volume. By comparison, field studies contributing to the PFT data base measured house volumes directly, but the aggregate sampling frame for these studies is not statistically representative of the naUonal housing stock. Although the PFT methodology is relatively simple to implement, it is subject to errors and uncertainties. The general performance of the sampling and analytical aspects of the system are quite good. That is, laboratory analysis will measure the correct average tracer concentration to within a few percent (Dietz et al., 1986). Nonetheless, significant errors can arise when conditions in the measurement scene greatly deviate from idealizations calling for constant, well-mixed conditions. Principal concerns focus on the effects of naturally varying air exchange and the effects of temperature in the permeation source. Sherman (1989) carried out an error analysis of the PFT methodology using mathematical models combined with typical weather data to calculate how an ideal sampling system would perform in a time-varying environment. He found that for simple single-story (ranch) and two-story plus basement (colonial) layouts, seasonal measurements would underpredict seasonal average air exchange by 20 to 30 percent. Underprediction can occur because the PFT methodology is measuring the effective ventilation (the product of ventilation efficiency and air exchange), and the temporal efficiency will generally be less than unity over averaging periods of this length. Sherman Exposure Factors Handbook August 1997 Volume Ill -Activity Factors Chapter 17 -Residential Building Characteristics (1989) also noted, however, that while the bias could have an impact on determining air exchange (absent knowledge of ventilation efficiency) for calculating energy loads, the effective air exchange term is directly relevant to determining average indoor concentrations resulting from constant sources. Leaderer et al. (1985) conducted a series of experiments in a environmental chamber to evaluate the practical impacts of varying air exchange and the temperature response of the permeation sources. The negative bias anticipated in the measured (effective) versus actual air exchange as conditions varied diurnally between 0.4 and 1.5. ACH was evident but minor (3 to 6 percent), most likely due to the mechanical mixing in the chamber and the relatively short integration time (72 h). Similarly, cycling temperature diurnally over an. 8°C range (holding air exchange steady at 0.6 ACH) would cause concentrations changes of about 20 percent as emissions fluctuated. The investigators found, however, that using a time-weighted average temperature to define the emission rate reduced the temperature bias to essentially zero. Exposure Factors Handbook August 1997 Table 17-1. Summary of Residential Volume Distributions in Cubic Metersa Parameter RECS Data (1) PFT Database (2) Arithmetic Mean 369 369 Standard Deviation 258 209 10th Percentile 147 167 25th Percentile 209 225 50th Percentile 310 321 75th Percentile 476 473 90th Percentile 672 575 a In cubic meters Sources: (1) Thomoson 1995* (2) Versar 1990 Table 17-2. Average Estimated Volumes of U.S. Residences; by Housing Type and Ownership Ownership Owner-Occupied Rental All Units Volume* Percent Volume* Percent Volume* Percent Housing Type (m3) ofTotal (m3) of Total (m3) of Total Single-Family 471 53.1 323 8.5 451 61.7 (Detached) Single-Family 406 4.6 291 2.9 362 7.5 (Attached) Multifamily 362 1.6 216 6.7 243 8.3 (2-4 units) I Multifamily 241 1.7 183 . 15.2 190 16.8 (5+ Units) Mobile Home 221 4.6 170 1.2 210 5.8 All Types 441 65.4 233 34.6 369 100.0 a Volumes calculated from floor areas assuming a ceiling height of 8 feet. Source: Adapted from U.S. DOE, 1995.
Table 17-3. Residential Volumes in Relation to Household Size and Year of Construction Volumea (m3) Percent of Total Household Size 1 Person 269 24.3 2 Persons 386 32.8 3 Persons 387 17.2 4 Persons 431 15.1 5 Persons 433 7.0 6 or More Persons 408 3.6 All Sizes 369 100.G Year of Construction 1939 or before 385 21.1 1940 to 1949 338 7.1 1950 to 1959 365 13.5 1960 to 1969 358 15.5 1970 to 1979 350 18.7 1980 to 1984 344 8.8 1985 to 1987 387 5.7 1988 to 1990 419 4.9 1991to1993 438 4.7 All Years 369 100.0 a Volumes calculated from floor areas assuming a ceiling height of 8 feet. Source: U.S. DOE, 1995. Table 17-4. Dimensional Quantities for Residential Rooms Length Width Height Volume Wall Area Floor Area Total Area Nominal Dimensions (m) (m) Im) (m3) (m2) (m2) (m2) Eight Foot Ceiling 12'x15' 4.6 3.7 2.4 41 40 17 74 12'x12' 3.7 3.7 2.4 33 36 13 62 10'x12' 3.0 3.7 2.4 27 33 11 55 9'x12' 2.7 3.7 2.4 24 31 10 51 6'x12' 1.8 3.7 2.4 16 27 7 40 4'x12' 1.2 3.7 2.4 11 24 4 32 Twelve Foot Ceiling 12'x15' 4.6 3.7 3.7 61 60 17 94 12'x12' 3.7 3.7 3.7 49 54 13 80 10'x12' 3.0 3.7 3.7 41 49 11 71 9'x12' 2.7 3.7 3.7 37 47 10 67 6'x12' 1.8 3.7 3.7 24 40 7 54 4'x12' 1.2 3.7 3.7. 16 36 4 44 Table 17-5. Examples of Products and Materials Associated with Floor and Wall Surfaces in Residences Material Sources Silicone caulk Floor adhesive Fl6orwax Wood stain Polyurethane wood finish Floor varnish or lacquer Plywood paneling Chipboard Gypsum board Wallpaper a Based on typical values for a residence. Source: Adapted from Tucker, 1991. Assumed Amount of Surface Covered" 0.2 m2 10.0 m2 50.0 m2 10.0 m2 10.0 m2 50.0 m2 100.0 m2 100.0 m2 100.0 m2 100.0 m2 Table 17-6. Percent of Residences with Basement, by Census Region and EPA Region EPA Percent of Census Region Region Residences with Basements Northeast 1 93.4 Northeast 2 55.9 Northeast 3 67.9 South 4 19.3 Midwest 5 73.5 South 6 4.1 Midwest 7 75.3 West 8 68.5 West 9 10.3 10 11.5 All Reaions 45.2 Source: Lucas et al. 1992. Table 17-7. Percent of Residences with Certain Foundation Types by Census Region Percent of Residencesa Census Region With With With Crawlsgace With Basement Enclosed Open to Ou side Concrete Slab Crawlspace Northeast 78.0 12.6 2.8 15.8 Midwest 78.1 19.5 5.6 14.7 South 18.6 31.8 11.0 44.6 West 19.4 36.7 8.1 43.5 All Regions 45.2 26.0 7.5 31.3
~~Percentage may add to more than 100 percent because more than one foundation type may apply to a given residence. Source: U.S. DOE, 1995.~~
Table 17-8. States Associated with EPA Regions and Census Regions US EPA Regions Region 1 Region 4 Region 6 Region 9 Connecticut Alabama Arkansas Arizona Maine Florida Louisiana California Massachusetts Georgia New Mexico Hawaii New Hampshire Kentucky Oklahoma Nevada Rhode Island Mississippi Texas Vermont North Carolina . Region 10 South Carolina Region 7 Alaska Region 2 Tennessee Iowa Idaho New Jersey Kansas *Oregon New York Region 5 Missouri Washington Illinois Nebraska Region 3 Indiana Delaware Michigan Region 8 District of Columbia Minnesota Colorado Maryland Ohio Montana Pennsylvania Wisconsin North Dakota Virginia South Dakota West Virginia Utah Wyoming US Bureau of Census Regions Northeast Region Midwest Region South Region West Region Connecticut Illinois Alabama Alaska Maine Indiana Arkansas ,, Arizona Massachusetts Iowa* Delaware California New Hampshire Kansas District of Columbia Colorado New Jersey Michigan Florida Hawaii New York Minnesota Georgia Idaho Pennsylvania Missouri Kentucky Montana Rhode island Nebraska Louisiana Nevada Vermont North Dakota Maryland New Mexico Ohio Mississippi Oregon South Dakota North Carolina Utah Wisconsin Oklahoma Washington South Carolina Wyoming Tennessee Texas Virginia West Virginia Table 17-9. Summary of Major Projects Providing Air Exchange Measurements in the PFT Database Number of Mean Air Percentiles Project Code State Month(s)' Measurements Exchange sob Rate 1oth 25th 50th 75th 90th ADM CA 5-7 29 0.70 0.52 0.29 0.36 0.48 0.81 1.75 BSG CA 1,8-12 40 0.53 0.30 0.21 0.30 0.40 0.70 0.90 GSS AZ. 1-3,8-9 25 0.39 0.21 0.16 0.23 0.33 0.49 0.77 FLEMING NY 1-6,8-12 56 0.24 0.28 0.05 0.12 0.22 0.29 0.37 GEOMET1 FL 1,6-8, 10-12 18 0.31 0.16 0.15 0.18 0.25 0.48 0.60 GEOMET2 MD 1-6 23 0.59 0.34 0.12 0.29 0.65 0.83 0.92 GEOMET3 TX 1-3 42 0.87 0.59 0.33 0.51 0.71 1.09 1.58 LAMBERT1 ID 2-3, 10-11 36 0.25 0.13 0.10 0.17 0.23 0.33 0.49 LAMBERT2 MT 1-3, 11 51 0.23 0.15 0.10 0.14 0.19 0.26 0.38 LAMBERT3 OR 1-3,10-12 83 0.46 0.40 0.19 0.26 0.38 0.56 0.80 LAMBERT4 WA 1-3,10-12 114 0.30 0.15 0.14 0.20 0.30 0.39 0.50 LBL1 OR 1-4,10-12 126 0.56 0.37 0.28 0.35 0.45 0.60 1.02 LBL2 WA 1-4, 10-12 71 0.36 0.19 0.18 0.25 0.32 0.42 0.52 LBL3 ID 1-5,11-12 23 1.03 0.47 0.37 0.73 0.99 1.34 1.76 LBL4 WA 1-4,11-12 29 0.39 0.27 0.14 0.18 0.36 0.47 0.63 LBL5 WA 2-4 21 0.36 0.21 0.13 0.19 0.30 0.47 0.62 LBL6 ID 3-4 19 0.28 0.14 0.11 0.17 0.26 0.38 o:ss NAHB MN 1-5,9-12 28 0.22 0.11 0.11 0.16 0.20 0.24 0.38 NYSDH NY 1-2,4,12 74 0.59 0.37 0.28 0.37 0.50 0.68 1.07 PEI MD 3-4 140 0.59 0.45 0.15 0.26 0.49 0.83 1.20 PIERCE CT 1-3 25 0.80 1.14 0.20 0.22 0.38 0.77 2.35 RTl1 CA 2 45 0.90 0.73 0.38 0.48 0.78 1.08 1.52 RTl2 CA 7 41 2.77 2.12 0.79 1.18 2.31 3.59 5.89 RTl3 NY 1-4 397 0.55 0.37 0.26 0.33 0.44 0.63 0.94 SOCAL1 CA 3 551 0.81 0.66 0.29 0.44 0.66 0.94 1.43 SOCAL2 CA 7 408 1.51 1.48 0.35 0.59 1.08 1.90 3.11 SOCAL3 CA 1 330 0.76 1.76 0.26 0.37 0.48 0.75 1.11 UMINN MN 1-4 35 0.36 0.32 0.17 0.20 0.28 0.40 0.56 UWISC WI 2-5 57 0.82 0.76 0.22 0.33 0.55 1.04 1.87 ' 1 =January, 2 = February, etc. b Standard deviation Source: Adapted from Versar, 1990. Table 17-10. Summary Statistics tor Air Exchange Rates (air changes per hour-ACH), by Region North Central Northeast West Region Region Region South Region All Regions Arithmetic Mean 0.66 0.57 0.71 0.61 0.63 Arithmetic Standard Deviation 0.87. 0.63 0.60 0.51 0.65 Geometric Mean 0.47 0.39 0.54 0.46" 0.46 Geometric Standard Deviation 2.11 2.36 2.14 2.28 2.25 10th Percentile 0.20 0.16 0.23 0.16 0.18 5oth Percentile 0.43 0.35 0.49 0.49 0.45 90th Percentile 1.25 1.49 1.33 1.21 1.26 Maximum 23.32 4.52 5.49 3.44 23.32 Source: Koontz and Rector, 1995. Table 17-11. Distributions of Residential Air Exchanqe Rates' by Climate Reqion and Season Percentiles Arithmetic Standard Climate Season Sample Size Mean Deviation 10th 25th 50th 75th 90th Reqion Coldest Winter 161 0.36 0.28 0.11 0.18 0.27 0.48 0.71 Spring 254 0.44 0.31 0.18 0.24 0.36 0.53 0.80 Summer 5 0.82 0.69 0.27 0.41 0.57 1.08 2.01 Fall 47 0.25 0.12 0.10 0.15 0.22 0.34 0.42 Colder Winter 428 0.57 0.43 0.21 0.30 0.42 0.69 1.18 Spring 43 0.52 0.91 0.13 0.21 0.24 0.39 0.83 Summer 2 1.31 ------------Fall 23 0.35 0.18 0.15 0.22 0.33 0.41 0.59 Warmer Winter 96 0.47 0.40 0.19 0.26 0.39 0.58 0.78 Spring 165 0.59 0.43 0.18 0.28 0.48 0.82 1.11 Summer 34 0.68 0.50 0.27 0.36 0.51 0.83 1.30 Fall 37 0.51 0.25 0.30 0.30 0.44 0.60 0.82 Warmest Winter 454 0.63 0.52 0.24 0.34 0.48 0.78 1.13 Spring 589 0.77 0.62 0.28 0.42 0.63 0.92 1.42 Summer 488 1.57 1.56 0.33 0.58 1.10 1.98 3.28 Fall 18 0.72 1.43 0.22 0.25 0.42 0.46 0.74 'In air changes per hour Source: Murrav and Burmaster 1995. Table 17-12. Deposition Rates for Indoor Particles Size Fraction Deposition Rate PM2.5 0.39 h-1 PM10 0.65 h-1 Coarse 1.0 h-1 Source: Adapted from Wallace, 1996. Table 17-13. Particle Deposition During Normal Activities Particle Size Range Particle Removal Rate (h-1) 1-5 0.5 5-10 1.4 10-25 2.4 >25 4.1 Source: Adaoted from Thatcher and Lavton 1995. Table 17-14. In-house Water Use Rates (Qcd), by Study and Type of Use Total, Shower Studv All Uses or Bath Toilet Laundrv Dishwashina Other MWD' 93 26 30 20 5 12 EBMUD2 67 20 28 9 4 6 U.S. DHUD3 40 15 10 13 2 --Nazaroff et al., 1988 52 6 17 11 18 -Study 1 Study 2 -Rural 46 11 18 14 3 ---Urban 43 10 18 11 4 --Study 3 42 9 20 7 4 2 Study 4 45 9 15 11 4 6 Study 5 70 21 32 7 7 3 Study 6 59 20 24 8 4 3 Study 7 40 10 9 11 5 5 Study 8 52-86 20-40 4-6 20-30 8-10 --Mean Across Studies5 59 17 18 13 6 5 Median Across Studies5 53 15 18 11 4 5 1 Metropolitan Water District of Southern California, 1991. 2 East Bay Municipal Utility District, 1992. 3 U.S. Department of Housing and Urban Development, 1984. 4 Results of eight separate studies. 5 The average value from each range reported in Study No. 8 was used to calculate the median across studies. The mean and median for the "Total, all Uses" column were obtained by summing across the means and medians for individual types of water use. Table 17-15. Summary of Selected HUD and Power Authority Water Use Studies Number of Households Location Reference U.S. DHUD Studies Study 1 37 Los Angeles, CA a,b Study2 7 Sacramento, CA a,c Study 3 40 Walnut Creek, CA a,c Study 4 7 Washington, DC a Study 5 21 Sacramento, CA a Study 6 19 Los Angeles, CA a Power Authority Studies Study 1 32 Seattle, WA a Study 2 23 Denver, CO a Study 3 15 Aurora, CO a Study4 10 Fairfax, VA a TOTAL 211 Sources: a U.S. Department of Housing and Urban Development, 1984. b Metropolitan Water District of Southern California, 1991. ' East Bay Municipal Utility District, 1992. Table 17-16. Showering and Bathing VVater Use Characteristics Characteristic Mean Duration* Mean Frequencv Individuals who Shower only 10.4 minutes/shower 0.74 showers/day/person Individuals who Bath only NA 0.41 baths/day/person Individuals who Shower and Bath NA NA Source: Adapted from U.S. DHUD, 1984. Table 17-17. Showering Characteristics for Various Types of Shower Heads Shower Head Type Mean Flow Rate (gpm) Non-Conserving (> 3 gpm) 3.4 Low Flow 3 gpm) 1.9 Restrictor 3 gpm) 2.1 Zinplas* 1.8 Turboiector" 1.3 a Types of low flow water fixtures. Source: Adapted from U.S. DHUD, 1984. Table 17-18. Toilet Water Use Characteristics Toilet Type Average Water Use (gallons/flush) Non-Conserving 5.5 Bottles 5.0 Bags 4.8 Oal')'ls 4.5 Low-flush 3.5 Source: Adapted from U.S. DHUD, 1984. Table 17-19. Toilet Frequency Use Characteristics Flush Frequency Study (flushes/person/day) U.S. DHUD, 1984a 4.2 flushes/household/day Ligman, et al., 1974 Rural, M-F 3.6 flushes/person/day Ligman, et al., 197 4 Rural, Sat-Sun 3.8 flushes/person/day Ligman, et al., 1974 Urban, M-F 3.6 flushes/person/day Ligman, et al., 1974 Urban, Sat-Sun 3.1 flushes/person/day Siegrist, 1976 2.3 flushes/person/day Unweiahted Mean 3.43 flushes/oerson/day a The HUD value may in fact be flushes/household/day Table 17-20. Dishwasher Frequencv Use Characteristics Studv Use Freauencv U.S. DHUD, 1984 0.47 loads/person/day ' Ligman, et al., 197 4 Rural 1 .3 loads/day Siegrist, 1976 0.39 loads/person/day Unweiahted Mean 0.92 loads/dav Table 17-21 . Dishwasher Water Use Characteristics , Average Water Use Cycle Duration Brand (gallons/regular cycle) (minutes) . 140°F 120°F Maytag 11.5 75 --Frigidaire 12 75 75 General Electric 10.5 80 95 Sears 10 75 95 Whirlpool 9.5 60 110 White/Westinghouse 12 75 75 Waste King 11.5 65 85 Kitchen Aid 9.5 80 80 Magic Chef 11.5 70 --Unweiahted Mean 10.9 72.8 87.9 Source: Adapted from Consumer Reports 1987. Table 17-22. Clothes Washer Frequencv Use Characteristics Studv Use Frenuencv U.S. DHUD, 1984 0.3 loads/person/day Ligman, et al., 1974 Rural 0.34 loads/person/day Ligman, et al., 1974 Urban 0.27 loads/person/day Siearist 1976 0.31 loads/dav Table 17-23. Clothes Washer Water Use Characteristics Average Water Use Cycle Duration Brand (gallons/regular cycle) (minutes) Maytag 41 32 Frigidaire 48 40 General Electric 51 48 Hotpoint 51 48 Sears 49 40 Whirlpool 53 44 White/Westinghouse 54 47 Kelvinator 46 52 No roe 55 49 Source: Adaoted from Consumer Reoorts 1982. Table 17-24. Range of Water Uses for Clothes Washers Tvoe of Clothes Washer Ranqe of Water Use Conventional 27-59 gallons/load Low Water 16-19 gallons/load All Clothes Washers 16-59 qallons/load Source: Adapted from Consumer Reports 1982. Table 17-25. Total Dust Loading for Carpeted Areas Household Total Dust Load Fine Dust (<150 µm) Load (Q-m-2) (Q-m-2) 1 10.8 6.6 .2 4.2 3.0 3 0.3 0.1 4 2.2; 0.8 1.2; 0.3 5 1.4; 4.3 1.0; 1.1 6 0.8 0.3 7 6.6 4.7 8 33.7 23.3 9 812.7 168.9 Source: Adapted from Roberts et al., 1991. Table 17-26. Particle Deposition and Resuspension DurinQ Normal Activities Particle Particle Resuspension . Particle Size Range Rate . ate W1) (µm) (h-1) 0.3-Q.5 (not measured) 9.9 x 10-1 0.6-1 (not measured) 4.4 x 10-7 1-5 0.5 1.8X10-5 5-10 1.4 8.3 X 10-s 10-25 2.4 3.8 x 104 >25 4.1 3.4 X 10-s Source: Adaoted from Thatcher and Lavton 1995. Table 17-27. Dust Mass LoadinQ After One Week Without Vacuum CleaninQ Location in Test House Dust (g-m1 Tracked area of downstairs carpet 2.20 Untracked area of downstairs carpet 0.58 Tracked area of linoleum 0.08 Untracked area of linoleum 0.06 Tracked area of upstairs carpet 1.08 Untracked area of upstairs carpet 0.60. Front doormat 43.34 Source: Adaoted from Thatcher and Lavton 1995. Table 17-28. Simplified Source Descriptions for Airborne Contaminants Description Components Dimensions Direct Discharge Combustion ErHrMr g h-1 Er = emission factor g j-1 Hr = fuel content J mo1-1 M1 =fuel consumptior:i rate mol h-1 Volume Discharge QpCp_eD g h-1 Qp = volume delivery rate m3 h-1 cp = concentration in carrier g m-3 eD = transfer efficiency gg-1 Mass Discharge MP w. e g h-1 MP = mass delivery rate g h-1 w. = weight fraction g g-1 eD = transfer efficiency g g-1 Diffusion Limited (D1 oO )(C. -C; )A; g h-1 Dr = diffusivity mz h-1 o -1 = boundary layer thickness m c. = vapor pressure of g m-3 surface g m-3 C; = room concentration mz Exponential A; =area g h-1 A; Ea e-kt mz A; =area g h-1m-2 Ea = initial unit emission rate h-1 k = emission decay factor h t =time Transport Infiltration ojicj g h-1 lnterzonal Qji = air flow from zone j m3 h_, Soil Gas cj = air concentration in zone g m-3 i Table 17-29. Volume of Residence Surve s Studv Key Studies U.S. DOE, 1995 (RECS) Versar, 1990 (PFT database) Murray, 1996 Number of Residences Over 7,000 Over 2,000 7,041 (RECS) 1,751 (PFT) SurvevTvoe Direct measurement of floor area; estimation of volume Direct measurement and estimated Direct measurements and estimated Areas Surve ed Nationwide (random sample) Nationwide (not random sample); a large fraction located in CA RECS-Nationwide (random sample); PFT -Nationwide (not random sample); a large fraction located in CA Comments Volumes were estimated assuming 8 ft. ceiling height. Provides relationships between average residential volumes and facilities such as housing type, ownership, household size, and structure age. Sample was not geographically balanced; statistical weighting was applied to develop nationwide distributions Duplicate measurement were eliminated; tested the effects of using 8 ft. assumption on ceiling height to calculate volume; data from both databases were anal zed.
Table 17-30. Air Exchange Rates Surveys Number of Studv Residences/Measurements Survev Tvoe Areas Surveved Comments Versar. 1990 Over 2,000 residences Measurements using Nationwide (not random Multiple measurements on the (PFT database) PFT technique sample); a large fraction located same home were included. in CA Koontz & Rector, 1995 2,971 measurements Measurements using Nationwide (not random Multiple measurements on the (PFT database) PFT technique sample); a large fraction located same home were included. in CA Compensated for geographic imbalances. Data are presented by region of the country and season. Murray and Burmaster, 1995 2,844 measurements Measurements using Nationwide (not random Multiple measurements on the (PFT database) PFT technique sample); a large fraction located same home were included. Did not in CA compensate for geographical imbalances. Data are presented by climate region and season. Nazaroff et al., 1988 255 (Grat and Clark, 1981) Direct measurement 255, low-income families in 14 Sample size was small and not cities representative of the u:s. 312 (Grimsrud, 1983) Direct measurement 321, newer residences, median Sample size was small and not aae <10 vears reoresentative of the U.S.
Table 17-31. Recommendations -Residential Parameters Volume of Residence 369 m3 (central estimate)" 217 m3 (mean)b Air Exchange Rate 0.45 ACH (median)' 0.18 ACH ( 1 oth percentile )d a Same mean value presented in two studies (Table 17-1)-recommended to be used as the central estimate. b Mean of two 25th. percentile values (Table 17-1) -recommended fo be used as the mean value. c Recommended to be used as a typical value (Table 17-10). d RecommendP.rl to hP. used as a rnn""rv"tive value IT"ble 17-10\. Table 17-32. Confidence in House Volume Recommendations Considerations Rationale Ratina Study Elements Level of peer review All key studies are from peer reviewed literature. High . Accessibility Papers are widely available from peer review journals. High . Reproducibility Direct measurements were made. High . Focus on factor of The focus of the studies was on estimating house High interest volume as well as other factors. . Data pertinent to U.S. Residences in the U.S. was the focus of the key High studies. Primary data All the studies were based on primary data. High . Currency Measurements in the PFT database were taken Medium between 1982-1987. The RECS survey was conducted in 1993. Adequacy of data Not applicable collection period
Validity of approach For the RECS survey, volumes were estimated Medium assuming an 8 ft. ceiling height. The effect of this assumption has been tested by Murray (1996) and found to be insignificant.

Study size The sample sizes used in the key studies were fairly Medium large, although only 1 study (RECS) was representative of the whole U.S. Not all samples were selected at random; however, RECS samples were selected at random.

Representativeness of the RECS sample is representative of the U.S. Medium population

Characterization of Distributions are presented by housing type and , Medium variability regions; although some of the sample sizes for the subcategories were small.

Lack of bias in study design . Selection of residences was random for RECS. Medium (high rating is desirable)

Measurement error Some measurement error may exist since surface Medium areas were estimated using the assumption of.8 ft. ceiling height. Other Elements

Number of studies There are 3 key studies; however there are only 2 Low data sets.

Agreement between researchers There is good agreement among researchers. High Overall Rating Results were consistent; 1 study (RECS) was Medium representative of residences in the whole U.S.; volumes were estimated rather than measured in some cases.
~~Table 17-33. Confidence in Air Exchange Rate Recommendations Considerations Rationale Ratina Study Elements~~
Level of peer review The studies appear in peer reviewed literature. High Although there are 3 studies, they are all based on the same database (PFT database). Accessibility Papers are widely available from government reports High and peer review journals. Reproducibility Precision across repeat analyses has been Medium documented to be acceptable. . Focus on factor of The focus of the studies was on estimating air High interest exchange rates as well as other factors. . Data pertinent to U.S. Residences in the U.S. was the focus of the PFT High database. Primary data All the studies were based on primary data. High Currency Measurements in the PFT database were taken Medium between 1982-1987. Adequacy of data Only short term data were collected; some residences Medium collection period were measured during different seasons; however, long term air exchange rates are not well characterized.

Validity of approach Although the PFT technology is an EPA standard Low method (Method IP-4A), it has some major limitations (e.g., uniform mixing assumption).

Study size The sample sizes used in the key studies were fairly Medium large, although not representative of the whole U.S. Not all samples were selected at random.

Representativeness of the Sample is not representative of the U.S .. Low population

Characterization of Distributions are presented by U.S. regions, seasons, Low variability and dimatic regions; although some of the sample sizes for the subcategories were small and not representative of U.S. The utility is limited ..

Lack of bias in study design Bias may result since the selection of residences was Low {high rating is desirable) not random.

Measurement error Some measurement error may exist. Medium Other Elements

Number of studies There are 3 key studies; however there are only 1 Medium data set. However, the database contains results of 20 projects of varying scope.

Agreement between researchers Not applicable Overall Rating Sample was not representative of residences in the Low whole U.S., but covered the range of occurrence. PFT methodology has limitations. Uniform mixing assumption may not be adequate. Results will vary depending on placement of samples and on whether windows and doors are dosed or ooened.
Air In Water In Soil In L Concentration, C .... Exposure, E for Occupant(s} Source -Decay Resuspension Removal *
Reversible. *

Sinks Figure 17-1. Elements of Residential Exposure Out 100 90 80 c 70 ., 60 Q. c 50 Ul ::> "'" LL. 40 ., > 'fii. 3 30 E ::> u 20 10 0 0 --e--ooE survey -i1-PfT database 100 200 300 400 500 600 700 800 900 Vollfne, clbic meters Figure 17-2. Cumulative Frequency Distributions for Residential Volumes from the PFT Data Base and the U.S. DOE's RECs. 1000 COMMON RETURN LAYOUT n' \.:= /--i.,,._ __ +--_____ _, fl4r Handler 8,1\LAMCED SUPPLY and RETURN LAYOUT l l 85"m 1 Zone 1 Zone2 Zone N 1 l j /Filter ........ " +--tir Handler Figure 17-3. Configuration for Residential Forced-air Systems 10-1 10-2 ' ' ' . ---... --. -.... -.............. --........ ---*-..... -. -.. -.. -....... -.. -.. -. ---. --.. (/) E :z;. 10-3 *c::; 0 w 10-4 > I:: 0 :;:::; *u; 10-5 0 0. Q) 0 10-s ' ' ' ---------. -. ----i----. -. -. ------. i-" -: : \; . -.......... -. -.: ... -. -. -.... -. -. -. -.......... -.t . --..... -. -... . : : ' ;\ : \ 1 o-7 __ ,__,......_+++,__--+--+-+-+-+-< ........ 0.001 O.G1 0.1 10 Particle Diameter (µm) Figure 17-4. Idealized Patterns of Particle Deposition Indoors ource: Adapted from Nazaroff and Cass, 1989.
~~SINGLE-ZONE I SYSTEM I I I TV\10-ZONE I~~
I

I

SYSTEM THREE-ZONE SYSTEM / -N-Zone System Defined by N (N+1) Airflows Figure 17-5. Air Flows for Multiple-zone Systems REFERENCES FOR CHAPTER 17 Andelman, J.B. (1990) Total exposure to volatile organic compounds in potable water. In: Ram, N, et al., eds. Significance and Treatment of Volatile Organic Compounds in Water Supplies. pp 485-504, Lewis Publishers, Chelsea, Ml. Andersson, B., K. Andersson, J. Sundell, and P.-A. Zingmark. (1993) Mass transfer of contaminants in rotary enthalpy heat exchangers. Indoor Air. 3:143-148. ASHRAE. (1988) ASHRAE Handbook: Equipment. American Society of Heating, Refrigerating, and Air-Conditioning Engineers. Atlanta, GA ASHRAE. (1993) ASHRAE Handbook: Fundamentals. American Society of Heating, Refrigerating, and Air-Conditioning Engineers. Atlanta, GA. ASTM. (1989) Standard laboratory test method for evaluation of carpet-embedded dirt removal effectiveness of household vacuum cleaners. Designation: F 608-89. American Society for Testing and Materials, Philadelphia, PA. ASTM. (1990) Test method for determining formaldehyde levels from wood products under defined conditions using a large chamber. Standard E 1333 90. American Society for Testing and Materials: Philadelphia. Axley, J.W. (1988) Progress toward a general analytical method for predicting indoor air pollution. in buildings: indoor air quality modeling phase Ill .report. NBSIR 883814. National Bureau of Standards, Gaithersberg, MD. Axley, J.W. (1989) Multi-zone dispersal analysis by element assembly. Building and Environment. 24(2):113-130. Axley, J.W.; Lorenzetti, D. (1993) Sorption transport models for indoor air quality analysis. In: Nagda, N.L. Ed., Modeling of Indoor Air Quality and Exposure. ASTM STP 1205. Philadelphia, PA: American Society for Testing and Materials, pp. 105127. Baughman, A.V.; Gadgil, A.J.; Nazaroff, W.W. (1994) Mixing of a point source pollutant by natural convection flow within a room. Indoor Air. 4:114-122. Chang, J.C.S.; Guo, Z. (1992) Characterization of organic emissions from a wood finishing product --wood stain. Indoor Air. 2(3):146-53. Consumer Reports. (1982) Washing machines. Consumer Reports Magazine. 47(10). Consumer Reports. (1987) Dishwashers. Consumer Reports Magazine. 52(6).
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Grat, R.A. (1991) User manual NBS/AVIS CONTAM88. NISTIR 4585, Gaithersberg, MD: National Institute of Standards and Technology. Grat, R.A.; Clark, R. E. ( 1981) Air leakage characteristics and weatherization techniques for low-income housing. In: Proceedings of the American Society of Heating, Refrigerating and Air-Conditioning Engineers Conference. Thermal Performance of Exterior Envelopes of Buildings. ASHRAE SP28, Atlanta, GA, pp. 178-194 . . Hanley, J.T.; Ensor, D.S.; Smith, D.D.; Sparks, L.E. (1994) Fractional aerosol filtration efficiency of in-duct ventilation air cleaners. Indoor Air. 4(3):179-188. Hirvonen, A.; Pasanen, P.; Tarhanen, J.; Ruuskanen, J. (1995) Thermal desorption of organic compounds associated with settled household dust. Indoor Air. 5:255-264. Jennings, P.D.; Carpenter, C.E.; Krishnan, M.S. (1985) Methods for assessing exposure to chemical substances volume 12: methods for estimating the concentration of chemical substances in indoor air. EPA 560/5-85-016, U.S. Environmental Protection Agency, Office of Pesticides and Toxic Substances, DC. Jennings, P.D.; Hammerstrom, K.A.; Adkins, L.C.; Chambers, T.; Dixon, D.A. (1987) Methods for assessing exposure to chemical substances volume 7: methods for assessing consumer exposure to chemical substances. EPA 560/5-85-007, U.S. Environmental Protection Agency, Office of Pesticides and Toxic Substances, Washington, DC. Koontz, M.D.; Nagda, N.L. (1991) A multichamber model for assessing consumer inhalation exposure. Indoor Air. 1(4):593-605. Koontz, M.D.; Rector, H.E. (1995) Estimation of distributions for residential air Exchange rates, EPA Contract No. 68-D9-0166, Work Assignment No. 3-19, U.S. Environmental Protection Agency, Office of Pollution Preventioa and Toxics, Washington, DC. Koontz, M.D.; Rector, H.E.; Fortmann, R.C.; Nagda, N.L. (1988) Preliminary experiments in a research house to investigate contaminant 'migration in indoor air.* EPA 560/5-88.-004. U.S. Environmental Protection Agency, Office of Pesticides and Toxic Substances, Washington, DC. Layton, D.W.; Thatcher, T.L. (1995) Movement of outdoor particles to the indoor environment: An analysis of the Arnhem Lead Study. Paper No. 95-MP4.02. Annual Meeting of the Air and Waste Management Association, San Antonio, TX. '-.
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U.S. DOE. (1995) Housing characteristics 1993, Residential Energy Consumption Survey (RECS) Report No. DOE/EIA-0314 (93), Washington, DC: U.S. Department of Energy, Energy Information Administration. Versar. (1990) Database of perfluorocarbon tracer (PFT) ventilation measurements: description and user's manual. USEPA Contract No. 68-02-4254, Task No. 39. Washington, D.C: U.S. Environmental Protection Agency, Office of Toxic Substances. Wallace, L.A. (1996) Indoor particles: A review. J. Air and Waste Management Assoc. (46)2:98-126. Walton, G.N. (1993) CONTAM 93 User Manual. NISTIR 5385. Gaithersburg, MD: National Institute of Standards and Technology. Wilkes, C.R.;*small, M.J.; Andelman, J.B.; Giardino, N.J.; Marshall, J. (1992) Inhalation _ exposure model for volatile chemicals from indoor uses of water. Atmospheric Environment (26A)12:2227-2236. Wolkoff, P. ( 1995) Volatile organic compounds: sources, measurements, emissions, and the impact on indoor air quality. Indoor Air Supplement No. 3/95, pp 1-73. Wolkoff, P.; Wilkins, C.K. (1994) Indoor VOCs from household floor dust: comparison of headspace with desorbed VOCs; Method for VOC release determination. Indoor Air 4:248-254. Zinn, T.W.; Cline, D.; Lehmann, W.F. (1990) Long-term study of formaldehyde emission decay from particleboard. Forest Products Journal (40)6:15-18. DOWNLOADABLE TABLES FOR CHAPTER 17 The following selected tables are available for download as Lotus 1-2-3 worksheets. Table 17-1. Summary of Residential Volume Distributions [WK1, 1 kb] Table 17-9. Summary of Major Projects Providing Air Exchange Measurements in the PFT Database [WK1, 6 kb] Table 17-11. Distributions of Residential Air Rates by Climate Region and Season [WK 1 , 3 kb]}}

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