U.S. Environmental Protection Agency
National Center for Environmental Assessment
Office of Research and Development
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Table of Contents
EFH
Chapter 1 Introduction
Chapter 3 Drinking Water
Intake
Chapter 5 Inhalation
Route
Chapter 7 Body Weight
Studies
Chapter 9 Intake of Fruits
and Vegetables
Ld
A
Chapter 2 Variability and
Uncertainty
Chapter 4 Soil Ingestion
and Pica
Chapter 6 Dermal Route
Chapter 8 Lifetime
Chapter 10 Intake of Fish
and Shellfish
Chapter 11 Intake of
Meat and Dairy Products
Chapter 12 Intake of
Grain Products
Chapter 13 Intake Rates
for Various Home
Produced Food Items
Chapter 15 Activity
Factors
Chapter 17 Residential
Building Characteristics
Chapter 14 Breast Milk
Intake
Chapter 16 Consumer
Products
Glossary
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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 available 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.
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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.
m
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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 Characterization,"
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
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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 the SAB reviewers. Comments from the SAB
review have been incorporated into the current handbook.
Exposure Factors Handbook
August 1997
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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 recommended 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.
Michael A. Callahan
Director
National Center for Environmental Assessment
Washington Office
Exposure Factors Handbook
August 1997
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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
DESKTOP PUBLISHING
GRAPHICS
Patricia Wood
Linda Phillips
Aderonke Adenuga
Mike Koontz
Harry Rector
Charles Wilkes
Maggie Wilson
Susan Perry
WORD PROCESSING
Valerie Schwartz
Kathy Bowles
Jennifer Baker
CD-ROM PRODUCTION
Charles Peck
Exposure Assessment Division
Versar Inc.
Springfield, VA
Exposure Factors Handbook
August 1997
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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
Dr. Paul Lioy
Environmental Occupational Health
Sciences Institute
Piscataway, New Jersey
Dr. Maria Morandi
University of Texas School of Public
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
Exposure Factors Handbook
August 1997
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EFH
Federal Experts
Dr. Richard Ellis
U.S. Department of Agriculture
Washington, D.C.
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
Patricia Guenther
Beltsville Human Nutrition
Research Center
U.S. Department of Agriculture
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.
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 Medicine
Neil Klepeis
Information Systems & Services,
Inc.
Exposure Factors Handbook
August 1997
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EFH
Andrew Persily
National Institute of Standards &
Technologies
Barbara Petersen
Technical Assessment Systems,
Inc.
Thomas Phillips
Research Division
California Air Resources Board
Paul Price
ChemRisk
John Risher
Division of Toxicology
The Agency for Toxic Substances &
Disease Registry
John Robinson
University of Maryland
Peter Robinson
The Proctor & Gamble Company
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
Exposure Factors Handbook
August 1997
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EFH
The following individuals within EPA have reviewed an earlier draft of this document
and provided valuable comments:
OFFICE
REVIEWERS/CONTRIBUTORS
Office of Research and Development
Maurice Berry
Jerry Blancato
Elizabeth Bryan
Curtis Dary
Stan Durkee
Manuel Gomez
Wayne Marchant
Sue Perlin
James Quanckenboss
Glen Rice
Lance Wallace
Office of Emergency and Remedial
Jim Konz
Response
Office of Pollution, Pesticides and
Pat Kennedy
Toxic Substances
Cathy Fehrenbacker
Office of Water
Denis Borum
Helen Jacobs
Office of Air Quality Planning and
Warren Peters
Standards
EPA Regions
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 Moyafrom 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
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EFH
The EPA Office of Water made an important contribution by conducting an analysis of
the USDA Continuing Survey of Food Intakes by Individual (CSFII) 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
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Figure 1-2. Road Map to Exposure Factor Recommendations
RECOMMENDATIONS
SECTION / RATINGS TABLE
POPULATION
VOLUME
EXPOSURE ROUTE
CHAPTER
EXPOSURE FACTOR
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(All Routes)
Residential
Building Characteristics
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Figure 1-2. Road Map to Exposure Factor Recommendations
EXPOSURE ROUTE
EXPOSURE FACTOR
POPULATION
,IIAnTrr RECOMMENDATIONS
VOLUME CHAPTER SECTION / RATINGS TABLE
Ingestion -^tT-—
Drinking Water
Intake Rate
Fruit and Vegetable Intake Rate
Meat and Dairy Intake Rate
Homegrown Foods
- Breast milk Intake Rate
Fish and Shellfish Intake Rate
\ Soil Intake Rate
iS Grain Intake
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(All Routes)
Residential
Building Characteristics
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Figure 1-2. Road Map to Exposure Factor Recommendations
EXPOSURE ROUTE
Ingestion
EXPOSURE FACTOR
Drinking Water
Intake Rate
Fruit and Vegetable Intake Rate
Meat and Dairy Intake Rate
Homegrown Foods
Breast milk Intake Rate
Fish and Shellfish Intake Rate
Soil Intake Rate
Grain Intake
POPULATION
VOLUME
Adults
Children
Pregnant Women
High Activity
CHAPTER
RECOMMENDATIONS
SECTION / RATINGS TABLE
3.6/3-35
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(All Routes)
Residential
Building Characteristics
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Figure 1-2. Road Map to Exposure Factor Recommendations
EXPOSURE ROUTE
EXPOSURE FACTOR
POPULATION
VOLUME
CHAPTER
RECOMMENDATIONS
SECTION / RATINGS TABLE
Drinking Water
Intake Rate
Fruit and Vegetable Intake Rate
- Meat and Dairy Intake Rate
Various Demographic Groups — Age,
Region, Season, Urbanization, Race
II
9
9.3/9-30
^^"""11 Homegrown Foods
Ingestion •?- -
—— Breast milk Intake Rate
Fish and Shellfish Intake Rate
Soil Intake Rate
Grain Intake
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(All Routes)
Residential
Building Characteristics
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Figure 1-2. Road Map to Exposure Factor Recommendations
EXPOSURE ROUTE
Ingestion
EXPOSURE FACTOR
POPULATION
VOLUME
CHAPTER
RECOMMENDATIONS
SECTION / RATINGS TABLE
Drinking Water
Intake Rate
Fruit and Vegetable Intake Rate
Meat and Dairy Intake Rate —
Homegrown Foods
Breast milk Intake Rate
Fish and Shellfish Intake Rate
Soil Intake Rate
Grain Intake
Various Demographic Groups — Age,
Region, Season, Urbanization, Race
11
11.4/11-31
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(All Routes)
Residential
Building Characteristics
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Figure 1-2. Road Map to Exposure Factor Recommendations
EXPOSURE ROUTE EXPOSURE FACTOR
POPULATION
VOLUME
CHAPTER
RECOMMENDATIONS
SECTION / RATINGS TABLE
Drinking Water
Intake Rate
Fruit arid Vegetable Intake Rate
Various Demographic Groups — Age,
Meat and Dairy Intake Rate
——- Region, Season, Urbanization, Race
- — Homegrown Foods
ii
13
13.5/13-72
Ingestion
11
* —-— Breast milk Intake Rate
Fish and Shellfish Intake Rate
v Soil Intake Rate
Grain Intake
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(All Routes)
Residential
Building Characteristics
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Figure 1-2. Road Map to Exposure Factor Recommendations
EXPOSURE ROUTE
EXPOSURE FACTOR
POPULATION
VOLUME
CHAPTER
RECOMMENDATIONS
SECTION / RATINGS TABLE
Ingestion-; ___
Drinking Water
Intake Rate
Fruit and Vegetable Intake Rate
Meat and Dairy Intake Rate
Homegrown Foods
Nursing Infants
II
14.6/14-14
Breast milk Intake Rate
14
^ Fish and Shellfish Intake Rate
I Soil Intake Rate
So rain Intake
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(All Routes)
Residential
Building Characteristics
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Figure 1-2. Road Map to Exposure Factor Recommendations
EXPOSURE ROUTE
EXPOSURE FACTOR
POPULATION
VOLUME
CHAPTER
RECOMMENDATIONS
SECTION / RATINGS TABLE
Ingestion
Drinking Water
Intake Rate
Fruit and Vegetable Intake Rate
Meat and Dairy Intake Rate
Homegrown Foods
Breast milk Intake Rate
Fish and Shellfish Intake Rate
Soil Intake Rate
Grain Intake
Genera! Population
Freshwater Recreational
Marine Recreational
Subsistence
10
10
10
10
10.10.1/10-87
10.10.3/10-89
10.10.2/10-88
10.10.4/10-90
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(All Routes)
Residential
Building Characteristics
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Figure 1-2. Road Map to Exposure Factor Recommendations
EXPOSURE ROUTE
Ingestion
EXPOSURE FACTOR
Drinking Water
Intake Rate
Fruit and Vegetable Intake Rate
Meat and Dairy Intake Rate
Homegrown Foods
Breast milk Intake Rate
Fish and Shellfish Intake Rate
Soil Intake Rate
Grain Intake
POPULATION
VOLUME
CHAPTER
RECOMMENDATIONS
SECTION / RATINGS TABLE
Typical Children
Adults
Pica Children
Various Demographic Groups — Age,
Region, Season, Urbanization, Race
4.7/4-21
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(All Routes)
Residential
Building Characteristics
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Figure 1-2. Road Map to Exposure Factor Recommendations
EXPOSURE ROUTE
Ingestion
EXPOSURE FACTOR
Drinking Water
Intake Rate
Fruit and Vegetable Intake Rate
Meat and Dairy Intake Rate
Homegrown Foods
Breast milk Intake Rate
Fish and Shellfish Intake Rate
Soil Intake Rate
Grain Intake
POPULATION
VOLUME
CHAPTER
RECOMMENDATIONS
SECTION / RATINGS TABLE
Typical Children
Adults
Pica Children
Various Demographic Groups — Age,
Region, Season, Urbanization, Race
12
12.3/12-24
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(Ail Routes)
Residential
Building Characteristics
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Figure 1-2. Road Map to Exposure Factor Recommendations
RECOMMENDATIONS
SECTION / RATINGS TABLE
POPULATION
VOLUME
EXPOSURE ROUTE
CHAPTER
EXPOSURE FACTOR
Ingestion
Inhalation
Inhalation Rate
Adults
Children
High Activity
5.2.4/5-23
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(All Routes)
Residential
Building Characteristics
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EXPOSURE ROUTE
Figure 1-2. Road Map to Exposure Factor Recommendations
EXPOSURE FACTOR
POPULATION
VOLUME
¦
CHAPTER
¦
RECOMMENDATIONS/
RATINGS TABLE PAGE NOS.
Ingestion
Inhalation
Dermal
- Skin Surface Area
— Soil Adherence —
Adults
• Children
General Populationn
6.
6.
6-8/6-25
6-8/6-27
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(All Routes)
Residential
Building Characteristics
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Figure 1-2. Road Map to Exposure Factor Recommendations
RECOMMENDATIONS
SECTION / RATINGS TABLE
POPULATION
VOLUME
EXPOSURE ROUTE
CHAPTER
EXPOSURE FACTOR
Ingestion
Inhalation
Dermal
(All Routes) Body Wei9ht
Human Characteristics
Lifetime
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(All Routes)
Residential
Building Characteristics
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Figure 1-2. Road Map to Exposure Factor Recommendations
RECOMMENDATIONS
SECTION / RATINGS TABLE
POPULATION
VOLUME
EXPOSURE ROUTE
CHAPTER
EXPOSURE FACTOR
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
Body Weight
Lifetime
Adults
Children
7.3/7-12
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(All Routes)
Residential
Building Characteristics
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Figure 1-2. Road Map to Exposure Factor Recommendations
RECOMMENDATIONS
SECTION / RATINGS TABLE
POPULATION
VOLUME
EXPOSURE ROUTE
CHAPTER
EXPOSURE FACTOR
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
Body Weight
Lifetime
Adults
Children
8
8.2/8-3
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(All Routes)
Residential
Building Characteristics
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Figure 1-2. Road Map to Exposure Factor Recommendations
RECOMMENDATIONS
SECTION / RATINGS TABLE
POPULATION
VOLUME
EXPOSURE ROUTE
CHAPTER
EXPOSURE FACTOR
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
15.4.1/15-172
15.4.2/15-173
15.4.3/15-175
(All Routes)
Consumer Product Use
(All Routes)
Residential
Building Characteristics
(All Routes)
Activity Factors
Activity Patterns
Occupational Mobility
Population Mobility
Adults
Children
Adults
Adults
Children
15
15
15
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Figure 1-2. Road Map to Exposure Factor Recommendations
RECOMMENDATIONS
SECTION / RATINGS TABLE
POPULATION
VOLUME
EXPOSURE ROUTE
CHAPTER
EXPOSURE FACTOR
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
Frequency of Use
Amount Used
Ad u its
Adults
16
16.4
(All Routes)
Residential
Building Characteristics
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Figure 1-2. Road Map to Exposure Factor Recommendations
RECOMMENDATIONS
SECTION / RATINGS TABLE
POPULATION
VOLUME
EXPOSURE ROUTE
CHAPTER
EXPOSURE FACTOR
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(All Routes)
Residential
Building Characteristics
Water Use
Air Exchange Rates
House Volumes
Building Characteristics
General Population
17
17.6/17-32, 17-33
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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 non-
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
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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 harvest 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 and thermophoresis.
Diary study-Survey 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 potential 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 - The 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.
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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 specific 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).
Interzonal 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 (LTM) - 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.
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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 distribution 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. Repeated 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.
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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
YP(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 would 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 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.).
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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 of 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).
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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. Considerations Used to Rate Confidence in Recommended Values
Table 1-2. Summary of Exposure Factor Recommendations and Confidence Ratings
Table 1-3. Characterization of Variability in Exposure Factors
Table 1A-1. Procedures for Modifying IRIS Risk Values for Non-standard Populations
Figure 1-1. Schematic of Dose and Exposure: Oral Route
Figure 1-2. Road Map to Exposure Factor Recommendations
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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 suggestions 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 providing a consistent set of exposure factors to calculate
dose.
Purpose
•~Summarize data on human behaviors and characteristics affecting exposure
•[Recommend 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;
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• 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
m icroenviron-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 is 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.
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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 peer-
reviewed literature and final government reports. Internal or interim reports were
therefore avoided.
• Accessibility: Studies were preferred that the user could access in their entirety
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 on 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
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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 and interpretation of 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.
Kev 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 III, 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 users, but having fewer attributes, are
designated "relevant."
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Key vs. Relevant Studies
•CKey studies used to derive recommendations
•[Relevant 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 contaminant 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 number 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 and 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.
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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, it is 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 dose-response factors to estimate risk. Some of the exposure factors (e.g.,
life time, body weight) presented in this document are also used in generating dose-
response relationships. In order to develop risk estimates properly, assessors must use
dose-response relationships in a manner consistent with exposure conditions. Although,
it is beyond the scope of this document to explain in detail how assessors should 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 literature 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
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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
•[Recommendations based on data from single or multiple key studies
•[Variability and limitation of the data evaluated
•[Recommendations rated as low, medium, and high confidence
1. Key studies were evaluated in terms of both quality and relevance to specific popula-
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
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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, the 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,
lognormal) 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
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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 necessary 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
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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 which
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.
1.4. 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,
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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 (Dpot) over body weight and an averaging time.
i Total Potential Dose
pot Body Weight x Averaging Time
For cancer effects, where the biological response is usually described in terms of
lifetime probabilities, even though exposure does not 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
(Eqn. 1-2)
Where:
C = Contaminant Concentration
IR = Intake Rate
ED = Exposure Duration
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
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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 III, 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 calculating 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, the administered doses are usually
averaged over a day or a single event. For nonchronic noncancer 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.
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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 case, 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
risk is being evaluated is non-standard in some way, such as for children or for first-
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 1A 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
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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 individual 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 exposure)
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 appropriate 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.
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• 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., inconsistencies
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 comprehensive 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 CSFII data.
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1.6. ORGANIZATION
The handbook is organized into three volumes as follows:
Volume I - 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
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 of fish.
Provides factors for estimating exposure through
ingestion of meats and dairy products.
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Chapter 12
Chapter 13
Chapter 14
Volume III - Activity Factors
Chapter 15
Chapter 16
Chapter 17
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 III.
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APPENDIX 1A
RISK CALCULATIONS USING EXPOSURE FACTORS HANDBOOK DATA
AND DOSE-RESPONSE INFORMATION FROM THE
INTEGRATED RISK INFORMATION SYSTEM (IRIS)
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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 dose-
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 animal 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
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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 sub-
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 Sections
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 parameters 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.
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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 |jg/l, and was calculated from the slope
factor assuming the standard intake, lws, 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 10"6 x (1.4/2) = 5.8 x 10"6 per //g/l. The risk to the average individual is
then estimated by multiplying this by the average concentration in units of //g/l.
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 1 A-1, is (70/60)2'3 = 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 10"6 x
1.11 = 9.2 x 10"6 per //g/l. 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 are: 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, W, 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
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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,
lAp = (m3/day)p, and the intake in the population described in this handbook, lAE = (m3/day)E
is:
lAp = Iae x (WP/WE)2/3.
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 (lAp), that quantity must be included in the equation, as follows:
(Risk)p= (air unit risk)p x (air concentration)
= (air unit risk)s x (lAp/20) x (JOlW)213 x (air concentration)
= (air unit risk)s x [(lAE x (Wp/WE)2/3/20)] x (7O/W)2'3 x (air concentration)
= (air unit risk)s x (lAE/20) x (70/WE)2/3 x (air concentration)
In this equation the air unit risk from the IRIS data base (air unit risk)s, the air intake
data in the handbook for the populations where it is available (lAE) and the body weight of
that population (W6) 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 1 A-1 are sufficient.
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5. REFERENCES
Federal Register. (1992) Cross-species scaling factor for carcinogen risk assessments
based on equivalence of (mg/kg-day)3/4. 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 Information 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.
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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
review (e.g., they appear in peer review
journals).
The studies received limited peer review.
Accessibility
The studies are widely available to the
public.
The studies are difficult to obtain (e.g., draft
reports, unpublished data).
Reproducibility
The results can be reproduced or
methodology can be followed and
evaluated.
The results cannot be reproduced, the
methodology is hard to follow, and the
author(s) cannot be located.
Focus on factor of interest
The studies focused on the exposure factor
of interest.
The purpose of the studies was to
characterize a related factor.
Data pertinent to U.S.
The studies focused on the U.S.
population.
The studies focused on populations outside
the U.S.
Primary data
The studies analyzed primary data.
The studies are based on secondary
sources.
Currency
The data were published after 1990.
The data were published before 1980.
Adequacy of data collection period
The study design captures the
measurement of interest (e.g., usual
consumption patterns of a population).
The study design does not very accurately
capture the measurement of interest.
Validity of approach
The studies used the best methodology
available to capture the measurement of
interest.
There are serious limitations with the
approach used.
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
population of interest.
The study population is very different from
the population of interest.®
Variability in the population
The studies characterized variability in the
population studied.
The characterization of variability is limited.
Lack of bias in study design
(a high rating is desirable)
Potential bias in the studies are stated or
can be determined from the study design.
The study design introduces biases in the
results.
Response rates
In-person interviews
Telephone interviews
Mail surveys
The response rate is greater than 80
percent.
The response rate is greater than 80
percent.
The respnose rate is greater than 70
percent.
The response rate is less than 40 percent.
The response rate is less than 40 percent.
The response rate is less than 40 percent.
Measurement error
The study design minimizes measurement
errors.
Uncertainties with the data exist due to
measurement error.
Other Elements
Number of studies
The number of studies is greater than 3.
The number of studies is 1.
Agreement between researchers
The results of studies from different
researchers are in agreement.
The results of studies from different
researchers are in disagreement.
a Differences include age, sex, race, income, or other demographic parameters.
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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 L/day (average)
34 ml/kg-day/2.3 L/day (90th percentile)
Percentiles and distribution also included
Means and percentiles also included for pregnant
and lactating women
Medium
Medium
Total fruit intake rate
3.4 g/kg-day ( per capita average)
12.4 g/kg-day (per capita 95th percentile)
Percentiles also included
Means presented for individual fruits
Medium
Low
Total vegetable intake rate
4.3 g/kg-day ( per capita average)
10 g/kg-day (per capita 95th percentile)
Percentiles also included
Means presented for individual vegetables
Medium
Low
Total meat intake rate
2.1 g/kg-day ( per capita average)
5.1 g/kg-day (per capita 95th percentile)
Percentiles also included
Percentiles also presented for individual meats
Medium
Low
Total dairy intake rate
8.0 g/kg-day (per capita average)
29.7 g/kg-day (per capita 95th percentile)
Percentiles also included
Means presented for individual dairy products
Medium
Low
Grain intake
4.1 g/kg-day (per capita average)
10.8 g/kg-day (per capita 95th percentile)
Percentiles also included
High
Low in long-term upper percentiles
Breast milk intake rate
742 ml/day (average)
1,033 ml/day (upper percentile)
Medium
Medium
Fish intake rate
General PoDulation
20.1 g/day (total fish) average
14.1 g/day (marine) average
6.0 g/day (freshwater/estuarine)average
53 g/day (total fish) 95th percentile long-term
Percentiles also included
Servina size
129 g (average)
326 g (95th percentile)
Recreational marine analers
2 - 7 g/day (finfish only)
Recreational freshwater
8 g/day (average)
25 g/day (95th percentile)
Native American Subsistence PoDulation
70 g/day (average)
170 a/dav (95th Dercentilel
High
High
High
Medium
High
High
Medium
Medium
Medium
Medium
Low
-------
Table 1-2. Summary of Exposure Factor Recommendations and Confidence Ratings (continued)
EXPOSURE FACTOR
RECOMMENDATION
CONFIDENCE RATING
Home produced food intake
Total Fruits
2.7 g/kg-day (consumer only average)
11.1 g/kg-day (consumer only 95th percentile)
Percentiles also included
Total veaetables
2.1 g/kg-day (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 Droducts
14 g/kg-day (consumer only average)
44 g/kg-day (consumer only 95th percentile)
Percentiles also included
Medium (for means and short-
term distributions)
Low (for long-term distributions)
Inhalation rate
Children (<1 vearl
4.5 m3/day (average)
Children (1-12 vearsl
8.7 m3/day (average)
Adult Females
11.3 m3/day (average)
Adult Males
15.2 m3/day (average)
High
High
High
High
Surface area
Water contact (bathina and swimminal
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')
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)
High
High
Soil adherence
Use values presented in Table 6-16 depending on
activity and body part
(central estimates only)
Low
Soil ingestion rate
Children
100 mg/day (average)
400 mg/day (upper percentile)
Adults
50 mg/day (average)
Pica child
10 g/day
Medium
Low
Low
Life expectancy
75 years
High
Body weight for adults
71.8 kg
Percentiles also presented in tables 7-4 and 7-5
High
Body weights for children
Use values presented in Tables 7-6 and 7-7 (mean
and percentiles)
High
Body weights for infants (birth to 6
months')
Use values presented in Table 7-1 (percentiles)
High
-------
Table 1-2. Summary of Exposure Factor Recommendations and Confidence Ratings (continued)
EXPOSURE FACTOR
RECOMMENDATION
CONFIDENCE RATING
Showering/Bathing
Showerina time
High
10 min/day (average)
35 min/day (95th percentile)
(percentiles are also included)
Bathina time
High
20 min/event (median)
45 min/event (90th percentile)
Bathina/showerina freauencv
High
1 shower event/day
Swimming
Freauencv
High
1 event/month
Duration
High
60 min/event (median)
180 min/event (90th percentile)
Time indoors
Children Caaes 3-111
Medium
19 hr/day (weekdays)
17 hr/day (weekends)
Adults Caaes 12 and olderl
Medium
21 hr/day
Residential
High
16.4 hrs/day
Time outdoors
Children Caaes 3-111
Medium
5 hr/day (weekdays)
7 hr/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 m3 (average)
Medium
217 m3 (conservative)
Medium
Residential air exchange
0.45 (median)
Low
0.18 (conservative)
Low
-------
Table
-3. Characterization of Variability in Exposure Factors
Exposure Factors
Average
Upper percentile
Multiple Percentiles
Fitted Distributions
Drinking water intake rate
~
~
~
~
Total fruits and total vegetables intake
rate
~
~
Qualitative discussion for
long-term
~
Individual fruits and individual vegetables
intake rate
~
Total meats and dairy products intake
rate
~
~
Qualitative discussion for
long-term
~
Individual meats and dairy products
intake rate
~
Grains intake
~
~
~
Breast milk intake rate
~
~
Fish intake rate for general population,
recreational marine, recreational
freshwater, and native american
~
~
Serving size for fish
~
~
~
Homeproduced food intake rates
~
~
~
Soil intake rate
~
Qualitative discussion for
long-term
Inhalation rate
Surface area
Soil adherence
Life expectancy
Body weight
Time indoors
Time outdoors
Showering time
Occupational tenure
Population mobility
Residence volume
Residential air exchange
ssssssssssss
~
~
~
~
~
~
~
~
~
-------
Table 1A-1. Procedures for Modifying IRIS Risk Values for Non-standard Populations3"
IRIS Risk Measure
[Units]
IRIS Risk Measure is Proportional
to:b
Correction Factor (CF) for modifying
IRIS Risk Measures:0
Slope Factor
[per mg/(kg/day)]
(Ws)1/3 = (70)1/3
(Wp/70)1/3
Water Unit Risk
[per |jg/l]
lws/[(Ws)2'3] = 2/[(70)2/3]
(lwP)/2 x [70/(Wp)]2/3
Air Unit Risk:
A. Particles or aerosols
[per |jg/m3], air concentration by
weight
lAs/[(Ws)2'3] = 20/[(70)2/3]
(Iap)/20 x [70/(Wp)]2/3
Air Unit Risk:
B. Gases
[per parts per million], air
concentration by volume,
No explicit proportionality to body
weight or air intake is assumed.
1.0
ppm by volume is assumed to be
the effective dose in both animals
and humans.
a W= Body weight (kg)
lw = Drinking water intake (liters per day)
lA = Air intake (cubic meters per day)
b Ws, lws', lAs denote standard parameters assumed by IRIS
c Modified risk measure = (CF) x IRIS value
Wp, lwp, lAp denote non-standard parameters of the actual population
-------
Exposure
Chemical
Potential Applied
Dose Dose
Biologically
Effective
Dose
Internal
Dose
Metabolism
Organ
Mouth
G.I. Tract
Effect
Intake
Source: U.S. EPA, 1992a
Uptake
Figure 1-1. Schematic of Dose and Exposure: Oral Route
-------
Figure 1-2. Road Map to Exposure Factor Recommendations
RECOMMENDATIONS
SECTION / RATINGS TABLE
POPULATION
VOLUME
EXPOSURE ROUTE
CHAPTER
EXPOSURE FACTOR
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
EXPOSURE ROUTE
EXPOSURE FACTOR
POPULATION
,IIAnTrr RECOMMENDATIONS
VOLUME CHAPTER SECTION / RATINGS TABLE
Ingestion -^tT-—
Drinking Water
Intake Rate
Fruit and Vegetable Intake Rate
Meat and Dairy Intake Rate
Homegrown Foods
- Breast milk Intake Rate
Fish and Shellfish Intake Rate
\ Soil Intake Rate
iS Grain Intake
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
EXPOSURE ROUTE
Ingestion
EXPOSURE FACTOR
Drinking Water
Intake Rate
Fruit and Vegetable Intake Rate
Meat and Dairy Intake Rate
Homegrown Foods
Breast milk Intake Rate
Fish and Shellfish Intake Rate
Soil Intake Rate
Grain Intake
POPULATION
VOLUME
Adults
Children
Pregnant Women
High Activity
CHAPTER
RECOMMENDATIONS
SECTION / RATINGS TABLE
3.6/3-35
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
EXPOSURE ROUTE
EXPOSURE FACTOR
POPULATION
VOLUME
CHAPTER
RECOMMENDATIONS
SECTION / RATINGS TABLE
Drinking Water
Intake Rate
Fruit and Vegetable Intake Rate
- Meat and Dairy Intake Rate
Various Demographic Groups — Age,
Region, Season, Urbanization, Race
II
9
9.3/9-30
^^"""11 Homegrown Foods
Ingestion •?- -
—— Breast milk Intake Rate
Fish and Shellfish Intake Rate
Soil Intake Rate
Grain Intake
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
EXPOSURE ROUTE
Ingestion
EXPOSURE FACTOR
POPULATION
VOLUME
CHAPTER
RECOMMENDATIONS
SECTION / RATINGS TABLE
Drinking Water
Intake Rate
Fruit and Vegetable Intake Rate
Meat and Dairy Intake Rate —
Homegrown Foods
Breast milk Intake Rate
Fish and Shellfish Intake Rate
Soil Intake Rate
Grain Intake
Various Demographic Groups — Age,
Region, Season, Urbanization, Race
11
11.4/11-31
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
EXPOSURE ROUTE EXPOSURE FACTOR
POPULATION
VOLUME
CHAPTER
RECOMMENDATIONS
SECTION / RATINGS TABLE
Drinking Water
Intake Rate
Fruit arid Vegetable Intake Rate
Various Demographic Groups — Age,
Meat and Dairy Intake Rate
——- Region, Season, Urbanization, Race
- — Homegrown Foods
ii
13
13.5/13-72
Ingestion
11
* —-— Breast milk Intake Rate
Fish and Shellfish Intake Rate
v Soil Intake Rate
Grain Intake
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
EXPOSURE ROUTE
EXPOSURE FACTOR
POPULATION
VOLUME
CHAPTER
RECOMMENDATIONS
SECTION / RATINGS TABLE
Ingestion-; ___
Drinking Water
Intake Rate
Fruit and Vegetable Intake Rate
Meat and Dairy Intake Rate
Homegrown Foods
Nursing Infants
II
14.6/14-14
Breast milk Intake Rate
14
^ Fish and Shellfish Intake Rate
I Soil Intake Rate
So rain Intake
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
EXPOSURE ROUTE
EXPOSURE FACTOR
POPULATION
VOLUME
CHAPTER
RECOMMENDATIONS
SECTION / RATINGS TABLE
Ingestion
Drinking Water
Intake Rate
Fruit and Vegetable Intake Rate
Meat and Dairy Intake Rate
Homegrown Foods
Breast milk Intake Rate
Fish and Shellfish Intake Rate
Soil Intake Rate
Grain Intake
Genera! Population
Freshwater Recreational
Marine Recreational
Subsistence
10
10
10
10
10 10.1/10-87
10.10.3/10-89
10.10.2/10-88
10.10.4/10-90
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
EXPOSURE ROUTE
Ingestion
EXPOSURE FACTOR
Drinking Water
Intake Rate
Fruit and Vegetable Intake Rate
Meat and Dairy Intake Rate
Homegrown Foods
Breast milk Intake Rate
Fish and Shellfish Intake Rate
Soil Intake Rate
Grain Intake
POPULATION
VOLUME
CHAPTER
RECOMMENDATIONS
SECTION / RATINGS TABLE
Typical Children
Adults
Pica Children
Various Demographic Groups — Age,
Region, Season, Urbanization, Race
4.7/4-21
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
EXPOSURE ROUTE
Ingestion
EXPOSURE FACTOR
Drinking Water
Intake Rate
Fruit and Vegetable Intake Rate
Meat and Dairy Intake Rate
Homegrown Foods
Breast milk Intake Rate
Fish and Shellfish Intake Rate
Soil Intake Rate
Grain Intake
POPULATION
VOLUME
CHAPTER
RECOMMENDATIONS
SECTION / RATINGS TABLE
Typical Children
Adults
Pica Children
Various Demographic Groups — Age,
Region, Season, Urbanization, Race
12
12.3/12-24
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(Ail Routes)
Residential
Building Characteristics
-------
Figure 1-2. Road Map to Exposure Factor Recommendations
RECOMMENDATIONS
SECTION / RATINGS TABLE
POPULATION
VOLUME
EXPOSURE ROUTE
CHAPTER
EXPOSURE FACTOR
Ingestion
Inhalation
Inhalation Rate
Adults
Children
High Activity
5.2.4/5-23
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(All Routes)
Residential
Building Characteristics
-------
EXPOSURE ROUTE
Figure 1-2. Road Map to Exposure Factor Recommendations
EXPOSURE FACTOR
POPULATION
VOLUME
¦
CHAPTER
¦
RECOMMENDATIONS/
RATINGS TABLE PAGE NOS.
Ingestion
Inhalation
Dermal
- Skin Surface Area
— Soil Adherence —
Adults
• Children
General Populationn
6.
6.
6-8/6-25
6-8/6-27
(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
SECTION / RATINGS TABLE
POPULATION
VOLUME
EXPOSURE ROUTE
CHAPTER
EXPOSURE FACTOR
Ingestion
Inhalation
Dermal
(All Routes) Body Wei9ht
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
SECTION / RATINGS TABLE
POPULATION
VOLUME
EXPOSURE ROUTE
CHAPTER
EXPOSURE FACTOR
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
Body Weight
Lifetime
Adults
Children
7.3/7-12
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(All Routes)
Residential
Building Characteristics
-------
Figure 1-2. Road Map to Exposure Factor Recommendations
RECOMMENDATIONS
SECTION / RATINGS TABLE
POPULATION
VOLUME
EXPOSURE ROUTE
CHAPTER
EXPOSURE FACTOR
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
Body Weight
Lifetime
Adults
Children
8
8.2/8-3
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(All Routes)
Residential
Building Characteristics
-------
Figure 1-2. Road Map to Exposure Factor Recommendations
RECOMMENDATIONS
SECTION / RATINGS TABLE
POPULATION
VOLUME
EXPOSURE ROUTE
CHAPTER
EXPOSURE FACTOR
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
15.4.1/15-172
15.4.2/15-173
15.4.3/15-175
(All Routes)
Consumer Product Use
(All Routes)
Residential
Building Characteristics
(All Routes)
Activity Factors
Activity Patterns
Occupational Mobility
Population Mobility
Adults
Children
Adults
Adults
Children
15
15
15
-------
Figure 1-2. Road Map to Exposure Factor Recommendations
RECOMMENDATIONS
SECTION / RATINGS TABLE
POPULATION
VOLUME
EXPOSURE ROUTE
CHAPTER
EXPOSURE FACTOR
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
Frequency of Use
Amount Used
Ad u its
Adults
16
16.4
(All Routes)
Residential
Building Characteristics
-------
Figure 1-2. Road Map to Exposure Factor Recommendations
RECOMMENDATIONS
SECTION / RATINGS TABLE
POPULATION
VOLUME
EXPOSURE ROUTE
CHAPTER
EXPOSURE FACTOR
Ingestion
Inhalation
Dermal
(All Routes)
Human Characteristics
(All Routes)
Activity Factors
(All Routes)
Consumer Product Use
(All Routes)
Residential
Building Characteristics
Water Use
Air Exchange Rates
House Volumes
Building Characteristics
General Population
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) Statistical 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.
E P 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-
9/01 1F.
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
(CSFII) 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
REFERENCES FOR CHAPTER 2
Table 2-1. Four Strategies for Confronting Variability
Table 2-2. Three Types of Uncertainty and Associated Sources and Examples
Table 2-3. Approaches to Quantitative Analysis of Uncertainty
Ex^osureFactors^Iandbool^
AugustJJW^
-------
A
Volume I - General Factors
Chagter^^Variabilit^
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 (ADDpot) that was introduced in the
opening chapter of this handbook:
Contaminant Concentration x Intake Rate x Exposure Duration
ADDPot = „ ^ . ux— : — (Eqn. 2-1)
p Body Weight x Averaging Time
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;
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 (NRC, 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
Ex^osureFactors^Iandbool^
August 1997
-------
Volume I - General Factors
Chagter^^VariabiUty^^
A
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. In 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 (NRC, 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
Ex^osureFactors^Iandbool^
August 1997
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——— Volume I - General Factors
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
measurements. 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 (NRC, 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.
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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 even for males and females within
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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 value 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. In this case, the variability is characterized by the range between the extreme
values and a measure of central tendency. This 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 factors to values that maximize
exposure or dose - such an approach will almost always lead to an overestimate.
2.4. CONCERN ABOUT UNCERTAINTY
Why should the 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.
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Additional 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 theory required to make predictions on the
basis of causal inferences (Model Uncertainty).
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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. Screening-
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 quality, 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 results of
variability/uncertainty analysis are discussed in the next section.
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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 in 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.
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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 uncertainty 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 upper-
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?
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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 described further in the 1992 Exposure Guidelines.
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Table 2-1. Four Strategies for Confronting Variability
Strategy
Example
Comment
Ignore variability
Assume that all adults
weigh 70 kg
Works best when variability is small
Disaggregate the
variability
Develop distributions of
body weight for
age/gender groups
Variability will be smaller in each group
Use the average
value
Use average body weight
for adults
Can the average be estimated reliably given what
is known about the variability?
Use a maximum or
minimum value
Use a lower-end value
from the weight distribution
Conservative approach — can lead to
unrealistically high exposure estimate if taken for
all factors
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Table 2-2. Three Types of Uncertainty and Associated Sources and Examples
Type of Uncertainty
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
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Table 2-3. Approaches to Quantitative Analysis of Uncertainty
Approach
Description
Example
Sensitivity Analysis
Changing one input variable at a time while
leaving others constant, to examine effect on
output
Fix each input at lower (then upper) bound
while holding others at nominal values (e.g.,
medians)
Analytical Uncertainty Propagation
Examining how uncertainty in individual
parameters affects the overall uncertainty of
the exposure assessment
Analytically or numerically obtain a partial
derivative of the exposure equation with
respect to each input parameter
Probabilistic Uncertainty Analysis
Varying each of the input variables over
various values of their respective probability
distributions
Assign probability density function to each
parameter; randomly sample values from
each distribution and insert them in the
exposure equation (Monte Carlo)
Classical Statistical Methods
Estimating the population exposure
distribution directly, based on measured
values from a representative sample
Compute confidence interval estimates for
various percentiles of the exposure
distribution
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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 -258.
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
quantitative 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. EPA/600/8-86/009.
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Chapter 3 - Drinking Water Intake
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. Daily Total Tapwater Intake Distribution for Canadians, by Age Group
(approx. 0.20 L increments, both sexes, combined seasons)
Table 3-2. Average Daily Tapwater Intake of Canadians (expressed as milliliters per
kilogram body weight)
Table 3-3. Average Daily Total Tapwater Intake of Canadians, by Age and Season
(L/day)
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, L/day)
Table 3-5. Average Daily Tapwater Intake by Canadians, Apportioned Among Various
Beverages (both sexes, by age, combined seasons, L/day)
Table 3-6. Total Tapwater Intake (mL/day) for Both Sexes Combined
Table 3-7. Total Tapwater Intake (mL/kg-day) for Both Sexes Combined
Table 3-8. Summary of Tapwater Intake by Age
Table 3-9. Total Tapwater Intake (as percent of total water intake) by Broad Age
Category
Table 3-10. General Dietary Sources of Tapwater for Both Sexes
Table 3-11. Summary Statistics for Best-Fit Lognormal Distributions for Water Intake
Rates
Table 3-12. Estimated Quantiles and Means for Total Tapwater Intake Rates (mL/day)
Table 3-13. Assumed Tapwater Content of Beverages
Table 3-14. Intake of Total Liquid, Total Tapwater, and Various Beverages (L/day)
Table 3-15. Summary of Total Liquid and Total Tapwater Intake for Males and Females
(L/day)
Table 3-16. Measured Fluid Intakes (mL/day)
Table 3-17. Intake Rates of Total Fluids and Total Tapwater by Age Group
Table 3-18. Mean and Standard Error for the Daily Intake of Beverages and Tapwater by
Age
Table 3-19. Average Total Tapwater Intake Rate by Sex, Age, and Geographic Area
Table 3-20. Frequency Distribution of Total Tapwater Intake Rates
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Table 3-21. Mean Per Capita Drinking Water Intake Based on USDA, CSFII Data From
1989-91 (mL/day)
Table 3-22. Number of Respondents that Consumed Tapwater at a Specified Daily
Frequency
Table 3-23. Number of Respondents that Consumed Juice Reconstituted with Tapwater
at a Specified Daily Frequency
Table 3-24. Total Fluid Intake of Women 15-49 Years Old
Table 3-25. Total Tapwater Intake of Women 15-49 Years Old
Table 3-26. Total Fluid (mL/Day) Derived from Various Dietary Sources by Women Aged
15-49 Years
Table 3-27. Water Intake at Various Activity Levels (L/hr)
Table 3-28. Planning Factors for Individual Tapwater Consumption
Table 3-29. Drinking Water Intake Surveys
Table 3-30. Summary of Recommended Drinking Water Intake Rates
Table 3-31. Total Tapwater Consumption Rates From Key Studies
Table 3-32. Daily Tapwater Intake Rates From Relevant Studies
Table 3-33. Key Study Tapwater Intake Rates for Children
Table 3-34. Summary of Intake Rates for Children in Relevant Studies
Table 3-35. Confidence in Tapwater Intake Recommendations
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Chapter 3 - Drinking Water Intake
3. DRINKING WATER INTAKE
3.1. BACKGROUND
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 tapwater 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 source-
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.
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All studies on drinking water intake that are currently available are based on short-
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, upper-
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. To 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,
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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 tapwater 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
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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 mL/day and mL/kg-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
approximately 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 mL/day) 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
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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 size (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.
Rose berry and Burmaster (1992) - Log normal Distributions for Water Intake -
Roseberry and Burmaster (1992) fit lognormal distributions to the water intake data
reported by Ershow and Cantor (1989) and estimated population-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 rates 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 population 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.
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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 etal. (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 tapwater 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 in 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
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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 socio-
economic factors. For these reasons this study is not considered a key study in this
document.
International Commission on Radiological Protection (ICRP) (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 (75 females; 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
willingness 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 surveyed 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.
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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-day 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 composed 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
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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 source-
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 consumed (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
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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 with 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 upper
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
(CSFII). The data used to estimate mean per capita intake 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 income levels in the 48
conterminous states and Washington D.C. were included in the sample. A complex three-
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
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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 (1995) 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 one-
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 and 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
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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 would 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
Ershow etal. (1991)- Intake of Tapwater and Total Water by Pregnant and Lactatlng
Women - Ershow et al. (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 non-
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
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water intake for control, pregnant, and lactating women, respectively. Food accounted for
the remaining portion of total water intake.
The same advantages and limitations associated 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 used to determine the appropriate water
consumption needs. Consumption factors have been established for the following uses:
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August 1997
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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
factors 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 areas
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
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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 retrospective dietary
assessments generally produce moderate correlations with "reference data from the past."
A summary of the recommended values for drinking water intake rates is presented 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 and 3-8) expressed as mL/kg-day are
recommended in preference to the liters/day units. For adults, the mean and 90th
percentile values are 21 mL/kg-day 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 to 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
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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 the 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
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August 1997
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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
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Table 3-1. Daily Total Tapwater Intake Distribution for Canadians, by Age Group
(approx. 0.20 L increments, both sexes, combined seasons)
Amount Consumed3
L/day
5 and under
%
Aae GrouD Cvearsl
6-17
Number %
Number
1£
%
i and over
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 (L/day)a
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
SummerAA/inter
0.61
0.87
1.14
1.38
1.55
1.57
1.34
90th Percentile
SummerA/Vinter
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 Ministry of National Health and Welfare, 1981.
-------
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, L/day)
Work
Spare Time
Activity
Level"
Consumption
L/day
Number of Respondents
Consumption Number of Respondents
L/day
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, L/day)a
Under 3
3-5
Aae GrouD Cvearsl
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 L/day
Source: Canadian Ministry of National Health and Welfare, 1981.
-------
Table 3-6. Total Tapwater Intake (mL/day) for Both Sexes Combined3
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
0
80
240
332
640
800
*
O)
o
LO
o
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
CD
•sf
1702
742
406
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 to prepare foods and beverages."
* Value not reported due to insufficient number of observations.
Source: Ershow and Cantor, 1989.
-------
Table 3-7. Total Tapwater Intake (mL/kg-day) for Both Sexes Combined3
Number of
Observations
Age (years)
Actual
Count
Weighted
Count
Mean
SD
S.E. of
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
*
O)
o
LO
o
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
CD
•sf
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. Summary of Tapwater Intake by Age
Age Group
Intake (mL/day)
Intake (mL/kg-day)
Mean
10th-90th Percentiles
Mean
10th-90th 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 Categorya,b
Age (years)
Mean
1
5
10
Percentile Distribution
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 Sexesa,b
% of Tapwater
Age
(years)
Source
Mean
Standard
Deviation
5
25
50
75
95
99
<1
Foodc
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
Foodc
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
Foodc
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
Foodc
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+
Foodc
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
Foodc
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: Ershowand Cantor, 1989.
-------
Table 3-11. Summary Statistics for Best-Fit Lognormal Distributions for Water Intake Rates3
In Total Fluid
Group Intake Rate
(age in years) o_
0 < age <1 6.979 0.291 0.996
1 < age <11 7.182 0.340 0.953
11 < age <20 7.490 0.347 0.966
20 < age <65 7.563 0.400 0.977
65 < age 7.583 0.360 0.988
All ages 7.487 0.405 0.984
Simulated balanced population 7.492 0.407 1.000
In Total Tapwater
Group Intake
(age in years) u_ o_ R2
0 < age <1 5.587
1 < age <11 6.429
11 < age <20 6.667
20 < age <65 7.023
65 < age 7.088
All ages 6.870
Simulated balanced population 6.864
0.615
0.498
0.535
0.489
0.476
0.530
0.575
0.970
0.984
0.986
0.956
0.978
0.978
0.995
a These values (mL/day) 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 \pi + (0.6745 a)]
50 percentile intake rate = exp [pi\
25 percentile intake rate = exp \pi - (0.6745 a)]
2.5 percentile intake rate = exp [u - (1.96 a)]
Mean intake rate - exp [u + 0.5 a2)]
Source: Roseberry and Burmaster, 1992.
-------
Table 3-12.
Estimated Quantiles and Means for Total Tapwater Intake Rates (mL/day)a
Age Group
Percentile
Arithmetic
(years)
2.5
25
50
75
97.5
Average
0
-------
Table 3-13. Assumed Tapwater Content of Beverages
Beverage
%
Tapwater
Cold Water
100
Home-made Beer/Cider/Lager
100
Home-made Wine
100
Other Hot Water Drinks
100
Ground/Instant Coffee:3
Black
100
White
80
Half Milk
50
All Milk
0
Tea
80
Hot Milk
0
Cocoa/Other Hot Milk Drinks
0
Water-based Fruit Drink
75
Fizzy Drinks
0
Fruit Juice 1b
0
Fruit Juice 2b
75
Milk
0
Mineral Waterc
0
Bought cider/beer/lager
0
Bouaht Wine
0
3 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: Hopkins and Ellis, 1980.
-------
Table 3-14.
Intake of Total Liquid, Total Tapwater, and Various Beverages (L/day)
All Individuals
Consumers Only®
Beverage
Mean
Intake
Approx. Std.
Error of Mean
Approx. 95%
Confidence
Interval for
Mean
10 and 90
Percentiles
1 and 99
Percentiles
Percentage of
Total Number
of Individuals
Mean
Intake
Approx.
Std. Error
of Mean
Approx. 95%
Confidence
Interval for Mean
Total Liquid
1.589
0.0203
1.547-1.629
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
Drinks
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
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
Beverages
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
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 (L/day)
Beverage
Age
Number
Mean Intake
Approx. Std. Error of
Mean
Approx 95% Confidence
Interval for Mean
10 and 90 Percentiles
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
Tapwater
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
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/day)
Subject
Total Fluids
Milk
Tapwater
Water-Based
Drinks"
Adults ("normal" conditions)b
1000-2400
120-450
45-730
320-1450
Adults (high environmental
temperature to 32°C)
2840-3410
3256 ±
SD = 900
Adults (moderately active)
Children (5-14 yr)
3700
1000-1200
1310-1670
330-500
540-650
ca. 200
ca. 380
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 of Total Fluids and Total Tapwater by Age Group
Average Daily Consumption Rate (L/day)
Aae Group
Total Fluids3 Total Tapwater"
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 years
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 Pennington, 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
1 to 4
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 Intake,a,b
Group/Subgroup
Respondents
L/day
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).
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 Rates3
Consumption
Cumulative Frequency"
Rate (L/day)
Frequency" (%) (%)
< 0.80
20.6 20.6
0.81-1.12
21.3 41.9
1.13-1.44
20.5 62.4
1.45-1.95
19.5 81.9
>1.96
18.1 100.0
a 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, CSFII Data From 1989-91 (mL/day)
Sex and Age
Plain Drinking
Fruit Drinks
(years)
Water
Coffee
Tea
and Adesa
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
Male
2,163
604
582
569
216
87
25
65
Female
2,498
728
643
684
284
64
6
73
Refused
2
2
•
•
•
•
•
•
Aae (years)
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
HisDanic
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
EmDlovment
Full-time
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 Reaion
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
Dav of Week
Weekday
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
Anaina
No
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
Bronchitis/EmDhvsema
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
Male
2,163
897
590
451
124
35
17
33
Female
2,498
980
826
482
117
38
4
33
Refused
2
•
2
•
•
•
•
•
Aae (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
HisDanic
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
EmDlovment
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 Reaion
Northeast
1,048
440
297
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
Dav of Week
Weekday
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
210
53
13
3
11
Asthma
No
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
Anaina
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/EmDhvsema
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
mL/dav
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
mL/ka/dav
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
a Number of observations:
nonpregnant, nonlactating 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
Status3
Mean
Standard
Deviation
5
10
25
50
75
90
95
mL/dav
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
mL/ka/dav
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 dailv fluid intake that is taDwater (%1
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 =
Source: Ershow et al., 1991.
6,201); pregnant (n = 188); lactating (n
= 77).
-------
Table 3-26. Total Fluid (mL/Day) Derived from Various Dietary Sources by Women Aged 15-49 Years8
Sources
Control Women
Pregnant Women
Lactating Women
Meanb
Percentile
Meanb
Percentile
Meanb
Percentile
50
95
50
95
50
95
Drinking Water
583
480
1440
695
640
1760
677
560
1600
Milk and Milk Drinks
162
107
523
308
273
749
306
285
820
Other Dairy Products
23
8
93
24
9
93
36
27
113
Meats, Poultry, Fish, Eggs
126
114
263
121
104
252
133
117
256
Legumes, Nuts, and Seeds
13
0
77
18
0
88
15
0
72
Grains and Grain Products
90
65
257
98
69
246
119
82
387
Citrus and Noncitrus Fruit Juices
57
0
234
69
0
280
64
0
219
Fruits, Potatoes, Vegetables, Tomatoes
198
171
459
212
185
486
245
197
582
Fats, Oils, Dressings, Sugars, Sweets
9
3
41
9
3
40
10
6
50
Tea
148
0
630
132
0
617
253
77
848
Coffee and Coffee Substitutes
291
159
1045
197
0
955
205
80
955
Carbonated Soft Drinks0
174
110
590
130
73
464
117
57
440
Noncarbonated Soft Drinks0
38
0
222
48
0
257
38
0
222
Beer
17
0
110
7
0
0
17
0
147
Wine Spirits, Liqueurs, Mixed Drinks
10
0
66
5
0
25
6
0
59
All Sources
1940
NA
NA
2076
NA
NA
2242
NA
NA
0 Number of observations: nonpregnant, nonlactating controls (n = 6,201); pregnant (n = 188); lactating (n = 77).
b Individual means may not add to all-sources total due to rounding.
0 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.
-------
Table 3-27.
Water Intake at Various Activity Levels (L/hr)a
Room
Temperatureb (°F)
Activity Level
Hiah CO.15 ho/man1c
Medium CO.10 ho/man1c
Low (0.05 ho/man1c
No."
Intake
No.
Intake
No.
Intake
100
-
-
-
15
0.653
(0.75)
95 18
0.540
(0.31)
12
0.345
(0.59)
6
0.50
(0.31)
90 7
0.286
(0.26)
7
0.385
(0.26)
16
0.23
(0.20)
85 7
0.218
(0.36)
16
0.213
(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. Planning Factors for Individual Tapwater Consumption
Environmental Condition
Recommended Planning Factor (gal/day)' Recommended Planning Factor (L/day)a b
Hot
Temperate
Cold
3.0C
1.5d
2.0"
11.4
5.7
7.6
a 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 L/day.
c 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-hour 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.
8 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.
-------
Table 3-29. Drinking Water Intake Surveys
Study
Number of Individuals
Type of Water
Consumed
Time Period/ Survey
Type
Population Surveyed
Comments
KEY
Canadian Ministry of
National Health and
Welfare, 1981
970
Total tapwater
consumption
Weekday and weekend
day in both summer and
winter; estimation based
on sizes and types of
containers used
All ages; Canada
Seasonal data; includes many tapwater-
containing items not commonly surveyed;
possible bias because identification of
vessel size used as survey techniques;
short-term study
Ershow and Cantor,
1989
Based on data from
NFCS; approximately
30,000 individuals
Total tapwater; total
fluid consumption
3-day recall, diaries
All ages; large sample
representative of U.S.
population
Short-term recall data; seasonally
balanced data
Rosenberry and
Burmaster, 1992
Based on data from
Ershow and Cantor,
1989
Total tapwater; total
fluid consumption
3-day recall, diaries
All ages; large sample
representative of US
population
Short-term recall data; seasonally
balanced; suitable for Monte Carlo
simulations
RELEVANT
Cantor et al., 1987
5,258
Total tapwater; total
fluid consumption
1 week/usual intake in
winter based on recall
Adults only; weighted
toward older adults; U.S.
population
Based on recall of behavior from previous
winter; short-term data; population not
representative of general U.S. population
Gillies and Paulin,
1983
109
Total tapwater
consumption
24 hours; duplicate water
samples collected
Adults only; New Zealand
Based on short-term data
Hopkin and Ellis,
1980
3,564
Total tapwater, total
liquid consumption
1 week period, diaries
All ages; Great Britain
Short-term diary data
ICRP, 1981
Based on data from
several sources
Water and water-based
drinks; milk; total fluids
NAa
NAa
Survey design and intake categories not
clearly defined
NAS, 1977
Calculated average
based on several
sources
Average per capita
"liquid" consumption
NAa
NAa
Total tapwater not reported; population and
survey design not reported
-------
Table 3-29. Drinking Water Intake Surveys (continued)
Study
Number of Individuals
Type of Water Consumed
Time Period/ Survey
Type
Population Surveyed
Comments
Pennington, 1983
Based on NFCS and
NHANES II; approximately
30,000 and 20,000
participants, respectively
Total tapwater; total fluid
consumption
NFCS:24-hour recall
on 2-day dairy;
NHANES ll:24-hour
recall
NFCS:1 month to 97 years;
NHANES ll:6 months to 74
years; representative
samples of U.S. population
Based on short-term recall data
USDA, 1995
Based on 89-91 CSF11;
approximately 15,000
individuals
Plain drinking water,
coffee, tea, fruit drinks
and ades
1-day recall
All ages, large sample
representative of U.S.
population
Short-term recall data; seasonally
adjusted
U.S. EPA, 1984
Based on NFCS;
approximately 30,000
individuals
Tapwater; water based
foods and beverages;
soups; beverage
consumption
3-day recall, diaries
All ages; large sample
representative of U.S.
population
Short-term recall data; seasonally
balanced
U.S. EPA, 1995
Over 4,000 participants of
NHAPS
Number of glasses of
drinking water and juice
with tapwater
24-hour diaries
All ages, large
representative sample of
U.S. population
Does not provide data on the volume
of tapwater consumed
McNall and
Schlegel, 1968
Based on 2 groups of 8
subjects each
Tapwater
8-hour work cycle
Males between 17-25 years
of age; small sample; high
activity levels/hot climates
Based on short-term data
U.S. Army, 1983
NA
All fluids consumed to
satisfy body needs for
internal water; includes
soups, hot and cold
drinks and tapwater
NA
High activity levels/hot
climates
Study designed to provide water
consumption planning factors for
various activities and field conditions;
based on estimated amount of water
required to account for losses from
urination, perspiration, and respiration
a Not applicable.
-------
Table 3-30.
Summary of Recommended Drinking Water Intake Rates
Percentiles
Age Group/
Population
Mean
50th
90th
95th
Multiple
Fitted
Distributions
<1 year®
0.30 L/day
44 mL/kg-day
0.24 L/day
35 mL/kg-day
0.65 L/day
102 mL/kg-day
0.76 L/day
127 mL/kg-day
Tables 3-6,
3-7, and 3-
8
Table 3-11b
<3 years'
3-5 years'
1 -10 years®
11-19 years®
0.61 L/day
0.87 L/day
0.74 L/day
35 mL/kg-day
0.97 L/day
18 mL/kg-day
0.66 L/day
31 mL/kg-day
0.87 L/day
16 mL/kg-day
1.5 L/day
1.5 L/day
1.3 L/day
64 mL/kg-day
1.7 L/day
32 mL/kg-day
1.5 L/day
79.4 mL/kg-
day
2.0 L/day
40 mL/kg-day
Table3-3
Table3-3
Tables 3-6,
3-7, and 3-
8
Tables 3-6,
3-7, and 3-
8
Table 3-11b
Table 3-11b
Adults®
1.4 L/day
21 mL/kg-day
1.3 L/day
19 mL/kg-day
2.3 L/day
34 mL/kg-day
Tables 3-6,
3-7, and 3-
R
Table 3-11b
Pregnant Womend
Lactating Women d
Adults in High
Activity/Hot Climate
Conditions8
Active Adults'
1.2 L/day 1.1 L/day 2.2 L/day 2.4 L/day Table 3-25
18.3 mL/kg-day 16 mL/kg-day 35 mL/kg-day 40 mL/kg-day
1.3 L/day 1.3 L/day 1.9 L/day 2.2 L/day Table 3-25
21.4 mL/kg-day 21 mL/kg-day 35 mL/kg-day 37 mL/kg-day
0.21 to 0.65 L/hour, depending on ambient temperature and activity level; see Table 3-27.
6 L/day (temperate climate) to 11 L/day (hot climate); see Table 3-28.
a Source: Ershowand 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
-------
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
1.30a
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
Hopkins and Ellis, 1980
a 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
(years)
Mean
(L/day)
90th Percentile
(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
(L/day)
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
11-19 yrs
0.91
Roseberry and Burmaster, 1992
-------
Table 3-35. Confidence in Tapwater Intake Recommendations
Considerations
Rationale
Rating
Study Elements
• Level of peer review
The study of Ershow and Cantor (1989) had a thorough expert
High
panel review. Review procedures were not reported in the
Canadian study; it was a government report. Other reports
presented are published in scientific journals.
• Accessibility
The two monographs are available from the sponsoring
High
agencies; the others are library-accessible.
• Reproducibility
Methods are well-described.
High
• Focus on factor of interest
The studies are directly relevant to tapwater.
High
• Data pertinent to U.S.
See "representativeness" below.
NA
• Primary data
The two monographs used recent primary data (less than one
High
week) on recall of intake.
• Currency
Data were all collected in the 1978 era. Tapwater use may
Low
have changed since that time period.
• Adequacy of data collection
These are one- to three-day intake data. However, long term
Medium
period
variability may be small. Their use as a chronic intake
measure can be assumed.
• Validity of approach
The approach was competently executed.
High
• Study size
This study was the largest monograph that had data for 11,000
High
individuals.
• Representativeness of the
The Ershow and Cantor (1989) and Canadian surveys were
High
population
validated as demographically representative.
• Characterization of
The full distributions were given in the main studies.
High
variability
• Lack of bias in study design
Bias was not apparent.
High
(high rating is desirable)
• Measurement error
No physical measurements were taken. The method relied on
Medium
recent recall of standardized volumes of drinking water
containers, and was not validated.
Other Elements
• Number of studies
There were two key studies for the adult and child
High for adult and
recommendations. There were six other studies for adults,
children.
one study for pregnant and lactating women, and two studies
Low for the other
for high activity/hot climates.
recommended
subpopulation values.
• Agreement between
This agreement was good.
High
researchers
Overall Rating
The data are excellent, but are not current.
Medium
-------
REFERENCES FOR CHAPTER 3
American Industrial Health Council (AIHC). (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. Estimated Daily Soil Ingestion Based on Aluminum, Silicon, and Titanium
Concentrations
Table 4-2. Calculated Soil Ingestion by Nursery School Children
Table 4-3. Calculated Soil Ingestion by Hospitalized, Bedridden Children
Table 4-4. Mean and Standard Deviation Percentage Recovery of Eight Tracer
Elements
Table 4-5. Soil and Dust Ingestion Estimates for Children Aged 1-4 Years
Table 4-6. Average Daily Soil Ingestion Values Based on Aluminum, Silicon, and
Titanium as Tracer Elements
Table 4-7. Geometric Mean (GM) and Standard Deviation (GSD) LTM Values for
Children at Daycare Centers and Campgrounds
Table 4-8. Estimated Geometric Mean LTM Values of Children Attending Daycare
Centers According to Age, Weather Category, and Sampling Period
Table 4-9. Distribution of Average (Mean) Daily Soil Ingestion Estimates Per Child for
64 Children (mg/day)
Table 4-10. Estimated Distribution of Individual Mean Daily Soil Ingestion Based on Data
for 64 Subjects Projected Over 365 Days
Table 4-11. Estimates of Soil Ingestion for Children
Table 4-12. Estimated Soil Ingestion Rate Summary Statistics and Parameters for
Distributions Using Binder et al. (1986) Data with Actual Fecal Weights
Table 4-13. Tukey's Multiple Comparison of Mean Log Tracer Recovery in Adults
Ingesting Known Quantities of Soil
Table 4-14. 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)
Table 4-15. Soil Ingestion Rates for Assessment Purposes
Table 4-16. Estimates of Soil Ingestion for Adults
Table 4-17. 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)
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Chapter 4 - Soil Ingestion and Pica
Table 4-18. Daily Soil Ingestion Estimation in a Soil-Pica Child by Tracer and by Week
(mg/day)
Table 4-19. Ratios of Soil, Dust, and Residual Fecal Samples in the Pica Child
Table 4-20. Soil Intake Studies
Table 4-21. Confidence in Soil Intake Recommendation
Table 4-22. Summary of Estimates of Soil Ingestion By Children
Table 4-23. Summary of Recommended Values for Soil Ingestion
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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 adhere 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
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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 useful 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:
Ti,e =
fie x F,
S,;e
(Eqn. 4-1)
where
Ti,e
= estimated soil ingestion for child i based on element e (g/day);
fi,e
= concentration of element e in fecal sample of child i (mg/g);
Fi
= fecal dry weight (g/day); and
Si,e
= concentration of element e in child i's yard soil (mg/g).
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.,
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>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 etal. (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 etal. (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. Twenty-
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 11,620 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 (LTM), 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 LTM 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 amount of soil ingested cannot be higher than the lowest estimate for the
individual 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 LTM 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
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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 LTM
(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 Clausing 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 background 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 tracer 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
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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 calculate 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 overestimated soil intake because of the 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 1 years: Population-Based Estimates Using Aluminum, Silicon,
and Titanium as Soil Tracer Elements - Davis et al. (1990) also used a mass-
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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 southeastern 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:
(DWf +
DWp ) x (Ef + 2EU ) - (DWfd x Efd)
(Eqn. 4-2)
i,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 (wg/g);
Eu =
tracer amount in urine (wg/g);
DWfd =
food dry weight (g);
Efd =
tracer amount in food (ug/g); and
Esoil —
tracer concentration in soil (ug/g).
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 of time 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,
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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 one-
week period during the summer and may not be representative of long-term (i.e., annual)
patterns of intake.
Van Wijnen et al. (1990) - Estimated Soil Ingestion by Children - In a study by Van
Wi'jnen 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 Wijnen et al. (1990) measured three tracers (i.e., titanium, aluminum, and
AIR) in soil and feces and estimated soil ingestion based on the LTM. 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 Wijnen et al. (1990)
also reported geometric mean LTM values because soil intake rates were found to be
skewed and the log transformed data were approximately normally distributed. Geometric
mean LTM values were estimated to be 111 mg/day for children in daycare centers, 174
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 intake 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 Wijnen et al. (1990) suggest that the mean LTM value for
hospitalized infants represents background intake of tracers and should be used to correct
the soil intake rates based on LTM 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
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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 Wi'jnen 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 relatively 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-by-
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 samples 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.
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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 estimates 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
forTi (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
through 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
ingestion 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
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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 mass-balance 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 selection
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.
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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 increases 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 summaries 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., 1974) 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 Connecticut were included in the study. Lepow et al. (1975) used data
from the 1974 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
contribution 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
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with the 2 to 20 "sticky sweets," Day et al. (1975) estimated that intake of soil among
children 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 times a day and that all of the
dirt is removed each time and replaced with new dirt prior to subsequent mouthing
behavior, Duggan and Wlliams (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 on 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 the 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 area
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
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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 Soil 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 one-
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 Binder 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
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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:
Y = x e (_ai12*yr)
(Eqn. 4-3)
where:
Y, = adjusted mean soil ingestion (mg/day)
x = a constant
yr = average age (2 years)
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 (ANOVA) and
Tukey's multiple comparison methodologies were employed to identify differences in the
recoveries of the various tracers (Sedman and Mahmood, 1994).
From 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 (^ =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
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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 children 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).
AIHC 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 Intertracer 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
during 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.
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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 developed 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 estimates 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
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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 ingestion 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 re-
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.,
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May through October). The ingestion estimate was based on the assumption that a 50
//m/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 1 to 100 mg/day. According to Calabrese et al. (1987), these
values "are conjectural and based on fractional estimates" of earlier Center for Disease
Control (CDC) estimates. In an evaluation of the scientific literature concerning soil
ingestion rates for children and adults (Krablin, 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 sterilized 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.
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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
The 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 soN 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) than 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, lllingworth 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 pregnant women, and 3 percent in nonpregnant women. However, "dirt" was
not clearly defined. The Bruhn and Pangborn (1971) study was conducted among 91 non-
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 Wi'jnen et
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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 Soil Pica Behavior and Quantification of Soil
Ingestion - Calabrese et al. (1991) estimated that upper range soil ingestion values may
range from approximately 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
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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 fecal 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
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Volume I - General Factors
Cha^t^^^SMAn^estionand^c^
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 when 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.
Soil 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 highest 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
of time 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 1,432 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
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Volume I - General Factors
Cha^ter^^SoUIn^estionandPic^
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 mg/day. 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.
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August 1997
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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
(mg/day)
(mg/day)
(mg/day)
(mg/day)
(mg/day)
(mg/day)
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
Cmo/davl
Cma/davl
Cma/davl
Cma/davl
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
L8
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: AdaDted from Clausina et al. 1987.
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Table 4-3. Calculated Soil Ingestion by Hospitalized, Bedridden Children
Soil Ingestion as
Soil Ingestion as
Calculated from Ti
Calculated from Al
Limiting Tracer
Child
SamDle
Cmo/davl
(ma/davl
(ma/davl
1
G5
3,290
57
57
G6
4,790
71
71
2
G1
28
26
26
3
G2
6,570
94
84
G8
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: AdaDted from Clausina et al. 1987.
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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: Adapted from Calabrese et al., 1989.
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Table 4-5. Soil and Dust Ingestion Estimates for Children Aged 1-4 Years
Tracer Element
Intake (mg/day)a
Mean
Median
SD
95th
Percentile
Maximum
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
3.597
a Corrected for Tracer Concentrations in Foods
Source: Adapted from Calabrese et al.. 1989.
-------
Table 4-6.
Average Daily Soil Ingestion Values Based on Aluminum, Silicon, and Titanium as Tracer Elements3
Element
Mean
(mg/d)
Median
(mg/d)
Standard Error of the
Mean
(mg/d)
Range
(mg/d)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: Adapted from Davis et al., 1990.
-------
Table 4-7. Geometric Mean (GM) and Standard Deviation (GSD) LTM Values
for Children at Daycare Centers and Campgrounds
Daycare Centers Campgrounds
Age (yrs) Sex n GM |_TM GSD LTM n GM LTM GSD LTM
(mg/day) (mg/day) (mg/day) (mg/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
162a
111
1.60
-v]
°0
174
1.73
a 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 LTM Values of Children Attending Daycare Centers
According to Age, Weather Category, and Sampling Period
First Sampling Period
Second Sampling Period
Weather Category
Age (years)
Estimated Geometric Mean
Estimated Geometric Mean
LTM Value
LTM Value
n
(ma/davl
n (ma/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.
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Table 4-9. Distribution of Average (Mean) Daily Soil Ingestion Estimates Per Child for 64 Children3 (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: Stanekand Calabrese, 1995a.
-------
Table 4-10. Estimated Distribution of Individual Mean Daily Soil Ingestion Based on
Data for 64 Subjects Projected Over 365 Days3
Range
1 - 2,268 mg/db
50th Percentile (median)
75 mg/d
90th Percentile
1,190 mg/d
95th Percentile
1.751 ma/d
a 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
(mg/day)
Activity
Content
(mg/day)
Youna Child (2.5 Years Oldl
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 Oldl
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 (mg/day)
Trace Element Basis
A1
Si Ti
MEAN3
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
a MEAN = arithmetic average of soil ingestion based on aluminum and silicon.
Source: Thompson 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
(mq/dav)
Age Adjusted Mean
(mq/dav)
Calabrese et al., 1989 Study
Aluminum
153
160
Silicon
154
161
Titanium
218
228
Vanadium
459
480
Yttrium
85
Davis et al., 1990 Study
89
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( 0112*yr), 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 Ingestion Estimate (mg/day)a
Negative Error
Lack of Fecal
Sample on Final
Other
Total Negative
Total Positive
Original
Adjusted
Study Day
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
a 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
Receptor Age
Setting
Soil Load on
Hands
(mg/cm2)
Soil Exposure
Ingestion Rate
(mg/hr)
Suggested
Exposure
Durations
(hr/yr)
Average Daily Soil
Ingestion
(mg/day)
Pica Child
...
1,000
200
500
2.5 yrs
Outdoor
0.5
20
1,000
50
Indoor
0.4
3
Remaining3
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
Source: Sheppard, 1995
3,760 hours/year minus the outdoor time.
-------
Table 4-16.
Estimates of Soil Ingestion for Adults
Scenarios
Media
Exposure
(mg/dav)
Days/Year
Activity
Fraction Soil
Content
Annual Average Soil
Intake
(mg/dav)
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
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
Week 2
Tracer Estimated Soil Estimated Soil
Inaestion
Inaestion
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/AI
11.318
10.207
19.520
100
13.
Ba/AI
10.182
9.778
8.692
73
14.
Si/AI
8.045
6.481
0.562
81
15.
V/AI
0.793
0.487
1.342
100
16.
Si/V
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
Studv
Studv Tvne
Number of
Observations
Ane
Population Studied
Comments
CHILDREN KEY STUDIES:
Binder et al., 1986
Tracer study using aluminum, silicon,
and titanium
59 children
1-3 years
Children living near lead
smelter in Montana
Did not account for tracer in food
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
aluminum, barium, manganese, silicon,
titanium, vanadium, ytrium, and
zirconium
64 Children
1-4 years
Children from greater
Amherst area of
Massachusetts; highly-
educated parents
Corrected for tracer in food and
medicine; study conducted over
two-week period; used adults to
validate methods; one pica child in
study group.
Clausing et al., 1987
Tracer study using aluminum, acid
insoluble residue, and titanium
18 nursery school
children; 6
hospitalized
children
2-4 years
Dutch children
Did not account for tracer in food
and medicines; used tracer-based
intake rates for hospitalized
children as background values;
short-term study conducted over 5
days
Davis et al., 1990
Tracer - mass balance study using
aluminum silicon and titanium
104 children
2-7 years
Children from 3-city area
in Washington State
Corrected for tracer in food and
medicine; short-term study
conducted over seven-day period;
collected information on
demographic characteristics
affecting soil intake.
Stanek and Calabrese,
1995a
Adjusted soil intake estimates
64 children
1-4 years
Same children as in
Calabrese et al., 1989
Based on data from Calabrese et
al., 1989
Stanek and Calabrese,
1995b
Recalculated intake rates based on three
previous mass-balance studies using the
Best Tracer Method
164 children
6 adults
1-7 years
25-41 years
Children from three
mass-balance studies
Based on studies of Calabrese et
al., 1989; Davis et al., 1990; and
Calabrese et al., 1990.
Van Wi'jnen et al., 1990
Tracer study using aluminum, acid
insoluble residue, and titanium
292 daycare
children; 78
campers; 15
hospitalized
children
1-5 years
Dutch children
Did not account for tracer in food
and medicines; used tracer-based
intake for hospitalized children as
background values; evaluated
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.,
1990
6 adults
21-41 years
Health adults
Used data from Calabrese et al.
(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,
1995
Evaluated errors in soil ingestion
estimates
64 children
1-4 years
Study population of
Calabrese et al.. 1989
Based on Calabrese et al., 1989
data.
-------
Table 4-20. Soil Intake Studies (continued)
Studv
Studv Tvne
Number of
Observations
Ane
Population Studied
Comments
CHILDREN RELEVANT STUDIES (continued):
Day et al., 1977
Measured dirt on sticky sweets
and assumed number of sweets
eaten per day
Not specified
Not specified
Not specified
Based on observations and crude
measurements.
Duggan and Williams, 1977
Measured soil on fingers and
observed mouthing behavior
Not specified
Not specified
Areas around London
Based on observations and crude
measurements.
Hawley, 1985
Assumed soil intake rates based
on nature and duration of activities
Not specified
Young children,
older children,
adults
Not specified
No data on soil intake collected;
estimates based on assumptions
regarding data from previous
studies.
Lepow et al., 1974; 1975
Measured soil on hands and
observed mouthing behavior
22 children
2-6 years
Urban children from
Connecticut
Based on observations over 3-6
hours of play and crude
measurement techniques.
Sedman and Mahmood, 1994
Adjusted data from earlier tracer-
mass balance studies to generate
mean soil intake rates for a 2-year
old child
64 children from
Calabrese et al.,
1989 study and 104
children from Davis et
al., 1990 study
Adjusted to 2-
year old child
Same children as in
Calabrese et al., 1989
and Davis et al., 1990
study
Based on data from Calabrese et al.,
1989 and Davis et al., 1990.
Sheppard, 1995
Provides estimates based on the
current literature on soil ingestion
from tracer methods and
recommends values for use in
assessments
Not specified
1 year-adults
(age not
specified)
Various
Presents mean estimates for
children and adults; provides
ingestion estimates for indoor and
outdoor activities based on Hawley,
1985.
Thompson and Burmaster,
1991
Re-evaluation of Binder et al.,
1986 data
59 children
1-3 years
Children living near
lead smelter in
Montana
Re-calculated soil intake rates from
Binder et al., 1986 data using actual
fecal weights instead of assumed
weights.
ADULT SOIL INTAKE STUDIES:
Hawley, 1985
Assumed soil intake rates based
on nature and duration of activities
Not specified
Young children,
older children,
adults
Not specified
No data on soil intake collected;
estimates based on assumptions
regarding data from previous
studies.
Calabrese et al., 1990
Measured excretory output after
ingestion of capsules with
sterilized soil
6 adults
21-41 years
Healthy adult
volunteers
Data used to validate the analytical
methodology used in the children's
study (Calabrese, 1989).
PICA STUDIES:
Calabrese et al., 1991
Tracer - mass balance
1 pica child
3.5 years
1 pica child from
greater Amherst area
of Massachusetts
Child was observed as part of the
Calabrese et al., 1989 study.
Calabrese and Stanek, 1992
Reanalysis of data from Calabrese
et al., 1991
1 pica child
3.5 years
1 pica child from
greater Amherst area
of Massachusetts
Distinguished between outdoor soil
ingestion and indoor dust ingestion
in a soil nica child.
-------
Table 4-21. Confidence in Soil Intake Recommendation
Considerations
Rationale
Ratina
Study Elements
Level of peer review
All key studies are from peer review literature.
High
Accessibility
Papers are widely available from peer review journals.
High
Reproducibility
Methodology used was presented, but results are difficult to
reproduce.
Medium
Focus on factor of interest
The focus of the studies was on estimating soil intake rate by
children; studies did not focus on intake rate by adults.
High (for children)
Low (for adults)
Data pertinent to U.S.
Two of the key studies focused on Dutch children; other
studies used children from specific areas of the U.S.
Medium
Primary data
All the studies were based on primary data.
High
Currency
Studies were conducted after 1980.
High
Adequacy of data collection
period
Children were not studied long enough to fully characterize day
to day variability.
Medium
Validity of approach
The basic approach is the only practical way to study soil
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.
Medium
Study size
The sample sizes used in the key studies were adequate for
children. However, only few adults have been studied.
Medium (for children)
Low (for adults)
Representativeness of the
population
The study population may not be representative of the U.S. in
terms of race, socio-economics, and geographical location;
Studies focused on specific areas; two of the studies used
Dutch children.
Low
Characterization of variability
Day-to-day variability was not very well characterized.
Low
Lack of bias in study design
(high rating is desirable)
The selection of the population studied may introduce some
bias in the results (i.e., children near a smelter site, volunteers
in nursery school, Dutch children).
Medium
Measurement error
Errors may result due to problems with absorption of the
tracers in the body and mismatching inputs and outputs.
Medium
Other Elements
Number of studies
There are 7 key studies.
High
Agreement between researchers
Despite the variability, there is general agreement among
researchers on central estimates of daily intake for children.
Medium
Overall
Rating
Studies were well designed; results were fairly consistent;
sample size was adequate for children and very small for
adults; accuracy of methodology is uncertain; variability cannot
be characterized due to limitations in data collection period.
Insufficient data to recommend upper percentile estimates for
both children and adults.
Medium (for children
- long-term central
estimate)
Low (for adults)
Low (for upper
Dercentilel
-------
Table 4-22. Summary of Estimates of Soil Ingestion by Children
Mean Cma/davl
191 mg/day soil and dust
combined
Upper Percentile Cmo/davl
References
Al
Si
AIRa
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
1,059"
159b
122
139
-
271
165
254
224
279
144
Stanek and Calabrese, 1995a
133c
21T
Stanekand Calabrese, 1995b
69-120d
Van Wi'jnen et al. 1990
Average
= 146 mg/day soil
383 mg/day soil
587 mg/day soil and dust
combined
AIR = Acid Insoluble Residue
Soil and dust combined
BTM
LTM: corrected value
-------
Table 4-23.
Summary of Recommended Values for Soil Ingestion
Population
Mean
Upper Percentile
Children
Adults
Pica child
100 mg/daya
50 mg/day
10 a/dav
400 mg/dayb
® 200 mg/day may be used as a conservative estimate of the mean (see text).
Study period was short; therefore, these values are not estimates of usual intake.
To be used in acute exposure assessments. Based on onlv one pica 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., III. (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, J.K. (1985) Assessment of health risk from exposure to contaminated 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.; Stemr, 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) [Letter to Jonathan Z. Cannon concerning soil ingestion rates.]
Denver, CO: Arco Coal Co.; October 13, 1989.
Lepow, M.L.; Bruckman, L.; Robino, 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.; Robino, R.; et al. (1975)
Investigations into sources of lead in the environment of urban children. Environ.
Res. 10:415-426.
Lourie, 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.; Lauwerys, 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, SC. (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 ofTCDD contaminated soil. Washington, DC: U.S.
Environmental Protection Agency, Office of Health and Environmental Assessment.
EPA 600/8-84-031.
Van Wijnen, J.H.; Clausing, P.; Brunekreff, B. (1990) Estimated soil ingestion by
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]
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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 Inhalation/Ventilation 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
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Volume I - General Factors
Chapter 5 - Inhalation
Table 5-18. Summary of Daily Inhalation Rates Grouped by Age and Activity Level
Table 5-19. Distribution Pattern of Predicted VR and EVR (equivalent ventilation rate)
for 20 Outdoor Workers
Table 5-20. Distribution Pattern of Inhalation Rate by Location and Activity Type for
20 Outdoor Workers
Table 5-21. Actual Inhalation Rates Measured at Four Ventilation Levels
Table 5-22. Confidence in Inhalation Rate Recommendations
Table 5-23. Summary of Recommended Values for Inhalation
Table 5-24. Summary of Inhalation Rate Studies
Table 5-25. Summary of Adult Inhalation Rates for Short-Term Exposure Studies
Table 5-26. Summary of Children's (18 years old or less) Inhalation Rates for
Long-Term Exposure Studies
Table 5-27. Summary of Children's Inhalation Rates for Short-Term Exposure Studies
Table 5A-1. Mean Minute Ventilation (VE, L/min) by Group and Activity for Laboratory
Protocols
Table 5A-2. Mean Minute Ventilation (VE, L/min) by Group and Activity for Field
Protocols
Table 5A-3. Characteristics of Individual Subjects: Anthropometric Data, Job
Categories, Calibration Results
Table 5A-4. Statistics of the Age/Gender Cohorts Used to Develop Regression
Equations for Predicting Basal Metabolic Rates (BMR)
Table 5A-5. Selected Ventilation Values During Different Activity Levels Obtained
FromVarious Literature Sources
Table 5A-6. 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
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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 Section 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 dose-
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
of "dose-response" relationships. When using IRIS for inhalation risk assessments, "dose-
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 currently
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
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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] / [BWx AT|] (Eqn. 5-1)
where:
ADD
= average daily dose (mg/kg-day);
C
= contaminant concentration in inhaled air (ug/m3);
IR
= inhalation rate (m3/day);
ED
= exposure duration (days);
BW
= 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. INHALATION 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
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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
temperature, 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
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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 potentail 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( VT).
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( VT) 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.
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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 VR-
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 et al. (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 1: 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
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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 most 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 exercises in everyday activities
may result 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 - Spier 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 walking. 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
corresponding predicted 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
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(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 ^day for moderate activities, and 0.98 m fclay for
heavy activities. For high school students the daily inhalation 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 size. The results may not be
representative of all children in these age groups. Another 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 measured variables: heart rate (HR),
breathing frequency (fB), and oxygen consumption (V )Q2 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 years 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 (jogging/
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, fB (breathing frequency), and VQ2 (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.
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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 fB were measured during each protocol. Most protocols
were conducted for 30 minutes. All the active field protocols were conducted twice.
During 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 males. Accurate predictions of IR across all
population groups and activity types were obtained by including body surface area (BSA),
HR, and fB in multiple regression analysis (Adams, 1993). Adams (1993) calculated BSA
from measured height and weight using the equation:
BSA = Height'0 725' x Weight'0 425' 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 etal. (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 included 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 slow walking, fast walking, jogging, lifting, and
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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
dictated 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 etal., 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 percentiles 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-
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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
(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 = E x H x VQ (Eqn. 5-3)
where:
VE =
ventilation rate (L/min 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 (L/min) 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
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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-NFCS 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 02/KJ 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 10
m3/day, respectively (Table 5-11). Inhalation rates were also calculated for active and
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 10 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
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males and 12 m3/day for females. 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 expenditures
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; light-
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 test subject (Layton, 1993).
The survey sample was 2,126 individuals (1,120 women and 1,006 men) ages 20-74 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
20-74 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 time-
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.
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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 obtained. 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.
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U.S. EPA (1985) - Development of Statistical 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
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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 (jogging 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
tended to underestimate their own physical activity levels at higher VR ranges. Shamoo
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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. (1991) - 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 rates 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 treadmill 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
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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 between-
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 VR/HR relationship may be biased.
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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 conducted 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 especially 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 presents 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
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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 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 L/min or 1.4 m3/hr); moderate/
medium exercise (VE= 24-43 L/min or 1.4-2.6 m3/hr); heavy exercise (VE= 43-63 L/min or
2.6-3.8 m3/hr); and very heavy exercise (VE> 64 L/min 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
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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 fclay 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 ?hr 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.
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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 "high-risk" subgroup
(Shamoo et al., 1991; Linn et al., 1992).
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Table 5-1. Calibration and Field Protocols for Self-Monitoring of Activities Grouped by Subject Panels
Panel
Calibration Protocol
Field Protocol
Panel 1 - Healthy Outdoor Workers -
15 female, 5 male, age 19-50
Panel 2 - Healthy Elementary School
Students - 5 male, 12 female, age
10-12
Panel 3 - Healthy High School
Students - 7 male, 12 female, age
13-17
Panel 4 - Adult Asthmatics, clinically
mild, moderate, and severe -15
male, 34 female, age 18-50
Panel 5 - Adult Asthmatics from 2
neighborhoods of contrasting 03 air
quality -10 male, 14 female, age 19-
46
Panel 6 - Young Asthmatics - 7 male,
6 female, age 11-16
Panel 7 - Construction Workers - 7
male, age 26-34
Laboratory treadmill exercise tests, indoor
hallway walking tests at different self-
chosen speeds, 2 outdoor tests consisted
of 1 -hour cycles each of rest, walking, and
jogging.
Outdoor exercises each consisted of 20
minute rest, slow walking, jogging and fast
walking
Outdoor exercises each consisted of 20
minute rest, slow walking, jogging and fast
walking
Treadmill and hallway exercise tests
Treadmill and hallway exercise tests
Laboratory exercise tests on bicycles and
treadmills
Performed similar exercises as Panel 2
and 3, and also performed job-related tests
including lifting and carrying a 9-kg pipe.
3 days in 1 typical summer week (included
most active workday and most active day off);
HR recordings and activity diary during
waking hours.
Saturday, Sunday and Monday (school day) in
early autumn; HR recordings and activity diary
during waking hours and during sleep.
Same as Panel 2, however, no HR recordings
during sleep for most subjects.
1 typical summer week, 1 typical winter week;
hourly activity /health diary during waking
hours; lung function tests 3 times daily; HR
recordings during waking hours on at least 3
days (including most active work day and day
off).
Similar to Panel 4, personal N02 and acid
exposure monitoring included. (Panels 4 and
5 were studied in different years, and had 10
subjects in common).
Similar to Panel 4, summer monitoring for 2
successive weeks, including 2 controlled
exposure studies with few or no observable
respiratory effects.
HR recordings and diary information during 1
typical summer work day.
Source: Linn et al.. 1992
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Table 5-2. Subject Panel Inhalation Rates by Mean VR, Upper Percentiles, and Self-Estimated Breathing Rates
Inhalation Rates (m3/hr)
Panel
Na
Mean VR
99th Percentile
Mean VR at Activity Levels
fm3/hrt
VR
Cm3/hr1b
Slow
Medium'
Fastc
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 Workers'
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 - Adults"
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 not 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
d Excluding subjects also in Panel 4.
Source: Linn et al.. 1992.
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Table 5-3. Distribution of Predicted IR by Location and Activity Levels for Elementary and High School Students
Inhalation Rates (m3/hr)
Age
(yrs)
Student
Location
% Recorded
Activity Level Time®
Percentile Rankingsb
Mean ± SD
1st
50th
99.9th
10-12
ELC
(nd=17)
Indoors
slow
medium
fast
49.6
23.6
2.4
0.84 ± 0.36
0.96 ± 0.42
1.02 ± 0.60
0.18
0.24
0.24
0.78
0.84
0.84
2.34
2.58
3.42
Outdoors
slow
medium
fast
8.9
11.2
4.3
0.96 ± 0.54
1.08 ± 0.48
1.14 ± 0.60
0.36
0.24
0.48
0.78
0.96
0.96
4.32
3.36
3.60
13-17
HSC
(nd=19)
Indoors
slow
medium
fast
70.7
10.9
1.4
0.78 ± 0.36
0.96 ± 0.42
1.26 ± 0.66
0.30
0.42
0.54
0.72
0.84
1.08
3.24
4.02
6.84c
Outdoors
slow
medium
fast
8.2
7.4
1.4
0.96 ± 0.48
1.26 ± 0.78
1.44 ± 1.08
0.42
0.48
0.48
0.90
1.08
1.02
5.28
5.70
5.94
a 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.
c EL = elementary school student; HS = high school student.
d N = number of students that participated in survey.
8 Highest single value.
Source:
SDier et al.. 1992.
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Table 5-4. Average Hours Spent Per Day in a Given Location and Activity Level for Elementary (EL) and High School (HS) Students
Student
(ELa. nc=17: HSb. Nc=19)
Location
Slow
Activity Level
Medium
Fast
Total Time Spent
(hrs/dav)
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: Spier et al., 1992.
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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®
(m3/day)
1st
50th
99.9th
EL (nc=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
Heavv
0.29
0.096
0.20
1.19
a 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).
c Number of elementary (EL) and high school students (HS)
Source: AdaDted from SDier et al.. 1992 (Generated usina data from Tables 5-3 and 5-41.
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Table 5-6. Summary of Average Inhalation Rates (m3/hr) by Age Group and Activity Levels for Laboratory Protocols
Age Group
Resting3
Sedentary
Light0
Moderate
Heavy8
Young Children'
Children
Adult Females'
Adult Males
0.37
0.45
0.43
0.54
0.40
0.47
0.48
0.60
0.65
0.95
1.33
1.45
DNP9
1.74
2.76
1.93
DNP
2.23
2.96'
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.
9 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.
' Adult females defined as adolescent, young to middle aged, and older adult females.
' 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.
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Table 5-7. Summary of Average Inhalation Rates (m3/hr) by Age Group and
Activity Levels in Field Protocols
Age Group
Light3
Sedentaryb
Moderate'
Young Children"1
DNP6
DNP
0.68
Children'
DNP
DNP
1.07
Adult Females9
1.10h
0.51
DNP
Adult Males'
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.
e DNP. Group did not perform this protocol or N was too small for appropriate
mean comparisons.
f 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.
' Adolescents not included in mean value since they did not perform this
activity.
Source: Adams, 1993.
-------
Table 5-8. Distributions of Individual and Group Inhalation/Ventilation Rate for Outdoor Workers
Ventilation Rate (VR) (m3/hr)
Percentile
Population Group and Subgroup®
Mean ± SD
1
50
99
All Subjects (nb = 19)
1.68 ± 0.72
0.66
1.62
3.90
Job
GCW7Laborers (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
Hospital 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) by Self-Estimated Breathing Rate
or Job Activity Category for Outdoor Workers
Self-Estimated
Breathing Rate (m3/hr)
Job Activity Category (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
GCW7Laborers (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
a GCW - general construction worker
b Trade - "Working at Trade" (i.e., tasks
Source: Linn et al., 1993
specific to the individual's job classification)
-------
Table 5-10. Comparisons of Estimated Basal Metabolic Rates (BMR) with Average Food-Energy Intakes for
Individuals Sampled in the 1977-78 NFCS
Cohort/Age Body Weight
BMRa
Energy Intake (EFD)
Ratio
(years)
kg
MJ d"1b
kcal d"1c
MJ d"1
kcal d"1
EFD/BMR
Children
Under 1
7.6
1.74
416
3.32
793
1.90
1 to 2
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 to 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
51 to 64
80
7.49
1788
9.04
2158
1.21
65 to 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
51 to 64
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. Daily Inhalation Rates Calculated from Food-Energy Intakes
Daily Inhalation Inhalation Rates
Rate3 Sleep METb Value Inactive0 Active0
Cohort/Ane A/ears')
Ld
(m3/dav1
M
Ae
Ff
(m3/dav1
(m3/dav1
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
13
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 (m3 1,000 L"1) for subjects under 9 years of
age and by 1.2 x H x VQ x (m3 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 L02/KJ or 0.21 L02/Kcal
VQ = Ventilation equivalent = 27 = geometric mean of VQs (unitless)
b MET = Metabolic equivalent
c 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.
e For individuals 9 years of age and older, 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)
9 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
(m302/MJ)
(m3/day)d
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
a Body weight was based on the average weights for age/gender cohorts in the U.S. population.
The BMRs (basal metabolic rate) are calculated using the respective body weights and BMR equations (see Appendix Table 5A-4).
c The values of the BMR multiplier (EFD/BMR) for those 1
3 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 < 1
3 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.
d Inhalation rate
= BMR x A x 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
w
»)
(M^day)
V e
(rrb/Say)
(nXftir)
Body
Weight
a
(kg)
BMRb
(KJ/hr)
Duration0
(hr/day)
Ed
(MJ/day)
vEe
(m3/day)
vEf
(m3/hr)
20-34
Sleep
Light
Moderate
Hard
Very Hard
Totals
1
1.5
4
6
10
76
76
76
76
76
320
320
320
320
320
7.2
14.5
1.2
0.64
0.23
24
2.3
7.0
1.5
1.2
0.74
17
3.1
9.4
2.1
1.7
1.0
17
0.4
0.7
1.7
2.6
4.3
62
62
62
62
62
283
283
283
283
283
7.2
14.5
1.2
0.64
0.23
24
2.0
6.2
1.4
1.1
0.65
11
2.8
8.3
1.8
1.5
0.88
15
0.4
0.6
1.5
2.3
3.8
35-49
Sleep
Light
Moderate
Hard
Very Hard
Totals
1
1.5
4
6
10
81
81
81
81
81
314
314
314
314
314
7.1
14.6
1.4
0.59
0.29
24
2.2
6.9
1.8
1.1
0.91
13
3.0
9.3
2.4
1.5
1.2
17
0.4
0.6
1.7
2.5
4.2
67
67
67
67
67
242
242
242
242
242
7.1
14.6
1.4
0.59
0.29
24
1.7
5.3
1.4
0.9
0.70
9.9
2.3
7.2
1.8
1.2
0.95
13
0.3
0.5
1.3
2.0
3.2
50-64
Sleep
Light
Moderate
Hard
Very Hard
Totals
1
1.5
4
6
10
80
80
80
80
80
312
312
312
312
312
7.3
14.9
1.1
0.50
0.14
24
2.3
7.0
1.4
0.94
0.44
12
3.1
9.4
1.9
1.3
0.6
16
0.4
0.6
1.7
2.5
4.2
68
68
68
68
68
244
244
244
244
244
7.3
14.9
1.1
0.5
0.14
24
1.8
5.4
1.1
0.7
0.34
9.4
2.4
7.4
1.4
1.0
0.46
13
0.3
0.5
1.3
2.0
3.3
65-74
Sleep
Light
Moderate
Hard
Very Hard
Totals
1
1.5
4
6
10
75
75
75
75
75
256
256
256
256
256
7.3
14.9
1.1
0.5
0.14
24
1.9
5.7
1.1
0.8
0.36
9.8
2.5
7.7
1.5
1.0
0.48
13
0.3
0.5
1.4
2.1
3.5
67
67
67
67
67
221
221
221
221
221
7.3
14.9
1.1
0.5
0.14
24
1.6
4.9
1.0
0.7
0.31
8.5
2.2
6.7
1.3
0.9
0.42
11
0.3
0.4
1.2
1.8
3.0
a Body weights were obtained from Najjar 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 VE (inhalation rate) was calculated by multiplying E (MJ/day) by H(0.05 m3 oxygen/MJ) by VQ (27)
f VE (m3/hr) was calculated by multiplying BMR (KJ/hr) x (MJ/1000 KJ) x MET x H (0.05 m3 oxygen/MJ) x VQ (27)
Source:
Layton, 1993.
-------
Table 5-14. Inhalation Rates for Short-Term Exposures
Activity Type
Sedentary Light Moderate Heavy
MET (BMR Multiplier)
1.2 £ 4? 10e
Inhalation Rate (m3/hhf,g
Male
CO
V
LO
d
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
b The BMRs for the age/gender cohorts were calculated using the respective body weights and the BMR equations (Appendix Table 5A-4).
c Range of 1.5 - 2.5.
d Range of 3 - 5.
e Range of >5 - 20.
f 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 L/min. Conversion to m3/hr was obtained as follows:
60 min m3 L
hr 1000L min
Source: Lavton. 1993.
Rest
Gender/Age (yrs) Weight BMR
(kg)a (MJ/day)
-------
Table 5-15. Daily Inhalation Rates Estimated From Daily Activities3
Inhalation Rate (IR)
Subject Resting Light Activity
(m3/hr) (m3/hr)
Daily Inhalation
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
1
DIR = — | IRjt:
T I "
IR, = Corresponding inhalation rate at ith activity
t, = Hours spent during the ith 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 (m3/hour)a
nb
Resting"
n
Lightd
n
Moderate8
n
Heavy'
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 adults
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, age 10 years
10
0.4
40
1.0
29
3.2
43
3.9
3 Values of inhalation rates for males, females, and children (male and female) presented in this table represent the mean of values reported for
each activity level in 1985. (See Appendix Table 5A-7 for a detailed listing of the data from U.S. EPA, 1985.)
b n = number of observations at each activity level.
c 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.
e 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.
9 Derived by taking the mean of the adult male and adult female values for each activity level.
Source: Adapted 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
Activity 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: Adapted 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
Subiect
Resting
Light
Moderate
Heavy
(m3/day)
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 Average0
5.60
6.71
2.96
0.85
16
Child
(age 6)
4.47
8.95
2.82
0.50
16.74
Child
(aae 10)
4.47
11.19
4.51
0.85
21.02
a Daily inhalation rate was calculated using the following equation:
1 K
IR = — i IR:t:
T I "
IR, = inhalation rate at ith activity (Table 5-18)
t, = hours spent per day during ith activity (Table 5-19)
k = number of activity periods
T = total time of the 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)a
EVRb (m3/hr/m2 body surface)
Self-Reported
Arithmetic
Geometric
Arithmetic
Geometric
Activity Level
Nc
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 Rankings, 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
a 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.
c 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
Location
Activity Type3
Self-reported
Activity Level
% of Time
Inhalation rate (m3/hr)b
± SD
% of Avg.c
Indoor
Essential
Sleep
Slow
Medium
Fast
28.7
29.5
2.4
0
0.42 ± 0.12
0.72 ± 0.36
0.72 ± 0.30
0
69 ± 15
106 ± 43
129 ± 38
0
Indoor
Non-essential
Slow
Medium
Fast
20.4
0.9
0.2
0.66 ± 0.36
0.78 ± 0.30
1.86 ± 0.96
98 ± 36
120 ± 50
278±124
Outdoor
Essential
Slow
Medium
Fast
11.3
1.8
0
0.78 ± 0.36
0.84 ± 0.54
0
117 ± 42
130 ± 56
0
Outdoor
Non-essential
Slow
Medium
Fast
3.2
0.8
0.7
0.90 ± 0.66
1.26 ± 0.60
2.82 ± 2.28
136 ± 90
213 ± 91
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 presented by Shamoo et al. (1991) in liters/mintue were converted to m3/hr.
c Statistic was calculated by converting each VR for a given subject to a percentage of her/his overall average.
Source: AdaDted from Shamoo et al.. (19911.
-------
Table 5-21.
Actual Inhalation Rates Measured at
Four Ventilation Levels
Mean Inhalation Rate3 (m3/hr)a
Subject
Location
Low Medium
Heavy
Very
Heavy
All subjects
Indoor 1.23 1.83
(Treadmill
3.13
4.13
Outdoor
Total
0.88 1.96
0.93 1.92
2.93
3.01
4.90
4.80
a Original data were presented in L/min. Conversion to m3/hr was obtained as
follows:
60 min x mJ x L
hr 1000L min
Source: Adapted from Shamoo et al., 1992
-------
Table 5-22.
Confidence in Inhalation Rate Recommendations
Considerations
Rationale
Ratina
Study
Elements
Peer Review
Studies are from peer reviewed journal articles and an EPA peer
reviewed report.
High
Accessibility
Studies in journals have wide circulation.
EPA reports are available from the National Technical Information
Service.
High
Reproducibility
Information on questionnaires and interviews were not provided.
Medium
Focus on factor of interest
Studies focused on ventilation rates and factors influencing them.
High
Data pertinent to U.S.
Studies conducted in the U.S.
High
Primary data
Both data collection and re-analysis of existing data occurred.
Medium
Currency
Recent studies were evaluated.
High
Adequacy of data collection period
Effort was made to collect data over time.
High
Validity of approach
Measurements were made by indirect methods.
Medium
Representativeness of the population
An effort has been made to consider age and gender, but not
systematically.
Medium
Characterization of variability
An effort has been made to address age and gender, but not
systematically.
High
Lack of bias in study design
Subjects were selected randomly from volunteers and measured in the
same way.
High
Measurement error
Measurement error is well documented by statistics, but procedures
measure factor indirectly.
Medium
Other Elements
Number of studies
Five key studies and six relevant studies were evaluated.
Agreement between researchers
There is general agreement among researchers using different
experimental methods.
High
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 Upper Percentile
Lona-term ExDosures
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
15.2m3/day
Short-term ExDosures
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
Heavy Activities
2.5 m3/hr
Note: See Tables 5-25. 5-26.
and 5-27 for reference studies.
-------
Table 5-24. Summary of Inhalation Rate Studies
Studv
Population Surveved
Survev Time Period
Data Generated
Limitations/Advantanes
KEY INHALATION RATE STUDIES:
Adams, 1993
n=160, ages 6-77; n = 40, ages 3-12.
Three 25 min phases of resting
protocol in the lab 6 mins of active
protocols in the lab. 30 min
phases of field protocols repeated
once.
Mean values of IR for adult
males and females and children
by their activity levels.
HR correlated poorly with IR.
Layton, 1993
NFCS survey: n~30,000; NHANES survey:
n~20,000
Time Activity survey: n~2,126
Daily IRs; IRs at 5 activity levels;
and IR for short-term exposures
at 5 activity levels.
Reported food biases in the dietary
surveys employed; time activity
survey was based on recall.
Linn et al., 1992
Panel 1-20 healthy outdoor workers, ages
19-50; Panel 2-17 healthy elementary
school students, ages 10-12; Panel 3-19
healthy high school students, ages 13-17;
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.
Late spring and early autumn. 3
diary days. Construction workers'
diary day.
Mean and upper estimates of IR;
Mean IR at 3 activity levels.
Small sample size; Calibration data
not obtained overfull HR range;
activities based on short-term diary
data.
Linn et al., 1993
n=19 construction workers.
(Mid-July-early November, 1991)
Diary recordings before work,
during work and break times
Distribution patterns of hourly IR
by activity level.
Small sample population size;
breathing rates subjective in nature;
activities based on short-term diary
Spier et al., 1992
n=36 students, ages 10-17.
(Late September - October)
Involved 3 consecutive days of
diary recording
Distribution patterns of hourly IR
by activity levels and location
Activities based on short-term diary
data; self-estimated breathing rate
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
females, adult males, children
(10 yrs), and infant (1 yr)
Validity and accuracy of data set
employed not defined; IR was
estimated not measured.
Shamoo et al.,
1990
n=9 volunteer workers ages 21-37, n=20
outdoor workers, 19-50 years old.
Involved 3-min indoor session/two
3-hr outdoor session at 4 activity
levels
No IR data presented.
No useful data were presented for
dose assessments studies.
Shamoo et al.,
1991
n=20 outdoor workers, ages 19-50
Diary recordings of three 24-hr.
periods within a week.
Distribution patterns of IR and
EVR by activity levels and
location.
Small sample size; short-term diary
data.
Shamoo et al.,
1992
n=9 non-sedentary subjects, ages 21-37.
3-min. intervals of indoor
exercises/two 3-hr outdoor
exercise sessions at 4 activity
levels.
Actual measured ventilation
rates presented.
Small sample size; training
approach may not be cost-effective;
VR obtained for outdoor workers
which are sensitive subpopulation.
U.S. EPA, 1985
Based on data from several literature
sources
Estimated IR for adult males,
adult females and children (ages
6 and 10) by various activity
levels.
Validity and accuracy of data set
employed not defined; IR was
estimated not measured.
Note: IR = inhalation rate: HR = heart rate: EVR = enuivalent ventilation rate.
-------
Rest
0.5
0.4
0.4
Table 5-25. Summary of Adult Inhalation Rates for Short-Term Exposure Studies
Arithmetic Mean (m3/hr)
Activity Level
Sedentary Light Moderate
0.5
0.6
0.4
1.4
1.2
0.7
0.6
1.0
2.4
1.8
1.4
1.5
1.6
High
3.3
3.6
3.0
3.0
Reference
Adams, 1993 (Lab protocols)
Adams, 1993 (Field protocols)
Layton, 1993 (Short-term
exposure)
Layton, 1993 (3rd approach)
Linn et al., 1992
-------
Table 5-26. Summary of Children's (18 years old or less) Inhalation Rates for Long-Term Exposure Studies3
Arithmetic Mean (m3/day)
Age
Males
Females
Males and
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
a 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
0.9
—
Adams, 1993 (Lab protocols)
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
Spier etal., 1992 (10-12 yrs)
--
--
0.8
1.0
11
Linn etal., 1992 (10-12yrs)
-------
Table 5A-1. Mean Minute Ventilation (VF, L/min) by Group and Activity for Laboratory Protocols
Activity
Young Children3
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
DNP
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 mph
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
comparisons
b 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 (VF, L/min) by Group and Activity for Field Protocols
Activity
Young
Children3
Children
Adult Females
Adult Males
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/31.89'
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
comparisons;
b 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 Categories, Calibration Results
Calibration
Subj. #
Age (years)
Ht. (in.)
Wt. (lb.)
Ethnic Group®
Job"
Site0
HR
Range"
r2e
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
Irn
Hosp
77-128
.95
1774
23
68
150
His
Car
Hosp
68-139
.98
1775
42
67
150
Wht
Irn
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
Irn
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, Irn = ironworker, Lab =
aborer
Site
Hosp = hospital buidling, Ofc = medical office complex. Calibration data
d HR range = range of heart rates in calibration study
e ? =
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
(BMR)
Gender/Age
BMR
Body
Weight
(V)
MJ d"1
±SD
>
o
(kg)
Nb
BMR Equation0
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
10 to < 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
10 to < 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)
N = number of subjects
c Body weight (bw) in kg
d coefficient of correlation
Source: Lavton. 1993.
-------
Table 5A-5.
Selected Ventilation Values During Different Activity 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
30 y; 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
113
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
Children
13
10 y; 140 cm L
16
300
4.8
24
600
14
14
males, 10-11 y
36.5
58
1330
71
15
males, 10-11 y; 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 a,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 (l/min); SA = surface area; cm L =
length/height; y = years of age; wk = week.
a Calculated from V* = fx VT.
b Crying.
Source: ICRP. 1981.
-------
Table 5A-6. Estimated Minute Ventilation Associated with Activity Level for Average Male Adult3
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
Heavy
Very heavy
55
63
72
Cross-country skiing; rock climbing; stair climbing
with load; playing squash or handball; chopping
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
(vears)
n
Ranqe
Mean
n
Ranqe
Mean
n
Ranqe
Mean
n
Ranqe
Mean
Infants
2
M/F
F
316
0.25 - 2.09
0.84
...
...
...
3
4
F
F
...
...
...
2
32.0 - 32.5
32.3
...
...
...
4
39.3 - 43.3
41.2
5
F
...
...
...
3
31.0-35.0
32.8
...
...
...
3
30.9 - 42.6
37.5
6
F
...
...
...
2
35.9 - 38.9
37.4
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
...
...
...
2
44.1 - 55.8
50.0
8
F
...
...
...
4
51.2-67.6
57.6
...
...
...
3
59.3 - 62.2
60.7
9
F
...
...
...
27
55.8 - 63.4
50.9
...
...
...
7
59.5 - 75.2
65.7
10
F
...
...
...
21
46.2 - 71.1
60.4
10
5.2-8.3
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
...
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
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
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
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
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
50
...
15.6
...
...
3
79.6- 132.2
102.5
17
F
...
...
...
2
91.9-95.3
93.6
12
5.8-9.0
7.3
...
12
40.0 - 63.0
48.6
3
89.4- 139.3
107.7
18
F
...
...
...
...
...
...
...
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 m3 /hour by multiplying by the conversion factor, 60 minutes/hour
1000 liters/m3
Source: Adapted from U.S. EPA, 1985.
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Biologically
Effective
Dose
Potential
Dose
Applied
Dose
Internal
Dose
Exposure
Organ
Chemical
Effect
Metabolism
Mouth / Nose
Lung
Intake Uptake
Figure 5-1. Schematic of Dose and Exposure: Respiratory Route
Source: U.S. EPA, 1992.
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REFERENCES FOR CHAPTER 5
Adams, W.C. (1993) Measurement of breathing rate and volume in routinely performed
daily activities, Final Report. California Air Resources Board (CARB) 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.; Finley, 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.
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Sallis, J.F.; Haskell, W.L.; Wood, P.D.; Fortmann, S.P.; Rogers, T.; Blair, S.N.;
Paffenbarger, Jr., R.S. (1985) Physical activity assessment methodology in the Five-
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 ventilation 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.
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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 Daily 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 [WK1, 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]
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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 Surface Area
6.4.2. Soil Adherence to Skin
REFERENCES FOR CHAPTER 6
APPENDIX 6A
Table 6-1. Summary of Equation Parameters for Calculating Adult Body Surface Area
Table 6-2. Surface Area of Adult Males in Square Meters
Table 6-3. Surface Area of Adult Females in Square Meters
Table 6-4. Surface Area of Body Part for Adults (m2)
Table 6-5. Percentage of Total Body Surface Area by Part for Adults
Table 6-6. Total Body Surface Area of Male Children in Square Meters
Table 6-7. Total Body Surface Area of Female Children in Square Meters
Table 6-8. Percentage of Total Body Surface Area by Body Part for Children
Table 6-9. Descriptive Statistics for Surface Area/BodyWeight (SA/WB) Ratios (m2/kg)
Table 6-10. Statistical Results for Total Body Surface Area Distributions (m2)
Table 6-11. Summary of Field Studies
Table 6-12. Geometric Mean and Geometric Standard Deviations of Soil Adherence by
Activity and Body Region
Table 6-13. Summary of Surface Area Studies
Table 6-14. Summary of Recommended Values for Skin Surface Area
Table 6-15. Confidence in Body Surface Area Measurement Recommendations
Table 6-16. Recommendations for Adult Body Surface Area
Table 6-17. Summary of Soil Adherence Studies
Table 6-18. 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
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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
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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
chemical 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 detailed 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 guide
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
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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, dermally absorbed average daily
dose can be estimated by (U.S. EPA, 1992b):
tf
ADD
BW x AT
(Eqn. 6-1)
where:
ADD = average daily dose (mg/kg-day);
DAevent = absorbed dose per event (mg/cm2-event);
EV = event frequency (events/day);
ED = exposure duration (years);
EF = exposure frequency (days/year);
SA = skin surface area available for contact (cm2);
BW = body weight (kg); and
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 DAevent 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 dermal 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.
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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 continuously, 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 contact 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, and 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
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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 that 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 using 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 total 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
rf
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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, 1985).
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 median 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 small 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 (height 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 increases.
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Phillips et at. (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 body weight (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 (1992) - 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 74 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.
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This formula is:
SA= 4W+7/W+90
(Eqn. 6-2)
where:
SA = Surface Area (m2); and
W = Weight (kg).
Formulae were compared and the effect of the correlation between height and weight on
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 random 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 Factors 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
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values. As such, 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 considered 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:
Surface Area (m2)
Men Women
Arms (includes upper arms and forearms) 0.228 0.210
Hands 0.084 0.075
Total area 0.312 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).
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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 cm2 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 and 6-3
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 discussion, 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
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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 factors.
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 //m. 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
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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 etal., 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.
Roels 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, lead 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 Dust and Hand Dust, in the Homes of Children - Que Hee et al. (1985) used soil
having particle sizes ranging from < 44 to 833 |jm 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 in 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
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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 <250 |jm and
<150 |jm. 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 minimal 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 approximately 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 |jm, 0.95 mg/cm2 for particle sizes less than 250 |jm, 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 most 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
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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 //m 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).
6.4. 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 recommendations 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 for adults 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
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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 straightforward
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 III, 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 6-7 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 characterize 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.
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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 seasonal
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
concern 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
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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).
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Appendix 6A
APPENDIX 6A
FORMULAE FOR TOTAL BODY SURFACE AREA
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APPENDIX 6A
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 = KW2/3 (Eqn. 6A-1)
where:
SA = surface area in square meters;
W = weight in kg; and
K = constant.
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 = an hH W;
(Eqn. 6A-2)
where:
SA = surface area in square meters;
H = height in centimeters; and
W = weight in kg.
The values of a0 (0.007182), a(0.725), and a2 (0.425) were estimated from a
sample of only nine individuals for whom surface area was directly measured. Boyd
(1935) 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
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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 area, height, and weight of all postnatal subjects listed in Boyd (1935). The
methods used to measure these subjects were coating (163 cases), surface integration
(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 H042246 W051456 (Eqn. 6A-3)
or in logarithmic form:
In SA= -3.75080 + 0.42246 In H + 0.51456 In W (Eqn. 6A-4)
where:
SA = surface area in square meters;
H = height in centimeters; and
W = weight in kg.
This prediction explains more than 99 percent of the variations in surface area
among the 401 individuals measured (Gehan and George, 1970).
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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 obtain 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 H,a1 W*2 e, (Eqn. 6A-5)
or in logarithmic form:
In (SA), = In a0 + a. In H, + a2 In W, + In e, (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, a-i, and a2 = parameters to be estimated; and
e, = 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 H0417 W0517 (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 0.00374. 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).
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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 a0 aa2
group of persons
All ages
401
0.02350
0.42246
0.51456
<5 years old
229
0.02667
0.38217
0.53937
> 5 - <20 years old
42
0.03050
0.35129
0.54375
> 20 years oldl
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, 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, and a2for the DuBois and DuBois
model. Their interest in making the DuBois and DuBois model more accurate resulted
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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 H03964 W05378 (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)
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The values for a0, a.,, 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 a0 a., 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 (m2)
Body Part
N
a„
Wa1
Ha2
P
R2
S.E.
Head
Female
Male
57
32
0.0256
0.0492
0.124
0.339
0.189
-0.0950
0.01
0.01
0.302
0.222
0.00678
0.0202
Trunk
Female
Male
57
32
0.188
0.0240
0.647
0.808
-0.304
-0.0131
0.001
0.001
0.877
0.894
0.00567
0.0118
Upper Extremities
Female
Male
57
48
0.0288
0.00329
0.341
0.466
0.175
0.524
0.001
0.001
0.526
0.821
0.00833
0.0101
Arms
Female
Male
13
32
0.00223
0.00111
0.201
0.616
0.748
0.561
0.01
0.001
0.731
0.892
0.00996
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
Male
12b
32
0.0131
0.0257
0.412
0.573
0.0274
-0.218
0.1
0.001
0.447
0.575
0.0172
0.0187
Lower Extremities'
Legs
Thighs
Lower legs
105
45
45
45
0.00286
0.00240
0.00352
0.000276
0.458
0.542
0.629
0.416
0.696
0.626
0.379
0.973
0.001
0.001
0.001
0.001
0.802
0.780
0.739
0.727
0.00633
0.0130
0.0149
0.0149
Feet
45
0.000618
0.372
0.725
0.001
0.651
0.0147
a SA = a0 Wa1 Ha2
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
Bodv Dart
5
10
15
25
50
75
85
90
95
S.E.a
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
0.935c
0.0118
Upper extremities
0.321
0.332
0.340
0.350
0.372
0.395
0.408
0.418
0.432c
0.00101
Arms
0.241
0.252
0.259
0.270
0.291
0.314C
0.328c
0.339c
0.354c
0.00387
Forearms
0.106
0.111
0.115
0.121
0.131
0.144c
0.151c
0.157c
0.166c
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
0.888c
0.00633
Legs
0.539
0.561
0.576
0.597
0.640
0.686c
0.714C
0.734c
0.762c
0.0130
Thighs
0.318
0.331
0.341
0.354
0.382
0.411c
0.429c
0.443c
0.463c
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
a Standard error for the 5-95 percentile of each body part.
b Trunk includes neck.
c 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.a
Total
1.45
1.49
1.53
1.58
1.69c
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
0.238c
0.243c
0.247c
0.253c
0.00996
Hands
0.0730
0.0746
0.0757
0.0777
0.0817
0.0868
0.0903
0.0927
0.0966=
0.0172
Lower extremities
0.564
0.582
0.595
0.615
0.657
0.704
0.592
0.357
0.233
0.121
0.736
0.623
0.379
0.243
0.126
0.757
0.645
0.394
0.249
0.129
0.796
0.00633
Legs
0.460
0.477
0.488
0.507
0.546
0.683c
0.0130
Thighs
0.271
0.281
0.289
0.300
0.326
0.421c
0.0149
Lower legs
0.186
0.192
0.197
0.204
0.218
0.261
0.0149
Feet
0.100
0.103
0.105
0.108
0.114
0.134
0.0147
a Standard error for the 5-95 percentile of each body part.
b Trunk includes neck.
c Percentile estimates exceed the maximum measured values upon which the equations are based.
Source: U.S. EPA, 1985.
-------
Table 6-4. Surface Area by Body Part for Adults (m2)
Men
Women
Body part
Na
Mean
(sd)b
Min.
Max.
N
Mean
(sd)
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
(0.104)
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 -
0.136
-
-
-
-
-
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
1.94c
(0.00374)d
1.66
2.28"
1.69c
(0.00374)d
1.45
2.09"
a number of observations.
b standard deviation.
c median (see Table 6-2).
d standard error.
8 percentiles (5th -
95th).
Source: Adapted from U.S. EPA, 1985.
-------
Table 6-5. Percentage of Total Body Surface Area by Part for Adults
Men Women
Body part
Na
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 Body Surface Area of Male Children
in Square Meters
a
Percentile
Age (yr)
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
precluded calculation of surface areas for this age group.
Estimated values calculated using NHANES II data.
Source: U.S
EPA. 1985.
-------
Table 6-7. Total Body Surface Area of Female Children in Square Meters3
Percentile
Age (yr)b
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. Percentage of Total Body Surface Area by Body Part for Children
N
Age fvrt M:F
Percent of Total
Head
Trunk
Arms
Hands
Legs
Feet
Mean
Min-Max
Mean Min-Max
Mean
Min-Max
Mean Min-Max
Mean
Min-Max
Mean Min-Max
< 1
1 <2
2 < 3
3 < 4
4 < 5
5 < 6
6 < 7
7 < 8
8 < 9
9< 10
10 < 11
11 < 12
12 < 13
13 < 14
14 < 15
15 < 16
16 < 17
17 < 18
2:0
1:1
1:0
0:5
1:3
1:0
0:2
1:0
1:0
1:0
1:0
18.2
16.5
14.2
13.6
13.8
13.1
12.0
8.74
9.97
7.96
7.58
18.2-18.3
16.5-16.5
13.3-14.0
12.1-15.3
11.6-12.5
35.7
35.5
38.5
31.9
31.5
35.1
34.2
34.7
32.7
32.7
31.7
34.8-36.6
34.5-36.6
29.9-32.8
30.5-32.4
33.4-34.9
13.7
13.0
11.8
14.4
14.0
13.1
12.3
13.7
12.1
13.1
17.5
12.4-15.1
12.8-13.1
14.2-14.7
13.0-15.5
11.7-12.8
5.3
5.68
5.30
6.07
5.70
4.71
5.30
5.39
5.11
5.68
5.13
5.21-5.39
5.57-5.78
5.83-6.32
5.15-6.62
5.15-5.44
20.6
23.1
23.2
26.8
27.8
27.1
28.7
30.5
32.0
33.6
30.8
18.2-22.9
22.1-24.0
26.0-28.6
26.0-29.3
28.5-28.8
6.54
6.27
7.07
7.21
7.29
6.90
7.58
7.03
8.02
6.93
7.28
6.49-6.59
5.84-6.70
6.80-7.88
6.91-8.10
7.38-7.77
N: Number of subjects, male to female ratios.
Source: U.S. EPA 1985.
-------
Table 6-9.
Descriptive
Statistics for Surface Area/Body Weight (SA/BW) Ratios (m2/kg)
Ane A/rs.1
Mean
Range
Min-Max
SDa
SEb
5
10
25
Percentiles
50
75
90
95
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 aries
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
a Standard deviation.
b Standard error of the mean.
Source: Phillins 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
0.20
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. Summary of Field Studies
Activity
Month
Event"
(hrs)
Nb
M
F
Age
Conditions
Clothing
Indoor
Tae 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
37-39
Plant watering,spraying, soil
blending, sterilization
Long pants, elbow length short
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
74 5
Outdoor
Daycare Kids No. 1a
Aug.
3.5
6
5
1
1-6.5
Indoors: linoleum surface;
outdoors: grass, bare earth,
barked area
4 of 6 in long pants, 4 of 6 short
sleeves, shoes
Daycare Kids No. 1 b
Aug.
4
6
5
1
1-6.5
Indoors: linoleum surface;
outdoors: grass, bare earth,
barked area
4 of 6 in long pants, 4 of 6 short
sleeves, no shoes
Daycare Kids No.2c
Sept.
8
5
4
1
1-4
Indoors, low napped carpeting,
linoleum surfaces
4 of 5 long pants, 3of5 long
sleeves, all barefoot for part of the
day
Daycare Kids No. 3
Nov.
8
4
3
1
1-4.5
Indoors: linoleum surface,
outside: grass, bare earth,
barked area
All long pants, 3 of 4 long sleeves,
socks and shoes
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
tires)
All in short sleeve shirts, shorts,
knee socks, shin guards
Soccer No. 3
Nov.
1.5
7
0
7
24-34
All-weather field (sand-ground
tires)
All in short sleeve shirts, shorts,
knee socks, shin guards
Groundskeepers No.
1
Mar.
1.5
2
1
1
29-52
Campus grounds, urban
horticulture center, arboretum
All in long pants, intermittent use of
gloves
Groundskeepers No.
2
Mar.
4.25
5
3
2
22-37
Campus grounds,urban
horticulture center, arboretum
All in long pants, intermittent use of
gloves
Groundskeepers No.
3
Mar.
8
7
5
2
30-62
Campus grounds,urban
horticulture center, arboretum
All in long pants, intermittent use of
gloves
Groundskeepers No.
4
Aug.
4.25
7
4
3
22-38
Campus grounds,urban
horticulture center, arboretum
5 of 7 in short sleeve shirts,
intermittent use of gloves
Groundskeepers No.
5
Aug.
8
8
6
2
19-64
Campus grounds,urban
horticulture center, arboretum
5 of 8 in short sleeve shirts,
intermittent use of gloves
Landscape/Rockery
June
9
4
3
1
27-43
Digging (manual
andmechanical), rock moving
All long pants, 2 long sleeves, all
socks and boots
Irrigationlnstallers
Oct.
3
6
6
0
23-41
Landscaping,surface restoration All in long pants, 3 of 6 short sleeve
or sleeveless shirts
Gardeners No. 1
Aug.
4
8
1
7
16-35
Weeding, pruning,digging a
trench
6 of 8 long pants, 7 of 8 short
sleeves, 1 sleeveless, socks,
shoes, intermittent use of aloves
-------
Table 6-11
Summary of Field Studies (continued)
Activity
Month
Event"
(hrs)
Nb
M
F
Age
Conditions
Clothing
Gardeners No. 2
Aug.
4
7
2
5
26-52
Weeding, pruning, digging a
trench, picking fruit, cleaning
3 of 7 long pants, 5of 7 short
sleeves, 1 sleeveless, socks,
shoes, no gloves
Rugby No. 1
Mar.
1.75
8
8
0
20-22
Mixed grass-barewet field
All in short sleeve shirts, shorts,
variable sock lengths
Rugby No. 2
July
2
8
8
0
23-33
Grass field (80% oftime) and all-
weather field (mix of gravel,
sand, and clay) (20% oftime)
All in shorts, 7 of 8 in short sleeve
shirts, 6 of 8 in low socks
Rugby No. 3
Sept.
2.75
7
7
0
24-30
Compacted mixedgrass and
bare earth field
All short pants, 7 of 8 short or rolled
up sleeves, socks, shoes
Archeologists
July
11.5
7
3
4
16-35
Digging withtrowel, screening
dirt, sorting
6 of 7 short pants,all short sleeves,
3 no shoes or socks, 2 sandals
Construction Workers
Sept.
8
8
8
0
21-30
Mixed bare earth and concrete
surfaces, dust and debris
5 of 8 pants,7 of 8 short sleeves, all
socks and shoes
Utility Workers No.1
July
9.5
5
5
0
24-45
Cleaning, fixing mains,
excavation (backhoe and
shovel)
All long pants,short sleeves, socks,
boots, gloves sometimes
Utility Workers No.2
Aug.
9.5
6
6
0
23-44
Cleaning, fixing mains,
excavation (backhoe and
shovel)
All long pants, 5 of 6 short sleeves,
socks, boots, gloves sometimes
Equip. Operators No.1
Aug.
8
4
4
0
21-54
Earth scraping withheavy
machinery, dusty conditions
All long pants, 3 of 4 short sleeves,
socks, boots, 2 of 4 gloves
Equip. Operators No.2
Aug.
8
4
4
0
21-54
Earth scraping withheavy
machinery, dusty conditions
All long pants, 3 of 4 short sleeves,
socks, boots, 1 gloves
Farmers No. 1
May
2
4
2
2
39-44
Manual weeding,mechanical
cultivation
All in long pants, heavy shoes, short
sleeve shirts, no gloves
Farmers No. 2
July
2
6
4
2
18-43
Manual weeding,mechanical
cultivation
2 of 6 short, 4 of 6long pants, 1 of 6
long sleeve shirt, no gloves
Reed Gatherers
Aug.
2
4
0
4
42-67
Tidal flats
2 of 4 shortsleeve shirts/knee
length pants, all wore shoes
Kids-in-mud No. 1
Sept.
0.17
6
5
1
9-14
Lake shoreline
All in short sleeve T-shirts, shorts,
barefoot
Kids-in-mud No. 2
Sept.
0.33
6
5
1
9-14
Lake shoreline
All in short sleeveT-shirts, shorts,
barefoot
Outdoor Totals
181
125 56
a Event duration
b Number of subject
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 Region
Post-activity Dermal Soil Loadings (mg/cm2)
Activity
Na
Hands
Arms
Legs
Faces
Feet
Indoor
Tae Kwon Do
7
0.0063
1.9
0.0019
4.1
0.0020
2.0
0.0022
2.1
GreenhouseWorkers
2
0.043
0.0064
0.0015
0.0050
Indoor Kids No. 1
4
0.0073
1.9
0.0042
1.9
0.0041
2.3
0.012
1.4
Indoor Kids No. 2
6
0.014
1.5
0.0041
2.0
0.0031
1.5
0.0091
1.7
Daycare Kids No. 1a
6
0.11
1.9
0.026
1.9
0.030
1.7
0.079
2.4
Daycare Kids No. 1 b
6
0.15
2.1
0.031
1.8
0.023
1.2
0.13
1.4
Daycare Kids No. 2
5
0.073
1.6
0.023
1.4
0.011
1.4
0.044
1.3
Daycare Kids No. 3
4
0.036
1.3
0.012
1.2
0.014
3.0
0.0053
5.1
Outdoor
Soccer No. 1
8
0.11
1.8
0.011
2.0
0.031
3.8
0.012
1.5
Soccer No. 2
8
0.035
3.9
0.0043
2.2
0.014
5.3
0.016
1.5
Soccer No. 3
7
0.019
1.5
0.0029
2.2
0.0081
1.6
0.012
1.6
Groundskeepers No. 1
2
0.15
0.005
0.0021
0.018
Groundskeepers No. 2
5
0.098
2.1
0.0021
2.6
0.0010
1.5
0.010
2.0
Groundskeepers No. 3
7
0.030
2.3
0.0022
1.9
0.0009
1.8
0.0044
2.6
0.0040
Groundskeepers No. 4
7
0.045
1.9
0.014
1.8
0.0008
1.9
0.0026
1.6
0.018
Groundskeepers No. 5
8
0.032
1.7
0.022
2.8
0.0010
1.4
0.0039
2.1
Landscape/Rockery
4
0.072
2.1
0.030
2.1
0.0057
1.9
Irrigation Installers
6
0.19
1.6
0.018
3.2
0.0054
1.8
0.0063
1.3
Gardeners No. 1
8
0.20
1.9
0.050
2.1
0.072
0.058
1.6
0.17
-------
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
Na
Hands
Arms
Legs
Faces
Feet
Gardeners No. 2
7
0.18
3.4
0.054
2.9
0.022
2.0
0.047
1.6
0.26
Rugby No. 1
8
0.40
1.7
0.27
1.6
0.36
1.7
0.059
2.7
Rugby No. 2
8
0.14
1.4
0.11
1.6
0.15
1.6
0.046
1.4
Rugby No. 3
7
0.049
1.7
0.031
1.3
0.057
1.2
0.020
1.5
Archeologists
7
0.14
1.3
0.041
1.9
0.028
4.1
0.050
1.8
0.24
1.4
Construction Workers
8
0.24
1.5
0.098
1.5
0.066
1.4
0.029
1.6
Utility Workers No.1
5
0.32
1.7
0.20
2.7
0.10
1.5
Utility Workers No. 2
6
0.27
2.1
0.30
1.8
0.10
1.5
Equip. Operators No. 1
4
0.26
2.5
0.089
1.6
0.10
1.4
Equip. Operators No. 2
4
0.32
1.6
0.27
1.4
0.23
1.7
Farmers No. 1
4
0.41
1.6
0.059
3.2
0.0058
2.7
0.018
1.4
Farmers No. 2
6
0.47
1.4
0.13
2.2
0.037
3.9
0.041
3.0
Reed Gatherers
4
0.66
1.8
0.036
2.1
0.16
9.2
0.63
7.1
Kids-in-mud No. 1
6
35
2.3
11
6.1
36
2.0
24
3.6
Kids-in-mud No. 2
6
58
2.3
11
3.8
9.5
2.3
6.7
12.4
a Number of subjects.
Sources: Kissel et al.. 1996b: Holmes et al..
1996 (submitted for publication).
-------
Table 6-13. Summary of Surface Area Studies
Surface Area
Study
No. of Individuals
Type of Surface Area
Measurement
Recommended
Formulae Used
Population
Surveyed
Comments
KEY STUDIES
Phillips etal. (1993)
Based on data from
U.S. EPA (1985): 401
individuals
NA
calculated surface area to
body weight ratios
Children
Adults
Developed distributions of
SA/BWand calculated
summary statistics for 3 age
groups and the combined data
set
U.S. EPA (1985)
401 individuals
Based on Gehan and
George (1970)
SA=0.0239*W°517*H0417
Children
Adults
Provides statistical distribution
data for total SA and SA of
body parts
RELEVANT STUDIES
AICH (1994)
Based on data from
U.S. EPA (1989);
Brainard et al. (1991);
Brorby and Finley
(1993)
@Risk simulation
software
Various
Adults
Children
Distribution data for: adult
men and women and both
sexes combined; total skin
area, children 8-18 years;
exposed skin area (hands and
forearms); head; upper body
Murray and Burmaster
(1992)
Based on data from
U.S. EPA (1985): N =
401;
Dubois and Dubois
(1976): N = 9;
Boyd (1935): N = 231;
Costeff (1966): N =
220
Calculated based on
regression equation using
the data of U.S. EPA
(1985)
Various
Children
Adults
Analysis of and comparision
of four models developed by
Dubois & Dubois (1916),
Boyd (1935), U.S. EPA
(1985), and Costeff (1966).
Presents frequency
distribtions
-------
Table 6-14. Summary of Recommended Values for Skin Surface Area
Surface Area
Central Tendency
Upper Percentile
Multiple Percentiles
Adults
Whole body and body
parts
see Tables 6-4 and 6-5
see Tables 6-2 and 6-3
see Tables 6-2 and 6-3
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
Rationale
Rating
Study Elements
• Level of Peer Review
Studies were from peer reviewed journal articles.
EPA report was peer reviewed before distribution.
High
• Accessibility
The journals used have wide circulation.
EPA report available from National Technical
Information Service.
High
• Reproducibility
Experimental methods are well-described.
High
• Focus on factor of interest
Experiments measured skin area directly.
High
• Data pertinent to U.S.
Experiments conducted in the U.S.
High
• Primary data
Re-analysis of primary data in more detail by two
different investigators.
Low
• Currency
Neither rapidly changing nor controversial area;
estimates made in 1935 deemed to be accurate and
subsequently used by others.
Low
• Adequacy of data collection
period
Not relevant to exposure factor; parameter not time
dependent.
NA
• Validity of approach
Approach used by other investigators; not challenged
in other studies.
High
• Representativeness of the
population
Not statistically representative of U.S. population.
Medium
• Characterization of variability
Individual variability due to age, race, or gender not
studied.
Low
• Lack of bias in study design
Objective subject selection and measurement methods
used; results reproduced by others with different
methods.
High
• Measurement error
Measurement variations are low; adequately described
by normal statistics.
Low/Medium
Other Elements
• Number of studies
1 experiment; two independent re-analyses of this data
set.
Medium
• Agreement among researchers
Consistent results obtained with different analyses; but
from a single set of measurements.
Medium
Overall Rating
This factor can be directly measured. It is not subject
to dispute. Influence of age, race, or gender have not
been detailed adequately in these studies.
High
-------
Table 6-16. Recommendations for Adult Body Surface Area
Water Contact
50th
95th
Bathing and Swimming
20,000 cm2
23,000 cm2
Soil Contact
50th
95th
Outdoor Activities
5,000 cm2
5,800 cm2
Source: U.S. EPA, 1992.
-------
Table 6-17.
Summary of Soil Adherence Studies
Study
Size
Fraction
(Mm)
Soil
Adherence
(mg/cm2)
Population
Surveyed
Comments
KEY STUDIES
Kissel et al., 1996a
<150, 150-
200, >250
Various
28 adults
24 children
Data presented for soil loadings by
body part. See Table 6-11.
Kissell et al., 1996b
—
Various
12 children
89 adults
Data presented by activity and body
part.
RELEVANT STUDIES
Driver et al., 1989
<150
<250
unsieved
1.40
0.95
0.58
Adults
Adults
Adults
Used 5 soil types and 2-3 soil
horizons (top soils and subsoils);
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 etal. (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
adherence to skin.
High
• Data pertinent to U.S.
Experiments were conducted in the U.S.
High
• Primary data
Experiments were directly measure soil adherence to
skin; exposure and dose of chemicals in soil were
measured indirectly or estimated from soil contact.
High
• Currency
New studies were presented.
High
• Adequacy of data collection
period
Seasonal factors may be important, but have not been
studied adequately.
Medium
• Validity of approach
Skin rinsing technique is a widely employed procedure.
High
• Representativeness of the
population
Studies were limited to the State of Washington and
may not be representative of other locales.
Low
• Characterization of variability
Variability in soil adherence is affected by many factors
including soil properties, activity and individual behavior
patterns.
Low
• Lack of bias in study design
The studies attempted to measure soil adherence in
selected activities and conditions to identify important
activities and groups.
High
• Measurement error
The experimental error is low and well controlled, but
application of results to other similar activities may be
subject to variation.
Low/High
Other Elements
• Number of studies
The experiments were controlled as they were
conducted by a few laboratories; activity patterns were
studied by only one laboratory.
Medium
• Agreement among researchers
Results from key study were consistent with earlier
estimates from relevant studies and assumptions, but
are limited to hand data.
Medium
Overall Rating
Data are limited, therefore it is difficult to extrapolate
from experiments and field observations to general
conditions .
Low
-------
Exposure
Chemical
Potential
Dose
Applied
Dose
Internal
Dose
Metabolism
Skin
Biologically
Effective
Dose
i
Organ
Uptake
Figure 6-1. Schematic of Dose and Exposure: Dermal Route
Effect
Source: U.S. EPA, 1992a.
-------
Infant SA/BW Ratios: Lognorm(0.0641,0.0114)
Q.25
Expectad Value
6.410E02
ValuH in 10*-2
Alt Ages SA/BW Ratios: NormaKO.0489,0.0187)
¦< -14 8 m
Values in 10*-2
Adult SA/BW Ratios: NorroaJ(0.0284,0.0028|
Expacted Value
2.840E-02
12 1? 22 27 32 37
VatuM in 10*-3
Figure 6-2. SA/BW Distributions for Infants, Adults, and All Ages Combined
Source: Phillips et al., 1993.
-------
.OS
06
•g 04
A
o
.02
.00
1.00
Surface Area: Men
Frequency Distribution
1,50
2.00
2.50
r 424
318
-n
-------
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. Contam. 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. Epidemiol. 3(4):451-
462.
Palisade. (1992) @Risk users guide. Palisade 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 exposure 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/OHEA. 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.
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.
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.
-------
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]
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Volume I - General Factors
Cha£ter7^Bo^Wei^htStudie^^^^^^^^^^^^^^_
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 Weights 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
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7. BODY WEIGHT STUDIES
There are several physiological 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. KEY 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
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Chapter 7 - Body Weight Studies ~~
probability sample of approximately 28,000 persons, aged 6 months to 74 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
inflating 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 greater than 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 74 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
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Volume I - General Factors
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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 lognormal 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 74 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 weight was 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 2/19/94 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 of 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 lognormal distributions give strong fits to the
body weights of children, ages 6 months to 20 years. Statistics for the lognormal
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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
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 body weights as well as other exposure factors.
7.3. RECOMMENDATIONS
The key studies described in this section was used 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
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Volume I - General Factors
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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.
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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
10.78
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
a Smoothed by cubic-spline approximation.
Source: Hamill et al., 1979.
-------
Table 7-2.
Body Weights of Adults3 (kilograms)
Men and Women
Age (years)
Men
Women
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 Children3
(kilograms)
Boys
Girls
Boys and Girls
Age
Mean
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
58.1
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
Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram.
Source: Adapted from National Center for Health Statistics (NCHS),
1987.
-------
Table 7-4. Weight in Kilograms for Males 18-74 Years of Age-Number Examined, Mean, Standard
Deviation, and Selected Percentiles, by Race and Age: United States, 1976-1980a
Percentile
Race and Age
Number of
Persons Mean
Examined (kg)
Standard
Deviation 5th
10th
15th
25th
50th
75th
85th
90th
95th
All races'1
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 . . .
745
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
65-74 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
*C
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 years . . .
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.
a Includes clothing weight, estimated as ranging from 0.09 to 0.28 kilogram.
b Includes all other races not shown as separate categories.
c Data not available.
Source: National Center for Health Statistics, 1987.
-------
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, 1976-1980a
Percentile
Number of
Persons
Mean
Standard
Race and Age
Examined
(kfl)
Deviation 5th
10th
15th
25th
50th
75th
85th
90th
95th
All races"
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
18-24years ...
. 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
47.4
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
57.3
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
18-74years ...
. 5,686
64.8
14.1
47.7
50.3
52.2
55.2
62.1
71.1
77.9
83.3
91.5
18-24years ...
... 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 . . .
... 647
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.
a 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, 1976-19803
Percentile
Number of
Persons Mean Standard
Age
Examined
(kg)
Deviation
5th
10th
15th
25th
50th
75th
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
13.5
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
6 years
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, 1976-19803
Percentile
Number of
Persons Mean Standard
Age
Examined
(kfl)
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
7 years
... 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 years
... 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
14 years
... 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
Age
Lognormal Probability Plots
Linear Curve
mE?
o7a
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
15 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 ^0 o2 - 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
Age
Lognormal Probability Plots
Linear Curve
o7a
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 ^0 o2 - 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
population
Authors noted that data are accurate measurements
from a large nationally representative sample of
children.
NCHS, 1987
(NHANES II)
20,322
U.S. general
population
Based on civilian non-institutionalized population aged
6 months to 74 years. Response rate was 73.1
percent.
RELEVANT STUDIES
Brainard and Burmaster,
1992
12,501 (5,916 men and
6,588 women)
U.S. general
population
Used data from NHANES II to fit bivarite distributions
to women and men age 18 to 74 years.
Burmaster et al., 1994
8,458 (4,079 females and
4,379 males)
U.S. general
population
Used data from NHANES II to develop fitted
distributions for children aged 6 to 20 years old.
Adjusted for non-response by age, gender, and race.
-------
Table 7-11. Summary of Recommended Values for Body Weight
PoDulation
Mean
UDDer Percentile
MultiDle Percentiles
Adults
71.8 kg (See Table 7-2)
See Tables 7-4 and 7-5
See Tables 7-4 and 7-5
Children
See Table 7-3
See Tables 7-6 and 7-7
See Tables 7-6 and 7-7
-------
Table 7-12. Confidence in Body Weight Recommendations
Considerations
Rationale
Rating
Study Elements
• Level of peer review
NHANES II was the major source of data for NCHS (1987). This is a
published study which received a high level of peer review. The
Hamill et al. (1979) is a peer reviewed journal publication.
High
• Accessibility
Both studies are available to the public.
High
• Reproducibility
Results can be reproduced by analyzing NHANES II data and the
Fels Research Institute data.
High
• 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
studies, thus these data are secondary.
Medium
• Currency
The data were collected between 1976-1980.
Low
• Adequacy of data collection
period
The NHANES II study included data collected over a period of 4
years. Body weight measurements were taken at various times of the
day and at different seasons of the year.
High
• Validity of approach
Direct body weights were measured for both studies. For NHANES II,
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.
High
• Study size
The sample size consisted of 28,000 persons for NHANES II. Author
noted in Hamill et al. (1979) that the data set was large.
High
• Representativeness of the
population
Data collected focused on the U.S. population for both studies.
High
• Characterization of
variability
Both studies characterized variability regarding age and sex.
Additionally NHANES II characterized race (for Blacks, Whites and
total populations) and sampled persons with low income.
High
• Lack of bias in study design
(high rating is desirable)
There are no apparent biases in the study designs for NHANES II.
The study design for collecting the Fels data was not provided.
Medium-
High
• Measurement error
For NHANES II, measurement error should be low since body weights
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.
High
Other Elements
• Number of studies
There are two studies.
Low
• Agreement between researchers
There is consistency among the two studies.
High
Overall Rating
Hiqh
-------
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Source: Hamill et al., 1979.
-------
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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 Anal. 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. (1992) @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 Males 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
REFERENCES FOR CHAPTER 8
Table 8-1. Expectation of Life at Birth, 1970 to 1993, and Projections, 1995 to 2010
Table 8-2. Expectation of Life by Race, Sex, and Age: 1992
Table 8-3. Confidence in Lifetime Expectancy Recommendations
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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 available 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 that the 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.
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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 use 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.
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Table
3-1. Expectation of Life at Birth, 1970 to 1993, and Projections, 1995 to 2010 (years)3
TOTAL
WHITE
BLACKAND 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
75.2
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
1993
75.5
72.1
78.9
76.3
73.0
79.5
71.5
67.4
75.5
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
73.8
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.
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At
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
Table 8-2. Expectation of Life by Race, Sex, and Age: 1992
Expectation of Life in Years
White Black
Total
Male
Female
Male
Female
75.8
73.2
79.8
65.0
73.9
75.4
72.8
79.3
65.2
74.1
74.5
71.8
78.3
64.3
73.1
73.5
70.9
77.3
63.4
72.2
72.5
69.9
76.3
62.4
71.2
71.6
68.9
75.4
61.4
70.3
70.6
67.9
74.4
60.5
69.3
69.6
66.9
73.4
59.5
68.3
68.6
65.9
72.4
58.5
67.3
67.6
65.0
71.4
57.5
66.3
66.6
64.0
70.4
56.5
65.4
65.6
63.0
69.4
55.5
64.4
64.6
62.0
68.4
54.6
63.4
63.7
61.0
67.4
53.6
62.4
62.7
60.0
66.5
52.6
61.4
61.7
59.1
65.5
51.7
60.4
60.7
58.1
64.5
50.7
59.5
59.8
57.2
63.5
49.8
58.5
58.8
56.2
62.5
48.9
57.5
57.9
55.3
61.6
48.1
56.6
56.9
54.3
60.6
47.2
55.6
56.0
53.4
59.6
46.3
54.6
55.1
52.5
58.7
45.5
53.7
54.1
51.6
57.7
44.6
52.7
53.2
50.6
56.7
43.8
51.8
52.2
49.7
55.7
42.9
50.8
51.3
48.8
54.8
42.1
49.9
50.4
47.8
53.8
41.2
48.9
49.4
46.9
52.8
40.4
48.0
48.5
46.0
51.8
39.5
47.1
47.5
45.1
50.9
38.7
46.1
46.6
44.1
49.9
37.8
45.2
45.7
43.2
48.9
37.0
44.3
44.7
42.3
48.0
36.2
43.4
43.8
41.4
47.0
35.3
42.4
42.9
40.5
46.0
34.5
41.5
42.0
39.6
45.1
33.7
40.6
41.0
38.7
44.1
32.9
39.7
40.1
37.8
43.2
32.1
38.8
39.2
36.9
42.2
31.3
37.9
38.3
36.0
41.2
30.5
37.1
37.4
35.1
40.3
29.7
36.2
36.5
34.2
39.3
28.9
35.3
35.6
33.3
38.4
28.2
34.4
34.7
32.4
37.5
27.4
33.6
33.8
31.5
36.5
26.7
32.7
32.9
30.6
35.6
25.9
31.9
32.0
29.7
34.7
25.2
31.0
31.1
28.8
33.7
24.4
30.2
30.2
28.0
32.8
23.7
29.3
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Table 8-2. Expectation of Life by Race, Sex, and Age: 1992 (continued)
Age in 1990
(years)
Expectation of Life in Years
Total
Male
White
Female
Male
Black
Female
50
29.3
27.1
31.9
23.0
28.5
51
28.5
26.3
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
16.3
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
14.2
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
Studv 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
trends from 1970 to 1993. The study has also made projections for
1995 until the year 2010.
High
• 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
study size is expected to be greater than 100.
High
• 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
Whites; no other nationalities were represented within the section.
Medium
• Lack of bias in study design (High
rating is desirable)
There are no apparent biases.
High
• Measurement error
Measurement error may be attributed to portions of the population that
avoid or provide misleading information on census surveys.
Medium
Other Elements
• Number of studies
Data presented in the section are from the U.S. Bureau of the
Census publication.
Low
• Agreement between researchers
Recommendation was based on only one study, but it is widely
accepted.
High
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]
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Volume II - Food Ingestion Factors
Chapter 9 - Intake of Fruits and Vegetables
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 CSFII
9.2.3. Relevant Fruits and Vegetables Intake Studies
9.2.4. Relevant Fruits and Vegetables Serving Size Study Based on the
USDANFCS
9.2.5. Conversion Between As Consumed and Dry Weight Intake Rates
9.3. RECOMMENDATIONS
REFERENCES FOR CHAPTER 9
APPENDIX 9A
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 CSFII 1989-91 Analysis
Weighted and Unweighted Number of Observations for 1989-91 CSFII 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-day 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)
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Volume II - Food Ingestion Factors
Chaj)terJ^Intakej)£Fru^^
Table 9-19. Mean Total Vegetable Intake (as consumed) in a Day by Sex and Age (1994
and 1995)
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)
Table 9-21. Mean and Standard Error for the Per Capita Daily Intake of Food Class and
Subclass by Region (g/day as consumed)
Table 9-22. Mean and Standard Error for the Daily Intake of Food Subclasses Per Capita
by Age (g/day as consumed)
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
Table 9-24. Mean Daily Intake of Foods (grams) Based on the Nutrition Canada Dietary
Survey
Table 9-25. Per Capita Consumption of Fresh Fruits and Vegetables in 1991
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
Table 9-27. Mean Moisture Content of Selected Fruits and Vegetables Expressed as
Percentages of Edible Portions
Table 9-28. Summary of Fruit and Vegetable Intake Studies
Table 9-29. Summary of Recommended Values for Per Capita Intake of Fruits and
Vegetables
Table 9-30. Confidence in Fruit and Vegetable Intake Recommendations
Table 9A-1. Fraction of Grain and Meat Mixture Intake Represented by Various Food
Items/Groups
Table 9 B. Food Codes and Definitions Used in Analysis of the 1989-91 USDA CSFII
Data
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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 (CSFII). 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. CSFII data from the 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 and
individuals who may eat the food items at some time, but did not consume them during the
survey 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 CSFII are based on "as eaten" (i.e., cooked or
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August 1997
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Volume II - Food Ingestion Factors
Chaj)terJ^Intakej)£Fr^
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
discussed in Volume I, Section 1.3.1 of the Introduction. Recommendations are based on
data from the CSFII 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 CSFII. The USDA NFCS and CSFII 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
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
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August 1997
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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 CSFII
data set is presented in this handbook. During 1989 through 1991, over 15,000 individuals
participated in the CSFII (USDA, 1995). Using a stratified sampling technique, individuals
of all 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 CSFII was approximately 45 percent. Published 1-day data from the 1994
and 1995 CSFII are also presented. The 1994 and 1995 CSFII included data for 2 non-
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 surveys (USDA, 1996a; 1996b).
Individual average daily intake rates calculated from NFCS and CSFII 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
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
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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 CSFII
U.S. EPA Analysis of USDA 1989-91 CSFII Data - EPA analyzed three years of data
from USDA's CSFII to generate distributions of intake rates for various fruit and vegetable
items/groups. Data from the 1989, 1990, and 1991 CFSII 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, carrots, 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 items eaten as meat and grain mixtures as described in Appendix
9A. Food items/groups were identified in the CSFII data base according to USDA-defined
food codes. Appendix 9B 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 1991 CSFII. USDA sample weights are calculated to account for inherent
biases in the sample selection process, and to adjust the sample population to reflect the
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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 consumer 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 100th 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, 6-11, 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 other). 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 results 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 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 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 CSFII 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; CSFII 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 CSFII 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
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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 CSFII is not the most up-
to-date information on food intake. USDA has recently made available the data from its
1994 and 1995 CSFII. 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 CSFII 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 (DRES) - 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 although 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 g/kg-
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 agricultural commodities (RACs) (White et al., 1983).
The DRES 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
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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 DRES data
base did not rely on a single body weight for all individuals. Instead, DRES 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 CSFII 1989-91 survey to be used in
DRES.
Food and Nutrient Intakes of Individuals in One Day in the U.S., USDA (1980, 1992b,
1996a, 1996b) - 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 CSFII 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 used 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 CSFII. The age groups used in this data set
are the same as those used 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
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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 CSFII, respectively (USDA, 1996a,
1996b). One-day per capita intake data for fats or oils from the 1994 and 1995 CSFII
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
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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 preceding 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 intake rates.
However, they appear to be consistent with the as consumed intake rates for consumers-
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 capita 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
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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 CSFII 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 CSFII 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
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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:
lRdw= lRac* [(100-W)/100] (Eqn.9-1)
"Dry weight" intake rates may be converted to "as consumed" rates by using:
IRac = IRdw/[(100-W)/100]
(Eqn. 9-2)
where:
IRdw
= dry weight intake rate;
IRac
= as consumed intake rate; and
w
= pe rce nt wate r co nte nt.
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9.3. RECOMMENDATIONS
The 1989-91 CSFII 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
CSFI11989-91, 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-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 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 CSFII 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 1989-91 and 1995.
Thus, the 1989-91 CSFII data are believed to be appropriate for assessing ingestion
exposure for current populations.
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APPENDIX 9A
CALCULATIONS USED IN THE 1989-91 CSFII ANALYSIS TO CORRECT FOR
MIXTURES
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APPENDIX 9A
Calculations Used in the 1989-91 CSFII Analysis to Correct for Mixtures
Distributions of intake for various food groups were generated for the food/items
groups using the USDA 1989-91 CSFII 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 J J = (IR * Fr , ) + (IR * Fr , ) + (IR )
meat-adjusted v gr mixtures meat/gr7 v mt mixtures meatlmv v meat7
where:
IRmeat-adjusted = adjusted individual intake rate for total meat;
IRgrmixtures = individual intake rate for grain mixtures;
IRmtmixtures = individual intake rate for meat mixtures;
IRmeat = individual intake rate for meats;
Frmeat/gr = fraction of grain mixture that is meat; and
Frmeat/mt = fraction of meat mixture that is meat.
Population distributions for mixture-adjusted intakes were based on adjusted intake rates
for the population of interest.
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Table 9-1. Sub-category Codes and Definitions Used in the CSFII 1989-91 Analysis
Code
Definition
Description
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 Wsconsin
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
2
3
Central City
Suburban
Nonmetropolitan
Cities with populations of 50,000 or more that is the main city within the metropolitan statistical area
(MSA).
An area that is generally within the boundaries of an MSA, but is not within the legal limit of the central
city.
An area that is not within an MSA.
Season
Spring
-
April, May, June
Summe
-
July, August, September
Fall
Winter
-
October, November, December
January, February, March
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
a Alaska and Hawaii were not included.
Source: CSFII 1989-91.
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Table 9-2. Weighted and Unweighted Number of Observations for
1989-91 CSFII 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 Capita Intake of Total Fruits (g/kg-day
as consumed)
Population
Percent
Group
Consum
ing
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
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
0
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
1.73
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
Nonmetropolitan
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 analyses of the 1989-91 CSFII
-------
Table 9-4. Per Capita Intake of Total Vegetables (g/kg-day as
consumed)
Population
Group
Percent
Consumi
ng
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
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 analyses of the 1989-91 CSFII
-------
Table 9-5. Per Capita Intake of Individual Fruits and Vegetables (g/kg-day as consumed)
Apples Asparagus Bananas Beets
Population
Group
Percent
Consuming
Mean
SE
Percent
Consuming
Mean
SE
Percent
Consuming
Mean
SE
Percent
Consuming
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
Nonmetropolitan
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
0.7%
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
Group
Percent
Consuming
Mean
SE
Percent
Consuming
Mean
SE
Percent
Consuming
Mean
SE
Percent
Consuming
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
8.4%
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%
0.151
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 Vegetables (g/kg-day
as consumed) (continued)
Cucumbers
Lettuce
Lima Beans
Okra
Population
Grouc
Percent
Consuminq
Mean
SE
Percent
Consuminq
Mean
SE
Percent
Consuminq
Mean
SE
Percent
Consuminq
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
0.009
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 Vegetables (g/kg-day as consumed) (continued)
Onions
Other Berries
Peaches
Pears
Population
Group
Percent
Consuming
Mean
SE
Percent
Consuming
Mean
SE
Percent
Consuming
Mean
SE
Percent
Consuming
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
0.040
16.1%
0.161
0.033
7.8%
0.087
0.037
Season
Fall
16.3%
0.045
0.007
2.6%
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
Nonmetropolitan
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 Vegetables (g/kg-day as consumed) (continued)
Peas Peppers Pumpkins Snap Beans
Population
Group
Percent
Consuming
Mean
SE
Percent
Consuming
Mean
SE
Percent
Consuming
Mean
SE
Percent
Consuming
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%
0.003
0.025
5.2%
0.497
0.363
16.7%
0.439
0.154
01-02
13.6%
0.174
0.083
2.4%
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%
0.012
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 Fruits and Vegetables (g/kg-day as consumed) (continued)
Strawberries
Tomatoes
White Potatoes
Population
Grouc
Percent
Consuminq
Mean
SE
Percent
Consuminq
Mean
SE
Percent
Consuminq
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
0.049
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
South
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 analyses of the
1989-91 CSFII
-------
Table 9-6. Per Capita Intake of USDA Categories of Fruits and Vegetables (g/kg-day as consumed)
Dark Green Vegetables Deep Yellow Vegetables Citrus Fruits Other Fruits Other Vegetables
Population
Groun
Percent
Consumina
Mean
SE
Percent
Consumina
Mean
SE
Percent
Consumina
Mean
SE
Percent
Consumina
Mean
SE
Percent
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
0.157
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
Nonmetropolitan
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 analyses of the 1989-91 CSFII
-------
Table 9-7. Per CaDita Intake of ExDosed Fruits (a/ka-dav as consumed1)
Population
Grouc
Percent
Consuminq
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 CSFII
-------
Table 9-8. Per Capita Intake of Protected Fruits fa/ka-dav as consumedl
Population
GrouD
Percent
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
0
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
0
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
0.854
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 CSFII
-------
Table 9-9. Per CaDita Intake of ExDosed Veaetables (a/ka-dav as consumed1)
Population
Percent
GrouD
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
0.302
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 CSFII
-------
Table 9-10.
Per CaDita Intake of Protected Veaetables (a/ka-dav as consumed1)
Population
Percent
GrouD
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
0
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 analyses of the 1989-91 CSFII
-------
Table 9-11. Per
CaDita Intake of Root Veaetables (a/ka-dav as consumed1)
Population
GrouD
Percent
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 analyses of the 1989-91
CSFII
-------
Table 9-12. Mean Daily Intake of Fruits and Vegetables Per Individual in a Day for USDA 1977-78, 87-8S
, 89-91, 94, and 95 Surveys
Food Product
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
Raw Agricultural Commodity®
Average Consumption
(Grams/kg Body Weight-Day)
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
Seed)
0.0000000
*
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
(Immature Seed)
0.0000000
*
Beans-Succulent-Green
0.2000500
0.0062554
Beans-Succulent-Hyacinth (Young
Pods)
0.0000000
*
Beans-Succulent-Lima
0.0256648
0.0021327
Beans-Succulent-Other
0.0263838
0.0042782
Beans-Succulent-Yellow, Wax
0.0054634
0.0009518
Beans-UnsDecified
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)
Raw Agricultural Commodity®
Average Consumption
(Grams/kg 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
Choy
0.0045632
0.0020966
Cabbage-Green and Red
0.0936402
0.0039046
Cactus Pads
0.0000010
*
Cantaloupes
0.0444220
0.0029515
Carambola
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/Age/Demographic Subgroups
(continued)
Raw Agricultural Commodity®
Average Consumption
(Grams/kg Body Weight-Day)
Standard Error
Collards
0.0188966
0.0032628
Corn, Pop
0.0067714
0.0003348
Corn, 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-
Gooseberries)
0.0000000
*
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 Based on All Sex/Age/Demographic Subgroups
(continued)
Raw Agricultural Commodity®
Average Consumption
(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
Lentiles-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)
Raw Agricultural Commodity®
Average Consumption
(Grams/kg Body Weight-Day)
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
Pitanaa (Surinam Cherrvl
0.0000010
*
-------
Table 9-13. Mean Per Capita Intake Rates (as consumed) for Fruits and Vegetables Based on All Sex/Age/Demographic Subgroups
(continued)
Raw Agricultural Commodity®
Average Consumption
(Grams/kg Body Weight-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)
Raw Agricultural Commodity®
Average Consumption
(Grams/kg Body Weight-Day)
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
Younaberries
0.0003570
*
* Not reported
8 Consumed in any raw or prepared form
Source: DRES data base (based on 1977-78 NFCS data).
-------
Table 9-14.
Mean Total Fruit Intake (as
consumed) in a Day by Sex and Age (1977-1978)a
Age (yr)
Per Capita Intake
Percent of Population Using
Intake (g/day) for Users Onlyb
Ca/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
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 fruit in a day.
Source: USDA. 1980.
-------
Table 9-15.
Mean Total Fruit Intake
(as consumed) in a Day by Sex and Age (1987-1988)a
Aae (vri
Percent of Population Using
Per CaDita Intake Ca/davl Fruit in 1 Dav
Intake (g/day) for Users Onlyb
Males and Females
5 and under
157
59.2
265
Males
6-11
12-19
20 and over
182
158
133
63.8
49.4
46.5
LO O CD
00 CN 00
CN CO CN
Females
6-11
12-19
20 and over
154
131
140
58.3
47.1
52.7
264
278
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
Only"
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
35-50
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 Vegetable Intake
(as consumed) in a Day by Sex and Age (1987-1988)®
Aae (vri
Per CaDita Intake Ca/davl
Percent of Population Using
Veaetables in a Dav
Intake (a/davl for Users Onlvb
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
All Aaes
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 Day by Sex and Age (1994 and 1995)a
Percent of Population Using
Aae (vri
Per CaDita Intake Ca/davl
Fruit in 1 Dav
Intake Ca/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 CSFII (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 Vegetable Intake (as consumed) in a
Day by Sex and Age (1994 and 1995)a
Aae (vri
Per CaDita Intake Ca/davl
Percent of Population Using
Veaetables in 1 Dav
Intake Ca/davl 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
12-19
20 and over
118
154
242
111
202
241
82.4
74.9
85.9
80.6
79.0
86.4
143
206
282
138
256
278
Females
6-11
12-19
20 and over
115
132
190
108
144
189
82.9
78.5
84.7
79.1
76.0
83.2
139
168
224
137
189
227
Males and Females
All Aaes
186
188
83.2
82.6
223
228
a Based on USDA CSFII (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)a
Total Fats and Oils"
Table Fatsc
Salad Dressings"
1994
1995
1994
1995
1994
1995
Males and Females
5 and
under
4
3
2
2
2
1
Males
6-11
8
7
3
3
5
4
12-19
11
14
2
5
8
10
20 and
over
19
18
5
5
11
10
Females
6-11
7
8
3
3
4
4
12-19
9
9
2
3
6
6
20 and
over
16
14
4
5
10
7
Males and Females
All Ages
14
14
4
4
9
8
a Based on USDA CSFII 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 Daily Intake of Food Class and Subclass by Region (g/day 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
Exposed" 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.
c 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.
c 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)
(0-1)
(1-5)
(6-13)
(14-19)
(20-44)
(45-70)
_ Estimated Lifetime
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
a The estimated lifetime dietary intakes were estimated by:
Estimated lifetime = IRfO-'H + 5vrs * IR (1-5^ + 8 vrs * IR (6-13^ + 6 vrs * IR (14-19^ + 25 vrs * IR (20-44) + 25 vrs * 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
Aqe (vrs)
Sample Size
Fruit Products
Includinq Potatoes
Potatoes
Lequmes
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
Preanant 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 Capita Consumption of Fresh Fruits and Vegetables in 1991a
Fresh Fruits
Fresh Veaetables
Food Item
Per Capita
Consumption
Ca/dav1b
Food Item
Per Capita
Consumption
Ca/dav1b
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
Noncitrus
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
a 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 Ibs/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 Eatinq Occasion and the Percentaqe of Individuals Usinq These Foods
in Three Days
Consumers-only
Food category
% Indiv. using Quantity consumed per eating
Quantity consumed per eatinq occasion at specified percentiles (q)a
food in 3 days
occasion (g)
5
25
50
75
90
95
99
Average
Standard
Deviation
Raw veqetables
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 veqetables
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
Corn, 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
0 Percentiles are cumulative; for example, 50 percent of people eat 105
white potatoes per day or less.
Source: Pao et al.. 1982 (based
on 1977-78 NFCS data).
-------
Table 9-27. Mean Moisture Content of Selected Fruits and Vegetables Expressed as Percentages of Edible Portions
Food Moisture Content CPercentl Comments
Raw Cooked
Fruit
Apples - dried 31.76
Apples - 83.93*
Apples - juice
Applesauce
Apricots 86.35
Apricots - dried 31.09
Bananas 74.26
Blackberries 85.64
Blueberries 84.61
Boysenberries 85.90
Cantaloupes - unspecified 89.78
Casabas 91.00
Cherries - sweet 80.76
Crabapples 78.94
Cranberries 86.54
Cranberries - juice cocktail 85.00
Currants (red and white) 83.95
Elderberries 79.80
Grapefruit 90.89
Grapefruit-juice 90.00
Grapefruit - unspecified 90.89
Grapes - fresh 81.30
Grapes-juice 84.12
Grapes - raisins 15.42
Honeydew melons 89.66
Kiwi fruit 83.05
Kumquats 81.70
Lemons-juice 90.73
Lemons - peel 81.60
Lemons - pulp 88.98
Limes-juice 90.21
Limes - unspecified 88.26
Loganberries 84.61
Mulberries 87.68
Nectarines 86.28
Oranges - unspecified 86.75
Peaches 87.66
Pears - dried 26.69
Pears - fresh 83.81
Pineapple 86.50
Pineapple - juice
Plums
Quinces 83.80
Raspberries 86.57
Strawberries 91.57
Tangerine-juice 88.90
Tangerines 87.60
Watermelon 91.51
Vegetables
Alfalfa sprouts 91.14
Artichokes - globe & French 84.38
Artichokes - Jerusalem 78.01
84.13* sulfured; 'without added sugar
84.46** *with skin; "without skin
87.93 canned or bottled
88.35* 'unsweetened
86.62* 'canned juice pack with skin
85.56* sulfured; 'without added sugar
86.59* 'frozen unsweetened
frozen unsweetened
84.95* 'canned, juice pack
bottled
90.10* 'canned unsweetened
pink, red, white
American type (slip skin)
canned or bottled
seedless
92.46* 'canned or bottled
92.52* 'canned or bottled
all varieties
87.49* 'canned juice pack
64.44* sulfured; 'without added sugar
86.47* 'canned juice pack
83.51 * 'canned juice pack
85.53 canned
85.20
89.97* 'frozen unsweetened
87.00* 'canned sweetened
89.51 * 'canned juice pack
86.50 boiled, drained
-------
Table 9-27. Mean Moisture Content of Selected Fruits and Vegetables Expressed as Percentages of Edible Portions (continued)
Food Moisture Content CPercentl 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 - lima
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
Celeriac
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
Corn - 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
94.91
Mung beans (sprouts)
90.40
93.39
boiled, drained
Mushrooms
91.81
91.08
boiled, drained
Mustard greens
90.80
94.46
boiled, drained
Okra
89.58
89.91
boiled, drained
Onions
90.82
92.24
boiled, drained
Onions - dehydrated or 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 CPercentl 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
Study
Survey Population Used
in Calculating Intake
Types of Data Used
Units
Food Items
KEY STUDIES
EPA Analysis of 1989-
91 USDA CSFII data
Per capita data;
consumer only data can
be calculated
1989-91 CSFII data;
Based on 3-day average individual
intake rate
g/kg-day; as consumed
Major food groups; individual food
items; exposed and protected fruits
and vegetables; USDA food
categories
RELEVANT STUDIES
AIHC, 1994
Per Capita
Based on the 1977-78 USDA NFCS
data provided in the 1989 version of
the Exposure Factors Handbook.
g/day
Distributions for vegetables using
@Risk software.
Canadian Department
of National Health and
Welfare, n.d.
Not known if per capita or
consumers only
1970-72 survey based on 24-hour
dietary recall
g/day; not known if as
consumed
Fruit and fruit products, vegetables
not including potatoes and nuts
and legumes
EPA's DRES
Per capita (i.e.,
consumers and
nonconsumers)
1977-78 NFCS
3-day individual intake data
g/kg-day; as consumed
Intake for a wide variety of fruits
and vegetables presented; complex
food groups were disaggregated
Pao etal., 1982
Consumers only serving
size data provided
1977-78 NFCS
3-day individual intake data
g; as consumed
Serving sizes for only a limited
number of products
USDA, 1980; 1992b;
1996a; 1996b
Per capita and consumer
only
1977-78 and 1987-88 NFCS, and
1994 and 1995 CSFII
1 -day individual intake data
g/day; as consumed
Total fruits and total vegetables
USDA, 1993
Per capita consumption
based on "food
disappearance"
Based on food supply and utilization
data provided by the National
Agricultural Statistics Service
(NASS), Customs Service Reports,
and trade associations
g/day; as consumed
Various food groups
U.S. EPA/ORP, 1984a;
1984b
Per capita
1977-78 NFCS
Individual intake data
g/day; as consumed
Exposed, protected, and leafy
produce
U.S. EPA/OST, 1989
Estimated lifetime dietary
intake
Based on FDA Total Diet Study Food
List which used 1977-78 NFCS data,
and NHANES II data
g/day; dry weight
Various food groups; complex
foods disaggregated
-------
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 CSFII
1989-91 Data
Total Veaetable Intake
4.3 g/kg-day
10 g/kg-day
see Table 9-4
EPA Analysis of CSFII
1989-91 Data
Individual Fruit and Veaetables Intake
see Table 9-5
—
—
EPA Analysis of CSFII
1989-91 Data
-------
Table 9-30.
Confidence in Fruit and Vegetable Intake Recommendations
Considerations
Rationale
Ratina
Study Elements
• Level of peer review
USDA CSFII survey receives high level of peer
review. EPA analysis of these data has been
peer reviewed outside the Agency.
High
• Accessibility
CSFII data are publicly available.
High
• Reproducibility
Enough information is included to reproduce
results.
High
• Focus on factor of interest
Analysis is specifically designed to address
food intake.
High
• 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
the time the analysis was conducted for the
Handbook.
High
• Adequacy of data collection
period
Survey is designed to collect short-term data.
Medium confidence for average
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
adequate.
High
• Representativeness of the
population
The population studied was the U.S.
population.
High
• Characterization of variability
Survey was not designed to capture long term
day-to-day variability. Short term distributions
are provided.
Medium
• Lack of bias in study design
(high rating is desirable)
Response rate was adequate.
Medium
• Measurement error
No measurements were taken. The study
relied on survey data.
N/A
Other Elements
• Number of studies
1; CSFII 1989-91 was the most recent data set
publicly available at the time the analysis was
conducted for the Handbook. Therefore, it was
the only study classified as key study.
Low
• Agreement between researchers
Although the CSFII was the only study
classified as key study, the results are in good
agreement with earlier data.
High
Overall Rating
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 analyzed the data was adequate.
However, due to the limitations of the survey
design estimation of long-term percentile values
CesDeciallv the UDDer Dercentilesl is uncertain.
High confidence in the average;
Low confidence in the long-term
upper percentiles
-------
Table 9A-1. Fraction of Grain and Meat Mixture Intake Represented by Various Food Items/Groups
Grain Mixtures
total vegetables
0.2360
tomatoes
0.1685
white potatoes
0.0000
total meats
0.0787
beef
0.0449
pork
0.0112
poultry
0.0112
dairy
0.1348
total grains
0.3146
Meat Mixtures
total vegetables
0.2778
tomatoes
0.1111
white potatoes
0.0333
total meats
0.3556
beef
0.2000
pork
0.0222
poultry
0.0778
dairy
0.0556
total grains
0.1333
-------
Appendix 9B. Food Codes and Definitions Used in Analysis of the 1989-91 USDA CSFII 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/j
uices baby 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 torn, 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, sausages, 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')
-------
Appendix 9B. Food Codes and Definitions Used in Analysis of the 1989-91 USDA CSFII Data (continued)
Food
Food Codes
Product
Corn
7510960
Corn, raw
7521621
Corn, cooked, white/fat not added
7521600
Corn, cooked, NS as to color/fat added
7521622
Corn, cooked, white/fat added
7521601
Corn, cooked, NS as to color/fat not added
7521625
Corn, white, cream style
7521602
Corn, cooked, NS as to color/fat added
7521630
Corn, yellow, canned, low sodium, NS fat
7521605
Corn, cooked, NS as to color/cream style
7521631
Corn, yell., canned, low sod., fat not add
7521607
Corn, cooked, dried
7521632
Corn, yell., canned, low sod., fat added
7521610
Corn, cooked, yellow/NS as to fat added
7521749
Hominy, cooked
7521611
Corn, cooked, yellow/fat not added
752175-
Hominy, cooked
7521612
Corn, cooked, yellow/fat added
7541101
Corn scalloped or pudding
7521615
Corn, yellow, cream style
7541102
Corn fritter
7521616
Corn, cooked, yell. & wh./NS as to fat
7541103
Corn with cream sauce
7521617
Corn, cooked, yell. & wh./fat not added
7550101
Corn relish
7521618
Corn, cooked, yell. & wh./fat added
76405-
Corn, baby
7521619
Corn, yellow, cream style, fat added
(does not include vegetable soups; vegetable mixtures; or
7521620
Corn, cooked, white/NS as to fat added
vegetable with meat mixtures; includes baby food)
Apples
6210110
Apples, dried, uncooked
6310141
Apple rings, fried
6210115
Apples, dried, uncooked, low sodium
6310142
Apple, pickled
6210120
Apples, dried, cooked, NS as to sweetener
6310150
Apple, fried
6210122
Apples, dried, cooked, unsweetened
6340101
Apple, salad
6210123
Apples, dried, cooked, with sugar
6340106
Apple, candied
6210130
Apple chips
6410101
Apple cider
6310100
Apples, raw
6410401
Apple juice
6310111
Applesauce, NS as to sweetener
6410405
Apple juice with vitamin C
6310112
Applesauce, unsweetened
6410409
Apple juice with calcium
6310113
Applesauce with sugar
6710200
Applesauce baby fd., NS as to str. or jr.
6310114
Applesauce with low calorie sweetener
6710201
Applesauce baby food, strained
6310121
Apples, cooked or canned with syrup
6710202
Applesauce baby food, junior
6310131
Apple, baked NS as to sweetener
6720200
Apple juice, baby food
6310132
Apple, baked, unsweetened
(includes baby food; except mixtures)
6310133
Apple, baked with sugar
Tomatoes
74- Tomatoes and Tomato Mixtures
raw, cooked, juices, sauces, mixtures, soups,
sandwiches
Snap Beans
7510180
Beans, string, green, raw
7520602
Beans, string, cooked, yellow/fat
7520498
Beans, string, cooked, NS color/fat added
7540301
Beans, string, green, creamed
7520499
Beans, string, cooked, NS color/no fat
7540302
Beans, string, green, w/mushroom sauce
7520500
Beans, string, cooked, NS color & fat
7540401
Beans, string, yellow, creamed
7520501
Beans, string, cooked, green/NS fat
7550011
Beans, string, green, pickled
7520502
Beans, string, cooked, green/no fat
7640100
Beans, green, string, baby
7520503
Beans, string, cooked, green/fat
7640101
Beans, green, string, baby, str.
7520511
Beans, str., canned, low sod.,green/NS fat
7640102
Beans, green, string, baby, junior
7520512
Beans, str., canned, low sod.,green/no fat
7640103
Beans, green, string, baby, creamed
7520513
Beans, str., canned, low sod.,green/fat
(does not include vegetable soups; vegetable mixtures; or
7520600
Beans, string, cooked, yellow/NS fat
vegetable with meat mixtures; includes baby foods)
7520601
Beans, string, cooked, yellow/no fat
Beef
21- Beef
(excludes meat, poultry, and fish with non-meat items; frozen
beef, nfs
plate meals; soups and gravies with meat, poultry and fish
beef steak
base; and gelatin-based drinks; includes baby food)
beef oxtails, neckbones, ribs
roasts, stew meat, corned, brisket, sandwich steaks
ground beef, patties, meatballs
other beef items
beef babv food
-------
Appendix 9B. Food Codes and Definitions Used in Analysis of the 1989-91 USDA CSFII Data (continued)
Food
Product
Food Codes
Pork
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)
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 gelatin-based drinks)
Poultry
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)
Eggs
3- Eggs
eggs
egg mixtures
egg substitutes
eggs baby food
froz. meals with egg as main ingred.
(includes baby foods)
Broccoli
722- Broccoli (all forms)
(does not include vegetable soups; vegetable mixtures; or
vegetable with meat mixtures)
Carrots
7310-
7311140
7311200
76201-
Carrots (all forms)
Carrots in Sauce
Carrot Chips
Carrots, baby
(does not include vegetable soups; vegetable mixtures; or
vegetable with meat mixtures; includes baby foods except
mixtures)
Pumpkin
732-
733-
76205-
Pumpkin (all forms)
Winter squash (all forms)
Squash, baby
(does not include vegetable soups; vegetables mixtures; or
vegetable with meat mixtures; includes baby foods)
Asparagus
7510080
75202-
7540101
Asparagus, raw
Asparagus, cooked
Asparagus, creamed or with cheese
(does not include vegetable soups; vegetables mixtures, or
vegetable with meat mixtures)
Lima Beans
7510200
752040-
752041-
75402-
Lima Beans, raw
Lima Beans, cooked
Lima Beans, canned
Lima Beans with sauce
(does not include vegetable soups; vegetable mixtures; or
vegetable with meat mixtures; does not include succotash)
Cabbage
7510300
7510400
7510500
7514100
7514130
75210-
75211-
Cabbage, raw
Cabbage, Chinese, raw
Cabbage, red, raw
Cabbage salad or coleslaw
Cabbage, Chinese, salad
Chinese Cabbage, cooked
Green Cabbaae. cooked
75212- Red Cabbage, cooked
752130- Savoy Cabbage, cooked
75230- Sauerkraut, cooked
7540701 Cabbage, creamed
755025- Cabbage, pickled or in relish
(does not include vegetable soups; vegetable mixtures; or
veaetable with meat mixtures')
-------
Appendix 9B. Food Codes and Definitions Used in Analysis of the 1989-91 USDA CSFII Data (continued)
Food
Product
Food Codes
Lettuce
75113- Lettuce, raw
75143- Lettuce salad with other veg.
7514410 Lettuce, wilted, with bacon dressing
7522005 Lettuce, cooked
(does not include vegetable soups; vegetable mixtures; or
vegetable with meat mixtures)
Okra
7522000 Okra, cooked, NS as to fat
7522001 Okra, cooked, fat not added
7522002 Okra, cooked, fat added
7522010 Lufta, cooked (Chinese Okra)
7541450 Okra, fried
7550700 Okra, pickled
(does not include vegetable soups; vegetable mixtures; or
vegetable with meat mixtures)
Peas
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)
Cucumbers
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)
Beets
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)
Strawberrie
s
6322- Strawberries
6413250 Strawberry Juice
(includes baby food; except mixtures)
Other
Berries
6320- Other Berries
6321- Other Berries
6341101 Cranberry salad
6410460 Blackberry Juice
64105- Cranberry Juice
(includes baby food; except mixtures)
Peaches
62116- Dried Peaches
63135- Peaches
6412203 Peach Juice
6420501 Peach Nectar
67108- Peaches ,baby
6711450 Peaches, dry, baby
(includes baby food; except mixtures)
Pears
62119- Dried Pears
63137- Pears
6341201 Pear salad
6421501 Pear Nectar
67109- Pears, baby
6711455 Pears, dry, baby
6721200 Pear juice, baby
(includes baby food; except mixtures)
-------
Appendix 9B. Food Codes and Definitions Used in Analysis of the 1989-91 USDA CSFII Data (continued)
Food
Food Codes
Product
EXPOSED/PROTECTED FRUITS/VEGETABLES, 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-
Acerola
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 foods/juices 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-
Genip
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-
PineaDDle
mixtures')
-------
Appendix 9B. Food Codes and Definitions Used in Analysis of the 1989-91 USDA CSFII Data (continued)
Food
Food Codes
Product
Exposed
721-
Dark Green Leafy Veg.
752167-
Cucumber, cooked
Veg.
722-
Dark Green NonleafyVeg.
752170-
Eggplant, cooked
74-
Tomatoes and Tomato Mixtures
752171-
Fern shoots
7510050
Alfalfa Sprouts
752172-
Fern 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 CSFII 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
Hominy
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-
Onions, 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
leafy
nonleafy, dk. gr. veg. soups
Deep
73- Deep Yellow Vegetables
Yellow
all forms
Vegetables
carrots, pumpkin, squash, sweetpotatoes, dp. yell.
veg.
soups
Other
75- Other Vegetables
Vegetables
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-ADricot Juice, babv food
(excludes dried fruits}
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Appendix 9B. Food Codes and Definitions Used in Analysis of the 1989-91 USDA CSFII Data (continued)
Food
Food Codes
Product
Other Fruits
62-
Dried Fruits
67204-
Baby Juices
63-
Other Fruits
67212-
Baby Juices
64-
Fruit Juices and Nectars Excluding Citrus
67213-
Baby Juices
671-
Fruits, baby
6725-
Baby Juice
67202-
Apple Juice, baby
673-
Baby Fruits
67203-
Baby Juices
674-
Baby Fruits
MIXTURES
Meat
27- Meat Mixtures
(includes frozen plate meals and soups)
Mixtures
28-
Grain
58- Grain Mixtures
(includes frozen plate meals and soups)
Mixtures
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REFERENCES FOR CHAPTER 9
American Industrial Health Council (AIHC). (1994) Exposure factors sourcebook. AIHC,
Washington, DC.
Canadian Department of National Health and Welfare, 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) 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 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]
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Volume II - Food Ingestion Factors
Chapter 10 - Intake of Fish and Shellfish
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 10A
APPENDIX 10B
APPENDIX 10C
Table
10-1.
Table
10-2.
Table
10-3.
Table
10-4.
Table
10-5.
Table
10-6.
Table
10-7.
Table
10-8.
Table
10-9.
Table
10-10
Table
10-11
Table
10-12
Total Fish Consumption by Demographic Variables
Mean and 95th Percentile of Fish Consumption (g/day) by Sex and Age
Percent Distribution of Total Fish Consumption for Females by Age
Percent Distribution of Total Fish Consumption for Males by Age
Mean Total Fish Consumption by Species
Best Fits of Lognormal Distributions Using the NonLinear Optimization
(NLO) Method
Per Capita Distribution of Fish Intake (g/day) by Habitat and Fish Type for
the U.S. Population (Uncooked Fish Weight)
Per Capita Distribution of Fish (Finfish and Shellfish) Intake (g/day) by
Habitat for Consumers Only (Uncooked Fish Weight)
Per Capita Distribution of Fish Intake (mg/kg-day) by Habitat and Fish Type
for U.S. Population (Uncooked Fish Weight)
Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day) by
Habitat for Consumers Only (Uncooked Fish Weight)
Per Capita Distribution of Fish Intake (g/day) by Habitat and Fish Type for
the U.S. Population (Cooked Fish Weight - As Consumed))
Per Capita Distribution of Fish Intake (g/day) by Habitat for Consumers Only
(Cooked Fish Weight - As Consumed))
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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 Consumed
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)
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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 Gender - 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
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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
Households 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 sport-caught
sources) For 1992 Lake Ontario Anglers
Table 10-69. Mean Annual Fish Consumption (g/day) for Lake Ontario Anglers, 1992, by
Sociodemographic Characteristics
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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 10-78. Mean Number of Local Fish Meals Consumed Per Year by Time Period and
Selected Characteristics for All Respondents (Mohawk, N=97; Control,
N=154)
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 10B-1. Percent of Fish Meals Prepared Using Various Cooking Methods by
Residence Size
Table 10B-2. Percent of Fish Meals Prepared Using Various Cooking Methods by Age
Table 10B-3. Percent of Fish Meals Prepared Using Various Cooking Methods by
Ethnicity
Table 10B-4. Percent of Fish Meals Prepared Using Various Cooking Methods by
Education
Table 10B-5. Percent of Fish Meals Prepared Using Various Cooking Methods by Income
Table 10B-6. Percent of Fish Meals Where Fat was Trimmed or Skin was Removed, by
Demographic Variables
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Table 10B-7. Method of Cooking of Most Common Species Kept by Sportfishermen
Table 10B-8. Adult Consumption of Fish Parts
Table 10C-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 10C-3. Daily Average Per Capita Estimates of Fish Consumption As Consumed
Fish - Mean Consumption by Species Within Habitat - U.S. Population
Table 10C-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
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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 be 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.
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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 re-
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 interviews 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
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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 population, 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 10A, 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
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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
offish consumption which was performed by the National Purchase Diary (NPD) during the
period of September, 1973 to August, 1974. 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 offish prepared and
consumed, and the number of servings consumed by household members and guests.
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Both meals eaten at home and away from 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 19+ 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
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optimal parameters. Ruffle et al. (1994) determined that, of the three methods, the non-
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 lognormal 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 (//), standard
deviation (s), and min SS, for all 89 modeled distributions. These parameters can be used
to determine percentiles of the corresponding distribution of average daily fish
consumption rates through the relation DFC(p)=exp[//+ 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[// + 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 was 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.
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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 mean /u, 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 (CSFII) — The USDA conducts the CSFII on an ongoing basis. U.S. EPA used
the 1989, 1990, and 1991 CSFII data to generate fish intake estimates. Participants in the
CSFII 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 CSFII started in April of the
given year and was completed in March of the following year.
The CSFII 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 offish 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 containing 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 in the given fish-
by-habitat category and then dividing by 3. Individual consumption per day consuming
fish (g/day) 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.
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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 100a percentile and 100 (1-a) percentile estimates from
the non-parametric distribution of the given point estimate (U.S. EPA, 1996a).
Analyses offish 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 10C. Table 10-8 displays the
mean and various percentiles of the distribution of total fish intake per day consuming 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 10-21 through 10-28 for consumers only. Tables 10-29 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 the percent fish content of each of
these codes. By contrast, some analyses of the USDA National Food Consumption
Surveys (NFCSs) which reported per 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.
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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 offish intake per (fish) eating occasion (Table 10-8).
Also, it should be noted that the 1989-91 CSFII data are not the most recent intake
survey data. USDA has recently made available data from its 1994 and 1995 CSFII. 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 data
(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 CSFII 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 offish consumed
per eating occasion. For each individual consuming fish in the 3 day survey period, the
quantity offish consumed per eating occasion was derived by dividing the total reported
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 offish consumed per fish meal was 117 g, with a 95th percentile of 284
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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 offish 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 detailed 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 offish 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. These 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.
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The 1987-1988 NFCS was also utilized to estimate consumption of home 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 average 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 offish 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
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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
survey 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 offish 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 per 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 CSFII
data. It should be noted that an all inclusive description for seafood was not presented in
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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 CSFII analysis.
10.4. KEY RECREATIONAL (MARINE FISH STUDIES)
National Marine Fisheries Service (1986a, b, c; 1993) - The National Marine Fisheries
Service (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 marine
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
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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 B1 or type B2 catch. The type A catch denoted fish that were taken
whole from the fishing site and were available for inspection. The type B1 and B2 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 B1 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 B1 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) * lA + (wt of B1 catch) * lB] * [Fishing frequency] (Eqn. 10-1)
where lA (lB) are indicator variables equal to 1 if the type A (B1) 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 (Chemrisk, 1991; Puffer
et al., 1981; West et al., 1989). Thus, the average daily intake rate (ADI) for each angler
was calculated as
ADI = Y * (0.5)/[2.5 * 365]
(Eqn. 10-2)
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Note that ADI will be 0 for those anglers who either did not 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.
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 B1 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
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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 uncertainty 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.
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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]
(Eqn. 10-3)
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.
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 10B. 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 employ weights reflective of sampling probabilities
will overestimate the target population intake distribution and will, in fact, be more
reflective of the "resource utilization distribution". Therefore, the reported 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
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37.3 from Puffer et al., 1981) and the 90th percentile at 35 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 percentiles 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 mid-
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 evenings; 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
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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. The 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 offish consumed per angling trip (380 g/person-trip) was based on data on mean
fish catch weight and 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
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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 //g/g. 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 long-
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 subsistence 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).
Table 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
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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 (self-
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.
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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 offish 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
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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 offish meals by the reported percent offish meals obtained from
recreational sources; recreational sources were defined 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 consumers) 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..
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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, 0.78 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 October, 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 during these seasons.
"Consuming anglers" were defined as those anglers who consumed freshwater fish
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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 (Chemrisk, 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
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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 and 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 23.1 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 based 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
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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, 1991-1992 -
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 etal., 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 the 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 offish, respectively.
A total of 2,681 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 survey 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
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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, 1992 - The objectives of this study were to provide
accurate estimates offish 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 offish 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 fishing trips to Lake
Ontario and 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 fishing 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.
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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 lower intake rates on average.
The main advantage of this study is the diary format. This format provides more
accurate information on fishing participation and 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, 853 of 1,410 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 burden levels of PCBs and DDE 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
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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 offish 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 offish 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 offish 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 sport-
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) offish
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 offish 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 questionnaire was
designed to measure catch and consumption offish, as well as methods of fish preparation
and knowledge of and attitudes towards health advisories (Connelly et al., 1992). The
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survey adjusted response rate was 52.8 percent (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 10B.
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
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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. The 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 percent 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 interviewed
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
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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 capita harvests were calculated for
each community. For the four urban centers, fish harvests ranged from 5 to 21 pounds
per capita per year (6.2 g/day to 26.2 g/day).
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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 person
each year in the western region of the United States. This contrasts with a median total
resource harvest of 260 Ibs/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 Factors Sourcebook
(AIHC, 1994) provides data for non-marine fish intake consistent with this document.
However, the total fish intake rate recommended in AIHC (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 CSFII (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
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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 were 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 of the Columbia
River Basin - CRITFC (1994) conducted a fish consumption survey among four 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 offish 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).
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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 (74.4 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 the 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 self-
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 10-74 gives the fish intake distribution for children 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
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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 in 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 offish meals
consumed per week during the last 2 months (recent consumption) before 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
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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 offish
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 offish 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.
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The dietary assessment involved the report by each participant on the consumption
of various foods with emphasis on local species offish and 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 due to 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 observed 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
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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 offish 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. Pao
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
offish 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 offish consumed, are presented in Appendix 10B.
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
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If
"as consumed" portions offish 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 = f residue level) x f 9-fat )
(Eqn. 10-4)
{ g-fat j { g-product/
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 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 offish presented in Table 10-80 and the following equation:
IRdw = IRac*[(100-W)/100] (Eqn. 10-5)
"Dry weight" intake rates may be converted to "as consumed" rates by using:
IRac = IRdw/[(100-W)/100]
(Eqn. 10-6)
where:
IRdw = dry weight intake rate;
IRac = as consumed intake rate; and
W = percent water content.
10.10. RECOMMENDATIONS
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 upper 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 body (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
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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 means 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 long-
term consumption) is U.S. EPA (1996a) analysis of USDA CSFII 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
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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 concentration. 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.
CSFII 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 reflect 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 CSFII 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 percentiles 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 ji by 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 CSFII 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 CSFII 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 CSFII data are believed to
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be appropriate for assessing ingestion exposure for current populations because the rate
offish 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 CSFII 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
etal., 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 harvests 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.
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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.
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APPENDIX 10A
RESOURCE UTILIZATION DISTRIBUTION
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Appendix 10A. 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 50th percentile of the resource
utilization distribution is that level such that 50 percent of the overall consumption in
the population is done by individuals 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 simply weights 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 offish consumption
may be related (approximately) to the (standard) percentiles offish 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 C|) by the frequency of
fishing (say f,). 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/
f,) should be employed in the analysis of the 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/ f,), one multiplies (1/ f,) by the fish consumption level of f, C| to get new
weights of C|.
Now if C| (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 assumed) 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.
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The accuracy of this approximation of the resource utilization distribution offish by
the (standard) distribution offish consumption derived from an unweighted analysis of
creel survey data depends then on two factors, how approximately constant the C|'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 re-
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 Yp(R) and 100-p percent is done by individuals with
consumption above Yp(R).
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Table 10-1. Total Fish Consumption by
Demographic Variables3
Intake (a/Derson/dav)
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
Aae (vears)
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 Reaion
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 TvDe
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, 1M - 2M
15.4
41.7
Outside central city, 1M - 2M
14.5
41.5
Central city, 500K - 1M
14.2
41.0
Outside central city, 500K - 1M
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 (g/day) by Sex and Agea
Age
(years)
Total Fish
Mean
95th Percentile
Female
0 - £
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 - £
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 of Total Fish Consumption for Females by Age3
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
2.2
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
3 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 Age3
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
3 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.
-------
Table 10-5. Mean Total Fish Consumption by Species®
Mean consumption
Mean consumption
Species
(g/day)
Species
(g/day)
Not reported
1.173
Mullet"
0.029
Aba lone
0.014
Oysters"
0.291
Anchovies
0.010
Perch (Freshwater)"
0.062
Bassb
0.258
Perch (Marine)
0.773
Bluefish
0.070
Pike (Marine)"
0.154
Bluegills"
0.089
Pollock
0.266
Bonito"
0.035
Pom pa no
0.004
Buffalofish
0.022
Rockfish
0.027
Butterfish
0.010
Sablefish
0.002
Carpb
0.016
Salmon"
0.533
Catfish (Freshwater)b
0.292
Scallops"
0.127
Catfish (Marine)"
0.014
Scup"
0.014
Clams"
0.442
Sharks
0.001
Cod
0.407
Shrimp"
1.464
Crab, King
0.030
Smelt"
0.057
Crab, other than King"
0.254
Snapper
0.146
Crappie"
0.076
Snook"
0.005
Croaker"
0.028
Spot"
0.046
Dolphin"
0.012
Squid and Octopi
0.016
Drums
0.019
Sunfish
0.020
Flounders"
1.179
Swordfish
0.012
Groupers
0.026
Tilefish
0.003
Haddock
0.399
Trout (Freshwater)"
0.294
Hake
0.117
Trout (Marine)"
0.070
Halibut"
0.170
Tuna, light
3.491
Herring
0.224
Tuna, White Albacore
0.008
Kingfish
0.009
Whitefish"
0.141
Lobster (Northern)"
0.162
Other finfish"
0.403
Lobster (Spiny)
0.074
Other shellfish"
0.013
Mackerel, Jack
0.002
Mackerel, other than Jack
0.172
a 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.
" 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 Teenagers Children
Shellfish
1.370
-0.183
0.854
o
0.858
1.092
0.730
(min SS)
27.57
1.19
16.06
Finfish (freshwater)
n
0.334
0.578
-0.559
a
1.183
0.822
1.141
(min SS)
6.45
23.51
2.19
Finfish (saltwater)
n
2.311
1.691
0.881
a
0.72
0.830
0.970
(min SSI
30.13
0.33
4.31
The following eguations may be used with the appropriate // and o values to obtain an average Daily Consumption Rate (DCR), in
grams, and percentiles of the DCR distribution.
DCR50 = exp (//)
DCR90 = exp [// + z(0.90) • o]
DCR99 = exp [// + z(0.99) • o]
DCRavg = exp [// + 0.5 • o2]
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 (65.4-74.2)
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
95th%
290.0
267.1 -325.6
99th%
489.3
424.9 - 534.2
Percent Consuming
18.5
Marineb 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 Fishc 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 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 10-9. Per Capita Distribution of Fish 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
e
Mean
50th%
90th%
95th%
99th%
58.1 (48.4-67.7)
0.0 (0.0 - 0.0)
5.9 (0.0-12.3)
340.5 (252.9-410.1)
1,401.9 (1,283.9- 1,511.8)
35.9 (30.2 - 41.6)
0.0 (0.0 - 0.0)
0.0 (0.0 - 3.8)
190.0 (155.7-268.3)
953.5 (871.3 - 1,007.4)
94.0 (83.4- 104.6)
0.0 (0.0 - 0.0)
251.8 (222.5 - 282.6)
677.7 (631.9-729.1)
1,593.3 (1,511.8 - 1,659.2)
Marine
Mean
50th%
90th%
95th%
99th%
215.8 (195.9-235.6)
0.0 (0.0 - 0.0)
783.4 (752.5 - 842.2)
1,208.1 (1,149.5- 1,264.9)
2,400.0 (2,284.2-2,660.1)
24.3 (20.6 - 28.0)
0.0 (0.0 - 0.0)
0.0 (0.0 - 0.0)
0.0 (0.0 - 88.8
701.3 (636.2 - 944.7)
240.1 (220.1 -260.0)
0.0 (0.0 - 0.0)
855.6 (809.7 - 909.8)
1,271.5 (1,227.2 - 1,371.2)
2,575.3 (2,393.2 - 2,708.6)
All Fish
Mean
50th%
90th%
95th%
99th%
273.9 (252.0 - 295.7)
0.0 (0.0 - 0.0)
966.1 (893.3- 1,039.5)
1,434.3 (1,371.2 - 1,526.8)
2,857.5 (2,649.6 - 3,003.6)
60.2 (52.3 - 68.2)
0.0 (0.0 - 0.0)
0.0 (0.0 - 47.4)
372.5 (324.1 -460.5)
1,412.4(1,296.0- 1,552.1)
334.1 (311.3-356.9)
0.0 (0.0 - 0.0)
1.123.1 (1,090.8- 1,179.0)
1.684.2 (1,620.5- 1,718.5)
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 (mg/kg-day) 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
50th%
819.7
736.9 -
895.7
90th%
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
90th%
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 Fishc
Mean
2,145.3
2,055.9 -
2,234.6
50th%
1,662.8
1,610.7-
1,720.1
90th%
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%
0.3 (0.0 - 0.7)
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 Fishc
Mean
100.6
96.7- 104.6
50th%
80.8
79.3 - 83.9
90th%
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)
Age
Sample Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.
99th % (90% B.I.
Females
14 or under
15-44
45 or older
All ages
Males
14 or under
15-44
45 or older
All ages
Both Sexes
14 or under
15-44
45 or older
All ages
1431
2891
2340
6662
1546
2151
1553
5250
2977
5042
3893
11912
1.58 (1.06-2.10)
4.28 (3.55-5.02)
5.27 (4.21-6.32)
4.02 (3.43-4.61)
2.17 (1.32-3.02)
6.14 (5.08-7.19)
7.12(5.87-8.38)
5.46 (4.81-6.11)
1.88(1.36-2.40)
5.17(4.46-5.87)
6.11 (5.20-7.02)
4.71 (4.17-5.25)
1.44 (0.00-4.07)
10.90(8.79-13.84)
18.72(15.19-22.12)
10.66(8.11-13.19)
0.99 (0.21-6.67)
18.19(10.21-24.20)
22.67(19.28-27.83)
16.05(12.41-19.30)
1.31 (0.00-4.33)
13.88(12.05-17.21)
21.48(16.69-23.33)
12.62(10.91-13.98)
12.51 (6.00-14.20)
28.80 (26.26-33.53)
34.67 (29.17-39.38)
28.11 (23.14-31.27)
14.94(11.88-22.33)
48.61 (35.42-54.65)
46.62 (41.27-58.01)
40.29(35.92-43.73)
13.90(9.32-15.05)
36.21 (28.64-47.31)
40.55(35.80-47.31)
32.16(29.81-35.15)
36.09 (28.53-43.20)
70.87 (64.74-90.56)
85.35 (71.71-100.50)
71.98 (60.38-86.40)
48.72 (37.48-52.29)
96.32 (85.60-115.75)
103.07(86.41-125.11)
86.40 (78.37-103.07)
40.77(35.15-44.82)
86.14(74.67-96.67)
88.18(85.33-103.07)
82.45 (77.17-86.40)
Percentile intervals (B.I.) 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)
Age
Sample Size Mean (90% C.I.)
90th % (90% B.I.) 95th % (90% B.I.
99th % (90% B.I.)
Females
14 or under
1431
15-44
2891
45 or older
2340
All ages
6662
Males
14 or under
1546
15-44
2151
45 or older
1553
All ages
5250
Both Sexes
14 or under
2977
15-44
5042
45 or older
3893
All ages
11912
6.60 (5.16-8.05)
9.97 (8.94-11.01)
12.59(11.36-13.82)
10.10(9.27-10.93)
7.25 (5.72-8.79)
13.33(11.89-14.77)
13.32(11.73-14.92)
11.85(10.75-12.95)
6.93 (5.63-8.23)
11.58(10.55-12.60)
12.92(11.86-13.98)
10.94(10.14-11.73)
24.84(18.67-31.20)
36.83(31.42-41.99)
42.92(38.92-47.66)
36.97 (34.86-37.33)
24.85(19.92-33.85)
52.73 (48.34-55.80)
50.39 (47.13-53.33)
47.13(44.52-49.80)
24.88 (22.64-28.08)
44.24(39.84-46.70)
46.51 (38.98-50.97)
39.51 (37.29-42.91)
37.32 (32.27-42.05)
55.53 (47.67-59.59)
63.85 (57.27-72.36)
55.54(51.67-56.98)
49.89 (42.09-56.45)
71.49 (63.99-80.00)
64.51 (61.64-74.58)
64.50 (62.46-67.53)
42.07(38.15-48.96)
62.18(57.88-69.72)
64.19(60.67-72.00)
59.62(57.03-61.84)
87.05 (63.26-112.06)
105.32(96.98-112.00)
103.08(91.61-121.52)
102.01 (97.67-110.69)
92.64 (65.87-132.39)
116.51 (106.06-143.31)
116.86(106.93-144.94)
113.94(103.47-130.00)
91.64 (68.59-112.06)
110.07(103.50-120.49)
113.33(104.59-119.53)
106.84(104.59-114.55)
Percentile intervals (B.I.) 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)
Age
Sample Size Mean (90% C.I.
90th % (90% B.I.) 95th % (90% B.I.
99th % (90% B.I.
Females
14 or under
15-44
45 or older
All ages
Males
14 or under
15-44
45 or older
All ages
Both Sexes
14 or under
15-44
45 or older
All ages
1431 8.19 (6.53-9.84)
2891 14.25(12.96-15.55)
2340 17.86(16.19-19.52)
6662 14.13(13.07-15.18)
1546 9.42(7.60-11.25)
2151 19.46(17.75-21.18)
1553 20.45(18.41-22.49)
5250 17.31 (16.04-18.59)
2977 8.82(7.39-10.24)
5042 16.74(15.54-17.94)
3893 19.03(17.54-20.52)
11912 15.65(14.67-16.63)
32.28 (26.78-37.33)
47.13(41.95-55.83)
56.70(54.13-62.99)
46.44 (43.63-49.67)
34.85 (27.77-42.09)
68.60 (65.74-74.70)
64.44 (61.33-69.27)
60.23(56.91-62.99)
32.88 (27.97-37.11)
57.88(56.00-60.85)
61.32(56.00-65.74)
55.02(51.38-56.00)
43.09(37.99-51.55)
71.58 (64.74-82.11)
81.94 (74.63-88.23)
70.23 (67.27-73.91)
52.85 (49.93-62.50)
93.65(85.60-96.96)
87.21 (85.33-100.19)
85.69(80.61-93.32)
50.95 (44.64-53.86)
84.59 (79.91-90.83)
86.21 (77.42-94.70)
78.34 (75.21-80.56)
95.19 (63.26-113.96)
120.84(110.69-132.79)
130.51 (122.02-140.21)
120.22(112.06-126.07)
98.36 (71.74-132.39)
149.07(142.73-154.41)
168.49(143.78-174.55)
143.91 (135.35-154.15)
98.33 (86.40-113.96)
138.21 (122.84-149.15)
143.91 (131.12-171.37)
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 Aged 18 Years and Older by Habitat - As Consumed
Grams/day
90% Interva
Habitat
Statistic
Estimate
Lower Bound
Upper 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)
Age
Sample Size Mean (90% C.I.'
90th % (90% B.I.;
95th % (90% B.I.:
99th % (90% B.I.:
Females
14 or under
15-44
45 or older
All ages
Males
14 or under
15-44
45 or older
All ages
Both Sexes
14 or under
15-44
45 or older
All ages
1431 67.12(46.16-88.09)
2891 66.22 (55.35-77.08)
2340 78.29 (63.27-93.30)
6662 70.32 (60.09-80.55)
1546 73.93(44.89-102.96)
2151 75.35(62.00-88.70)
1553 86.75(70.91-102.58)
5250 78.36(69.10-87.61)
2977 70.59 (53.29-87.89)
5042 70.58 (61.27-79.89)
3893 82.12(70.19-94.05)
11912 74.16(65.74-82.57)
57.30 (0.00-128.52)
174.96 (115.11-205.05)
273.63 (209.63-300.11)
177.91 (132.69-212.30)
28.10(8.86-231.33)
230.13(132.30-309.85)
291.50 (230.15-364.24)
231.57 (186.27-276.04)
53.24 (0.00-118.48)
197.11 (154.78-229.29)
286.93 (228.49-332.88)
204.00 (177.97-225.16)
460.16(218.56-559.86)
451.04 (421.65-505.49)
548.66 (466.18-633.87)
497.30 (442.20-558.85)
723.93 (423.52-785.58)
577.84 (410.09-706.31)
584.96 (512.66-630.77)
589.22 (549.64-630.09)
556.34 (417.11-683.80)
502.26 (410.09-604.29)
566.30 (505.10-625.21)
547.64 (505.10-565.37)
1356.54(1295.24-2118.93)
1188.16(977.85-1278.63)
1251.00 (1038.97-1324.90)
1269.76 (1093.19-1328.24)
1290.10(1279.82-1355.11)
1132.23 (1028.61-1416.47)
1231.60 (1115.58-1566.68)
1265.10(1133.18-1355.11)
1347.67 (1279.82-1390.82)
1167.57 (1021.96-1279.82)
1251.55 (1115.58-1324.90)
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-
for the U.S. Population by Age and Gender - As Consumed
(Marine)
day)
Age
Sample Size Mean (90% C.I.)
90th % (90% B.I.)
95th % (90% B.I.:
99th % (90% B.I.:
Females
14 or under
15-44
45 or older
All ages
Males
14 or under
15-44
45 or older
All ages
Both Sexes
14 or under
15-44
45 or older
All ages
1431 256.90(207.04-306.76)
2891 159.79(142.76-176.82)
2340 191.08(171.33-210.83)
6662 190.61 (172.89-208.33)
1546 230.25(188.33-272.17)
2151 165.92(147.73-184.12)
1553 164.37(144.87-183.87)
5250 181.08(163.00-199.15)
2977 243.31 (202.43-284.18)
5042 162.72(148.13-177.31)
3893 178.99(164.13-193.84)
11912 186.06(170.81-201.31)
936.94 (723.73-1055.43)
573.49 (493.39-663.16)
644.33 (608.39-725.83)
658.64 (627.61-700.33)
846.57 (734.83-987.18)
626.85 (593.90-680.90)
621.00 (562.90-691.03)
670.19(622.62-714.53)
873.87 (741.53-1093.69)
602.58 (564.88-648.54)
628.06 (555.84-700.65)
663.00 (627.39-717.18)
1545.15(1260.24-1760.26)
873.73 (780.56-929.55)
978.84 (881.06-1103.01)
1024.76 (958.94-1096.14)
1504.37 (1320.60-1749.26)
933.05 (833.43-982.30)
839.06 (800.23-946.97)
981.87 (934.45-1071.54)
1522.52 (1371.10-1587.20)
893.82 (856.58-940.85)
914.67 (825.21-1040.75)
991.96 (960.40-1044.69)
3060.22 (2403.50-4354.46)
1700.21 (1578.65-1815.48)
1694.58 (1488.32-1791.84)
1979.45(1793.40-2137.78)
2885.08 (2631.87-3430.60)
1472.98 (1411.97-1525.47)
1422.94(1293.89-1791.31)
1923.63 (1802.17-1972.86)
3059.93 (2732.63-3430.60)
1576.09 (1503.11-1697.71)
1568.85 (1483.71-1760.74)
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)
Age
Sample Size Mean (90% C.I.I
90th % (90% B.I.;
95th % (90% B.I.:
99th % (90% B.I.;
Females
14 or under
15-44
45 or older
All ages
Males
14 or under
15-44
45 or older
All ages
Both Sexes
14 or under
15-44
45 or older
All ages
1431 324.02(264.25-383.80)
2891 226.01 (205.01-247.01)
2340 269.37 (243.36-295.38)
6662 260.93 (239.15-282.72)
1546 304.17(251.91-356.43)
2151 241.27(219.25-263.29)
1553 251.12 (225.48-276.76)
5250 259.43(239.81-279.06)
2977 313.90(268.42-359.38)
5042 233.30 (216.16-250.44)
3893 261.10 (240.34-281.87)
11912 260.22 (242.60-277.83)
1091.52 (929.29-1407.54)
755.51 (641.02-879.29)
862.18(796.63-955.82)
873.61 (796.63-911.89)
1172.17(1085.62-1320.60)
867.70 (814.06-919.25)
797.83 (762.30-858.52)
894.96 (842.29-938.16)
1128.26 (1005.58-1320.60)
828.12(771.73-868.89)
818.10(771.23-882.53)
880.47 (844.35-918.79)
1690.99 (1513.97-2072.35)
1126.02 (975.49-1269.56)
1296.64(1186.00-1344.85)
1323.29 (1269.56-1418.85)
1575.43(1496.19-1943.82)
1208.43(1101.68-1266.32)
1122.80 (1041.28-1266.18)
1298.95 (1224.82-1366.86)
1679.91 (1546.20-1848.43)
1155.30 (1102.57-1212.19)
1249.97 (1101.32-1323.53)
1308.54(1267.15-1346.71)
3982.60 (3219.32-4568.45)
2195.86 (1762.90-2310.54)
2147.32 (1791.84-2354.25)
2361.12(2272.41-2598.14)
3393.84 (2731.95-3733.22)
1760.48(1611.45-1851.26)
1922.33 (1786.53-2275.93)
2346.64(1972.86-2631.87)
3419.49(3184.04-3733.22)
2003.46(1787.65-2182.19)
1967.01 (1796.52-2257.50)
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
Habitat
90% Interval
Statistic
Estimate
Lower Bound
Upper Bound
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
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
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
1,133.18
1,264.74
99th %
2,014.67
1,839.55
2,180.87
Fresh/Estuarine
Marine
All Fish
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)
Age
Sample
Size
Mean (90% C.I.)
90th % (90% B.I.)
95th % (90% B.I.)
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 (173.88-219.03)
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.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 10-22. 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(74.43-82.51)
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 ages
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 ages
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
Habitat
Statistic
90% Interval
Estimate
Lower Bound
Upper Bound
Fresh/Estuarine
Mean
70.91
64.16
77.65
n = 1,541
50th %
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
50th %
77.56
74.89
78.52
N = 57,830,000
90th %
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(1011.55-1223.94)
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.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 10-26. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day)
for Consumers Only 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
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 ages
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.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 10-27. Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day)
for Consumer 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
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 ages
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 Only Aged 18 Years and Older by 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
Sample Size Mean (90% C.I.) 90th % (90% B.I.)
95th % (90% B.I.)
99th % (90% B.I.)
Females
14 or under
15-44
45 or older
All ages
Males
14 or under
15-44
45 or older
All ages
Both Sexes
14 or under
15-44
45 or older
All ages
1431 1.99(1.34-2.64)
2891 5.50 (4.53-6.48)
2340 6.65 (5.30-8.00)
6662 5.13(4.37-5.88)
1546 2.69(1.62-3.76)
2151 7.87(6.46-9.29)
1553 8.87 (7.32-10.43)
5250 6.91 (6.07-7.75)
2977 2.35 (1.70-3.00)
5042 6.64 (5.71-7.56)
3893 7.66(6.50-8.81)
11912 5.98(5.29-6.67)
1.81 (0.00-4.63)
13.62(9.99-18.11)
24.18(18.11-27.41)
13.31 (10.48-16.67)
1.07 (0.33-8.67)
22.10(13.43-31.80)
28.74 (24.23-33.07)
19.00(14.99-23.69)
1.72 (0.00-5.00)
18.30(14.99-21.14)
26.11 (21.95-28.85)
15.89(14.39-17.76)
15.88 (7.89-18.38)
36.68(32.53-40.31)
46.91 (37.94-52.92)
35.63 (28.92-40.07)
18.47(14.39-25.91)
63.26(50.62-70.12)
61.15(52.57-71.59)
51.43 (47.32-54.82)
17.46(12.78-18.68)
47.31 (36.22-59.65)
52.92 (45.73-61.51)
40.03(37.94-44.75)
46.82 (36.72-54.55)
94.93 (75.74-114.34)
108.90(92.06-123.72)
94.61 (77.70-109.09)
57.07 (47.32-65.37)
126.61 (108.54-162.80)
125.90(112.28-147.62)
112.11 (108.54-127.19)
50.14(43.58-55.00)
109.66(94.43-127.19)
113.10(107.18-133.74)
107.63(98.25-109.09)
Percentile intervals (B.I.) 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
Sample Size Mean (90% C.I.) 90th % (90% B.I.) 95th % (90% B.I.
99th % (90% B.I.)
Females
14 or under
15-44
45 or older
All ages
Males
14 or under
15-44
45 or older
All ages
Both Sexes
14 or under
15-44
45 or older
All ages
1431 8.61(6.67-10.56) 31.23(26.85-37.29)
2891 12.84(11.51-14.18) 46.66(38.35-54.30)
2340 16.26(14.68-17.84) 56.01(50.00-61.97)
6662 13.05(11.97-14.12) 46.70(44.49-49.72)
1546 9.40(7.36-11.45) 31.32(25.20-44.12)
2151 17.11 (15.31-18.90) 66.06(62.21-73.20)
1553 17.22(15.19-19.25) 62.64(59.39-68.44)
5250 15.27(13.86-16.68) 61.12(56.59-63.09)
2977 9.02 (7.28-10.75) 31.52(30.19-35.75)
5042 14.88(13.57-16.19) 55.99(53.04-61.33)
3893 16.69(15.34-18.04) 59.12(52.84-64.53)
11912 14.11(13.07-15.14) 52.10(47.83-55.93)
49.75 (41.46-57.49)
72.16(63.12-77.18)
84.71 (75.05-93.29)
72.22 (65.55-75.47)
65.37(54.60-73.39)
93.32 (81.26-106.67)
84.96 (79.93-99.44)
81.89 (77.91-87.16)
56.35(50.22-62.25)
80.70 (75.19-87.16)
84.92 (76.67-93.32)
76.51(74.58-80.89)
104.26(83.35-140.07)
133.69(121.33-142.82)
131.43(112.07-156.01)
130.73(121.33-137.18)
118.42(82.34-176.52)
155.16(136.77-181.18)
146.78(142.58-185.44)
147.09(134.55-174.31)
117.75(91.82-140.07)
138.23(128.40-157.23)
142.92(134.55-155.13)
138.22(132.98-155.13)
Percentile intervals (B.I.) 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)
Age
Sample Size Mean (90% C.I.)
90th % (90% B.I.
95th % (90% B.I.)
99th % (90% B.I.
Females
14 or under
15-44
45 or older
All ages
Males
14 or under
15-44
45 or older
All ages
Both Sexes
14 or under
15-44
45 or older
All ages
1431 10.60(8.40-12.81)
2891 18.35(16.67-20.02)
2340 22.91 (20.78-25.04)
6662 18.17(16.82-19.53)
1546 12.09(9.70-14.49)
2151 24.98(22.79-27.17)
1553 26.09(23.52-28.67)
5250 22.18(20.52-23.83)
2977 11.36(9.49-13.24)
5042 21.51 (19.97-23.06)
3893 24.35(22.46-26.24)
11912 20.08(18.82-21.35)
41.10(35.80-47.57)
62.21 (54.47-73.56)
74.56 (65.37-79.67)
61.08(56.94-63.12)
45.59(34.69-53.11)
87.15(80.89-94.63)
81.76 (76.67-88.03)
76.13(74.22-79.92)
43.00(34.69-47.32)
75.15(73.56-79.71)
77.57 (72.07-84.02)
70.11 (65.37-74.20)
56.16(49.78-65.55)
93.13 (82.29-108.03)
107.66(97.64-111.71)
92.03(86.94-96.11)
68.18(64.28-79.90)
122.29(111.05-124.83)
112.33(109.65-130.36)
110.88(108.54-118.56)
65.34(56.28-68.51)
109.57(106.72-117.47)
110.13(100.42-119.87)
102.01 (99.26-106.67)
130.78(83.35-160.66)
155.75(137.18-174.31)
159.97(157.17-173.74)
157.08(147.34-168.83)
127.20(87.29-176.52)
197.15(179.86-198.87)
211.20(190.74-223.72)
180.90(174.39-198.87)
130.41 (107.12-160.66)
175.73(162.80-198.63)
180.74(164.76-210.75)
173.18(162.80-176.52)
Percentile intervals (B.I.) 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 Aged 18 Years and Older by Habitat - Uncooked Fish Weight
Habitat
90% Interval
Statistic
Estimate
Lower Bound
Upper Bound
Mean
7.09
6.22
7.96
50th %
0.00
0.00
0.00
90th %
21.72
18.52
25.82
95th %
49.89
47.32
54.67
99th %
111.13
107.18
116.38
Mean
16.01
14.89
17.12
50th %
0.00
0.00
0.00
90th %
59.35
56.59
61.49
95th %
82.95
80.37
88.36
99th %
142.78
131.02
156.89
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
Fresh/Estuarine
Marine
All Fish
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)
Age
Sample
Size
Mean (90% C.I.)
90th % (90% B.I.)
95th % (90% B.I.:
99th % (90% B.I.:
Females
14 or under
15-44
45 or older
All ages
Males
14 or under
15-44
45 or older
All ages
Both Sexes
14 or under
15-44
45 or older
All ages
1431 84.78(58.06-111.50)
2891 85.15(70.68-99.62)
2340 98.97(79.89-118.04)
6662 89.54(76.51-102.58)
1546 91.62(55.18-128.05)
2151 96.91 (78.91-114.90)
1553 107.87(88.47-127.28)
5250 98.86(87.19-110.52)
2977 88.26(66.69-109.83)
5042 90.77(78.37-103.16)
3893 103.00(87.86-118.15)
11912 93.99(83.41-104.57)
70.75 (0.00-143.13)
202.83 (153.48-259.97)
333.38 (269.96-379.98)
225.51 (176.38-280.11)
38.98 (12.26-281.50)
281.17(165.37-387.46)
361.99 (304.96-455.29)
292.58 (217.42-342.11)
66.00 (0.00-143.13)
250.26 (194.04-289.19)
345.69 (291.80-423.39)
251.82 (222.54-282.58)
599.06 (266.71-722.58)
584.79 (538.05-631.86)
733.74 (606.36-820.68)
625.30 (552.99-713.85)
868.97 (485.33-1063.50)
740.91 (546.79-850.52)
702.35 (628.25-810.62)
755.53 (677.47-790.85)
717.37 (485.60-880.64)
631.31 (538.05-773.91)
719.81 (637.94-790.85)
677.66 (631.86-729.11)
1713.06 (1511.78-
1411.42 (1236.72-
1561.40 (1331.46-
1558.08 (1394.99-
1642.60 (1599.78-
1589.97 (1353.43-
1612.49(1344.07-
1596.61 (1538.89-
1688.55 (1511.78-
1529.94(1352.50-
1590.13(1373.97-
1593.28 (1511.78-
2313.50)
1659.15)
¦1667.88)
1659.15)
1693.88)
1992.23)
¦1848.39)
¦1711.41)
¦1824.44)
¦1659.15)
1668.93)
¦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
Size
Mean (90% C.I.)
90th % (90% B.I.)
95th % (90% B.I.)
99th % (90% B.I.)
Females
14 or under
15-44
45 or older
All ages
Males
14 or under
15-44
45 or older
All ages
Both Sexes
14 or under
15-44
45 or older
All ages
1431
2891
2340
6662
1546
2151
1553
5250
2977
5042
3893
11912
333.99 (267.25-400.72)
206.03 (183.95-228.11)
246.73 (221.45-272.00)
246.47 (223.28-269.66)
1132.99 (864.83-1407.24)
762.54 (617.86-857.55)
829.52 (777.87-944.26)
847.60 (811.19-893.29)
296.99 (241.85-352.13) 1089.46 (1003.46-1256.97)
212.88 (190.31 -235.44) 800.79 (741.29-859.61)
792.86 (747.56-890.31)
859.01 (798.27-907.76)
212.15(187.25-237.04)
233.07 (209.65-256.49)
315.12(260.95-369.29)
209.30 (190.68-227.92)
231.06 (212.18-249.95)
240.07 (220.14-260.01)
1123.28 (993.12-1371.24)
780.16(722.86-843.41)
813.12(747.56-907.76)
855.63 (809.67-909.76)
1959.91 (1780.61-2347.02)
1137.58 (1036.38-1211.86)
1236.00 (1174.14-1413.34)
1305.49(1215.53-1385.66)
1907.65 (1685.30-2186.58)
1191.75 (1096.61-1245.94)
1100.20 (1039.02-1210.66)
1255.35 (1204.46-1382.05)
1909.37 (1785.09-2062.64)
1174.69 (1104.42-1215.53)
1193.22 (1076.85-1333.72)
1271.54(1227.16-1371.24)
3776.60 (3173.86-5736.90)
2174.21 (2014.41-2393.16)
2161.65 (1952.51-2303.80)
2615.85 (2365.65-2857.62)
3723.81 (3274.93-4574.13)
1890.42(1685.30-1969.63)
1842.38 (1749.67-2219.32)
2520.94 (2263.58-2733.15)
3820.21 (3370.59-4574.13)
2019.59 (1918.45-2237.22)
2029.16(1863.17-2219.32)
2575.29 (2393.16-2708.59)
Percentile intervals
Source: U.S. EPA.
(B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications.
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)
Age
Sample
Size
Mean (90% C.I.;
90th % (90% B.I.;
95th % (90% B.I.:
99th % (90% B.I.:
Females
14 or under
15-44
45 or older
All ages
Males
14 or under
15-44
45 or older
All ages
Both Sexes
14 or under
15-44
45 or older
All ages
1431 418.76 (339.58-497.95)
2891 291.18(263.86-318.50)
2340 345.69(312.49-378.90)
6662 336.01 (307.83-364.20)
1546 388.61 (320.66-456.56)
2151 309.78 (281.55-338.02)
1553 320.02 (287.79-352.25)
5250 331.93 (306.46-357.40)
2977 403.38(343.65-463.12)
5042 300.06 (277.94-322.19)
3893 334.07 (307.87-360.26)
11912 334.06 (311.25-356.88)
1389.10(1150.77-1785.09)
993.92 (854.63-1127.32)
1122.26 (1050.15-1230.68)
1120.91 (1054.05-1172.38)
1476.31 (1371.24-1632.55)
1096.57 (1044.57-1194.06)
1013.05 (955.37-1096.43)
1126.66 (1081.06-1225.66)
1442.72 (1279.82-1672.75)
1040.98 (1003.55-1097.08)
1069.14(978.95-1140.98)
1123.14(1090.76-1178.95)
2341.90 (2062.64-2860.52)
1436.00 (1234.66-1631.25)
1669.72 (1556.83-1784.37)
1720.84(1642.63-1855.69)
2038.58 (1909.00-2631.42)
1566.39 (1410.20-1609.35)
1459.73 (1340.97-1601.79)
1621.80 (1599.78-1696.20)
2191.90 (2021.16-2536.75)
1514.82 (1421.34-1572.40)
1579.43(1373.97-1696.20)
1684.23 (1620.48-1718.51)
4985.96 (3971.54-
2726.50 (2406.11-
2684.71 (2303.80-
3093.76 (2973.66-
4294.12(3556.31-
2275.15(2047.18-
2392.05 (2233.16-
3031.31 (2806.51-
4425.27 (4000.27-
2481.23 (2383.54-
2653.45 (2292.45-
3092.77 (2973.66-
5736.90)
¦3044.81)
3064.38)
3265.54)
¦4574.13)
¦2465.77)
¦2806.51)
¦3274.93)
4669.59)
¦2773.15)
¦2806.51)
3250.20)
Percentile intervals (B.I.) were estimated using the percentile bootstrap method with 1,000 bootstrap replications.
Source: U.S. EPA. 1996a.
-------
Table 10-36
for the U.S.
Per Capita Distribution of Fish (Finfish and Shellfish) Intake (mg/kg-day)
Population Aged 18 Years and Older by Habitat - Uncooked Fish Weight
Habitat
Statistic
90% Interval
Estimate
Lower Bound
Upper Bound
Fresh/Estuarine
Mean
95.99
84.30
107.69
50th %
0.00
0.00
0.00
90th %
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
90th %
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.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 10-38. 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.)
90th % (90% B.I.)
95th % (90% B.I.)
99th % (90% B.I.)
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 ages
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.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 10-39. 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 ages
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 by Habitat - Uncooked Fish Weight
Habitat
Statistic
90% Interval
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 (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 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 of Fish (Finfish and Shellfish) Intake (mg/kg-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
2070.41
15-44
445
1229.97
45 or older
453
1171.17
All ages
1036
1317.18(1150.10-'
Males
14 or under
157
2229.31
15-44
356
1294.27
45 or older
343
1235.55
All ages
856
1411.35 (1278.61-'
Both Sexes
14 or under
295
2153.11
15-44
801
1261.99
45 or older
796
1201.57
All ages
1892
1363.44(1242.24-'
4450.54 6915.31
3045.41 4191.25
2886.48 3519.87
1317.18(1150.10-1484.26) 3250.31 (2988.81-3491.38) 4240.89(3710.16-5025.02)
4638.34 5071.41
3318.89 4275.83
2898.00 4097.24
1411.35 (1278.61 -1544.08) 3579.06 (3225.84-4060.30) 4615.66 (4121.91 -5081.65)
4634.82 5756.93
3276.06 4246.63
2892.52 3981.84
1363.44 (1242.24-1484.65) 3325.14 (3232.58-3676.99) 4408.18 (4085.55-4781.34)
13269.61
7711.43
5577.34
8912.52 (6385.55-11533.98)
9622.15
5974.96
7217.68
6594.61 (5980.19-7944.55)
12388.27
6625.15
6378.11
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
All ages
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.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 10-43. 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
Size
Mean (90% C.I.)
90th % (90% B.I.)
95th % (90% B.I.)
99th % (90% B.I.)
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 ages
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 Aged 18 Years and Older by Habitat - Uncooked Fish Weight
Habitat
Statistic
90% Interval
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 3-year combined survey weights. The population for this survey consisted of individuals in the 48
conterminous states.
Source: U.S. EPA. 1996a.
-------
Table 10-45.
Distribution of Quantity of Fish Consumed (in grams) Per Eating Occasion, by Age and Sex
Percentiles
Aqe (vears)-Sex Group
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
15-18 Male
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 onlyb
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
a Based on USDA Nationwide Food Consumption Survey 1987-8
8 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 Responded Yes, No, or Don't Know to Eatinq Seafood in 1 Month (including shellfish, eels, or squid)
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
Age (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
*
*
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: Tsanq and Klepeis,
1996.
-------
Table 10-48.
Number of Respondents Reportina Consumption of
a Specified 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
*
*
*
*
*
Age (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: Tsanq and Klepeis
. 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
*
*
Age (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
20
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
*
741
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: Tsanq and Klepeis, 1996.
-------
Table 10-50. Estimated Number of Participants in
Marine Recreational Fishing by State and Subreg
on
Subregion
State
Coastal
Non Coastal
Out of State a
Total Participants
Participants
Participants
a
Pacific
So. California
902
8
159
910
N. California
534
99
63
633
Oregon
265
_19
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
M
157
97
TOTAL
787
88
Mid-Atlantic
Delaware
90
*
159
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
131
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
M
GRAND TOTAL
8,053
760
a Not additive across states. One person can be counted as "OUT OF STATE" for more than one state.
An asterisk (*) denotes no non-coastal counties in state.
Source: NMFS
1993.
-------
Table 10-51
Estimated Weight of Fish Caught (Catch Type A and B1) by
Marine Recreational Fishermen, by Wave and Subreg
on
Atlantic and Gulf
Pacific
Reaion
Weinht H000 ktri
Reaion
Weinht HOOO ktri
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
144
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
581
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
39
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
724
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
Region8
Mean
95th Percentile
(Coastal)'
(Coastal & Non-Coastal)c
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
3 N. Atlantic - ME, NH, MA, Rl, 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 Mean intake rate among entire population of region.
Source: NMFS, 1993.
-------
Table 10-53.
Estimated Weight of Fish Caught (Catch Type A and B1)a by Marine Recreational Fishermen
by Species
Group and Subregion, Atlantic and Gulf
North Atlantic
Mid Atlantic
South Atlantic
Gulf
All Regions
M .000 knl
M .000 knl
M .000 knl
M .000 knl
M .000 knl
Cartilaginous fishes
66
1,673
162
318
2,219
Eels
14
9
*b
0C
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
T riggerfishes/Filefishes
0
48
109
544
701
Puffers
*
16
56
4
76
Other fishes
105
72
709
915
1,801
a For Catch Type A and B1, the fish were not thrown back.
b An asterisk (*) denotes data not reported.
0 Zero (0) = < 1000 kg.
Source: NMFS. 1993.
-------
Table 10-54. Estimated Weight of Fish Caught (Catch Type A and B1)a by Marine Recreational
Fishermen by Species Group and Subregion, Pacific
SDecies GrouD
Southern California
(1.000 kal
Northern California
(1.000 kal
Oregon
(1.000 kal
Total
Cartilaginous fish
35
162
1
198
Sturgeons
0b
89
13
102
Herrings
10
15
40
65
Anchovies
*c
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
Other fishes
89
36
307
432
a For Catch Type A and B1, the fish were not thrown back.
b Zero (0) = <1000 kg.
c An asterisk (*) denotes data not reported.
Source: NMFS. 1993.
-------
Table 10-55. Median Intake Rates Based on Demographic Data of Sport Fishermen and Their Family/Living Group
Percent of total interviewed
Median intake rates
(g/person-day)
Ethnic Group
Caucasian
42
46.0
Black
24
24.2
Mexican-American
16
33.0
Oriental/Samoan
13
70.6
Other
5
a
Aoe (years)
< 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 etal. (19811.
-------
Table 10-57. Catch Information for Primary Fish Species Kept by Sport Fishermen (n = 1059)
Species
Average 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
Opaleye
307
6
Black Perch
196
5
Kelp Bass
440
5
California Halibut
1752
4
Shellfish"
421
3
a Crab, mussels, lobster, abalone.
Source: Modified from Puffer et al.. 1981.
-------
Table 10-58.
Percent of Fishing Frequency During the Summer and Fall Seasons in Commencement Bay, Washington
Fishing Frequency
Frequency Percent
in the Summer®
Frequency Percent Frequency Percent
in the Fallb in the Fallc
Daily
Weekly
Monthly
Bimonthly
Biyearly
Yearly
10.4
50.3
20.1
6.7
4.4
8.1
8.3 5.8
52.3 51.0
15.9 21.1
3.8 4.2
6.1 6.3
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 etal. (1981)
37
225
Pierce etal. (1981)
19
155
Average
28
190
Total Angler Population
Puffer etal. (1981)
2.9"
35b
Pierce etal. (1981)
10
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
Everglades, Florida
Variables
Mean ± Std. Devb
fNa=3301
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 Wth Recreational Fish Consumption
GrouD
All Fish
meals/week
Recreational
Fish meals/week
n
Total Fish
arams/dav
Recreational
Fish
arams/dav
Total Fish
grams/
ka/dav
Recreational
Fish grams/
ka/dav
All household
members
0.686
0.332
2196
21.9
11.0
0.356
0.178
Respondents (i.e.,
licensed anglers)
0.873
0.398
748
29.4
14.0
0.364
0.168
Aae GrouDS Cvearsl
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
1 to 20
0.407
0.229
349
12.3
7.27
0.219
0.123
21 to 40
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
Freauencv Cateaorv
7-dav Recall Data
for Data Analvsis (times/week)
Almost daily
no data
4 [if 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 (1.3 times/monthl
0.2 CO.9 times/monthl
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 usina data from West et al
CD
00
CD
-------
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
a
Intake Rates (grams/day)
Percentile Rankings
All Waters"
Rivers and Streams
All Anglers'
Consuming Anglersd
River Anglers8
Consuming Anglersd
(N = 1.3691
(N = 1.0531
(N = 7411
•Sf
-------
Table 10-65. Analysis of Fish Consumption by Ethnic Groups for "All Waters" (g/day)a
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)0,11
2.3
2.4
1.8
2.3
1.9
1.3
66th percentile'11
4.1
4.4
2.6
4.7
3.8
2.6
75th percentile'11
6.2
6.0
5.0
6.2
5.7
4.9
Arithmetic Meanc
7.4
5.2
4.5
10
6.0
5.3
Percentile at the Meand
80
70
74
83
76
78
90th percentile0'"
15
12
12
16
13
9.4
95th percentile'11
27
20
21
51
24
25
Percentile at 6.5 g/dayd e
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.
8 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
of Freshwater 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
Togue (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
Hornpout (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
20.046
1.168
Source: Chemrisk. 1991.
-------
Table 10-67.
Mean Sport-Fish Consumption by Demographic Variables, Michigan Sport
Anglers Fish Consumption Study, 1991
-1992
N
Mean Ca/davl
95% C.I.
Income®
<$15,000
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
Aae (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/Ethnicitvb
Minority
160
23.2
13.4-33.1
White
2,289
16.3
14.9-17.6
® P < .01, F test
b P < .05, F test
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 Anglers
Percentile of Lake Ontario Analers Fish from All Sources (a/dav)
SDort-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 Sociodemographic Characteristics
Mean Consumpti
on
Demographic Group
Fish from all Sources
Sport-Caught 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
Aae (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.
-------
Table 10-70. Percentile and Mean Intake Rates for Wisconsin Sport Anglers
Percentile Annual Number of Sport Cauaht Meals
Intake Rate of Soort-Cauoht Meals (g/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.
grams per fish meal: this value is dervied from Pao et al.
EPA calculated intake rates using a value of 150
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 Background
Caucasian American
67 %
African American
21 %
Hispanic American
10 %
Asian American
1 %
Native American
1 %
a A total of 336 shore-based anglers were interviewed
Source: Hudson River Sloop Clearwater. Inc.. 1993
-------
Table 10-72
Number of Grams Per Day of Fish Consumed by All Adult Respondents
(Co
nsumers 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 Throughout the Year by Sex, Age, 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
Aae (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
Unweighted 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
Unweighted SE = 1.94
Source: CRITFC. 1994.
-------
Table 10-75. Sociodemog
raphic Factors and Recent Fish Consumption
Peak Consumption3
Recent Consumptionb
Averaae0 >
3d (%)
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
0.5a
0.5
0.7a
Female (n-175)
1.5
15
3.4
0.2
0.1
0.3
Age (y)
<35 (n-150)
1.8
23
CO
LO
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
0.4
0.2
0.4
Unemployed
Yes (n-78)
1.9
27
4.8
0.6
0.6
1.1
No fn-2451
1.6
18
4.0
0.3
0.2
0.3
a Highest number offish meals consumed/week.
Number of meals of each species in the previous 2 months.
c Average peak fish consumption.
Percentage of population reporting peak fish consumption of
>3 fish meals/week.
Source: Peterson et al.
1994.
-------
Table 10-76. Number of Local Fish Meals Consumed Per Year by Time Period for All Respondents
Time Period
NumDer ot
Local Fish
During Pregnancy
<
1 Yr. Before Pregnancy3
>Yr. Before Pregnancy
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 by Time
Period for All Respondents and Consumers Only
All Respondents
(N=97 Mohawks and 154 Controls)
Consumers Only
(N=82 Mohawks and 72 Controls)
During <1 Yr. Before
Pregnancy Pregnancy
>1 Yr. Before
Pregnancy
During <1 Yr. Before >1 Yr. Before
Pregnancy Pregnancy Pregnancy
Mohaw
k
Control
3.9(1.2) 9.2(2.3)
7.3(2.1) 10.7(2.6)
23.4 (4.3)a
10.9 (2.7)
4.6(1.3) 10.9(2.7) 27.6(4.9)
15.5 (4.2)a 23.0 (5.1 )b 23.0(5.5)
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
Purina Pregnancy <1 Year Before Pregnancy >1 Year Before Pregnancy
Background 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
22.1a
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
CO
CD
12.1
4.7C
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.
c 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: Fitzgerald et al.. 1995.
-------
Table 10-79.
Percentage of Individuals Using Various Cooking Methods at Specified Frequencies
Studv
Use
Frequency
Bake
Pan Fry
Deep
Frv
Broil or
Grill
Poach
Boil
Smoke
Raw
Other
Connelly et al.,
1992
Always
Ever
24(a)
75(a)
51
88
13
59
24(a)
75(a)
Connelly et al.,
1996
Always
Ever
13
84
4
72
4
42
CRITFC, 1994
At least
monthly
79
51
14
27
11
46
31
1
34(b)
29(c)
49(d)
Ever
98
80
25
39
17
73
66
3
67(b)
71(c)
75(d)
Fitzgerald et al.,
1995
Not
Specified
94(e)(f)
71(e)(g)
Puffer et al.,
1981
As Primary
Method
16.3
52.5
12
0.25
19(h)
a 24 and 75 listed as bake, BBQ, or poach
b Dried
c Roasted
d Canned
8 Not specified whether deep or pan fried
' Mohawk women
9 Control population
h boil, stew, soud, or steam
-------
Table 10-80.
Percent Moisture and Fat Content for Selected Species®
Moisture
Content
Total Fat Content
SDecies
<%)
<%)"
Comments
FINFISH
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 heat
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
SDecies
(%)
(%)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 and fried
Snapper, mixed species
76.87
0.995
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
Sword fish
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 SDecies
74.52
NA
Raw
-------
Table 10-80. Percent Moisture and Fat Content for Selected Species® (continued)
Moisture
Total Fat
Content
Content
Species
(%)
(%)b
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
a 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. 6
-------
Table 10-81. Recommendations - General Population
Mean Intake
(g/day)
95th Percentile of Long-term
Intake Distribution (g/day)
Study (Reference)
53 (Value of 42 from Javitz was adjusted
upward by 25 percent to account for
recent increase in fish consumption)
TRI (Javitz, 1980; Ruffle etal., 1994)
20.1 (Total Fish)
14.1 (Marine Fish)
6.0 (Freshwater/Estuarine Fish)
U.S. EPA Analysis ofCSFII, 1989-91
-------
Table 10-82. Recommendations - General Population -
Fish Serving Size
Mean Intake (grams)
95th Percentile (grams) Study (Reference)
129
326 1989-1991 CSFII (U.S. EPA. 1996)
-------
Table 10-83. Recommendations - Recreational Marine Anglers
Mean Intake (g/day)
95th Percentile (g/day) Study Location
Study
5.6
7.2
2.0
18.0 Atlantic
26.0 Gulf
6.8 Pacific
NMFS, 1993
-------
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
—
Michigan
West et al, 1993
-------
Table 10-85.
Recommendations - Native American Subsistence Populations
Per-Capita (or Mean) Intake
(g/day)
Upper Percentile
(g/day) Study Population
Reference
59
170 (95th) 4 Columbia River Tribes
CRITFC, 1994
16
94 Alaska Communities
(Lowest of 94)
Wolfe and Walker, 1989
81
94 Alaska Communities
(Median of 94)
Wolfe and Walker, 1989
770
94 Alaska Communities
(Hiqhest of 94)
Wolfe and Walker, 1989
-------
Table 10-86. Summary of Fish Intake Studies
Source of Data
(Reference)
Population
Surveyed
Survey Time Period/Type
Analyses Performed (References)
Limitations/Advantages
General Population
Kev Studies
Javitz, 1980 - TRI
Survey
25,162 individuals -
general population;
the TRI Survey
sample
Sept. 1973-Aug. 1974 (1 year
survey). Completed diary over 1
month period on date of meal
consumption, species of fish,
packaging type, amount of fish
prepared, number of servings
consumed, etc.
Mean and distribution of fish
consumption rates grouped by race,
age, gender, census region, fish
species, community type, and religion.
Lognormal distribution fit to fish intake
distribution by age and region by Ruffle
et al. (1994).
High response rate (80%); population
was large and geographically and
seasonally representative;
consumption rates based on one
month of diary data; survey data is over
20 years out of date
U.S. EPA, 1996a
11,912 individuals -
general population
Participants provided 3
consecutive days of dietary data.
Three survey years (1989-1991)
combined into one data set.
Analysis of CSFII 1989-91. Fish
grouped by habitat (freshwater vs.
marine) and type (finfish vs. shellfish).
Per capita fish intake rates calculated
using cooked and uncooked equivalent
weight and reported in g/day and g/kg-
day; also intake distribution per day
eating fish.
Large, geographically representative
study; relatively recent. Based on
short-term (3 day) data so long-term
percentiles of fish intake distribution
could not be estimated.
Relevant Studies
AIHC, 1994
--
--
Distributions using @Risk simulation
software.
Limited reviews of supporting studies;
good alternative source of information.
Pao et al., 1982
37,874 individuals -
general population
Participants provided 3
consecutive days of dietary data.
Survey conducted between April
1977 and March 1978.
Mean and distribution of average daily
fish intake and average fish intake per
eating occasion; by age-sex groups and
overall.
Population was large and
geographically representative; data
were based on short-term dietary
recall; data are almost 20 years out of
date.
Tsang and Klepeis,
1996
9,386 individuals -
general population
Participants provided 24-hour diary
data. Follow-up questionnaires,
survey conducted between
October 1992 and September
1994.
Frequency of eating fish and number of
servings per month provided.
Population large and geographically
and seasonally balanced; data based
on recall; intake data not provided.
USDA, 1992
10,000 individuals-
general population
Participants provided 3
consecutive days of dietary data.
Survey conducted between April
1987 and March 1988.
Per capita fish intake rates and percent
of population consuming fish in one
day; by age and sex.
Population was large and
geographically and seasonally
balanced; data based on short-term
dietary recall.
-------
Table 10-86. Summary of Fish Intake Studies (continued)
Source of Data
(Reference)
Population Surveyed
Survey Time Period/Type
Analyses Performed (References)
Limitations/Advantages
Recreational-Marine Fish
Kev Studv
NMFS 1986a, b, c; 1993
Atlantic and Gulf Coasts -
41,000 field interviews and
58,000 telephone
interviews; Pacific Coast -
38,000 field interviews and
73,000 telephone
interviews.
Telephone interviews with residents
of coastal counties; information on
fishing frequency and mode of fishing
trips. Field interviews with marine
anglers; information on area and
mode fished, fishing frequency,
species caught, weight of fish, and
whether fish were intended to be
consumed.
Intake rates were not calculated;
total catch size grouped by marine
species, seasons, and number of
fishermen for each coastal region
were presented.
Population was large geographically
and seasonally balanced; fish caught
were weighed in the field. No
information on number of potential
consumers of catch.
Relevant Studies
Pierce et al., 1981
-500 anglers in
Commencement Bay,
Washington
July-November 1980; creel survey
interviews conducted consisting of 5
summer days and 4 fall days.
Distribution of fishing frequency;
total weight of catch grouped by
species. Re-analysis by Price et
al. (1994) using inverse fishing
frequency as sample weights.
Local survey. Original analysis by
Pierce et al. (1981) did not calculate
intake rates; analysis over-estimated
fishing frequency distribution by
oversampling frequent anglers. Re-
analysis by Price et. al. (1994)
involved several assumptions; thus
results are questionable.
Puffer et al., 1981
1,067 anglers in the Los
Angeles, California area.
Creel survey conducted for the full
1980 calendar year.
Distribution of sport fish intake
rates. Median rates by age,
ethnicity and fish species. Re-
analysis by Price et al. (1994)
using inverse fishing frequency as
sample weights.
Local survey. Original (unweighted)
analysis over-estimated fish intake by
oversampling frequent anglers. Re-
analysis by Price et al. (1994) involves
several assumptions; thus results are
questionable.
U.S. DHHS, 1995
330 everglade residents/
subsistence fishermen or
both
1992-1993; questionnaire with
demographic information and fishing
and eating habits.
Provides data for fishing frequency
by sex, age, and ethnicity.
Intake rates were not reported, study
not representative of the U.S.
population; one of few studies that
tarnet subsistence fishermen.
-------
Table 10-86. Summary of Fish Intake Studies (continued)
Source of Data
(Reference)
Population Surveved
Survev Time Period/Tvne
Analvses Performed (References)
Limitations/Advantanes
Recreational Fresh Water Fish
Kev Studies
Chemrisk, 1991; Ebert
et al., 1993
1,612 licensed Maine
anglers
1989-1990 ice fishing season and
1990 open water season; mailed
survey; one year recall of frequency
of fishing trips, number and length
of fish species caught.
Mean and distribution of fish
consumption rates by ethnic groups
and overall. Mean and distribution of
fish consumption rates for fish from
rivers and streams. EPA analysis of
fish intake for household members.
Data based on one year recall; high
response rate; area-specific
consumption patterns.
Connelly et al., 1996
825 anglers with NY State
fishing licenses intending to
fish Lake Ontario.
Survey consisted of self-recording
information in a diary for 1992
fishing trips and fish consumption.
Distribution of intake rates of sport
caught fish.
Meal size estimated by comparison
with pictures of 8 oz. fish meals.
West et al., 1993
2,681 persons with
Michigan fishing licenses
January 1991 through January 1992;
mailed survey; 7-day recall;
demographics information
requested, and quantity of fish
eaten, if any, at each meal based on
a photograph of 1/2 lb of fish (more
about same, or less).
Mean consumption rate for sport
and total fish by demographic
category (West et al., 1993) and
50th, 90th, and 95th percentile (U.S.
EPA, 1995).
Relatively low response made and
only three categories were used to
assign fish portion size. Relatively
large-scale study and reliance on
short-term recall.
West et al., 1989
1,171 Michigan residents
with fishing licenses
January-May 1988; anglers
completed questionnaires based on
7-day and 1-year recall.
Mean intake rates of self-caught fish
based on 7-day recall period
and mean and percentiles of self-
caught fish intake based on one year
recall.
Weight of fish consumed was
estimated using a picture of an 8 oz.
fish meal; smaller meals were
judged to be 5 oz., larger ones 10
oz.
Relevant Studies
Connelly et al., 1992
1,030 anglers licensed in
New York
Survey mailed out in Jan. 1992; one
year recall of the period Oct. 1990-
Sept. 1991
Knowledge and effects of fish health
advisories. Mean number of sport-
caught fish meals.
Response rate of 52.8%; only
number of fish mealsreported.
Fiore et al., 1989
801 individuals with
Wisconsin fish or sporting
licenses
1985 summer; mailed survey; one
year recall of sport fish
consumption.
Mean number of sport caught fish
meals of Wisconsin anglers.
Constant meal size assumed.
Hudson River Sloop
Clearwater, Inc.
(1993)
336 shore-based anglers
Survey conducted June-November
1991; April-July 1992. Onsite
interview with annlers
Knowledge and adherance to health
advsisories
Data collected from personal
interviews; intake data not provided;
fish meal data nrovided.
-------
Table 10-86. Summary of Fish Intake Studies (continued)
Source of Data
(Reference)
Population Surveved
Survev Time Period/Tvne
Analvses Performed (References)
Limitations/Advantanes
Native American
Kev Studies
CRITFC, 1994
Four tribes in Washington
state; total of 513 adults
and 204 children under five
Fall and Winter of 1991-1992; stratified
random sampling approach; in-person
interviews; information requested
included 24-hour dietary recall,
seasonal and annual number of fish
meals, average weight of fish meals
and species consumed.
Mean and distribution of fish intake
rates for adults and for children.
Mean intake rates by age and
gender. Frequency of cooking and
preparation methods.
Survey was done at only one time of
the year and involved one year recall;
fish intake rates were based on all fish
sources but great majority was locally
caught; study provides consumption
and habits for subsistence
subpopulation group.
Fitzgerald et al.
1995
97 Mohawk women in New
York; 154 Caucasian
women; nursing mothers
1988-1992, up to 3-year recall
Mean number of sport-caught fish
meals per year.
Survey for nursing mothers only, recall
for up to 3 years; small sample size;
may be representative of Mohawk
women; measured in fish meals.
Petersen et al.,
1994
327 residents of Chippewa
reservation, Wisconsin
Self-administered questionaire
completed in May, 1990.
Mean number of fish meals per
year.
Did not distinguish between commercial
and sport-caught meals.
Wolfe and Walker,
1987
Ninety-eight communities
in Alaska surveyed by
various researchers
Surveys conducted between 1980 and
1985; data based on 1-year recall
period. Annual per capita harvest of
fish, land mammals, marine mammals
and other resources estimated for
each community.
Distribution among communities of
annual per-capita harvests for
each resource category.
Data based on 1-year recall; data
provided are harvest data that must be
converted to individual intake rates;
surveyed communities are only a
sample of all Alaska communities.
s NFMS - National Marine Fisheries Services.
-------
Table 10-87. Confidence in Fish Intake Recommendations for General Population
Considerations
Rationale
Rating
Study Elements
Level of peer review
Peer reviewed by USDA and EPA.
High
Accessibility
CSFII data are publicly available. Javitz is a
contractor report to EPA.
High (CSFII)
Medium (Javitz)
Reproducibility
Enough information is available to reproduce
results.
High
Focus on factor of interest
The studies focused on fish ingestion.
High
Data pertinent to U.S.
The studies were conducted for U.S.
population.
High
Primary data
The studies are primary studies.
High
Currency
Studies were conducted from 1973-1974 to
1989-1991.
Medium (mean)
Low (Long-Term Distribution)
Adequacy of data collection period
Long-term distribution are based on one month
data collection period.
High (Mean)
Medium (Long-term distribution)
Validity of approach
Data are collected using diaries and one-day
recall. However, data adjusted to account for
changes in eating pattern.
Medium
Study size
The Range of samples was 10,000 -37,000.
High
Representativeness of the
population
The data are representative of overall U.S.
population.
High
Characterization of variability
Long-term distribution (generated from 1973-
1974 data) was shifted upward based on recent
increase in mean consumption.
Medium
Lack of bias in study design (high
rating is desirable)
Response rates were fairly high; there was no
obvious source of bias.
High
Measurement error
Estimates of intake amounts were imprecise.
Medium
Other Elements
Number of studies
There was 1 study for the mean, the results of
2 studies were utilized for long-term
distribution.
Low
Agreement between researchers
Medium
Overall Rating
Medium (Mean)
Low (Long-term distribution)
-------
Table 10-88. Confidence in Fish Intake Recommendations for Recreational Marine Anglers
Considerations
Rationale
Rating
Study Elements
Level of peer review
Data were reviewed by NMFS and EPA.
High
Accessibility
The analysis of the NMFS data is presented in the
Handbook and NMFS data can be found in NMFS
publications.
High
Reproducibility
Enough information is available to reproduce results.
High
Focus on factor of interest
Studies focused on fish catch rather than fish consumption
perse.
Medium
Data pertinent to U.S.
The studies were conducted in the U.S.
High
Primary data
Data are from primary studies.
High
Currency
The data were based on 1993 studies.
High
Adequacy of data collection period
Data were collected once for each angler. The yearly catch
of anglers were estimated from catch on intercepted trip and
reported fishing frequency.
Medium
Validity of approach
The creel survey provided data on fishing frequency and fish
weight; telephone survey data provided number of anglers.
An average value was used for the number of intended fish
consumers and edible fraction.
Medium
Study size
Studies encompassed a population of over 100,000.
High
Representativeness of the
population
Data were representative of overall U.S. coastal state
population.
High
Characterization of variability
Distributions were generated.
High
Lack of bias in study design (high
rating is desirable)
Response rates were fairly high; There was no obvious
source of bias.
High
Measurement error
Fish were weighed in the field.
High
Other Elements
Number of studies
There was 1 study.
Low
Agreement between researchers
N/A
Overall Rating
Medium
-------
Table 10-89. Confidence in Recommendations for Fish Consumption - Recreational Freshwater
Considerations
Rationale
Rating
Study Elements
Level of peer review
Studies can be found in peer reviewed journals and has
been reviewed by the EPA.
High
Accessibility
The original study analyses are reported in accessible
journals. Subsequent EPA analyses are detailed in
Handbook.
High
Reproducibility
Enough information is available to reproduce results.
High
Focus on factor of interest
Studies focused on ingestion offish by the recreational
freshwater angler.
High
Data pertinent to U.S.
The studies were conducted in the U.S.
High
Primary data
Data are from primary references.
High
Currency
Studies were conducted between 1988-1992.
High
Adequacy of data collection period
Data were collected for one year period for 3 studies; and a
one week period for one study.
High
Validity of approach
Data presented are as follows: one year recall of fishing trips
(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 offish meal.
Medium
Study size
Study population ranged from 800-2600.
High
Representativeness of the
population
Each study was localized to a single state or area.
Low
Characterization of variability
Distributions were generated.
High
Lack of bias in study design (high
rating is desirable)
Response rates were fairly high. One year recall of fishing
trips may result in overestimate.
Medium
Measurement error
Weight of fish portions were estimated in one study, fish
weight was estimated from reported fish length in another
study.
Medium
Other Elements
Number of studies
There are 4 key studies.
High
Agreement between researchers
Intake rates in different parts of country may be expected to
show some variation.
Medium
Overall Rating
The main drawback is that studies are not nationally
representative and not representative of long-term
consumption.
Medium
-------
Table 10-90. Confidence in Recommendations for Native American Subsistence Fish Consumption
Considerations
Rationale
Rating
Study Elements
Level of peer review
Studies are from peer reviewed journal (1 study), and
technical reports (1 study).
Medium
Accessibility
Journal articles are publicly available. CRITFC is a
technical report.
Medium
Reproducibility
The studies were adequately detailed.
High
Focus on factor of interest
Studies focused on fish ingestion and fish harvest.
High
Data pertinent to U.S.
All studies were specific to area in the U.S.
High
Primary data
One study used primary data, the other used
secondary data.
Medium
Currency
Data were from early 1980'sto 1992.
Medium
Adequacy of data collection period
Data collected for one year period.
High
Validity of approach
One study used fish harvest data; EPA used a factor
to convert to individual intake. Other study measured
individual intake directly.
Medium
Study size
The sample population was 500 for the study with
primary data.
Medium
Representativeness of the
population
Only two states were represented.
Low
Characterization of variability
Individual variation were not described in summary
study.
Medium
Lack of bias in study design (high
rating is desirable)
The response rate was 69% in study with primary
data. Bias was hard to evaluate in summary study.
Medium
Measurement error
The weight of the fish was estimated.
Medium
Other Elements
Number of studies
There were two studies; only one study described
individual variation in intake.
Medium
Agreement between researchers
Range of per-capita rates from summary study
includes per-capita rate from study with primary data.
High
Overall Rating
Studies are not nationally representative. Upper
percentiles are based on only one study.
Medium (per capita intake)
Low (upper percentiles)
-------
Table 10B-1. Percent of Fish Meals Prepared Using Various Cooking Methods by Residence Size'
Large Rural Non-
Residence Size City/Suburb Small City Town Small Town Farm Farm
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 fl\H
205
171
257
176
314
62
a 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 10B-2. Percent of Fish Meals Prepared Using Various Cooking Methods by Age
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)a
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 (N)
174
287
246
294
163
1187
a N = Total number of respondents.
Source: West et al.. 1993.
-------
Table 10B-3.
Percent of Fish Meals Prepared Using Various Cooking Methods by Ethnicity
Ethnicity
Black
Native American
Hispanic
White
Other
Total Fish
Cookina 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)a
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 fl\H
19
60
4
39
0
a N = Total number of respondents
Source: West et al.. 1993.
-------
Table 10B-4. Percent of Fish Meals Prepared Using Various Cooking Methods by Education
Post Graduate
Education
Through Some H.S.
H.S. Degree
College Degree
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)a
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 fl\H
146
524
421
91
a N = Total number of respondents.
Source: West et al.. 1993.
-------
Table 10B-5.
Percent of Fish Meals Prepared Using Various Cooking Methods by Income
Income
0 - $24,999
$25,000 - $39,999
$40,000 - or more
Total Fish
Cookina 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, etc.)
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 fl\H
387
344
369
a N = Total number of respondents.
Source: West et al.. 1993.
-------
Table 10B-6.
Percent of Fish Meals Where Fat was Trimmed or Skin was Removed, by Demographic Variables
Total Fish
Sport Fish
PoDulation
Trimmed Fat (%1
Skin Off (%)
Trimmed Fat (%1
Skin Off (%)
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
Aae (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
Over 65
41.6
43.1
43.0
42.9
Ethnicitv
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 10B-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%
Jacksmelt
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)
a Crab, mussels, lobster, abalone
b Boil, soup, steam, stew
Source: Modified from Puffer et al., 1981.
-------
Table 10B-8. Adult Consumption of Fish Parts
Weighted Percent Consuming Specific Parts
Species
Number
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 (CSFII).
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-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 (CSFII).
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
Habitat
Species
Estimated
Mean
Grams/person/day
Habitat
Species
Estimated
Mean
Grams/person/day
Habitat
Species
Estimated
Mean
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
Pom pa no
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
Pom pa no
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
Aba lone
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
Aba lone
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 10C-4. Daily Average Per Capita Estimates Of Fish Consumption
Uncooked Fish** - Mean Consumption by Species Within Habitat
U.S. Population
Habitat
Species
Estimated
Mean
Grams/person/day
Habitat
Species
Estimated
Mean
Grams/person/day
Habitat
Species
Estimated
Mean
Grams/person/day
Estuarine
Shrimp
1.78619
Marine (Con't.)
Swordfish
0.17903
All Species
Flounder
0.28559
Perch
0.66494
Squid
0.14420
(Con't.)
Lobster
0.27563
Flatfish
0.50832
Sardine
0.13750
Sea Bass
0.26661
Crab
0.40848
Pom pa no
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
Pom pa no
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
Aba lone
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
Aba lone
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.
-------
Which months of the year do you
tat the most fish?
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Momh
* Participants could B»t mom than one month.
Figure 10-1. Seasonal Fish Consumption: Wisconsin Chippewa, 1990
During thota momta of the yaw when you eat the most fish,
how many fish meals do you eat in a week?
2 3 4 6 6
Hah meal* per week
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.
ChemRisk (1992) Consumption of freshwater fish by Maine anglers. A Technical
Report. Portland, ME: ChemRisk, A Division of MeLaren / Hart. Revised July 24,
1994.
Columbia River Inter-Tribal Fish Commission (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.; Sonzogni, 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 concentrations 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.; Kuykendall, 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
fish consumption by the general U.S. population. Risk Analysis 14(4):395-404.
Rupp, E.; Miler, F.L.; Baes, C.F. III. (1980) Some results of recent surveys offish 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 (CSFII). 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.
Statistical 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 (CSFII) 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. Per 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
Cha£terJJ^Intake^£MeatandDair^Product^^^_
11. INTAKE OF MEAT AND DAIRY PRODUCTS
11.1. INTAKE STUDIES
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 CSFII
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 11A
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 (g/kg-
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)
Ex^osureFactors^Iandboo^t
August 1997
-------
Volume II - Food Ingestion Factors
Cha£terJJ^Intake^£MeatandDair^Product^
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 11-28. Percentage Mean Moisture Content (Expressed as Percentages of 100
Grams of Edible Portions)
Table 11-29. 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
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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).
The U.S. Department of Agriculture's (USDA) Nationwide Food Consumption Survey
(NFCS) and Continuing Survey of Food Intakes by Individuals (CSFII) 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. CSFI11989-91 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 CSFII 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 CSFII survey, which
was considered the only key intake study for meats and dairy products. Other relevant
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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 CSFII. The USDA NFCS and CSFII are described below.
11.1.1. U.S. Department of Agriculture Nationwide Food Consumption Survey and
Continuing Survey of Food Intake by Individuals
The NFCS and CSFII 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 one-
day data from the 1987-88 NFCS and 1994 and 1995 CSFII are also presented. Recently,
EPA conducted an analysis of USDA's 1989-91 CSFII. 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 CSFII data are presented in Volume II, Chapter 9 - Intake
of Fruits and Vegetables.
Individual average daily intake rates calculated from NFCS and CSFII 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 distribution 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.
11.1.
INTAKE STUDIES
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11.1.2. Key Meat and Dairy Products Intake Study Based on the CSFII
U.S. EPA Analysis of 1989-91 USDA CSFII Data - EPA conducted an analysis of
USDA's 1989-91 CSFII 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 9B 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 meats, 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 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, Body Weight)
should be used because the total survey population included children as well as adults.
The advantages of using the 1989-91 CSFII 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; CSFII 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
CSFII 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 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.
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The data presented in this handbook for the USDA 1989-91 CSFII is not the most up-
to-date information on food intake. USDA has recently made available the data from its
1994 and 1995 CSFII. Over 5,500 people nationwide participated in both of these
surveys, providing recalled food intake information for 2 separate days. Although the two-
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 day for 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 CSFII 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 the 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.
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11.1.3. Relevant Meat and Dairy Products Intake Studies
The U.S. EPA's Dietary Risk Evaluation System (DRES) - U.S. EPA, Office of
Pesticide Programs (OPP) - EPA OPP's DRES 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 DRES 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 DRES 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 DRES data base did not rely on a single body weight for all
individuals. Instead, DRES 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 CSFII 1989-91 survey to be used in
DRES.
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 CSFII 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
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NFCSs. Tables 11-14 and 11-15 present similar data from the 1994 and 1995 CSFII 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-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
per capita dietary intake of food 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.
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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 weight (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 people 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
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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 Nutrient 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 (18 percent), and pork (16 percent) (NLMB, 1993).
Table 11-22 shows the amount of meat consumed by the adult population grouped as non-
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
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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 CSFII 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 g-fat
= X 2
g-product g-fat g-product
(Eqn. 11-1)
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The resulting residue levels may then be used in conjunction with "as consumed"
consumption rates. The percentages of lipid fat in meat 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 III to calculate
daily 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."
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Volume II - Food Ingestion Factors
Cha£terJJ^Intake^£MeatandDair^Product^
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:
lRdw= lRac* [(100-W)/100] (Eqn. 11-2)
"Dry weight" intake rates may be converted to "as consumed" rates by using:
iRac = iRdw/[(ioo-w)/ioo]
(Eqn. 11-3)
where:
IRdw = dry weight intake rate;
IRac = as consumed intake rate; and
W = percent water content.
11.4. RECOMMENDATIONS
The 1989-91 CSFII 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
Ex^osureFactors^Iandboo^t
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 g/kg-
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 CSFII 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 CSFII data are believed to be appropriate
for assessing ingestion exposure for current populations.
Ex^osureFactors^Iandboo^t
August 1997
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Volume II - Food Ingestion Factors
§ar
Appendix 11A "
APPENDIX 11A
SAMPLE CALCULATION OF MEAN DAILY FAT INTAKE BASED ON CDC (1994)
DATA
-------
Volume II - Food Ingestion Factors
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 = g2 g-fat
day
day
day
• DX = 0.12
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 to g-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 n io §
x 0.33 x 0.12 — = 63
day
kcal
g-fat
day
Ex^osureFactors^Iandboo^t
August 1997
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Table 11-1
Per Capita
Intake of Total Meats
(g/kg-day as
consumed)
Population
Percent
GrouD
Consumina
Mean
SE
P1
P5
P10
P25
P50
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
1.13
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 CSFII
-------
Table 11-2.
Per Capita
Intake of Total Dairy
Products
(g/kg-day as consumed)
Population
Percent
GrouD
Consumina
Mean
SE
P1
P5
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
Nonmetropolitan
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 CSFII
-------
Table 11-3. Per Capita Intake of Beef (a/ka-dav as consumed)
Population
GrouD
Percent
Consumina
Mean
SE
P1
P5
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
0
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
0
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 CSFII
-------
Table 11-4. Per Capita Intake of Pork (a/ka-dav as consumed)
Population
GrouD
Percent
Consumina
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
0.235
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 CSFII
-------
Table 11-5. Per Capita Intake of Poultry (a/ka-dav as consumed)
Population
GrouD
Percent
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
91.7%
0.598
0.007
0
0
0.015
0.097
0.344
0.83
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
94.6%
0.53
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
Nonmetropolitan
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
4.745
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 of the 1989-91 CSFII
-------
Table 11-6. Per Capita Intake of Game (a/ka-dav as consumed)
Population
GrouD
Percent
Consumina
Mean
SE
P1
P5
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
0
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
0
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%
0
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 analyses of the 1989-91 CSFII
-------
Table 11-7. Per Capita Intake of Eaas (a/ka-dav as consumed)
Population
GrouD
Percent
Consumina
Mean
SE
P1
P5
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
0
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 CSFII
-------
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
77-78 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 Mixtures1 69 86 90 95 104
Dairy Products2 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 milk includes 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 Agricultural Commodity3
(Grams/kg Body Weight/Day)
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 Meats) - 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 - Yolk 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 (+ Skin, w/o Bones)
0.3793205
0.0104779
NA = Not applicable
a Consumed in any raw or prepared form.
Source: DRES database (based on 1977-78 NFCS1
-------
Table 11-10. Mean Meat Intakes Per Individual in a Day, by Sex and Age (g/day as consumed)3 for 1977-1978
Total
Lamb,
Frankfurters,
Meat,
Veal,
Sausages,
Total
Chicken
Meat
Group Age (yrs.)
Poultry and
Fish
Beef
Pork
Game
Luncheon Meats,
Spreads
Poultry
Only
Mixtures
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
a Based on USDA Nationwide Food Consumption Survey 1977-78 data for one day.
b Less than 0.5 g/day but more than 0.
c 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)3 for 1987-1988
Total Meat, Lamb, Frankfurters,
Group Poultry, and Veal, Sausages, Total Chicken Meat
Age (yrs.) Fish Beef Pork Game Luncheon Poultry Only Mixtures"
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
a 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)3 for 1977-1978
Group Age (yrs.)
Total Milk
Fluid Milk
Cheese
Eggs
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
9-11
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
184
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
3 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)3 for 1987-1988
Group Age (yrs.) Total Fluid Milk Whole Milk Lowfat/Skim Cheese Eggs
Milk
Males and Females
5 and under
347
177
129
7
11
Males
6-11
439
224
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
a 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)3 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
Mixtures0
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
20 and 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
98
104
a Based on USDA CSFI11994 and 1995 data for one day.
b Less than 0.5 g/day but more than 0.
c 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)3 for 1994 and 1995
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
a Based on USDA CSFI11994 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
Dairv Products (Total!
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
Eqqs
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 = 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).
-------
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"
g - dry weight/day
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
7.64
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
1 The estimated lifetime dietary intakes were estimated by:
Estimated lifetime intake = IRIO-1) + 5vrs * IR (1-5) + 8 vrs * IR (6-13) + 6 vrs * IR (14-19) + 25 vrs * IR (20-44) + 25 vrs * 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 Poultry in 1991a
Per Capita Consumption
Per Capita
Per Capita Consumption Retail Per Capita Consumption Boneless
Carcassb Weight
Consumption RTCC
Cut Equivalent
Trimmed Equivalent®
Food Item (a/dav^f
fa/davV
fa/davV
fa/davV
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
Total3 201.7
...
147.9
139.1
Poultrv
Young Chicken
...
78.3
...
Other Chicken
...
1.7
...
Chicken
91.3
...
54.5hi
Turkey
22.2
...
17.5h
Total3
109.2
77.0
72.1
3 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.
c RTC - ready-to-cook poultry weight is the entire dressed bird which includes bones, skin, fat, liver, heart, gizzard, and neck.
d 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 foryoung chicken, other chicken, and turkey.
f Original data were presented in lbs; converted to g/day by multiplying by a factor of 453.6 g/lb and dividing by 365 days/yr.
3 Computed from unrounded data.
h Includes skin, neck, and giblets.
1 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 1991a
Food Item
Per Capita
Food Item
Per Capita
Consumption
Consumption
(q/day)J
(q/day)J
Eqqs
Cheese
Farm Weight" 6
37.8
American
Retail Weight0 6
37.3
Cheddar
11.2
Other"
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
Evaporated 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
Drv Milk Products'
Cottage Cheese (lowfat)
1.6
Dry Whole Milk
0.5
Nonfat Dry Milk
3.2
Frozen Dairv 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 Products"
5.3
Butter
5.2
Total®
36.4
All Diarv 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.
' Includes imports of Gruyere and Emmenthaler.
9 Includes Gorgonzola.
11 Includes mellorine, frozen yogurt beginning 1981, and other nonstandardized frozen diary products.
' Includes quantities used in other dairy products.
1 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 Daily Intake (as consumed) of Meat and Poultry Grouped by Region and Gender3
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
Poultry
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 (as consumed) of Meat Consumed bv Adults Grouped bv Frequency of Eatings6
Percent of Eaters Total
Consumption Median Daily
Percent of Total Male Fema|e for 14 Days Intake
Frequency of Eatings Eaters Jcj] (q/day)
Non-Meat Eaters3
1%
20
80
None
None
Light Meat Eaters"
30%
27
73
<1025
54
Medium Meat Eatersc
33%
39
61
1025-1584
93
Heavv Meat Eaters"
36%
73
27
>1548
144
a A female who is employed and on a diet. She lives alone or 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.
c 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.
d Male who is not on a diet and lives in a household of 2-4 individuals, which may include children.
e 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 Percentage of Individuals Using These Foods in Three Days
% Indiv. using Quantity consumed per eating
food in 3 days occasion Consumers-only
Food category (g) Quantity consumed per eating occasion at Specified Percentiles (g)
Average Standard 5 25 50 75 90 95 99
Deviation
Meat3
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
Dairv 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
Milkb
82.5
203
134
15
122
244
245
366
488
552
Cheese0
40
41
28
14
28
28
56
58
85
140
a Meat - beef, pork, lamb, and veal.
b 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 Dairy Products3
Product
Fat Percentage
Comment
Meats
Beef
Lean only
6.16
Raw
Lean and fat, 1/4 in. fat trim
9.91
Cooked
Brisket (point half)
19.24
Raw
Lean and fat
21.54
Cooked
Brisket (flat half)
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 Dairy Products3 (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
a Based on the lipid content in 100 grams, edible portion.
Source: USDA, 1979-1984.
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Table 11-25.
Fat Content of Meat Products
Meat Product
Total Fat
Percent Fat
3-oz cooked serving (85.05 q)
(q)
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
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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
Population
Heavy Meat
Eaters
Medium Meat
Eaters
Light Meat
Eaters
Non-Meat
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 (%)a
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.
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Table 11-27.
Mean Total Daily Dietary Fat Intake (g/day) Grouped by Age and Gender"
Total
Males
Females
Age
N
Mean Fat Intake
N
Mean Fat Intake
N
Mean Fat Intake
(vrs)
(g/day)
(g/day)
(g/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
8.720
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: Adapted from CDC. 1994.
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Table 11-28. Percentage Mean Moisture Content (Expressed as Percentages of 100 Grams of Edible Portions)3
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
Dairv 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%
a Based on the water content in 100 grams, edible portion.
Source: USDA, 1979-1984.
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Table 11-29. Summary of Meat, Poultry, and Dairy Intake Studies
Study
Survey Population Used in
Calculating Intake
Types of Data Used
Units
Food Items
KEY STUDIES
EPA Analysis of
1989-91 CSFII Data
Per capita
1989-91 CSFII data;
Based on 3-day average
individual intake rates.
g/kg-day; as consumed
Distributions of intake rates for total
meats and total dairy; individual
food items.
RELEVANT STUDIES
AIHC, 1994
Adults, Per Capita
USDA NFCS 1977-78 data
presented in the 1989 version
of the Exposure Factors
Handbook that were analyzed
by Finley and Paustenbach
(1992).
g/day
Distribution for beef consumption
presented in @Risk format.
EPA's DRES
(White et al„ 1983)
Per capita (i.e., consumers
and nonconsumers)
1977-78 NFCS
3-day individual intake data
g/kg-day; as consumed
Intake for a wide variety of meats,
poultry, and dairy products
presented; complex food groups
were disaggregated
NLMB, 1993
Adult daily mean intake
rates
MRCA s Menu Census
g/day; as consumed
Intake rates for various meats by
region and gender.
Pao et al., 1982
Consumers only serving
size data provided
1977-78 NFCS
3-day individual intake data
g; as consumed
Distributions of serving sizes for
meats, poultry, and diary products.
USDA, 1980; 1992;
1996a; 1996b
Per capita and consumer
only grouped by age and
sex
1977-78 and 1987-88 NFCS,
and 1994 and 1995 CSFII
1-day individual intake data
g/day; as consumed
Total meat, poultry and fish, total
poultry, total milk, cheese and eggs.
USDA, 1993
Per capita consumption
based on "food
disappearance"
Based on food supply and
utilization data which were
provided by National
Agricultural Statistics Service
(NASS), Customs Service
reports, and trade
associations.
g/day; as consumed
Intake rates of meats, poultry, and
diary products; intake rates of
individual food items.
U.S. EPA/ORP,
1984a; 1984b
Per capita
1977-78 NFCS
Individual intake data
g/day; as consumed
Mean intake rates for total meats,
total diary products, and individual
food items.
U.S. EPA/OST,
1989
Estimated lifetime dietary
intake
Based on FDA Total Diet
Study Food List which used
1977-78 NFCS data, and
NHANES II data
g/day; dry weight
Various food groups; complex
foods disaggregated
-------
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 CSFI11989-91 Data
Total Dairv Intake
8.0 g/kg-day
29.7 g/kg-day
see Table 11-2 EPA Analysis of CSFI11989-91 Data
Individual Meat and Dairv Products
see Tables 11-3 to 11-7
see Tables 11-3 to
11-7
see Tables 11-3 to 11-7 EPA Analysis of CSFI11989-91 Data
-------
Table 11-31. Confidence in Meats and Dairy Products Intake Recommendations
Considerations
Rationale
Rating
Study Elements
Level of peer review
USDA CSFII survey receives high level of peer
review. EPA analysis of these data has been peer
reviewed outside the Agency.
High
Accessibility
CSFII data are publicly available.
High
Reproducibility
Enough information is included to reproduce
results.
High
Focus on factor of interest
Analysis is specifically designed to address food
intake.
High
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
the time the analysis was conducted for this
Handbook.
High
Adequacy of data collection period
Survey is designed to collect short-term data.
Medium confidence for average 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
adequate.
High
Representativeness of the population
The population studied was the U.S. population.
High
Characterization of variability
Survey was not designed to capture long term
day-to-day variability. Short term distributions
are provided for various age groups, regions, etc.
Medium
Lack of bias in study design (high rating is desirable)
Response rate was adequate.
Medium
Measurement error
No measurements were taken. The study relied
on survey data.
N/A
Other Elements
Number of studies
1
CSFII 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.
Low
Agreement between researchers
Although the CSFII was the only study classified
as key study, the results are in good agreement
with earlier data.
High
Overall Rating
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.
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 and 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 FOR CHAPTER 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 Intake 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]
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Volume II - Food Ingestion Factors
Cha£terJ^^Intake^£GrainProduct^
12. INTAKE OF GRAIN PRODUCTS
12.1. INTAKE STUDIES
12.1.1. U.S. Department of Agriculture Nationwide Food Consumption
Survey and Continuing Survey of Food Intake by Individuals
12.1.2. Key Grain Products Intake Studies Based on the CSFII
12.1.3. Relevant Grain Products Intake Studies
12.1.4. 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
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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 of 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
CSFII Grains Data
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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 (CSFII) 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. CSFII 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 CSFII survey, which
was considered the only key intake study for grain products. Other relevant studies are
also presented to provide 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 USDA's NFCS and CSFII. The USDA NFCS and CSFII are described below.
12.1. INTAKE STUDIES
12.1.1. U.S. Department of Agriculture Nationwide Food Consumption
Survey and Continuing Survey of Food Intake by Individuals
The NFCS and CSFII 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
Ex^osureFactors^Iandboo^t
August 1997
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Volume II - Food Ingestion Factors
Cha£terJ^^Intake^£GrainProduct^
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 CSFII are also presented. Recently, EPA
conducted an analysis of USDA's 1989-91 CSFII. 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 CSFII data are presented in Volume II, Chapter 9 - Intake of Fruits and
Vegetables.
Individual average daily intake rates calculated from NFCS and CSFII 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 distribution 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 term 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 long-
term distribution.
12.1.2. Key Grain Products Intake Studies Based on the CSFII
U.S. EPA Analysis of 1989-91 USDA CSFII Data - EPA conducted an analysis of
USDA's 1989-91 CSFII 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
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Cha£terJ^^Intake^£GrainProduct^
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 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 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 CSFII 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; CSFII 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
CSFII 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
Table 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 CSFII is not the most up-
to-date information on food intake. USDA has recently made available the data from its
1994 and 1995 CSFII. 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
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Cha£terJ^^Intake^£GrainProduct^
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 CSFII 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 (DRES) - USEPA, Office of Pesticide
Programs (OPP) - EPA OPP's DRES 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 DRES 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 DRES per capita, as consumed intake rates for all
age/sex/demographic 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 be 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 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 DRES data base did not
rely on a single body weight for all individuals. Instead, DRES 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 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 CSFII 1989-91 survey to be used in DRES.
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 grain
products using NFCS data from 1977-78 and 1987-88 (USDA 1980; 1992) and CSFII data
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August 1997
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Volume II - Food Ingestion Factors
Cha£terJ^^Intake^£GrainProduct^
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 CSFII 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 USDA-
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 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 12-18 presents intake rates for grain
products for various age groups. Estimated lifetime ingestion rates derived by U.S. EPA
(1989) 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
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Volume II - Food Ingestion Factors
Cha£terJ^^Intake^£GrainProduct^
basis. These data, however, may not reflect current 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 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 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 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
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 interview and the day after the interview. Quantities consumed per eating occasion,
are presented in Table 12-20.
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August 1997
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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:
lRdw= lRac* [(100-W)/100]
(Eqn. 12-1)
"Dry weight" intake rates may be converted to "as consumed"
rates by using:
iRac = iRdw/[(ioo-w)/ioo]
(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 CSFII data described in this section
recommended grain, product intake rates for the general
were used in selecting
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-
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August 1997
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Volume II - Food Ingestion Factors
Cha£terJ^^Intake^£GrainProduct^
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 of foods (i.e., total grains, breads), 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
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 CSFII 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 CSFII data are believed to be appropriate for assessing ingestion
exposure for current populations.
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August 1997
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Table 12-1.
Per Capita Intake of Total 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 analysis of the 1989-91 CSFII.
-------
Table 12-2. Per Capita Intake of Breads (g/kg-day as consumed)3
Population Group
Percent
Consuminq
MEAN
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
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
Nonmetropolitan
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 breads, 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 CSFII.
-------
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
Grouc
Consuminq
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
0
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
0
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
9.67
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 CSFII
-------
Table 12-4. Per Capita Intake of Snacks Containing Grain (g/kg-day as consumed) a
Population Group
Percent
Consuminq
MEAN
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
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
0
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 analysis of the 1989-91 CSFII.
-------
Table 12-5.
Per Capita Intake of Breakfast Foods (g/kg-day as consumed) a
Population Group
Percent
Consuminq
MEAN
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
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
0
0.21
0.53
0.61
1.23
6.83
Other/NA
13.7%
0.079
0.037
0
0
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
13.61
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 french 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)
Population
Group
Percent
Consuminq
MEAN
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
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
3-5
15.3%
0.543
0.142
0
0
0
0
0
0
2.19
3.37
6.51
7.72
3-11
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
20-39
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
Nonmetropolitan
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
*\sian
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
0.00
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
Vlidwest
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
i/Vest
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 analysis of the 1989-91 CSFII.
-------
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
Grouc
Consuminq
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 CSFII.
-------
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
Grouc
Consuminq
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
20.8%
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
0
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 CSFII.
-------
Table 12-9. Per Capita Intake of Ready-to-Eat Cereals (g/kg-day as consumed)3
Population Group
Percent
Consuminq
MEAN
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
45.6%
0.306
0.007
0
0
0
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
0.078
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 Incluldes 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 analysis of the 1989-91 CSFII.
-------
Table 12-10.
Per Capita Intake of Baby Cereals (g/kg-day as consumed)
Population Group
Percent
Consuminq
MEAN
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
1.1%
0.037
0.051
0
0
0
0
0
0
0
0
0
22.57
Age (years)3
<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
a 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 analysis of the 1989-91 CSFII.
-------
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
Food Product
77-78 Data
(g/day)
87-88 Data
(g/day)
89-91 Data
(g/day)
94 Data
(g/day)
95 Data
(g/day)
Grains
215
237
273
300
303
Grains
Mixtures
52
72
89
112
107
Source: USDA, 1980; 1992; 1996a; 1996b.
-------
Table 12-12. Mean Per Capita Intake Rates for Grains Based on All Sex/Age/Demographic Subgroups
Average Consumption
Raw Agricultural Commodity®
(Grams/kg Body Weight-Day)
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
0.0121575
0.0004864
Wheat-flour
1.2572489
0.0127412
Millet
0.0000216
0.0000104
a Consumed in any raw or prepared form
Source: DRES data base (based on 1977-78 NFCS).
-------
Table 12-13.
Mean Grain Intake Per Individual in a Day 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 Grainb
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
a Based on USDA Nationwide Food Consumption Survey 1977-78 data for one day.
b 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
Age (years)
Grains
and Rolls
Toast
Pies
Corn Chips
and Pastas
Grain"
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 1987-8
8 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 Day by Sex and Age (g/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
Age (years)
Total Grains
and Rolls
French Toast
Chips
Pastas
Grain
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
a Based on USDA CSFII 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, by Age (g/day
as consumed)
Age (years)
Breads
Cereals
Other Grains
All ages
147.3+1.4
29.9+1.3
22.9+1.7
Under 1
16.2+9.2
37.9+8.2
1.8+10.9
1 to 4
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 Region (g/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).
-------
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) Estimated'lifetime
(0-1)
(1-5)
(6-13)
(14-19)
(20-44)
(45-70)
Wheat
27.60
42.23
60.80
79.36
65.86
55.13
60.30
Corn
4.00
15.35
19.28
23.21
12.83
14.82
12.01
Rice
2.22
4.58
5.24
5.89
5.78
4.21
5.03
Oats
3.73
2.65
2.27
1.89
1.32
2.00
1.85
Other Grain
0.01
0.08
0.41
0.73
13.45
4.41
6.49
Total Grain
37.56
64.82
87.58
110.34
90.59
76.12
84.19
a The estimated lifetime dietary intakes were estimated by:
Estimated lifetime = IRfO-'H + 5vrs * IR (1-5^ + 8 vrs * IR (6-13^ + 6 vrs * IR (14-19^ + 25 vrs * IR (20-44) + 25 vrs * 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 12-19. Per Capita Consumption of Flour and Cereal Products in 1991a
Per Capita Consumption
Food Item (g/day)a
Total Wheat Flour" 169.8
Rye Flour 0.7
Ricec 20.9
Total Corn Products'1 27.2
Oat Products8 10.7
Barley Products' 1.1
Total Flour and Cereal Products9 230.6
a Original data were presented in Ibs/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.
c Milled basis.
d Includes corn flour and meal, hominy and grits, and corn starch.
8 Includes rolled oats, ready-to-eat cereals, oat flour, and oat bran.
' Includes barley flour, pearl barley, and malt and malt extract used in food processing.
9 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 Percentage of Individuals Using These Foods in Three Days
% Indiv. Quantity consumed
using per eating occasion Consumers-only
Food category food in 3 (g) Quantity consumed per eating occasion at specified percentiles (g)
days
Average
Standard
Deviation
5
25
50
75
90
95
99
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
123
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 Cbased on 1977-78 NFCS1
-------
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
Study
Survey Population Used in
Calculating Intake
Types of Data Used
Units
Food Items
KEY STUDIES
EPA Analysis of 1989-91
CSFII Data
Per capita
1989-91 CSFII data;
Based on 3-day average
individual intake rates.
g/kg-day; as
consumed
Distributions of intake rates for total
grain; individual grain items
RELEVANT STUDIES
EPA's DRES
(White etal., 1983)
Per capita (i.e., consumers
and nonconsumers)
1977-78 NFCS
3-day individual intake data
g/kg-day; as
consumed
Intake for a wide variety of grain
products presented; complex food
groups were disaggregated
Pao etal., 1982
Consumers only serving size
data provided
1977-78 NFCS
3-day individual intake data
g; as consumed
Distributions of serving sizes for grain
products
USDA, 1980; 1992;
1996a; 1996b
Per capita and consumer
only grouped by age and sex
1977-78 and 1987-88 NFCS,
and 1994 and 1995 CSFII
1 -day individual intake data
g/day; as consumed
Total grains and various grain
products
USDA, 1993b
Per capita consumption
based on "food
disappearance"
Based on food supply and
utilization data
g/day; as consumed
Intake rates of grain products
U.S. EPA/ORP,
1984a; 1984b
Per capita
1977-78 NFCS
Individual intake data
g/day; as consumed
Mean intake rates for total grain
products, and individual grain items.
U.S. EPA/OST, 1989
Estimated lifetime dietary
intake
Based on FDA Total Diet Study
Food List which used 1977-78
NFCS data, and NHANES II
data
g/day; dry weight
Various food groups; complex foods
disaggregated
-------
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 CSFI11989-91 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 Analysis of CSFI11989-91 Data
-------
Table 12-24. Confidence in Grain Products Intake Recommendation
Considerations
Rationale
Rating
Study Elements
• Level of peer review
USDA CSFII survey receives high level of peer
review. EPA analysis of these data has been peer
reviewed outside the Agency.
High
• Accessibility
CSFII data are publicly available.
High
• Reproducibility
Enough information is included to reproduce results.
High
• Focus on factor of
interest
Analysis is specifically designed to address food
intake.
High
• 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 the
time the analysis was conducted for this Handbook.
High
• Adequacy of data
collection period
Survey is designed to collect short-term data.
Medium confidence for average 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 adequate.
High
• Representativeness of the
population
The population studied was the U.S. population.
High
• Characterization of
variability
Survey was not designed to capture long term day-to-
day variability. Short term distributions are provided
for various age groups, regions, etc.
Medium
• Lack of bias in study design
(high rating is desirable)
Response rate was adequate.
Medium
• Measurement error
No measurements were taken. The study relied on
survey data.
N/A
Other Elements
• Number of studies
1
CSFII 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.
Low
• Agreement between researchers
Although the CSFII was the only study classified as
key study, the results are in good agreement with
earlier data.
High
Overall Rating
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.
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 CSFII 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
Snacks
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
french toast
Grain Mixtures
58-
grain mixtures
Meat Mixtures
27-
meat mixtures
28-
-------
REFERENCES FOR CHAPTER 12
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 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. (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 FOR CHAPTER 12
The following selected tables are available for download as Lotus 1-2-3 worksheets.
Table
12-1.
Per Capita Intake of
consumed) [WK1,
Table
12-2.
Per Capita Intake of
Table
12-3.
Per Capita Intake of
Table
12-4.
Per Capita Intake of
[WK1, 6 kb]
Table
12-5.
Per Capita Intake of
[WK1, 6 kb]
Table
12-6.
Per Capita Intake of
Table
12-7.
Per Capita Intake of
[WK1, 5 kb]
Table
12-8.
Per Capita Intake of
Table
12-9.
Per Capita Intake of
[WK1, 6 kb]
[WK1, 6 kb]
[WK1, 6 kb]
[WK1, 5 kb]
[WK1, 5 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]
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Cha£terJJ^Intake^ates^or^Various^IomeProducedFoodItem^^^^^^^^_
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
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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
Table
13-35.
Consumer
Only
Intake
of
Table
13-36.
Consumer
Only
Intake
of
Table
13-37.
Consumer
Only
Intake
of
Table
13-38.
Consumer
Only
Intake
of
Table
13-39.
Consumer
Only
Intake
of
Table
13-40.
Consumer
Only
Intake
of
Table
13-41.
Consumer
Only
Intake
of
Table
13-42.
Consumer
Only
Intake
of
Table
13-43.
Consumer
Only
Intake
of
Table
13-44.
Consumer
Only
Intake
of
Table
13-45.
Consumer
Only
Intake
of
Table
13-46.
Consumer
Only
Intake
of
Table
13-47.
Consumer
Only
Intake
of
Table
13-48.
Consumer
Only
Intake
of
Table
13-49.
Consumer
Only
Intake
of
Table
13-50.
Consumer
Only
Intake
of
Table
13-51.
Consumer
Only
Intake
of
Table
13-52.
Consumer
Only
Intake
of
Table
13-53.
Consumer
Only
Intake
of
Table
13-54.
Consumer
Only
Intake
of
Table
13-55.
Consumer
Only
Intake
of
Table
13-56.
Consumer
Only
Intake
of
Table
13-57.
Consumer
Only
Intake
of
Table
13-58.
Consumer
Only
Intake
of
Table
13-59.
Consumer
Only
Intake
of
Table
13-60.
Consumer
Only
Intake
of
Table
13-61.
Consumer
Only
Intake
of
Table
13-62.
Consumer
Only
Intake
of
Table
13-63.
Consumer
Only
Intake
of
Table
13-64.
Consumer
Only
Intake
of
Table
13-65.
Consumer
Only
Intake
of
Table
13-66.
Consumer
Only
Intake
of
Table
13-67.
Consumer
Only
Intake
of
Table
13-68.
Consumer
Only
Intake
of
Table
13-69.
Consumer
Only
Intake
of
Table
13-70.
Consumer
Only
Intake
of
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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
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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 and 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 seven-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
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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. Appendix 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 (1) 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.
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^_^^^^^^^_^^^^^_Cha£terJJ^Intake^atesJbr^VariousHome^rodu£edFoodItems
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 of the 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:
W;
W,
m,q,
m, g,
(Eqn. 13-1)
where:
Wj =
Wf =
mi =
qi =
Homegrown amount of food item/group attributed to member i during the week (g/week);
Total quantity of homegrown food item/group used by the family members (g/week);
Number of meals of household food consumed by member i during the week (meals/week); and
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
(W|) 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 estimating 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
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Cha^terJJ^Intake^ates^or^Various^Iome^roducedFoodlter^
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 to 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.
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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 percentiles
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
year.
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 Nc is the weighted number of individuals consuming the homegrown food item, and NT
is the weighted total number of individuals surveyed, then NT - Nc is the weighted number
of individuals who reported zero consumption of the food item. In addition, there are
(p/100 x Nc) 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 N + (Nj - N ,
= 100 x U00 L (Eqn. 13-2)
Nt
T
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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 (Nc) is 14,744,000. 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 Nc) + (Nt - Nc) = 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 / 188,109,000)
Povemii = gg^ 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 population. 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, NC/NT.
Table 13-4 displays the weighted numbers NT, 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
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Cha£terJJ^Intake^ates^or^Various^Iome^rodu£edFoodIten^
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:
lA=l*(1 - L,)x(1 - L2)
(Eqn
13-3)
lA=|x(1 -Lp)
(Eqn.
13-4)
where lA is the adjusted intake rate, I is the tabulated intake rate, L., 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
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Cha^terJJ^Intake^ates^or^Various^Iome^roducedFoodlter^
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
among populations in non-metropolitan and suburban areas and lowest in central city
areas. Results of the regional analyses indicate that intake of homegrown fruits,
vegetables, 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 13-34 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
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Cha£terJJ^Intake^ates^or^Various^Iome^rodu£edFoodIten^
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 utilized. 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 each household member. Thus, for instance, in a two-
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 the 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 periods 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.
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Cha^terJJ^Intake^ates^or^Various^Iome^roducedFoodlter^
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 this 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 CSFII 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 to 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 compared with previous values since the results from the new
analyses are presented on a body weight basis.
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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
Reaion/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
Description
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
Animals
Question 76
Did anyone in the household produce any animal products such as milk, eggs, meat,
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
-
January, February, March
a 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 Reqions
Northeast
Midwest
South
West
wgtd
unwgtd
wgtd
unwgtd
wgtd
unwgtd
wgtd
unwgtd
wgtd
unwgtd
Total
188019000
9852
41167000
2018
46395000
2592
64331000
3399
36066000
1841
Age (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
1586000
90
-------
Table 13-5. Percent Weight Losses from Preparation of Various Meats
Mean Net Cooking Loss (%)
9
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
1 to 67
10
36
14 to 52
11
Chicken
32
7 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
Fishc
30
-19 to 81
19
11
1 to 26
6
Shellfish
33
1 to 94
30
10
10 to 10
0
a
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.
c
Averaged over a variety offish, to include: bass, bluefish, butterfish, cod, flounder, haddock, halibut, lake trout, makerel,
perch, porgy, red snapper, 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 (%)b c
Range of
Standard
Range of
Type of Fruit
Mean Means
Deviation
Mean
Means
Standard
Apples
25 3 to 42
13
22"
13 to 40b
NAb
Pears
..
-
22"
12 to 60b
NAb
41 =
25 to 47c
NAC
Peaches
36 19 to 50
12
24"
6 to 68b
NAb
Strawberries
..
-
10b
6 to 14b
NAb
30c
96 to 41c
15c
Oranaes
..
—
29b
19 to 38b
NAb
a Includes losses from draining cooked forms.
b Includes losses from removal of skin or peel, core or pit, stems or caps, seeds and defects.
c Includes losses from removal of drained liquids from canned or frozen forms.
Source: USDA. 1975
-------
Table 13-7. Percent Weight Losses from Preparation of Various Vegetables
Type of
Vegetable
Mean
Mean Net Cooking Loss (%)"
Range of Means
Standard
Deviation
Mean
Mean Net Post Cooking Loss (%)b
Standard
Ranqe of Means Deviation
Asparagus
23
5 to 47
16
Beets
28
4 to 60
17
--
--
--
Broccoli
14
0 to 39
13
-
-
-
Cabbage
11
4 to 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
-12
-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
3 to 27
9
-
-
-
Pumpkins
19
8 to 30
11
-
-
-
Snap Beans
18
5 to 42
13
-
-
-
Tomatoes
15
2 to 34
10
-
-
-
Potatoes
-22
-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
ntake of Homegrown Fruits
(g/kg-dav)
All Regions Combined
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
14744000
817
7.84
2.68E+00
1.89E-01
6.26E-02
1.68E-01
2.78E-01
4.97E-01
1.07E+00
2.37E+00
5.97E+00
1.11E+01
2.40E+01
6.06E+01
Age (years)
01-02
360000
23
6.32
8.74E+00
3.10E+00
9.59E-01
1.09E+00
1.30E+00
1.64E+00
3.48E+00
7.98E+00
1.93E+01
6.06E+01
6.06E+01
6.06E+01
03-05
550000
34
6.79
4.07E+00
1.48E+00
1.00E-02
1.00E-02
3.62E-01
9.77E-01
1.92E+00
2.73E+00
6.02E+00
8.91 E+00
4.83E+01
4.83E+01
06-11
1044000
75
6.25
3.59E+00
6.76E-01
1.00E-02
1.91 E-01
4.02E-01
6.97E-01
1.31 E+00
3.08E+00
1.18E+01
1.58E+01
3.22E+01
3.22E+01
12-19
1189000
67
5.80
1.94E+00
3.66E-01
8.74E-02
1.27E-01
2.67E-01
4.41 E-01
6.61 E-01
2.35E+00
6.76E+00
8.34E+00
1.85E+01
1.85E+01
20-39
3163000
164
5.13
1.95E+00
3.33E-01
8.14E-02
1.28E-01
2.04E-01
3.74E-01
7.03E-01
1.77E+00
4.17E+00
6.84E+00
1.61E+01
3.70E+01
40-69
5633000
309
9.93
2.66E+00
3.04E-01
6.26E-02
1.91 E-01
2.86E-01
4.69E-01
1.03E+00
2.33E+00
5.81 E+00
1.30E+01
2.38E+01
5.33E+01
70 +
2620000
134
16.50
2.25E+00
2.34E-01
4.41 E-02
2.24E-01
3.80E-01
6.11 E-01
1.18E+00
2.35E+00
5.21 E+00
8.69E+00
1.17E+01
1.53E+01
Season
Fall
3137000
108
6.58
1.57E+00
1.59E-01
2.63E-01
3.04E-01
3.90E-01
5.70E-01
1.04E+00
1.92E+00
3.48E+00
4.97E+00
1.06E+01
1.06E+01
Spring
2963000
301
6.42
1.58E+00
1.37E-01
8.89E-02
1.98E-01
2.54E-01
4.23E-01
8.57E-01
1.70E+00
4.07E+00
5.10E+00
8.12E+00
3.17E+01
Summer
4356000
145
9.58
3.86E+00
6.40E-01
1.00E-02
9.18E-02
1.56E-01
4.45E-01
1.26E+00
3.31 E+00
1.09E+01
1.46E+01
5.33E+01
6.06E+01
Winter
4288000
263
8.80
3.08E+00
3.41 E-01
4.41 E-02
1.72E-01
2.69E-01
5.56E-01
1.15E+00
2.61 E+00
8.04E+00
1.53E+01
2.49E+01
4.83E+01
Urbanization
Central City
3668000
143
6.51
2.31 E+00
2.64E-01
4.41 E-02
1.82E-01
3.33E-01
5.67E-01
1.08E+00
2.46E+00
5.34E+00
1.05E+01
1.43E+01
1.93E+01
Nonmetropolitan
4118000
278
9.15
2.41 E+00
3.09E-01
6.26E-02
1.27E-01
2.32E-01
4.50E-01
1.15E+00
2.42E+00
4.46E+00
8.34E+00
2.40E+01
5.33E+01
Suburban
6898000
394
7.97
3.07E+00
3.22E-01
1.25E-01
2.30E-01
2.95E-01
4.91 E-01
9.93E-01
2.33E+00
7.26E+00
1.52E+01
3.70E+01
6.06E+01
Race
Black
450000
20
2.07
1.87E+00
8.53E-01
1.32E-01
2.84E-01
4.55E-01
6.08E-01
1.13E+00
1.53E+00
2.29E+00
2.29E+00
1.93E+01
1.93E+01
White
14185000
793
9.00
2.73E+00
1.94E-01
7.22E-02
1.82E-01
2.82E-01
5.10E-01
1.07E+00
2.46E+00
6.10E+00
1.17E+01
2.40E+01
6.06E+01
Questionnaire Response
Households who garden
12742000
709
18.70
2.79E+00
2.10E-01
5.60E-02
1.84E-01
2.87E-01
5.30E-01
1.12E+00
2.50E+00
6.10E+00
1.18E+01
2.49E+01
6.06E+01
Households who farm
1917000
112
26.16
2.58E+00
2.59E-01
7.22E-02
2.76E-01
4.13E-01
7.53E-01
1.61 E+00
3.62E+00
5.97E+00
7.82E+00
1.58E+01
1.58E+01
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987/88 NFCS
-------
Table 13-9. Consumer Only Intake of Homeg
rown Fruits
g/kg-day) - Northeast
Population Nc
Nc
%
Grouo watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total 1279000
72
3.11
9.29E-01
2.20E-01
7.91 E-02
8.48E-02
1.61E-01
3.11E-01
4.85E-01
7.82E-01
1.29E+00
2.16E+00
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+00
2.16E+00
7.13E+00
7.13E+00
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
8.81 E-01
1.38E+00
1.79E+00
2.75E+00
2.75E+00
Urbanization
Central City 50000
3
0.52
*
*
*
*
*
*
*
*
*
Nonmetropolitan 176000
10
3.19
*
*
*
*
*
*
*
*
*
Suburban 1053000
59
4.05
1.05E+00
2.63E-01
1.84E-01
2.30E-01
2.93E-01
4.37E-01
5.43E-01
8.12E-01
1.29E+00
2.75E+00
1.17E+01
1.17E+01
Questionnaire Response
Households who garden 983000
59
7.86
1.04E+00
2.64E-01
8.74E-02
1.82E-01
2.13E-01
3.75E-01
5.43E-01
8.81 E-01
1.38E+00
2.75E+00
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
Nc wgtd = weighted number of consumers; Nc unwgtd =
Source: Based on EPA's analyses of the 1987-88 NFCS
unweighted number of consumers in survey.
-------
Table 13-10. Consumer Only
Intake of Homegrown Fruits
(g/kg-dav)
Midwest
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
4683000
302
10.09
3.01 E+00
4.13E-01
4.41 E-02
1.25E-01
2.35E-01
4.68E-01
1.03E+00
2.31 E+00
6.76E+00
1.39E+01
5.33E+01
6.06E+01
Season
Fall
1138000
43
7.90
1.54E+00
1.86E-01
2.63E-01
3.04E-01
4.74E-01
6.11 E-01
1.07E+00
1.92E+00
3.48E+00
4.34E+00
5.33E+00
5.33E+00
Spring
1154000
133
10.83
1.69E+00
2.76E-01
8.89E-02
2.09E-01
2.62E-01
4.23E-01
9.23E-01
1.72E+00
2.89E+00
4.47E+00
1.60E+01
3.17E+01
Summer
1299000
44
12.70
7.03E+00
1.85E+00
6.26E-02
9.18E-02
1.25E-01
4.28E-01
1.55E+00
8.34E+00
1.61E+01
3.70E+01
6.06E+01
6.06E+01
Winter
1092000
82
9.83
1.18E+00
1.80E-01
2.57E-02
5.60E-02
1.46E-01
3.62E-01
6.09E-01
1.42E+00
2.61 E+00
3.73E+00
1.09E+01
1.09E+01
Urbanization
Central City
1058000
42
6.08
1.84E+00
3.93E-01
4.15E-02
1.01 E-01
2.63E-01
5.21 E-01
1.07E+00
1.90E+00
2.82E+00
9.74E+00
1.09E+01
1.09E+01
Nonmetropolitan
1920000
147
13.43
2.52E+00
5.43E-01
5.60E-02
1.08E-01
1.46E-01
3.96E-01
1.03E+00
2.07E+00
4.43E+00
6.84E+00
5.33E+01
5.33E+01
Suburban
1705000
113
11.60
4.29E+00
8.72E-01
9.18E-02
2.04E-01
3.10E-01
4.81 E-01
7.64E-01
3.01 E+00
1.39E+01
1.80E+01
6.06E+01
6.06E+01
Response to Questionnaire
Households who garden
4060000
267
18.17
3.27E+00
4.69E-01
4.41 E-02
1.01 E-01
2.04E-01
4.48E-01
1.07E+00
2.37E+00
7.15E+00
1.46E+01
5.33E+01
6.06E+01
Households who farm
694000
57
25.89
2.59E+00
3.01 E-01
5.60E-02
1.91 E-01
4.08E-01
1.26E+00
1.63E+00
3.89E+00
6.76E+00
8.34E+00
1.11E+01
1.11E+01
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd =
Source: Based on EPA's analyses of the 1987-88 NFCS
unweighted number of consumers in survey.
-------
Table 13-11. ConsumerOnly
Intake of Homegrown Fruits
(q/kq-dav)
South
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
4148000
208
6.45
2.97E+00
3.00E-01
1.12E-01
2.42E-01
3.55E-01
5.97E-01
1.35 E+00
3.01 E+00
8.18E+00
1.41 E+01
2.38E+01
2.40E+01
Season
Fall
896000
29
6.80
1.99E+00
4.39E-01
3.92E-01
4.27E-01
4.46E-01
6.50E-01
1.13E+00
1.96 E+00
4.97E+00
8.18E+00
1.06E+01
1.06E+01
Spring
620000
59
3.69
2.05E+00
2.55E-01
1.55E-01
2.82E-01
3.11 E-01
4.50E-01
1.06 E+00
4.09 E+00
5.01 E+00
6.58 E+00
7.05E+00
7.05E+00
Summer
1328000
46
7.48
2.84E+00
6.50E-01
8.14E-02
1.56E-01
2.67E-01
4.41 E-01
1.31 E+00
2.83 E+00
6.10E+00
1.43 E+01
2.40E+01
2.40E+01
Winter
1304000
74
7.86
4.21 E+00
6.51 E-01
1.12E-01
2.36E-01
3.82E-01
8.92E-01
1.88 E+00
3.71 E+00
1.41 E+01
1.97E+01
2.38E+01
2.38E+01
Urbanization
Central City
1066000
39
6.18
3.33E+00
5.39E-01
2.36E-01
3.92E-01
4.55E-01
8.34E-01
2.55 E+00
4.77 E+00
8.18E+00
1.06 E+01
1.43E+01
1.43E+01
Nonmetropolitan
1548000
89
8.10
2.56E+00
3.87E-01
8.14E-02
2.67E-01
3.38E-01
6.12E-01
1.40 E+00
2.83 E+00
5.97E+00
1.04 E+01
2.40E+01
2.40E+01
Suburban
1534000
80
5.48
3.14E+00
6.02E-01
1.12E-01
1.56E-01
2.84E-01
5.08E-01
1.10E+00
2.29 E+00
1.18E+01
1.55 E+01
2.38E+01
2.38E+01
Response to Questionnaire
Households who garden
3469000
174
16.91
2.82E+00
2.94E-01
1.56E-01
2.84E-01
3.84E-01
6.50E-01
1.39 E+00
2.94 E+00
6.10E+00
1.41 E+01
2.11 E+01
2.40E+01
Households who farm
296000
16
13.26
*
*
*
*
*
*
*
* Intake data not provided for subpopulatins for which there were less than 20 observations
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-88 NFCS
-------
Table 13-12. Consumer Only Intake of Homeg
rown Fruits
(g/kg-dav) -
West
Population
Nc
Nc
%
3rouo
watd u
nwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
4574000
233
12.68
2.62E+00
3.07E-01
1.50E-01
2.75E-01
3.33E-01
6.17E-01
1.20E+00
2.42E+00
5.39 E+00
1.09 E+01
2.49E+01
4.83E+01
Season
Fall
843000
28
7.88
1.47E+00
2.49E-01
2.91 E-01
2.91 E-01
2.95E-01
4.83E-01
1.04E+00
2.15E+00
2.99 E+00
4.65 E+00
5.39E+00
5.39E+00
Spring
837000
78
10.26
1.37E+00
1.59E-01
1.73E-01
1.96E-01
2.51 E-01
5.10E-01
9.81 E-01
1.61 E+00
2.95 E+00
5.29 E+00
6.68E+00
7.02E+00
Summer
1398000
44
17.51
2.47E+00
4.72E-01
1.86E-01
2.75E-01
4.04E-01
6.17E-01
1.28E+00
3.14E+00
7.26 E+00
1.09 E+01
1.30E+01
1.30E+01
Winter
1496000
83
16.22
4.10E+00
7.91 E-01
7.14E-02
2.96E-01
3.33E-01
7.74E-01
1.51 E+00
3.74E+00
1.11 E+01
1.85 E+01
4.83E+01
4.83E+01
Jrbanization
Central City
1494000
59
12.41
1.99E+00
4.24E-01
7.14E-02
2.35E-01
3.42E-01
5.26E-01
8.63E-01
2.04 E+00
4.63 E+00
9.52E+00
1.93E+01
1.93E+01
Nonmetropolitan
474000
32
7.76
2.24E+00
5.25E-01
1.84E-01
2.76E-01
4.24E-01
6.25E-01
7.68E-01
2.64 E+00
4.25 E+00
1.09 E+01
1.09E+01
1.09E+01
Suburban
2606000
142
14.54
3.04E+00
4.63E-01
1.83E-01
2.75E-01
3.14E-01
7.10E-01
1.39 E+00
3.14E+00
5.81 E+00
1.03 E+01
3.22E+01
4.83E+01
Response to Questionnaire
Households who garden
4170000
207
32.77
2.76E+00
3.39E-01
1.00E-01
2.75E-01
3.14E-01
6.29E-01
1.20 E+00
2.54 E+00
5.81 E+00
1.09 E+01
2.49E+01
4.83E+01
Households who farm
795000
35
50.13
1.85E+00
2.59E-01
2.75E-01
2.76E-01
5.98E-01
7.10E-01
1.26 E+00
2.50 E+00
4.63 E+00
5.00 E+00
6.81 E+00
6.81 E+00
MOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc 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 Homeg
rown Vegetables ("g/kg-day")
- All Regions Combined
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
34392000
1855
18.29
2.08E+00
6.76E-02
4.79E-03
1.10E-01
1.80E-01
4.47E-01
1.11 E+00
2.47E+00
5.20E+00
7.54E+00
1.55E+01
2.70E+01
Age
01-02
951000
53
16.69
5.20E+00
8.47E-01
2.32E-02
2.45E-01
3.82E-01
1.23E+00
3.27E+00
5.83E+00
1.31E+01
1.96E+01
2.70E+01
2.70E+01
03-05
1235000
76
15.24
2.46E+00
2.79E-01
0.00E+00
4.94E-02
3.94E-01
7.13E-01
1.25E+00
3.91 E+00
6.35E+00
7.74E+00
1.06E+01
1.28E+01
06-11
3024000
171
18.10
2.02E+00
2.54E-01
5.95E-03
1.00E-01
1.60E-01
4.00E-01
8.86E-01
2.21 E+00
4.64E+00
6.16E+00
1.76E+01
2.36E+01
12-19
3293000
183
16.07
1.48E+00
1.35E-01
0.00E+00
6.46E-02
1.45E-01
3.22E-01
8.09E-01
1.83E+00
3.71 E+00
6.03E+00
7.71 E+00
9.04E+00
20-39
8593000
437
13.95
1.47E+00
9.59E-02
1.69E-02
7.77E-02
1.57E-01
2.73E-01
7.61 E-01
1.91 E+00
3.44E+00
4.92E+00
1.05E+01
2.06E+01
40-69
12828000
700
22.62
2.07E+00
1.02E-01
5.13E-03
1.19E-01
2.14E-01
5.26E-01
1.18E+00
2.47E+00
5.12E+00
6.94E+00
1.49E+01
2.29E+01
70 +
4002000
211
25.20
2.51 E+00
1.94E-01
5.21 E-03
1.51 E-01
2.39E-01
5.81 E-01
1.37E+00
3.69E+00
6.35E+00
8.20E+00
1.25E+01
1.55E+01
Seasons
Fall
11026000
394
23.13
1.88E+00
1.28E-01
4.98E-02
1.13E-01
1.80E-01
4.13E-01
9.83E-01
2.11 E+00
4.88E+00
6.94E+00
1.25E+01
1.89E+01
Spring
6540000
661
14.17
1.36E+00
7.23E-02
2.44E-03
4.47E-02
1.35E-01
3.21 E-01
7.04E-01
1.63E+00
3.37E+00
5.21 E+00
8.35E+00
2.36E+01
Summer
11081000
375
24.36
2.86E+00
1.93E-01
6.93E-02
1.57E-01
2.24E-01
7.12E-01
1.62E+00
3.44E+00
6.99E+00
9.75E+00
1.87E+01
2.70E+01
Winter
5745000
425
11.79
1.79E+00
1.14E-01
3.73E-03
4.49E-02
1.56E-01
4.69E-01
1.05E+00
2.27E+00
3.85E+00
6.01 E+00
1.06E+01
2.06E+01
Urbanizations
Central City
6183000
228
10.97
1.40E+00
1.23E-01
1.01E-02
6.59E-02
1.50E-01
3.00E-01
7.50E-01
1.67E+00
3.83E+00
4.67E+00
9.96E+00
1.66E+01
Nonmetropolitan
13808000
878
30.67
2.68E+00
1.19E-01
2.12E-02
1.58E-01
2.58E-01
5.99E-01
1.45E+00
3.27E+00
6.35E+00
9.33E+00
1.75E+01
2.70E+01
Suburban
14341000
747
16.56
1.82E+00
9.12E-02
3.34E-03
1.10E-01
1.63E-01
3.94E-01
9.63E-01
2.18E+00
4.32E+00
6.78E+00
1.25E+01
2.06E+01
Race
Black
1872000
111
8.61
1.78E+00
2.33E-01
0.00E+00
7.77E-02
1.39E-01
4.38E-01
9.32E-01
2.06E+00
4.68E+00
5.70E+00
8.20E+00
1.89E+01
White
31917000
1714
20.26
2.10E+00
7.09E-02
7.34E-03
1.13E-01
1.84E-01
4.54E-01
1.12E+00
2.48E+00
5.18E+00
7.68E+00
1.55E+01
2.70E+01
Response to Questionnaire
Households who garden
30217000
1643
44.34
2.17E+00
7.09E-02
5.21 E-03
1.11 E-01
1.85E-01
4.84E-01
1.18E+00
2.68E+00
5.35E+00
7.72E+00
1.55E+01
2.36E+01
Households who farm
4319000
262
58.93
3.29E+00
2.51 E-01
0.00E+00
1.61 E-01
2.92E-01
8.46E-01
1.67E+00
3.61 E+00
8.88E+00
1.18E+01
1.76E+01
2.36E+01
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-88 NFCS
-------
Table 13-14
Cnnsumer
Only Intake of Homegrown
Vegetables (g/kg-day) -
Northeast
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
4883000
236
11.86
1.78E+00
1.68E-01
2.18E-03
8.27E-02
1.43E-01
2.80E-01
7.47E-01
1.89E+00
6.03 E+00
7.82E+00
1.27E+01
1.49E+01
Seasons
Fall
1396000
41
14.87
1.49E+00
4.06E-01
8.27E-02
1.34E-01
1.74E-01
2.69E-01
5.81 E-01
1.17E+00
6.64 E+00
9.97E+00
1.02E+01
1.02E+01
Spring
1204000
102
11.43
8.18E-01
1.07E-01
0.00E+00
2.89E-03
4.47E-02
1.72E-01
4.55E-01
9.52E-01
2.26 E+00
3.11 E+00
6.52E+00
6.78E+00
Summer
1544000
48
16.32
2.83E+00
4.67E-01
1.11 E-01
1.45E-01
1.59E-01
7.38E-01
1.29E+00
3.63E+00
7.82E+00
9.75E+00
1.49E+01
1.49E+01
Winter
739000
45
6.27
1.67E+00
2.74E-01
3.23E-03
4.23E-03
9.15E-02
2.56E-01
1.25E+00
2.77E+00
3.63 E+00
6.10E+00
8.44E+00
8.44E+00
Urbanizations
Central City
380000
14
3.93
*
*
*
*
*
*
*
*
*
Nonmetropolitan
787000
48
14.25
3.05E+00
5.41 E-01
0.00E+00
4.68E-02
1.14E-01
2.02E-01
2.18E+00
4.61 E+00
9.04 E+00
1.27E+01
1.49E+01
1.49E+01
Suburban
3716000
174
14.30
1.59E+00
1.74E-01
2.44E-03
8.27E-02
1.42E-01
2.75E-01
7.18E-01
1.64E+00
4.82E+00
6.80 E+00
1.02E+01
1.02E+01
Response to Questionnaire
Households who garden
4381000
211
35.05
1.92E+00
1.84E-01
2.18E-03
8.27E-02
1.42E-01
3.10E-01
8.83E-01
2.18E+00
6.16E+00
7.82E+00
1.27E+01
1.49E+01
Households who farm
352000
19
42.41
*
*
*
*
*
*
*
*
*
* Intake data not provided for subpopulations for which there were less than 20 observations
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-88 NFCS
-------
Table 13-15.
Consumer
Only Intake of
Homegrown
Vegetables (g/kg-dav) -
Midwest
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
12160000
699
26.21
2.26E+00
1.20E-01
1.59E-02
7.77E-02
1.80E-01
4.88E-01
1.15E+00
2.58E+00
5.64E+00
7.74E+00
1.75E+01
2.36E+01
Seasons
Fall
4914000
180
34.13
1.84E+00
1.76E-01
1.01E-02
6.51 E-02
1.60E-01
4.16E-01
1.03E+00
2.10E+00
5.27E+00
6.88E+00
1.31E+01
1.31E+01
Spring
2048000
246
19.22
1.65E+00
1.49E-01
6.04E-02
1.53E-01
2.21 E-01
4.59E-01
9.13E-01
1.72E+00
4.49E+00
5.83E+00
1.28E+01
2.36E+01
Summer
3319000
115
32.45
3.38E+00
3.87E-01
1.05E-01
1.62E-01
3.02E-01
8.47E-01
2.07E+00
3.94E+00
7.72E+00
1.40E+01
1.96E+01
2.29E+01
Winter
1879000
158
16.91
2.05E+00
2.64E-01
2.41 E-03
2.14E-02
6.59E-02
3.62E-01
8.77E-01
2.13E+00
5.32E+00
7.83E+00
1.67E+01
2.06E+01
Urbanizations
Central City
3177000
113
18.26
1.36E+00
1.91E-01
0.00E+00
6.05E-02
1.10E-01
2.45E-01
7.13E-01
1.67E+00
3.94E+00
5.50E+00
9.96E+00
1.66E+01
Nonmetropolitan
5344000
379
37.38
2.73E+00
1.86E-01
2.12E-02
1.13E-01
2.61 E-01
5.98E-01
1.31E+00
3.15E+00
7.19E+00
1.06E+01
1.75E+01
2.36E+01
Suburban
3639000
207
24.75
2.35E+00
2.16E-01
3.26E-02
1.54E-01
2.22E-01
6.36E-01
1.39E+00
2.75E+00
4.87E+00
7.18E+00
1.96E+01
2.06E+01
Response to Questionnaire
Households who garden
10927000
632
48.89
2.33E+00
1.27E-01
1.59E-02
1.04E-01
1.76E-01
5.03E-01
1.18E+00
2.74E+00
5.81 E+00
7.75E+00
1.67E+01
2.36E+01
Households who farm
1401000
104
52.26
3.97E+00
4.31 E-01
1.40E-01
3.35E-01
5.51 E-01
8.67E-01
2.18E+00
5.24E+00
1.06E+01
1.44E+01
1.75E+01
2.36E+01
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-88 NFCS
-------
Table 13-16. Consumer Only Intake of Homegrown Vegetables (g/kg-day)
South
Population
Nc
Nc
%
Group
wgtd
unwqtc
Consuming
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
1125400
0
618
17.49
2.19E+00
1.21E-01
2.92E-02
1.60E-01
2.41 E-01
5.63E-01
1.24E+00
2.69E+00
4.92E+00
7.43E+00
1.70E+01
2.70E+01
Seasons
Fall
2875000
101
21.80
2.07E+00
2.82E-01
9.59E-02
1.13E-01
1.91E-01
5.24E-01
1.14E+00
2.69E+00
4.48E+00
6.02E+00
1.55E+01
1.89E+01
Spring
2096000
214
12.47
1.55E+00
1.13E-01
1.41E-02
9.21 E-02
2.61 E-01
5.33E-01
9.35E-01
2.07E+00
3.58E+00
4.81 E+00
8.35E+00
1.03E+01
Summer
4273000
151
24.07
2.73E+00
3.16E-01
1.10E-01
1.72E-01
2.50E-01
6.15E-01
1.54E+00
3.15E+00
5.99E+00
9.70E+00
2.36E+01
2.70E+01
Winter
2010000
152
12.12
1.88E+00
1.37E-01
3.03E-03
1.63E-01
3.53E-01
6.40E-01
1.37E+00
2.69E+00
3.79E+00
5.35E+00
7.47E+00
8.36E+00
Urbanizations
Central City
1144000
45
6.63
1.10E+00
1.62E-01
1.10E-02
9.59E-02
1.50E-01
2.63E-01
6.15E-01
1.37E+00
2.79E+00
3.70E+00
4.21 E+00
4.58E+00
Nonmetropolitan
6565000
386
34.37
2.78E+00
1.84E-01
5.08E-02
2.23E-01
3.50E-01
7.12E-01
1.66E+00
3.31 E+00
5.99E+00
9.56E+00
1.89E+01
2.70E+01
Suburban
3545000
187
12.67
1.44E+00
1.13E-01
0.00E+00
1.13E-01
1.99E-01
3.96E-01
9.33E-01
1.72E+00
3.61 E+00
5.26E+00
8.20E+00
8.20E+00
Response to Questionnaire
Households who garden
9447000
522
46.04
2.27E+00
1.22E-01
3.46E-02
1.61E-01
2.62E-01
6.10E-01
1.37E+00
3.02E+00
5.18E+00
7.43E+00
1.55E+01
2.36E+01
Households who farm
1609000
91
72.09
3.34E+00
4.57E-01
0.00E+00
1.32E-01
2.33E-01
1.03E+00
1.72E+00
3.15E+00
9.56E+00
1.18E+01
2.36E+01
2.36E+01
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd =
Source: Based on EPA's analyses of the 1987-88 NFCS
unweighted number of consumers in survey.
-------
Table 13-17. Consumer Only Intake of Homegrown Vegetables (g/kg-day)
West
Population
Nc
Nc
%
Group
wgtd
unwgt
d Consuming
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
6035000
300
16.73
1.81 E+00
1.38E-01
7.35E-03
9.85E-02
1.66E-01
3.79E-01
9.01 E-01
2.21 E+00
4.64E+00
6.21 E+00
1.14E+01
1.55E+01
Seasons
Fall
1841000
72
17.21
2.01 E+00
2.93E-01
9.83E-02
1.50E-01
2.04E-01
4.81 E-01
1.21 E+00
2.21 E+00
4.85E+00
7.72E+00
1.25E+01
1.25E+01
Spring
1192000
99
14.61
1.06 E+00
1.74E-01
3.31 E-03
7.35E-03
4.66E-02
1.95E-01
3.56E-01
9.08E-01
3.37E+00
5.54E+00
8.60E+00
8.60E+00
Summer
1885000
59
23.60
2.39 E+00
3.71 E-01
6.93E-02
1.04E-01
2.46E-01
5.45E-01
1.37E+00
3.23E+00
4.67E+00
8.36E+00
1.55E+01
1.55E+01
Winter
1117000
70
12.11
1.28E+00
1.72E-01
1.29E-02
1.52E-01
1.99E-01
4.83E-01
7.65E-01
1.43E+00
2.81 E+00
5.12E+00
7.57E+00
7.98E+00
Urbanizations
Central City
1482000
56
12.31
1.80 E+00
2.76E-01
2.58E-02
7.39E-02
1.57E-01
4.81 E-01
1.10E+00
2.95E+00
4.64E+00
4.85E+00
1.14E+01
1.14E+01
Nonmetropolitan
1112000
65
18.21
1.52E+00
2.24E-01
3.42E-03
9.80E-03
2.04E-01
2.69E-01
6.75E-01
2.13E+00
4.13E+00
5.12E+00
8.16E+00
8.16E+00
Suburban
3441000
179
19.20
1.90 E+00
1.98E-01
1.29E-02
1.04E-01
1.52E-01
3.94E-01
9.32E-01
2.20E+00
4.63E+00
7.98E+00
1.25E+01
1.55E+01
Response to Questionnaire
Households who garden
5402000
276
42.45
1.91 E+00
1.04E-03
8.53E-03
1.04E-01
1.66E-01
4.33E-01
1.07E+00
2.37E+00
4.67E+00
6.21 E+00
1.25E+01
1.55E+01
Households who farm
957000
48
60.34
2.73E+00
3.32E-03
1.17E-01
4.14E-01
4.69E-01
7.65E-01
1.42E+00
3.27E+00
6.94E+00
1.09E+01
1.55E+01
1.55E+01
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-88
NFCS
-------
Table 13-18. Consumer Only
Intake of Home Produced Meats (g/kg-day)
- All Regions Combined
Population
Nc
Nc
%
Grouo
watd u
nwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
9257000
569
4.92
2.21 E+00
1.07E-01
1.21 E-01
2.37E-01
3.74E-01
6.60E-01
1.39E+00
2.89E+00
4.89E+00
6.78E+00
1.40E+01
2.32E+01
Age
01-02
276000
22
4.84
3.65E+00
6.10E-01
3.85E-01
9.49E-01
9.49E-01
1.19E+00
2.66E+00
4.72E+00
8.68E+00
1.00E+01
1.15E+01
1.15E+01
03-05
396000
26
4.89
3.61 E+00
5.09E-01
8.01 E-01
8.01 E-01
1.51 E+00
2.17E+00
2.82E+00
3.72E+00
7.84E+00
9.13E+00
1.30E+01
1.30E+01
06-11
1064000
65
6.37
3.65 E+00
4.51 E-01
3.72E-01
6.52E-01
7.21 E-01
1.28E+00
2.09E+00
4.71 E+00
8.00E+00
1.40E+01
1.53E+01
1.53E+01
12-19
1272000
78
6.21
1.70E+00
1.68E-01
1.90E-01
3.20E-01
4.70E-01
6.23E-01
1.23E+00
2.35E+00
3.66E+00
4.34E+00
6.78E+00
7.51 E+00
20-39
2732000
158
4.43
1.82E+00
1.53E-01
1.23E-01
1.85E-01
2.95E-01
5.28E-01
1.11 E+00
2.65E+00
4.52E+00
6.23E+00
9.17E+00
1.09E+01
40-69
2872000
179
5.06
1.72E+00
1.11 E-01
1.81E-02
2.12E-01
3.43E-01
5.84E-01
1.17E+00
2.38E+00
3.67E+00
5.16E+00
5.90E+00
7.46E+00
70 +
441000
28
2.78
1.39 E+00
2.34E-01
9.26E-02
9.26E-02
1.25E-01
5.47E-01
1.01 E+00
1.81 E+00
2.82E+00
3.48E+00
7.41 E+00
7.41 E+00
Seasons
Fall
2852000
107
5.98
1.57E+00
1.39E-01
1.23E-01
2.10E-01
3.52E-01
5.21 E-01
1.11 E+00
2.27E+00
3.19E+00
4.41 E+00
6.78E+00
7.84E+00
Spring
1726000
197
3.74
2.37E+00
1.52E-01
2.44E-01
3.20E-01
4.46E-01
7.76E-01
1.69E+00
3.48E+00
5.00E+00
6.67E+00
1.01E+01
1.30E+01
Summer
2368000
89
5.21
3.10E+00
3.82E-01
1.81E-02
1.85E-01
4.06E-01
8.52E-01
1.77E+00
4.34E+00
7.01 E+00
1.05E+01
2.23E+01
2.23E+01
Winter
2311000
176
4.74
1.98 E+00
1.74E-01
1.35E-01
2.37E-01
3.67E-01
6.48E-01
1.33E+00
2.43E+00
3.96E+00
6.40E+00
1.09E+01
2.32E+01
Urbanizations
Central City
736000
28
1.31
1.15E+00
1.83E-01
1.82E-01
1.85E-01
2.10E-01
4.42E-01
7.21 E-01
1.58E+00
2.69E+00
3.40E+00
3.64E+00
3.64E+00
Nonmetropolitan
4932000
315
10.95
2.70E+00
1.76E-01
1.23E-01
2.63E-01
4.06E-01
7.49E-01
1.63E+00
3.41 E+00
6.06E+00
8.47E+00
1.53E+01
2.32E+01
Suburban
3589000
226
4.15
1.77 E+00
1.03E-01
2.90E-02
2.87E-01
3.67E-01
6.80E-01
1.33E+00
2.49E+00
3.66E+00
4.71 E+00
7.20E+00
1.01E+01
Race
Black
128000
6
0.59
*
*
*
*
*
*
*
*
*
*
White
8995000
556
5.71
2.26 E+00
1.09E-01
9.26E-02
2.57E-01
3.86E-01
6.80E-01
1.41 E+00
2.91 E+00
5.00E+00
7.01 E+00
1.40E+01
2.32E+01
Response to Questionnaire
Households who
raise animals
5256000
343
52.06
2.80 E+00
1.45E-01
2.12E-01
3.86E-01
6.23E-01
1.03E+00
1.94E+00
3.49E+00
5.90E+00
7.84E+00
1.40E+01
2.32E+01
Households who farm
3842000
243
52.42
2.86 E+00
1.85E-01
1.97E-01
4.45E-01
5.98E-01
8.94E-01
1.84E+00
3.64E+00
6.09E+00
8.00E+00
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
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-88 NFCS
-------
Table 13-19. Consume
Only Intake of Home Produced Meats
(g/kg-day) -
Northeast
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
1113000
52
2.70
1.46E+00
2.10E-01
2.92E-01
3.40E-01
3.52E-01
6.44E-01
8.94E-01
1.87E+00
2.68 E+00
2.89E+00
1.09E+01
1.09E+01
Seasons
Fall
569000
18
6.06
*
*
*
*
*
*
*
Spring
66000
8
0.63
*
*
*
*
*
*
*
Summer
176000
6
1.86
*
*
*
*
*
*
*
Winter
302000
20
2.56
2.02E+00
5.56E-01
2.92E-01
3.14E-01
4.30E-01
6.19E-01
1.11 E+00
2.38 E+00
2.93 E+00
7.46E+00
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+00
1.53E-01
2.92E-01
3.52E-01
4.30E-01
6.80E-01
1.39 E+00
2.34 E+00
2.68 E+00
2.89E+00
3.61 E+00
3.61 E+00
Response to Questionnaire
Households who raise animals
509000
25
43.21
2.03E+00
3.85E-01
6.19E-01
6.46E-01
6.46E-01
8.78E-01
1.62 E+00
2.38 E+00
2.93 E+00
7.46 E+00
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
Nc wgtd = weighted number of consumers; Nc 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 Nc
Nc
%
Grouo watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total 3974000
266
8.57
2.55E+00
1.81E-01
1.25E-01
2.57E-01
3.85E-01
6.60E-01
1.40E+00
3.39 E+00
5.75E+00
7.20E+00
1.53E+01
2.23E+01
Seasons
Fall 1261000
49
8.76
1.76E+00
2.31 E-01
2.10E-01
2.57E-01
3.72E-01
4.95E-01
1.19E+00
2.66 E+00
3.49 E+00
6.06E+00
6.78E+00
6.78E+00
Spring 940000
116
8.82
2.58E+00
2.24E-01
2.44E-01
3.11 E-01
4.08E-01
7.33E-01
1.98E+00
3.67E+00
5.14E+00
7.79E+00
1.15E+01
1.30E+01
Summer 930000
38
9.09
4.10E+00
7.45E-01
9.26E-02
1.25E-01
5.78E-01
8.93E-01
2.87E+00
5.42E+00
8.93 E+00
1.53E+01
2.23E+01
2.23E+01
Winter 843000
63
7.59
2.00E+00
2.41 E-01
1.21 E-01
2.37E-01
3.28E-01
6.48E-01
1.36E+00
2.69 E+00
4.11 E+00
5.30E+00
8.10E+00
1.22E+01
Urbanizations
Central City 460000
18
2.64
*
*
*
*
*
Nonmetropolitan 2477000
175
17.33
3.15E+00
2.58E-01
9.26E-02
2.95E-01
4.25E-01
8.16E-01
2.38E+00
4.34 E+00
6.15E+00
9.17E+00
1.53E+01
2.23E+01
Suburban 1037000
73
7.05
1.75E+00
1.99E-01
2.87E-01
3.65E-01
4.08E-01
6.60E-01
1.11 E+00
2.03 E+00
4.16E+00
5.39E+00
7.20E+00
1.01E+01
Response to Questionnaire
Households who raise animals 2165000
165
57.86
3.20E+00
2.23E-01
2.56E-01
3.86E-01
5.78E-01
1.07E+00
2.56E+00
4.42E+00
6.06 E+00
9.13E+00
1.53E+01
1.53E+01
Households who farm 1483000
108
55.32
3.32E+00
2.91 E-01
3.65E-01
5.43E-01
5.89E-01
1.07E+00
2.75E+00
4.71 E+00
6.78E+00
9.17E+00
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
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-88 NFCS
-------
Table 13-21. Consumer Only Intake of Home Produced Meats
(g/kg-dav)
South
Population Nc
Nc
%
Grouo watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total 2355000
146
3.66
2.24E+00
1.94E-01
1.81E-02
1.56E-01
2.97E-01
7.21 E-01
1.53E+00
3.07E+00
5.07E+00
6.71 E+00
1.40E+01
1.40E+01
Seasons
Fall 758000
28
5.75
1.81E+00
2.87E-01
1.23E-01
1.56E-01
1.90E-01
8.19E-01
1.53E+00
2.38 E+00
3.19E+00
4.41 E+00
7.84E+00
7.84E+00
Spring 511000
53
3.04
2.33E+00
2.66E-01
1.93E-01
2.97E-01
4.99E-01
7.52E-01
1.80E+00
2.82E+00
5.16E+00
6.71 E+00
7.51 E+00
7.51 E+00
Summer 522000
18
2.94
*
*
*
*
*
*
Winter 564000
47
3.40
1.80E+00
2.45E-01
3.70E-02
1.97E-01
2.51 E-01
7.16E-01
1.40E+00
2.17E+00
3.55 E+00
4.58 E+00
8.47E+00
8.47E+00
Urbanizations
Central City 40000
1
0.23
*
*
*
*
*
*
Nonmetropolitan 1687000
97
8.83
2.45E+00
2.59E-01
1.23E-01
1.90E-01
4.02E-01
7.77E-01
1.61 E+00
3.19E+00
6.09 E+00
7.84 E+00
1.40E+01
1.40E+01
Suburban 628000
48
2.24
1.79E+00
2.30E-01
1.81E-02
2.90E-02
3.70E-02
6.28E-01
1.40E+00
2.31 E+00
4.56 E+00
4.61 E+00
6.40E+00
6.40E+00
Response to Questionnaire
Households who raise animals 1222000
74
46.95
3.16E+00
3.16E-01
2.63E-01
6.67E-01
8.35E-01
1.34E+00
2.11 E+00
3.79E+00
6.67E+00
8.47E+00
1.40E+01
1.40E+01
Households who farm 1228000
72
55.02
2.85E+00
3.24E-01
1.95E-01
4.99E-01
5.98E-01
1.01E+00
1.93E+00
3.48 E+00
6.23 E+00
8.47E+00
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
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-88 NFCS
-------
Table 13-22. Consumer Only Intake of Home Produced Meats
(g/kg-day)
West
Population Nc
Nc
%
Grouo watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total 1815000
105
5.03
1.89E+00
2.12E-01
1.52E-01
2.25E-01
3.90E-01
6.58E-01
1.42E+00
2.49E+00
3.66E+00
4.71 E+00
8.00E+00
2.32E+01
Seasons
Fall 264000
12
2.47
*
*
*
*
*
*
Spring 209000
20
2.56
1.86E+00
2.27E-01
2.99E-01
4.25E-01
8.70E-01
1.22E+00
1.56E+00
2.43E+00
3.48E+00
4.20E+00
4.20E+00
4.20E+00
Summer 740000
27
9.27
2.20E+00
3.18E-01
1.85E-01
4.06E-01
5.35E-01
1.07E+00
1.69E+00
3.27E+00
4.44E+00
4.71 E+00
8.00E+00
8.00E+00
Winter 602000
46
6.53
2.11E+00
4.55E-01
1.35E-01
3.56E-01
4.28E-01
6.72E-01
1.19E+00
2.35E+00
3.64E+00
7.02E+00
2.32E+01
2.32E+01
Urbanizations
Central City 236000
9
1.96
*
*
*
*
*
*
Nonmetropolitan 377000
26
6.17
2.10E+00
7.00E-01
3.30E-01
3.30E-01
4.06E-01
6.72E-01
1.19E+00
1.77E+00
3.72E+00
4.97E+00
2.32E+01
2.32E+01
Suburban 1202000
70
6.71
1.95E+00
1.99E-01
1.52E-01
2.25E-01
3.67E-01
7.80E-01
1.52E+00
2.71 E+00
4.20E+00
4.71 E+00
8.00E+00
8.00E+00
Response to Questionnaire
Households who raise animals 1360000
79
52.84
2.12E+00
2.65E-01
1.52E-01
2.25E-01
3.90E-01
8.15E-01
1.56E+00
2.71 E+00
4.20E+00
4.97E+00
8.00E+00
2.32E+01
Households who farm 758000
48
47.79
2.41 E+00
4.26E-01
1.35E-01
3.30E-01
4.67E-01
7.85E-01
1.55E+00
2.91 E+00
4.71 E+00
7.02E+00
2.32E+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
Nc wgtd = weighted number of consumers; Nc 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
:ish (g/kg-day)
All Regions Combined
Population
Nc
Nc %
Grouo
watd u
nwatd Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
3914000
239
2.08
2.07E+00
2.38E-01
8.16E-02
9.11E-02
1.95E-01
2.28E-01
4.31 E-01
9.97E-01
2.17E+00
4.68E+00
7.83E+00
1.55E+01
Age
01-02
82000
6
1.44
*
*
*
*
*
*
*
*
*
*
*
*
03-05
142000
11
1.75
*
*
*
*
*
*
*
*
*
*
*
*
06-11
382000
29
2.29
2.78E+00
8.40E-01
1.60E-01
1.60E-01
1.84E-01
2.28E-01
5.47E-01
1.03E+00
3.67E+00
7.05E+00
7.85E+00
2.53E+01
12-19
346000
21
1.69
1.52E+00
4.07E-01
1.95E-01
1.95E-01
1.95E-01
1.95E-01
3.11 E-01
9.84E-01
1.79E+00
4.68E+00
6.67E+00
8.44E+00
20-39
962000
59
1.56
1.91 E+00
3.34E-01
8.16E-02
8.16E-02
9.11E-02
1.18E-01
4.43E-01
1.06E+00
2.18E+00
4.46E+00
9.57E+00
1.30E+01
40-69
1524000
86
2.69
1.79E+00
2.56E-01
9.47E-02
9.47E-02
2.10E-01
2.75E-01
3.45E-01
9.85E-01
1.99E+00
4.43E+00
6.56E+00
1.08E+01
70 +
450000
24
2.83
1.22 E+00
2.30E-01
9.88E-02
9.88E-02
2.33E-01
2.33E-01
5.68E-01
7.64E-01
1.56E+00
3.73E+00
3.73E+00
5.12E+00
Season
Fall
1220000
45
2.56
1.31 E+00
2.16E-01
1.84E-01
1.84E-01
1.96E-01
2.10E-01
3.18E-01
9.16E-01
1.79E+00
2.64E+00
3.73E+00
6.56E+00
Spring
1112000
114
2.41
3.08 E+00
5.55E-01
9.88E-02
1.16E-01
3.08E-01
3.40E-01
5.59E-01
1.27E+00
2.64E+00
6.68E+00
1.08E+01
3.73E+01
Summer
911000
29
2.00
1.88 E+00
4.24E-01
8.16E-02
8.16E-02
9.11E-02
2.04E-01
3.01 E-01
7.64E-01
3.19E+00
4.43E+00
5.65E+00
9.57E+00
Winter
671000
51
1.38
2.05 E+00
3.68E-01
9.47E-02
9.47E-02
1.11 E-01
1.60E-01
5.10E-01
1.06E+00
2.09E+00
5.89E+00
7.85E+00
1.31E+01
Urbanization
Central City
999000
46
1.77
1.79E+00
3.40E-01
9.47E-02
9.47E-02
1.60E-01
2.84E-01
6.08E-01
1.07E+00
1.85E+00
3.73E+00
9.57E+00
9.57E+00
Nonmetropolitan
1174000
94
2.61
3.15E+00
5.74E-01
9.88E-02
1.16E-01
3.10E-01
3.62E-01
5.68E-01
1.88E+00
3.86E+00
6.52E+00
7.83E+00
3.73E+01
Suburban
1741000
99
2.01
1.50 E+00
2.30E-01
8.16E-02
8.16E-02
1.84E-01
2.01 E-01
2.86E-01
5.87E-01
1.38E+00
4.37E+00
7.05E+00
1.08E+01
Race
Black
593000
41
2.73
1.81 E+00
3.74E-01
1.84E-01
1.84E-01
2.01 E-01
2.86E-01
3.18E-01
9.84E-01
2.17E+00
4.68E+00
9.57E+00
9.57E+00
White
3228000
188
2.05
2.07E+00
2.81 E-01
8.16E-02
8.16E-02
1.60E-01
2.27E-01
3.93E-01
9.97E-01
2.16E+00
4.99E+00
6.68E+00
1.61E+01
Response to Questionnaire
Households who fish
3553000
220
8.94
2.22 E+00
2.58E-01
8.16E-02
8.16E-02
1.84E-01
2.27E-01
4.66E-01
1.09E+00
2.23E+00
5.61 E+00
7.85E+00
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
Nc wgtd = weighted number of consumers; Nc unwgtd
Source: Based on EPA's analyses of the 1987-88 NFCS
= unweighted number of consumers in survey.
-------
Table 13-24. Consumer Only Intake of Home Caught
Fish (q/kq-dav) - Northeast
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
Mean SE P1
P5
P10 P25 P50
P75
P90
P95
P99
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
Nc wgtd = weighted number of consumers; Nc 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
Caught Fish
(g/kg-dav)
Midwest
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
1113000
71
2.40
2.13E+00
4.19E-01
8.16E-02
8.16E-02
1.96E-01
2.27E-01
4.71 E-01
1.03E+00
1.95E+00
6.10E+00
6.56E+00
1.61E+01
Season
Fall
362000
13
2.51
*
*
*
*
*
*
Spring
224000
27
2.10
3.45E+00
1.22E+00
1.16E-01
1.16E-01
1.18E-01
3.10E-01
4.87E-01
8.21 E-01
1.67E+00
1.55E+01
1.61E+01
2.53E+01
Summer
264000
8
2.58
*
*
*
*
*
*
Winter
263000
23
2.37
2.38E+00
5.33E-01
5.10E-01
5.10E-01
5.10E-01
5.48E-01
1.03E+00
1.56E+00
2.13E+00
5.89E+00
6.10E+00
1.31E+01
Urbanization
Central City
190000
9
1.09
*
*
*
*
*
Nonmetropolitan
501000
40
3.50
3.42E+00
7.17E-01
1.16E-01
1.16E-01
3.30E-01
4.66E-01
5.33E-01
1.88E+00
5.65E+00
6.56E+00
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
3.01 E-01
5.48E-01
1.28E+00
2.09E+00
2.78E+00
3.73E+00
Response to Questionnaire
Households who fish
956000
60
7.57
2.35E+00
4.85E-01
8.16E-02
8.16E-02
1.18E-01
2.27E-01
4.66E-01
1.12E+00
2.16E+00
6.52E+00
6.56E+00
2.53E+01
* Intake data not provided for subpopulations for which there were less than 20 observations
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd =
Source: Based on EPA's analyses of the 1987-88 NFCS
unweighted number of consumers in survey.
-------
Table 13-26. Consumer Only
Intake of Home
Caught Fish
(g/kg-day) -
South
Population Nc
Nc
%
Grouo watd
unwatc
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total 1440000
101
2.24
2.74E+00
4.76E-01
9.47E-02
9.47E-02
2.04E-01
2.86E-01
5.07E-01
1.48E+00
3.37E+00
5.61 E+00
8.44E+00
3.73E+01
Season
Fall 274000
11
2.08
*
*
*
*
*
*
*
*
Spring 538000
58
3.20
4.00E+00
9.42E-01
3.08E-01
3.08E-01
3.87E-01
4.46E-01
8.74E-01
1.94E+00
3.71 E+00
8.33E+00
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+00
1.06E+00
2.85E-01
2.85E-01
3.38E-01
5.07E-01
1.12E+00
1.94E+00
3.19E+00
4.43E+00
6.67E+00
4.52E+01
Suburban 609000
44
2.18
2.73E+00
4.98E-01
2.04E-01
2.04E-01
2.75E-01
2.86E-01
4.26E-01
1.08E+00
4.37E+00
8.33E+00
1.04E+01
1.30E+01
Response to Questionnaire
Households who fish 1280000
95
9.42
3.00E+00
5.14E-01
9.47E-02
9.47E-02
2.04E-01
2.80E-01
7.06E-01
1.93E+00
3.67E+00
6.68E+00
8.44E+00
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
Nc wgtd = weighted number of consumers; Nc 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
(q/kq-dav) -
West
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
1027000
55
2.85
1.57E+00
2.72E-01
9.88E-02
1.60E-01
2.01 E-01
2.38E-01
4.43E-01
8.38E-01
1.79E+00
3.73E+00
5.67E+00
9.57E+00
Season
Fall
449000
17
4.20
*
*
*
*
*
*
*
*
Spring
336000
27
4.12
1.35E+00
2.94E-01
9.88E-02
9.88E-02
2.38E-01
3.27E-01
4.43E-01
6.08E-01
1.68E+00
4.68E+00
5.61 E+00
5.67E+00
Summer
139000
4
1.74
*
*
*
*
*
*
*
*
Winter
103000
7
1.12
*
*
*
*
*
*
*
*
Urbanization
Central City
528000
21
4.38
2.03E+00
5.25E-01
3.27E-01
3.27E-01
4.33E-01
5.29E-01
7.12E-01
1.45E+00
1.85E+00
3.73E+00
9.57E+00
9.57E+00
Nonmetropolitan
81000
9
1.33
*
*
*
*
*
*
*
*
Suburban
418000
25
2.33
1.09E+00
2.49E-01
1.84E-01
1.84E-01
2.01 E-01
2.10E-01
3.08E-01
5.87E-01
1.21E+00
2.90E+00
4.68E+00
5.61 E+00
Response to Questionnaire
Households who fish
983000
53
12.99
1.63E+00
2.81 E-01
9.88E-02
1.60E-01
2.01 E-01
2.18E-01
5.47E-01
9.64E-01
1.79E+00
3.73E+00
5.67E+00
9.57E+00
* Intake data not provided for subpopulations for which there were less than 20 observations
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey
Source: Based on EPA's analyses of the 1987-88 NFCS
-------
Table 13-28.
Consumer Only
Intake of Home Produced
Dairy (g/kg-dav) - All Reg
ons
Population
Nc
Nc
%
Grouo
watd
u nwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
1409000
89
0.75
1.40E+01
1.62E+00
1.80E-01
4.46E-01
5.08E-01
3.18E+00
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
7.41 E+00
1.02E+00
2.05E-01
3.96E-01
4.46E-01
1.89E+00
6.46E+00
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+00
6.28E-01
6.54E-01
6.72E-01
5.06E+00
1.22E+01
1.95E+01
5.09E+01
8.01 E+01
1.11E+02
1.11E+02
Summer
549000
22
1.21
1.53E+01
2.73E+00
4.46E-01
4.46E-01
5.08E-01
5.36E+00
1.06E+01
2.51 E+01
3.49E+01
3.67E+01
4.68E+01
4.68E+01
Winter
396000
33
0.81
8.08E+00
1.99E+00
1.80E-01
2.05E-01
2.80E-01
7.36E-01
5.47E+00
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+00
4.79E-01
9.58E-01
1.89E+00
6.74E+00
1.08E+01
2.04E+01
3.49E+01
4.40E+01
8.01 E+01
1.11E+02
Suburban
306000
23
0.35
9.86E+00
2.38E+00
3.96E-01
3.96E-01
4.46E-01
5.71E-01
5.36E+00
1.31 E+01
2.81 E+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+00
1.80E-01
4.46E-01
5.08E-01
3.82E+00
1.03E+01
1.95E+01
3.42E+01
4.40E+01
8.01 E+01
1.11E+02
Response to Questionnaire
Households who raise animals
1228000
80
12.16
1.59E+01
1.73E+00
1.80E-01
3.96E-01
1.89E+00
6.13E+00
1.08E+01
1.96E+01
3.49E+01
4.40E+01
8.01 E+01
1.11E+02
Households who farm
1020000
63
13.92
1.71E+01
1.99E+00
3.96E-01
7.36E-01
3.18E+00
9.06E+00
1.21E+01
2.04E+01
3.49E+01
4.40E+01
8.01 E+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
Nc wgtd = weighted number of consumers; Nc unwgtd
Source: Based on EPA's analyses of the 1987-88 NFCS
= unweighted number of consumers in survey.
-------
Table 13-29.
Consumer Only Intake of Home Produced Dairy (g/kg-day) - Northeast
Population
Nc
Nc
%
Group
wgtd
unwgtd
Consuming
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
Nonmetropolitan
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
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-
88 NFCS
-------
Table 13-30.
Consumer
Only Intake of Home Produced Dairy (g/kg-day) - Midwest
Population Nc
Nc
%
Grouo watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total 594000
36
1.28
1.86E+01
3.15E+00
4.46E-01
4.46E-01
1.97E+00
8.27E+00
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+00
4.25E+00
8.27E+00
9.06E+00
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+00
4.25E+00
5.36E+00
8.27E+00
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+00
4.25E+00
5.36E+00
8.27E+00
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
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey
Source: Based on EPA's analyses of the 1987-88 NFCS
-------
Table 13-31
Consumer Only Intake of Home Produced
Dairy (q/kq-dav) - South
Population Nc
Nc
%
Grouo watd
unwatd Consumina
Mean SE P1 P5
P10 P25
P50
P75
P90
P95
P99
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
*
*
*
*
*
Nonmetropolitan 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
Nc wgtd = weighted number of consumers; Nc unwgtd
Source: Based on EPA's analyses of the 1987-88 NFCS
= unweighted number of consumers in survey.
-------
Table 13-32.
Consumer
Only Intake of Home Produced Dairy (g/kg-dav) - West
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25 P50
P75
P90
P95
P99
P100
Total
261000
20
0.72
1.00E+01
2.75E+00
1.80E-01 1.80E-01
2.05E-01
5.08E-01 6.10E+00
1.33E+01
2.81 E+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
*
*
*
*
*
Winter
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
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987
88 NFCS
-------
Table 13-33.
Seasonally Adjusted Consumer Only Homegrown Intake (g/kg-day)
Population
Group
Percent
Consuming
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total Veaetables
Northeast
16.50
1.16E-03
1.59E-02
3.56E-02
1.99E-01
4.55E-01
1.37E+00
3.32E+00
5.70E+00
8.78E+00
1.01E+01
Midwest
33.25
3.69E-03
4.11E-02
8.26E-02
2.91 E-01
8.11 E-01
1.96E+00
4.40E+00
7.41 E+00
1.31 E+00
2.01 E+01
South
24.00
4.78E-03
3.24E-02
5.58E-02
2.05E-01
6.10E-01
1.86E+00
3.95E+00
5.63E+00
1.20E+01
1.62E+01
West
23.75
1.80E-03
1.91E-02
3.83E-02
1.14E-01
4.92E-01
1.46E+00
2.99E+00
5.04E+00
8.91 E+00
1.12E+01
All Regions
24.60
5.00E-03
2.90E-02
5.90E-02
2.19E-01
6.38E-01
1.80E+00
4.00E+00
6.08E+00
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+00
3.00E+00
5.10E+00
5.63E+00
Midwest
12.75
1.22E-03
7.01 E-03
1.46E-02
1.36E-01
7.87E-01
2.98E+00
5.79E+00
9.52E+00
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+00
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
6.88E-01
1.81E+00
4.75E+00
8.54E+00
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+00
5.61 E+00
9.12E+00
1.76E+01
2.71 E+01
Total Meat
Northeast
6.25
3.78E-03
3.01 E-02
7.94E-02
1.25E-01
2.11 E-01
7.00E-01
1.56E+00
1.91 E+00
4.09E+00
4.80E+00
Midwest
9.25
1.77E-03
3.68E-02
2.21 E-01
5.25E-02
1.61E+00
3.41 E+00
5.25E+00
7.45E+00
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+00
3.78E+00
4.95E+00
8.45E+00
9.45E+00
West
9.50
7.24E-04
2.83E-02
9.56E-02
2.35E-01
5.64E-01
1.30E+00
2.29E+00
3.38E+00
7.20E+00
9.10E+00
All Regions
7.40
3.20E-03
3.90E-02
9.20E-02
2.20E-01
6.55E-01
1.96E+00
4.05E+00
5.17E+00
9.40E+00
1.36E+01
-------
Table 13-34.
Consumer Only Intake of
Homegrown
Apples (g/kg-day)
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
5306000
272
2.82
1.19E+00
7.58E-02
8.34E-02
2.30E-01
2.84E-01
4.50E-01
8.17E-01
1.47E+00
2.38E+00
3.40E+00
5.42E+00
1.01E+01
Age
01-02
199000
12
3.49
*
*
*
*
*
*
*
03-05
291000
16
3.59
*
*
*
*
*
*
*
06-11
402000
25
2.41
1.28E+00
1.88E-01
4.72E-01
4.72E-01
5.63E-01
7.40E-01
9.56E-01
1.29E+00
2.98E+00
4.00E+00
4.00E+00
4.00E+00
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+00
1.97E+00
5.42E+00
5.42E+00
40-69
1719000
90
3.03
9.61 E-01
1.37E-01
5.57E-02
8.94E-02
2.55E-01
3.98E-01
6.48E-01
1.08E+00
1.59E+00
2.38E+00
9.83E+00
9.83E+00
70 +
1061000
52
6.68
1.45E+00
1.41 E-01
1.99E-01
2.60E-01
4.46E-01
6.27E-01
1.18E+00
1.82E+00
3.40E+00
3.62E+00
4.20E+00
4.20E+00
Season
Fall
1707000
60
3.58
1.28E+00
1.24E-01
2.56E-01
2.95E-01
3.20E-01
5.83E-01
1.03E+00
1.66E+00
2.69E+00
3.40E+00
4.25E+00
4.25E+00
Spring
639000
74
1.38
9.50E-01
1.14E-01
1.94E-01
2.38E-01
2.84E-01
3.76E-01
5.67E-01
1.10E+00
2.00E+00
2.78E+00
5.87E+00
5.87E+00
Summer
1935000
68
4.25
1.12E+00
1.69E-01
5.57E-02
8.94E-02
1.86E-01
3.98E-01
6.92E-01
1.41E+00
2.29E+00
2.98E+00
9.83E+00
9.83E+00
Winter
1025000
70
2.10
1.30E+00
1.78E-01
1.85E-01
2.30E-01
3.23E-01
5.71 E-01
8.81E-01
1.59E+00
2.75E+00
3.40E+00
1.01E+01
1.01E+01
Urbanization
Central City
912000
30
1.62
1.24E+00
2.60E-01
2.31 E-01
2.56E-01
3.92E-01
5.10E-01
9.17E-01
1.59E+00
2.19E+00
2.26E+00
1.01E+01
1.01E+01
Nonmetropolitan
2118000
122
4.70
1.27E+00
1.26E-01
5.57E-02
1.18E-01
2.49E-01
4.11 E-01
9.00E-01
1.55E+00
2.92E+00
3.48E+00
9.83E+00
9.83E+00
Suburban
2276000
120
2.63
1.09E+00
9.16E-02
1.86E-01
2.37E-01
2.91 E-01
4.37E-01
7.74E-01
1.29E+00
2.29E+00
3.40E+00
5.42E+00
5.42E+00
Race
Black
84000
4
0.39
*
*
*
*
*
*
*
White
5222000
268
3.31
1.18E+00
7.67E-02
8.34E-02
2.30E-01
2.79E-01
4.48E-01
7.98E-01
1.41E+00
2.38E+00
3.40E+00
5.42E+00
1.01E+01
Region
Midwest
2044000
123
4.41
1.38E+00
1.45E-01
2.16E-01
2.85E-01
3.04E-01
5.20E-01
9.23E-01
1.61E+00
2.69E+00
3.40E+00
9.83E+00
1.01E+01
Northeast
442000
18
1.07
*
*
*
*
*
*
*
South
1310000
65
2.04
1.10E+00
1.07E-01
1.99E-01
2.38E-01
3.01 E-01
4.39E-01
9.17E-01
1.38E+00
1.90E+00
2.98E+00
4.00E+00
4.91 E+00
West
1510000
66
4.19
1.20E+00
1.29E-01
5.57E-02
1.86E-01
2.64E-01
4.72E-01
7.89E-01
1.82E+00
2.75E+00
3.62E+00
4.25E+00
4.25E+00
Response to Questionnaire
Households who garden
4707000
246
6.91
1.21E+00
8.22E-02
1.27E-01
2.49E-01
2.95E-01
4.70E-01
8.17E-01
1.47E+00
2.38E+00
3.40E+00
5.87E+00
1.01E+01
Households who farm
1299000
68
17.72
1.39E+00
1.31 E-01
5.57E-02
3.57E-01
5.36E-01
7.03E-01
9.56E-01
1.58E+00
2.99E+00
4.00E+00
4.91 E+00
5.87E+00
* Intake data not provided for subpopulations for which there were less than 20 observations
NOTE: SE = standard error
P = percentile of the distibution
Nc wgtd = weighted number of consumers; Nc unwgtd =
Source: Based on EPA's analyses of the 1987-88 NFCS
unweighted number of consumers in survey.
-------
Table 13-35. Consumer Only Intake of Homeg
rown Asparag
us (g/kg-dav)
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
Mean
SE
P1
P5
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+00
1.63E+00
1.97E+00
1.97E+00
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+00
1.75E+00
1.75E+00
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+00
1.63E+00
1.97E+00
1.97E+00
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+00
1.75E+00
1.92E+00
1.97E+00
1.97E+00
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
7.01 E-01
9.31 E-01
1.12E+00
1.12E+00
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+00
1.63E+00
1.97E+00
1.97E+00
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
9.31 E-01
1.12E+00
1.97E+00
1.97E+00
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+00
1.63E+00
1.92E+00
1.92E+00
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+00
1.63E+00
1.97E+00
1.97E+00
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
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-88 NFCS
-------
Table 13-36. Consumer
Only Intake of Home Produced Beef
("g/kg-day)
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
4958000
304
2.64
2.45E+00
1.49E-01
1.83E-01
3.74E-01
4.65E-01
8.78E-01
1.61E+00
3.07E+00
5.29E+00
7.24E+00
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+00
5.94E-01
3.54E-01
6.63E-01
7.53E-01
1.32E+00
2.11E+00
4.43E+00
1.14E+01
1.25E+01
1.33E+01
1.33E+01
12-19
656000
41
3.20
1.72E+00
1.63E-01
3.78E-01
4.78E-01
5.13E-01
8.96E-01
1.51E+00
2.44E+00
3.53E+00
3.57E+00
4.28E+00
4.28E+00
20-39
1495000
83
2.43
2.06E+00
2.00E-01
2.69E-01
3.52E-01
3.94E-01
6.80E-01
1.59E+00
2.73E+00
4.88E+00
6.50E+00
8.26E+00
8.26E+00
40-69
1490000
105
2.63
1.84E+00
1.41E-01
1.83E-01
3.61 E-01
4.55E-01
8.33E-01
1.52E+00
2.38E+00
4.10E+00
5.39E+00
5.90E+00
5.90E+00
70 +
188000
11
1.18
*
*
*
*
*
*
Season
Fall
1404000
55
2.95
1.55E+00
1.74E-01
1.83E-01
3.52E-01
3.61 E-01
5.17E-01
1.33E+00
2.01 E+00
2.86E+00
3.90E+00
7.24E+00
7.24E+00
Spring
911000
108
1.97
2.32E+00
1.63E-01
2.70E-01
3.90E-01
5.10E-01
1.04E+00
1.96E+00
3.29E+00
4.22E+00
5.23E+00
8.62E+00
9.28E+00
Summer
1755000
69
3.86
3.48E+00
4.12E-01
1.02E-01
6.08E-01
7.45E-01
1.02E+00
2.44E+00
4.43E+00
7.51 E+00
1.14E+01
1.87E+01
1.87E+01
Winter
888000
72
1.82
1.95E+00
2.75E-01
3.93E-02
3.75E-01
3.94E-01
6.74E-01
1.33E+00
2.14E+00
4.23E+00
5.39E+00
1.94E+01
1.94E+01
Urbanization
Central City
100000
5
0.18
*
*
*
*
*
*
Nonmetropolitan
3070000
194
6.82
2.80E+00
2.18E-01
1.83E-01
3.77E-01
4.99E-01
8.64E-01
1.81E+00
3.57E+00
6.03E+00
8.44E+00
1.87E+01
1.94E+01
Suburban
1788000
105
2.07
1.93E+00
1.50E-01
2.67E-01
3.75E-01
4.16E-01
9.07E-01
1.52E+00
2.44E+00
4.06E+00
5.10E+00
7.51 E+00
9.28E+00
Race
Black
0
0
0.00
White
4950000
303
3.14
2.45E+00
1.50E-01
1.83E-01
3.74E-01
4.65E-01
8.78E-01
1.61E+00
3.07E+00
5.29E+00
7.24E+00
1.33E+01
1.94E+01
Region
Midwest
2261000
161
4.87
2.83E+00
2.31 E-01
1.83E-01
3.54E-01
4.16E-01
8.47E-01
2.01 E+00
3.66E+00
5.90E+00
8.39E+00
1.87E+01
1.87E+01
Northeast
586000
25
1.42
1.44E+00
2.13E-01
3.52E-01
3.52E-01
4.73E-01
7.42E-01
1.06E+00
1.68E+00
2.62E+00
2.62E+00
6.03E+00
6.03E+00
South
1042000
61
1.62
2.45E+00
3.46E-01
1.02E-01
3.90E-01
5.84E-01
8.16E-01
1.59E+00
2.41 E+00
6.36E+00
7.24E+00
1.33E+01
1.33E+01
West
1069000
57
2.96
2.20E+00
2.83E-01
3.13E-01
3.80E-01
5.56E-01
1.04E+00
1.60E+00
2.86E+00
4.06E+00
4.42E+00
7.51 E+00
1.94E+01
Response to Questionnaire
Households who raise animals
3699000
239
36.63
2.66E+00
1.60E-01
1.83E-01
3.88E-01
6.63E-01
1.04E+00
1.83E+00
3.48E+00
5.39E+00
7.51 E+00
1.25E+01
1.94E+01
Households who farm
2850000
182
38.89
2.63E+00
1.96E-01
2.70E-01
3.94E-01
5.85E-01
8.96E-01
1.64E+00
3.25E+00
5.39E+00
7.51 E+00
1.13E+01
1.94E+01
* I ntake data not provided for subpopulations for which there were less than 20 observations
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd
Source: Based on EPA's analyses of the 1987-88 NFCS
= unweighted number of consumers in survey.
-------
Table 13-37. Consumer Only Intake of Homegrown Beets
(q/kq-dav)
Population
Nc
Nc
%
Grouo
watd
unwatc
Consumina
Mean
SE
P1
P5
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+00
1.36E+00
3.69E+00
4.08E+00
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
3.81 E-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+00
1.12E+00
40-69
951000
51
1.68
4.28E-01
4.34E-02
5.00E-02
7.31 E-02
7.46E-02
2.05E-01
3.97E-01
5.49E-01
9.25E-01
1.15E+00
1.40E+00
1.40E+00
70 +
408000
23
2.57
5.80E-01
8.80E-02
3.21 E-02
3.21 E-02
4.76E-02
2.71 E-01
4.49E-01
9.09E-01
1.36E+00
1.36E+00
1.59E+00
1.59E+00
Season
Fall
562000
21
1.18
5.45E-01
9.36E-02
3.21 E-02
4.76E-02
5.00E-02
2.57E-01
3.56E-01
9.49E-01
1.36E+00
1.36E+00
1.40E+00
1.40E+00
Spring
558000
55
1.21
4.70E-01
8.98E-02
7.46E-02
8.06E-02
1.09E-01
1.43E-01
2.73E-01
4.47E-01
8.73E-01
1.59E+00
4.08E+00
4.08E+00
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
7.31 E-02
7.31 E-02
7.37E-02
2.80E-01
5.20E-01
8.28E-01
1.13E+00
2.32E+00
3.69E+00
3.69E+00
Urbanization
Central City
651000
27
1.16
5.18E-01
1.15E-01
1.11 E-01
1.35E-01
1.83E-01
2.57E-01
4.01 E-01
5.49E-01
9.09E-01
1.12E+00
3.69E+00
3.69E+00
Nonmetropolitan
758000
51
1.68
5.77E-01
9.06E-02
5.00E-02
7.31 E-02
7.37E-02
1.80E-01
3.86E-01
6.61 E-01
1.36E+00
1.40E+00
4.08E+00
4.08E+00
Suburban
805000
47
0.93
4.45E-01
5.77E-02
3.21 E-02
4.76E-02
8.06E-02
1.43E-01
3.97E-01
5.56E-01
9.25E-01
9.99E-01
2.32E+00
2.32E+00
Race
Black
0
0
0.00
White
2186000
124
1.39
5.18E-01
4.99E-02
3.21 E-02
7.46E-02
1.13E-01
2.05E-01
3.97E-01
5.87E-01
1.03E+00
1.36E+00
3.69E+00
4.08E+00
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+00
1.36E+00
3.69E+00
3.69E+00
Northeast
230000
13
0.56
*
*
*
*
*
*
*
South
545000
31
0.85
4.51 E-01
1.17E-01
7.46E-02
7.57E-02
8.06E-02
1.80E-01
2.64E-01
4.84E-01
6.61 E-01
9.44E-01
4.08E+00
4.08E+00
West
554000
28
1.54
3.96E-01
7.75E-02
3.21 E-02
4.76E-02
7.31 E-02
1.21 E-01
2.86E-01
5.49E-01
6.24E-01
7.04E-01
2.32E+00
2.32E+00
Response to Questionnaire
Households who garden
2107000
120
3.09
5.26E-01
5.16E-02
3.21 E-02
7.37E-02
9.56E-02
2.05E-01
4.01 E-01
6.06E-01
1.03E+00
1.36E+00
3.69E+00
4.08E+00
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
Nc wgtd = weighted number of consumers; Nc unwgtd =
Source: Based on EPA's analyses of the 1987-88 NFCS
unweighted number of consumers in survey.
-------
Table 13-38.
Consumer Only Intake of
Homegrown Broccoli (g/kg-day)
Population
Nc
Nc
%
Grouo
watd
u nwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
1745000
80
0.93
4.20E-01
4.75E-02
7.61 E-02
8.24E-02
1.56E-01
1.96E-01
2.90E-01
4.59E-01
8.15E-01
9.74E-01
2.48E+00
3.02E+00
Age
01-02
0
0
0.00
03-05
13000
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
3.51 E-01
4.61 E-01
6.14E-01
8.15E-01
3.02E+00
3.02E+00
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
2.31 E-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
3.31 E-01
5.89E-01
1.25E+00
2.37E+00
3.02E+00
3.02E+00
Summer
682000
22
1.50
5.08E-01
1.05E-01
7.61 E-02
1.29E-01
1.78E-01
2.15E-01
3.99E-01
6.61 E-01
8.86E-01
9.74E-01
2.48E+00
2.48E+00
Winter
181000
11
0.37
*
*
*
*
*
*
*
*
Urbanization
Central City
165000
5
0.29
*
*
*
*
*
*
*
*
Nonmetropolitan
647000
34
1.44
4.23E-01
4.21 E-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
4.41 E-01
6.84E-01
2.37E+00
2.48E+00
3.02E+00
Race
Black
0
0
0.00
White
1719000
79
1.09
4.22E-01
4.81 E-02
7.61 E-02
8.24E-02
1.56E-01
1.96E-01
2.88E-01
4.59E-01
8.15E-01
9.74E-01
2.48E+00
3.02E+00
Region
Midwest
792000
38
1.71
2.63E-01
5.86E-02
7.61 E-02
7.99E-02
8.24E-02
1.75E-01
2.13E-01
2.75E-01
3.44E-01
4.03E-01
3.02E+00
3.02E+00
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
7.61 E-02
8.24E-02
1.64E-01
1.96E-01
2.90E-01
4.59E-01
8.15E-01
9.74E-01
2.48E+00
3.02E+00
Households who farm
599000
29
8.17
4.66E-01
8.37E-02
4.50E-02
7.61 E-02
1.54E-01
1.95E-01
3.10E-01
6.61 E-01
8.86E-01
9.74E-01
3.02E+00
3.02E+00
* Intake data not provided for subpopulations for which there were less than 20 observations
NOTE: SE = standard error
P = percentile of the distibution
Nc wgtd = weighted number of consumers; Nc unwgtd =
Source: Based on EPA's analyses of the 1987-88 NFCS
unweighted number of consumers in survey.
-------
Table 13-39. Consumer Only Intake of Homegrown Cabbage (g/kg-dav)
Population
Nc
Nc
%
Grouo
wgtd u
nwgtd
Consuming
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
2019000
89
1.07
1.03E+00
1.00E-01
1.07E-01
2.03E-01
3.17E-01
4.21 E-01
7.76E-01
1.33E+00
1.97E+00
2.35E+00
5.43E+00
5.43E+00
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+00
1.80E-01
2.17E-01
2.22E-01
3.25E-01
4.08E-01
7.13E-01
1.41E+00
1.82E+00
5.29E+00
5.43E+00
5.43E+00
70 +
326000
13
2.05
*
*
*
*
*
*
*
Season
Fall
570000
21
1.20
1.28E+00
3.24E-01
1.86E-01
1.86E-01
2.03E-01
3.85E-01
5.42E-01
1.49E+00
5.29E+00
5.43E+00
5.43E+00
5.43E+00
Spring
126000
15
0.27
*
*
*
*
*
*
*
Summer
1142000
39
2.51
9.65E-01
9.35E-02
2.01 E-01
2.22E-01
3.25E-01
5.55E-01
8.28E-01
1.24E+00
1.79E+00
2.35E+00
2.77E+00
2.77E+00
Winter
181000
14
0.37
*
*
*
*
*
*
*
Urbanization
Central City
157000
5
0.28
*
*
*
*
*
*
*
Nonmetropolitan
1079000
48
2.40
9.37E-01
8.83E-02
2.01 E-01
3.17E-01
3.40E-01
4.54E-01
7.13E-01
1.33E+00
1.79E+00
2.35E+00
2.77E+00
2.77E+00
Suburban
783000
36
0.90
1.26E+00
2.11E-01
3.20E-02
2.22E-01
3.25E-01
4.49E-01
1.05E+00
1.37E+00
2.17E+00
5.29E+00
5.43E+00
5.43E+00
Race
Black
7000
1
0.03
*
*
*
*
*
*
*
White
1867000
83
1.19
1.05E+00
1.07E-01
1.07E-01
2.03E-01
2.46E-01
4.13E-01
7.88E-01
1.37E+00
1.97E+00
2.35E+00
5.43E+00
5.43E+00
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+00
1.29E+00
1.49E+00
1.82E+00
1.98E+00
Northeast
277000
11
0.67
*
*
*
*
*
*
*
South
616000
32
0.96
1.11E+00
1.34E-01
3.20E-02
2.01 E-01
2.17E-01
4.49E-01
8.50E-01
1.79E+00
2.17E+00
2.35E+00
2.77E+00
2.77E+00
West
242000
9
0.67
*
*
*
*
*
*
*
Response to Questionnaire
Households who garden
1921000
86
2.82
1.07E+00
1.03E-01
1.07E-01
2.03E-01
3.17E-01
4.54E-01
7.88E-01
1.37E+00
1.97E+00
2.35E+00
5.43E+00
5.43E+00
Households who farm
546000
26
7 45
9 96F-01
1 15F-01
2 01F-01
2 06F-01
3 51F-01
5 87F-01
8 28F-01
1 37F+00
1 79F+00
2 35F+00
2 35F+00
2 35F+00
* Intake data not provided for subpopulations for which there were less than 20 observations
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey
Source: Based on EPA's analyses of the 1987-88 NFCS
-------
Table 13-40. Consumer
Only Intake of Homegrown Carrots
(g/kg-dav)
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
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+00
2.21 E+00
7.79E+00
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+00
1.19E+00
40-69
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+00
1.53E+00
2.21 E+00
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+00
1.08E+00
1.08E+00
Season
Fall
1810000
66
3.80
4.61 E-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+00
1.71 E+00
7.79E+00
Spring
267000
28
0.58
5.55E-01
1.01 E-01
1.39E-01
1.49E-01
2.02E-01
2.16E-01
3.92E-01
6.09E-01
9.94E-01
2.11E+00
2.94E+00
2.94E+00
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+00
1.19E+00
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+00
1.53E+00
3.06E+00
3.06E+00
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
6.81 E-02
2.00E-01
3.28E-01
5.13E-01
9.55E-01
1.19E+00
7.79E+00
7.79E+00
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+00
1.71 E+00
1.71 E+00
Race
Black
107000
7
0.49
*
*
*
*
*
*
White
3970000
178
2.52
4.13E-01
2.58E-02
4.34E-02
7.96E-02
1.11 E-01
1.94E-01
3.33E-01
5.27E-01
7.76E-01
1.01E+00
1.59E+00
3.06E+00
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+00
2.11 E+00
3.06E+00
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+00
1.71E+00
2.21 E+00
2.21 E+00
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+00
7.79E+00
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
6.81 E-02
9.34E-02
1.79E-01
3.28E-01
5.09E-01
7.62E-01
1.08E+00
1.71 E+00
3.06E+00
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+00
2.11 E+00
2.94E+00
* Intake data not provided for subpopulations for which there were less than 20 observations
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Source: Based on EPA' analyses of the 1987-88 NFCS
-------
Table 13-41. Consumer Only
Intake of Homegrown Corn
(g/kg-dav)
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
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+00
3.37E+00
7.44E+00
9.23E+00
Age
01-02
205000
13
3.60
*
*
*
*
*
03-05
313000
24
3.86
1.25E+00
2.57E-01
3.25E-01
3.25E-01
4.00E-01
5.98E-01
1.00E+00
1.21E+00
1.67E+00
5.35E+00
5.35E+00
5.35E+00
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+00
3.13E+00
3.37E+00
4.52E+00
4.52E+00
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
7.11 E-01
1.55E+00
1.88E+00
1.88E+00
1.88E+00
20-39
1913000
108
3.11
5.97E-01
6.00E-02
6.59E-02
1.41E-01
1.52E-01
2.08E-01
3.71 E-01
7.08E-01
1.53E+00
2.04E+00
3.70E+00
3.70E+00
40-69
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+00
3.22E+00
7.44E+00
7.44E+00
70 +
871000
53
5.48
9.43E-01
2.59E-01
3.91 E-02
5.15E-02
1.05E-01
1.88E-01
3.64E-01
7.57E-01
1.34E+00
6.49E+00
9.23E+00
9.23E+00
Season
Fall
2458000
89
5.16
5.44E-01
8.37E-02
3.91 E-02
1.05E-01
1.42E-01
1.88E-01
3.17E-01
5.46E-01
1.27E+00
1.42E+00
5.35E+00
5.69E+00
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+00
1.57E+00
5.15E+00
6.68E+00
Summer
1777000
62
3.91
1.82E+00
2.62E-01
6.59E-02
1.78E-01
3.43E-01
6.44E-01
9.36E-01
2.13E+00
4.52E+00
6.84E+00
9.23E+00
9.23E+00
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+00
1.47E+00
2.04E+00
3.94E+00
Urbanization
Central City
748000
27
1.33
7.37E-01
1.41E-01
3.91 E-02
3.91 E-02
5.15E-02
1.77E-01
5.46E-01
9.29E-01
2.04E+00
2.23E+00
3.04E+00
3.04E+00
Nonmetropolitan
4122000
268
9.16
9.63E-01
8.18E-02
7.40E-02
1.22E-01
1.66E-01
2.49E-01
5.31 E-01
1.00E+00
2.13E+00
3.38E+00
7.44E+00
8.97E+00
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+00
1.71E+00
9.23E+00
9.23E+00
Race
Black
188000
9
0.86
*
*
*
*
*
White
6703000
412
4.26
8.87E-01
6.51 E-02
5.15E-02
1.22E-01
1.63E-01
2.37E-01
4.80E-01
8.84E-01
1.88E+00
3.22E+00
7.44E+00
9.23E+00
Region
Midwest
2557000
188
5.51
9.34E-01
9.74E-02
3.91 E-02
1.19E-01
1.68E-01
2.47E-01
4.56E-01
9.29E-01
2.28E+00
3.22E+00
6.84E+00
7.44E+00
Northeast
586000
33
1.42
6.14E-01
8.42E-02
9.87E-02
1.66E-01
1.86E-01
2.44E-01
3.81 E-01
8.83E-01
1.34E+00
1.71E+00
1.71E+00
1.71E+00
South
2745000
153
4.27
8.73E-01
9.52E-02
7.40E-02
1.22E-01
1.66E-01
2.83E-01
5.61 E-01
9.35E-01
1.55E+00
3.37E+00
5.69E+00
8.97E+00
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+00
6.49E+00
9.23E+00
9.23E+00
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+00
3.13E+00
6.84E+00
9.23E+00
Households who farm
1739000
114
23.73
1.20E+00
1.77E-01
3.91 E-02
1.08E-01
1.66E-01
2.29E-01
3.81 E-01
9.74E-01
3.37E+00
6.49E+00
9.23E+00
9.23E+00
* Intake data not provided for subpopulations for which there were less than 20 observations
NOTE: SE = standard error
P = percentile of the distributions
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-88 NFCS
-------
Table 13-42.
Consumer
Only Intake of
Homegrown Cucumbers
(g/kg-day)
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
3994000
141
2.12
1.02E+00
1.55E-01
3.08E-02
6.71 E-02
1.08E-01
2.40E-01
5.40E-01
1.13E+00
2.11E+00
2.79E+00
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
6.31 E-02
1.83E-01
3.09E-01
6.17E-01
1.35E+00
1.49E+00
2.12E+00
2.12E+00
40-69
1882000
68
3.32
1.33E+00
3.01 E-01
4.16E-02
7.46E-02
1.76E-01
3.93E-01
6.84E-01
1.29E+00
2.11E+00
3.27E+00
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+00
1.83E-01
0.00E+00
7.46E-02
1.08E-01
2.42E-01
5.18E-01
1.13E+00
2.12E+00
2.79E+00
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+00
3.43E-01
1.01 E-01
1.21 E-01
1.90E-01
3.86E-01
1.06E+00
1.67E+00
3.09E+00
4.50E+00
1.37E+01
1.37E+01
Suburban
1824000
59
2.11
6.71 E-01
7.52E-02
0.00E+00
7.46E-02
1.62E-01
2.78E-01
4.99E-01
8.33E-01
1.34E+00
1.73E+00
3.27E+00
3.27E+00
Race
Black
86000
2
0.40
*
*
*
*
*
White
3724000
132
2.36
9.35E-01
1.62E-01
3.08E-02
6.31 E-02
1.01 E-01
2.22E-01
5.01 E-01
1.03E+00
1.49E+00
2.40E+00
1.34E+01
1.37E+01
Region
Midwest
969000
31
2.09
1.00E+00
3.92E-01
3.08E-02
4.16E-02
5.45E-02
1.35E-01
4.53E-01
1.03E+00
2.35E+00
2.45E+00
1.34E+01
1.34E+01
Northeast
689000
22
1.67
1.92E+00
6.78E-01
2.33E-01
2.78E-01
2.78E-01
4.75E-01
6.84E-01
1.53E+00
4.18E+00
1.17E+01
1.37E+01
1.37E+01
South
1317000
54
2.05
8.85E-01
1.05E-01
0.00E+00
1.21 E-01
1.83E-01
2.87E-01
7.53E-01
1.28E+00
1.73E+00
2.13E+00
4.50E+00
4.50E+00
West
1019000
34
2.83
6.01 E-01
1.06E-01
6.71 E-02
7.46E-02
1.01 E-01
2.09E-01
4.30E-01
7.01 E-01
1.29E+00
2.11E+00
3.27E+00
3.27E+00
Response to Questionnaire
Households who garden
3465000
123
5.08
1.05E+00
1.75E-01
3.08E-02
6.71 E-02
1.01 E-01
2.78E-01
5.18E-01
1.13E+00
2.11E+00
2.79E+00
1.34E+01
1.37E+01
Households who farm
710000
29
9.69
6.99E-01
1.07E-01
0.00E+00
0.00E+00
1.43E-01
1.88E-01
3.86E-01
1.27E+00
1.49E+00
1.71E+00
2.09E+00
2.09E+00
* Intake data not provided for subpopulations for which there were less than 20 observations
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtc
Source: Based on EPA's analyses of the 1987-88 NFCS
= unweighted number of consumers in survey.
-------
Table 13-43.
Consumer Only
Intake of Home Produced
Eggs (g/kg-dav)
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
2075000
124
1.10
7.31 E-01
1.00E-01
7.16E-02
1.50E-01
1.75E-01
2.68E-01
4.66E-01
9.02E-01
1.36E+00
1.69E+00
6.58E+00
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+00
1.93E+00
2.50E+00
2.50E+00
40-69
718000
43
1.27
5.91 E-01
5.77E-02
1.37E-01
1.41 E-01
1.52E-01
3.17E-01
5.14E-01
8.44E-01
1.30E+00
1.36E+00
1.38E+00
1.38E+00
70 +
489000
18
3.08
*
*
*
*
*
*
*
*
*
*
*
Seasons
Fall
542000
18
1.14
*
*
*
*
*
*
*
*
*
*
*
Spring
460000
54
1.00
1.31 E+00
2.88E-01
1.57E-01
3.25E-01
3.94E-01
5.02E-01
6.66E-01
1.31 E+00
2.10E+00
3.26E+00
1.35E+01
1.35E+01
Summer
723000
26
1.59
4.96E-01
8.14E-02
7.16E-02
1.37E-01
1.41 E-01
2.60E-01
3.32E-01
5.41 E-01
1.36E+00
1.51 E+00
1.65E+00
1.65E+00
Winter
350000
26
0.72
8.60E-01
9.50E-02
1.67E-01
1.75E-01
2.15E-01
4.03E-01
7.51 E-01
1.17E+00
1.62E+00
1.93E+00
1.93E+00
1.93E+00
Urbanization
Central City
251000
9
0.45
*
*
*
*
*
*
*
*
*
*
*
Nonmetropolitan
1076000
65
2.39
7.34E-01
1.23E-01
7.16E-02
1.41 E-01
1.67E-01
2.60E-01
4.74E-01
9.16E-01
1.34E+00
1.65E+00
6.58E+00
9.16E+00
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+00
1.36E+00
1.85E+00
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+00
1.69E+00
6.58E+00
1.35E+01
Region
Midwest
665000
37
1.43
7.93E-01
1.96E-01
7.16E-02
1.37E-01
1.41 E-01
2.17E-01
3.39E-01
1.08E+00
1.51 E+00
2.10E+00
9.16E+00
9.16E+00
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+00
1.62E+00
1.93E+00
1.93E+00
West
500000
36
1.39
9.21 E-01
2.75E-01
1.67E-01
2.06E-01
2.08E-01
4.58E-01
6.66E-01
1.05E+00
1.36E+00
1.36E+00
1.35E+01
1.35E+01
Response to Questionnaire
Households who raise animals
1824000
113
18.06
7.46E-01
1.11 E-01
7.16E-02
1.50E-01
1.65E-01
2.56E-01
4.82E-01
9.02E-01
1.36E+00
1.85E+00
6.58E+00
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+00
1.65E+00
1.85E+00
6.58E+00
9.16E+00
* Intake data not provided for subpopulations for which there were less than 20 observations
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc 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 (q/kq-day)
Population
Nc
Nc
%
Grouo
wqtd
unwqtd
Consuminq
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+00
1.17E-01
2.10E-01
3.97E-01
7.09E-01
1.22E+00
2.27E+00
2.67E+00
3.61 E+00
4.59E+00
Age
01-02
89000
8
1.56
*
*
*
*
*
*
03-05
94000
8
1.16
*
*
*
*
*
*
06-11
362000
28
2.17
1.09E+00
1.44E-01
1.16E-01
2.31 E-01
4.28E-01
6.33E-01
7.61 E-01
1.48E+00
2.67E+00
2.85E+00
2.90E+00
2.90E+00
12-19
462000
27
2.25
1.04E+00
1.39E-01
2.10E-01
2.10E-01
2.91 E-01
6.30E-01
8.46E-01
1.22E+00
1.99E+00
3.13E+00
3.13E+00
3.13E+00
20-39
844000
59
1.37
8.24E-01
1.08E-01
1.04E-01
1.17E-01
1.88E-01
3.01 E-01
6.31 E-01
1.09E+00
1.57E+00
2.50E+00
4.59E+00
4.59E+00
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+00
2.51 E+00
3.19E+00
3.61 E+00
3.61 E+00
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+00
2.50E+00
3.13E+00
3.19E+00
3.19E+00
Spring
554000
68
1.20
9.06E-01
8.78E-02
0.00E+00
1.04E-01
1.72E-01
4.43E-01
7.46E-01
1.22E+00
1.75E+00
2.52E+00
3.61 E+00
3.61 E+00
Summer
273000
9
0.60
*
*
*
*
*
*
Winter
1004000
77
2.06
1.07E+00
1.05E-01
0.00E+00
0.00E+00
1.65E-01
3.88E-01
8.18E-01
1.52E+00
2.20E+00
2.67E+00
4.59E+00
4.59E+00
Urbanization
Central City
506000
20
0.90
6.89E-01
1.27E-01
0.00E+00
0.00E+00
1.88E-01
2.77E-01
6.30E-01
7.74E-01
1.48E+00
1.99E+00
2.34E+00
2.34E+00
Nonmetropolitan
1259000
101
2.80
9.45E-01
8.91 E-02
0.00E+00
1.17E-01
1.65E-01
3.20E-01
6.59E-01
1.19E+00
2.27E+00
3.05E+00
4.59E+00
4.59E+00
Suburban
942000
64
1.09
1.15E+00
1.04E-01
0.00E+00
2.56E-01
3.97E-01
5.21 E-01
8.18E-01
1.52E+00
2.51 E+00
2.85E+00
3.13E+00
3.61 E+00
Race
Black
0
0
0.00
White
2605000
182
1.65
9.77E-01
6.30E-02
0.00E+00
1.17E-01
2.02E-01
3.76E-01
7.29E-01
1.38E+00
2.34E+00
2.85E+00
3.61 E+00
4.59E+00
Region
Midwest
1321000
97
2.85
8.83E-01
8.32E-02
0.00E+00
7.53E-02
2.18E-01
3.42E-01
6.12E-01
1.10E+00
1.99E+00
2.51 E+00
4.59E+00
4.59E+00
Northeast
394000
20
0.96
1.13E+00
2.16E-01
2.87E-01
2.87E-01
3.21 E-01
4.30E-01
7.74E-01
1.41E+00
3.13E+00
3.13E+00
3.61 E+00
3.61 E+00
South
609000
47
0.95
1.26E+00
1.29E-01
0.00E+00
1.17E-01
1.48E-01
6.32E-01
1.09E+00
1.93E+00
2.38E+00
3.19E+00
3.19E+00
3.19E+00
West
383000
21
1.06
6.28E-01
7.21 E-02
1.24E-01
1.51 E-01
1.88E-01
3.97E-01
6.33E-01
7.74E-01
1.12E+00
1.22E+00
1.52E+00
1.52E+00
Response to Questionnaire
Households who hunt
2357000
158
11.66
1.04E+00
6.84E-02
0.00E+00
1.40E-01
2.77E-01
4.42E-01
7.46E-01
1.44E+00
2.38E+00
2.90E+00
3.61 E+00
4.59E+00
* Intake data not provided for subpopulations for which there were less than 20 observations
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-88 NFCS
-------
Table 13-45. Consumer Only Intake of Home Produced Lettuce (q/kq-dav)
Population
Nc
Nc
%
Grouo
wqtd
unwqtd
Consuminq
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
1520000
80
0.81
3.87E-01
3.18E-02
0.00E+00
4.49E-02
9.43E-02
1.70E-01
2.84E-01
5.45E-01
8.36E-01
1.03E+00
1.05E+00
1.28E+00
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
2.21 E-01
4.91 E-01
6.84E-01
8.86E-01
1.05E+00
1.28E+00
1.28E+00
70 +
317000
20
2.00
4.52E-01
7.17E-02
5.04E-02
6.71 E-02
1.12E-01
2.23E-01
2.88E-01
5.68E-01
1.03E+00
1.03E+00
1.03E+00
1.03E+00
Season
Fall
214000
8
0.45
*
*
*
*
*
Spring
352000
35
0.76
4.52E-01
4.86E-02
5.04E-02
6.71 E-02
1.24E-01
1.99E-01
4.53E-01
5.79E-01
7.98E-01
9.94E-01
1.28E+00
1.28E+00
Summer
856000
30
1.88
3.02E-01
3.96E-02
1.98E-02
3.35E-02
4.93E-02
1.42E-01
2.30E-01
4.24E-01
5.98E-01
8.14E-01
8.86E-01
8.86E-01
Winter
98000
7
0.20
*
*
*
*
*
Urbanization
Central City
268000
8
0.48
*
*
*
*
*
Nonmetropolitan
566000
36
1.26
3.67E-01
4.78E-02
1.98E-02
3.35E-02
4.49E-02
1.23E-01
2.88E-01
5.45E-01
8.14E-01
8.86E-01
1.28E+00
1.28E+00
Suburban
686000
36
0.79
3.49E-01
4.32E-02
0.00E+00
9.43E-02
9.68E-02
1.53E-01
2.30E-01
4.91 E-01
7.67E-01
9.94E-01
1.05E+00
1.05E+00
Race
Black
51000
3
0.23
*
*
*
*
*
White
1434000
75
0.91
3.79E-01
3.33E-02
0.00E+00
4.49E-02
9.43E-02
1.56E-01
2.75E-01
5.45E-01
8.86E-01
1.03E+00
1.05E+00
1.28E+00
Region
Midwest
630000
33
1.36
3.83E-01
5.54E-02
1.98E-02
3.35E-02
4.49E-02
1.56E-01
2.34E-01
5.68E-01
9.42E-01
1.03E+00
1.03E+00
1.03E+00
Northeast
336000
16
0.82
*
*
*
*
*
South
305000
20
0.47
3.52E-01
5.74E-02
0.00E+00
0.00E+00
1.27E-01
1.64E-01
2.75E-01
4.83E-01
5.79E-01
1.04E+00
1.28E+00
1.28E+00
West
249000
11
0.69
*
*
*
*
*
Responses to Questionnaire
Households who garden
1506000
78
2.21
3.90E-01
3.22E-02
0.00E+00
4.49E-02
9.43E-02
1.74E-01
2.84E-01
5.45E-01
8.36E-01
1.03E+00
1.05E+00
1.28E+00
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
Nc wgtd = weighted number of consumers; Nc unwgtd =
Source: Based on EPA's analyses of the 1987-88 NFCS
unweighted number of consumers in survey.
-------
Table 13-46. Consumer Only Intake of Home Produced Lima Beans (q/kq-dav)
Population
Nc
Nc
%
Grouo
wqtd
unwqtd
Consuminq
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
1917000
109
1.02
4.53E-01
4.11E-02
0.00E+00
9.19E-02
1.21E-01
1.88E-01
2.90E-01
5.45E-01
9.90E-01
1.69E+00
1.86E+00
1.91E+00
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+00
1.10E+00
1.10E+00
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+00
1.91E+00
1.91E+00
70 +
361000
25
2.27
5.23E-01
1.05E-01
8.20E-02
1.86E-01
1.88E-01
2.25E-01
2.86E-01
6.38E-01
1.86E+00
1.86E+00
1.86E+00
1.86E+00
Season
Fall
375000
14
0.79
*
*
*
*
*
*
*
Spring
316000
39
0.68
4.19E-01
5.50E-02
8.20E-02
9.02E-02
1.31E-01
2.32E-01
3.06E-01
5.45E-01
7.48E-01
1.31E+00
1.91E+00
1.91E+00
Summer
883000
29
1.94
4.99E-01
9.68E-02
0.00E+00
9.43E-02
1.21E-01
1.72E-01
2.90E-01
4.87E-01
1.53E+00
1.71E+00
1.86E+00
1.86E+00
Winter
343000
27
0.70
5.27E-01
6.25E-02
0.00E+00
3.23E-02
1.08E-01
3.05E-01
5.39E-01
7.58E-01
8.61 E-01
8.69E-01
1.69E+00
1.69E+00
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
3.20E-01
4.87E-01
7.69E-01
1.69E+00
1.91E+00
Suburban
638000
32
0.74
7.53E-01
9.60E-02
0.00E+00
8.20E-02
9.19E-02
3.20E-01
6.78E-01
9.90E-01
1.71E+00
1.86E+00
1.86E+00
1.86E+00
Race
Black
213000
9
0.98
*
*
*
*
*
*
*
White
1704000
100
1.08
3.83E-01
3.27E-02
0.00E+00
9.19E-02
1.08E-01
1.77E-01
2.54E-01
4.87E-01
8.61 E-01
9.90E-01
1.53E+00
1.91E+00
Region
Midwest
588000
36
1.27
4.28E-01
6.17E-02
0.00E+00
0.00E+00
1.06E-01
2.53E-01
3.06E-01
4.15E-01
9.90E-01
1.53E+00
1.69E+00
1.69E+00
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+00
1.71E+00
1.86E+00
1.91E+00
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+00
1.86E+00
1.91E+00
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
Nc wgtd = weighted number of consumers; Nc unwgtd =
Source: Based on EPA's analyses of the 1987-88 NFCS
unweighted number of consumers in survey.
-------
Table 13-47. Consumer Only Intake of Homeg
rown Okra
(q/kq-dav)
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
1696000
82
0.90
3.91 E-01
3.81 E-02
0.00E+00
5.03E-02
9.59E-02
1.48E-01
2.99E-01
4.58E-01
7.81 E-01
1.21E+00
1.53E+00
1.53E+00
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
1.11 E-01
1.37E-01
2.47E-01
3.07E-01
4.62E-01
7.81 E-01
1.14E+00
1.14E+00
1.14E+00
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
7.81 E-01
9.99E-01
1.07E+00
1.07E+00
Summer
1144000
41
2.52
3.86E-01
5.75E-02
0.00E+00
5.03E-02
9.59E-02
1.44E-01
2.99E-01
4.38E-01
1.15E+00
1.53E+00
1.53E+00
1.53E+00
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+00
2.69E-02
8.48E-02
1.48E-01
2.57E-01
4.38E-01
7.81 E-01
1.53E+00
1.53E+00
1.53E+00
Suburban
449000
21
0.52
5.14E-01
6.97E-02
6.57E-02
9.60E-02
1.11 E-01
3.13E-01
4.62E-01
6.00E-01
1.14E+00
1.15E+00
1.15E+00
1.15E+00
Race
Black
236000
13
1.09
*
*
*
*
*
*
*
*
*
*
White
1419000
68
0.90
4.26E-01
4.40E-02
0.00E+00
6.57E-02
9.60E-02
1.76E-01
3.30E-01
5.23E-01
1.14E+00
1.21E+00
1.53E+00
1.53E+00
Region
Midwest
113000
7
0.24
*
*
*
*
*
*
*
*
*
*
Northeast
South
1443000
70
2.24
3.73E-01
4.21 E-02
0.00E+00
5.03E-02
8.48E-02
1.44E-01
2.59E-01
4.38E-01
7.47E-01
1.21E+00
1.53E+00
1.53E+00
West
140000
5
0.39
*
*
*
*
*
*
*
*
*
*
Response to Questionnaire
Households who garden
1564000
77
2.29
3.84E-01
4.05E-02
0.00E+00
5.03E-02
9.59E-02
1.48E-01
2.98E-01
4.52E-01
1.07E+00
1.21E+00
1.53E+00
1.53E+00
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
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-88 NFCS
-------
Table 13-48. Consumer Only Intake of Homeg
rown Onions
(g/kg-dav)
Population
Nc
Nc
%
Grouo
watd u
nwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
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
8.81 E-02
2.06E-01
3.77E-01
6.09E-01
9.12E-01
1.49E+00
3.11E+00
Age
01-02
291000
17
5.11
*
*
*
*
*
*
*
03-05
178000
9
2.20
*
*
*
*
*
*
*
06-11
530000
31
3.17
3.03E-01
5.61 E-02
9.80E-03
1.08E-02
2.76E-02
1.06E-01
2.28E-01
3.83E-01
6.09E-01
1.36E+00
1.36E+00
1.36E+00
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+00
1.49E+00
40-69
2402000
143
4.23
2.50E-01
2.07E-02
3.03E-03
4.59E-03
1.11 E-02
7.66E-02
1.72E-01
3.58E-01
5.52E-01
6.90E-01
1.11E+00
1.41E+00
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
4.61 E-01
5.63E-01
2.68E+00
3.11E+00
3.11E+00
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+00
3.11E+00
Spring
1434000
147
3.11
1.95E-01
1.96E-02
2.01 E-03
5.47E-03
2.68E-02
5.73E-02
1.06E-01
2.59E-01
4.26E-01
5.23E-01
1.41E+00
1.77E+00
Summer
2891000
101
6.36
3.06E-01
2.91 E-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+00
1.49E+00
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+00
1.36E+00
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+00
1.77E+00
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+00
3.11E+00
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+00
3.11E+00
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+00
1.34E+00
Northeast
876000
52
2.13
2.32E-01
4.43E-02
2.01 E-03
3.73E-03
8.36E-03
1.08E-02
1.08E-01
3.53E-01
6.35E-01
1.05E+00
1.36E+00
1.41E+00
South
1919000
107
2.98
3.32E-01
2.93E-02
4.79E-03
2.76E-02
3.70E-02
1.46E-01
2.51 E-01
3.93E-01
6.90E-01
1.08E+00
1.49E+00
1.77E+00
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+00
3.11E+00
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
9.11 E-02
2.13E-01
3.81 E-01
6.09E-01
9.16E-01
1.77E+00
3.11E+00
Households who farm
1390000
81
18.97
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+00
1.49E+00
1.49E+00
* Intake data not provided for subpopulations for which there were less than 20 observations
NOTE: SE = standard error
P = percentile of the distributions
Nc wgtd = weighted number of consumers; Nc 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 Homeg
rown Other Berries (g/kg-dav)
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
1626000
99
0.86
4.80E-01
4.24E-02
0.00E+00
4.68E-02
9.24E-02
2.32E-01
3.84E-01
5.89E-01
1.07E+00
1.28E+00
2.21 E+00
2.21 E+00
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
6.31 E-02
7.95E-02
9.18E-02
9.18E-02
1.25E-01
3.30E-01
5.52E-01
7.94E-01
1.07E+00
1.07E+00
1.07E+00
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+00
2.21 E+00
2.21 E+00
70 +
159000
7
1.00
*
*
*
Season
Fall
379000
13
0.80
*
*
*
Spring
287000
29
0.62
3.06E-01
4.11 E-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+00
1.07E+00
Summer
502000
18
1.10
*
*
*
Winter
458000
39
0.94
5.35E-01
7.39E-02
0.00E+00
1.02E-01
1.59E-01
2.32E-01
3.89E-01
6.23E-01
1.07E+00
1.95E+00
2.08E+00
2.08E+00
Urbanization
Central City
378000
15
0.67
*
*
*
Nonmetropolitan
466000
37
1.04
6.43E-01
8.96E-02
0.00E+00
9.24E-02
1.02E-01
2.51 E-01
4.39E-01
1.02E+00
1.31E+00
2.21 E+00
2.21 E+00
2.21 E+00
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+00
2.08E+00
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
2.51 E-01
3.95E-01
6.04E-01
1.07E+00
1.31 E+00
2.21 E+00
2.21 E+00
Region
Midwest
736000
56
1.59
4.57E-01
6.26E-02
0.00E+00
7.69E-02
9.18E-02
1.25E-01
3.00E-01
5.87E-01
1.12E+00
1.28E+00
2.21 E+00
2.21 E+00
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
0.00E+00
9.18E-02
2.00E-01
3.53E-01
5.52E-01
1.07E+00
1.28E+00
2.21 E+00
2.21 E+00
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
Nc wgtd = weighted number of consumers; Nc unwgtd =
Source: Based on EPA's analyses of the 1987-88 NFCS
unweighted number of consumers in survey.
-------
Table 13-50. Consumer Only
Intake of Homegrown Peaches (g/kg-day)
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumin
a Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
2941000
193
1.56
1.67E+00
1.70E-01
5.20E-02
1.65E-01
2.25E-01
4.74E-01
8.97E-01
1.88E+00
3.79E+00
6.36E+00
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+00
6.32E-01
9.75E-02
1.01 E-01
1.40E-01
6.25E-01
1.13E+00
6.36E+00
8.53E+00
8.53E+00
1.15E+01
1.15E+01
12-19
177000
13
0.86
*
*
*
*
20-39
573000
35
0.93
1.17E+00
1.74E-01
5.07E-02
5.50E-02
2.25E-01
4.74E-01
8.09E-01
1.30E+00
2.92E+00
2.99E+00
5.27E+00
5.27E+00
40-69
1076000
70
1.90
1.53E+00
2.83E-01
5.87E-02
1.90E-01
2.39E-01
5.56E-01
8.92E-01
1.61E+00
2.63E+00
4.43E+00
1.23E+01
1.23E+01
70 +
598000
33
3.77
1.01E+00
1.97E-01
9.13E-02
1.38E-01
1.79E-01
2.82E-01
8.22E-01
1.19E+00
1.60E+00
3.79E+00
7.13E+00
7.13E+00
Season
Fall
485000
19
1.02
*
*
*
*
Spring
756000
91
1.64
1.67E+00
3.04E-01
5.07E-02
5.87E-02
1.01 E-01
2.76E-01
7.74E-01
1.45E+00
4.44E+00
6.77E+00
2.23E+01
2.23E+01
Summer
1081000
35
2.38
2.26E+00
4.78E-01
1.65E-01
2.25E-01
3.61 E-01
5.67E-01
1.12E+00
2.99E+00
6.36E+00
8.53E+00
1.23E+01
1.23E+01
Winter
619000
48
1.27
1.25E+00
1.03E-01
3.52E-02
2.39E-01
5.56E-01
7.79E-01
1.04E+00
1.71E+00
2.35E+00
2.60E+00
3.56E+00
3.56E+00
Urbanization
Central City
429000
12
0.76
*
*
*
*
Nonmetropolitan
1110000
99
2.47
1.87E+00
2.59E-01
5.87E-02
2.62E-01
3.93E-01
6.46E-01
1.02E+00
2.18E+00
3.86E+00
6.36E+00
1.15E+01
2.23E+01
Suburban
1402000
82
1.62
1.47E+00
1.75E-01
5.07E-02
1.40E-01
2.04E-01
4.61 E-01
9.20E-01
1.87E+00
3.79E+00
4.43E+00
7.37E+00
7.37E+00
Race
Black
39000
1
0.18
*
*
*
*
White
2861000
191
1.82
1.70E+00
1.73E-01
5.20E-02
1.65E-01
2.30E-01
5.03E-01
8.97E-01
1.96E+00
3.79E+00
6.36E+00
1.23E+01
2.23E+01
Region
Midwest
824000
75
1.78
1.39E+00
2.91 E-01
1.76E-01
2.20E-01
2.59E-01
4.60E-01
7.40E-01
1.19E+00
3.06E+00
3.56E+00
1.15E+01
2.23E+01
Northeast
75000
5
0.18
*
*
*
*
South
852000
51
1.32
1.67E+00
2.57E-01
3.52E-02
1.38E-01
1.79E-01
6.43E-01
1.02E+00
1.96E+00
3.83E+00
6.36E+00
8.53E+00
8.53E+00
West
1190000
62
3.30
1.80E+00
3.26E-01
5.07E-02
1.40E-01
2.25E-01
4.68E-01
8.63E-01
1.94E+00
4.43E+00
7.37E+00
1.23E+01
1.23E+01
Response to Questionnaire
Households who garden
2660000
174
3.90
1.75E+00
1.85E-01
5.20E-02
1.66E-01
2.59E-01
5.26E-01
9.25E-01
1.96E+00
3.79E+00
6.36E+00
1.23E+01
2.23E+01
Households who farm
769000
54
10.49
1.56E+00
2.49E-01
6.79E-02
1.76E-01
2.26E-01
4.61 E-01
9.02E-01
2.02E+00
2.99E+00
6.36E+00
8.53E+00
8.53E+00
* Intake data not provided for subpopulations for which there were less than 20 observations
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd =
Source: Based on EPA's analyses of the 1987-88 NFCS
unweighted number of consumers in survey.
-------
Table 13-51. Consumer Only
Intake of Homegrown Pears (g/kg-day)
Population
Nc
Nc
%
Grouo
watd
unwatc
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
1513000
94
0.80
9.37E-01
9.68E-02
1.01 E-01
1.84E-01
2.38E-01
4.28E-01
6.82E-01
1.09E+00
1.60E+00
2.76E+00
5.16E+00
5.16E+00
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+00
1.24E+00
1.24E+00
1.24E+00
40-69
557000
33
0.98
6.57E-01
5.53E-02
1.01 E-01
1.08E-01
3.33E-01
4.23E-01
6.45E-01
9.22E-01
1.10E+00
1.13E+00
1.51E+00
1.51E+00
70 +
256000
15
1.61
*
*
*
*
*
*
Season
Fall
308000
11
0.65
*
*
*
*
*
*
Spring
355000
39
0.77
6.87E-01
7.89E-02
1.01 E-01
1.13E-01
1.82E-01
3.38E-01
6.02E-01
8.66E-01
1.15E+00
1.83E+00
2.54E+00
2.54E+00
Summer
474000
16
1.04
*
*
*
*
*
*
Winter
376000
28
0.77
1.48E+00
2.77E-01
1.08E-01
1.08E-01
3.79E-01
6.45E-01
9.49E-01
1.38E+00
4.82E+00
5.16E+00
5.16E+00
5.16E+00
Urbanization
Central City
222000
11
0.39
*
*
*
*
*
*
Nonmetropolitan
634000
44
1.41
7.81 E-01
8.52E-02
3.33E-01
3.52E-01
4.19E-01
4.43E-01
5.70E-01
8.13E-01
1.56E+00
1.86E+00
2.88E+00
2.88E+00
Suburban
657000
39
0.76
8.50E-01
1.17E-01
1.01 E-01
1.08E-01
1.82E-01
3.89E-01
7.29E-01
1.10E+00
1.50E+00
2.57E+00
4.79E+00
4.79E+00
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
7.01 E-01
1.09E+00
1.60E+00
2.88E+00
5.16E+00
5.16E+00
Region
Midwest
688000
57
1.48
8.71 E-01
9.49E-02
2.22E-01
3.38E-01
3.76E-01
4.43E-01
6.45E-01
1.04E+00
1.60E+00
2.57E+00
4.79E+00
4.79E+00
Northeast
18000
2
0.04
*
*
*
*
*
*
South
377000
13
0.59
*
*
*
*
*
*
West
430000
22
1.19
1.14E+00
2.89E-01
1.01 E-01
1.08E-01
1.13E-01
3.56E-01
7.52E-01
1.13E+00
2.76E+00
4.82E+00
5.16E+00
5.16E+00
Response to Questionnaire
Households who garden
1312000
85
1.93
9.45E-01
1.04E-01
1.01 E-01
1.82E-01
3.52E-01
4.31 E-01
6.75E-01
1.09E+00
1.56E+00
2.88E+00
5.16E+00
5.16E+00
Households who farm
528000
35
7.20
1.09E+00
2.10E-01
1.08E-01
2.22E-01
3.76E-01
4.28E-01
6.14E-01
1.09E+00
2.76E+00
4.82E+00
5.16E+00
5.16E+00
* Intake data not provided for subpopulations for which there were less than 20 observations
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd =
Source: Based on EPA's analyses of the 1987-88 NFCS
unweighted number of consumers in survey.
-------
Table 13-52. Consumer Only Intake of Homegrown Peas
(g/kg-dav)
Population
Nc
Nc
%
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
3.21 E-01
6.22E-01
1.04E+00
1.46E+00
2.66E+00
2.89E+00
Age
01-02
163000
9
2.86
*
*
*
*
*
03-05
140000
7
1.73
*
*
*
*
*
06-11
515000
26
3.08
6.05E-01
8.91 E-02
1.54E-01
1.54E-01
2.18E-01
3.04E-01
3.87E-01
9.00E-01
1.35E+00
1.40E+00
2.06E+00
2.06E+00
12-19
377000
22
1.84
4.08E-01
4.28E-02
5.81 E-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
6.21 E-02
9.96E-02
1.15E-01
1.40E-01
1.80E-01
2.54E-01
4.06E-01
8.47E-01
1.36E+00
2.71 E+00
2.71 E+00
40-69
1366000
80
2.41
4.58E-01
4.61 E-02
6.78E-02
1.02E-01
1.20E-01
2.26E-01
3.04E-01
6.10E-01
9.95E-01
1.30E+00
2.36E+00
2.36E+00
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+00
1.46E+00
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
5.81 E-02
1.08E-01
1.18E-01
1.90E-01
3.26E-01
5.16E-01
9.19E-01
1.40E+00
2.06E+00
2.06E+00
Summer
1516000
51
3.33
5.85E-01
7.36E-02
6.78E-02
1.27E-01
1.74E-01
2.24E-01
3.87E-01
8.22E-01
1.35E+00
1.60E+00
2.66E+00
2.66E+00
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+00
2.36E+00
2.89E+00
2.89E+00
Urbanization
Central City
558000
19
0.99
*
*
*
*
*
Nonmetropolitan
2028000
126
4.50
4.81 E-01
3.55E-02
8.42E-02
1.36E-01
1.74E-01
2.48E-01
3.53E-01
5.79E-01
1.04E+00
1.36E+00
1.89E+00
2.89E+00
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+00
2.28E+00
2.36E+00
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+00
2.66E+00
2.89E+00
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+00
2.71 E+00
2.89E+00
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+00
1.60E+00
2.66E+00
2.66E+00
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+00
1.40E+00
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
3.21 E-01
6.28E-01
1.04E+00
1.54E+00
2.66E+00
2.89E+00
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+00
1.60E+00
2.89E+00
* Intake data not provided for subpopulations for which there were less than 20 observations
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-88 NFCS
-------
Table 13-53. Consumer Only Intake of Homeg
rown Pepp
srs (q/kq-day)
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
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+00
0.00E+00
3.03E-02
8.99E-02
1.62E-01
2.98E-01
4.25E-01
7.70E-01
8.45E-01
8.45E-01
12-19
342000
16
1.67
*
*
*
*
*
*
20-39
1048000
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
2.48E+00
2.48E+00
40-69
2221000
88
3.92
2.50E-01
2.78E-02
5.32E-03
3.40E-02
4.52E-02
7.58E-02
1.66E-01
3.21 E-01
4.77E-01
7.44E-01
1.50E+00
1.50E+00
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+00
1.07E+00
Season
Fall
1726000
53
3.62
1.97E-01
2.51 E-02
0.00E+00
3.26E-02
4.05E-02
8.55E-02
1.66E-01
2.39E-01
3.49E-01
3.97E-01
1.07E+00
1.07E+00
Spring
255000
28
0.55
2.95E-01
7.15E-02
0.00E+00
1.73E-02
3.86E-02
6.93E-02
1.47E-01
3.21 E-01
1.09E+00
1.20E+00
1.53E+00
1.53E+00
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
3.61 E-01
9.39E-01
1.10E+00
1.10E+00
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
2.48E+00
2.48E+00
Suburban
2246000
87
2.59
2.47E-01
3.00E-02
0.00E+00
2.70E-02
3.50E-02
8.55E-02
1.60E-01
2.91 E-01
4.90E-01
9.73E-01
1.50E+00
1.53E+00
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
2.91 E-01
4.90E-01
9.24E-01
1.81E+00
2.48E+00
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+00
2.48E+00
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+00
1.81E+00
West
778000
29
2.16
2.13E-01
5.04E-02
1.73E-02
2.30E-02
2.70E-02
4.05E-02
8.58E-02
2.53E-01
5.37E-01
9.24E-01
1.07E+00
1.07E+00
Response to Questionnaire
Households who garden
4898000
199
7.19
2.35E-01
2.09E-02
0.00E+00
2.22E-02
3.40E-02
7.58E-02
1.54E-01
2.85E-01
4.77E-01
8.45E-01
1.50E+00
2.48E+00
Households who farm
867000
35
11.83
3.03E-01
7.50E-02
0.00E+00
2.70E-02
2.96E-02
7.11 E-02
1.66E-01
3.55E-01
6.00E-01
8.45E-01
2.48E+00
2.48E+00
* Intake data not provided for subpopulations for which there were less than 20 observations
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd =
Source: Based on EPA's analyses of the 1987-88 NFCS
unweighted number of consumers in survey
-------
Table 13-54. Consumer Only
Intake of Home Produced Pork
(g/kg-dav)
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
1732000
121
0.92
1.23E+00
9.63E-02
9.26E-02
1.40E-01
3.05E-01
5.41 E-01
8.96E-01
1.71E+00
2.73E+00
3.37E+00
4.93E+00
7.41 E+00
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+00
2.42E-01
3.05E-01
3.23E-01
3.37E-01
5.24E-01
8.85E-01
1.75E+00
3.69E+00
3.69E+00
4.29E+00
4.29E+00
20-39
511000
32
0.83
1.21E+00
1.80E-01
1.11E-01
2.83E-01
4.09E-01
5.52E-01
7.89E-01
1.43E+00
2.90E+00
3.08E+00
4.93E+00
4.93E+00
40-69
557000
38
0.98
1.02E+00
1.15E-01
1.19E-01
1.81E-01
2.22E-01
4.05E-01
8.11 E-01
1.71E+00
1.78E+00
2.28E+00
3.16E+00
3.16E+00
70 +
180000
12
1.13
*
*
*
*
*
*
*
Season
Fall
362000
13
0.76
*
*
*
*
*
*
*
Spring
547000
59
1.19
1.13E+00
1.29E-01
1.11E-01
1.40E-01
2.22E-01
3.52E-01
8.96E-01
1.50E+00
2.68E+00
3.68E+00
4.29E+00
4.29E+00
Summer
379000
15
0.83
*
*
*
*
*
*
*
Winter
444000
34
0.91
1.40E+00
2.39E-01
1.26E-01
2.58E-01
3.77E-01
5.03E-01
8.83E-01
2.21 E+00
3.08E+00
4.93E+00
7.41 E+00
7.41 E+00
Urbanization
Central City
90000
2
0.16
*
*
*
*
*
*
*
Nonmetropolitan
1178000
77
2.62
1.39E+00
1.31E-01
9.26E-02
2.15E-01
4.05E-01
6.17E-01
9.66E-01
1.75E+00
3.16E+00
3.69E+00
4.93E+00
7.41 E+00
Suburban
464000
42
0.54
8.77E-01
1.20E-01
1.11E-01
1.19E-01
1.81E-01
3.31 E-01
5.89E-01
1.10E+00
2.28E+00
2.73E+00
2.90E+00
2.90E+00
Race
Black
0
0
0.00
White
1732000
121
1.10
1.23E+00
9.63E-02
9.26E-02
1.40E-01
3.05E-01
5.41 E-01
8.96E-01
1.71 E+00
2.73E+00
3.37E+00
4.93E+00
7.41 E+00
Region
Midwest
844000
64
1.82
1.06E+00
1.19E-01
9.26E-02
1.19E-01
2.13E-01
5.02E-01
6.72E-01
1.20E+00
2.68E+00
3.37E+00
3.69E+00
3.73E+00
Northeast
97000
5
0.24
*
*
*
*
*
*
*
South
554000
32
0.86
1.35E+00
1.46E-01
1.81E-01
2.58E-01
3.37E-01
8.11 E-01
1.26E+00
1.75E+00
2.44E+00
3.08E+00
4.29E+00
4.29E+00
West
237000
20
0.66
1.15E+00
3.09E-01
1.26E-01
3.23E-01
3.77E-01
4.40E-01
7.29E-01
1.10E+00
1.75E+00
2.73E+00
7.41 E+00
7.41 E+00
Response to Questionnaire
Households who raise animals
1428000
100
14.14
1.34E+00
9.86E-02
1.40E-01
3.23E-01
4.05E-01
5.89E-01
9.66E-01
1.75E+00
2.90E+00
3.37E+00
4.29E+00
4.93E+00
Households who farm
1218000
82
16.62
1.30E+00
1.11E-01
2.15E-01
3.42E-01
4.08E-01
5.85E-01
9.24E-01
1.71 E+00
3.08E+00
3.69E+00
4.93E+00
4.93E+00
* Intake data not provided for subpopulations for which there were less than 20 observations
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-88 NFCS
-------
Table 13-55. Consumer Only Intake of Home Produced Poultry (q/kq-dav)
Population
Nc
Nc
%
Grouo
wqtd
unwqtd
Consuminq
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
1816000
105
0.97
1.57E+00
1.15E-01
1.95E-01
3.03E-01
4.18E-01
6.37E-01
1.23E+00
2.19E+00
3.17E+00
3.83E+00
5.33E+00
6.17E+00
Age
01-02
91000
8
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+00
1.47E-01
1.73E-01
4.02E-01
4.02E-01
5.57E-01
1.15E+00
1.37E+00
1.80E+00
2.93E+00
4.59E+00
4.59E+00
40-69
568000
30
1.00
1.51E+00
2.43E-01
1.95E-01
1.97E-01
3.03E-01
4.91 E-01
7.74E-01
2.69E+00
3.29E+00
4.60E+00
5.15E+00
5.15E+00
70 +
80000
3
0.50
*
*
*
*
Season
Fall
562000
23
1.18
1.52E+00
1.75E-01
4.07E-01
4.18E-01
4.60E-01
8.11E-01
1.39E+00
2.23E+00
2.69E+00
3.17E+00
3.17E+00
3.17E+00
Spring
374000
34
0.81
1.87E+00
2.79E-01
1.73E-01
2.28E-01
3.03E-01
5.22E-01
1.38E+00
3.29E+00
4.60E+00
5.15E+00
5.33E+00
5.33E+00
Summer
312000
11
0.69
*
*
*
*
Winter
568000
37
1.17
1.55E+00
2.00E-01
1.95E-01
1.97E-01
4.33E-01
5.95E-01
1.23E+00
2.18E+00
2.95E+00
3.47E+00
6.17E+00
6.17E+00
Urbanization
Central City
230000
8
0.41
*
*
*
*
Nonmetropolitan
997000
56
2.21
1.48E+00
1.32E-01
1.95E-01
2.82E-01
4.07E-01
6.72E-01
1.19E+00
2.10E+00
3.17E+00
3.29E+00
3.86E+00
5.33E+00
Suburban
589000
41
0.68
1.94E+00
2.30E-01
2.28E-01
2.67E-01
4.33E-01
6.24E-01
1.59E+00
2.69E+00
4.59E+00
4.83E+00
6.17E+00
6.17E+00
Race
Black
44000
2
0.20
*
*
*
*
White
1772000
103
1.12
1.57E+00
1.17E-01
1.95E-01
3.03E-01
4.18E-01
6.24E-01
1.23E+00
2.19E+00
3.17E+00
3.86E+00
5.33E+00
6.17E+00
Region
Midwest
765000
41
1.65
1.60E+00
1.40E-01
4.07E-01
4.18E-01
5.57E-01
9.79E-01
1.39E+00
2.19E+00
2.70E+00
3.17E+00
3.86E+00
5.33E+00
Northeast
64000
4
0.16
*
*
*
*
South
654000
38
1.02
1.67E+00
2.50E-01
1.73E-01
1.97E-01
3.03E-01
4.60E-01
9.08E-01
2.11E+00
4.59E+00
4.83E+00
6.17E+00
6.17E+00
West
333000
22
0.92
1.24E+00
1.80E-01
2.67E-01
2.67E-01
4.27E-01
5.60E-01
1.02E+00
1.89E+00
2.45E+00
2.93E+00
2.93E+00
2.93E+00
Response to Questionnaire
Households who raise animals
1333000
81
13.20
1.58E+00
1.18E-01
2.28E-01
4.07E-01
4.72E-01
7.09E-01
1.37E+00
2.19E+00
2.93E+00
3.29E+00
5.33E+00
6.17E+00
Households who farm
917000
59
12.51
1.54E+00
1.79E-01
1.95E-01
2.28E-01
3.03E-01
5.95E-01
1.06E+00
2.18E+00
3.47E+00
4.83E+00
6.17E+00
6.17E+00
* Intake data not provided for subpopulations for which there were less than 20 observations
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd
Source: Based on EPA's analyses of the 1987-88 NFCS
= unweighted number of consumers in survey.
-------
Table 13-56. Consumer Only Intake of Homeg
rown Pumpkins ("g/kg-day")
Population
Nc
Nc
%
Grouo
watd u
nwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
2041000
87
1.09
7.78E-01
6.83E-02
1.25E-01
1.84E-01
2.41 E-01
3.18E-01
5.55E-01
1.07E+00
1.47E+00
1.79E+00
3.02E+00
4.48E+00
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
8.01 E-01
1.29E-01
1.76E-01
1.84E-01
3.01 E-01
3.77E-01
4.77E-01
1.03E+00
1.73E+00
2.67E+00
2.67E+00
2.67E+00
40-69
415000
20
0.73
8.22E-01
1.57E-01
2.86E-01
2.86E-01
3.16E-01
3.71 E-01
5.23E-01
9.62E-01
1.47E+00
3.02E+00
3.02E+00
3.02E+00
70 +
373000
15
2.35
*
*
*
*
*
*
*
*
*
Season
Fall
1345000
49
2.82
8.19E-01
8.91 E-02
1.25E-01
1.76E-01
2.81 E-01
3.71 E-01
6.14E-01
1.17E+00
1.73E+00
1.79E+00
3.02E+00
3.02E+00
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
2.41 E-01
2.81 E-01
3.77E-01
9.40E-01
1.24E+00
1.33E+00
2.24E+00
2.24E+00
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+00
1.45E+00
4.48E+00
4.48E+00
Suburban
613000
23
0.71
1.10E+00
1.34E-01
2.86E-01
2.88E-01
3.01 E-01
4.67E-01
1.04E+00
1.47E+00
1.79E+00
2.67E+00
2.67E+00
2.67E+00
Race
Black
22000
1
0.10
*
*
*
*
*
*
*
*
*
White
2019000
86
1.28
7.82E-01
6.90E-02
1.25E-01
1.84E-01
2.41 E-01
3.16E-01
5.55E-01
1.10E+00
1.47E+00
1.79E+00
3.02E+00
4.48E+00
Region
Midwest
1370000
54
2.95
8.21 E-01
9.68E-02
1.25E-01
2.34E-01
2.41 E-01
3.18E-01
5.72E-01
1.04E+00
1.73E+00
2.67E+00
3.02E+00
4.48E+00
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
3.71 E-01
7.44E-01
1.17E+00
1.47E+00
1.51E+00
1.51E+00
1.51E+00
Response to Questionnaire
Households who garden
1987000
85
2.92
7.70E-01
6.93E-02
1.25E-01
1.84E-01
2.41 E-01
3.16E-01
5.55E-01
1.04E+00
1.46E+00
1.79E+00
3.02E+00
4.48E+00
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
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-88 NFCS
-------
Table 13-57. Consumer Only Intake of Homeg
rown Snap Beans (g/kg-dav)
Population
Nc
Nc
%
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+00
1.58E+00
2.01 E+00
3.90E+00
9.96E+00
Age
01-02
246000
17
4.32
*
*
*
*
03-05
455000
32
5.62
1.49E+00
2.37E-01
0.00E+00
0.00E+00
3.49E-01
9.01 E-01
1.16E+00
1.66E+00
3.20E+00
4.88E+00
6.90E+00
6.90E+00
06-11
862000
62
5.16
8.97E-01
1.15E-01
0.00E+00
1.99E-01
2.21 E-01
3.21 E-01
6.42E-01
1.21E+00
1.79E+00
2.75E+00
4.81 E+00
5.66E+00
12-19
1151000
69
5.62
6.38E-01
6.10E-02
0.00E+00
1.61 E-01
2.22E-01
3.20E-01
5.04E-01
8.11 E-01
1.34E+00
1.79E+00
2.72E+00
2.72E+00
20-39
2677000
160
4.35
6.13E-01
4.09E-02
7.05E-02
1.31 E-01
1.57E-01
2.60E-01
4.96E-01
7.85E-01
1.24E+00
1.64E+00
2.05E+00
4.26E+00
40-69
4987000
292
8.79
7.19E-01
3.20E-02
9.99E-02
1.61 E-01
2.28E-01
3.62E-01
5.61 E-01
8.59E-01
1.45E+00
1.77E+00
2.70E+00
4.23E+00
70 +
1801000
100
11.34
9.15E-01
1.16E-01
5.65E-02
7.44E-02
1.51 E-01
3.69E-01
6.38E-01
1.22E+00
1.70E+00
2.01 E+00
9.96E+00
9.96E+00
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+00
1.52E+00
2.01 E+00
4.82E+00
9.96E+00
Spring
2706000
288
5.86
9.00E-01
5.44E-02
2.93E-02
1.51 E-01
2.19E-01
3.70E-01
5.91 E-01
1.11E+00
1.72E+00
2.85E+00
5.66E+00
6.90E+00
Summer
2946000
98
6.48
6.33E-01
4.81 E-02
0.00E+00
1.18E-01
1.57E-01
3.31 E-01
5.04E-01
8.50E-01
1.30E+00
1.70E+00
2.05E+00
2.63E+00
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+00
1.72E+00
2.02E+00
3.85E+00
7.88E+00
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+00
1.54E+00
1.93E+00
3.35E+00
Nonmetropolitan
5696000
404
12.65
9.61 E-01
5.06E-02
9.35E-02
1.77E-01
2.29E-01
3.67E-01
6.75E-01
1.19E+00
1.89E+00
2.70E+00
4.88E+00
9.96E+00
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+00
1.77E+00
2.98E+00
6.08E+00
Race
Black
634000
36
2.92
7.55E-01
1.43E-01
2.51 E-01
2.51 E-01
2.79E-01
2.99E-01
4.78E-01
1.04E+00
1.30E+00
1.34E+00
5.98E+00
5.98E+00
White
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+00
1.63E+00
2.01 E+00
3.90E+00
9.96E+00
Region
Midwest
4651000
307
10.02
8.60E-01
6.11 E-02
7.44E-02
1.54E-01
1.89E-01
3.36E-01
5.50E-01
9.88E-01
1.70E+00
2.47E+00
4.88E+00
9.96E+00
Northeast
990000
52
2.40
5.66E-01
6.63E-02
0.00E+00
9.66E-02
1.06E-01
1.81 E-01
4.91 E-01
8.15E-01
1.28E+00
1.36E+00
1.97E+00
3.09E+00
South
4755000
286
7.39
8.82E-01
4.04E-02
1.33E-01
2.13E-01
2.51 E-01
3.98E-01
6.75E-01
1.22E+00
1.72E+00
2.01 E+00
3.23E+00
5.98E+00
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
7.41 E-01
1.20E+00
1.52E+00
2.19E+00
2.19E+00
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
3.31 E-01
5.63E-01
1.02E+00
1.60E+00
2.01 E+00
3.85E+00
9.96E+00
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+00
1.54E+00
1.98E+00
2.96E+00
4.23E+00
* Intake data not provided for subpopulations for which there were less than 20 observations
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-88 NFCS
-------
Table 13-58. Consumer Only Intake of Homeg
rown Strawberries fg/kg-day)
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
Mean
SE
P1
P5
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+00
1.77E+00
2.72E+00
4.83E+00
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
3.21 E-01
6.41 E-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+00
1.56E+00
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+00
1.47E+00
2.37E+00
2.37E+00
70 +
449000
27
2.83
6.36E-01
1.11 E-01
4.15E-02
4.41 E-02
8.64E-02
2.62E-01
4.69E-01
7.00E-01
1.66E+00
1.89E+00
2.72E+00
2.72E+00
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+00
2.54E+00
4.83E+00
4.83E+00
Summer
388000
11
0.85
*
*
*
*
Winter
821000
54
1.69
5.13E-01
6.42E-02
2.44E-02
4.41 E-02
1.05E-01
2.07E-01
3.86E-01
6.01 E-01
1.27E+00
1.46E+00
2.37E+00
2.37E+00
Urbanization
Central City
505000
23
0.90
7.54E-01
1.22E-01
4.15E-02
4.41 E-02
8.92E-02
3.82E-01
4.88E-01
1.33E+00
1.47E+00
1.69E+00
2.37E+00
2.37E+00
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+00
2.16E+00
4.83E+00
4.83E+00
Suburban
888000
64
1.03
6.20E-01
5.88E-02
7.92E-02
1.81 E-01
2.21 E-01
3.45E-01
5.30E-01
6.96E-01
1.27E+00
1.56E+00
2.97E+00
2.97E+00
Race
Black
0
0
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+00
1.77E+00
2.72E+00
4.83E+00
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+00
1.66E+00
1.93E+00
2.97E+00
4.83E+00
Northeast
382000
25
0.93
6.35E-01
1.01 E-01
8.92E-02
1.59E-01
1.82E-01
2.55E-01
4.67E-01
8.65E-01
1.46E+00
1.83E+00
2.16E+00
2.16E+00
South
333000
23
0.52
6.69E-01
8.41 E-02
1.33E-01
2.05E-01
3.77E-01
5.15E-01
6.21 E-01
6.96E-01
1.00E+00
1.00E+00
2.72E+00
2.72E+00
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+00
1.77E+00
2.54E+00
4.83E+00
Households who farm
87000
9
1.19
*
*
*
*
* Intake data not provided for subpopulations for which there were less than 20 observations
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc 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 Homegrown Tomatoes (q/kq-dav)
Population
Nc
Nc
%
Grouo
wqtd
unwqtc
Consuminq
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
16737000
743
8.90
1.18E+00
5.26E-02
7.57E-02
1.52E-01
2.34E-01
3.92E-01
7.43E-01
1.46E+00
2.50E+00
3.54E+00
7.26E+00
1.93E+01
Age
01-02
572000
26
10.04
3.14E+00
5.30E-01
7.26E-01
8.55E-01
9.34E-01
1.23E+00
1.66E+00
4.00E+00
7.26E+00
1.07E+01
1.07E+01
1.07E+01
03-05
516000
26
6.37
1.61E+00
2.65E-01
4.96E-01
5.07E-01
5.07E-01
7.54E-01
1.25E+00
1.65E+00
3.00E+00
6.25E+00
6.25E+00
6.25E+00
06-11
1093000
51
6.54
1.63E+00
2.68E-01
2.17E-01
3.10E-01
3.92E-01
5.30E-01
7.55E-01
1.66E+00
5.20E+00
5.70E+00
9.14E+00
9.14E+00
12-19
1411000
61
6.89
7.15E-01
8.52E-02
0.00E+00
0.00E+00
1.82E-01
2.68E-01
5.21 E-01
8.50E-01
1.67E+00
1.94E+00
3.39E+00
3.39E+00
20-39
4169000
175
6.77
8.54E-01
1.03E-01
7.32E-02
1.31E-01
1.47E-01
2.54E-01
5.15E-01
1.00E+00
1.83E+00
2.10E+00
5.52E+00
1.93E+01
40-69
6758000
305
11.92
1.05E+00
5.23E-02
1.13E-01
1.73E-01
2.81 E-01
3.97E-01
7.46E-01
1.41E+00
2.40E+00
3.05E+00
4.50E+00
5.00E+00
70 +
1989000
89
12.53
1.26E+00
9.40E-02
1.13E-01
2.36E-01
2.98E-01
4.82E-01
1.14E+00
1.77E+00
2.51 E+00
2.99E+00
3.67E+00
3.67E+00
Season
Fall
5516000
201
11.57
1.02E+00
8.55E-02
7.32E-02
1.35E-01
2.23E-01
3.43E-01
5.95E-01
1.34E+00
2.24E+00
2.87E+00
6.25E+00
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
6.31 E-01
1.11E+00
1.75E+00
2.00E+00
3.79E+00
5.28E+00
Summer
8122000
279
17.86
1.30E+00
8.75E-02
1.05E-01
1.66E-01
2.36E-01
4.08E-01
8.03E-01
1.55E+00
3.05E+00
4.05E+00
7.26E+00
1.09E+01
Winter
1835000
136
3.77
1.37E+00
1.77E-01
9.07E-02
2.07E-01
2.85E-01
4.97E-01
8.29E-01
1.49E+00
2.48E+00
3.38E+00
8.29E+00
1.93E+01
Urbanization
Central City
2680000
90
4.76
1.10E+00
1.27E-01
0.00E+00
1.52E-01
2.25E-01
3.54E-01
7.54E-01
1.51E+00
2.16E+00
2.95E+00
7.26E+00
8.29E+00
Nonmetropolitan
7389000
378
16.41
1.26E+00
7.35E-02
1.13E-01
2.16E-01
2.62E-01
4.23E-01
7.62E-01
1.47E+00
2.77E+00
3.85E+00
6.87E+00
1.07E+01
Suburban
6668000
275
7.70
1.13E+00
9.14E-02
7.57E-02
1.35E-01
1.78E-01
3.70E-01
6.68E-01
1.38E+00
2.35E+00
3.32E+00
5.52E+00
1.93E+01
Race
Black
743000
28
3.42
6.14E-01
8.60E-02
0.00E+00
0.00E+00
7.32E-02
2.36E-01
5.07E-01
9.02E-01
1.18E+00
1.55E+00
1.66E+00
1.66E+00
White
15658000
703
9.94
1.22E+00
5.54E-02
1.05E-01
1.68E-01
2.41 E-01
4.06E-01
7.55E-01
1.49E+00
2.55E+00
3.59E+00
7.26E+00
1.93E+01
Region
Midwest
6747000
322
14.54
1.18E+00
8.91 E-02
6.34E-02
1.45E-01
2.06E-01
3.62E-01
6.82E-01
1.41E+00
2.51 E+00
3.69E+00
6.87E+00
1.93E+01
Northeast
2480000
87
6.02
1.17E+00
1.64E-01
7.57E-02
1.35E-01
1.48E-01
3.50E-01
7.51 E-01
1.38E+00
2.44E+00
3.52E+00
1.09E+01
1.09E+01
South
4358000
202
6.77
1.15E+00
9.07E-02
0.00E+00
2.07E-01
2.53E-01
4.23E-01
7.46E-01
1.43E+00
2.32E+00
3.67E+00
6.82E+00
9.14E+00
West
3152000
132
8.74
1.23E+00
9.90E-02
1.80E-01
2.39E-01
2.84E-01
4.11 E-01
7.65E-01
1.84E+00
2.78E+00
3.08E+00
7.26E+00
7.26E+00
Response to Questionnaire
Households who garden
14791000
661
21.70
1.21E+00
5.70E-02
7.57E-02
1.52E-01
2.34E-01
4.06E-01
7.58E-01
1.50E+00
2.51 E+00
3.52E+00
7.26E+00
1.93E+01
Households who farm
2269000
112
30.96
1.42E+00
1.58E-01
0.00E+00
1.80E-01
2.26E-01
4.23E-01
7.66E-01
1.86E+00
3.55E+00
5.20E+00
9.14E+00
9.14E+00
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd =
Source: Based on EPA's analyses of the 1987-88 NFCS
unweighted number of consumers in survey
-------
Table 13-
30. Consumer Only Intake of Homeg
own White Potatoes fg/kg-day)
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
5895000
281
3.14
1.66E+00
1.05E-01
0.00E+00
1.87E-01
3.08E-01
5.50E-01
1.27E+00
2.07E+00
3.11 E+00
4.76E+00
9.52E+00
1.28E+01
Age
01-02
147000
10
2.58
*
*
*
03-05
119000
6
1.47
*
*
*
06-11
431000
24
2.58
2.19E+00
3.85E-01
0.00E+00
0.00E+00
4.10E-01
7.20E-01
1.76E+00
3.10E+00
5.94 E+00
6.52E+00
6.52E+00
6.52E+00
12-19
751000
31
3.67
1.26E+00
1.85E-01
6.67E-02
1.87E-01
2.59E-01
3.84E-01
1.22E+00
1.80 E+00
2.95 E+00
3.11 E+00
4.14E+00
4.14E+00
20-39
1501000
66
2.44
1.24E+00
1.21 E-01
1.64E-01
1.64E-01
1.96E-01
4.77E-01
1.00E+00
1.62 E+00
2.54 E+00
3.08 E+00
4.29E+00
5.09E+00
40-69
1855000
95
3.27
1.86E+00
2.29E-01
1.27E-01
2.62E-01
3.50E-01
6.99E-01
1.31 E+00
2.04 E+00
3.43 E+00
5.29 E+00
1.28E+01
1.28E+01
70 +
1021000
45
6.43
1.27E+00
1.22E-01
2.06E-01
2.17E-01
3.57E-01
5.50E-01
1.21 E+00
1.69 E+00
2.35 E+00
2.88E+00
3.92E+00
3.92E+00
Season
Fall
2267000
86
4.76
1.63E+00
2.23E-01
1.64E-01
2.23E-01
2.65E-01
4.61 E-01
1.13E+00
1.79E+00
3.43 E+00
4.14E+00
1.28E+01
1.28E+01
Spring
527000
58
1.14
1.23E+00
1.28E-01
6.67E-02
1.05E-01
1.96E-01
4.10E-01
8.55E-01
1.91 E+00
2.86 E+00
3.08E+00
4.28E+00
4.28E+00
Summer
2403000
81
5.28
1.63E+00
1.82E-01
0.00E+00
1.87E-01
3.19E-01
6.20E-01
1.32E+00
2.09 E+00
3.08 E+00
5.29E+00
9.43E+00
9.43E+00
Winter
698000
56
1.43
2.17E+00
1.98E-01
1.41 E-01
3.95E-01
4.97E-01
8.64E-01
2.02 E+00
2.95 E+00
4.26 E+00
5.40E+00
6.00E+00
6.00E+00
Urbanization
Central City
679000
25
1.20
9.60E-01
1.51 E-01
1.64E-01
1.64E-01
1.75E-01
3.75E-01
5.55E-01
1.52E+00
2.07E+00
2.25E+00
2.54E+00
2.54E+00
Nonmetropolitan
3046000
159
6.77
1.96E+00
1.55E-01
1.84E-01
2.65E-01
3.68E-01
7.67E-01
1.50 E+00
2.38 E+00
3.55 E+00
5.64E+00
1.28E+01
1.28E+01
Suburban
2110000
95
2.44
1.49E+00
1.67E-01
1.05E-01
1.87E-01
3.19E-01
5.40E-01
9.29E-01
1.68 E+00
3.11 E+00
4.76E+00
9.43E+00
9.43E+00
Race
Black
140000
5
0.64
*
*
*
White
5550000
269
3.52
1.67E+00
1.09E-01
1.41 E-01
2.06E-01
3.08E-01
5.50E-01
1.28E+00
2.09 E+00
3.11 E+00
4.76E+00
9.52E+00
1.28E+01
Region
Midwest
2587000
133
5.58
1.77E+00
1.47E-01
1.75E-01
2.36E-01
3.39E-01
6.41 E-01
1.35 E+00
2.15E+00
3.77 E+00
5.29E+00
9.43E+00
9.43E+00
Northeast
656000
31
1.59
1.28E+00
2.04E-01
6.67E-02
1.27E-01
1.67E-01
3.48E-01
8.64E-01
1.97E+00
2.95 E+00
3.80E+00
5.09E+00
5.09E+00
South
1796000
84
2.79
2.08E+00
2.39E-01
1.64E-01
3.50E-01
4.61 E-01
9.24E-01
1.56 E+00
2.40 E+00
3.44 E+00
5.64E+00
1.28E+01
1.28E+01
West
796000
31
2.21
7.61 E-01
1.05E-01
1.64E-01
2.16E-01
2.59E-01
4.11 E-01
5.43E-01
9.63E-01
1.40 E+00
1.95E+00
3.11 E+00
3.11 E+00
Response to Questionnaire
Households who garden
5291000
250
7.76
1.65E+00
1.09E-01
0.00E+00
2.06E-01
3.08E-01
5.55E-01
1.28E+00
2.09 E+00
3.10E+00
4.28E+00
9.52E+00
1.28E+01
Households who farm
1082000
62
14.76
1.83E+00
1.78E-01
6.67E-02
2.06E-01
5.76E-01
9.24E-01
1.46 E+00
2.31 E+00
3.80 E+00
5.09E+00
6.52E+00
6.52E+00
* Intake data not provided for subpopulations for which there were less than 20 observations
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc 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 Homeg
rown Exposed
Fruit (g/kg-day)
Population
Nc
Nc
%
Grouo
watd unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
11770000
679
6.26
1.49E+00
8.13E-02
4.41 E-02
1.37E-01
2.55E-01
4.46E-01
8.33E-01
1.70E+00
3.16E+00
4.78E+00
1.20E+01
3.25E+01
Age
01-02
306000
19
5.37
*
*
*
*
*
03-05
470000
30
5.80
2.60E+00
7.78E-01
0.00E+00
0.00E+00
3.73E-01
1.00E+00
1.82E+00
2.64E+00
5.41 E+00
6.07E+00
3.25E+01
3.25E+01
06-11
915000
68
5.48
2.52E+00
4.24E-01
0.00E+00
1.71E-01
3.73E-01
6.19E-01
1.11E+00
2.91 E+00
6.98E+00
1.17E+01
1.57E+01
1.59E+01
12-19
896000
50
4.37
1.33E+00
2.06E-01
8.46E-02
1.23E-01
2.58E-01
4.04E-01
6.09E-01
2.27E+00
3.41 E+00
4.78E+00
5.90E+00
5.90E+00
20-39
2521000
139
4.09
1.09E+00
1.44E-01
7.93E-02
1.30E-01
1.67E-01
3.04E-01
6.15E-01
1.07E+00
2.00E+00
3.58E+00
1.29E+01
1.29E+01
40-69
4272000
247
7.53
1.25E+00
1.10E-01
6.46E-02
1.64E-01
2.54E-01
4.39E-01
7.19E-01
1.40E+00
2.61 E+00
3.25E+00
1.30E+01
1.30E+01
70 +
2285000
118
14.39
1.39E+00
1.17E-01
4.41E-02
2.07E-01
2.82E-01
5.71 E-01
9.57E-01
1.66E+00
3.73E+00
4.42E+00
5.39E+00
7.13E+00
Season
Fall
2877000
100
6.04
1.37E+00
1.16E-01
2.59E-01
2.91 E-01
3.42E-01
5.43E-01
1.03E+00
1.88E+00
2.88E+00
4.25E+00
5.41 E+00
5.41 E+00
Spring
2466000
265
5.34
1.49E+00
1.51E-01
8.91E-02
1.98E-01
2.54E-01
4.32E-01
8.56E-01
1.65E+00
2.91 E+00
4.67E+00
8.27E+00
3.25E+01
Summer
3588000
122
7.89
1.75E+00
2.50E-01
0.00E+00
8.66E-02
1.30E-01
3.89E-01
6.41 E-01
1.76E+00
4.29E+00
6.12E+00
1.30E+01
1.57E+01
Winter
2839000
192
5.83
1.27E+00
1.06E-01
4.15E-02
1.04E-01
2.31 E-01
4.59E-01
8.29E-01
1.55E+00
2.61 E+00
4.66E+00
8.16E+00
1.13E+01
Urbanization
Central City
2552000
99
4.53
1.34E+00
1.98E-01
4.41E-02
1.01 E-01
2.59E-01
4.46E-01
8.63E-01
1.60E+00
2.37E+00
2.88E+00
1.30E+01
1.30E+01
Nonmetropolitan
3891000
269
8.64
1.78E+00
1.67E-01
6.46E-02
1.04E-01
1.67E-01
4.15E-01
9.42E-01
1.94E+00
4.07E+00
5.98E+00
1.57E+01
3.25E+01
Suburban
5267000
309
6.08
1.36E+00
9.00E-02
9.18E-02
2.07E-01
2.93E-01
4.69E-01
7.73E-01
1.65E+00
3.16E+00
4.67E+00
7.29E+00
1.29E+01
Race
Black
250000
12
1.15
*
*
*
*
*
White
11411000
663
7.24
1.51E+00
8.33E-02
6.49E-02
1.55E-01
2.59E-01
4.49E-01
8.56E-01
1.72E+00
3.31 E+00
4.78E+00
1.20E+01
3.25E+01
Region
Midwest
4429000
293
9.55
1.60E+00
1.42E-01
4.41E-02
1.25E-01
2.23E-01
4.23E-01
8.78E-01
1.88E+00
3.58E+00
4.78E+00
1.20E+01
3.25E+01
Northeast
1219000
69
2.96
7.55E-01
1.18E-01
8.08E-02
8.66E-02
1.65E-01
3.00E-01
4.74E-01
7.84E-01
1.39E+00
2.86E+00
5.21 E+00
7.13E+00
South
2532000
141
3.94
1.51E+00
1.84E-01
7.93E-02
2.32E-01
3.01 E-01
5.08E-01
9.16E-01
1.63E+00
2.63E+00
5.98E+00
1.57E+01
1.57E+01
West
3530000
174
9.79
1.60E+00
1.43E-01
1.00E-01
2.40E-01
3.17E-01
5.69E-01
9.57E-01
1.97E+00
3.72E+00
5.00E+00
1.30E+01
1.30E+01
Response to Questionnaire
Households who garden
10197000
596
14.96
1.55E+00
9.12E-02
4.15E-02
1.58E-01
2.58E-01
4.49E-01
8.78E-01
1.73E+00
3.41 E+00
5.00E+00
1.29E+01
3.25E+01
Households who farm
1917000
112
26.16
2.32E+00
2.50E-01
7.21E-02
2.76E-01
3.71 E-01
6.81 E-01
1.30E+00
3.14E+00
5.00E+00
6.12E+00
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
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-88 NFCS
-------
Table 13-62. Consume
Only Intake of Homeg
rown Protected Fruits (q/kq-dav)
Population
Nc
Nc
%
Grouo
watd
unwatc
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
3855000
173
2.05
5.74E+00
6.25E-01
1.50E-01
2.66E-01
3.35E-01
9.33E-01
2.34E+00
7.45E+00
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+00
9.93E-01
1.17E-01
1.60E-01
2.83E-01
3.93E-01
1.23E+00
2.84E+00
7.44E+00
1.14E+01
1.91 E+01
1.91 E+01
20-39
755000
29
1.23
4.51 E+00
1.08E+00
1.81 E-01
3.62E-01
4.87E-01
1.22E+00
1.88E+00
4.47E+00
1.46E+01
1.61 E+01
2.41 E+01
2.41 E+01
40-69
1702000
77
3.00
5.65E+00
8.66E-01
1.12E-01
2.44E-01
2.87E-01
6.69E-01
2.22E+00
9.36E+00
1.55E+01
2.12E+01
4.13E+01
4.13E+01
70 +
601000
26
3.78
4.44E+00
6.91 E-01
2.62E-01
2.62E-01
2.85E-01
1.95E+00
3.29E+00
7.06E+00
8.97E+00
9.97E+00
1.52E+01
1.52E+01
Season
Fall
394000
12
0.83
*
*
*
*
*
*
Spring
497000
36
1.08
2.08E+00
3.47E-01
1.60E-01
1.81 E-01
2.55E-01
3.78E-01
1.22E+00
4.08E+00
5.10E+00
6.57E+00
6.79E+00
6.79E+00
Summer
1425000
47
3.13
7.39E+00
1.45E+00
1.12E-01
2.66E-01
3.93E-01
1.25E+00
3.06E+00
1.03E+01
1.66E+01
2.41 E+01
5.36E+01
5.36E+01
Winter
1539000
78
3.16
6.24E+00
9.10E-01
1.50E-01
3.02E-01
3.76E-01
1.39E+00
2.65E+00
8.23E+00
1.78E+01
2.12E+01
4.73E+01
4.73E+01
Urbanization
Central City
1312000
50
2.33
3.94E+00
5.80E-01
1.50E-01
2.62E-01
3.33E-01
8.34E-01
3.01 E+00
5.01 E+00
9.23E+00
9.97E+00
1.88E+01
1.88E+01
Nonmetropolitan
506000
19
1.12
*
*
*
*
*
*
Suburban
2037000
104
2.35
6.83E+00
9.38E-01
1.12E-01
2.53E-01
2.92E-01
5.94E-01
2.01 E+00
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
5.91 E+00
6.48E-01
1.17E-01
2.62E-01
3.33E-01
1.06E+00
2.44E+00
7.46E+00
1.60E+01
2.12E+01
4.73E+01
5.36E+01
Region
Midwest
657000
24
1.42
1.07E+01
2.60E+00
2.53E-01
2.62E-01
2.85E-01
1.18E+00
7.44E+00
1.46E+01
2.41 E+01
4.13E+01
5.36E+01
5.36E+01
Northeast
105000
5
0.26
*
*
*
*
*
*
South
1805000
74
2.81
4.77E+00
6.47E-01
1.60E-01
3.64E-01
4.50E-01
1.23E+00
2.54E+00
5.10E+00
1.52E+01
1.66E+01
2.38E+01
2.40E+01
West
1288000
70
3.57
4.85E+00
9.26E-01
1.12E-01
1.81 E-01
2.68E-01
4.94E-01
1.84E+00
5.34E+00
1.23E+01
1.88E+01
4.73E+01
4.73E+01
Response to Questionnaire
Households who garden
3360000
146
4.93
5.90E+00
6.97E-01
1.17E-01
2.65E-01
3.35E-01
1.16E+00
2.42E+00
7.46E+00
1.60E+01
1.91 E+01
4.73E+01
5.36E+01
Households who farm
357000
14
4.87
*
*
*
*
*
*
* Intake data not provided for subpopulations for which there were less than 20 observations
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-88 NFCS
-------
Table 13-63
Consumer
Only Intake of
Homegrown
Exposed Ve
getables (g/kg-dav)
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
28762000
1511
15.30
1.52E+00
5.10E-02
3.25E-03
9.15E-02
1.72E-01
3.95E-01
8.60E-01
1.83E+00
3.55E+00
5.12E+00
1.03E+01
2.06E+01
Age
01-02
815000
43
14.30
3.48E+00
5.14E-01
2.28E-02
2.39E-01
8.34E-01
1.20E+00
1.89E+00
4.23E+00
1.07E+01
1.19E+01
1.21E+01
1.21E+01
03-05
1069000
62
13.19
1.74E+00
2.20E-01
0.00E+00
7.23E-03
4.85E-02
5.79E-01
1.16E+00
2.53E+00
3.47E+00
6.29E+00
7.36E+00
8.86E+00
06-11
2454000
134
14.68
1.39E+00
1.76E-01
0.00E+00
4.44E-02
9.42E-02
3.12E-01
6.43E-01
1.60E+00
3.22E+00
5.47E+00
1.33E+01
1.33E+01
12-19
2611000
143
12.74
1.07E+00
9.43E-02
0.00E+00
2.92E-02
1.42E-01
3.04E-01
6.56E-01
1.46E+00
2.35E+00
3.78E+00
5.67E+00
5.67E+00
20-39
6969000
348
11.31
1.05E+00
8.14E-02
8.20E-03
6.56E-02
1.17E-01
2.55E-01
5.58E-01
1.26E+00
2.33E+00
3.32E+00
7.57E+00
2.06E+01
40-69
10993000
579
19.38
1.60E+00
8.32E-02
3.25E-03
1.41E-01
2.44E-01
4.79E-01
9.81 E-01
1.92E+00
3.59E+00
5.22E+00
8.99E+00
1.90E+01
70 +
3517000
185
22.15
1.68E+00
1.21E-01
5.21 E-03
1.51E-01
2.39E-01
5.22E-01
1.13E+00
2.38E+00
4.08E+00
4.96E+00
6.96E+00
1.02E+01
Season
Fall
8865000
314
18.60
1.31E+00
9.80E-02
5.24E-02
1.11E-01
1.80E-01
3.33E-01
6.49E-01
1.56E+00
3.13E+00
4.45E+00
8.92E+00
1.22E+01
Spring
4863000
487
10.54
1.14E+00
6.35E-02
2.35E-03
4.53E-02
1.53E-01
3.38E-01
6.58E-01
1.39E+00
2.76E+00
4.02E+00
7.51 E+00
1.07E+01
Summer
10151000
348
22.32
2.03E+00
1.26E-01
2.17E-03
1.13E-01
2.04E-01
6.07E-01
1.30E+00
2.52E+00
4.32E+00
6.35E+00
1.27E+01
1.90E+01
Winter
4883000
362
10.02
1.21E+00
9.50E-02
4.23E-03
2.28E-02
1.37E-01
3.70E-01
6.67E-01
1.42E+00
2.76E+00
3.69E+00
8.86E+00
2.06E+01
Urbanization
Central City
4859000
173
8.62
1.11E+00
1.02E-01
1.01 E-02
6.04E-02
8.02E-02
2.83E-01
7.01 E-01
1.43E+00
2.49E+00
3.29E+00
8.34E+00
1.21E+01
Nonmetropolitan
11577000
711
25.71
1.87E+00
8.79E-02
1.65E-02
1.72E-01
2.52E-01
5.01 E-01
1.16E+00
2.20E+00
4.12E+00
6.10E+00
1.22E+01
1.90E+01
Suburban
12266000
625
14.17
1.35E+00
7.01 E-02
2.93E-03
9.68E-02
1.56E-01
3.55E-01
7.44E-01
1.58E+00
3.22E+00
5.22E+00
8.61 E+00
2.06E+01
Race
Black
1713000
100
7.88
1.23E+00
1.27E-01
0.00E+00
7.74E-02
1.41E-01
3.52E-01
8.93E-01
1.51E+00
3.32E+00
3.92E+00
5.55E+00
7.19E+00
White
26551000
1386
16.85
1.53E+00
5.41 E-02
4.67E-03
9.74E-02
1.77E-01
3.95E-01
8.59E-01
1.82E+00
3.48E+00
5.12E+00
1.03E+01
2.06E+01
Region
Midwest
10402000
570
22.42
1.48E+00
8.91 E-02
1.00E-02
7.14E-02
1.57E-01
3.88E-01
8.06E-01
1.69E+00
3.55E+00
4.67E+00
1.19E+01
2.06E+01
Northeast
4050000
191
9.84
1.65E+00
1.78E-01
2.35E-03
8.05E-02
1.38E-01
2.61 E-01
6.65E-01
1.75E+00
5.58E+00
6.80E+00
1.27E+01
1.49E+01
South
9238000
503
14.36
1.55E+00
7.79E-02
5.20E-02
1.63E-01
2.61 E-01
5.18E-01
9.99E-01
1.92E+00
3.19E+00
4.52E+00
9.92E+00
1.33E+01
West
5012000
245
13.90
1.43E+00
1.02E-01
3.25E-03
2.61 E-02
1.45E-01
3.91 E-01
7.63E-01
2.13E+00
3.45E+00
4.84E+00
7.51 E+00
8.34E+00
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+00
3.63E+00
5.45E+00
1.03E+01
2.06E+01
Households who farm
3596000
207
49.07
2.17
1.61E-01
0.00E+00
1.84E-01
3.72E-01
6.47E-01
1.38E+00
2.81 E+00
6.01 E+00
6.83E+00
1.03E+01
1.33E+01
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-88 NFCS
-------
Table 13-64.
Consumer Only Intake of
Homegrown Protected V
egetables (g/kg-dav)
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
11428000
656
6.08
1.01E+00
4.95E-02
1.03E-01
1.54E-01
1.94E-01
3.22E-01
6.25E-01
1.20E+00
2.24E+00
3.05E+00
6.49E+00
9.42E+00
Age
01-02
348000
21
6.11
2.46E+00
4.91 E-01
3.15E-01
3.15E-01
5.38E-01
1.36E+00
1.94E+00
2.96E+00
3.88 E+00
9.42E+00
9.42E+00
9.42E+00
03-05
440000
32
5.43
1.30E+00
2.13E-01
2.33E-01
2.33E-01
3.22E-01
4.80E-01
1.04E+00
1.48E+00
2.51 E+00
5.10E+00
5.31 E+00
5.31 E+00
06-11
1052000
63
6.30
1.10E+00
1.34E-01
1.89E-01
2.08E-01
3.18E-01
3.87E-01
7.91 E-01
1.31 E+00
2.14E+00
3.12E+00
5.40E+00
5.40E+00
12-19
910000
51
4.44
7.76E-01
8.71 E-02
5.88E-02
1.61 E-01
2.39E-01
3.54E-01
5.83E-01
8.24E-01
1.85 E+00
2.20E+00
2.69E+00
2.69E+00
20-39
3227000
164
5.24
7.62E-01
6.03E-02
1.13E-01
1.52E-01
1.71 E-01
2.41 E-01
5.08E-01
9.67E-01
1.73E+00
2.51 E+00
3.63E+00
4.76E+00
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
1.11 E+00
1.87E+00
3.04E+00
6.84E+00
7.44E+00
70 +
1442000
89
9.08
1.05E+00
1.62E-01
1.19E-01
2.10E-01
2.42E-01
3.57E-01
5.72E-01
1.21 E+00
1.86 E+00
3.05E+00
9.23E+00
9.23E+00
Season
Fall
3907000
143
8.20
8.51 E-01
7.02E-02
1.19E-01
1.61 E-01
2.04E-01
3.22E-01
5.68E-01
1.10E+00
1.73E+00
2.51 E+00
4.78E+00
5.31 E+00
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
1.44 E+00
1.86E+00
3.74E+00
5.73E+00
Summer
3559000
118
7.82
1.40E+00
1.56E-01
1.03E-01
1.77E-01
2.33E-01
3.81 E-01
7.81 E-01
1.69 E+00
3.05 E+00
5.40E+00
9.23E+00
9.42E+00
Winter
1876000
159
3.85
9.30E-01
7.70E-02
1.18E-01
1.42E-01
1.82E-01
3.12E-01
6.01 E-01
1.20 E+00
2.32E+00
3.06E+00
4.76E+00
6.39E+00
Urbanization
Central City
1342000
49
2.38
9.96E-01
1.51 E-01
1.19E-01
1.53E-01
1.67E-01
3.18E-01
7.21 E-01
1.18E+00
2.36 E+00
2.83E+00
4.78E+00
4.78E+00
Nonmetropolitan
5934000
391
13.18
1.07E+00
6.36E-02
1.14E-01
1.66E-01
2.14E-01
3.53E-01
6.48E-01
1.30 E+00
2.51 E+00
3.55E+00
6.84E+00
9.42E+00
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+00
1.85 E+00
2.67E+00
6.49E+00
9.23E+00
Race
Black
479000
27
2.20
1.50E+00
2.25E-01
1.62E-01
2.64E-01
3.31 E-01
8.66E-01
9.35E-01
2.20 E+00
3.05 E+00
3.23E+00
4.95E+00
4.95E+00
White
10836000
625
6.88
9.93E-01
4.83E-02
1.03E-01
1.53E-01
1.92E-01
3.21 E-01
6.10E-01
1.20 E+00
2.17E+00
3.04E+00
6.49E+00
9.42E+00
Region
Midwest
4359000
273
9.40
1.01E+00
7.38E-02
1.13E-01
1.71 E-01
2.31 E-01
3.26E-01
5.72E-01
1.08 E+00
2.45 E+00
3.68E+00
6.84E+00
7.44E+00
Northeast
807000
48
1.96
7.01 E-01
8.99E-02
5.88E-02
1.50E-01
1.68E-01
2.65E-01
5.09E-01
9.91 E-01
1.71 E+00
2.33E+00
2.77E+00
2.77E+00
South
4449000
253
6.92
1.08E+00
7.17E-02
1.29E-01
1.71 E-01
2.14E-01
3.76E-01
7.12E-01
1.38 E+00
2.32E+00
3.05E+00
5.40E+00
9.42E+00
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
1.01 E+00
1.86 E+00
3.12E+00
9.23E+00
9.23E+00
Response to Questionnaire
Households who garden
10286000
602
15.09
1.01E+00
4.73E-02
1.03E-01
1.53E-01
1.92E-01
3.36E-01
6.42E-01
1.21 E+00
2.32E+00
3.05E+00
6.49E+00
9.23E+00
Households who farm
2325000
142
31.72
1.30E+00
1.45E-01
8.65E-02
1.66E-01
2.09E-01
3.37E-01
5.99E-01
1.40 E+00
3.55 E+00
5.40E+00
9.23E+00
9.23E+00
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-88 NFCS
-------
Table 13-65
Consumer
Only Intake o
Homegrown Root Veqe
tables (g/kg-dav)
Population
Nc
Nc
%
Grouo
watd u
nwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
13750000
743
7.31
1.16E+00
5.84E-02
4.72E-03
3.64E-02
1.12E-01
2.51 E-01
6.66E-01
1.47E+00
2.81 E+00
3.71 E+00
9.52E+00
1.28E+01
Age
01-02
371000
22
6.51
2.52E+00
6.10E-01
1.66E-01
1.66E-01
2.19E-01
3.59E-01
9.20E-01
3.67E+00
7.25E+00
1.04E+01
1.04E+01
1.04E+01
03-05
390000
23
4.81
1.28E+00
3.24E-01
0.00E+00
0.00E+00
1.17E-01
2.25E-01
4.62E-01
1.68E+00
4.26E+00
4.73E+00
4.73E+00
4.73E+00
06-11
1106000
67
6.62
1.32E+00
2.14E-01
0.00E+00
1.39E-02
3.64E-02
2.32E-01
5.23E-01
1.63E+00
3.83E+00
5.59E+00
7.47E+00
7.47E+00
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+00
2.26E+00
3.32E+00
5.13E+00
5.13E+00
20-39
3252000
164
5.28
8.74E-01
7.39E-02
1.21 E-02
5.35E-02
9.93E-02
2.00E-01
5.64E-01
1.24E+00
2.11 E+00
3.08E+00
4.64E+00
6.03E+00
40-69
4903000
276
8.64
1.13E+00
9.86E-02
3.34E-03
3.29E-02
1.17E-01
2.51 E-01
6.75E-01
1.27E+00
2.74E+00
3.56E+00
9.52E+00
1.28E+01
70 +
2096000
107
13.20
1.22E+00
1.02E-01
1.73E-02
2.90E-02
1.69E-01
3.76E-01
8.51 E-01
1.71E+00
2.86E+00
3.21 E+00
4.01 E+00
4.77E+00
Season
Fall
4026000
153
8.45
1.42E+00
1.53E-01
5.15E-02
1.38E-01
1.72E-01
3.09E-01
9.20E-01
1.67E+00
3.26E+00
3.85E+00
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+00
2.80E+00
4.24E+00
7.69E+00
Summer
5011000
169
11.02
1.19E+00
1.20E-01
0.00E+00
4.76E-02
1.32E-01
2.77E-01
7.26E-01
1.51E+00
2.74E+00
3.64E+00
1.04E+01
1.19E+01
Winter
2161000
161
4.44
1.17E+00
1.19E-01
3.23E-03
8.57E-03
4.34E-02
2.38E-01
5.57E-01
1.56E+00
3.08E+00
4.14E+00
6.21 E+00
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
1.91 E+00
2.70E+00
3.56E+00
3.93E+00
Nonmetropolitan
6094000
366
13.54
1.43E+00
9.81 E-02
8.57E-03
6.87E-02
1.29E-01
2.78E-01
7.58E-01
1.85E+00
3.32E+00
4.24E+00
1.13E+01
1.28E+01
Suburban
5211000
279
6.02
1.06E+00
8.62E-02
3.73E-03
1.21 E-02
7.17E-02
2.32E-01
7.34E-01
1.19E+00
2.34E+00
3.26E+00
6.29E+00
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+00
1.25E+00
1.23E+01
1.23E+01
White
12861000
697
8.16
1.18E+00
5.97E-02
7.79E-03
4.58E-02
1.29E-01
2.61 E-01
6.80E-01
1.50E+00
2.82E+00
3.72E+00
9.52E+00
1.28E+01
Region
Midwest
5572000
314
12.01
1.31E+00
9.54E-02
3.37E-02
7.48E-02
1.66E-01
2.69E-01
7.39E-01
1.67E+00
3.23E+00
4.26E+00
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
4.81 E-01
1.18E+00
2.05E+00
2.77E+00
4.78E+00
6.03E+00
South
3842000
205
5.97
1.38E+00
1.38E-01
1.10E-02
5.35E-02
1.32E-01
2.77E-01
6.90E-01
1.70E+00
3.32E+00
3.83E+00
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
9.77E-01
1.69E+00
2.45E+00
3.72E+00
3.72E+00
Response to Questionnaire
Households who garden
12578000
682
18.46
1.15E+00
5.72E-02
4.79E-03
3.64E-02
1.17E-01
2.58E-01
6.74E-01
1.50E+00
2.81 E+00
3.64E+00
7.47E+00
1.28E+01
Households who farm
2367000
136
32.30
1.39E+00
1.26E-01
1.11E-01
1.58E-01
1.84E-01
3.65E-01
8.83E-01
1.85E+00
3.11 E+00
4.58E+00
7.47E+00
7.69E+00
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-88 NFCS
-------
Table 13-6
3. Consumer
Only Intake of
Homegrown Dark Green \
egetables (g/kg-dav)
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
8855000
428
4.71
3.91 E-01
2.95E-02
2.01 E-03
4.28E-03
1.01E-02
8.70E-02
2.11 E-01
4.35E-01
9.19E-01
1.25E+00
3.53E+00
5.82E+00
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+00
6.34E-03
2.42E-02
9.00E-02
1.81 E-01
3.87E-01
9.48E-01
1.04E+00
1.28E+00
1.28E+00
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+00
4.86E+00
4.86E+00
20-39
1976000
87
3.21
3.36E-01
6.09E-02
2.21 E-03
3.74E-03
1.00E-02
8.70E-02
1.76E-01
3.79E-01
6.69E-01
9.19E-01
2.94E+00
4.29E+00
40-69
3710000
184
6.54
4.01 E-01
4.24E-02
2.25E-03
3.67E-03
2.60E-02
8.19E-02
2.33E-01
4.80E-01
9.79E-01
1.25E+00
3.29E+00
5.82E+00
70 +
1253000
63
7.89
4.08E-01
7.27E-02
2.84E-03
4.23E-03
5.68E-03
1.10E-01
2.31 E-01
4.69E-01
9.29E-01
1.08E+00
3.45E+00
3.45E+00
Season
Fall
2683000
88
5.63
4.41 E-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+00
3.86E+00
4.29E+00
Spring
1251000
127
2.71
5.59E-01
7.90E-02
1.63E-03
3.66E-03
5.72E-03
1.01 E-01
3.09E-01
5.38E-01
1.28E+00
2.81 E+00
4.86E+00
5.82E+00
Summer
3580000
124
7.87
3.39E-01
4.10E-02
0.00E+00
2.84E-03
5.68E-03
6.34E-02
1.51 E-01
4.05E-01
9.79E-01
1.15E+00
2.48E+00
2.48E+00
Winter
1341000
89
2.75
2.72E-01
3.92E-02
2.01 E-03
3.97E-03
5.21 E-03
2.30E-02
1.51 E-01
3.71 E-01
6.59E-01
1.17E+00
2.04E+00
2.18E+00
Urbanization
Central City
1298000
48
2.30
2.69E-01
3.68E-02
2.84E-03
4.71 E-03
1.01E-02
1.06E-01
2.05E-01
3.24E-01
6.32E-01
9.19E-01
1.07E+00
1.07E+00
Nonmetropolitan
3218000
167
7.15
3.31 E-01
3.54E-02
2.21 E-03
4.67E-03
1.70E-02
6.86E-02
1.72E-01
4.52E-01
7.52E-01
1.00E+00
2.48E+00
5.82E+00
Suburban
4279000
211
4.94
4.79E-01
5.23E-02
2.25E-03
5.21 E-03
2.15E-02
9.22E-02
2.33E-01
4.59E-01
1.15E+00
2.18E+00
3.86E+00
4.86E+00
Race
Black
724000
49
3.33
1.04E+00
1.80E-01
0.00E+00
1.00E-01
1.13E-01
2.21 E-01
5.52E-01
1.17E+00
3.29E+00
3.86E+00
4.86E+00
4.86E+00
White
7963000
373
5.05
3.21 E-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+00
2.37E+00
5.82E+00
Region
Midwest
2668000
121
5.75
2.81 E-01
3.54E-02
2.84E-03
4.77E-03
6.26E-03
6.34E-02
2.11 E-01
3.58E-01
4.96E-01
9.79E-01
2.48E+00
3.02E+00
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+00
1.93E+00
3.53E+00
5.82E+00
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+00
3.86E+00
4.29E+00
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+00
4.86E+00
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+00
3.53E+00
5.82E+00
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
2.31 E-01
4.84E-01
9.48E-01
1.25E+00
2.48E+00
3.02E+00
* Intake data not provided for subpopulations for which there were less than 20 observations
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey
Source: Based on EPA's analyses of the 1987-88 NFCS
-------
Table 13-67. Consumer Only
Intake of Homegrown Deep Yellow Vegetables (g/kg-dav)
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
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+00
2.03E+00
2.67E+00
6.63E+00
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+00
1.44E+00
1.58E+00
1.58E+00
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
5.11 E-01
1.22E+00
2.03E+00
2.67E+00
2.67E+00
40-69
2074000
96
3.66
5.39E-01
5.15E-02
3.90E-02
9.22E-02
1.43E-01
2.21 E-01
4.03E-01
6.54E-01
1.09E+00
1.33E+00
3.02E+00
3.02E+00
70 +
761000
32
4.79
7.81 E-01
9.20E-02
7.64E-02
2.02E-01
2.77E-01
3.70E-01
5.72E-01
1.24E+00
1.61 E+00
1.99E+00
1.99E+00
1.99E+00
Season
Fall
2664000
97
5.59
7.38E-01
8.18E-02
9.21 E-02
1.22E-01
1.43E-01
2.61 E-01
4.51 E-01
9.74E-01
1.73E+00
2.23E+00
3.02E+00
6.63E+00
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
1.01 E+00
1.42E+00
2.41 E+00
2.41 E+00
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+00
2.31 E+00
2.31 E+00
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
1.54 E+00
2.23E+00
4.37E+00
4.37E+00
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
1.41 E+00
2.24E+00
2.24E+00
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
1.39 E+00
2.12E+00
4.37E+00
6.63E+00
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+00
2.03E+00
2.67E+00
2.67E+00
Race
Black
129000
8
0.59
*
*
*
*
*
*
White
5093000
229
3.23
6.45E-01
4.03E-02
4.89E-02
9.21 E-02
1.43E-01
2.41 E-01
4.25E-01
7.96E-01
1.50 E+00
2.03E+00
2.67E+00
4.37E+00
Region
Midwest
2792000
128
6.02
7.52E-01
6.01 E-02
4.34E-02
1.32E-01
1.93E-01
2.82E-01
5.09E-01
9.55E-01
1.73E+00
2.23E+00
3.02E+00
4.37E+00
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
1.09 E+00
1.37E+00
2.21 E+00
2.21 E+00
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+00
6.63E+00
6.63E+00
West
1383000
58
3.83
5.97E-01
7.07E-02
6.48E-02
1.27E-01
1.43E-01
2.21 E-01
4.10E-01
6.42E-01
1.44 E+00
1.89E+00
2.31 E+00
2.31 E+00
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+00
1.99E+00
2.67E+00
4.37E+00
Households who farm
1088000
51
14.85
6.06E-01
8.52E-02
9.21 E-02
9.22E-02
1.22E-01
1.94E-01
3.40E-01
9.40E-01
1.28E+00
1.73E+00
3.02E+00
3.02E+00
* Intake data not provided for subpopulations for which there were less than 20 observations
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-88 NFCS
-------
Table13-68
Consumer
Only Intake of
Homegrown Other Vegetables (g/kg-day)
Population
Nc
Nc
%
Grouo
watd
u nwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
25221000
1437
13.41
1.38E+00
5.00E-02
9.44E-03
1.07E-01
1.76E-01
3.62E-01
7.78E-01
1.65E+00
3.09E+00
4.52E+00
9.95E+00
1.84E+01
Age
01-02
613000
38
10.76
3.80E+00
6.27E-01
1.92E-01
2.73E-01
4.04E-01
1.04E+00
2.61 E+00
4.55E+00
7.74E+00
1.12E+01
1.80E+01
1.80E+01
03-05
887000
59
10.95
2.15E+00
2.67E-01
0.00E+00
2.28E-01
3.72E-01
7.20E-01
1.37E+00
3.16E+00
4.47E+00
5.96E+00
8.41 E+00
1.40E+01
06-11
2149000
134
12.86
1.30E+00
1.38E-01
0.00E+00
1.21 E-01
1.93E-01
3.54E-01
8.00E-01
1.61 E+00
3.04E+00
4.57E+00
9.95E+00
9.95E+00
12-19
2379000
141
11.61
9.80E-01
8.56E-02
0.00E+00
5.76E-02
1.15E-01
3.17E-01
6.40E-01
1.33E+00
2.05E+00
3.17E+00
5.41 E+00
5.41 E+00
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+00
2.19E+00
3.04E+00
5.10E+00
7.00E+00
40-69
9649000
547
17.01
1.40E+00
8.72E-02
5.20E-03
1.11 E-01
1.86E-01
3.95E-01
8.43E-01
1.58E+00
2.92E+00
4.65E+00
1.41E+01
1.84E+01
70 +
3226000
174
20.31
1.58E+00
1.41 E-01
1.85E-02
1.52E-01
2.38E-01
4.62E-01
9.48E-01
1.91 E+00
3.46E+00
5.79E+00
9.96E+00
1.14E+01
Season
Fall
6934000
253
14.55
1.19E+00
8.62E-02
4.92E-02
1.48E-01
1.86E-01
3.28E-01
7.16E-01
1.44E+00
2.74E+00
4.00E+00
6.74E+00
9.96E+00
Spring
5407000
567
11.71
1.16E+00
6.19E-02
3.66E-03
4.32E-02
1.04E-01
3.10E-01
7.10E-01
1.39E+00
2.67E+00
4.21 E+00
7.35E+00
1.40E+01
Summer
8454000
283
18.59
1.79E+00
1.53E-01
0.00E+00
1.18E-01
1.81 E-01
3.85E-01
9.68E-01
1.97E+00
4.13E+00
6.14E+00
1.46E+01
1.84E+01
Winter
4426000
334
9.09
1.19E+00
7.28E-02
4.79E-03
1.41 E-01
2.31 E-01
4.09E-01
7.33E-01
1.49E+00
2.41 E+00
3.37E+00
7.00E+00
1.10E+01
Urbanization
Central City
4148000
161
7.36
9.66E-01
8.81 E-02
3.50E-02
9.37E-02
1.63E-01
3.24E-01
6.07E-01
1.23E+00
1.97E+00
3.22E+00
7.00E+00
8.85E+00
Nonmetropolitan
10721000
710
23.81
1.78E+00
8.99E-02
2.74E-02
1.60E-01
2.26E-01
4.68E-01
1.01 E+00
2.01 E+00
4.05E+00
5.74E+00
1.41E+01
1.84E+01
Suburban
10292000
564
11.89
1.14E+00
5.98E-02
4.79E-03
8.98E-02
1.46E-01
3.06E-01
6.47E-01
1.44E+00
2.69E+00
3.77E+00
6.81 E+00
1.14E+01
Race
Black
1347000
84
6.19
1.30E+00
1.70E-01
4.41E-02
1.74E-01
2.06E-01
3.50E-01
7.11 E-01
1.49E+00
3.88E+00
5.47E+00
6.21 E+00
7.72E+00
White
23367000
1327
14.83
1.39E+00
5.26E-02
1.29E-02
1.10E-01
1.79E-01
3.76E-01
7.93E-01
1.65E+00
3.04E+00
4.49E+00
9.96E+00
1.84E+01
Region
Midwest
8296000
522
17.88
1.43E+00
9.25E-02
3.19E-02
1.21 E-01
1.90E-01
3.66E-01
7.29E-01
1.65E+00
3.05E+00
4.65E+00
1.12E+01
1.84E+01
Northeast
2914000
162
7.08
1.33E+00
1.65E-01
1.97E-03
5.69E-02
1.07E-01
2.44E-01
5.97E-01
1.64E+00
3.07E+00
5.41 E+00
1.20E+01
1.41E+01
South
9218000
518
14.33
1.53E+00
7.82E-02
1.41E-02
1.68E-01
2.53E-01
4.87E-01
1.03E+00
1.76E+00
3.37E+00
4.70E+00
8.33E+00
1.80E+01
West
4733000
233
13.12
1.08E+00
9.85E-02
1.11E-02
7.06E-02
1.22E-01
2.55E-01
5.73E-01
1.21 E+00
2.41 E+00
3.73E+00
8.02E+00
1.14E+01
Response to Questionnaire
Households who garden
22417000
1291
32.89
1.44E+00
5.25E-02
1.11E-02
1.11 E-01
1.80E-01
3.84E-01
8.18E-01
1.70E+00
3.22E+00
4.65E+00
9.95E+00
1.84E+01
Households who farm
3965000
239
54.10
1.95E+00
1.63E-01
1.41E-02
1.36E-01
2.34E-01
5.20E-01
1.21 E+00
2.04E+00
5.32E+00
7.02E+00
1.46E+01
1.59E+01
NOTE: SE = standard error
P = percentile of the distribution
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Source: Based on EPA's analyses of the 1987-88 NFCS
-------
Table 13-69. Consumer Only
Intake of Homegrown Citrus (g/kg-dav)
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
2530000
125
1.35
4.76E+00
6.05E-01
7.82E-02
1.57E-01
2.86E-01
7.56E-01
1.99E+00
5.10E+00
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+00
8.06E-01
8.11E-02
1.50E-01
2.47E-01
5.21 E-01
1.74E+00
5.24E+00
1.52E+01
1.97E+01
2.38E+01
2.38E+01
70 +
457000
21
2.88
4.43E+00
7.58E-01
7.82E-02
7.82E-02
4.94E-01
1.95E+00
3.53E+00
6.94E+00
8.97E+00
8.97E+00
1.57E+01
1.57E+01
Season
Fall
280000
8
0.59
*
*
*
*
*
Spring
437000
33
0.95
2.31 E+00
3.76E-01
1.57E-01
1.84E-01
2.35E-01
3.69E-01
1.36E+00
4.15E+00
5.10E+00
6.50E+00
7.52E+00
7.52E+00
Summer
334000
11
0.73
*
*
*
*
*
Winter
1479000
73
3.04
6.47E+00
9.53E-01
1.50E-01
3.33E-01
4.94E-01
1.64E+00
2.93E+00
8.59E+00
1.91E+01
2.38E+01
4.79E+01
4.79E+01
Urbanization
Central City
1053000
43
1.87
3.57E+00
5.18E-01
1.50E-01
3.33E-01
4.50E-01
1.13E+00
3.01 E+00
4.97E+00
7.46E+00
8.97E+00
2.00E+01
2.00E+01
Nonmetropolitan
0
0
0.00
Suburban
1477000
82
1.71
5.61 E+00
9.14E-01
7.82E-02
1.14E-01
2.47E-01
5.17E-01
1.81 E+00
8.12E+00
1.79E+01
2.38E+01
4.79E+01
4.79E+01
Race
Black
200000
8
0.92
*
*
*
*
*
White
2330000
117
1.48
4.93E+00
6.31 E-01
7.82E-02
1.50E-01
2.84E-01
7.82E-01
2.34E+00
5.34E+00
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+00
7.37E-01
1.57E-01
3.76E-01
6.44E-01
1.60E+00
3.42E+00
6.50E+00
1.41E+01
1.97E+01
2.38E+01
2.38E+01
West
1226000
66
3.40
4.56E+00
9.79E-01
7.82E-02
1.14E-01
2.35E-01
3.69E-01
1.42E+00
4.53E+00
1.24E+01
2.00E+01
4.79E+01
4.79E+01
Response to Questionnaire
Households who garden
2151000
102
3.16
4.55E+00
6.61 E-01
7.82E-02
1.50E-01
2.84E-01
7.56E-01
1.99E+00
4.99E+00
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
Nc wgtd = weighted number of consumers; Nc unwgtd = unweighted number of consumers in survey.
Sources: Based on EPA's analyses of the 1987-88 NFCS
-------
Table 13-70. Consumer Only Intake of Homec
rown Other Fruit ("g/kg-day)
Population
Nc
Nc
%
Grouo
watd
unwatd
Consumina
Mean
SE
P1
P5
P10
P25
P50
P75
P90
P95
P99
P100
Total
12615000
706
6.71
2.20E+00
1.86E-01
5.41 E-02
1.47E-01
2.55E-01
4.60E-01
9.06E-01
1.91E+00
4.59E+00
8.12E+00
1.84E+01
6.26E+01
Age
01-02
306000
19
5.37
*
*
*
*
03-05
499000
31
6.16
2.66E+00
7.60E-01
0.00E+00
0.00E+00
3.80E-01
1.02E+00
1.87E+00
2.71 E+00
5.54E+00
6.30E+00
3.32E+01
3.32E+01
06-11
915000
68
5.48
2.60E+00
4.38E-01
0.00E+00
1.77E-01
3.86E-01
6.37E-01
1.14E+00
2.99E+00
7.13E+00
1.21E+01
1.62E+01
1.65E+01
12-19
1021000
54
4.98
1.62E+00
2.77E-01
8.40E-02
1.20E-01
2.57E-01
3.86E-01
6.09E-01
2.36E+00
3.92E+00
6.81 E+00
8.12E+00
8.12E+00
20-39
2761000
146
4.48
1.85E+00
3.72E-01
7.94E-02
1.30E-01
1.80E-01
3.07E-01
6.20E-01
1.39E+00
3.70E+00
6.64E+00
3.70E+01
3.70E+01
40-69
4610000
259
8.13
2.09E+00
3.08E-01
6.52E-02
1.47E-01
2.54E-01
4.44E-01
7.68E-01
1.77E+00
3.17E+00
9.77E+00
1.84E+01
5.33E+01
70 +
2326000
119
14.65
1.66E+00
1.84E-01
4.41 E-02
2.07E-01
3.56E-01
5.71 E-01
1.07E+00
1.65E+00
4.06E+00
5.21 E+00
1.17E+01
1.17E+01
Season
Fall
2923000
102
6.13
1.39E+00
1.14E-01
2.59E-01
3.04E-01
3.81 E-01
5.67E-01
1.07E+00
1.88E+00
2.89E+00
4.06E+00
5.39E+00
5.54E+00
Spring
2526000
268
5.47
1.47E+00
1.51E-01
8.66E-02
1.98E-01
2.54E-01
4.25E-01
8.33E-01
1.65E+00
2.89E+00
4.59E+00
8.26E+00
3.32E+01
Summer
4327000
144
9.51
Winter
2839000
192
5.83
1.29E+00
1.08E-01
4.15E-02
1.01E-01
2.25E-01
4.54E-01
8.33E-01
1.55E+00
2.70E+00
4.79E+00
8.06E+00
1.13E+01
Urbanization
Central City
2681000
102
4.76
1.79E+00
2.88E-01
4.41 E-02
1.66E-01
2.91 E-01
5.21 E-01
8.87E-01
1.60E+00
2.61 E+00
1.04E+01
1.54E+01
1.54E+01
Nonmetropolitan
4118000
278
9.15
2.43E+00
3.10E-01
6.52E-02
1.20E-01
2.38E-01
4.50E-01
1.13E+00
2.43E+00
4.60E+00
8.12E+00
2.40E+01
5.33E+01
Suburban
5756000
324
6.65
2.25E+00
3.06E-01
1.25E-01
1.99E-01
2.82E-01
4.46E-01
7.64E-01
1.81 E+00
4.72E+00
7.61 E+00
1.84E+01
6.26E+01
Race
Black
250000
12
1.15
*
*
*
*
White
12256000
690
7.78
2.24E+00
1.91E-01
6.96E-02
1.50E-01
2.59E-01
4.66E-01
9.16E-01
1.94E+00
4.65E+00
8.26E+00
1.84E+01
6.26E+01
Region
Midwest
4619000
298
9.96
3.07E+00
4.25E-01
4.41 E-02
1.25E-01
2.35E-01
4.54E-01
1.04E+00
2.35E+00
6.73E+00
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
3.11 E-01
4.75E-01
8.12E-01
1.29E+00
2.16E+00
1.17E+01
1.17E+01
South
3004000
157
4.67
1.99E+00
2.59E-01
7.94E-02
2.38E-01
2.99E-01
5.46E-01
1.10E+00
1.82E+00
4.06E+00
6.30E+00
1.62E+01
2.40E+01
West
3653000
177
10.13
1.76E+00
1.64E-01
1.00E-01
2.16E-01
2.91 E-01
5.44E-01
9.71 E-01
2.04E+00
4.35E+00
5.75E+00
1.30E+01
1.30E+01
Response to Questionnaire
Households who garden
10926000
619
16.03
2.38E+00
2.12E-01
4.41 E-02
1.58E-01
2.57E-01
4.74E-01
9.94E-01
1.96E+00
4.94E+00
1.04E+01
1.84E+01
6.26E+01
Households who farm
1917000
112
26.16
2.57E+00
2.65E-01
6.96E-02
2.76E-01
3.61 E-01
7.33E-01
1.55E+00
3.62E+00
5.80E+00
8.06E+00
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
Nc wgtd = weighted number of consumers; Nc 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
Veaetables
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
Fall
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
0.018
0.004
0.075
0.079
0.054
0.035
0.043
0.050
Race
Black
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
Reaions
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 Resoonse
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
Veaetables
Veaetables
Veaetables
Fruits
Fruits
Aooles
Peaches
Pears
Strawberries
Other Berries
Total
0.044
0.065
0.069
0.038
0.042
0.030
0.147
0.067
0.111
0.217
Season
Fall
0.059
0.099
0.069
0.114
0.027
0.032
0.09
0.038
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
0.038
0.107
0.228
Nonmetropolitan
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
Black
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
Reaions
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
0.083
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 Resoonse
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")
Asparaaus
Beets
Broccoli
Cabbaae
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
Fall
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
0.016
0.045
0.039
0.047
0.088
0.009
0.165
0.299
0.050
Race
Black
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
Reaions
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
0.119
0.009
0.000
0.333
0.083
Questionnaire Response
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
0.361
-------
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
Fall
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
Black
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
Reaions
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 Resoonse
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
collection period
Statistical method used to estimate long-
term distribution from one-week survey
data.
High (Means & Short-term distributions)
Low (Long-term distributions)
• Validity of approach
Individual intakes inferred from household
consumption.
Medium (Means)
Low (Distributions)
• Study size
10,000 individuals, 4500 households
High
• Representativeness of the
population
Nationwide survey representative of
general U.S. population
High
• Bias in study design (high
rating desirable)
Non-response bias can not be ruled out
due to low response rate.
Medium
• Measurement Error
(high rating desirable)
Individuals' estimates of food weights
imprecise
Medium
Other Elements
• Number of studies
1
Low
• Agreement between
researchers
N/A
Overall Rating
Highest confidence in means, lowest
confidence in long term percentiles
Medium (Means)
Medium
(Short-term distributions)
Low (Long-term
distributions)
-------
Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data
Food
Product
Household Code/Definition
Individual Code
MAJOR FOOD GROUPS
Total Fruits
50- Fresh Fruits
citrus
other vitamin-C rich
other fruits
512- Commercially Canned Fruits
522- Commercially Frozen Fruits
533- Canned Fruit Juice
534- Frozen Fruit Juice
535- Aseptically Packed Fruit Juice
536- Fresh Fruit Juice
542- Dried Fruits
(includes baby foods)
6- Fruits
citrus fruits and juices
dried fruits
other fruits
fruits/juices & nectar
fruit/juices baby food
(includes baby foods)
Total
Vegetables
48- Potatoes, Sweetpotatoes
49- Fresh Vegetables
dark green
deep yellow
tomatoes
light green
other
511- Commercially Canned Vegetables
521 - Commercially Frozen 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)
7- Vegetables (all forms)
white potatoes & PR starchy
dark green vegetables
deep yellow vegetables
tomatoes and torn, mixtures
other vegetables
veg. and mixtures/baby food
veg. with meat mixtures
(includes baby foods; mixtures, mostly vegetables)
Total Meats
44- Meat
beef
pork
veal
lamb
mutton
goat
game
lunch meat
mixtures
451- Poultry
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
20- Meat, type not specified
21- Beef
22- Pork
23- Lamb, veal, game, carcass meat
24- Poultry
25- Organ meats, sausages, lunchmeats, meat
spreads
(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
foods)
Total Dairy
40- Milk Equivalent
fresh fluid milk
processed milk
cream and cream substitutes
frozen desserts with milk
cheese
dairy-based dips
(does not include soups, sauces, gravies, mixtures, and
readv-to-eat dinners)
1 - Milk and Milk Products
milk and milk drinks
cream and cream substitutes
milk desserts, sauces, and gravies
cheeses
(includes regular fluid milk, human milk, imitation milk
products, yogurt, milk-based meal replacements, and
infant formulas)
-------
Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued)
Food
Household Code/Definition
Individual Code
Product
Total Fish
452- Fish, Shellfish
26- Fish, Shellfish
various species
various species and forms
fresh, frozen, commercial, dried
(does not include soups, sauces, gravies, mixtures, and
(excludes meat, poultry, and fish with non-meat items;
ready-to-eat dinners)
frozen plate meals; soups and gravies with meat, poultry
and fish base; and gelatin-based drinks)
INDIVIDUAL FOODS
White
4811 - White Potatoes, fresh
71- White Potatoes and PR Starchy Veg.
Potatoes
4821 - White Potatoes, commercially canned
baked, boiled, chips, sticks, creamed,
4831 - White Potatoes, commercially frozen
scalloped, au gratin, fried, mashed, stuffed,
4841 - White Potatoes, dehydrated
puffs, salad, recipes, soups, Puerto Rican
4851 - White Potatoes, chips, sticks, salad
starchy vegetables
(does not include soups, sauces, gravies, mixtures, and
(does not include vegetables soups; vegetable mixtures;
ready-to-eat dinners)
or vegetable with meat mixtures)
Peppers
4913- Green/Red Peppers, fresh
7512100 Pepper, hot chili, raw
5111201 Sweet Green Peppers, commercially canned
7512200 Pepper, raw
5111202 Hot Chili Peppers, commercially canned
7512210 Pepper, sweet green, raw
5211301 Sweet Green Peppers, commercially frozen
7512220 Pepper, sweet red, raw
5211302 Green Chili Peppers, commercially frozen
7522600 Pepper, green, cooked, NS as to fat added
5211303 Red Chili Peppers, commercially frozen
7522601 Pepper, green, cooked, fat not added
5413112 Sweet Green Peppers, dry
7522602 Pepper, green, cooked, fat added
5413113 Red Chili Peppers, dry
7522604 Pepper, red, cooked, NS as to fat added
(does not include soups, sauces, gravies, mixtures, and
7522605 Pepper, red, cooked, fat not added
ready-to-eat dinners)
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 vegetable with meat mixtures)
Onions
4953- Onions, Garlic, fresh
7510950 Chives, raw
onions
7511150 Garlic, raw
chives
7511250 Leek, raw
garlic
7511701 Onions, young green, raw
leeks
7511702 Onions, mature
5114908 Garlic Pulp, raw
7521550 Chives, dried
5114915 Onions, commercially canned
7521740 Garlic, cooked
5213722 Onions, commercially frozen
7522100 Onions, mature cooked, NS as to fat added
5213723 Onions with Sauce, commercially frozen
7522101 Onions, mature cooked, fat not added
5413103 Chives, dried
7522102 Onions, mature cooked, fat added
5413105 Garlic Flakes, dried
7522103 Onions, pearl cooked
5413110 Onion Flakes, dried
7522104 Onions, young green cooked, NS as to fat
(does not include soups, sauces, gravies, mixtures, and
7522105 Onions, young green cooked, fat not added
ready-to-eat dinners)
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}
-------
Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued)
Food
Product
Household Code/Definition
Individual Code
Corn
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. Corn with Sauce, commercially frozen
5213504 Corn with other Veg., commercially frozen
5213505 White Corn 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)
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, baby
(does not include vegetable soups; vegetable mixtures;
or vegetable with meat mixtures; includes baby food)
Apples
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)
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
Cincludes babv food: exceDt mixtures')
-------
Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued)
Food
Product
Household Code/Definition
Individual Code
Tomatoes
4931- Tomatoes, fresh
5113- Tomatoes, commercially canned
5115201 Tomatoes, low sodium, commercially canned
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)
74- Tomatoes and Tomato Mixtures
raw, cooked, juices, sauces, mixtures, soups,
sandwiches
Snap Beans
4943- Snap or Wax Beans, fresh
5114401 Green or Snap Beans, commercially canned
5114402 Wax or Yellow Beans, commercially canned
5114403 Beans, baby/jr., commercially canned
5115302 Green Beans, low sodium, comm. canned
5115303 Yell, or Wax Beans, low sod., comm. canned
5213301 Snap or Green Beans, comm. frozen
5213302 Snap or Green w/sauce, comm. frozen
5213303 Snap or Green Beans w/otherveg., comm. fr.
5213304 Sp. or Gr. Beans w/other veg./sc., comm. fr.
5213305 Wax or Yell. Beans, comm. frozen
(does not include soups, mixtures, and ready-to-eat
dinners; includes baby foods)
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, str., canned, low sod.,green/NS fat
7520512 Beans, str., canned, low sod.,green/no fat
7520513 Beans, str., canned, low sod.,green/fat
7520600 Beans, string, cooked, yellow/NS fat
7520601 Beans, string, cooked, yellow/no fat
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, str.
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)
Beef
441- Beef
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
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 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)
-------
Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued)
Food
Product
Household Code/Definition
Individual Code
Pork
442- Pork
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
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)
Game
445- Variety Meat, Game
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
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)
Poultry
451- Poultry
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
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)
Eggs
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)
3- Eggs
eggs
egg mixtures
egg substitutes
eggs baby food
froz. meals with egg as main ingred.
(includes baby foods)
Broccoli
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)
722- Broccoli (all forms)
(does not include vegetable soups; vegetable mixtures;
or vegetable with meat mixtures)
Carrots
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')
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
Product
Household Code/Definition
Individual Code
Pumpkin
4922- Fresh Pumpkin, Winter Squash (and home
canned/froz.)
51122- Pumpkin/Squash, Baby or Junior, Comm.
Canned
52122- Winter Squash, Comm. Frozen
5413504 Squash, Dried Baby Food
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
732- Pumpkin (all forms)
733- Winter squash (all forms)
76205- Squash, baby
(does not include vegetable soups; vegetables mixtures;
or vegetable with meat mixtures; includes baby foods)
Asparagus
4941 - Fresh Asparagus (and home canned/froz.)
5114101 Comm. Canned Asparagus
5115301 Asparagus, Low Sodium, Comm. Canned
52131- Comm. Frozen Asparagus
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
7510080 Asparagus, raw
75202- Asparagus, cooked
7540101 Asparagus, creamed or with cheese
(does not include vegetable soups; vegetables mixtures,
or vegetable with meat mixtures)
Lima Beans
4942- Fresh Lima and Fava Beans (and home
canned/froz.)
5114204 Comm. Canned Mature Lima Beans
5114301 Comm. Canned Green Lima Beans
5115304 Comm. Canned Low Sodium Lima Beans
52132- Comm. Frozen Lima Beans
54111 - Dried Lima Beans
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)
7510200 Lima Beans, raw
752040- Lima Beans, cooked
752041- Lima Beans, canned
75402- Lima Beans with sauce
(does not include vegetable soups; vegetable mixtures;
or vegetable with meat mixtures; does not include
succotash)
Cabbage
4944- Fresh Cabbage (and home canned/froz.)
4958601 Sauerkraut, home canned or pkgd
5114801 Sauerkraut, comm. canned
5114904 Comm. Canned Cabbage
5114905 Comm. Canned Cabbage (no sauce; incl.
baby)
5115501 Sauerkraut, low sodium., comm. canned
5312102 Sauerkraut Juice, comm. canned
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
7510300 Cabbage, raw
7510400 Cabbage, Chinese, raw
7510500 Cabbage, red, raw
7514100 Cabbage salad or coleslaw
7514130 Cabbage, Chinese, salad
75210- Chinese Cabbage, cooked
75211 - Green Cabbage, cooked
75212- Red Cabbage, cooked
752130- Savoy Cabbage, cooked
75230- Sauerkraut, cooked
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
canned/froz.)
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
75113- Lettuce, raw
75143- Lettuce salad with other veg.
7514410 Lettuce, wilted, with bacon dressing
7522005 Lettuce, cooked
(does not include vegetable soups; vegetable mixtures;
or vegetable with meat mixtures)
Okra
4946- Fresh Okra (and home canned/froz.)
5114914 Comm. Canned Okra
5213720 Comm. Frozen Okra
5213721 Comm. Frozen Okra with Oth. Veg. & Sauce
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures)
7522000 Okra, cooked, NS as to fat
7522001 Okra, cooked, fat not added
7522002 Okra, cooked, fat added
7522010 Lufta, cooked (Chinese Okra)
7541450 Okra, fried
7550700 Okra, pickled
(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
Household Code/Definition
Individual Code
Peas
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)
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)
Cucumbers
4952- Fresh Cucumbers (and home canned/froz.)
(does not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; 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)
Beets
4954- Fresh Beets (and home canned/froz.)
51145- Comm. 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)
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)
Strawberries
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 exceDt 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
Product
Household Code/Definition
Individual Code
Other
Berries
5033- Fresh Berries Other than Strawberries
5122804 Comm. Canned Blackberries with sugar
5122805 Comm. Canned Blackberries without sugar
5122806 Comm. Canned Blueberries with sugar
5122807 Comm. Canned Blueberries without sugar
5122808 Canned Blueberry Pie Filling
5122809 Comm. Canned Gooseberries with sugar
5122810 Comm. Canned 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 except mixtures)
6320- Other Berries
6321- Other Berries
6341101 Cranberry salad
6410460 Blackberry Juice
64105- Cranberry Juice
(includes baby food; except mixtures)
Peaches
5036- Fresh Peaches
51224- Comm. Canned Peaches (incl. baby)
5223601 Comm. Frozen Peaches
5332405 Home Canned Peach Juice
5423105 Dried Peaches (baby)
5423106 Dried Peaches
(does not include ready-to-eat dinners; includes baby
foods except mixtures)
62116- Dried Peaches
63135- Peaches
6412203 Peach Juice
6420501 Peach Nectar
67108- Peaches, baby
6711450 Peaches, dry, baby
(includes baby food; except mixtures)
Pears
5037- Fresh Pears
51225- Comm. Canned Pears (incl. baby)
5332403 Comm. Canned Pear Juice, baby
5362204 Fresh Pear Juice
5423107 Dried Pears
(does not include ready-to-eat dinners; includes baby
foods exceDt mixtures')
62119- Dried Pears
63137- Pears
6341201 Pear salad
6421501 Pear Nectar
67109- Pears, baby
6711455 Pears, dry, baby
Cincludes babv food: exceDt 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 FRUITS/VEGETABLES, 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 GraDe 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 foods/juices 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
5122909 Bananas, 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
Product
Household Code/Definition
Individual Code
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
6710503 Bananas, 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 foods/juices except mixtures; excludes
53323- Canned Pineapple Juice
fruit mixtures)
5332408 Canned Papaya Juice
5332410 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
Cincludes babv foodsi
-------
Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued)
Food
Product
Household Code/Definition
Individual Code
Exposed
491- Fresh Dark Green Vegetables
721- Dark Green Leafy Veg.
Veg.
493- Fresh Tomatoes
722- Dark Green Nonleafy Veg.
4941- Fresh Asparagus
74- Tomatoes and Tomato Mixtures
4943- Fresh Beans, Snap or Wax
7510050 Alfalfa Sprouts
4944- Fresh Cabbage
7510075 Artichoke, Jerusalem, raw
4945- Fresh Lettuce
7510080 Asparagus, raw
4946- Fresh Okra
75101 - Beans, sprouts and green, raw
49481- Fresh Artichokes
7510275 Brussel Sprouts, raw
49483- Fresh Brussel Sprouts
7510280 Buckwheat Sprouts, raw
4951- Fresh Celery
7510300 Cabbage, raw
4952- Fresh Cucumbers
7510400 Cabbage, Chinese, raw
4955- Fresh Cauliflower
7510500 Cabbage, Red, raw
4958103 Fresh Kohlrabi
7510700 Cauliflower, raw
4958111 Fresh Jerusalem Artichokes
7510900 Celery, raw
4958112 Fresh Mushrooms
7510950 Chives, raw
4958113 Mushrooms, home canned
7511100 Cucumber, raw
4958114 Mushrooms, home frozen
7511120 Eggplant, raw
4958118 Fresh Eggplant
7511200 Kohlrabi, raw
4958119 Eggplant, cooked
75113- Lettuce, raw
4958120 Eggplant, home frozen
7511500 Mushrooms, raw
4958200 Fresh Summer Squash
7511900 Parsley
4958201 Summer Squash, cooked
7512100 Pepper, hot chili
4958202 Summer Squash, home canned
75122- Peppers, raw
4958203 Summer Squash, home frozen
7512750 Seaweed, raw
4958402 Fresh Bean Sprouts
7512775 Snowpeas, raw
4958403 Fresh Alfalfa Sprouts
75128- Summer Squash, raw
4958504 Bamboo Shoots
7513210 Celery Juice
4958506 Seaweed
7514100 Cabbage or cole slaw
4958508 Tree Fern, fresh
7514130 Chinese Cabbage Salad
4958601 Sauerkraut
7514150 Celery with cheese
5111 - Dark Green Vegetables (all are exposed)
75142- Cucumber salads
5113- Tomatoes
75143- Lettuce salads
5114101 Asparagus, comm. canned
7514410 Lettuce, wilted with bacon dressing
51144- Beans, green, snap, yellow, comm. canned
7514600 Greek salad
5114704 Snow Peas, comm. canned
7514700 Spinach salad
5114801 Sauerkraut, comm. canned
7520600 Algae, dried
5114901 Artichokes, comm. canned
75201- Artichoke, cooked
5114902 Bamboo Shoots, comm. canned
75202- Asparagus, cooked
5114903 Bean Sprouts, comm. canned
75203- Bamboo shoots, cooked
5114904 Cabbage, comm. canned
752049- Beans, string, cooked
5114905 Cabbage, comm. canned, no sauce
75205- Beans, green, cooked/canned
5114906 Cauliflower, comm. canned, no sauce
75206- Beans, yellow, cooked/canned
5114907 Eggplant, comm. canned, no sauce
75207- Bean Sprouts, cooked
5114913 Mushrooms, comm. canned
752085- Breadfruit
5114914 Okra, comm. canned
752090- Brussel Sprouts, cooked
5114918 Seaweeds, comm. canned
75210- Cabbage, Chinese, cooked
5114920 Summer Squash, comm. canned
75211 - Cabbage, green, cooked
-------
Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued)
Food
Product
Household Code/Definition
Individual Code
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 Summer 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 Cexcl. most souds & mixtures')
-------
Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued)
Food
Product
Household Code/Definition
Individual Code
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- Corn, cooked
51146- Corn, comm. canned
752161- Corn, yellow, cooked
5114701 Peas, green, comm. canned
752162- Corn, white, cooked
5114702 Peas, baby, comm. canned
752163- Corn, 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 Corn, 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, comm. 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
Household Code/Definition
Individual Code
Root
48- Potatoes, Sweetpotatoes
71- White Potatoes and Puerto Rican St. Veg.
Vegetables
4921- Fresh Carrots
7310- Carrots
4953- Fresh Onions, Garlic
7311140 Carrots in sauce
4954- Fresh Beets
7311200 Carrot chips
4957- Fresh Turnips
734- Sweetpotatoes
4958101 Fresh Celeriac
7510250 Beets, raw
4958102 Fresh Horseradish
7511150 Garlic, raw
4958104 Fresh Radishes, no greens
7511180 Jicama (yambean), raw
4958105 Radishes, home canned
7511250 Leeks, raw
4958106 Radishes, home frozen
75117- Onions, raw
4958107 Fresh Radishes, with greens
7512500 Radish, raw
4958108 Fresh Salsify
7512700 Rutabaga, raw
4958109 Fresh Rutabagas
7512900 Turnip, raw
4958110 Rutabagas, home frozen
752080- Beets, cooked
4958115 Fresh Parsnips
752081 - Beets, canned
4958116 Parsnips, home canned
7521362 Cassava
4958117 Parsnips, home frozen
7521740 Garlic, cooked
4958502 Fresh Lotus Root
7521771 Horseradish
4958509 Ginger Root
7521850 Lotus root
4958510 Jicama, including yambean
752210- Onions, cooked
51121 - Carrots, comm. canned
7522110 Onions, dehydrated
51145- Beets, comm. canned
752220- Parsnips, cooked
5114908 Garlic Pulp, comm. canned
75227- Radishes, cooked
5114910 Horseradish, comm. prep.
75228- Rutabaga, cooked
5114915 Onions, comm. canned
75229- Salsify, cooked
5114916 Rutabagas, comm. canned
75234- Turnip, cooked
5114917 Salsify, comm. canned
75235- Water Chestnut
5114921 Turnips, comm. canned
7540501 Beets, harvard
5114922 Water Chestnuts, comm. canned
75415- Onions, creamed, fried
51151 - Carrots, canned, low sod.
7541601 Parsnips, creamed
5115305 Beets, canned, low sod.
7541810 Turnips, creamed
5115502 Turnips, low sod.
7550021 Beets, pickled
52121- Carrots, comm. froz.
7550309 Horseradish
5213714 Beets, comm. froz.
7551201 Radishes, pickled
5213722 Onions, comm. froz.
7553403 Turnip, pickled
5213723 Onions, comm. froz., with sauce
76201- Carrots, baby
5213725 Turnips, comm. froz.
76209- Sweetpotatoes, baby
5312103 Canned Carrot Juice
76403- Beets, baby
5312104 Canned Beet Juice
(does not include vegetable soups; vegetable mixtures;
5372102 Fresh Carrot Juice
or vegetable with meat mixtures)
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')
-------
Appendix 13A. Food Codes and Definitions Used in Analysis of the 1987-88 USDA NFCS Data (continued)
Food
Product
Household Code/Definition
Individual Code
USDA SUBCATEGORIES
Dark Green
Vegetables
491- Fresh Dark Green Vegetables
5111 - Comm. Canned Dark Green Veg.
51154- Low Sodium Dark Green Veg.
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
vegetables)
72- Dark Green Vegetables
all forms
leafy, nonleafy, dk. gr. veg. soups
Deep Yellow
Vegetables
492- Fresh Deep Yellow Vegetables
5112- Comm. Canned Deep Yellow Veg.
51151 - Low Sodium Carrots
5212- Comm. Frozen Deep Yellow Veg.
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)
73- Deep Yellow Vegetables
all forms
carrots, pumpkin, squash, sweetpotatoes, dp.
yell. veg. soups
Other
Vegetables
494- Fresh Light Green Vegetables
495- Fresh Other Vegetables
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 not include soups, sauces, gravies, mixtures, and
ready-to-eat dinners; includes baby foods except
mixtures/dinners; excludes vegetable juices and dried
vegetables)
75- Other Vegetables
all forms
Citrus Fruits
501- Fresh Citrus Fruits
5121- Comm. Canned Citrus Fruits
5331- Canned Citrus and Citrus Blend Juice
5341- Frozen Citrus and Citrus Blend Juice
5351- Aseptically Packed Citrus and Citr. Blend
Juice
5361 - Fresh Citrus and Citrus Blend Juice
(includes baby foods; excludes dried fruits)
61 - Citrus Fruits and Juices
6720500 Orange Juice, baby food
6720600 Orange-Apricot Juice, baby food
6720700 Orange-Pineapple Juice, baby food
6721100 Orange-Apple-Banana Juice, baby food
(excludes dried fruits)
Other Fruits
502- Fresh Other Vitamin C-Rich Fruits
503- Fresh Other Fruits
5122- Comm. Canned Fruits Other than Citrus
5222- Frozen Strawberries
5223- Frozen Other than Citr. or Vitamin C-Rich Fr.
5332- Canned Fruit Juice Other than Citrus
5342- Frozen Juices Other than Citrus
5352- Aseptically Packed Fruit Juice Other than Citr.
5362- Fresh Fruit Juice Other than Citrus
542- Dry Fruits
(includes baby foods; excludes dried fruits)
62- Dried Fruits
63- Other Fruits
64- Fruit Juices and Nectars Excluding Citrus
671- Fruits, baby
67202- Apple Juice, baby
67203- Baby Juices
67204- Baby Juices
67212- Baby Juices
67213- Baby Juices
673- Baby 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
Food 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.
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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]
Table 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, 3 kb]
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
[WK1, 3 kb]
Table 13-23. Consumer Only Intake of Home Caught Fish (g/kg-day) - All Regions
Combined [WK1, 5 kb]
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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 kb]
Table 13-28. Consumer Only Intake of Home Produced Dairy (g/kg-day) - All 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-day) [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
[WK1, 6 kb]
Table
13-50.
Consumer Only
Intake
of
Table
13-51.
Consumer Only
Intake
of
Table
13-52.
Consumer Only
Intake
of
Table
13-53.
Consumer Only
Intake
of
Table
13-54.
Consumer Only
Intake
of
Table
13-55.
Consumer Only
Intake
of
Table
13-56.
Consumer Only
Intake
of
Table
13-57.
Consumer Only
Intake
of
[WK1, 7 kb]
Table
13-58.
Consumer Only
Intake
of
[WK1, 6 kb]
Table
13-59.
Consumer Only
Intake
of
Table
13-60.
Consumer Only
Intake
of
[WK1, 7 kb]
Table
13-61.
Consumer Only
Intake
of
[WK1, 7 kb]
Table
13-62.
Consumer Only
Intake
of
[WK1, 6 kb]
Table
13-63.
Consumer Only
Intake
of
[WK1, 7 kb]
Table
13-64.
Consumer Only
Intake
of
[WK1, 7 kb]
Table
13-65.
Consumer Only
Intake
of
[WK1, 7 kb]
Table
13-66.
Consumer Only
Intake
of
[WK1, 7 kb]
Table
13-67.
Consumer Only
Intake
of
[WK1, 7 kb]
Table
13-68.
Consumer Only
Intake
of
[WK1, 7 kb]
Table
13-69.
Consumer Only
Intake
of
Table
13-70.
Consumer Only
Intake
of
Intake of Homegrown Other Berries (g/kg-day)
Homegrown Peaches (g/kg-day) [WK1, 6 kb]
Homegrown Pears (g/kg-day) [WK1, 6 kb]
Homegrown Peas (g/kg-day) [WK1, 7 kb]
Homegrown Peppers (g/kg-day) [WK1, 6 kb]
Home Produced Pork (g/kg-day) [WK1, 6 kb]
Home Produced Poultry (g/kg-day) [WK1, 6 kb]
Homegrown Pumpkins (g/kg-day) [WK1, 6 kb]
Homegrown Snap Beans (g/kg-day)
ntake of Homegrown Strawberries (g/kg-day)
ntake of Homegrown Exposed Fruit (g/kg-day)
ntake of Homegrown Protected Fruits (g/kg-day)
ntake of Homegrown Exposed Vegetables (g/kg-day)
ntake of Homegrown Protected Vegetables (g/kg-day)
ntake of Homegrown Root Vegetables (g/kg-day)
ntake of Homegrown Dark Green Vegetables (g/kg-day)
ntake of Homegrown Deep Yellow Vegetables (g/kg-day)
ntake of Homegrown Other Vegetables (g/kg-day)
-------
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.
Table 14-2.
Table 14-3.
Table 14-4.
Table 14-5.
Table 14-6.
Table 14-7.
Table 14-8.
Table 14-9.
Table 14-10.
Table 14-11.
Table 14-12.
Table 14-13.
Table 14-14.
Table 14-15.
Table 14-16.
Daily Intakes of Breast Milk
Breast Milk Intake for Infants Aged 1 to 6 Months
Breast Milk Intake Among Exclusively Breast-fed Infants During the First 4
Months of Life
Breast Milk Intake During a 24-Hour Period
Breast Milk Intake Estimated by the DARLING Study
Milk Intake for Bottle- and Breast-fed Infants by Age Group
Milk Intake for Boys and Girls
Intake of Breast Milk and Formula
Lipid Content of Human Milk and Estimated Lipid Intake Among Exclusively
Breast-fed Infants
Predicted Lipid Intakes for Breast-fed Infants Under 12 Months of Age
Number of Meals Per Day
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
Breast Milk Intake Studies
Confidence in Breast Milk Intake Recommendations
Breast Milk Intake Rates Derived From Key Studies
Summary of Recommended Breast Milk and Lipid Intake Rates
Ex^osure^actors^IanJbool^
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). Neville 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. When 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).
-------
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 at. (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 enroll 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
collected over 3 consecutive days which would account for some individual variability.
However, the 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
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Davis area of California. Breast milk intake volume was estimated based on two 24-hour
test weighings per month. Breast milk intake rates 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 at. (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, 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 mean 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
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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., 1991a; 1991b). Seventy-
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.
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Chapter 14 - Breast Milk Intake
14.3. RELEVANT STUDIES ON BREAST MILK INTAKE
Hofvander et at. (1982) - The Amount of Milk Consumed by 1- to 3-Month Old Breast-
orBottle-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 intake 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 short-term data were collected.
Kohleret al. (1984) - Food Intake and Growth of Infants Between Six and Twenty-six
Weeks of Age on Breast Milk, Cows 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 milk-
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 population studied was not representative of the U.S.
population, similar intake rates were observed in the studies that were previously
summarized.
Axelsson etal. (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
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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. KEY 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
lipid 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
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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 et al. (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 infants at 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 (1991), the percentage of breast-feeding women has changed
dramatically over the years. Between 1936 and 1940, approximately 77 percent of infants
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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 1982. 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 underprivileged 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 that the lactational capacity and
energy concentration of marginally-nourished women in Bangladesh were "modestly less
than in better nourished mothers." 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 etal. (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
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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 limitations 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, 742 mL/day is recommended to represent
an average breast milk intake rate, and 1,033 mL/day represents an upper-percentile
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 mL/day for 12-month olds (Neville etal. 1988; Dewey et al. 1991a; 1991b).
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 mL/day) 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).
-------
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.
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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:
Dewev and Lonnerdal, 1983.
-------
Table 14-3. Breast Milk Intake Among Exclusively Breast-fed
Infants During the First 4 Months of Life
Age (months)
Number
of
Infants
Breast Milk
Intake3
(g/day)
Breast Milk
Intake3
(g/kg-day)
Body
Weight1
(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.
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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
-31-149 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 insensible water loss correction.
Source: Neville et al., 1988.
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Table 14-5. Breast Milk Intake Estimated by the DARLING Study
Age (months)
Number of
Mean Intake
Standard Deviation
Infants
(cj/day)
(cj/day)
3
73
812
133
6
60
769
171
9
50
646
217
12
42
448
251
Source: Dewev et al. (1991 b1
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Table 14-6.
Milk Intake for Bottle- and Breast-fed
Infants by Age Group
Age
Breast Milk Substitutes
Breast Milk
(months)
Mean (g/day)a
Mean (g/day)a
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.
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Table 14-7. Milk Intake for Boys and Girls
Boys
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.
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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)
(g/day)
(g/day)
(g/day)
(g/day)
(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
Among Exclusively Breast-fed Infants
Age (months) Number
Lipid
Lipid
Lipid
Lipid
of
Content
Content
Intake
Intake
Observations
(mg/g)a
(percent)b
(g/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
Minimum Lipid Intake
Maximum Lipid Intake
Arithmetic Mean Lipid Intake
Standard Deviation Lipid Intake
1,113
1.0 g/day
51.5 g/day
26.8 g/day
7.4 a/dav
Source: Maxwell and Burmaster, 1993.
-------
Table 14-11. Number of Meals Per Day
Age (months) Bottle-fed Infants
(meals/day) a
Breast-fed
(meals/day) a
1 5.4 (4-7)
5.8 (5-7)
2 4.8 (4-6)
5.3 (5-7)
3 4.7 (3-6)
5.1 (4-8)
a Data expressed as mean with range in parentheses.
Source: Hofvander et al., 1982.
-------
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 1989a
by Ethnic Background and Selected Demographic Variablesb
Total
White
Black
Hispa
nicc
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
>35 yr
66.5
36.2
71.9
40.5
35.6
14.3
53.9
24.4
Maternal education
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
>$25,000
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
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.
College includes all women who reported completing at least 1 year of college.
Source: NAS. 1991.
-------
Table 14-13. Breast Milk Intake Studies
Study
Number of
Individuals
Type of Feeding
Sampling Time and Interval
Population Studied
Comments
KEY STUDIES
Butte etal., 1984
45
Exclusively breast-fed
for first 4 months
Most infants studied over 1
day only, at 1, 2, 3, 4 months
some studied over 48 to 96
hours to study individual
variability
Mid- to upper-
socioeconomic stratum
Estimated breast milk intake;
corrected for insensible water loss
Dewey et al.,
1991a; 1991b
73
Breast-fed for 12
months; exclusively
breast-fed for at least
first 4 months
Test weighing over 4-day
period every 3 months for 1
year
Highly educated, high-
socioeconomic class from
Davis area of California
Estimated breast milk intake;
corrected for insensible water loss
Dewey and
Lonnerdal, 1983
20
Most infants exclusively
breast-fed
Two test weighings per month
for 6 months
Mid to upper class from
Davis area of California
Estimated breast milk intake; did
not correct for insensible water
loss
Neville et al.,
1988
13
Exclusively breast-fed
infants
Infants studied over 24-hour
period at each sampling
interval; numerous sampling
intervals over first year of life
Nonsmoking Caucasian
mothers; middle- to
upper-socioeconomic
status
Estimated breast milk intake and
lipid intake; corrected for
insensible water loss; estimated
frequency and duration of feeding
Pao et al., 1980
22
Completely or partially
breast-fed infants
Three consecutive days at 1,
3, 6, and 9 months
White middle class from
southeastern Ohio
Estimated breast milk intake; did
not correct for insensible water
loss
-------
Table 14-13. Breast Milk Intake Studies (continued)
Study
Number of
Individuals
Type of Feeding
Sampling Time and Interval
Population Studied
Comments
RELEVANT
STUDIES
Axelsson et al.,
1987
30
Breast-fed infants and
infants fed formula with
two different energy
contents
Studied over 2-day periods
at 4.5 and 5.5 months of
age
Swedish infants
Measured intake rates; not
corrected for insensible water loss
Brown et al., 1986a;
1986b
58, 60
Breast-fed infants
Studied over 3 days at each
interval
Bangledeshi infants;
marginally nourished
mothers
Measured milk and nutrient intake
based on nutritional status; not
corrected for insensible water loss
Hofvanderetal.,
1982
50
25 breast-fed and 25
formula-fed infants
Studied 24-hour period at 1,
2, and 3 months
Swedish infants
Estimated breast milk and formula
intake; no corrections for insensible
water loss among breast-fed infants;
estimated frequency of feeding
Kohleret al., 1984
59
25 fully breast-fed and 34
formula-fed infants
Studied over 48-hour
periods at 6,14, 22, and 26
weeks of age
Swedish infants
Estimated breast milk and formula
intake based on nutritional status;
no corrections for insensible water
loss among breast-fed infants
Maxwell and
Burmaster, 1993
1,113
Population of 1,113
breast-fed infants based
on a hypothetical
population of 5,000
breast-fed and bottle-fed
infants
NA
NA
Simulated distribution of breast milk
intake based on data from Dewey
1991 a; estimated percent of breast-
fed infants under 12 months of age
NAS, 1991
NA
Breast-fed infants
NA
NA
Summarizes current
state-of-knowledge on breast milk
volume, composition and
breast-feedina populations
-------
Table 14-14. Confidence in Breast Milk Intake Recommendations
Considerations
Rationale
Rating
Study Elements
Level of peer review
All key studies are from peer review literature.
High
Accessibility
Papers are widely available from peer review journals.
High
Reproducibility
Methodology used was clearly presented.
High
Focus on factor of interest
The focus of the studies was on estimating breast milk intake.
High
Data pertinent to U.S.
Subpopulations of the U.S. were the focus of all the key studies.
High
Primary data
All the studies were based on primary data.
High
Currency
Studies were conducted between 1980-1986. Although incidence of
breast feeding may change with time, breast milk intake among
breastfed infants may not.
Medium
Adequacy of data collection period
Infants were not studied long enough to fully characterize day to day
variability.
Medium
Validity of approach
Methodology uses changes in body weight as a surrogate for total
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.
Medium
Study size
The sample sizes used in the key studies were fairly small (range 13-
73).
Representativeness of the
population
Population is not representative of the U.S.; only mid-upper class, well
nourished mothers were studied. Socioeconomic factors may affect
the incidence of breastfeeding. Mother's nourishment may affect milk
production.
Low
Characterization of variability
Not very well characterized. Infants under 1 month not captured,
mothers committed to breast feeding over 1 year not captured.
Low
Lack of bias in study design (high
rating is desirable)
Bias in the studies was not characterized. Three out of 5 studies
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).
Low
Measurement error
All mothers were well educated and trained in the use of the scale
which helped minimize measurement error.
Medium
Other Elements
Number of studies
There are 5 key studies.
High
Agreement between researchers
There is good agreement among researchers.
High
Overall Rating
Studies were well designed. Results were consistent. Sample size
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.
Medium
-------
Table 14-15.
Breast Milk Intake Rates Derived From Key Studies
Mean (mL/day)
N
Upper Percentile (mL/day)
(mean plus 2 standard
deviations)
Reference
Age: 1 Month
600
729
747
673
11
37
13
16
918
981
1,095
1,057
Pao et al., 1980
Butte et al., 1984
Neville et al., 1988
Dewey and Lonnerdal, 1983
weighted avg = 702
1,007"
Age: 3 Months
833
702
712
782
788
2
37
12
16
73
923
934
1,126
1,046
Pao et al., 1980
Butte et al., 1984
Neville et al., 1988
Dewey and Lonnerdal, 1983
Dewey et al., 1991b
weighted avg = 759
1,025"
6 Months
682
744
896
747
I
13
II
60
978
1,140
1,079
Pao et al., 1980
Neville et al., 1988
Dewey and Lonnerdal, 1983
Dewey et al., 1991b
weighted avg = 765
1,059a
9 Months
600
627
12
50
1,027
1,049
Neville et al., 1988
Dewey et al., 1991b
avg = 622
1,038
72 Months
391
435
9
42
877
923
Neville et al., 1988
Dewey et al., 1991 a; 1991 b
weighted avg = 427
900
12-MONTH TIME WEIGHTED
AVERAGE
688
Range 900-1,059
(middle of the range 980)
a Middle of the range.
-------
Table 14-16. Summary of Recommended Breast Milk and Lipid Intake Rates
Age
Mean
Upper Percentile
Breast Milk
1-6 Months
742 mL/day
1,033 mL/day
12 Month Average
688 mL/day
980 mL/day
Lipids3
<1 Year
26.0 mL/day
40.4 mL/day
-------
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.D.; Ahmed, M.G. (1986a) Lactational capacity
of marginally nourished mothers: relationships between maternal nutritional status
and quantity and proximate composition of milk. Pediatrics. 78: 909-919.
Brown, K.H.; Robertson, A.D.; 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 breast-
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 PATTERNS
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 CARB 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 CARB and National Study (ages 18-64 years)
Table 15-7. Mean Time Spent at Three Locations for both CARB and National Studies
(ages 12 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
Ex^osureFactors^Iandbool^
August 1997
-------
Volume III - Activity Factors
Cha^terJJ^A^tivi^^actor^
Mean Time (minutes/day) Children Spent in Ten Major Activity Categories
for All Respondents
Mean Time Children Spent in Ten Major Activity Categories Grouped by Age
and Gender
Mean Time Children Spent in Ten Major Activity Categories Grouped by
Seasons and Regions
Mean Time Children Spent in Six Major Location Categories for All
Respondents (minutes/day)
Mean Time Children Spent in Six Location Categories Grouped by Age and
Gender
Mean Time Children Spent in Six Location Categories Grouped by Season
and Region
Mean Time Children Spent in Proximity to Three Potential Exposures
Grouped by All Respondents, Age, and Gender
Range of Recommended Defaults for Dermal Exposure Factors
Number of Times Taking a Shower at Specified Daily Frequencies by the
Number of Respondents
Times (minutes) Spent Taking Showers by the Number of Respondents
Number of Minutes Spent Taking a Shower (minutes/shower)
Time (minutes) Spent in the Shower Room Immediately After Showering by
the Number of Respondents
Number of Minutes Spent in the Shower Room Immediately After Showering
(minutes/shower)
Number of Baths Given or Taken in One Day by Number of Respondents
Total Time Spent Taking or Giving a Bath by the Number of Respondents
Number of Minutes Spent Giving and Taking the Bath(s) (minutes/bath)
Time Spent in the Bathroom Immediately After the Bath(s) by the Number
of Respondents
Number of Minutes Spent in the Bathroom Immediately After the Bath(s)
(minutes/bath)
Total Time Spent Altogether in the Shower or Bathtub by the Number of
Respondents
Total Number of Minutes Spent Altogether in the Shower or Bathtub
(minutes/bath)
Time Spent in the Bathroom Immediately Following a Shower or Bath by the
Number of Respondents
Number of Minutes Spent in the Bathroom Immediately Following a Shower
or Bath (minutes/bath)
Range of Number of Times Washing the Hands at Specified Daily
Frequencies by the Number of Respondents
Number of Minutes Spent (at home) Working or Being Near Food While
Fried, Grilled, or Barbequed (minutes/day)
Table
15-11
Table
15-12
Table
15-13
Table
15-14
Table
15-15
Table
15-16
Table
15-17
Table
15-18
Table
15-19
Table
15-20
Table
15-21
Table
15-22
Table
15-23
Table
15-24
Table
15-25
Table
15-26
Table
15-27
Table
15-28
Table
15-29
Table
15-30
Table
15-31
Table
15-32
Table
15-33
Table
15-34
Ex^osureFactors^Iandbool^
August 1997
-------
Volume III - Activity Factors
Cha^terJJ^Activi^^actor^
Table 15-35. Number of Minutes Spent (at home) Working or Being Near Open Flames
Including Barbeque Flames (minutes/day)
Table 15-36. Number of Minutes Spent Working or Being Near Excessive 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 Spent 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
Ex^osureFactors^Iandbool^
August 1997
-------
Volume III - Activity Factors
Cha^terJJ^A^tivi^^actor^
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
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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 at
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
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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 at a
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 Home 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-up/Van)
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
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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 Cumulative 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 Outdoors
(outside the residence)
Table 15-133. 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
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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 Sex, 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. Occupational Tenure of Employed Individuals by Age and Sex
Table 15-159. Occupational Tenure for Employed Individuals Grouped by Sex and Race
Table 15-160. Occupational Tenure for Employed 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
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Table 15-173. Confidence in Occupational Mobility Recommendations
Table 15-174. 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.
Table 15A-2.
Table 15A-3.
Table 15A-4.
Table 15A-5.
Table 15A-6.
Table 15A-7.
Table 15B-1.
Table 15B-2.
Activity Codes and Descriptors Used for Adult Time Diaries
Differences in Average Time Spent in Different Activities Between
California and National Studies (minutes per day for age 18-64 years)
Time Spent in Various Microenvironments
Major Time Use Activity Categories
Mean Time Spent (minutes/day) for 87 Activities Grouped by Day of the
Week
Weighted Mean Hours Per Week by Gender: 87 Activities and 10
Subtotals
Ranking of Occupations by Median Years of Occupational Tenure
Annual Geographical Mobility Rates, by Type of Movement for Selected 1-
Year Periods: 1960-1992 (numbers in thousands)
Mobility of the Resident Population by State: 1980
Figure 15-1. Distribution of Individuals Moving by Type of Move: 1991 -92
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Chapter 15 -Activity 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
the 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.
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
15.1.
ACTIVITY PATTERNS
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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
of four 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 contact 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 location 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
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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.
A 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
conducted 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 results in Table 15-3, approximate showering times
are 7 minutes for the median value, 13 minutes for the 90th percentile, 16 minutes 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.
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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 (CARB)
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 CARB code categories, in order to
make data comparisons (Robinson and Thomas, 1991).
The CARB study involved 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. Telephone interviews based on the random-digit-dialing
(RDD) procedure were conducted for approximately 1,762 respondents in the CARB
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
RDD method. The RDD 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
household. 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 keeping 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 CARB 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,
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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 (time 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 population. Table 15-6 shows the mean
time spent at 3 major locations for the CARB 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 CARB 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 CARB 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 CARB 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 (CARB 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
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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 activities.
Limitations associated with the Robinson and Thomas (1991) study are that the
CARB 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. (1991) - 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 RDD 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
questionnaire 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 highest time expenditure of 794 mins/day
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(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
gender. 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 various 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
m ins/day).
A limitation of this study is that the sampling population was restricted to only English-
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 respondents 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
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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 of 91 different activities. Participants were selected using a
Random Digit Dial (RDD) 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. population. 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 follow-
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 provides frequency distributions of
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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
15-92. NHAPS data on the time spent in selected microenvironments are presented in
Tables 15-93 to 15-139 and of these tables, 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 taking 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 dust in the air.
• Tables 15-37 through 15-39 provide data for the number of times 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.
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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.
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; bar/ 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.
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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 through 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 two 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, diaries were kept on 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.
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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 sub-
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 these 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)
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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 eligible. 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 obtained 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.
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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.
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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 10 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
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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 percent 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
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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 Average 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 references.
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
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study because it is not the primary source for the data used to make recommendations.
It is a relevant source of alterative information.
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 a farmer 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 occupations" (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. The 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 and 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).
15.2. OCCUPATIONAL MOBILITY
15.2.1.
Background
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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. Another 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 Mobility -
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 tenure was 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).
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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 apply 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 exposure 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 of movers by type of move
(BOC, 1993a).
Available information was provided by the Oxford Development Corporation, the
National Association of Realtors (NAR), and the BOC. According to Oxford Development
Corporation, a property management firm, the typical residence time for an apartment
dweller for their corporation has been estimated to range from 18 to 30 months (S.
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Cameron Hendricks, Sales Department, Oxford Development Corporation, Gaithersburg,
MD, personal communication with P. Wood (Versar) August 10, 1992).
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 move 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 the 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 is 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.
15.3.2.
Key Population Mobility Studies
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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 current house. 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 Cape! (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 demographic 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 gender. The estimated mean ROP for the total population was 11.7 years.
The distribution was skewed (Johnson and Capel, 1992): the 25th, 50th, and 75th
percentiles were 4, 9, and 16 years, respectively. The 90th, 95th, and 99th percentiles
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were 26, 33, and 47 years, respectively. The mean ROP was 11.1 years for males and
12.3 years for females, 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. These
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
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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 the following
recommended values. These values are applicable to individuals 12 years and older.
Approximately 21 hrs/day are spent indoors; 1.5 hrs/day are spent outdoors, and 1.5
hrs/day are spent in a vehicle.
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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) as 2 hr/day. These data apply to adult populations.
•~Tsang 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. These
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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 these 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 minutes 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
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day (16.4 hours/day); and a 90th percentile 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 CARB 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 value 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
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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 15-174.
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.
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Table 15-1. Time Use Table Locator Guide
Percentile
Basis
PoDulation
ADDlication
Studv
Table
Averages
Activity
Children 3-17yrs
National
Timmeret al., 1985
15-2
Distribution
Activity
Children and Teens
National
Timmeret al., 1985
15-3
Distribution
Showering
Adults
Foreign-Australia
James and Knuiman, 1987
Tsang and Klepeis, 1996
15-4
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
15-7 to 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
season
Infants and Children
Regional-California
Wiley et al., 1991
15-16
Distribution
Microenvironment near
pollutant
Infant and Children
Regional-California
Wiley et al., 1991
15-17
Averages
Bathing and swimming
Adults
Regional-National
USEPA, 1992
Tsang and Klepeis, 1996
15-18
15-22, 15-63
Average
Activity by employment
Adults
National
Robinson, 1977
15-147
Averages
Occupational Tenure
by race and gender
Teens and Adults
National
Carey, 1988
15-157
Averages
Occupational Tenure
by employment and
gender
Teens and Adults
National
Carey, 1988
15-158
Distribution
Occupational Tenure
by employment
Teens and Adults
National
Carey, 1988
15-159
Distribution
Occupational Mobility
by age
Teens and Adults
National
Carey, 1990
15-160
Distribution
Population Mobility by
locale
All ages
National
Census, 1993
Figure 15-1
Averages
Residence Time by
region, setting
All ages
National
Israeli and Nelson, 1992
15-161
Distribution
Residence Time by
region, setting
All ages
National
Israeli and Nelson, 1992
15-162
Distribution
Residence Time by
year moved in
All ages
National
Census, 1993
15-163
Distribution
Residence Time by
years in current home
All ages
National
Census, 1993
15-164
Distribution
Residence Time by
gender
All ages
National
Johnson and Capel, 1992
15-165
Distribution
Residence Time by age All ages
National
Johnson and Capel, 1992
15-166
Distribution
Residence Time by
years in previous house
All ages
National
NAR, 1993
15-167
Distribution
Residence Time by
tenure in previous
home
All ages
National
NAR, 1993
15-168
Distribution
Relocation Distance
All aqes
National
NAR, 1993
15-169
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Table 15-2. Mean Time Spent (minutes) Performing Major Activities Grouped by Age, Sex and Type of Day
Activity Aoe C3-11 vearsl Age C12-17 vearsl
Duration of Time (mins/day) Duration of Time (mins/day)
Weekdays Weekends Weekdays Weekends
Boys
(n=118)
Girls
(n=111)
Boys
(n=118)
Girls
(n=111)
Boys
(n=77)
Girls
(n=83)
Boys
(n=77)
Girls
(n=83)
Market Work
16
0
7
4
23
21
58
25
Household Work
17
21
32
43
16
40
46
89
Personal Care
43
44
42
50
48
71
35
76
Eating
81
78
78
84
73
65
58
75
Sleeping
584
590
625
619
504
478
550
612
School
252
259
-
-
314
342
-
-
Studying
14
19
4
9
29
37
25
25
Church
7
4
53
61
3
7
40
36
Visiting
16
9
23
37
17
25
46
53
Sports
25
12
33
23
52
37
65
26
Outdoors
10
7
30
23
10
10
36
19
Hobbies
3
1
3
4
7
4
4
7
Art Activities
4
4
4
4
12
6
11
9
Playing
137
115
177
166
37
13
35
24
TV
117
128
181
122
143
108
187
140
Reading
9
7
12
10
10
13
12
19
Household Conversations
10
11
14
9
21
30
24
30
Other Passive Leisure
9
14
16
17
21
14
43
33
NAa
22
25
20
29
14
17
10
4
Percent of Time Accounted
94%
92%
93%
89%
93%
92%
88%
89%
for bv Activities Above
a NA = Unknown
Source: Timmeret al.. 1985.
-------
Table 15-3.
Mean Time Spent (min
utes) in Maior Activities Grouped by Type of Day for Five Different Age Groups
Time Duration (m
ns)
Significant
Weekday
Weekend
Effects3
Aae Cvearsl
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,AxS (F>M)
Household Work
14
15
18
27
34
17
27
51
72
60
A,S, AxS (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, AxS (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 = females spend more time than males, or vice versa; and AxS = age by sex
interaction, PO.05.
Source: Timmeret al.. 1985.
-------
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 CARB and National Studies (age 18-64 years)
Time Duration (mins/day)
Activity Category3
Activity
Codes
CARB
(1987-88)
National
(1985)
CARB
(1987-88)
National
(1985)
Total Sample
Men
Women
Men
Women
nc = 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
Services
30-39
61
55
48
73
44
62
Personal Needs and
Care
40-49
642
642
630
655
636
645
Education and Training
50-59
22
19
25
20
21
16
Organizational Activities
60-69
12
17
11
13
12
20
Entertainment/Social
Activities
70-79
60
62
57
55
64
62
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 CARB and National Study (ages 18-64 years)
Location3
Codeb
CARB
(1987-88)
National
(1985)
CARB
(1987-88)
National
(1985)
Total Sample
Men
Women
Men
Women
nc = 1359
nc = 1980
nc = 39
nc = 720
nc = 921
nc = 1059
At Home
WC01-13
892
954
822
963
886
1022
Away From Home
WC21-40
430
384
487
371
445
324
Travel
WC51-61
116
94
130
102
101
87
Not Ascertained
WC99
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)
Location Category
Mean duration (mins/day)
CARB
(n = 1762)b
S.E.!
National
(n = 2762)b
S.E.
Indoor
Outdoor
In-Vehicle
Total Time Spent
1255c
86d
98?
1440
28
5
4
1279c
74d
8Z!
1440
21
4
2
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 years and over) in the National and CARB Data
National Data
Mean Duration (mins/day) (standard
error)3
Microenvironment
N = 1284b
Men
"Doer"c
Men
N = 1478b
Women
"Doer"
Women
N = 2762b
Total
"Doer"
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
SleeD/indoors
491 (14)
492
496 (11)
497
494 (9)
495
CARB Data
Mean Duration (mins/day) (standard
error)®
Microenvironment
N = 867b
Men
"Doer"c
Men
N = 895b
Women
"Doer"
Women
N = 1762b
Total
"Doer"
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
Work/study-residence
14(3)
126
11 (2)
120
13(2)
131
Work/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
SleeD/indoors
492 (17)
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.
Source: 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)3
Mean Duration for
'Doer"b
Microenvironment
(mins/day)
(mins/day)
CARB
NAT
(n=1259)c
(n=1973)c
CARB
NAT
1 Autoplaces
21 (5)
3(1)
108
73
2 Restaurant/Bar
29(3)
20 (2)
83
73
3 In-Vehicle/lnternal 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)3
Mean Duration for
'Doer"b
Microenvironment
(mins/day)
(mins/day)
CARB
NAT
(n=503)c
(n=789)c
CARB
NAT
1 Autoplaces
19(4)
3(1)
82
62
2 Restaurant/Bar
55 (6)
23 (2)
127
84
3 In-Vehicle/lnternal 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
a Standard Error of Mean
b Doer = Respondent who reported participating in each activity /location spent in microenvironments.
"Weighted Number
Source: Robinson and Thomas,
1991.
-------
Table 15-10. Mean Time Spent (minutes/day) in Various Microenvironments by Age Groups for the National and California Surveys
Microenvironment
National Data
Mean Duration (Standard Error)®
Age 12-17
years
N=340b
"Doer"c
Age 18-24
years
N=340
"Doer"
Age 24-44
years
N=340
"Doer"
Age 45-64
years
N=340
"Doer"
Age 65+
years
N=340
"Doer"
Autoplaces
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-
eat/indoors
237 (16)
242
181 (11)
189
200 (8)
208
238 (11)
244
303 (20)
312
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)
Microenvironment
CARB Data
Mean Duration (Standard Error)
a
Age 12-17
years
N=183b
"Doer"c
Age 18-24
years
N=250
"Doer"
Age 24-44
years
N=749
"Doer"
Age 45-64
years
N=406
"Doer"
Age 65+
years
N=158
"Doer"
Autoplaces
16(8)
124
16(4)
71
25 (9)
114
20 (5)
94
9(2)
53
Restaurant/bar
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-eat/indoors
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.
c Doer = Respondents who reported participating in each activity/location spent in microenvironments.
Source: Robinson and Thomas, 1991.
-------
Table 15-11. Mean Time (minutes/day) Children Spent in Ten Major
Activity Categories for All Respondents
Mean Median Maximum
Activity Cateaorv
Mean
Duration
(mins/davl
%
Doina
Duration
for Doersb
(mins/davl
Duration
for Doer
(mins/davl
Duration
for Doers
(mins/davl
Detailed Activity with
Highest Avg. Minutes
(coael
Work-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 Carec
794
100
794
770
1440
Night sleep (45)
Education11
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
Leisure
192
93
205
180
898
TV use (91)
Don't know/Not coded
2
4
41
15
600
-
All Activities8
1441
a Includes eating at school or daycare, an activity not grouped under the "education activities" (codes 50-59, 549).
b "Doers" indicate the respondents who reported participating in each activity category.
c Personal care includes night sleepand daytime naps, eating, travel for personal care.
d Education includes student and other classes, homework, library, travel for education.
8 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 Age and Gender
Mean Duration Cminutes/davl
Activity Boys Girls
Category
0-2 yrs
3-5 yrs
6-8 yrs
9-11 yrs
All
Ages
0-2 yrs
3-5 yrs
6-8 yrs
9-11 yrs
All
Ages
Work-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
Care"
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
Entertainment/Social
3
15
5
34
13
5
16
9
36
17
Recreation
217
311
236
229
250
223
255
238
194
228
Communication/Passive
Leisure
187
166
195
250
197
171
173
189
213
186
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
Unweiqhted N's
172
151
145
156
624
141
151
124
160
576
a 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: Wilev 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
Wnter
(Jan-Mar)
Spring
(Apr-June)
Summer
(July-Sept)
Fall
(Oct-Dec)
All
Seasons
So.
Coast
Bay
Area
Rest of
State
All
Regions
Work-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
Care"
799
774
815
789
794
799
785
794
794
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
e Leisure
203
180
189
195
192
206
190
175
192
Don't know/Not coded
<1
2
3
<1
2
1
1
3
2
All Activities'
1442
1439
1441
1441
1441
1440
1442
1439
1441
Sample Sizes
(Unweighted)
318
204
407
271
1200
224
263
713
1200
a 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 not be equal to 1440 due to rounding error.
Source: Wiley et al., 1991.
-------
Table 15-14.
Mean Time Children Spent
in Six Maior Location Catego
ries for All Respondents (minutes/day)
Location Category
Mean
Duration
(mins)
%
Doing
Mean
Duration
for Doers
Cminsl
Median
Duration
for Doers
Cminsl
Maximum
Duration for
Doers
Cminsl
Detailed Location with Highest
Avg. Time
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,
Shopping Places
24
35
69
50
475
Shopping mall
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 Categories
Grouped by Age and Gender
Mean Duration (minutes/day)
Boys
Girls
Location Category
All
All
0-2 yrs
3-5 yrs
(/)
><
CO
CD
9-11 yrs
Boys
0-2 yrs
3-5 yrs
(/)
><
CO
CD
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,
Shopping Places
21
25
22
15
21
23
35
27
26
28
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
(Unweighted)
172
151
145
156
624
141
151
124
160
576
a The column totals ma\
Source: Wiley et al., 1E
not sum to 1,440 due to rounding error.
91.
-------
Table 15-16. Mean Time Children Spent in Six Location Catego
ries Grouped by Season and Reg
on
Mean Duration (minutes/day)
Season
Region of California
Location Category
Winter
(Jan-Mar)
Spring
(Apr-June)
Summer
(July-Sept)
Fall
(Oct-Dec)
All
Seasons
So.
Coast
Bay
Area
Rest of
State
All
Regions
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
House
69
75
108
69
80
73
86
86
80
Stores, Restaurants,
Shopping Places
22
21
30
24
24
26
23
23
24
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
Coded
<1
<1
<1
<1
<1
<1
<1
<1
<1
All Locations®
1,439
1,439
1,440
1,439
1,439
1,439
1,440
1,440
1,439
Sample Sizes
(Unweighted N's)
318
204
407
271
1,200
224
263
713
1,200
a The column totals ma\
Source: Wiley et al., 1i
not sum to 1,440 due to rounding error.
)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
Children
0-2 yrs
3-5 yrs
6-8 yrs
9-11 yrs
All
Boys
0-2 yrs
3-5 yrs 6-8 yrs
9-11 yrs
All
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
a 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
frequency®
10 min/event 15 min/event
1 event/day 1 event/day
350 days/yr 350 days/yr
0.5 hr/event 1.0 hr/event
1 event/day 1 event/day
5 days/yr 150 days/yr
40 events/yr
350 events/yr
Exposure
duration
9 years 30 years
9 years 30 years
9 years
30 years
a Bathing event time is presented to be representative of baths as well as showers.
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
2
3
4
5
8
10
11:1-1
802
30
1
1
1
1
4
436
21
1
*
.
.
1
366
9
*
1
1
1
3
*
17
.
*
*
.
.
.
9
1
*
*
*
*
*
26
1
*
*
*
*
*
65
6
*
*
*
*
*
636
21
1
1
1
1
3
49
1
1
562
17
*
1
.
.
4
140
7
1
*
1
*
*
14
1
*
*
*
23
2
*
*
*
*
*
56
2
*
*
*
1
*
7
1
*
*
*
*
711
24
1
1
1
.
4
81
5
1
4
*
*
*
*
6
1
*
*
*
*
*
99
8
.
*
.
.
.
454
17
*
*
*
1
2
65
*
1
*
177
5
1
*
1
*
2
7
*
*
121
9
.
*
.
.
.
54
2
*
*
*
*
1
243
5
*
1
1
*
1
176
4
*
1
133
7
1
*
*
*
1
75
3
*
*
*
1
196
7
.
*
.
.
.
131
3
*
*
*
*
*
334
14
1
*
*
*
3
141
6
1
1
1
1
563
17
1
1
1
1
4
239
13
198
9
.
*
.
.
1
205
7
*
*
*
1
254
10
1
*
*
*
2
145
4
1
1
1
730
25
1
1
1
1
4
67
5
5
*
*
*
*
*
786
29
1
i
1
1
4
12
1
4
*
*
*
*
*
758
27
1
i
1
1
4
39
3
5
*
*
*
*
*
DK
Overall
Gender
Male
Female
Refused
Age (years)
1-4
5-11
12-17
18-64
>64
Race
White
Black
Asian
Some Others
Hispanic
Refused
Hispanic
No
Yes
DK
Refused
Employment
-ull Time
3art Time
slot Employed
Refused
Education
< High School
High School Graduate
< College
College Graduate
Post Graduate
Census Region
Northeast
Midwest
South
West
Day of Week
Weekday
Weekend
Season
Winter
Spring
Summer
Fall
Asthma
No
Yes
DK
Angina
No
Yes
DK
Bronchitis/Emphysema
Yes
DK
3594
1720
1872
2
64
41
140
270
2650
429
2911
349
64
65
162
43
3269
277
17
31
439
1838
328
967
22
515
297
1042
772
576
392
828
756
1246
764
2481
1113
941
889
1003
761
3312
261
21
3481
91
22
3419
154
21
2747
1259
1486
2
46
30
112
199
1983
377
2323
199
49
40
103
33
2521
190
13
23
330
1361
261
780
15
382
240
789
589
434
313
622
621
893
611
1889
858
732
674
735
606
2543
189
15
2653
77
17
2620
112
15
Note: * Signifies missing data, Dk=
Source: Tsanq and Klepeis.1996
don't know; N = sample size.
-------
Table 15-20. Times (minutes) Spent Taking Showers by the Number of Respondents
Minutes/Shower
Overall
Gender
Male
Female
Refused
Age
1-4
5-11
12-17
18-64
>64
Race
White
Black
Asian
Some Others
Hispanic
Refused
Hispanic
Nok
Yes
DK
Refused
Employment
- ull Time
3art Time
slot Employed
Refused
Education
< High School
High School Graduate
< College
College Graduate
Post Graduate
Census Region
Northeast
Midwest
South
West
Day of Week
Weekday
Weekend
Season
Wnter
Spring
Summer
Fall
Asthma
No
Yes
DK
Angina
No
Yes
DK
Bronchitis/Emphysema
Yes
DK
-*
0-10
10-20
20-30
30-40
40-50
50-60
60-6
3594
47
1640
1348
397
72
52
51
17
1720
13
788
625
213
35
25
14
7
1872
34
850
693
184
37
27
37
-iO
2
2
64
6
27
23
3
1
.
2
2
41
1
13
14
10
1
*
2
*
140
1
60
52
18
3
2
4
*
270
2
94
104
40
13
9
7
1
2650
16
1238
977
288
50
37
33
11
429
21
208
148
38
4
4
3
3
2911
38
1406
1070
292
39
31
26
9
349
5
115
120
58
20
11
16
4
64
*
25
25
10
1
2
*
1
65
*
18
29
6
3
4
4
1
162
1
57
60
25
8
4
5
2
43
3
19
14
6
1
3269
43
1526
1188
352
61
42
44
13
277
1
98
109
40
10
8
7
4
17
*
5
9
1
*
2
*
*
31
3
11
12
4
1
439
4
163
165
66
17
10
12
2
1838
10
875
682
191
32
20
20
8
328
4
160
112
39
4
5
3
1
967
27
431
355
97
1,9
16
16
6
22
2
11
4
4
1
515
10
190
186
79
21
13
14
2
297
8
93
125
51
6
7
6
1
1042
12
451
409
108
23
17
16
6
772
12
377
271
79
14
6
7
6
576
2
297
211
50
5
5
5
1
392
3
232
116
30
3
4
3
1
828
7
374
326
79
15
11
12
4
756
11
385
253
70
16
9
9
3
1246
26
490
461
179
35
26
23
6
764
3
391
278
69
6
6
7
4
2481
34
1134
908
279
46
38
32
10
1113
13
506
410
118
26
14
19
7
941
2
421
358
95
18
5
6
6
889
4
410
314
93
21
4
8
5
1003
1
435
366
128
29
7
2
5
761
0
374
280
81
4
6
5
1
3312
38
1526
1222
362
65
44
41
14
261
4
108
89
33
7
8
10
2
21
5
6
7
2
*
*
*
1
3481
91
36
1591
1276
389
70
51
51
17
22
7
38
36
8
1
1
*
*
4
11
6
1
3419
40
1566
1258
375
67
47
50
16
154
3
66
54
19
5
5
1
1
21
4
8
6
3
NOTE: * - Missing data; DK = don't know; N = sample size; Refused = Refused to answer. A value of 61 for number of minutes
signifies that more than 60 minutes were spent.
Source: Tsang and Klepeis, 1996.
-------
Table 15-21. Number of Minutes Spent Taking a Shower (minutes/shower)
Total ¦
N
Percentiles
Category
Population Group
1
2
5
10
25
50
75
91
95
98
99
100
Overall
3547
3
4
5
5
10
15
20
30
35
50
60
61
Gender
Male
1707
3
4
5
5
10
15
20
30
30
45
60
61
Gender
Female
1838
3
4
5
5
10
15
20
30
40
60
60
61
Age (years)
1-4
40
5
5
5
5
5
10
17.5
30
50
60
60
60
Age (years)
5-11
139
3
4
5
5
10
15
20
30
40
60
60
60
Age (years)
12-17
268
5
5
5
7
10
15
25
35
45
60
60
61
Age (years)
18-64
2634
3
3
5
5
10
15
20
30
30
45
60
61
Age (years)
>64
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
Wnter
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
percentage of doers below or equal to a given number of minutes.
Source: Tsang and Klepeis, 1996.
-------
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
61
241
2561
509
138
24
28
27
5
22
113
1316
207
46
5
4
6
1
39
128
1243
302
92
19
24
2.1
4
2
*
6
9
37
7
3
.
1
1
.
5
31
3
1
*
1
*
3
9
110
14
3
*
*
1
*
1
17
206
29
10
3
2
1
1
31
171
1897
388
99
19
18
23
4
20
30
280
68
22
2
6
1
39
189
2074
430
110
20
23
21
5
8
23
254
42
17
*
3
2
*
*
7
45
9
2
*
*
1
*
3
7
41
6
3
3
1
1
*
6
11
118
19
4
1
1
2
*
5
4
29
3
2
48
216
2328
470
130
23
26
23
5
8
19
200
35
8
1
2
4
*
1
2
11
3
*
4
4
22
1
4
28
336
48
14
3
4
2
?*
20
109
1332
267
71
12
11
16
*
5
21
223
55
13
4
4
3
*
29
81
655
138
39
5
9
6
5
3
2
15
1
1
11
38
390
51
15
3
4
2
14
18
193
48
16
*
6
1
17
68
733
160
37
6
7
13
11
56
536
118
33
7
4
5
2
3
28
426
86
19
8
3
3
*
5
33
283
46
18
4
3
6
61
603
16
20
6
8
8
.
19
39
536
18
29
5
3
7
*
26
74
885
71
58
10
15
4
3
10
67
537
04
31
3
2
8
2
43
165
1784
342
88
20
16
19
4
18
76
777
167
50
4
12
8
1
11
50
678
138
36
13
9
4
2
13
56
636
125
37
4
8
9
1
25
92
691
138
39
5
5
7
1
12
43
556
108
26
2
6
7
1
52
225
2374
465
123
19
24
26
4
2
14
178
42
1J5
5
3
1
1
7
2
9
2
1
52
233
2495
486
132
24
27
27
5
3
5
55
22
5
1
6
3
11
1
1
53
226
2446
482
131
23
27
26
5
2
12
104
26
7
1
1
1
*
6
3
11
1
*
Overall
Gender
Male
Female
Refused
Age (years)
1-4
5-11
12-17
18-64
>64
Race
White
Black
Asian
Some Others
Hispanic
Refused
Hispanic
No
Yes
DK
Refused
Employment
-ull Time
3art Time
slot Employed
Refused
Education
< High School
High School Graduate
< College
College Graduate
Post Graduate
Census Region
Northeast
Midwest
South
West
Day of Week
Weekday
Weekend
Season
Winter
Spring
Summer
Fall
Asthma
No
Yes
DK
Angina
No
Yes
DK
Bronchitis/Emphysema
Yes
DK
3594
1720
1872
2
64
41
140
270
2650
429
2911
349
64
65
162
43
3269
277
17
31
439
1838
328
967
22
515
297
1042
772
576
392
828
756
1246
764
2481
1113
941
889
1003
761
3312
261
21
3481
91
22
3419
154
21
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 61 for number of minutes signifies that more than 60 minutes
were spent.
Source: Tsang 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
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
Wnter
930
0
0
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
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 sample size. Percentiles are the percentage of doers below or equal to a given number of minutes. Avalueof 61 for
number of minutes signifies that more than 60 minutes were spent.
Source: Tsanq and Klepeis,1996
-------
Table 15-24. Number of Baths Given or Taken in One Day by Number of Respondents
Number of Baths/Day
Total N
10
11
15
DK
Overall
Gender
Male
Female
Age (years)
18-64
>64
Race
White
Black
Asian
Some Others
Hispanic
Refused
Hispanic
No
Yes
DK
Refused
Employment
-ull Time
3art Time
slot Employed
Refused
Education
< High School
High School Graduate
< College
College Graduate
Post Graduate
Census Region
Northeast
Midwest
South
West
Day of Week
Weekday
Weekend
Season
Wnter
Spring
Summer
Fall
Asthma
No
Yes
DK
Angina
No
Yes
DK
Bronchitis/Emphysema
Yes
DK
649
159
490
9
491
149
487
106
12
12
26
6
600
40
6
3
1
283
76
287
2
4
96
235
163
102
49
137
151
255
106
415
234
78
60
74
37
596
52
1
620
26
3
610
36
3
459
117
342
322
129
364
68
5
7
10
5
430
21
5
3
1
183
56
217
2
4
66
167
112
68
42
100
116
164
79
299
160
24
26
12
97
424
34
1
435
22
2
429
27
3
144
33
111
1
127
16
92
29
5
4
13
1
127
16
1
76
17
51
19
54
38
28
5
25
29
70
20
89
55
37
27
49
31
129
15
141
2
1
137
7
20
5
15
20
13
5
1
1
19
1
12
1
7
3
4
9
4
10
10
10
4
4
2
19
1
19
1
20
NOTE: * Signifies missing data; Dk= respondents answered don't know; N = sample size; Refused = respondents refused to answer.
Source: Tsana and Klepeis.1996
-------
Table 15-25. Total Time Spent Taking or Giving 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
Gender
Male
Female
Age (years)
18-64
>64
Race
White
Black
Asian
Some Others
Hispanic
Refused
Hispanic
No
Yes
DK
Refused
Employment
-ull Time
3art Time
slot Employed
Refused
Education
< High School
High School Graduate
< College
College Graduate
Post Graduate
Census Region
Northeast
Midwest
South
West
Day of Week
Weekday
Weekend
Season
Winter
Spring
Summer
Fall
Asthma
No
Yes
DK
Angina
No
Yes
DK
Bronchitis/Emphysema
Yes
DK
649
159
490
9
491
149
487
106
12
12
26
6
600
40
6
3
1
283
76
287
2
4
14
2
6
10
11
4
16
1
4
1
12
1
153
48
105
2
105
46
124
16
2
2
8
1
136
15
1
1
58
26
69
237
59
178
4
174
59
185
35
6
3
6
2
224
10
2
1
107
26
104
128
23
105
1
111
16
97
19
3
5
3
1
120
6
2
1
64
15
48
27
8
19
22
5
16
26
1
12
5
10
29
4
25
24
5
19
9
27
1
1
12
1
16
36
7
29
31
5
24
9
33
3
19
2
15
21
6
15
11
6
1
3
13
1
4
1
*
2
1
*
*
*
*
96
7
15
35
16
3
6
7
7
235
6
57
85
51
13
5
11
7
163
4
45
53
32
4
11
8
6
102
18
44
20
5
5
9
1
49
*
18
18
8
2
2
1
*
137
5
43
36
31
6
7
6
3
151
2
42
67
26
3
3
5
3
255
9
42
87
55
16
14
21
11
106
2
26
47
16
2
5
4
4
415
12
90
161
84
11
23
23
11
234
6
63
76
44
16
6
13
10
178
5
44
63
33
9
11
9
4
160
6
39
60
27
9
7
6
6
174
3
43
62
34
7
4
14
7
137
4
27
52
34
2
7
7
4
596
16
144
218
114
26
28
33
17
52
1
9
19
14
1
1
3
4
1
1
620
14
147
226
124
25
28
35
21
26
3
6
10
3
2
1
1
*
3
1
1
1
*
610
15
150
218
119
26
26
35
21
36
2
3
17
9
1
3
1
*
3
1
2
*
NOTE: * Signifies missing data. Dk= respondents answered don't know. Refused = respondents refused to answer. N = doer
sample size in a 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 Klepeis.1996
-------
Table 15-26. Number of Minutes Spent Giving and Taking the Bath(s) (minutes/bath)
Category
Population Group
Percentiles
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
Wnter
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 signifies that more than 60 minutes were spent.
Source: Tsana and Klepeis.1996
-------
Table 15-27. Time Spent 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
Gpr
Female
Age (years)
6sian
Some Others
Hispanic
Refused
Hispanic
es
Refused
Employment
jme
SEbfoyed
Refused
Education
Hi
iooT Graduate
College Graduate
Post Graduate
CBSeaR|gi0"
est
Day of Week
Weel
-------
Table 15-28. Number of Minutes Spent in the Bathroom Immediately After the Bath(s) (minutes/bath)
Category
Population Group
Percentiles
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
0
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
Wnter
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/Emphysema
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 signifies that more than 60 minutes were spent.
Source: Tsana and Klepeis.1996
-------
Table 15-29. Total Time Spent Altogether in the Shower or Bathtub by the Number of Respondents
Minutes/Bath
Total
N
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
Overall
Gender
Male
-emale
Refused
Age (years)
1-4
w
6sian
Some Others
Hispanic
Refused
Hispanic
es
Refused
Employment
jme
SEbfoyed
Refused
Education
Hi
iooT Graduate
College Graduate
Post Graduate
CBSeaR|gi0"
est
Day of Week
Weel
-------
Table 15-30. Total Number of Minutes Spent Altogether in the Shower or Bathtub (minutes/bath)
Category
Population Group
Percentiles
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
Wnter
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 Klepeis. 1996.
-------
Table 15-31. Time Spent in the Bathroom Immediately Following 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
Overall
Gender
Male
-emale
Refused
Age (years)
1-4
> 64
Race
BlacK
6sian
Some Others
Hispanic
Refused
HCniC
Refused
Employment
Full "Ome
Mjfoyed
Refused
Education
Hij
College^Graduate
Post Graduate
C?n0SrtUh!aRs?giOn
"%eSt
est
Day of Week
Weel
-------
Table 15-32. Number of Minutes Spent in the Bathroom Immediately 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
4
6
15
30
30
60
60
60
Race
Asian
74
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
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
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
Wnter
1090
0
0
0
1
5
7
15
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
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
4.5
LO
LO
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: Tsana and Klepeis. 1996.
-------
Table 15-33. Range of Number of Times Washing the Hands at Specified Daily Frequencies by the Number of Respondents
Number of Times/Day
Total N
0-0
1-2
3-5
6-9
10-19
20-29
30+
DK
311
1692
1106
892
223
178
189
i128
1
m
1
$
59
1§4
f9
if
1
25
15
11
4
5
15
Overall
Gpr
Female
Refused
Age (years)
fk
>64
R9.ce
lite
vislan
Some Others
Hispanic
Refused
*nic
Refused
Employment
;ull Time
3art Time
feal0yed
Education
fiMMraduate
< College
College Graduate
Post Graduate
Census Region
Northeast
%eSt
est
Day of Week
Weel
-------
Table 15-34. Number of Minutes Spent (at home) Working
or Being Near Food While Fried, Grilled, or Barbequed (minutes/day)
Category
Population Group
Percentiles
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
90
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
Wnter
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/Emphysema
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,
the percentage of doers below or equal to a given number of minutes.
Source: Tsana and Kleoeis. 1996.
N = doer sample size.
Percentiles are
-------
Table 15-35. Number of Minutes Spent (at home) Working or Being Near Open Flames Including Barbeque Flames (minutes/day)
Cateqory
Population Group
Percentiles
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
121
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
Census 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
Wnter
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: Tsano and Klepeis. 1996.
-------
Table 15-36. Number of Minutes Spent Working or Being Near Excessive Dust in the Air (minutes/day)
Category
Population Group
Percentiles
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
Education
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
Wnter
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/Emphysema
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
the percentage of doers below or equal to a given number of minutes.
Source: Tsana and Kleoeis. 1996.
N =
doer sample size.
Percentiles are
-------
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
Gender
Male
Female
Age(years)
1-4
5-11
12-17
18-64
>64
Race
White
Black
Asian
Some Others
Hispanic
Refused
Hispanic
No
Yes
DK
Refused
Employment
-ull Time
3art Time
slot Employed
Refused
Education
< High School
High School Graduate
< College
College Graduate
Post Graduate
Census Region
Northeast
Midwest
South
West
Day of Week
Weekday
Weekend
Season
Winter
Spring
Summer
Fall
Asthma
No
Yes
DK
Angina
No
Yes
DK
Bronchitis/Emphysema
Yes
DK
2009
939
1070
20
111
150
145
1287
296
1763
110
46
24
55
11
1879
111
12
7
398
919
149
536
7
427
84
464
440
326
268
289
541
702
477
1383
626
567
518
525
399
1861
146
2
1959
48
2
1922
84
3
1321
588
733
13
68
93
86
840
221
1164
70
34
19
26
1239
68
9
5
241
610
93
372
5
262
59
336
304
201
159
213
360
430
318
903
418
396
336
313
276
1228
92
1
1288
33
1266
54
1
559
290
269
2
39
49
42
367
60
486
31
10
5
24
3
519
35
3
2
127
253
48
129
2
134
17
107
107
106
64
142
221
132
386
173
36
41
78
04
514
44
1
545
12
2
532
25
2
78
40
38
1
2
6
12
50
7
69
4
2
74
4
20
35
4
19
21
2
13
20
10
12
29
27
14
63
15
20
25
18
15
70
76
2
74
4
17
7
10
1
2
1
12
1
17
17
11
6
5
5
6
1
17
17
17
34
14
20
27
5
30
4
7
12
2
13
16
20
14
10
11
10
3
32
2
33
1
33
1
Note: Signifies missing data; "DK" = respondent answered don't know; Refused ¦
sample size.
Source: Tsana and Klepeis. 1996
the respondent refused to answer; N = doer
-------
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
Vlale
Female
939
1070
860
970
41
58
15
11
2
23
29
Age (years)
1-4
5-11
12-17
18-64
>64
20
111
150
145
1287
296
14
99
141
127
1184
265
1
8
6
9
57
18
2
4
18
2
1
1
5
2
3
4
27
11
Race
White
Black
Asian
Some Others
Hispanic
Refused
1763
110
46
24
55
11
1616
95
41
21
46
11
82
6
4
2
5
22
2
2
1
1
42
6
1
1
2
Hispanic
No
Yes
DK
Refused
1879
111
12
7
1714
97
12
7
92
7
23
3
2
48
4
Employment
-ull Time
3art Time
slot Employed
Refused
398
919
149
536
7
360
840
137
488
5
22
46
6
24
1
5
13
2
5
1
1
1
10
19
4
1,9
Education
< High School
High School Graduate
< College
College Graduate
Post Graduate
427
84
464
440
326
268
387
74
429
399
299
242
23
2
24
24
12
14
6
1
2
8
6
3
1
1
10
7
9
8
9
9
Census Region
Northeast
Vlidwest
South
West
289
541
702
477
270
500
628
432
10
22
42
25
5
4
8
9
1
1
3
14
24
11
Day of Week
Weekday
Weekend
1383
626
1269
561
66
33
21
5
2
27
25
Season
Wnter
Spring
Summer
Fall
567
518
525
399
509
470
476
375
32
29
23
15
9
3
11
3
1
1
16
16
15
5
Asthma
No
Yes
DK
1861
146
2
1696
132
2
92
7
23
3
1
1
49
3
Angina
No
Yes
DK
1959
48
2
1785
43
2
96
3
26
2
50
2
Bronchitis/Emphysema
Yes
DK
1922
84
3
1747
80
3
96
3
26
2
51
1
Note: Signifies missing data; "DK" = respondents answered don't know; N = doer sample size; Refused = the respondent refused
to answer.
Source: Tsana and Klepeis. 1996
-------
Table 15-39. Number of Minutes Spent at a Gas Station or Auto Repair Shop (minutes/day)
Category
Population Group
Percentiles
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
Wnter
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 Klepeis. 1996.
-------
Table 15-40. Number of Minutes Spent at Home While the Windows Were Left Open (minutes/day)
Category
Population Group
Percentiles
N
1
2
5
10
25
50
75
90
95
98
99
100
Overall
1960
2
10
30
180
360
840
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
Employment
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
10
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" for number 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
given number of minutes.
Source: Tsana and Kleoeis. 1996.
-------
Table 15-41. Number of Minutes the Outside Door Was Left Open 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/emphysema
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: Tsana and Klepeis. 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
Gender
Male
Female
511
676
80
112
96
152
100
129
118
149
93
103
24
31
Age (years)
1-4
5-11
12-17
18-64
>64
19
68
109
79
730
182
6
13
15
11
112
35
3
14
16
17
145
53
2
8
18
17
156
28
3
17
31
13
171
32
1
13
23
17
123
19
4
3
6
4
23
15
Race
White
Black
Asian
Some Others
Hispanic
Refused
979
103
23
22
46
14
155
22
1
3
8
3
193
28
9
4
11
3
188
21
4
2
10
4
233
12
6
7
8
1
168
14
2
4
8
42
6
1
2
1
3
Hispanic
NS
Yes
DK
Refused
1086
83
7
11
179
U
2
227
17
2
2
208
16
1
4
244
20
3
180
15
1
48
4
3
Er
riployment
-ull Time
3art Time
slot Employed
Refused
255
458
95
369
10
40
79
14
58
1
46
98
20
81
3
43
95
19
69
3
60
104
22
80
1
53
72
18
52
1
13
10
2
29
1
Education
< High School
High School Graduate
< College
College Graduate
Post Graduate
267
98
318
228
150
126
42
21
48
44
21
16
48
17
66
52
37
28
46
15
65
37
39
27
63
18
71
49
31
35
54
20
54
34
19
15
14
7
14
12
3
5
Census Region
Northeast
Midwest
South
West
228
225
365
369
37
44
59
52
38
54
81
75
49
39
69
72
53
50
71
93
38
33
66
59
13
5
19
18
Day of Week
Weekday
Weekend
746
441
116
76
167
81
156
73
167
100
106
90
34
21
Season
Wnter
Spring
Summer
Fall
185
417
387
198
19
73
72
28
51
94
68
35
39
66
81
43
42
90
80
55
27
73
66
30
7
21
20
7
Asthma
No
Yes
DK
1087
99
1
175
16
1
228
20
211
1,8
245
22
179
17
49
6
Angina
No
Yes
DK
1147
39
1
183
8
1
241
7
221
8
259
8
192
4
51
4
Bronchitis/emphysema
Yes
DK
1121
64
2
179
12
1
230
18
216
12
1
258
9
186
-iO
52
3
Note: * Signifies missing data: "DK"
Source: Tsana and KleTseis, 1996
= respondent answered don't know;
N = sample size; Refused
= respondent refused to answer.
-------
Table 15-43. Number of Minutes Spent Running, Walking, or
Standing Alongside
a Road with Heavy Traffic (minutes/day)
Category
Population Group
Percentiles
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 Graduate
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
Wnter
104
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/Emphysema
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
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 15-44. Number of Minutes Spent in a Car, Van, Truck, or Bus in Heavy Traffic (minutes/day)
Category
Population Group
Percentiles
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
Wnter
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 =
are the percentage of doers below or equal to a given number of minutes.
Source: Tsana and Kleoeis.1996
doer sample size.
Percentiles
-------
Table 15-45. Number of Minutes Spent in a Parking Garage or Indoor Parking 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
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
5
5
5
5
10
30
60
121
121
121
Employment
Not Employed
58
0
1
1
2
4
10
20
40
120
121
121
121
Education
< High School
13
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
5
6
10
30
90
121
121
121
Census Region
Midwest
59
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
Wnter
67
0
1
1
2
3
5
10
20
30
120
121
121
Season
Spring
78
0
1
1
2
3
5.5
15
60
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
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
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
120
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 Klepeis.1996
-------
Table 15-46. Number of Minutes Spent Walking Outside to a Car in the Driveway or Outside Parking 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
0
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
60
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
Wnter
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
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 15-47. Number of Minutes Spent Running or Walking Outside Other Than to the Car (minutes/day)
Category
Population Group
Percentiles
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
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
1
3
5
15
30
90
121
121
121
121
121
Education
High School Graduate
287
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
Wnter
312
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
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: Tsana and Klepeis.1996
-------
Table 15-48.
Number of Hours Spent Working for Pay (hours/week)
Category
Population Group
Percentiles
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
Some 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
Wnter
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/Emphysema
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
Percentiles are the percentage of doers below or equal to a given number of hours.
Source: Tsana and KleDeis. 1996.
= doer sample size.
-------
Table 15-49. Number of Hours Spent Working for Pay Between 6PM and 6AM (hours/week)
Category
Population Group
Percentiles
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
0
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
Wnter
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,
percentage of doers below or equal to a given number of hours.
Source: Tsana and Kleoeis. 1996.
N = doer sample size
Percentiles are the
-------
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
0
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
Wnter
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
percentage of doers below or equal to a given number of hours.
Source: Tsana and Klepeis.1996
-------
Table 15-51. Number of Times Floors Were Swept or Vacuumed at Specified Frequencies by the Number of Respondents
Total N
Number of Times
Almost Every Day 3-5/week
-5/week
1 -2/week
1 -2/month
< Often
Never
DK
1108
2178
373
48
10
25
520
976
201
27
5
19
588
1201
172
21
5
6
0
1
0
0
0
0
11
41
12
3
0
1
74
88
4
0
0
1
107
120
6
0
0
0
83
144
15
2
0
0
723
1420
252
34
6
13
110
365
84
9
4
10
879
1868
324
36
8
18
115
150
19
5
2
5
15
39
8
3
0
1
29
32
8
1
0
0
61
55
7
2
0
0
9
34
7
1
0
1
988
2035
345
43
9
25
107
110
21
3
0
0
3
11
2
1
1
0
10
22
5
1
0
0
267
342
24
2
0
1
486
1018
184
27
2
9
82
177
34
1
0
3
263
626
127
18
8
11
10
15
4
0
0
1
285
384
31
4
0
3
91
162
20
6
2
8
302
591
69
12
3
7
223
438
93
8
2
1
132
346
93
9
3
3
75
257
67
9
0
3
230
484
83
8
2
5
249
527
86
0
2
6
403
707
93
1
2
9
226
460
111
9
4
5
765
1458
248
33
5
16
343
720
125
15
5
9
309
557
105
15
2
8
286
560
96
12
3
7
312
596
94
13
1
8
201
465
78
8
4
2
1013
2030
351
39
10
23
88
133
17
7
0
1
7
15
5
2
0
1
1080
2098
352
44
10
24
23
63
16
2
0
0
5
17
5
2
0
1
1064
2063
349
44
9
24
39
99
17
2
1
0
5
16
7
2
0
1
Overall
Gender
Male
Female
Refused
Age (years)
1-4
5-11
12-17
18-64
>64
Race
White
Black
Asian
Some Others
Hispanic
Refused
Hispanic
No
Yes
DK
Refused
Employment
-ull Time
3art Time
slot Employed
Refused
Education
< High School
High School Graduate
< College
College Graduate
Post Graduate
Census Region
Northeast
Midwest
South
West
Day of Week
Weekday
Weekend
Season
Wnter
Spring
Summer
Fall
Asthma
No
Yes
DK
Angina
No
Yes
DK
Bronchitis/emphysema
Yes
DK
4663
2163
2498
2
84
263
348
326
2972
670
3774
463
77
96
193
60
4244
347
26
46
926
2017
379
1309
32
1021
399
1253
895
650
445
048
036
601
978
3156
1507
1264
1181
1275
943
4287
341
35
4500
125
38
4424
203
36
921
415
505
1
16
96
115
82
524
641
167
11
26
68
799
106
290
291
82
256
2
314
110
269
130
64
34
236
156
376
153
631
290
268
217
251
185
821
95
5
892
21
871
45
5
Note: * Signifies missing data; DK = respondent answered don't know; N = sample size; Refused :
Source: Tsanq and Klepeis. 1996
respondent refused to answer.
-------
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
Age (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
Hispanic
385
300
52
15
9
2
2
0
1
1
0
0
0
1
2
Refused
126
122
2
0
0
0
1
1
0
0
0
0
0
0
0
Hispanic
No
8534
7421
460
248
170
80
57
29
15
24
2
1
5
14
8
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
Employment
*
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
Education
*
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
High School Graduate
2612
2447
76
39
26
9
7
1
2
0
1
0
0
2
2
< College
1801
1681
55
25
18
10
6
0
1
3
0
0
0
2
0
College Graduate
1247
1155
28
19
17
10
5
3
1
7
0
0
0
1
1
Post Graduate
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
Weekday
6316
5487
366
160
125
57
51
18
13
15
2
1
4
11
6
Weekend
3070
2625
184
118
64
28
12
13
4
11
0
0
1
5
5
Season
Wnter
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
0
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 data: DK = respondents answered don't know; N=
sample size; Refused = respondent refused to answer.
Source: Tsanq and Kleceis, 1996
-------
Table 15-53. Number of Loads of Laundry Washed in a Washing Machine at Home by the Number of Respondents
i otai n
1
2
3
4
5
6
7
8
9
10
>10
DK
1762
582
604
303
123
55
27
11
12
1
5
1
38
678
219
241
120
41
17
8
.
.
1
1
.
30
1083
363
363
183
82
38
19
10
12
*
4
1
8
1
1
*
30
9
14
2
3
1
.
.
.
*
.
.
1
109
29
36
24
12
5
2
*
*
*
1
*
*
141
38
55
28
8
6
2
1
*
1
1
*
1
127
39
52
22
10
1
1
*
1
*
*
*
1
1161
385
376
209
80
35
22
9
V
*
3
1
30
194
82
71
18
10
7
1
5
1511
513
519
254
101
48
23
11
12
1
3
.
26
112
27
41
23
11
4
1
*
*
*
1
*
4
22
7
4
3
5
*
*
*
*
3
31
8
12
5
1
1
1
*
*
*
*
*
3
68
18
24
15
5
2
2
*
*
*
1
*
1
18
9
4
3
*
*
*
1
1
1615
536
556
271
115
50
24
11
12
1
4
.
35
126
38
42
26
8
5
3
*
*
*
1
*
3
6
*
2
4
*
*
*
*
*
*
*
*
*
15
8
4
2
*
*
*
*
*
*
*
1
*
369
102
143
71
29
12
5
1
1
1
2
.
2
734
259
244
128
42
20
10
5
4
*
2
*
20
160
58
53
23
10
8
3
*
1
*
*
*
4
482
158
158
79
41
15
8
5
6
*
1
1
10
17
5
6
2
1
1
*
2
413
118
160
77
32
12
6
1
1
1
2
.
3
133
44
44
22
10
4
3
2
*
*
*
*
4
508
175
166
85
35
18
8
3
4
*
*
*
14
321
105
101
61
25
9
3
2
5
*
2
1
7
212
83
68
32
11
8
4
*
1
*
*
*
5
175
57
65
26
10
4
3
3
1
*
1
*
5
367
111
146
57
23
13
7
2
1
*
.
.
7
406
125
123
76
42
14
5
3
6
1
*
1
10
628
205
228
110
39
17
6
6
4
*
3
*
10
361
141
107
60
19
11
9
*
1
*
2
*
11
1172
418
409
194
62
29
17
7
7
1
1
1
26
590
164
195
109
61
26
10
4
5
4
12
458
154
159
73
31
14
6
3
4
1
3
1
9
465
154
159
87
28
10
10
3
2
*
1
*
11
482
158
166
85
38
11
8
4
3
*
1
*
8
357
116
120
58
26
20
3
1
3
10
1615
548
545
274
105
50
27
11
12
1
5
1
36
140
31
56
28
18
5
*
*
*
*
*
*
2
7
3
3
1
*
*
*
*
*
*
1710
564
592
294
113
54
26
11
12
1
5
1
37
40
14
9
7
8
1
1
12
4
3
2
2
*
*
*
*
*
*
*
1
1658
544
572
285
112
53
26
10
12
1
5
1
37
96
36
28
16
11
2
1
1
*
*
*
*
1
8
2
4
2
*
*
*
*
Overall
Gender
Male
Female
Refused
Age (years)
1-4
5-11
12-17
18-64
>64
Race
White
Black
Asian
Some Others
Hispanic
Refused
Hispanic
No
Yes
DK
Refused
Employment
Full Time
3art Time
slot Employed
Refused
Education
< High School
High School Graduate
< College
College Graduate
Post Graduate
Census Region
Northeasr
Midwest
South
West
Day of Week
Weekday
Weekend
Season
Wnter
Spring
Summer
Fall
Asthma
No
Yes
DK
Angina
No
Yes
DK
Bronchitis/Emphysema
Yes
DK
Note: * Signifies missing data, "DK":
Source: TsanoAnd Klepeis. 1996
respondent answered don't know; N= sample size; Refused = respondent refused to answer.
-------
Table 15-54.
Number of Times Using a
Dishwasher at Specified Freq
uencies by the Number of Respondents
Number of Times/Week
Tuldl N
*
Almost Every Day
3-5/Week 1-
2/Week
<1-2/Week
DK
Overall
2635
1
557
678
529
824
46
Gender
Male
Female
Refused
1235
1399
1
1
259
298
282
396
247
282
417
406
1
30
16
Age (years)
1-4
5-11
12-17
18-64
>64
35
145
211
206
1718
320
1
4
9
14
27
438
65
13
4
8
33
512
108
11
3
15
31
397
72
6
118
157
113
360
70
1
11
17
2
11
4
Race
White
Black
Asian
Some Others
Hispanic
Refused
2267
163
54
45
84
22
1
504
19
7
9
13
5
603
32
8
8
15
12
487
19
7
1
12
3
637
90
31
24
40
2
35
3
1
3
4
Hispanic
No
Yes
DK
Refused
2444
164
11
16
1
524
27
2
4
635
32
2
9
504
21
2
2
739
79
5
1
41
5
En
iployment
-ull Time
3art Time
slot Employed
Refused
552
1191
204
678
10
1
49
276
48
181
3
45
359
70
200
4
46
298
46
136
3
382
249
38
155
30
9
2
5
Education
< High School
High School Graduate
< College
College Graduate
Post Graduate
593
124
582
560
446
330
1
55
29
153
144
105
71
51
27
173
181
134
112
55
26
114
117
126
91
400
41
132
117
80
54
32
10
1
1
2
Census Region
Northeasr
Midwest
South
West
538
514
953
630
1
133
116
200
108
144
130
251
153
95
110
169
155
159
152
312
201
7
6
21
12
Day of Week
Weekday
Weekend
1768
867
1
378
179
466
212
341
188
549
275
33
13
Season
Winter
Spring
Summer
Fall
711
664
721
539
1
144
122
157
134
175
181
185
137
149
132
134
114
223
214
239
148
20
14
6
6
Asthma
No
Yes
DK
2439
189
7
1
521
35
1
622
54
2
492
35
2
765
58
1
38
7
1
Angina
No
Yes
DK
2570
60
5
1
538
19
664
11
3
512
16
1
809
14
1
46
Bronchitis/Emphysema
Yes
DK
2533
93
9
1
540
16
1
646
27
5
504
23
2
796
27
1
46
Note: * Signifies missing data, "DK" = respondent answered don't know; N= sample size; Refused
Source: Tsana And Kleoeis. 1996
= respondent refused to answer.
-------
Table 15-55. Number of Times Washing Dishes by Hand at Specified Frequencies
by the Number of Respondents
Total N
Number of Times/Week
*
Almost Every
Day
3-5/Week 1
-2/Week <1-2/Week
DK
Overall
3626
1
2600
490
326
197
12
Gender
Male
Female
Refused
1554
2071
1
1
982
16,18
264
225
1
183
143
117
80
8
4
Age (years)
1-4
5-11
12-17
18-64
>64
65
1
103
228
2642
587
1
51
12
57
1979
501
6
14
45
379
46
2
1
33
69
201
20
6
44
56
76
15
1
6
5
Race
White
Black
Asian
Some Others
Hispanic
Refused
2928
385
61
67
147
38
1
2114
261
48
44
108
25
391
61
6
9
17
6
257
40
3
9
12
5
157
21
4
5
8
2
8
2
2
Hispanic
No
Yes
DK
Refused
3322
258
21
25
1
2383
185
16
16
454
32
4
296
25
3
2
178
14
2
3
10
2
En
iployment
-ull Time
3art Time
slot Employed
Refused
328
1765
349
1165
19
1
71
1282
270
965
12
57
284
44
104
1
102
145
17
60
2
97
50
15
31
4
1
4
3
4
Education
< High School
High School Graduate
< College
College Graduate
Post Graduate
386
354
1106
796
591
393
1
101
298
856
606
445
294
65
26
140
116
86
57
107
15
74
57
47
26
112
12
30
16
13
14
1
3
5
1
2
Census Region
Northeasr
Midwest
South
West
832
811
1214
769
1
636
569
840
555
90
114
175
111
60
81
124
61
43
45
70
39
3
2
4
3
Day of Week
Weekday
Weekend
2474
1152
1
1759
841
335
155
236
90
136
61
8
4
Season
Winter
Spring
Summer
Fall
985
902
987
752
1
691
648
705
556
138
117
132
103
90
85
92
59
63
46
55
33
3
5
3
1
Asthma
No
Yes
DK
3345
263
18
1
2407
179
14
455
33
2
290
34
2
183
I4
9
3
Angina
No
Yes
DK
3501
105
20
1
2499
86
15
475
11
4
321
5
194
2
1
12
Bronchitis/Emphysema
Yes
DK
3438
169
19
1
2459
126
15
460
27
3
314
11
1
192
5
12
Note: * Signifies missing data. "DK"
Source: Tsana And Kleoeis. 1996
= respondent answered don't know;
N= sample size; Refused =
respondent refused to answer.
-------
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
Day
3-5 / Day
1 -2/week
<1/week
Never
DK
Overall
4663
404
566
1033
1827
331
465
37
Gender
Male
Female
Refused
2163
2498
2
212
191
1
211
355
458
575
811
1015
1
154
T7
300
-I65
17
20
Age (years)
1-4
5-11
12-17
18-64
>64
84
263
348
326
2972
670
3
261
101
1
31
7
6
2
22
489
47
11
4
29
832
157
47
16
83
1328
353
3
15
67
197
49
2
1
206
124
83
49
12
1
4
12
8
Race
White
Black
Asian
Some Others
Hispanic
Refused
3774
463
77
96
193
60
316
39
4
16
29
499
33
1
10
19
4
883
72
12
15
41
10
1445
207
39
36
77
23
246
52
13
8
10
2
370
55
8
11
17
4
15
5
17
Hispanic
No
Yes
DK
Refused
4244
347
26
46
342
59
2
1
528
31
3
4
950
69
6
8
1674
130
10
13
307
20
3
1
424
38
2
1
19
18
Employment
Full Time
Part Time
Not Employed
Refused
926
2017
379
1309
32
366
21
6
10
1
23
305
64
170
4
32
569
101
326
5
97
929
166
628
7
76
119
29
105
2
327
66
13
58
1
5
8
12
12
Education
< High School
High School Graduate
< College
College Graduate
Post Graduate
1021
399
1253
895
650
445
367
3
14
3
12
5
33
61
218
126
78
50
37
88
367
261
171
109
129
178
548
432
321
219
89
40
55
51
57
39
343
27
47
19
9
20
23
2
4
3
2
3
Census Region
Northeast
Midwest
South
West
1048
1036
1601
978
84
88
147
85
119
108
229
110
216
229
376
212
454
408
557
408
81
78
97
75
87
121
182
75
7
4
13
13
Day of Week
Weekday
Weekend
3156
1507
257
147
407
159
697
336
1217
610
232
99
320
145
26
11
Season
Wnter
Spring
Summer
Fall
1264
1181
1275
943
121
122
102
59
157
135
163
111
273
259
280
221
472
464
484
407
101
82
88
60
129
113
142
81
11
6
16
4
Asthma
No
Yes
DK
4287
341
35
371
32
1
522
42
2
951
79
3
1700
118
9
303
26
2
421
43
1
19
1
17
Angina
No
Yes
DK
4500
125
38
403
1
555
8
3
993
37
3
1759
58
10
321
7
3
451
13
1
18
2
17
Bronchitis/emphysema
No
Yes
DK
4424
203
36
397
7
549
15
2
979
51
3
1724
92
11
315
14
2
441
23
1
19
1
17
Note: * Signifies missing data. "DK" = respondent answered don't know; N= sample size; Refused = respondent refused to answer.
Source: Tsanq And Klepeis. 1996
-------
Table 15-57. Number of Minutes Spent Playing on Sand or Gravel in a Day by the Number of Respondents
Minutes/Day
rota I N
...
0-0
0-10
10-20
20-30
30-40
40-50 50-60 70-80 80-90
90-100
110-120
121
700
41
348
42
34
57
4
12
66
2
9
2
27
56
352
18
189
20
13
25
.
7
32
.
7
1
10
30
347
23
158
22
21
32
4
5
34
2
2
1
17
26
1
*
1
*
*
*
*
*
*
*
*
*
*
*
3
1
.
.
1
.
.
.
.
.
.
*
.
1
216
13
115
15
9
15
2
3
15
1
5
*
7
16
200
7
96
11
12
14
*
5
25
1
2
1
6
20
41
1
23
1
2
4
*
*
3
*
*
1
3
3
237
18
112
15
10
24
2
4
23
*
2
*
11
16
3
1
2
*
*
*
*
*
*
*
*
*
*
*
568
34
274
37
30
49
2
9
57
1
8
2
21
44
68
4
42
5
3
2
*
1
4
*
*
*
3
4
5
*
2
*
*
1
*
*
1
*
*
*
*
1
16
2
9
*
*
*
2
*
1
*
*
*
*
3
41
*
19
*
1
5
*
2
3
1
1
*
3
4
2
2
*
*
*
*
*
*
*
*
*
*
*
619
36
309
41
29
49
4
10
59
1
7
2
23
49
77
5
36
1
4
8
*
2
7
1
2
*
4
7
3
*
2
*
1
*
*
*
*
*
*
*
*
*
1
*
1
*
*
*
*
*
*
*
*
*
*
*
461
22
234
27
24
33
2
8
43
2
7
2
16
41
149
9
73
7
7
16
1
3
17
*
2
*
6
8
29
2
10
4
1
2
1
*
4
*
*
*
2
3
60
7
31
4
2
6
*
1
2
*
*
*
3
4
1
1
*
*
*
*
*
*
*
*
*
*
*
*
461
22
234
27
24
33
2
8
43
2
7
2
16
41
22
5
9
*
*
3
*
*
1
*
*
*
2
2
73
4
39
4
1
8
1
*
6
*
1
*
2
7
66
2
34
6
2
6
*
2
6
*
*
*
4
4
54
4
26
3
3
6
1
2
7
*
*
*
*
2
24
4
6
2
4
1
*
*
3
*
1
*
3
*
124
8
60
8
5
7
.
4
16
.
1
*
6
9
128
6
69
8
6
14
*
2
11
*
2
*
3
7
273
17
133
18
12
25
3
3
30
*
3
2
6
21
175
10
86
8
11
11
1
3
9
2
3
*
12
19
445
35
216
27
22
40
3
10
37
2
6
2
17
28
255
6
132
15
12
17
1
2
29
*
3
*
10
28
107
10
44
9
6
11
1
2
8
2
1
*
4
9
240
8
113
21
14
22
1
3
25
*
2
*
12
19
262
12
146
5
9
20
2
5
25
*
5
2
9
22
91
11
45
7
5
4
*
2
8
*
1
*
2
6
638
38
319
39
34
51
4
10
57
2
9
2
22
51
61
3
28
3
*
6
*
2
9
*
*
*
5
5
1
*
1
*
*
*
*
*
*
*
*
*
*
*
699
40
348
42
34
57
4
12
66
2
9
2
27
56
1
1
*
*
*
*
*
*
*
*
*
*
*
*
679
41
339
41
34
54
4
12
62
2
9
2
26
53
21
*
9
1
*
3
*
*
4
*
*
*
1
3
Overall
Gender
Male
Female
Refusedused
Age (years)
1-4
5-11
12-17
18-64
>64
Race
White
Black
Asian
Some Others
Hispanic
Refused
Hispanic
No
Yes
DK
Refused
Employment
Full Time
Part Time
Not Employed
Refused
Education
< High School
High School Graduate
< College
College Graduate
Post Graduate
Census Region
Northeast
Midwest
South
West
Day of Week
Weekday
Weekend
Season
Winter
Spring
Summer
Fall
Asthma
No
Yes
DK
Angina
No
DK
Bronchitis/Emphysema
No
Yes
Note: = Signifies missing data. "DK" = Don't know. Refused = 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 klepeis. 1996.
-------
Table 15-58. Number of Minutes Spent Playing in Sand or Gravel (minutes/day)
Percentiles
Category
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
Wnter
97
0
0
0
0
0
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. N = doer sample size. Percentiles
are the percentage of doers below or equal to a given number of minutes.
Source: Tsana and Klepeis.1996
-------
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
Minutes/Day
Total N
0-0 0-10 10-20 20-30 30-40 40-50 50-60 70-80 80-90 110-120 121
700
53
380
51
29
48
1
6
60
352
26
183
22
18
33
.
3
24
347
27
196
29
V
15
1
3
36
1
*
1
3
.
.
1
.
.
.
.
1
216
11
118
14
10
13
1
4
18
200
15
103
14
8
15
*
1
17
41
3
19
3
2
7
*
*
4
237
23
138
19
9
13
*
1
20
3
1
2
*
568
40
317
40
21
38
.
5
48
68
8
33
5
2
6
*
1
7
5
2
2
*
16
*
10
1
2
1
1
*
1
41
5
17
5
4
*
4
2
1
1
*
*
619
45
345
42
21
44
1
6
54
77
8
32
9
8
3
*
*
6
3
3
*
*
1
*
*
*
1
*
*
*
461
29
240
32
20
35
1
5
40
149
11
91
8
8
8
*
1
12
29
4
17
3
2
*
2
60
8
32
8
1
3
*
*
6
1
1
*
*
461
29
240
32
20
35
1
5
40
22
5
9
*
*
3
*
*
2
73
6
44
7
2
3
*
*
7
66
4
38
7
3
3
*
1
7
54
3
35
3
4
4
*
*
3
24
6
14
2
*
*
*
*
1
124
6
70
13
3
5
.
.
18
128
12
77
6
7
10
*
1
7
273
23
153
17
12
20
*
3
17
175
12
80
15
7
13
1
2
18
445
39
235
34
21
34
1
2
38
255
14
145
17
8
14
4
22
107
4
51
6
6
5
.
2
7
240
0
134
17
10
20
1
2
21
262
7
143
19
12
19
*
1
25
91
2
52
9
1
4
*
1
7
638
48
354
47
25
41
1
5
50
61
5
25
4
4
7
*
1
10
1
1
*
699
53
380
51
29
48
1
6
60
1
*
679
52
368
51
28
46
1
5
57
21
1
12
*
1
2
*
1
3
Overall
Gender
Male
-emale
Refused
Age (years)
1-4
5-11
12-17
18-64
>64
Race
White
Black
Asian
Some Others
Hispanic
Refused
Hispanic
No
Yes
DK
Refused
Employment
-ull Time
3art Time
slot Employed
Refused
Education
< High School
High School Graduate
< College
College Graduate
Post Graduate
Census Region
Northeast
Midwest
South
West
Day of Week
weekday
Weekend
Season
Winter
Spring
Summer
Fall
Asthma
No
Yes
DK
Anngina
No
DK
Bronchitis/Emphysema
Yes
7
1
21
16
5
15
3
17
4
21
21
43
21
22
1
16
17
38
2
1
38
5
18
35
3
5
1
*
2
*
18
35
1
2
1
1
3
*
2
1
2
6
2
4
11
13
6
20
10
24
11
19
2
2
10
3
8
5
1
3
19
40
2
3
43
42
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 Klepeis. 1996.
-------
Table 15-60. Number of Minutes Spent Playing on Sand, Gravel, Dirt, or Grass When Fill Dirt Was Present (minutes/day)
Percentiles
Cateaorv
Population Group
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
0
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
0
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. N = doer sample size. Percentiles
are the percentage of doers below or equal to a given number of minutes.
Source: Tsana and Klepeis.1996
-------
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-
288-
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
8
2
1
*
11
Female
2498
53
1618
683
68
40
12
14
*
2
1
2
*
1
*
1
3
Refused
2
1
1
*
*
*
Age (years)
*
84
11
51
17
*
2
2
1
*
*
*
*
*
*
*
*
*
1-4
263
7
189
55
4
3
2
2
*
*
*
*
*
*
*
*
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
7
1
8
8
3
*
*
13
>64
670
24
414
165
29
19
8
3
*
2
2
3
*
*
*
1
*
Race
White
3774
59
2303
1128
127
69
22
21
7
4
11
7
3
1
1
10
Black
463
9
351
77
9
8
3
*
*
2
1
*
1
*
*
*
2
Asian
77
1
50
25
1
*
*
*
*
*
*
*
*
*
*
*
*
Some Others
96
2
64
23
2
2
1
*
*
*
1
*
*
*
*
*
Hispanic
193
6
126
50
5
1
2
1
*
*
*
*
*
*
*
*
2
Refused
60
14
34
9
1
1
*
1
*
*
*
*
*
*
*
*
*
Hispanic
No
4244
65
2669
1206
135
73
25
20
8
5
12
8
3
1
1
12
Yes
347
11
218
94
9
6
3
3
*
*
*
*
*
*
*
2
DK
26
1
18
5
*
1
*
*
*
*
*
*
*
*
*
*
Refused
46
14
23
7
1
1
*
*
*
*
*
*
*
*
*
*
*
Employment
926
19
638
230
20
8
2
3
*
2
1
,
,
1
,
1
Full Time
2017
18
1235
600
68
35
12
9
7
1
10
8
2
*
*
11
Part Time
379
4
234
120
9
3
2
4
*
2
*
*
*
*
*
*
1
Not Employed
1309
39
808
354
48
35
12
7
*
*
2
1
*
1
*
1
1
Refused
32
11
13
8
*
*
*
*
*
*
*
*
*
*
*
*
*
Education
*
1021
34
699
246
22
8
3
3
*
2
1
*
*
1
*
1
< High School
399
18
263
86
11
9
4
4
*
*
1
*
*
*
*
2
High School
1253
25
770
355
41
22
9
7
*
5
2
8
4
*
*
1
4
Graduate
895
11
545
265
33
18
6
3
*
*
2
4
3
*
*
4
< College
650
1
406
200
19
12
3
5
*
1
*
*
*
*
*
2
College Graduate
445
2
245
160
19
12
3
1
*
*
*
*
*
*
1
Post Graduate
Census Region
Northeast
Midwest
South
West
Day of Week
Weekday
Weekend
Season
Wnter
Spring
Summer
Fall
Asthma
No
Yes
DK
Angina
NO
Yes
DK
Bronchitis/emphysema
No
Yes
DK
1048
17
714
259
24
12
4
8
*
3
*
2
1
*
1
*
3
1036
23
687
273
19
18
5
3
*
*
*
3
*
3
*
*
2
1601
35
989
446
64
26
11
7
1
4
4
3
6
*
*
1
4
978
16
538
334
38
25
8
5
3
1
4
1
5
3156
62
1982
890
96
54
18
15
1
8
3
6
7
2
.
1
11
1507
29
946
422
49
27
10
8
2
2
6
1
1
1
3
1264
9
1038
171
20
9
5
3
.
2
2
2
.
.
.
1
2
1181
29
614
434
50
20
8
7
*
4
1
4
5
2
*
*
3
1275
39
690
421
56
33
12
9
1
2
1
3
3
1
*
*
4
943
14
586
286
19
19
3
4
*
2
1
3
*
*
1
*
5
4287
70
2697
1206
135
77
27
23
1
10
5
12
6
3
1
1
13
341
6
216
101
10
4
1
*
*
*
*
*
2
*
*
*
1
35
15
15
5
*
*
*
*
*
*
*
*
*
*
*
*
*
4500
74
2825
1277
143
77
28
21
1
10
5
12
8
3
1
1
14
125
4
86
29
1
3
*
2
*
*
*
*
*
*
*
*
*
38
13
17
6
1
1
*
*
*
*
*
*
*
*
*
*
4424
72
2766
1265
140
77
27
22
1
10
5
12
8
3
1
1
14
203
5
146
43
5
2
1
1
*
*
*
*
*
*
*
*
*
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
specified range of number of minutes spent.
Sburce: Tsanq and Klepeis.1996
-------
Table 15-62. Number of Hours Spent Working with Soil in a Garden or Other Circumstances Working (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
Wnter
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 Klepeis. 1996.
-------
Table 15-63. Range of Number of Minutes Spent Playing on Grass in a Day by the Number of Respondents
Minutes/Day
Total
N
*.*
0-0
0-10
10-20
20-30
30-40
40-50
50-60
60-70
70-80
80-90
90-
100
100-
110
110-
120
121-
121
700
43
79
49
49
85
7
11
125
1
21
1
2
66
160
352
25
35
23
25
41
3
5
64
.
12
.
1
33
84
347
18
44
26
24
44
4
6
61
1
*
9
1
1
33
75
1
*
*
*
*
*
*
*
*
*
*
*
*
*
1
3
.
.
1
1
.
.
.
.
*
*
.
.
.
1
216
10
24
19
21
25
1
4
35
*
8
*
1
18
49
200
15
24
10
10
19
2
3
38
*
8
1
20
49
41
2
5
1
2
8
*
1
8
*
*
1
*
8
5
237
16
26
18
15
32
4
3
44
*
*
4
*
1
20
54
3
*
*
*
*
1
*
*
*
*
*
*
*
*
2
568
36
65
40
39
58
7
9
98
17
1
1
56
139
68
3
4
6
7
14
*
1
15
*
*
2
*
5
11
5
*
*
1
*
3
*
*
*
*
*
*
*
*
1
16
*
4
*
1
1
*
*
4
*
*
1
*
2
3
41
4
5
2
2
9
*
*
8
*
*
1
*
1
3
6
2
*
1
*
*
*
*
1
*
*
*
*
*
*
*
619
38
65
44
42
73
6
11
110
18
1
1
62
146
77
5
13
5
7
11
1
*
14
*
*
3
*
1
4
13
3
*
*
*
*
1
*
*
1
*
*
*
*
*
1
1
*
1
*
*
*
*
*
*
*
*
*
*
*
*
461
27
54
31
34
52
3
8
81
17
1
1
46
104
149
8
16
12
10
21
3
3
25
*
*
2
*
13
36
29
2
5
1
1
6
*
*
4
*
*
2
*
3
5
60
5
4
5
4
6
1
*
15
*
*
*
*
1
4
15
1
1
*
*
*
*
*
*
*
*
*
*
*
*
*
461
27
54
31
34
52
3
8
81
17
1
1
46
104
22
2
2
1
1
4
*
*
3
*
*
*
*
1
3
5
73
4
8
9
4
6
1
1
9
*
*
3
*
*
6
22
66
2
7
4
6
13
2
*
20
*
*
*
*
*
3
9
54
3
5
3
4
6
1
1
10
*
*
*
*
*
6
15
24
5
3
1
*
4
*
1
2
*
*
1
*
*
2
5
124
5
14
10
4
13
.
3
26
*
*
2
1
.
10
36
128
8
7
10
10
15
1
3
23
*
4
*
*
15
31
273
21
22
20
25
30
5
4
52
1
*
11
*
2
23
57
175
9
36
9
10
27
1
1
24
4
18
36
445
33
55
35
32
55
3
7
82
*
1
15
1
1
38
87
255
10
24
14
17
30
4
4
43
6
1
28
73
107
12
22
6
6
15
2
.
15
*
*
5
.
.
5
19
240
9
23
16
13
28
1
5
49
*
*
7
1
1
26
61
262
12
20
20
18
36
2
5
48
*
7
*
1
29
63
91
10
14
7
12
6
2
1
13
*
2
*
*
6
17
638
38
73
46
44
78
7
9
114
18
1
2
60
146
61
5
6
3
5
7
*
2
10
*
*
3
*
*
6
14
1
*
*
*
*
*
*
*
1
*
*
*
*
*
*
*
699
43
79
49
48
85
7
11
125
21
1
2
66
160
1
*
*
*
1
*
*
*
*
*
*
*
*
*
*
*
679
43
76
49
47
83
7
11
120
20
1
2
65
153
21
*
3
*
2
2
*
*
5
*
*
1
*
*
1
7
Overall
Gender
Male
Female
Refused
Age (years)
1-4
5-11
12-17
18-64
>64
Race
White
Black
Asian
Some Others
Hispanic
Refused
Hispanic
No
Yes
DK
Refused
Employment
Full Time
Part Time
Not Employed
Refused
Education
< High School
High School Graduate
< College
College Graduate
Post Graduate
Census Region
Northeast
Midwest
South
West
Day of Week
Weekday
Weekend
Season
Winter
Spring
Summer
Fall
Asthma
No
Yes
DK
Angina
NO
DK
Bronchitis/emphysema
No
Yes
NOTE: A value of "121" for number of minutes signifies that more than 120 minutes were spent. N = doer sample size,
the percentage of doers below or equal to a given number of minutes. Refused = respondent refused to answer.
Source: Tsang and Klepeis.1996.
Percentiles are
-------
Table 15-64. Number of Minutes Spent Playing on Grass (minutes/day)
Category
Population Group
Percentiles
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
20
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
Wnter
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/Emphysema
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 Klepeis.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
653
147
94
73
47
42
26
11
26
2
38
3
27
2
2
27
2
300
62
47
37
20
16
17
5
9
2
16
2
13
1
.
16
1
352
85
47
36
27
26
9
6
17
*
22
1
I4
1
1
•n
1
1
*
1
8
2
2
1
1
1
1
.
.
.
.
.
.
.
.
.
.
63
11
14
7
3
3
4
1
3
1
4
*
2
1
1
2
*
100
16
15
7
9
6
4
2
4
7
*
5
11
2
84
21
13
7
4
8
4
2
3
1
8
*
1
*
*
2
*
360
86
48
50
27
22
11
5
14
*
18
3
15
1
1
10
*
38
11
2
1
3
2
2
1
2
*
1
*
4
*
*
2
*
Overall
Gender
Male
-emale
Refused
Age (years)
1-4
5-11
12-17
18-64
>64
Race
White
Black
Asian
Some Others
Hispanic
Refused
Hispanic
No
Yes
DK
Refused
Employment
-ull Time
3art Time
slot Employed
Refused
Education
< High School
High School Graduate
-------
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
2
2
2
5
Ge
rider
Vlale
*
10
*
*
4
2
1
*
10
2
*
*
*
4
-emale
2
15
1
1
5
*
*
1
16
*
*
1
1
1
1
2
1
Refused
*
*
*
*
Age (years)
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
1-4
*
2
*
*
*
*
*
1
2
*
1
*
*
*
*
*
*
5-11
*
3
*
1
2
*
*
5
*
*
*
*
1
*
*
12-17
1
4
*
1
*
*
2
*
*
*
*
*
1
18-64
*
15
1
*
7
1
1
*
15
2
*
2
1
*
*
3
>64
1
1
*
*
2
*
*
1
Race
White
Black
Asian
Some Others
Hispanic
Hispanic
No
Yes
DK
Refused
Employment
-ull Time
3art Time
slot Employed
Refused
Education
< High School
High School Graduate
< College
College Graduate
Post Graduate
Census Region
Northeast
Midwest
South
West
Day of Week
Weekday
Weekend
Season
Winter
Spring
Summer
Fall
Asthma
No
Yes
DK
Angina
Wo
Yes
DK
Bronchitis/Emphysema
Yes
DK
19
3
1
1
1
23
1
1
9
7
I
II
1
6
3
2
2
7
4
7
7
18
7
10
4
21
3
1
24
1
22
2
1
19
3
3
1
20
6
9
10
1
6
23
3
*
i
9
*
1
*
*
*
1
*
1
*
*
*
*
*
*
4
*
*
*
i
*
*
*
*
4
*
*
*
1
*
*
*
3
2
*
2
i
*
1
*
5
*
*
*
.
.
2
1
.
1
1
.
.
*
*
4
*
i
*
*
i
i
9
1
*
1
*
1
11
1
*
1
i
.
19
.
1
1
.
1
1
1
7
2
1
2
i
.
.
1
.
.
1
.
.
*
3
*
*
1
*
1
*
i
21
1
1
2
*
1
*
*
2
*
*
i
i
23
2
1
2
2
1
*
2
1
*
*
1
*
*
*
*
*
i
i
26
2
1
2
1
1
1
1
2 5
2 4
1
Note: * Signifies missing data. "DK" = respondent answered don't know; N= sample size; Refused = respondent refused to <
Source: Tsang And Klepeis. 1996
-------
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
653
13
62
75
120
20
39
131
8
2
31
2
68
10
32
40
300
5
31
38
60
6
17
55
3
.
18
1
28
6
17
15
352
7
31
37
60
14
22
76
5
2
13
1
40
4
15
25
1
1
*
*
*
*
*
*
*
*
*
*
*
*
*
*
8
1
2
1
2
.
.
.
.
.
.
.
2
.
.
.
63
3
5
12
12
1
4
8
*
*
2
*
7
1
3
5
100
5
3
2
12
5
4
25
*
*
7
*
16
2
11
8
84
1
3
7
10
2
6
15
*
1
8
1
14
4
6
6
360
3
45
50
75
8
22
74
8
*
13
1
26
3
12
20
38
*
4
3
9
4
3
9
*
1
1
*
3
*
*
1
555
7
53
67
105
18
36
109
8
2
24
2
59
9
26
30
30
3
1
1
4
*
*
8
*
*
5
*
1
1
1
5
13
*
1
1
3
1
*
4
*
*
1
*
1
*
*
1
12
*
1
2
1
*
*
3
*
*
*
*
2
*
1
2
35
1
5
4
4
1
2
7
*
*
1
*
4
*
4
2
8
2
1
*
3
*
1
*
*
*
*
*
1
*
*
*
591
11
57
67
108
19
35
120
8
2
29
2
62
9
28
34
55
1
5
8
10
1
3
10
*
*
2
*
5
1
4
5
2
*
*
*
*
*
*
1
*
*
*
*
*
*
*
1
5
1
*
*
2
*
1
*
*
*
*
1
*
*
243
9
11
20
34
8
13
48
.
1
16
1
37
7
19
19
240
3
31
29
51
4
14
51
3
*
8
*
21
3
10
12
43
*
3
10
12
1
3
2
1
*
5
*
2
*
*
4
122
1
16
16
21
7
8
30
4
1
2
1
7
*
3
5
5
*
1
*
2
*
1
*
*
*
*
*
1
*
*
*
257
9
13
22
35
8
15
50
.
1
17
1
39
7
20
20
16
*
4
2
3
*
*
3
1
*
1
*
*
*
*
2
112
1
12
10
16
5
8
26
1
1
5
1
11
*
5
10
104
2
15
16
27
2
4
20
3
*
4
*
6
1
2
2
93
1
8
15
21
2
6
17
1
*
1
*
10
2
4
5
71
*
10
10
18
3
6
15
2
*
3
*
2
*
1
1
136
2
12
17
28
5
9
20
3
1
4
.
13
3
9
10
130
3
10
17
27
4
8
24
1
*
6
*
17
1
7
5
235
8
20
19
37
6
15
56
*
*
13
1
26
4
12
18
152
*
20
22
28
5
7
31
4
1
8
1
12
2
4
7
445
11
45
52
82
14
23
87
7
2
19
.
46
8
22
27
208
2
17
23
38
6
16
44
1
*
12
2
22
2
10
13
62
2
6
6
10
5
3
14
.
.
3
1
7
1
1
3
174
3
21
24
37
7
12
32
*
2
6
1
13
3
6
7
363
7
29
36
64
6
20
77
6
*
20
*
44
6
23
25
54
1
6
9
9
2
4
8
2
2
4
2
5
590
12
52
71
114
19
33
117
8
2
26
2
64
9
26
35
56
1
9
3
4
*
5
14
*
*
5
*
3
1
6
5
7
*
1
1
2
1
1
*
*
*
*
*
1
*
*
*
639
13
60
73
118
19
37
130
8
2
30
2
66
10
32
39
8
*
*
2
1
1
1
1
*
*
1
*
1
*
*
*
6
*
2
*
1
*
1
*
*
*
*
*
1
*
*
1
621
13
56
72
115
19
37
123
7
2
31
2
67
10
30
37
26
*
5
3
4
1
1
7
*
*
*
*
*
*
2
3
6
*
1
*
1
*
1
1
1
*
*
*
1
*
*
*
Overall
Gender
Male
Female
Refused
Age (years)
1-4
5-11
12-17
18-64
>64
Race
White
Black
Asian
Some Others
Hispanic
Refused
Hispanic
No
Yes
DK
Refused
Employment
Full Time
Part Time
Not Employed
Refused
Education
< High School
High School Graduate 112
< College
College Graduate
Post Graduate
Census Region
Northeast
Midwest
South
West
Day of Week
Weekday
Weekend
Season
Wnter
Spring
Summer
Fall
Asthma
No
Yes
DK
Angina
No
Yes
DK
Bronchitis/emphysema
No
Yes
DK
Note: * Signifies missing data. DK= respondents answered don't know. Ref = respondents refused to answer. N = doer sample size
in specified range of number of minutes spent. Values of 120, 150, and 180 for number of minutes signify that 2 hours, 2.5 hours,
and 3 hours, respectively, were spent.
Source: Tsanq and Klepeis.1996.
-------
Table 15-67. Number of Minutes Spent Swimming in a Month in Freshwater Swimming Pool (minutes/month)
Category
Population Group
Percentiles
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
Wnter
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. N
= doer sample size.
Percentiles are
the percentage of doers below or equal to a given number of minutes.
Source: Tsano and Klepeis.1996.
-------
Table 15-68. Statistics for 24-Hour Cumulative Number of Minutes Spent Working 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: Tsana and Kleoeis. 1996.
-------
Table 15-69. Statistics for 24-Hour Cumulative Number of Minutes Spent in Food Preparation
Percentiles
Category
Population Group
N
Mean
Stdev
Stderr
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
210
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
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
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
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: Tsana and Kleoeis. 1996.
-------
Table 15-70. Statistics for 24-Hour Cumulative Number of Minutes Spent in Food Cleanup
Group Name
Group Code
N
Mean
Stdev
Stderr
Min
Max
5
25
50
Percentiles
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
825
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 minufes 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 15-71. Statistics for 24-Hour Cumulative Number of Minutes Spent Cleaning House
Percentiles
Category
Population Group
N
Mean
Stdev
Stderr
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
104.234
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. 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 15-72. Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor Cleaning
Category
Population Group
N
Mean
Stdev
Stderr
Min
Max
5
25
50
Percentiles
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
Employment
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
655
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 minufes 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 15-73. Statistics for 24-Hour Cumulative Number of Minutes Spent in Clothes Care
Category
Population Group
N
Mean
Stdev
Stderr
Min
Max
5
25
50
Percentiles
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 Kleoeis. 1996.
-------
Table 15-74. Statistics for 24-Hour Cumulative Number of Minutes Spent in Car Repair/Maintenance
Category
Population Group
N
Mean
Stdev
Stderr
Min
Max
5
25
50
Percentiles
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 Kleoeis. 1996.
-------
Table 15-75. Statitstics for 24-Hour Cumulative Number of Minutes Spent in Other Repairs
Group Name
Group Code
N
Mean
Stdev
Stderr
Min
Max
5
25
50
Percentiles
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 Others
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 missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour
cumulative number of minufes 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 15-76. 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
Education
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 Kleoeis. 1996.
-------
Table 15-77. Statistics for 24-Hour Cumulative Number of Minutes Spent in Animal Care
Category
Population Group
N
Mean
Stdev
Stderr
Min
Max
5
25
50
Percentiles
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
2.3505
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 Spent in Other Household Work
Group Name
Group Code
N
Mean
Stdev
Stderr Min
Max
5
25
50
Percentiles
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
10
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 Kleoeis. 1996.
-------
Table 15-79. Statistics for 24-Hour Cumulative Number of Minutes Spent in Indoor Playing
Category
Population Group
N
Mean
Stdev
Stderr
Min
Max
5
25
50
Percentiles
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
300
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)
18-64
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
Some 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
Wnter
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
No
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
No
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 Klepeis. 1996.
-------
Table 15-80. Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor Playing
Category
Population Group
N
Mean
Stdev
Stderr
Min
Max
5
25
50
Percentiles
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
30
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
108
115.681
40.899
25
360
25
30
67.5
142
360
360
360
360
Asthma
No
56
94.821
91.447
12.22
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 Kleoeis. 1996.
-------
Table 15-81. Statistics for 24-Hour Cumulative Number of Minutes Spent for Car Repair Services
Percentiles
Category
Population Group
N
Mean
Stdev
Stderr
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
12.5
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 missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour
cumulative number of minufes 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 Spent Washing, etc.
Percentiles
Category
Population Group
N
Mean
Stdev
Stderr
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
60
10
15
17.5
30
50
60
60
60
Hispanic
Refused
58
21.3966
18.5708
2.4385
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
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
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
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
100
6
15
25
30
45
60
60
75
Angina
DK
38
16.8947
8.5481
1.3867
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. 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 15-83. Statistics for 24-Hour Cumulative Number of Minutes Spent Sleeping/Napping
Percentiles
Category
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
900
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
645
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
< College
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 Of Week
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. 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 15-84. Statistics for 24-Hour Cumulative Number of Minutes Spent Attending Full Time School
Percentiles
Category
Population Group
N
Mean
Stdev
Stderr
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
400
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
28.2699
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
Census 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 minufes 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: Tsang and Klepeis. 1996.
-------
Table 15-85. Statistics for 24-Hour Cumulative Number of Minutes Spent in Active Sports
Percentiles
Category
Population Group
N
Mean
Stdev
Stderr
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
110
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 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 15-86. Statistics for 24-Hour Cumulative Number of Minutes Spent in Outdoor Recreation
Percentiles
Category
Population Group
N
Mean
Stdev
Stderr
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
Asthma
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
195
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. 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 15-87. Statistics for 24-Hour Cumulative Number of Minutes Spent in Exercise
Percentiles
Category
Population Group
N
Mean
Stdev
Stderr
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
10
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
73.627
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
149.57
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. 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 15-88. Statistics for 24-Hour Cumulative Number of Minutes Spent in Food Preparation8
Category
Population Group
N
Mean
Stdev
Stderr
Min
Max
5
25
50
Percentiles
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
20
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
0.8896
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
Refused
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
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
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
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 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 15-89. Statistics for 24-Hour Cumulative Number of Minutes Spent Doing Dishes/Laundry3
Category
Population Group
N
Mean
Stdev
Stderr
Min
Max
5
25
50
Percentiles
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
150
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
183
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 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 food cleanup, clothes care.
Source: Tsana and Kleoeis. 1996.
-------
Table 15-90. Statistics for 24-Hour Cumulative Number of Minutes Spent in Housekeeping9
Percentiles
Category
Population Group
N
Mean
Stdev
Stderr
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
270
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. 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 cleaning house, other repairs, and household work.
Source: Tsana and 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
Stderr
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
100
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
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
< High 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
1.0121
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
90
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
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
546
5
15
25
30
50
60
105
131
Angina
DK
42
22.1905
40.9153
6.3134
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, personal care services, washing and personal hygiene (bathing, showering, etc.)
Source: Tsana and Kleoeis. 1996.
-------
Table 15-92. Statistics for 24-Hour Cumulative Number of Minutes Spent in Yardwork/Maintenance (a)
Category
Population Group
N
Mean
Stdev
Stderr
Min
Max
5
25
50
Percentiles
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
205
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
472.5
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. 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 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
Stderr
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 ana Kleoeis. 1996.
-------
Table 15-94. Statistics for 24-Hour Cumulative Number of Minutes Eating or Drinking
Percentiles
Category
Population Group
N
Mean
Stdev
Stderr
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 Employed
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. 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 15-95. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at an Auto Repair Shop/Gas Station
Category
Population Group
N
Mean
Stdev
Stderr
Min
Max
5
25
50
Percentiles
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
Race
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
percentage of doers below or equal to a given number of minutes.
Source: Tsana and Kleoeis. 1996.
-------
Table 15-96. Statistics for 24-Hour Cumulative Numbr of Minutes Spent Indoors at a Gym/Health Club
Category
Population Group
N
Mean
Stdev
Stderr
Min
Max
5
25
50
Percentiles
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 Kleoeis. 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)
18-64
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 number of minutes.
Source: Tsang and Klepeis, 1996.
-------
Table 15-98. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at Work (non-specific)
Percentiles
Category
Population 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 Spent Indoors at the Dry Cleaners
Category
Population Group
N
Mean
Stdev
Stderr
Min
Max
5
25
50
Percentiles
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
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 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 Kleoeis. 1996.
-------
Table 15-100. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at a Bar/Nightclub/Bowling Alley
Percentiles
Category
Population Group
N
Mean
Stdev
Stderr
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
98.75
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
Refused
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
169.818
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 Kleoeis. 1996.
-------
Table 15-101. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at a Restaurant
Percentiles
Category
Population Group
N
Mean
Stdev
Stderr
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
101.01
124.69
3.8065
1
925
10
40
60
105
230
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
10
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. 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 15-102. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at School
Percentiles
Category
Population Group
N
Mean
Stdev
Stderr
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
180.277
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 minufes 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 Klepeis. 1996.
-------
Table 15-103. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors at a Plant/Factory/Warehouse
Percentiles
Category
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
5
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
Hispanic
Refused
5
397
314.833
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
705
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
Season
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 Neighborhood
Category
Population Group
N
Mean
Stdev
Stderr
Min
Max
5
25
50
Percentiles
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
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
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
Hispanic
Refused
9
100.778
115.933
38.6443
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
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
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 Spent Outdoors in a Parking Lot
Percentiles
Category
Population Group
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
37.093
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. 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 15-106. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a Service Station or Gas Station
Category
Population Group
N
Mean
Stdev
Stderr
Min
Max
5
25
50
Percentiles
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
110
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
Summer
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 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 15-107. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a Construction Site
Percentiles
Group Name
Group Code
N
Mean
Stdev
Stderr
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
600
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. 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 15-108. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors on School Grounds/Playground
Category
Population Group
N
Mean
Stdev
Stderr
Min
Max
5
25
50
Percentiles
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
94.553
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 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 15-109. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a Park/Golf Course
Category
Population Group
N
Mean
Stdev
Stderr
Min
Max
5
25
50
Percentiles
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
-------
Table 15-110. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a Pool/River/Lake
Percentiles
Category
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 Region
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: Tsana and Kleoeis. 1996.
-------
Table 15-111. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a Restaurant/Picnic
Category
Population Group
N
Mean
Stdev
Stderr
Min
Max
5
25
50
Percentiles
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
68.75
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
West
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
percentage of doers below or equal to a given number of minutes.
Source: Tsana and Kleoeis. 1996.
-------
Table 15-112. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors at a Farm
Percentiles
Category
Population Group
N
Mean
Stdev
Stderr
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
21.564
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
E mployment
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. 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 15-113. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Kitchen
Percentiles
Category
Population Group
N
Mean
Stdev
Stderr
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
300
10
35
60
112.5
185
240
300
300
Hispanic
Refused
76
88.421
118.56
13.6
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
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
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
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
657
10
45
100
155
255
360
415
620
Angina
DK
58
105.948
138.38
18.17
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: Tsana and Kleoeis. 1996.
-------
Table 15-114. Statistics for 24-Hour Cumulative Number of Minutes Spent in the Bathroom
Percentiles
Category
Population Group
N
Mean
Stdev
Stderr
Min
Max
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
530
5
15
30
45
85
120
300
360
Age (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
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
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
422
10
15
30
45
60
120
422
422
Hispanic
Refused
63
44.0794
95.224
11.997
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
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
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
600
7
20
30
45
75
185
546
570
Angina
DK
43
44.8605
111.216
16.96
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 Kleoeis. 1996.
-------
Table 15-115. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Bedroom
Percentiles
Category
Population Group
N
Mean
Stdev
Stderr
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
210.883
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
564.897
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: Tsana and Kleoeis. 1996.
-------
Table 15-116. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Garage
Category
Population Group
N
Mean
Stdev
Stderr
Min
Max
5
25
50
Percentiles
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: Tsana and Kleoeis. 1996.
-------
Table 15-117. Statistics for 24-Hour Cumulative Number of Minutes Spent in the Basement
Category
Population Group
N
Mean
Stdev
Stderr
Min
Max
Percentiles
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 minufes 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 Klepeis. 1996.
-------
Table 15-118. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Utility Room or Laundry Room
Percentiles
Group Name
Group Code
N
Mean
Stdev
Stderr
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 (years)
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 Of 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. 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 15-119. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Outdoor Pool or Spa
Percentiles
Category
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
Age (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: Tsana and Kleoeis. 1996.
-------
Table 15-120. Statistics for 24-Hour Cumulative Number of Minutes Spent at Home in the Yard or Other Areas Outside the House
Category
Population Group
N
Mean
Stdev
Stderr
Min
Max
5
25
50
Percentiles
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
10
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
1
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 Graduate
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 minufes 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 Klepeis. 1996.
-------
Table 15-121. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling in a Car
Percentiles
Category
Population Group
N
Mean
Stdev
Stderr
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. 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 15-122. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling in a Truck (Pick-up/Van)
Percentiles
Group Name
Group Code
N
Mean
Stdev
Stderr
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 Region
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
Season
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. 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 15-123. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on a Motorcycle, Moped, or Scooter
Category
Population Group
N
Mean
Stdev
Stderr
Min
Max
5
25
50
Percentiles
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
145
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 Kleoeis. 1996.
-------
Table 15-124. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling in Other Trucks
Percentiles
Category
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
»
»
95
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
670
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
173.143
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. 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 15-125. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on a Bus
Percentiles
Category
Population Group
N
Mean
Stdev
Stderr
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
945
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
945
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
161.48
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
109.5
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 Kleoeis. 1996.
-------
Table 15-126. Statistics for 24-Hour Cumulative Number of Minutes Spent Walking
Percentiles
Category
Population Group
N
Mean
Stdev
Stderr
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
150
8
15
20
40
65
65
150
150
Hispanic
No
1467
29.8718
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
80
2
10
17.5
55
77.5
80
80
80
Hispanic
Refused
18
35.7222
34.7847
8.1988
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
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
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
150
4
6
14.5
36
60
115
150
150
Angina
DK
17
46.6471
63.1456
15.3151
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
110
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 Kleoeis. 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
Stderr
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 Spent Waiting on a Bus, Train, etc. Stop
Percentiles
Category
Population Group
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 (years)
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
67
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 Kleoeis. 1996.
-------
Table 15-129. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on a Train/Subway/Rapid Transit
Percentiles
Group Name Group Code N Mean Stdev Stderr Mi Max 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. 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 15-130. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling on an Airplane
Group Name
Group Code
N
Mean
Stdev
Stderr
Min
Max
5
25
50
Percentiles
75 90
95
98
99
All
53
234
203.736
27.985
10
900
15
70
210
300
480
660
900
900
Gender
Male
28
241.25
230.979
43.651
15
900
20
65
210
292.5
555
900
900
900
Gender
Female
25
225.88
172.581
34.516
10
660
15
110
210
300
480
510
660
660
Age (years)
»
3
175
145.688
84.113
15
300
15
15
210
300
300
300
300
300
Age (years)
12-17
3
113.333
118.568
68.455
15
245
15
15
80
245
245
245
245
245
Age (years)
18-64
42
226.429
193.962
29.929
10
900
20
60
202.5
300
480
555
900
900
Age (years)
> 64
5
405.4
292.392
130.762
195
900
195
210
287
435
900
900
900
900
Race
White
44
241.068
215.555
32.496
10
900
15
65
210
300
510
660
900
900
Race
Black
7
199.286
134.364
50.785
15
435
15
110
210
255
435
435
435
435
Race
Asian
1
60
»
»
60
60
60
60
60
60
60
60
60
60
Race
Hispanic
1
340
»
»
340
340
340
340
340
340
340
340
340
340
Hispanic
No
51
234.745
206.224
28.877
10
900
15
60
210
300
480
660
900
900
Hispanic
Yes
2
215
176.777
125
90
340
90
90
215
340
340
340
340
340
Employment
»
3
113.333
118.568
68.455
15
245
15
15
80
245
245
245
245
245
Employment
Full Time
33
212.424
194.008
33.773
15
900
20
60
180
285
480
555
900
900
Employment
Part Time
3
510
375.899
217.025
150
900
150
150
480
900
900
900
900
900
Employment
Not Employed
13
259.385
168.387
46.702
10
660
10
195
225
300
435
660
660
660
Employment
Refused
1
150
»
»
150
150
150
150
150
150
150
150
150
150
Education
»
4
122.5
98.531
49.265
15
245
15
47.5
115
197.5
245
245
245
245
Education
< High School
4
111.25
179.647
89.823
10
380
10
12.5
27.5
210
380
380
380
380
Education
High School Graduate
9
253.889
191.046
63.682
15
660
15
195
270
285
660
660
660
660
Education
< College
13
293.846
170.784
47.367
20
555
20
180
300
435
510
555
555
555
Education
College Graduate
15
194.8
113.998
29.434
45
480
45
90
210
255
287
480
480
480
Education
Post Graduate
8
305
375.129
132.628
20
900
20
45
137.5
577.5
900
900
900
900
Census Region
Northeast
17
254.706
234.81
56.95
15
900
15
70
245
380
510
900
900
900
Census Region
Midwest
17
235.118
234.348
56.838
15
900
15
60
195
287
660
900
900
900
Census Region
South
9
212.778
103.565
34.522
15
340
15
150
255
270
340
340
340
340
Census Region
West
10
216
181.702
57.459
10
555
10
45
202.5
240
517.5
555
555
555
Day Of Week
Weekday
37
258.919
192.755
31.689
15
900
15
150
230
305
510
660
900
900
Day Of Week
Weekend
16
176.375
222.825
55.706
10
900
10
37.5
95
262.5
360
900
900
900
Season
Winter
17
216.294
172.818
41.914
20
660
20
60
210
275
480
660
660
660
Season
Spring
14
191.786
160.547
42.908
15
555
15
90
150
230
435
555
555
555
Season
Summer
17
230.882
222.171
53.884
10
900
10
60
245
300
480
900
900
900
Season
Fall
5
423
294.398
131.659
180
900
180
240
285
510
900
900
900
900
Asthma
No
51
224.843
201.484
28.213
10
900
15
60
210
287
480
660
900
900
Asthma
Yes
2
467.5
123.744
87.5
380
555
380
380
467.5
555
555
555
555
555
Angina
No
51
233.725
207.562
29.064
10
900
15
60
210
300
480
660
900
900
Angina
Yes
2
241
65.054
46
195
287
195
195
241
287
287
287
287
287
Bronchitis/Emphysema
No
51
231.608
206.7
28.944
10
900
15
60
210
300
480
660
900
900
Bronchitis/Emphysema
Yes
2
295
120.208
85
210
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 Kleoeis. 1996.
-------
Table 15-131. Statistics for 24-Hour Cumulative Number of Minutes Spent Indoors in a Residence (all rooms)
Category
Population Group
N
Mean
Stdev
Stderr
Min
Max
5
25
50
Percentiles
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
1250
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
1400
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
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 missing data. "DK" = The respondent replied "don't know". Refused = Refused data. N = doer sample size. Mean = Mean 24-hour
cumulative number of minufes 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 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
10
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
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
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
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
660
5
15
60
125
555
600
660
660
Education
»
825
174.105
156.184
5.4376
1
1250
15
60
125
240
380
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
Season
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
1080
5
30
68.5
252.5
465
660
1065
1080
Angina
DK
25
195
170.434
34.0869
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 of minufes 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 Klepeis. 1996.
-------
Table 15-133. Statistics for 24-Hour Cumulative Number of Minutes Spent Traveling Inside a Vehicle
Category
Population Group
N
Mean
Stdev
Stderr
Min
Max
5
25
50
Percentiles
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 minufes 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 Klepeis. 1996.
-------
Table 15-134. Statistics for 24-Hour Cumulative Number of Minutes Spent Outdoors Near a Vehicle
Percentiles
Category
Population Group
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
675
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
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
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
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
240
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
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
DK
23
68.696
91.209
19.0183
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
Stderr
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 minufes 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 Klepeis. 1996.
-------
Table 15-136. Statistics for 24-Hour Cumulative Number of Minutes Spent in an Office or Factory
Percentiles
Category
Population Group
N
Mean
Stdev
Stderr
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. 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 15-137. Statistics for 24-Hour Cumulative Number of Minutes Spent in Malls, Grocery Stores, or Other Stores
Percentiles
Group Name
Group Code
N
Mean
Stdev
Stderr
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 Time
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. 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 15-138. Statistics for 24-Hour Cumulative Number of Minutes Spent in Schools, Churches, Hospitals, and Public Buildings
Percentile
Category
Population Group
N
Mean
Stdev
Stderr
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: Tsana and Kleoeis. 1996.
-------
Table 15-139. Statistics for 24-Hour Cumulative Number of Minutes Spent in Bars/Nightclubs, Bowling Alleys, and Restaurants
Percentiles
Category
Population Group
N
Mean
Stdev
Stderr
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
Hispanic
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 School 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. 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 15-140. Statistics for 24-Hour Cumulative Number of Minutes Spent in Other Outdoors
Such as Auto Repair Shops, Laundromats, Gyms, and at Work (non-specific)
Percentiles
Group Name
Group Code
N
Mean
Stdev
Stderr
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 Kleoeis. 1996.
-------
Table 15-141. Statistics for 24-Hour Cumulative Number of Minutes Spent with Smokers Present
Category
Population Group
N
Mean
Stdev
Stderr
Min
Max
5
25
50
Percentiles
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
9.953
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
9.405
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 minufes 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 Klepeis. 1996.
-------
Table 15-142 Range of Time (minutes) Spent Smoking Based on the Number of Respondents
Number of Minutes
*.*
0-
60
60-
120
120-
180
180-
240
240-
300
300-
360
360-
420
420-
480
480-
540
540-
600
600-
660
9386
5381
628
444
338
285
258
242
236
192
228
186
185
4294
2327
280
184
167
141
119
114
128
92
101
92
89
5088
3053
348
259
171
144
138
128
108
99
127
94
96
4
1
*
1
*
*
1
*
*
1
*
*
*
187
133
10
6
2
3
2
4
3
6
4
3
3
499
344
29
23
14
8
10
7
8
7
8
7
5
703
479
40
38
32
23
10
9
6
12
6
11
6
589
333
75
31
30
20
22
15
13
7
13
5
3
6059
3083
412
305
225
196
195
187
192
143
184
148
154
1349
1009
62
41
35
35
19
20
14
17
13
12
14
7591
4312
496
368
261
233
208
208
186
154
173
160
149
945
550
66
41
37
26
29
18
31
23
33
15
22
157
109
12
3
7
5
3
2
5
3
3
2
1
182
103
10
8
9
5
7
3
2
3
5
4
4
385
220
39
17
21
13
9
9
10
8
12
5
6
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
702
414
48
38
38
16
18
14
21
10
23
11
13
47
29
3
4
2
*
1
*
1
*
1
2
1
103
70
4
6
3
2
1
2
1
1
2
*
3
1773
1149
143
91
74
50
39
29
26
28
27
22
14
4096
2054
286
203
140
141
124
126
134
96
134
109
110
802
421
51
42
36
25
32
27
17
23
28
12
16
2644
1709
145
105
87
67
61
56
58
43
38
43
44
71
48
3
3
1
2
2
4
1
2
1
*
1
1968
1264
153
98
81
56
49
38
30
31
30
27
18
834
457
34
28
23
16
15
23
38
15
20
26
12
2612
1297
160
115
94
86
92
84
69
71
93
64
76
1801
972
114
87
76
62
50
56
49
44
52
35
44
1247
774
88
70
42
38
32
24
32
23
20
22
21
924
617
79
46
22
27
20
17
18
8
13
12
14
2075
1143
150
108
66
73
61
63
54
52
56
40
38
2102
1164
145
110
75
65
69
37
63
42
55
51
41
3243
1834
206
137
116
106
76
92
85
58
87
60
76
1966
1240
127
89
81
41
52
50
34
40
30
35
30
6316
3655
430
301
227
188
164
146
171
127
169
128
116
3070
1726
198
143
111
97
94
96
65
65
59
58
69
2524
1478
180
113
91
81
65
68
53
39
60
48
41
2438
1404
154
120
82
73
73
61
61
50
58
40
61
2536
1477
165
116
88
71
64
64
68
61
52
57
45
1888
1022
129
95
77
60
56
49
54
42
58
41
38
8629
4942
580
419
308
264
237
223
216
175
213
172
173
694
396
42
24
29
20
20
17
20
16
13
13
12
63
43
6
1
1
1
1
2
*
1
2
1
*
9061
5169
610
430
331
273
252
235
233
187
223
184
181
250
63
13
11
5
11
5
5
2
5
4
*
4
75
49
5
3
2
1
1
2
1
*
1
2
*
8882
5133
593
423
311
267
246
224
219
182
215
177
174
433
197
30
20
24
17
11
16
17
10
11
7
11
71
51
5
1
3
1
1
2
*
*
2
2
*
Overall
Gender
Male
Female
Refused
Age (years)
1-4
5-11
12-17
18-64
>64
Race
White
Black
Asian
Some Others
Hispanic
Refused
Hispanic
No
Yes
DK
Refused
Employment
Full Time
Part Time
Not Employed
Refused
Education
< High School
High School Graduate
< College
College Graduate
Post Graduate
Census Region
Northeast
Midwest
South
West
Day of Week
Weekday
Weekend
Season
Winter
Spring
Summer
Fall
Asthma
No
Yes
DK
Angina
No
Yes
DK
Bronchitis/emphysema
No
Yes
DK
-------
Table 15-142 Range of Time (minutes) Spent Smoking Based on the Number of Respondents (continued)
Number of Minutes
660- 720-
720 780
780- 840-
840 900
900-
960
960- 1020-
1020 1080
1080- 1140- 1200-
1140 1200 1260
1260-
1320
1320-
1380
1380-
1440
Overall
Gender
Male
Female
Refused
Age (years)
1-4
5-11
12-17
18-64
>64
Race
White
Black
Asian
Some Others
Hispanic
Refused
Hispanic
No
Yes
DK
Refused
Employment
Full Time
Part Time
Not Employed
Refused
Education
< High School
High School Graduate
< College
College Graduate
Post Graduate
Census Region
Northeast
Midwest
South
West
Day of Week
Weekday
Weekend
Season
Winter
Spring
Summer
Fall
Asthma
No
Yes
DK
Angina
No
Yes
DK
Bronchitis/emphysema
No
Yes
DK
149 135 162 105
66
39
1
3
2
3
91
5
90
9
2
2
2
96
72
6
18
1
10
16
45
18
10
6
23
29
37
16
63
42
26
29
31
19
92
13
103
2
91
14
84
76
87
65
59
75
*
*
*
2
1
1
3
5
6
7
2
5
7
3
5
119
114
129
11
10
16
135
118
139
7
10
8
*
*
2
3
2
6
3
3
6
1
2
1
141
127
149
5
6
11
1
1
*
2
1
2
16
10
16
83
82
82
18
11
16
31
32
48
1
*
*
19
12
18
15
24
34
60
64
62
36
22
29
11
9
12
8
4
7
37
34
34
36
28
36
52
63
60
24
10
32
95
84
103
54
51
59
30
47
46
41
36
44
38
23
45
40
29
27
134
124
150
15
9
11
*
2
1
141
130
157
4
3
4
4
2
1
139
128
150
10
5
12
*
2
*
83
53
48
37
35
17
*
*
.
?
?
3
*
1
1
1
7?
44
8
2
74
49
6
3
*
*
?
*
1
*
*
1
81
5?
?
1
*
*
*
*
27
18
9
2
5
18
2
21
5
25
1
21
14
7
2
2
17
16
2
1
1
1
19
1
12
9
3
11
1
12
12
6
6
3
2
5
2
11
11
1
15
10
5
1
1
2
10
1
14
1
13
1
1
3
5
7
4
3
5
1
*
3
50
34
10
11
5
2
*
2
6
10
2
2
3
*
2
*
1
1
19
12
8
3
4
3
2
3
5
1
*
*
*
*
*
*
*
*
3
7
8
4
3
5
1
.
3
16
7
6
2
1
1
*
2
3
33
17
6
5
5
3
1
2
8
23
12
5
6
3
2
1
2
1
6
8
1
4
*
*
*
*
*
2
2
1
*
*
1
*
*
*
20
10
2
4
2
2
.
1
2
15
13
11
8
1
2
1
1
4
37
21
11
6
7
5
*
4
7
11
9
3
3
2
3
2
*
2
55
38
17
12
8
8
2
1
8
28
15
10
9
4
4
1
5
7
21
11
7
6
4
1
2
1
5
10
14
5
5
4
5
1
2
5
33
13
11
5
2
3
*
2
2
19
15
4
5
2
3
*
1
3
77
47
24
20
9
9
3
5
13
6
5
3
1
3
3
*
1
2
*
1
*
*
*
*
*
*
*
82
48
26
20
12
12
2
5
15
1
4
1
1
*
*
1
1
*
*
1
*
*
*
*
*
*
*
75
48
25
20
11
9
3
4
15
8
4
2
1
1
3
*
2
*
*
1
*
*
*
*
*
*
*
Note: * = Missing Data; DK =Don't know; N = Number of Respondents; Refused
Source: Tsang And Klepeis, 1996.
: Respondent Refused to Answer.
-------
Table 15-143 Number of Minutes Spent Smoking (minutes/day)
Percentiles
Category
Population Group
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
Wnter
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/emphysema
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 Kleoeis. 1996.
-------
Table 15-144 Range of Time Spent Smoking Ciga
rs or
Pipe Tobacco by the Number of Respondents
Total N
Number of Minutes per Dav
...
0-3
3-6
6-9
9-12 12-15 15-18 1
8-61
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.
-------
Table 15-145 Number of Minutes Spent Smoking Cigars 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
10
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
Wnter
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 KleDeis. 1996.
-------
Table 15-146 Range of Numbers of Cigarettes Smoked Based on the Number of Respondents
Total N Number of Cigarettes Smoked by Respondent on the Day Before the Survey
*
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
*
*
*
*
*
*
*
*
Age (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
*
Hispanic
193
37
133
7
5
2
2
7
*
*
*
Refused
60
*
46
*
2
*
2
7
*
3
*
Hispanic
No
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
*
Employment
*
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
37
34
76
108
29
24
4
West
978
115
716
13
18
16
28
56
4
9
3
Day of Week
Weekday
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
*
*
*
Angina
No
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
*
*
*
*
*
*
*
*
*
Age (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
Hispanic
No
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
Employment
*
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
Day of Week
Weekday
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
Angina
No
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
*
*
*
*
*
*
*
*
*
Age (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
3045
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
Employment
*
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
Bronchitis/emphysema
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)a 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)
(ISM 218)
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)
(ISM 17)
(ISM 08)
(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)
(47.4)
(38.5)
a Data weighted to ensure equal days of the week.
Source: Robinson, 1977.
-------
Table 15-150
Time Use (hours/week)a Differences by Age for the Surveys Conducted in 1965 and 1975
Mean Duration (hrs/wk)
Age Group (years)
1£
5-25
25-35
36-45
46-55
56-65
1965
1975
1965
1975
1965
1975
1965
1975
1965
1975
Activity
(N=200)
(ISM 49)
(N=321)
(N=234)
(N=306)
(ISM 50)
(N=252)
(N=141)
(ISM 56)
(ISM 11)
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
Time
168.0
(39.1)
168.0
(50.0)
168.0
(35.6)
168.0
(38.4)
168.0
(33.8)
168.0
(37.3)
168.0
(33.4)
168.0
(35.2)
168.0
(37.1)
168.0
(41.8)
a Data weighted to ensure equal days of the week.
Source: Robinson, 1977.
-------
Table 15-151. Time Use (hours/week)3 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=171)
(N=75)
(N=220)
(ISM 14)
(N=452)
(N=319)
(ISM 95)
(ISM 37)
(ISM91)
(ISM 44)
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
23.5
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)
(40.0)
(47.5)
a Data weighted to ensure equal days of the week.
Source: Robinson, 1977.
-------
Table 15-152.
Time Use (hours/week)a Differences by Race for the Surveys Conducted in 1965 and 1975
Mean duration (hours/weekl
White
Black
1965
1975
1965
1975
(N = 10301
II
O)
00
o
(N = 1031
II
-v|
-sj
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
(34.91
'40.31
(36.8)
(44.61
a Data weighted to ensure equal days of the week.
Source: Robinson. 1977.
-------
Table 15-153. Mean Time Spent (hours/week)81 in Ten Major Activity Categories Grouped by Regions
Total"
N=975
Activity West North Central Northeast South
Mean S.D.C
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.
c 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
[Na = 8311 [N = 8311 [N = 8311
Activity Category
Market Work
288.0 (257.7)b
97.9 (211.9)
58.0 (164.8)
House/Yardwork
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/day) in Ten Maior Activity Categories During Four Waves of Interviews
a
Fall
(Nov. 1, 1975)"
N=861
Wnter
(Feb. 28, 1976)"
Spring
(June 1, 1976)"
N=861
Summer
(Sept. 21, 1976)"
N=861
Range of
Standard
Deviations
Activity Category
Wave 1
Wave 2
Wave 3
Wave 4
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
143-181
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% of the interviews for each wave were taken.
Source: Hill. 1985.
-------
Table 15-156. Mean Time Spent (hours/week) in Ten 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 leisure
22.8 (14.1)
22.7
(12.7)
22.8
(13.3)
Total time
168.1
168.1
168.1
a Detailed components of activities (87) are presented in Table 1A-4.
b () = Numbers in parentheses 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)
n = 211 n = 45
Intermediate Grades
(4-6)
CD
CD
II
C
Residential Yards
143b
124"
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
Natural/Vacant 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
Survey was conducted in Maryvale (West Central Phoenix), Arizona.
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 Individuals3 by Age and Sex
Aae Group (years)
Median Tenure (years)
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: Carey. 1988.
-------
Table 15-159. Occupational Tenure for Employed Individuals3 Grouped by Sex and Race
Median Tenure (Years)
Race All Individuals
Men
Women
White 6.7
8.3
5.4
Black 5.8
5.8
5.8
Hispanic 4.5
5.1
3.7
a Working population = 109.1 million persons.
Source: Carey. 1988.
-------
Table 15-160. Occupational Tenure for Employed Individuals3 Grouped by Sex and Employment Status
Median Tenure (Years)
Employment Status All Individuals
Men
Women
Full-Time 7.2
8.4
5.9
Part-Time 3.1
2.4
3.6
a Working population = 109.9 million persons.
Source: Carey. 1988.
-------
Table 15-161. Occupational Tenure of Employed Individuals3 Grouped by Major Occupational Groups and Age
Occupational Group
Median Tenure (years)
Age Group
—I
0
1 1
Q)_
O"
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
Farming, 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 Workers3 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, age 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: Carey, 1990.
-------
Table 15-163. Values and Their Standard Errors for Average Total Residence Time, T, for Each Group in Survey3
Average total Households (percent)
Households
residence time
T (years)
S.D.St
Average current
residence
Tcr (years)
1985
1987
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
aValues 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)a
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 for t 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
15-19
10.06
20-24
6.69
25-34
8.52
35-44
5.1
45-54
1.9
> 55
0.95
Total3
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
Na = 500,000
N = 244,274
N = 255,726
Statistic
11.7
11.1
12.3
Mean
2
2
2
5th percentile
2
2
2
10th percentile
3
4
5
25th percentile
9
8
9
50th 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 Capel, 1992.
-------
Table 15-168. Descriptive Statistics for Both Genders by Current Age
Residential occupancy period (years)
Current
age, years
Mean
Percentile
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 previous 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)
All Buyers
First-Time
Buyer
Repeat Buyer
New Home
Buyer
Existing Home
Buyer
Miles
Percent
Less than 5 miles
29
33
27
23
31
5 to 9 miles
20
25
16
18
20
10 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
Rating
TIME SPENT INDOORS VS. OUTDOORS
Studv 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
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.
Medium
• Focus on factor of
interest
The study focused on general activity patterns. One study delineated
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.
High
• 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
remaining study was collected to via questionnaires and interviews.
High
• Currency
The studies were published in 1985 (data was collected 1981-1982), 1987,
1991 (data was collected 1987-1990) and 1992.
Medium
• Adequacy of data
collection period
In one study, households were sampled 4 times during 3 month intervals from
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.
High
• Validity of approach
The approach used to collect data was direct and included questionnaires or
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.
High
• Study size
The study sizes ranged from 922 to 5,000 depending on the sub-group
considered.
High
• Representativeness of
the population
Timmer focused on activities of children. Robinson studies activities of both
children and adults. The studies are representative of the US population and
California State.
High
• Characterization of
variability
Variability was characterized by age, gender, and day of the week; location of
activities and various age categories for children. There was no mention of
race and no socio-economic characterizations made.
Medium
• Lack of bias in study
design (high rating is
desirable)
Biases noted were sampled during time when children were in school
(activities during vacation time are not represented); activities in the 1980's
may different than they are now;
Medium
• Measurement error
Measurement or recording error may occur since the diaries were based on
recall (in most cases a 24 hour recall).
Medium
Other Elements
• Number of studies
Two
High
• Agreement between
researchers
Difficult to compare due to varying categories of activities and the unique age
distributions found within each study.
Not
Ranked
Overall Rating
Medium
-------
Table 15-172. Confidence in Activity Patterns Recommendations (continued)
Considerations
Rationale
Rating
TIME SPENT IN A VEHICLE
Studv 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
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.
Medium
• Focus on factor of
interest
The study focused specifically focused on time spent in vehicle.
High
• 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
data.
High
• Currency
The studies were published in 1985 (data was collected 1981-1982), 1987,
1991 (data was collected 1987-1990) and 1992.
Medium
• Adequacy of data
collection period
In one study, households were sampled 4 times during 3 month intervals from
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.
High
• Validity of approach
The approach used to collect primary data was based on diary entries
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.
High
• Study size
The study sizes ranged from 922 to 5,000 depending on the sub-group
considered.
High
• Representativeness of
the population
The studies are representative of the US population and California State.
High
• Characterization of
variability
Variability was characterized by age, gender, and day of the week. There was
no mention of race and no socio-economic characterizations made.
Medium
• Lack of bias in study
design (high rating is
desirable)
Both studies lacked time distributions and were based on short-term data.
Wiley et al. (1991) data was based recall, is limited to California's population,
and only considered English speaking households.
Medium
• Measurement error
Measurement or recording error may occur when diaries were based on 24
hr recall.
Medium
Other Elements
• Number of studies
One secondary study analyzing two primary studies
Medium
• Agreement between
researchers
Similar activity patterns were found in both studies.
High
Overall Rating
Medium
-------
Table 15-172. Confidence in Activity Patterns Recommendations (continued)
Considerations
Rationale
Rating
TIME SPENT SHOWERING
Studv 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
be publicly available.
Low
• Reproducibility
Results are reproducible.
High
• Focus on factor of
interest
The study focused specifically focused on time spent showering.
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
collection period
The data were collected between October 1992 and September 1994.
High
• Validity of approach
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.
High
• Study size
Study consisted of 9,386 total participants..
High
• Representativeness of
the population
The data were representative of the U.S. population.
High
• Characterization of
variability
The study provides a distribution on showering duration.
High
• Lack of bias in study
design (high rating is
desirable)
The study includes distributions for showering duration. Study is based on
short-term data.
High
• Measurement error
Measurement or recording error may occur because diaries are based on 24-
hour recall.
Medium
Other Elements
• Number of studies
One; the study was a national study.
Low
• Agreement between
researchers
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
Overall Rating
High
-------
Table 15-172. Confidence in Activity Patterns Recommendations (continued)
Considerations
Rationale
Rating
TIME SPENT BATHING
Studv 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
be publicly available.
Low
• Reproducibility
Results can be reproduced or methodology can be followed and evaluated
provided comparable economic and social conditions exists.
High
• Focus on factor of
interest
The survey collected information on duration and frequency of selected
activities and time spent in selected micro-environments.
High
• 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
collection period
The data were collected between October 1992 and September 1994.
High
• Validity of approach
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.
High
• Study size
The study consisted of 9,386 total participants.
High
• Representativeness of
the population
The studies were based on the U.S. population.
High
• Characterization of
variability
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..
High
• Lack of bias in study
design (high rating is
desirable)
The study includes distributions for bathing duration. Study is based on
short-term data.
Medium
• Measurement error
Measurement or recording error may occur because diaries were based on
24-hour recall.
Medium
Other Elements
• Number of studies
One; the study was based on one, primary, national study.
Low
• Agreement between
researchers
Recommendation was based on only one study.
Not
Ranked
Overall Rating
High
-------
Table 15-172. Confidence in Activity Patterns Recommendations (continued)
Considerations
Rationale
Rating
SHOWER AND BATHING FREQUENCY
Studv 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
publicly available.
Low
• Reproducibility
Results can be reproduced or methodology can be followed and evaluated
provided comparable economic and social conditions exists.
High
• Focus on factor of
interest
The survey collected information on duration and frequency of selected
activities and time spent in selected micro-environments.
High
• 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
collection period
The data were collected between October 1992 and September 1994.
High
• Validity of approach
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.
High
• Study size
The study consisted of 9,386 total participants
High
• Representativeness of
the population
Studies were based on the U.S. population.
High
• Characterization of
variability
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..
High
• Lack of bias in study
design (high rating is
desirable)
Study is based on short term data..
Medium
• Measurement error
Measurement or recording error may occur because diaries were based on
24-hour recall.
Medium
Other Elements
• Number of studies
One; the study was based on one, primary, national study.
Low
• Agreement between
researchers
Recommendation was based on only one study.
Not
Ranked
Overall Rating
High
-------
Table 15-172. Confidence in Activity Patterns Recommendations (continued)
Considerations
Rationale
Rating
TIME SPENT SWIMMING
Studv Elements
• Level of peer review
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
publicly available.
Low
• Reproducibility
Results can be reproduced or methodology can be followed and evaluated
provided comparable economic and social conditions exists.
High
• Focus on factor of
interest
The survey collected information on duration and frequency of selected
activities and time spent in selected micro-environments.
High
• 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
collection period
The data were collected between October 1992 and September 1994.
High
• Validity of approach
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.
High
• Study size
The study consisted of 9,386 total participants
High
• Representativeness of
the population
Studies were based on the U.S. population.
High
• Characterization of
variability
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..
High
• Lack of bias in study
design (high rating is
desirable)
The study includes distributions for swimming duration. Study is based on
short term data.
Medium
• Measurement error
Measurement or recording error may occur because diaries were based on
24-hour recall.
Medium
Other Elements
• Number of studies
One; the study was based on one, primary, national study.
Low
• Agreement between
researchers
Recommendation was based on only one study.
Not
Ranked
Overall Rating
High
-------
Table 15-172. Confidence in Activity Patterns Recommendations (continued)
Considerations
Rationale
Rating
RESIDENTIAL TIME SPENT INDOORS AND OUTDOORS
Studv 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
publicly available.
Low
• Reproducibility
Results can be reproduced or methodology can be followed and evaluated
provided comparable economic and social conditions exists.
High
• Focus on factor of
interest
The survey collected information on duration and frequency of selected
activities and time spent in selected micro-environments.
High
• 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
collection period
Data were collected between October 1992 and September 1994.
High
• Validity of approach
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.
High
• Study size
The study consisted of 9,386 total participants
High
• Representativeness of
the population
The studies were based on the U.S. population.
High
• Characterization of
variability
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..
High
• Lack of bias in study
design (high rating is
desirable)
The study includes distribitions for time spent indoors and outdoors at ones
residence. Study is based on short term data.
Medium
• Measurement error
Measurement or recording error may occur because diaries were based on
24-hour recall.
Medium
Other Elements
• Number of studies
One; the study was based on one, primary, national study.
Low
• Agreement between
researchers
Recommendation was based on only one study.
Not
Ranked
Overall Rating
High
-------
Table 15-173. Confidence in Occupational Mobility Recommendations
Considerations
Rationale
Rating
Studv 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
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.
Medium
• Focus on factor of
interest
Occupational tenure was the focus of both key studies.
High
• 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
supplemental data to the January 1987 Current Population Study (a U.S.
Census publication).
Medium
• Currency
The studies were published in 1988 (data was collection in 1987) and 1990
(data collected from 1986-1987).
Medium
• Adequacy of data
collection period
The studies are based on census data, which is collected over a period of
years. One study analyzed data for January 1987. The remaining study
based data between a January 1986 and January 1987 time frame.
High
• 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
100.1 Million.
High
• Representativeness of
the population
The data are representative of the U.S. population.
High
• Characterization of
variability
The studies provided averaged data according to gender, race, and
education; age averages and percentiles were provided.
High
• Lack of bias in study
design (high rating is
desirable)
Much of the original study data is not available. Only median values are
reported.
Medium
• Measurement error
There is no apparent error in measurement
High
Other Elements
• Number of studies
Two
Medium
• Agreement between
researchers
Difficult to compare between the number of years worked on a job and entry
verses exit rate of various occupations. One set of data was recorded in
number of years. The other set of data was recorded as a percent motility
rate and grouped by age.
Not
Ranked
Overall Rating
High
-------
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
(70yr) = 11.7 (modeled)
US Bureau of the Census, 1993
9 yr (50th percentile)
Current residence time
33 yr (90th percentile)
Johnson and Capel, 1992
26 yr (90th percentile)
Residential occupancy period
33 yr (95th percentile)
47 yr (99th percentile)
12 vr (mean)
-------
Table 15-175. Confidence in Population Mobility Recommendations
Considerations
Rationale
Rating
Studv Elements
• Level of peer review
The studies received high levels of peer review and appear in publications.
High
• Accessibility
The studies are widely available to the public.
High
• Reproducibility
Results can be reproduced or methodology can be followed and evaluated.
High
• Focus on factor of
The Census data provided length of time at current. Two of the studies used
Medium
interest
modeling to estimate total time.
• Data pertinent to US
The data is based on the U.S. population
High
• Primary data
Two studies based results on modeled data and one based results on
interviews.
Medium
• Currency
The reports were published in 1992 (based on data collected in 1985-1987)
and 1993 (based on data collected from 1939 and 1994 (projected).
Medium
• Adequacy of data
The collection period was based on data collected over several years.
High
collection period
• Validity of approach
There are some concerns regarding the validity of approach. Data does not
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 90th percentiles.
Medium
• Study size
The study size ranged from 15,000 to 500, 000.
High
• Representativeness of
Studies were based on the U.S. population.
High
the population
• Characterization of
Variability across several geographic regions was noted. Type of ownership
Medium
variability
was also addressed. One study provided data grouped by race.
• Lack of bias in study
Mentioned above in validity of approach section.
Not
design (high rating is
Ranked
desirable)
• Measurement error
There is no apparent error in measurement.
High
Other Elements
• Number of studies
Three
High
• Agreement between
The studies produced very similar results.
High
researchers
Overall Rating
Medium
-------
Table 15-176. Summary of Recommended Values for Activity Factors
Type
Value
Study
Indoor Activities
Children (aaes 3-11)
19 hr/day (weekdays)
17 hr/day (weekends)
Adults (ages 12 and older)
21 hr/day
Timmer et al.. 1985 -Key study
Timmer et al.. 1985 -Key study
Robinson and Thomas. 1991 - Key
study
Outdoor Activities
Children
5 hr/day (weekdays)
7 hr/day (weekends)
Adults
1.5 hr/day
Timmer et al.. 1985 -Key study
Timmer et al.. 1985 -Key study
Robinson and Thomas. 1991 - Key
study
Time Spent Inside
Vehicle
Adults
1.3 hr/day
Robinson and Thomas. 1991 - Key
study
Tsang and Klepeis. 1996 - Key study
Taking Baths
20 minutes/event
Tsang and Klepeis. 1996 - Key study
Taking Showers
10 min/day shower duration
Tsang and Klepeis. 1996 - Key study
1 shower event/day
Tsang and Klepeis. 1996 - Key study
Occupational Tenure
6.6 yrs (16 years and older)
Carey. 1988 - Key study
Population Mobility
Average: 9 yr
95th percentile: 30 yr
US Bureau of the Census. 1993:
Israeli and Nelson. 1992: Johnson
and Capel. 1992 - Key study
Swimming
1 event/month
60 minutes/event
Tsang and Klepeis. 1996 - Key study
Residential
Indoors
Outdoors
16.4 hr/day
Tsang and Klepeis. 1996 - Key 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; looking 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
Indoor
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." NAif indoor 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)
-------
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)
-------
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 for related 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
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
65 - 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,
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)
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/Familv Organizations: PTA, PTO; Boy/Girl Scouts; Little Leagues; YMCA/YWCA; school
volunteer
67 - Meetings, family organizations; attending meetings of child/youth/fa mi ly*-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)
Other 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
74 - 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 (repairing 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)
Nonsocial dancing (ballet, modern dance, body movement)
Gymnastics (lessons - code 88)
Games
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
Travel
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 move
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 (just 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.
-------
00-
00-
00
01
02
03
04
05
06
07
08
09
10-
10
11
12
13
14
15
16
17
18
19
20-
20
21
22
23
24
25
26
27
28
29
Table 15A-2. Differences in Average Time Spent in Different Activities Between California
and National Studies (minutes per day forage 18-64 years)
NON-FREE TIME
California National
1987-88 1985
C13591 C19801
50-59
Free Time
California National
1987-88 1985
C13591 C19801
PAID WORK
(not used)
Main Job
Unemployment
Travel during work
(not used)
Second job
Eating
Before/after work
Breaks
Travel to/from work
224
1
3
6
1
2
28
211
1
NR
2
2
25
50-99 EDUCATION AND TRAINING
50 Students' Classes
51 Other Classes
52 (not used)
53 (not used)
54 Homework
55 Library
56 Other Education
57 (not used)
58 (not used)
5 9 Travel. Education
HOUSEHOLD WORK
Food Preparation
Meal Cleanup
Cleaning House
Outdoor Cleaning
Clothes Care
Car Repair/Maintenance
R)
Other Repairs (by R)
Plant Care
Animal Care
Other Household
(by
29
10
21
9
7
5
8
3
3
7
36
11
24
7
11
5
6
5
5
60-69 ORGANIZATIONAL ACTIVITIES
60 Professional/Union 0
61 Special Interest *
62 Political/Civic 0
63 Volunteer/Helping 1
64 Religious Groups 1
65 Religious Practice 5
66 Fraternal 0
67 Child/Youth/Family 1
68 Other Organizations 2
6 9 Travel Organizations 2_
CHILD CARE
Baby Care
Child Care
Helping/Teaching
Talking/Reading
Indoor Playing
Outdoor Playing
Medical care - Care
Other Child Care
(At Dry Cleaners)
Travel. Child care
5
1
1
3
1
1
1
NR
4
70-79
70
71
72
73
74
75
76
77
78
7 9
ENTERTAINMENT/ SOCIAL ACTIVITIES
Sports Events
Entertainment Events
Movies
Theatre
Museums
Visiting
Parties
Bars/Lounges
Other Social
Travel. Events/Social
2
5
2
1
1
26
6
4
13
2
1
3
1
25
7
6
1
16
-------
Table 15A-2. Differences in Average Time Spent in Different Activities Between California
and National Studies (minutes per day for age 18-64 years) (continued)
00-49
NON-FREE TIME
California
1987-88
(1359)
National
1985
(1980)
50-59
Free Time
California
1987-88
(1359)
National
1985
(1980)
30-39
OBTAINING GOODS AND
SERVICES
80-89
RECREATION
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
CARE
90-99
COMMUNICATION
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
Survey
Total Travel
108
90
* =
Less than 0.5 Min. per day
(Codes 09, 29, 39, 49, 59,
69. 79. 89. 99)
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, Spa
1
NR
1
NR"
1
NR"
Yard
33
21
27
37
Room to Room
9
160c
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 awav
—
from home
487
445
371
324
430
383
-------
Table 15A-3. Time Spent in Various Microenvironments (continued)
Mean duration
Women
Men
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
-
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
1
8
4
7
2
9
Total Time Outdoors - - - - 88 70
a Totals do not necessarily reflect exact averages presented for each gender. Totals were revised, but revisions for each gender were
not provided.
b NR = Not Reported
c Is total mean duration for those categories; breakdowns per category were not reported.
Source: Robinson and Thomas, 1991.
National California
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 Categories3
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 Day of the Week
Weekday Saturday Sunday
N=831 N=831 N=831
Activity
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-Coffee 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-Outdoor 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-Other 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/Talking
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-Outdoor 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-Other 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-Other Classes
2.65
17.92
0.40
11.52
0.27
5.63
-------
Table 15A-5. Mean Time Spent (minutes/day) for 87 Activities Grouped by Day of the Week
(continued)
Weekday
N=831
Saturday
N=831
Sunday
N=831
Activity
Mean
Std. Dev.
Mean
Std. Dev.
Mean
Std. Dev.
54-Homework
4.56
24.35
3.48
27.98
5.40
38.68
56-Other 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-Identity 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-Fraternal 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-Other 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-Other 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-Outdoors
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/N.A.
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-Other 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
Activity
Men
N=410
Mean Std. dev.
Women
N=561
Mean
Std. dev.
Men and women
N=971
Mean
Std. dev.
01 - Normal work
02 - Unemployment acts
05 - Second job
06 - Lunch at work
07 - Before/after work
08 - Coffee breaks
09 - Travel: to/from work
29.78
0.14
0.73
1.08
0.51
0.57
2.98
20.41
1.06
3.20
1.43
1.27
1.05
2.87
14.99
0.08
0.17
0.65
0.23
0.36
1.45
17.62
0.75
1.62
1.21
0.69
1.03
2.17
21.82
0.11
0.43
0.85
0.36
0.46
2.16
20.33
0.90
2.49
1.33
1.01
1.04
2.63
10 - Meal preparation
11 - Meal cleanup
12 - Indoor cleaning
13 - Outdoor cleaning
14 - Laundry
16 - Repairs/maintenance
17 - Gardening/pet care
19 - Other household
1.57
0.33
0.85
1.59
0.13
2.14
0.94
0.92
2.61
0.83
2.01
3.59
0.72
4.29
2.78
2.42
7.25
2.30
5.03
0.56
2.44
0.68
1.00
0.72
5.04
2.19
5.05
1.59
3.34
3.43
2.19
1.84
4.63
1.39
3.10
1.03
1.38
1.35
0.97
0.81
4.98
1.97
4.46
2.75
2.75
3.92
2.48
2.13
20 - Baby care
21 - Child care
22 - Helping/teaching
23 - Reading/talking
24 - Indoor playing
25 - Outdoor playing
26 - Medical care - child
27 - Babysitting/other
29 - Travel: child care
0.24
0.24
0.07
0.07
0.13
0.06
0.01
0.14
0.23
1.20
0.78
0.61
0.35
0.69
0.37
0.09
0.78
0.67
0.90
0.99
0.15
0.30
0.18
0.12
0.09
0.64
0.50
3.04
2.11
0.76
0.86
0.82
0.72
0.67
2.58
1.21
0.60
0.64
0.11
0.19
0.16
0.09
0.05
0.41
0.38
2.40
1.68
0.70
0.68
0.76
0.58
0.50
1.98
1.00
30 - Everyday shopping
31 - Durables/house shopping
32 - Personal care services
33 - Medical appointments
34 - Govt/financial services
35 - Repair services
37 - Other services
38 - Errands
39 - Travel: goods/services
1.45
0.19
0.06
0.15
0.15
0.11
0.11
0.04
1.60
2.18
1.39
0.42
0.75
0.44
0.45
0.61
0.41
2.02
2.78
0.08
0.35
0.37
0.19
0.17
0.13
0.06
2.14
3.25
0.51
1.14
1.63
0.61
0.78
0.61
0.68
2.17
2.17
0.13
0.22
0.27
0.17
0.14
0.12
0.05
1.89
2.89
1.01
0.90
1.31
0.54
0.65
0.61
0.57
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
Activity
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
0.22
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=
CD
-v]
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 magazines/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
Median years of
Occupation
occupational tenure
Barbers
24.8
Farmers, except horticultural
21.1
Railroad conductors and yardmasters
18.4
Clergy
15.8
Dentists
15.7
Telephone line installers and repairers
15.0
Millwrights
14.8
Locomotive operating occupations
14.8
Managers; farmers, except horticultural
14.4
Telephone installers and repairers
14.3
Airplane pilots and navigators
14.0
Supervisors: police and detectives
13.8
Grader, dozer, and scraper operators
13.3
Tailors
13.3
Civil engineers
13.0
Crane and tower operators
12.9
Supervisors, n.e.c.
12.9
Teachers, secondary school
12.5
Teachers, elementary school
12.4
Dental laboratory and medical applicance technicians
12.3
Separating, filtering, and clarifying machine oeprators
12.1
Tool and die makers
12.0
Lathe and turning machine operators
11.9
Machinists
11.9
Pharmacists
11.8
Stationary engineers
11.7
Mechanical engineers
11.4
Chemists, except biochemists
11.1
Inspectors, testers, and graders
11.0
Electricians
11.0
Operating engineers
11.0
Radiologic technicians
10.9
Electrical power installers and repairers
10.8
Supervisors; mechanics and repairers
10.7
Heavy equipment mechanics
10.7
Bus, truck, and stationary engine mechanics
10.7
Physicians
10.7
Construction inspectors
10.7
Cabinet makers and bench carpenters
10.6
Industrial machinery repairers
10.6
Automobile body and related repairers
10.4
(Continued on the following page)
-------
Table 15A-7. Ranking of Occupations by Median Years of Occupational Tenure (continued)
Median years of
Occupation
occupational tenure
Electrical and electronic engineers
10.4
Plumbers, pipefitters, and steamfitters
10.4
Licensed practical nurses
10.3
Brickmasons and stonemasons
10.2
Truck drivers, heavy
10.1
Tile setters, hard and soft
10.1
Lawyers
10.1
Supervisors: production occupations
10.1
Administrators, education and related fields
10.1
Engineers, n.e.c.
10.0
Excavating and loading machine operators
10.0
Firefighting occupations
10.0
Aircraft engine mechanics
10.0
Police and detectives, public service
9.7
Counselors, educational and vocational
9.7
Architects
9.6
Stuctural metal workers
9.6
Aerospace engineers
9.6
Miscellaneous aterial moving equipment operators
9.4
Dental hygienists
9.4
Automobile mechanics
9.3
Registered nurses
9.3
Speech therapists
9.3
Binding and twisting machine operators
9.3
Managers and administrators, n.e.c.
9.1
Personnel and labor relations managers
9.0
Office machine repairer
9.0
Electronic repairers, commercial and industrial equipment
9.0
Welders and cutters
9.0
Punching and stamping press machine operators
9.0
Sheet metal workers
8.9
Administrators and officials, public administraion
8.9
Hairdressers and cosmetologists
8.9
Industrial engineers
8.9
Librarians
8.8
Inspectors and compliance officers, except construction
8.8
Upholsterers
8.6
Payroll and timekeeping clerks
8.6
Furnace, kiln, and oven operators, except food
8.6
Surveying and mapping technicians
8.6
Chemical engineers
8.6
(continued on the following page)
-------
Table 15A-7. Ranking of Occupations by Median Years of Occupational Tenure (continued)
Median years of
Occupation occupational tenure
Sheriffs, bailiffs, and other law enforcement officers
8.6
Concrete and terrazzo finishers
8.6
Sales representatives, mining, manufacturing, and wholesale
8.6
Supervisors: general office
8.6
Specified mechanics and repairers, n.e.c.
8.5
Stenographers
8.5
Typesetters and compositors
8.5
Financial managers
8.4
Psychologists
8.4
Teachers: special education
8.4
Statistical clerks
8.3
Designers
8.3
Water and Sewage Treatment plant operators
8.3
Printing machine operators
8.2
Heating, air conditioning, and refrigeration mechanics
8.1
Supervisors; distribution, scheduling, and adjusting clerks
8.1
Insurance sales occupations
8.1
Carpenters
8.0
Public transportation attendants
8.0
Drafting occupations
8.0
Butchers and meatcutters
8.0
Miscellaneous electrical and electronic equipment repairers
7.9
Dressmakers
7.9
Musicians and composers
7.9
Supervisors and proprietors; sales occupations
7.9
Painters, Sculptors, craft-artists, and artist printmakers
7.9
Mechanics and repairers, not specified
7.7
Engineering technicians, n.e.c.
7.7
Clinical laboratory technologists and technicians
7.7
Purchasing managers
7.7
Purchasing agents and buyers, n.e.c.
7.7
Photographers
7.6
Chemical technicians
7.6
Managers; properties and real estate
7.6
Accountants and auditors
7.6
Religious workers, n.e.c.
7.6
Secretaries
7.5
Social workers
7.5
Operations and systems researchers and analysts
7.4
Postal clerks, except mail carriers
7.4
Managers; marketing, advertising, and public relations
7.3
(continued on the following page)
-------
Table 15A-7. Ranking of Occupations by Median Years of Occupational Tenure (continued)
Median years of
Occupation occupational tenure
Farm workers
7.3
Managers; medicine and health
7.2
Data processing equipment repairers
7.2
Bookkeepers, accounting and auditing clerks
7.1
Grinding, abrading, buffing, and polishing machine operators
7.0
Management related occupations, n.e.c.
7.0
Supervisors; cleaning and building service workers
7.0
Management analysts
7.0
Science technicians, n.e.c.
7.0
Mail carriers, postal service
7.0
Knitting, looping, taping, and weaving machine operators
6.9
Electrical and electronic technicians
6.9
Painting and paint spraying machine operators
6.9
Postsecondary teachers, subject not specified
6.8
Crossing guards
6.8
Inhalation therapists
6.7
Carpet installers
6.7
Computer systems analysts and scientists
6.6
Other financial officers
6.6
Industrial truck and tractor equipment operators
6.6
Textile sewing machine operators
6.6
Correctional institution officers
6.5
Teachers, prekindergarten and kindergarten
6.4
Supervisors; financial records processing
6.4
Miscellaneous Textile machine operators
6.4
Production inspectors, checkers, and examiners
6.3
Actors and directors
6.3
Health technologists and technicians, n.e.c.
6.3
Miscellaneous machine operators, n.e.c.
6.2
Private household cleaners, and servants
6.2
Buyers, wholesale and retail trade, excluding farm products
6.0
Real estate sales occupations
6.0
Electrical and electronic equipment assemblers
6.0
Bus drivers
6.0
Editors and reporters
6.0
Laundering and dry cleaning machine operators
6.0
Meter readers
5.9
Painters, construction and maintenance
5.9
Driver-sales workers
5.9
Teachers, n.e.c.
5.9
Order clerks
5.8
Physicians' assistants
5.8
(continued on the following page)
-------
Table 15A-7. Ranking of Occupations by Median Years of Occupational Tenure (continued)
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)
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
-------
Table 15A-7. Ranking of Occupations by Median Years of Occupational Tenure (continued)
Median years of
Occupation occupational tenure
Traffic, shipping, and receiving clerks
4.5
Salesworkers, hardware and building supplies
4.5
Biological technicians
4.4
Athletes
4.4
Bill and account collectors
4.4
Taxicab drivers and chauffeurs
4.4
Slicing and cutting machine operators
4.3
Administrative support occupations, n.e.c.
4.3
Mixing and blending machine operators
4.3
Waiters and waitresses
4.2
Janitors and cleaners
4.2
Production helpers
4.1
General office clerks
4.0
Machine feeders and offbearers
3.9
Interviewers
3.9
Bartenders
3.9
Eligibility clerks, social welfare
3.9
Bank tellers
3.8
Cooks, except short-order
3.8
Health aides, except nursing
3.7
Laborers, except construction
3.7
Welfare service aides
3.7
Salesworkers, motor vehicles and boats
3.7
Cost and rate clerks
3.6
Construction laborers
3.6
Hand packers and packagers
3.5
Transportation ticket and reservation agents
3.5
Animal caretakers, except farm
3.5
Photographic process machine operators
3.5
Freight, stock, and material movers, hand, n.e.c.
3.4
Data-entry keyers
3.4
Bakers
3.4
Dispatchers
3.3
Guards and police, except public service
3.3
Packaging and filling machine operators
3.3
Receptionists
3.3
Library clerks
3.3
Truckdrivers, light
3.2
Salesworkers, radio, television, hi-fi, and appliances
3.2
Salesworkers, apparel
3.1
Sales counter clerks
3.1
Salesworkers, other commodities
3.1
(continued on the following page)
-------
Table 15A-7. Ranking of Occupations by Median Years of Occupational Tenure (continued)
Median years of
Occupation occupational tenure
Small engine repairers
3.1
Supervisors, food preparation and service occupations
3.0
Health record technologists and technicians
2.9
Helpers, construction trades
2.9
Attendants, amusement and recreation facilities
2.8
Street and door-to-door salesworkers
2.7
Child-care workers, private household
2.7
Child-care workers, except private household
2.7
Information clerks, n.e.c.
2.7
Hotel clerks
2.7
Personal service occupations, n.e.c.
2.7
Salesworkers, shoes
2.6
Garage and service station related occupations
2.6
Short-order cooks
2.5
File clerks
2.5
Cashiers
2.4
Mail clerks, except postal service
2.3
Miscellaneous food preparation occupations
2.3
News vendors
2.3
Vehicle washers and equipment cleaners
2.3
Messengers
2.3
Kitchen workers, food preparation
2.1
Stock handlers and baggers
1.9
Waiters and waitresses assistants
1.7
Food counter, fountain, and related occupations
1.5
a n.e.c. - not elsewhere classified
Source: Carey, 1988.
-------
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
1.6
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 15B-2. Mobility of the Resident Population by State: 1980
Percent distribution -
residence in 1975a
Persons
Same
5 years
house
old, and
in
Different
Different
Different
ovei^
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 15B-2. Mobility of the Resident Population by State: 1980 (continued)
Percent distribution -
residence in 1975a
Persons
Same
5 years
house
old, and
in
Different
Different
Different
ovei^
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 15B-2. Mobility of the Resident Population by State: 1980 (continued)
Percent distribution -
residence in 1975a
Persons
Same
5 years
house
old, and
in
Different
Different
Different
overb
1980
house,
county,
county,
Region, division,
1980
as
same
same
different
and state
(1,000)
1975
county
state
state
Pacific
29,493
44.2
29.4
11.6
10.7
Washington
3,825
43.7
27.7
10.1
16.2
Oregon
2,437
41.4
26.6
13.4
16.9
California
21,980
44.6
30.2
12.1
8.5
Alaska
363
32.2
27.6
8.7
29.1
Hawaii
888
49.3
25.2
2.8
16.9
a 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.
-------
Different State
16.8%
Different County
Same State v
18.5%
Abroad
' 2.9%
Local Movers, Within
Same County
61.95%
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, I.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-
91-011B. 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.
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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
Showering (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) (minutes/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]
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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
Fill 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, 10kb]
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 [WK1, 12 kb]
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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 [WK1, 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-up/Van) [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 [WK1, 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]
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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) [WK1, 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]
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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
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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
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Volume III - Activity Factors
Chapter 16 - Consumer Products
16. CONSUMER PRODUCTS
16.1. 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 and 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
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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 (RDD) 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
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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 substantially.
• 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, and 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 RDD technique.
Exposure Factors Handbook
August 1997
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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
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Volume III - Activity Factors
Chapter 16 - Consumer Products
The survey data are presented in Tables 16-12 through 16-16. Table 16-12 presents
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 one-
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
conducted 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 RDD 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 Household 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. Seven-
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
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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 RDD procedure (Waksberg Method) previously
described in Westat (1987a) was used to generate sample blocks of telephone numbers
in this survey. Questions were asked on 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 of the
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
RDD. 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
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Volume III - 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-related
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, data 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).
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August 1997
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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" and "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
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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 that if 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
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Table 16-1. Consumer Products Found in the Typical U.S. Household®
Consumer Product Category
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 diauidl
-------
Table 16-1. Consumer Products Found in the Typical U.S. Household® (continued)
Consumer Product Category
Consumer Product
Household Maintenance Products
(continued)
Home Building/Improvement Products (DIY)b
Fabric rinse/softener (powder)
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 pump)
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)
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 ffoaml
-------
Table 16-1. Consumer Products Found in the Typical U.S. Household® (continued)
Consumer Product Category
Consumer Product
Home Building/Improvement Products (DIY)b
(Continued)
Paint/varnish removers
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 polish/wax
Fuel/lubricant additives
Gasoline/diesel fuel
Interior upholstery/components, synthetic
Motor oil
Radiator flush/cleaner
Automotive touch-up paint (aerosol)
Wndshield 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. Frequency of Use for Household Solvent Products (users-only)
Products
Mean
Std. dev.
Min.
1
5
Percentile Rankings for Frequency of Use/Year
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
150.00
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 TVs, 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
1.00
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
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Table 16-3.
Exposure
Time of Use for Household Solvent Products (users-only)
Percentile Rankings for Duration of Use (minutes)
Mean
Std.
Products
(minsl
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
15.00
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
120.00
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
-------
Table 16-4.
Amount of Products Used for Household Solvent Products (users-only)
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
44.95
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)
Products
Mean
(mins)
Std.
dev.
Min.
1
Percentile Rankings for Time Exposed After Duration of Use (minutes)
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 Frostings, 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
Carburetor 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: Westat. 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"
Using"
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
1 st 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
75th Percentile
2.00
240.00
0.00
420.00
96.00
64.00
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
a 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 Usage by Gender
Gender
Male
N=25
Female
N=33
Mean number of months since last time adhesive remover was used - includes all
respondents. (Unweighted N=240)
35.33
43.89
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
recent users)
19.76
0
Mean number of minutes spent in the room after last use of product. (Includes only
those who did not leave immediately)
143.37
0
Mean ounces of product used in the past year.
70.48
139.71
Mean ounces of product used per use in the past year.
48.70
130.36
Source: Abt, 1992.
-------
Table 16-8. Frequency of Use and Amount of Product Used for Spray Paint
No. of Times
Minutes in
Amount Used in
Used Within the
Minutes
Minutes in Room
Room After
Past Year
Amount per
Last 12 Months
Using
After Using"
Using"
(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
Standard 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
1 st 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
10th 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
90th 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
a 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. Spray Paint Usage by Gender
Gender
Male
N=405
Female
N=386
Mean number of months since last time spray paint was used - includes all
respondents. (Unweighted N=1724)
17.39
26.46
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
recent users)
5.49
0.40
Mean number of minutes spent in the room after last use of product. (Includes only
those who did not leave immediately)
67.76
34.69
Mean ounces of product used in the past year.
103.07
59.99
Mean ounces of product used per use in the past year.
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"
Using"
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
1 st 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
10th 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
90th 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
a 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 16-11. Paint Stripper Usage by Gender
Gender
Male
N=156
Female
N=162
Mean number of months since last time paint stripper was used - includes all
respondents. (Unweighted N=1724)
32.07
47.63
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
recent users)
15.07
9.80
Mean number of minutes spent in the room after last use of product. (Includes only
those who did not leave immediately)
101.42
80.15
Mean ounces of product used in the past year.
160.27
114.05
Mean ounces of product used per use in the past year.
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 (hrs/vearl (hrs/vearl
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
Liquid
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 Cleaning Products
(continued)
Mean
Median
Product Type
Percent of
Tasks (hrs/vearl
(hrs/vearl
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 Exposu
re 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
Walls
208
52
36
26
8.67
3
1
0.17
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
Appliances
365
95.29
91.25
30.42
13
4.33
1.81
0.1
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 Rankings
or Frequency of Performing Household Tasks
Percentile Rankings
Tasks
Mean
0th
10th
25th
50th
75th
90th
95th
100th
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
kitchen
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
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
kitchen
2 x/day
0 x/day
0.4 x/day
1 x/day
1 x/day
3 x/day
4 x/day
6 x/day
16 x/day
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
walls
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
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
and tables
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
Clean outside of refrigerator and other
appliances
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
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
Mean
(minutes/event)
Percentile Rankings (minutes/event)
Tasks
0th
10th
25th
50th
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
kitchen
137
5
24
44
120
180
240
360
2,880
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
tables
24
1
5
10
15
30
60
60
180
Clean outside of refrigerator and other
appliances
19
1
4
5
10
20
30
45
240
Clean spots or dirt on walls or doors
50
1
5
10
20
60
120
216
960
Source: Westat, 1987b.
-------
Table 16-16. Total Exposure Time for Ten Product Groups Most Frequently Used for Household Cleaning
Mean
Percentile Rankings of Total Exposure Time
Products
(hrs/yr)
0th
10th
25th
50th
75th
90th
95th
100th
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 PurDose 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)
Types of Paint
Mean
(hrs)
Std. dev.
Min.
Percentile Rankings for Duration of Painting Activity
(hrs)
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.
-------
Table 16-18. Exposure Time of Interior Painting Activity/Occasion (hours) and Frequency of Occasions 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
Types of Paint
Median
(gallons)
Mean
(gallons)
Std.
dev.
Min
10
25
(gallons)
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
Varnishes
Source: Westat, 1987c.
-------
Table 16-20. Number of Respondents Using Cologne, Perfume, Aftershave or Other Fragrances at Specified Daily Frequencies
Number of Times Used in a Day
Population Group
Total N
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
*
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
*
Season
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
*
*
*
DK
8
8
*
*
*
*
Note: * = Missing Data; DK = Don't Know; Refused = Respondents Refused to Answer; N = Number of Respondents.
Source: Tsang and Klepeis. 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 Day
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
Employment
0
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 Region
Northeast
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
Day of Week
Weekday
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
Angina
No
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: Tsang 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
0
0
1
2
15
60
121
121
121
121
121
121
Gender
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
0
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
Wnter
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: Tsanq and Klepeis. 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)
Category
Population Group
Percentiles
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
0
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
Wnter
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
30
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: Tsanq and Klepeis. 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
Census 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
Wnter
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
percentage of doers below or equal to a given number of minutes.
Source: Tsanq and Kleceis, 1996.
= doer sample size; percentiles are the
-------
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
Wnter
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: Tsanq and Klepeis. 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
Wnter
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: Tsanq and Klepeis. 1996.
-------
Table 16-27. Number of Minutes Spent in Activities Working with or Near Stain or Spot Removers (minutes/day)
Percentiles
Category
Population 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
Wnter
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
percentage of doers below or equal to a given number of minutes.
Source: Tsanq and Kleceis, 1996.
= doer sample size; percentiles are the
-------
Table 16-28. Number of Minutes Spent in Activities Working with or Near Gasoline or
Diesel-powered Equipment, Besides Automobiles (minutes/day)
Category
Population Group
Percentiles
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
Wnter
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
percentage of doers below or equal to a given number of minutes.
Source: Tsanq and Klepeis. 1996.
-------
Table 16-29. Number of Minutes Spent Using Any Microwave Oven (minutes/day)
Percentiles
Cateqorv
Poculation Grouc
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
1
1
2
5
10
15
20
30
30
Age (years)
12-17
141
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
3
5
10
30
30
50
50
50
Race
Hispanic
74
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
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
1.5
3
5
10
20
33
60
121
121
Education
High School Graduate
717
0
0
1
2
3
5
10
20
30
45
60
121
Education
< College
518
0
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
0
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
Wnter
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
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
percentage of doers below or equal to a given number of minutes.
Source: Tsanq and Kleceis, 1996.
= doer sample size; percentiles are the
-------
Table 16-30.
Number of Respondents Using a Humidifier at Home
Frequency
Almost
Every
3-5 Times a
1-2 Times a
1-2 Times a
DK
i otai n
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
*
Age (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
Hispanic
No
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 Region
Northeast
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
Day of Week
Weekday
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
*
Angina
No
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: Tsanq and Kleceis, 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 Freq
uencies
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
*
*
*
*
*
Age (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
*
Hispanic
No
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
*
*
Employment
*
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
643
355
188
43
45
4
8
Season
Wnter
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
*
*
Angina
No
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: Tsanq and Klepeis, 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 Over 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
*
*
*
*
Age (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
*
Hispanic
No
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
*
Employment
*
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
Day of Week
Weekday
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
Angina
No
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: Tsana 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)
Category
Population Group
Percentiles
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
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
Wnter
39
0
0
0
0
2
5
90
121
121
121
121
121
Season
Spring
78
0
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: Tsanq and Klepeis. 1996.
-------
Table 16-34. Amount and Frequency of Use of Various Cosmetic and Baby Products
Amount of
Average Frequency of Use
(per day)
Upper 90th Percentile Frequency of Use
(per day)
Product Type
Product Pe|
Application
(grams)
Survey Type
Survey Type
CTFA
Cosmetic
Co.
Market
Research
Bureau
CTFA
Cosmetic
Co.
Market
Research
Bureau
Baby Lotion - baby usec
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 usec
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 usec
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 usec
-
0.43
1.3
-
0.43
3.0
-
Baby Cream - adult use
-
0.07
0.10
0.11f
0.14
0.14e
0.43f
Baby Shampoo - baby usec
0.5
0.14
-
0.14
-
Baby Shampoo - adult use
5.0
0.02
-
-
0.86e
-
-
Bath Oils
14.7
0.08
0.19
0.229
0.29
0.86
1.09
Bath Tablets
-
0.003
0.008
-
0.14e
0.14s
-
Bath Salts
18.9
0.006
0.013
-
0.14e
0.14s
-
Bubble Baths
11.8
0.088
0.13
-
0.43
0.57
-
Bath Capsules
-
0.018
0.019
-
0.296
0.14s
-
Bath Crystals
-
0.006
-
-
0.296
0.14s
-
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
-
0.14e
0.14s
-
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)
Amount of
Average Frequency of Use
(per day)
Upper 90th Percentile Frequency of Use
(per day)
Product Type
Product Pe|
Application
(grams)
Survey Type
Survey Type
CTFA
Cosmetic
Co.
Market
Research
Bureau
CTFA
Cosmetic
Co.
Market
Research
Bureau
Powders
2.01
0.18
0.39
-
1.0
1.0
-
Sachets
0.2
0.0061
0.034
-
0.14e
0.14s
-
Fragrance Lotion
-
0.0061
-
-
0.296
-
-
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
0.14s
-
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
-
0.14e
0.14s
-
Nail Polish & Enamel
0.28
0.16
0.20
0.07
0.71
0.43
1.0
Nail Polish & Enamel
Remover
3.06
0.088
0.19
-
0.29
0.43
-
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
0.14e
0.29
0.29
Feminine Hygiene
Deodorants
-
0.021
0.084
0.05
1.0"
0.29
0.14
Cleansing Products (cold
creams, cleansing lotions
liquids & pads)
1.7
0.63
0.80
0.54
1.71
2.0
1.5
Depilatories
-
0.0061
0.051
0.009
0.016
0.14
0.033
Face, Body & Hand Preps
(excluding shaving preps)
3.5
0.65
-
1.12
2.0
-
2.14
Foot Powder & Sprays
-
0.061
0.079
-
0.57s
0.29
-
Hormones
-
0.012
0.028
-
0.57s
0.14s
-
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)
Amount of
Average Frequency of Use
(per day)
Upper 90th Percentile Frequency of Use
(per day)
Product Type
Product Pe|
Application
Survey Type
Survey Type
(g)
CTFA
Cosmetic
Co.
Market
Research
Bureau
CTFA
Cosmetic
Co.
Market
Research
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 Cream
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.
(~'s) indicate no data available.
b 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 90th percentile figures in many instances. The 90th 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.
8 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
the period of the study.
' Usage data reflected "entire household" use.
9 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 Population
Comments
KEY STUDIES
Abt, 1992
Westat, 1987a
Westat, 1987b
Westat, 1987c
Tsang and Klepeis, 1996
RELEVANT STUDY
CTFA, 1983
4,997 product interviews;
527 mailed questionnaires
4,920 individuals
193 households
777 households
9,386 individuals
Survey 1: 47 women
employees and relatives or
employees
Survey 2:1,129 cosmetics
purchasers
Survey 3:19,035 females
Direct - interviews and Adults
questionnaires
Direct - questionnaire
Direct - telephone survey; 2
post-survey validation efforts: 30
reinterviewed, then another 50
reeinterviewed
Direct - telephone survey; 1
post-survey validation effort
conducted with 30 reinterviewed
Direct - interviews and
questionnaires
Survey 1: Direct -1 wk
prospective survey
Survey 2: Direct - prospective
survey
Survey 3: Direct - 9.5 months,
prospective survey
18+ yrs selected to be
representative of US
population
Adult household members
who do cleaning tasks in
household
Household members who do
painting tasks in household
Representative of U.S.
general population
Survey 1: 16-61 yrold
females
Survey 2: Customers of
cosmetic manufacturer
Survey 3: Market research
company sampled female
consumers nationwide
Random digit dialing method used to select sample.
Information on use of 3 products containing methyl chloride
was requested.
Waksberg Method (random digit dialing) used to select
sample. Respondents asked to recall use in past 2 months of
32 catagories of household products containing methyl
chloride.
Waksberg Method (random digit dialing) used to select
sample. Household use of cleaning products requested.
Phone survey during end of year holidays may reflect biased
usage data. Two validation resurveys conducted 3 months
after survey.
Waksberg Method (random digit dialing) used to select
sample. Painting product use information in past 12 months
was requested. One validation resurvey conducted 3 months
after survey.
National Human Activity Patterns Survey (NHAPS).
Participants selected using random Dial Digit (RDD) and
Computer Assisted Telephone Interviewing (CATI). 24-hour
diary data, and follow-up questions; nationally representative;
represent all seasons, age groups, and genders.
Interviewees asked to recall their use of cosmetics and some
baby products during a specific past time period. Surveys 1
and 2 had small populations, but Survey 3 had large
population selected to be representative of U.S. population
-------
Table 16A-1. Volumes Included in 1992 Simmons Study
The volumes included in the Media series are as follows:
M1
Publications: Total Audiences
M2
Publications: Qualitative Measurements And In-Home Audiences
M3
Publications: Duplication Of Audiences
M4
Multi-Media Audiences: Adults
M5
Multi-Media Audiences: Males
M6
Multi-Media Audiences: Females and Mothers
M7
Business To Business
M8
Multi-Media Reach and Frequency and Television Attentiveness & Special Events
The following volumes are included in the Product series:
P1
Automobiles, cycles, Trucks & Vans
P2
Automotive Products & Services
P3
Travel
P4
Banking, Investments, Insurance, Credit Cards & Contributions, Memberships & Public Activities
P5
Games & Toys, Children's & Babies' Apparel & Specialty Products
P6
Computers, Books, Discs, Records, Tapes, Stereo, Telephones, TV & Video
P7
Appliances, Garden Care, Sewing & Photography
P8
Home Furnishings & Home Improvements
P9
Sports & Leisure
P10
Restaurants, Stores & Grocery Shopping
P11
Direct Mail & Other In-Home Shopping, Yellow Pages, Florist, Telegrams, Faxes & Greeting Cards
P12
Jewelry, Watches, Luggage, Writing Tools & Men's Apparel
P13
Women's Apparel
P14
Distilled Spirits, Mixed Drinks, Malt Beverages, Wne & Tobacco Products
P15
Coffee, Tea, Cocoa, Milk, Soft Drinks, Juices & Bottled Water
P16
Dairy Products, Desserts, Baking & Bread Products
P17
Cereals & Spreads, Rice, Pasta, Pizza, Mexican Foods, Fruits & Vegetables
P18
Soup, Meat, Fish, Poultry, Condiments & Dressings
P19
Chewing Gum, Candy, Cookies & Snacks
P20
Soap, Laundry, Paper Products & Kitchen Wraps
P21
Household Cleaners, Room Deodorizers, Pest Controls & Pet Foods
P22
Health Care Products & Remedies
P23
Oral Hygiene Products, Skin Care, Deodorants & Drug Stores
P24
Hair Care, Shaving Products & Fragrances
P25
Women's Beauty Aids, Cosmetics & Personal Products
P26
Relative Volume of Consumption
-------
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 estimating 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,
Springfield, 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 of 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]
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Volume III - Activity Factors
Chapter 17 - Residential Building Characteristics
17. RESIDENTIAL BUILDING CHARACTERISTICS
17.1. INTRODUCTION
17.2. BUILDING CHARACTERISTICS
17.2.1. Key Volumes 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. Interzonal 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.
Table
17-2.
Table
17-3.
Table
17-4.
Table
17-5.
Table
17-6.
Table
17-7.
Table
17-8.
Table
17-9.
Table
17-10
Table
17-11
Summary of Residential Volume Distributions
Average Estimated Volumes of U.S. Residences, by Housing Type and
Ownership
Residential Volumes in Relation to Household Size and Year of Construction
Dimensional Quantities for Residential Rooms
Examples of Products and Materials Associated with Floor and Wall
Surfaces in Residences
Percent of Residences with Basement, by Census Region and EPA Region
Percent of Residences with Certain Foundation Types by Census Region
States Associated with EPA Regions and Census Regions
Summary of Major Projects Providing Air Exchange Measurements in the
PFT Database
Summary Statistics for Air Exchange Rates (air changes per hour-ACH), by
Region
Distributions of Residential Air Exchange Rates by Climate Region and
Season
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August 1997
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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 Air 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 17-4. Idealized Patterns of Particle Deposition Indoors
Figure 17-5. Air Flows for Multiple-zone Systems
Exposure Factors Handbook August 1997
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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 factors 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-bound 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 code-
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 interactions with other connecting zones, the multizone model is stated
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August 1997
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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 Laboratory (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 Harry 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 systems, 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,
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August 1997
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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 residences occupied by one-
person households.
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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 382 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 standard
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 assemblies 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 volume of 480 cubic feet or 13.6 cubic meters.
Murray (1996) analyzed the distribution of selected residential zones (i.e., a series
of connected 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 ±
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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 area-to-
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 m2nr3 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 m2nr3 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
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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 (HAC);
(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 HAC 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 accomplished through increased air movement when the air handler is
operating.
Figure 17-3 also distinguishes forced-air HAC 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 house, 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.
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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 which 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"11400 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.
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By comparison, homes with crawl spaces open to the outside have 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 about
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 crawlspace 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.
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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;
• Interzonal airflows - Transport through doorways, ductwork, and service
chaseways that interconnect 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
during the heating season and a generally falling current during the cooling season. When
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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 at. (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.
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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 field-
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-RTI2 and
SOCAL2. Both projects involved measurements in Southern California during a time of
year (July) when 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 determined 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
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the limitations of the underlying 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 climate region during the summer. As noted earlier (Section 17.3.2), many
of the measurements 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
individual buildings. A number of these models have been reviewed, for example, by
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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 |Tj - T0| + cU " (Eqn. 17-1)
where:
A = air infiltration rate (h"1)
T, = 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 10.006AT + Ml U15J (Eqn. 17-2)
where:
A = average air changes per hour or infiltration rate, h"1
L = generalized house leakiness factor (1 < L < 5)
C = terrain sheltering factor (1 < C < 10)
AT = indoor-outdoor temperature difference (C°)
U = windspeed (ms"1)
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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 systems (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. Deposition 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 rrr3) 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 //m). 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).
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Wallace (1996) - Indoor Particles: A Review - In a major review of indoor particles,
Wallace (1996) cited overall particle deposition rates for respirable (PM25), inhalable
(PM10), and coarse (difference between PM10 and PM25) 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 //m) 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
principles 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 al. (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. Interzonal 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
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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 not convenient)
assumptions. Interzonal 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 chemicals, 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 Metropolitan 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 in-
house water use as well as each type of use. Central values for total use, were obtained
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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 Characteristics - 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 observed mean frequencies in
these studies are given in Table 17-19. Tables 17-20 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 contain VOCs (see, for example, Wolkoff and
Wilkins, 1994; Hirvonen et al., 1995), pesticides from imported soil particles as well as
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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
fj,m aerodynamic diameter penetrate the building envelope as completely as nonreactive
gases (Wallace, 1996).
Roberts et at. (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 single-
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 //m. 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 the study of 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
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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 time-
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;
Wolkoff, 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, NOx) have been measured for a number of combustion appliances
using room-sized chambers (see, for example, Relwani et al., 1986). Other direct-
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 source 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
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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 diffusion-
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; Cussler, 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 (E0) 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 (Ec) 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:
(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:
°°D ^
M= Ene "kstdt=—
m 0 k
(Eqn. 17-4)
0 s
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
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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 nr3) with the flow rate for the water use (m3 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 system (see, for example, Little,
1992; Andelman, 1990; McKone, 1987).
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Release rates are formulated as:
S = KmFw
[c - SI
w H
where:
S =
chemical release rate (g h"1)
Km =
dimensionless mass-transfer coefficient
Fw =
water flow rate (m3 h"1)
cw =
concentration in feed water (g m"3)
ca =
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):
1
=a.=jl - m ^r/3
(H"
(Eqn. 17-6)
K
KJ
K|_r KGr "h| DGi J
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 nr2) combined with resuspension rates (Rd, h"1) and floor area (Af, m2):
Sd = Md Rd Af (Eqn. 17-7)
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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 (1994) 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 point-
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 of 2:1.
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
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gradient will reverse, allowing the chemical to escape. For persistent indoor sources, 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 emission
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 et al.,
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.
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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 national 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 time-weighted-
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
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(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 room-sized-
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.
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Table 17-1. Summary of Residential Volume Distributions
in Cubic Meters3
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) Thompson, 1995: (2) Versar, 1990
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Table 17-2. Average Estimated Volumes of U.S. Residences, by Housing Type and Ownership
Ownership
Owner-Occupied Rental All Units
Housing Type
Volume3
(m3)
Percent
of Total
Volume3
(m3)
Percent
of Total
Volume3
(m3)
Percent
of Total
Single-Family
(Detached)
471
53.1
323
8.5
451
61.7
Single-Family
(Attached)
406
4.6
291
2.9
362
7.5
Multifamily
(2-4 units)
362
1.6
216
6.7
243
8.3
Multifamily
(5+ Units)
241
1.7
183
15.2
190
16.8
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.
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Table 17-3. Residential Volumes in Relation to Household
Size and Year of Construction
Volume3
(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
100.0
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
1991 to 1993
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.
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Table 17-4. Dimensional Quantities for Residential Rooms
Length
Width
Height
Volume
Wall Area
Floor Area
Total Area
Nominal Dimensions
(m)
(m)
(m)
(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
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Table 17-5. Examples of Products and Materials Associated with Floor
and Wall Surfaces in Residences
Assumed Amount
Material Sources
of
Surface Covered3
Silicone caulk
0.2 m2
Floor adhesive
10.0 m2
Floor wax
50.0 m2
Wood stain
10.0 m2
Polyurethane wood finish
10.0 m2
Floor varnish or lacquer
50.0 m2
Plywood paneling
100.0 m2
Chipboard
100.0 m2
Gypsum board
100.0 m2
Wallpaper
100.0 m2
a Based on typical values for a residence.
Source: Adapted from Tucker, 1991.
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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
West
10
11.5
All Reaions
45.2
Source: Lucas et al.. 1992.
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Table 17-7.
Percent of Residences with Certain Foundation Types by Census Region
Percent of Residences3
Census Region
With
Basement
With
Enclosed
Crawlspace
With Crawlspace With
Open to Outside Concrete Slab
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
a 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.
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Table 17-8. States Associated with EPA Regions and Census Regions
US EPA Regions
Reaion 1
Reaion 4
Reaion 6
Reaion 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
Reaion 10
South Carolina
Reaion 7
Alaska
Reaion 2
Tennessee
Iowa
Idaho
New Jersey
Kansas
Oregon
New York
Reaion 5
Missouri
Washington
Illinois
Nebraska
Reaion 3
Indiana
Delaware
Michigan
Reaion 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 Reaion
Midwest Reaion
South Reaion
West Reaion
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
Project Code
State
Month(s)a
Number of
Measurements
Mean Air
Exchange
Rate
SDb
10th
25th
Percentiles
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
0.55
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
RTI1
CA
2
45
0.90
0.73
0.38
0.48
0.78
1.08
1.52
RTI2
CA
7
41
2.77
2.12
0.79
1.18
2.31
3.59
5.89
RTI3
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
Wl
2-5
57
0.82
0.76
0.22
0.33
0.55
1.04
1.87
a 1 = January, 2 = February, etc.
b Standard deviation
Source: Adapted from Versar, 1990.
-------
Table 17-10. Summary Statistics for 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
50th 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 Exchange Rates8 by Climate Region and Season
Percentiles
Arithmetic
Standard
Climate
Reqion
Season
Sample Size
Mean
Deviation
10th
25th
50th
75th
90th
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
a In air changes per hour
Source: Murrav and Burmaster. 1995.
-------
Table 17-12. Deposition Rates for Indoor Particles
Size Fraction
Deposition Rate
pm25
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: Adapted from Thatcher and Lavton,
1995.
-------
Table 17-14.
n-house Water Use Rates (gcd), by Study and Type of Use
Total,
Shower
Studv
All Uses
or Bath
Toilet
Laundrv
Dishwashina
Other
MWD1
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 HUDand Power Authority Water Use Studies
Number of Households
Location
Reference
U.S. DHUD Studies
Study 1
37
Los Angeles, CA
a,b
Study 2
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
Study 4
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.
c East Bay Municipal Utility District, 1992.
-------
Table 17-16. Showering and Bathing Water Use Characteristics
Characteristic Mean Duration
Mean Frequency
Individuals who Shower only 10.4 minutes/shower
Individuals who Bath only NA
Individuals who Shower and Bath NA
0.74 showers/day/person
0.41 baths/day/person
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
(cipm)
Non-Conserving (> 3 gpm)
3.4
Low Flow (< 3 gpm)
1.9
Restrictor (< 3 gpm)
2.1
Zinplas3
1.8
Turboiector3
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
Dams
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., 1974 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
Unweighted Mean
3.43 flushes/oerson/dav
a The HUD value may in fact be flushes/household/day
-------
Table 17-20. Dishwasher Frequency Use Characteristics
Studv
Use Freauencv
U.S. DHUD, 1984
0.47 loads/person/day
Ligman, et al., 1974 Rural
1.3 loads/day
Siegrist, 1976
0.39 loads/person/day
Unweighted Mean
0.92 loads/day
-------
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
-
Unweighted Mean
10.9
72.8
87.9
Source: Adapted from Consumer Reports, 1987.
-------
Table 17-22. Clothes Washer Frequency Use Characteristics
Studv
Use Freauencv
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/day
-------
Table 17-23. Clothes Washer Water Use Characteristics
Brand
Average Water Use
(gallons/regular cycle)
Cycle Duration
(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
Norae
55
49
Source: Adapted from Consumer Reports, 1982.
-------
Table 17-24. Range of Water Uses for Clothes Washers
Tvoe of Clothes Washer
Ranae of Water Use
Conventional
27-59 gallons/load
Low Water
16-19 gallons/load
All Clothes Washers
16-59 gallons/load
Source: Adapted from Consumer Reports, 1982.
-------
Table 17-25.
Total Dust Loading for Carpeted Areas
Household
Total Dust Load
Fine Dust (<150 ^m) Load
(g-rrr2)
(g-rrr2)
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 During Normal Activities
Particle Size Range
(um)
Particle
Deposition
Rate
Or1)
Particle Resuspension
Rate
(h"1)
0.3-0.5
(not measured)
9.9 x 10"7
0.6-1
(not measured)
4.4 x 10"7
1-5
0.5
1.8 x 10"5
5-10
1.4
8.3 x 10"5
10-25
2.4
3.8 x 10"4
>25
4.1
3.4 x 10"5
Source: AdaDted from Thatcher and Lavton. 1995.
-------
Table 17-27. Dust Mass Loading After One Week Without Vacuum Cleaning
Location in Test House
Dust Loading (g-
m )
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: AdaDted from Thatcher and Lavton. 1995.
-------
Table 17-28. Simplified Source Descriptions for Airborne Contaminants
Description
Components
Dimensions
Direct Discharge
Combustion
Ef Hf Mf
gh"1
Ef = emission factor
gJ"1
Hf = fuel content
J mol"1
Mf = fuel consumption rate
mol h"1
Volume Discharge
QP Cp_eD
gh"1
Qp = volume delivery rate
m3 h"1
Cp = concentration in carrier
g m"3
eD = transfer efficiency
(Q
(Q
Mass Discharge
Mp we e
gh-1
Mp = mass delivery rate
gh"1
we = weight fraction
(Q
(Q
eD = transfer efficiency
(Q
(Q
Diffusion Limited
(D, 50 )(CS - C, )Aj
gh"1
Df = diffusivity
m2 h"1
5 1 = boundary layer thickness
m
Exponential
Cs = vapor pressure of
surface
Cj = room concentration
Aj = area
gm"3
g m"3
m2
A E0 e"kt
Aj = area
E0 = initial unit emission rate
gh"1
m2
g h"1 m"2
h"1
k = emission decay factor
h
Transport
t =time
Infiltration
Q„c,
gh"1
Interzonal
Qji = air flow from zone j
m3 h"1
Soil Gas
Cj = air concentration in zone
i
g m"3
-------
Table 17-29. Volume of Residence Surveys
Studv
Number of
Residences
Survev TvDe
Areas Surveyed
Comments
Kev Studies
U.S. DOE, 1995
(RECS)
Over 7,000
Direct measurement of floor
area; estimation of volume
Nationwide (random sample)
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.
Versar, 1990
(PFT database)
Over 2,000
Direct measurement and
estimated
Nationwide (not random
sample); a large fraction located
in CA
Sample was not geographically
balanced; statistical weighting was
applied to develop nationwide
distributions
Murray, 1996
7,041 (RECS)
1,751 (PFT)
Direct measurements and
estimated
RECS-Nationwide (random
sample); PFT - Nationwide (not
random sample); a large fraction
located in CA
Duplicate measurement were eliminated;
tested the effects of using 8 ft.
assumption on ceiling height to calculate
volume; data from both databases were
analyzed.
-------
Table 17-30. Air Exchange Rates Surveys
Studv
Number of
Residences/Measurements
Survev TvDe
Areas Surveyed
Comments
Versar, 1990
(PFT database)
Over 2,000 residences
Measurements using
PFT technique
Nationwide (not random
sample); a large fraction located
in CA
Multiple measurements on the
same home were included.
Koontz & Rector, 1995
(PFT database)
2,971 measurements
Measurements using
PFT technique
Nationwide (not random
sample); a large fraction located
in CA
Multiple measurements on the
same home were included.
Compensated for geographic
imbalances. Data are presented by
region of the country and season.
Murray and Burmaster, 1995
(PFT database)
2,844 measurements
Measurements using
PFT technique
Nationwide (not random
sample); a large fraction located
in CA
Multiple measurements on the
same home were included. Did not
compensate for geographical
imbalances. Data are presented by
climate region and season.
Nazaroff et al., 1988
255 (Grot and Clark, 1981)
Direct measurement
255, low-income families in 14
cities
Sample size was small and not
representative of the U.S.
312 (Grimsrud, 1983)
Direct measurement
321, newer residences, median
aae <10 vears
Sample size was small and not
reDresentative 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 (10th percentile)11
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 to be used as the mean value,
c Recommended to be used as a typical value (Table 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
interest
The focus of the studies was on estimating house
volume as well as other factors.
High
• Data pertinent to U.S.
Residences in the U.S. was the focus of the key
studies.
High
• Primary data
All the studies were based on primary data.
High
• Currency
Measurements in the PFT database were taken
between 1982-1987. The RECS survey was
conducted in 1993.
Medium
• Adequacy of data
Not applicable
collection period
• Validity of approach
For the RECS survey, volumes were estimated
assuming an 8 ft. ceiling height. The effect of this
assumption has been tested by Murray (1996) and
found to be insignificant.
Medium
• Study size
The sample sizes used in the key studies were fairly
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.
Medium
• Representativeness of the
RECS sample is representative of the U.S.
Medium
population
• Characterization of
variability
Distributions are presented by housing type and
regions; although some of the sample sizes for the
subcategories were small.
Medium
• 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
areas were estimated using the assumption of 8 ft.
ceiling height.
Medium
Other Elements
• Number of studies
There are 3 key studies; however there are only 2
data sets.
Low
• Agreement between researchers
There is good agreement among researchers.
High
Overall Rating
Results were consistent; 1 study (RECS) was
representative of residences in the whole U.S.;
volumes were estimated rather than measured in
some cases.
Medium
-------
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.
Although there are 3 studies, they are all based on
the same database (PFT database).
High
• Accessibility
Papers are widely available from government reports
and peer review journals.
High
• Reproducibility
Precision across repeat analyses has been
documented to be acceptable.
Medium
• Focus on factor of
interest
The focus of the studies was on estimating air
exchange rates as well as other factors.
High
• Data pertinent to U.S.
Residences in the U.S. was the focus of the PFT
database.
High
• Primary data
All the studies were based on primary data.
High
• Currency
Measurements in the PFT database were taken
between 1982-1987.
Medium
• Adequacy of data
collection period
Only short term data were collected; some residences
were measured during different seasons; however,
long term air exchange rates are not well
characterized.
Medium
• Validity of approach
Although the PFT technology is an EPA standard
method (Method IP-4A), it has some major limitations
(e.g., uniform mixing assumption).
Low
• Study size
The sample sizes used in the key studies were fairly
large, although not representative of the whole U.S.
Not all samples were selected at random.
Medium
• Representativeness of the
Sample is not representative of the U.S..
Low
population
• Characterization of
variability
Distributions are presented by U.S. regions, seasons,
and climatic regions; although some of the sample
sizes for the subcategories were small and not
representative of U.S. The utility is limited..
Low
• Lack of bias in study design
(high rating is desirable)
Bias may result since the selection of residences was
not random.
Low
• Measurement error
Some measurement error may exist.
Medium
Other Elements
• Number of studies
There are 3 key studies; however there are only 1
data set. However, the database contains results of
20 projects of varying scope.
Medium
• Agreement between researchers
Not applicable
Overall Rating
Sample was not representative of residences in the
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 closed or ODened.
Low
-------
Air In
Water In
Soil In
Concentration, C
Source
Exposure, E for Occupant(s)
Decay
Resuspension
n.
Removal
I
Reversible
Sinks
¦f
Out
4
Figure 17-1. Elements of Residential Exposure
-------
DOE survey
PFT database
100 200 300 400 500 600 700 BOO 900 1000
Volune, cUoicmeters
Figure 17-2. Cumulative Frequency Distributions for Residential Volumes
from the PFT Data Base and the U.S. DOE's RECs.
-------
COMMON RETURN LAYOUT
Return
Zone 1
Zone 2
Zone N
Supply
Filter
.Air Handler
BALANCED SUPPLY and RETURN LAYOUT
Return
Zone 1
Zone 2
Zone H
Supply
Filter
£ir Handler
Figure 17-3. Configuration for Residential Forced-air Systems
-------
Floor
!l..
Walls
Ceiling\
L
1—I 1 1 I III
1—1 1 1 11II
n
1 1 MINI1 1 1 llllll
0.001 0.01 0.1 1 10
Particle Diameter (|jm)
Figure 17-4. Idealized Patterns of Particle Deposition Indoors
Source: Adapted from Nazaroff and Cass, 1989.
-------
SINGLE-ZONE
SYSTEM
TWO-ZONE
SYSTEM
THREE-ZONE
N-Zone System Defined by N (N+1) Airflows
Figure 17-5. Air Flows for Multiple-zone Systems
-------
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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 Exchange Rates by Climate Region and
Season [WK1, 3 kb]
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