CHILDREN
AND THE ENVIRONMENT
THIRD EDITION
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AMERICAS CHILDREN
AND THE ENVIRONMENT
THIRD EDITION
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Foreword
I am pleased to present the U.S. Environmental Protection Agency's America's Children and the
Environment, Third Edition. This report marks the important progress we have made as a nation
to reduce environmental risks to children's health.
The report contains good news for children and families including significant improvements in
the quality of the air we breathe, substantial decreases in childhood blood lead levels, and a
steady reduction in children's exposure to secondhand smoke. We are encouraged by these
findings. We also know that there is still much work to be done, including further research on
the causes of increases in asthma rates, the potential impacts of early life exposures to
chemicals, and disease disparities in minority children and children in low-income families.
America's Children and the Environment will help focus our efforts in addressing these
challenges and others.
Protecting children's health is central to the EPA's mission, and the agency has taken great
strides to improve the environment for children where they live, learn, and play, including:
• Finalizing the Mercury and Air-Toxics Standards Rule to limit mercury and other air toxics
emissions from electric generating utilities. These new standards address the largest
remaining domestic source of mercury emissions to the environment—a well known
neurotoxin in children. The controls put in place by these standards will also avoid 130,000
asthma attacks every year—which disproportionately impact children especially in
underserved communities.
• Updating the National Ambient Air Quality Standard for fine-particle pollution (PM2.s) to
improve public health protection. Exposure to PM2.5 can aggravate asthma and lead to
other respiratory symptoms in children.
• Establishment of new National Ambient Air-Quality Standards for nitrogen dioxide (NO2)
and sulfur dioxide (SOz), and a network of monitors to limit near roadway exposures to
N02. These new standards will limit respiratory-related emergency room visits and hospital
admissions and will improve public health protection, especially for children, the elderly,
and people with asthma.
• Supporting cutting-edge research through the Centers for Children's Environmental
Health and Disease Prevention Research, in partnership with the National Institute of
Environmental Health Sciences, to enhance scientific understanding of the relationships
between environmental contaminants and children's health.
• Launching new voluntary guidelines that promote environmentally safe siting of schools
and the establishment of school environmental health programs by states.
• Working with other federal agencies to develop and implement the Coordinated Federal
Action Plan to Reduce Racial and Ethnic Asthma Disparities to reduce the disproportionate
impact of asthma on minority and low-income children.
As we move forward, the EPA is committed to continuing the success of our children's health
efforts. The national indicators presented in this comprehensive report are important for
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Foreword
informing future research related to children's health. We will continue to partner with other
federal agencies to develop increasingly reliable information that will help us to further
improve children's health.
I want to thank the many individuals who contributed to this report for their hard work
and efforts. By monitoring trends, identifying successes, and shedding light on areas of concern,
we can continue to improve the health of our children and all Americans.
Lisa P. Jackson
Administrator
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Table of Contents
Table of Contents
Authors, Contributors, and Reviewers 1
About This Report 6
Key Findings 18
Environments and Contaminants 25
Criteria Air Pollutants 31
Hazardous Air Pollutants 50
Indoor Environments 58
Drinking Water Contaminants 72
Chemicals in Food 85
Contaminated Lands 95
Climate Change 105
Biomonitoring 109
Lead 118
Mercury 127
Cotinine 135
Perfluorochemicals(PFCs) 144
Polychlorinated Biphenyls (PCBs) 151
Polybrominated Diphenyl Ethers (PBDEs) 159
Phthalates 168
BisphenolA(BPA) 180
Perchlorate 190
Health 199
Respiratory Diseases 207
Childhood Cancer 223
Neurodevelopmental Disorders 233
Obesity 254
Adverse Birth Outcomes 264
Supplementary Topics 275
Birth Defects 279
Contaminants in Schools and Child Care Facilities 288
References 305
Appendices 391
Appendix A: Data Tables A-l
Appendix B: Metadata B-l
Appendix C: Alignment of ACES Indicators with Healthy People 2020 Objectives C-l
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Authors, Contributors, and Reviewers
Authors
Daniel Axelrad, Office of Policy
Kristen Adams, Office of Policy (Association of Schools of Public Health Fellow)
Farah Chowdhury, Office of Policy
Louis D'Amico, Office of Children's Health Protection (American Association for the
Advancement of Science, Science and Technology Policy Fellow)
Erika Douglass, Office of Policy (Association of Schools of Public Health Fellow)
Gwendolyn Hudson, Office of Children's Health Protection (Association of Schools of Public
Health Fellow)
Erica Koustas, Office of Policy (Oak Ridge Institute for Science and Education Fellow)
Juleen Lam, Office of Policy (Oak Ridge Institute for Science and Education Fellow)
Alyson Lorenz, Office of Children's Health Protection (Association of Schools of Public Health
Fellow)
Gregory Miller, Office of Children's Health Protection
Kathleen Newhouse, Office of Children's Health Protection (on detail from Office of Research
and Development)
Onyemaechi Nweke, Office of Environmental Justice
Doreen Cantor Paster, Office of Policy (on detail from Office of Chemical Safety and Pollution
Prevention)
Julie Sturza, Office of Policy
Lindsay Underbill, Office of Policy
Kari Weber, Office of Policy
Contributors
Robin Schafer, Office of Solid Waste and Emergency Response
Jennifer Parker, Centers for Disease Control and Prevention, National Center for Health
Statistics
Contractor Support
Jonathan Cohen, ICF International
Brad Hurley, ICF International
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Authors, Contributors, and Reviewers
Internal Reviewers
EPA Reviewers
John Bowser, Office of Chemical Safety and Pollution Prevention
Rich Cook, Office of Air and Radiation
Glinda Cooper, Office of Research and Development
Elizabeth Corr, Office of Water
Rebecca Dzubow, Office of Research and Development
Alison Freeman, Office of Air and Radiation
Jane Gallagher, Office of Research and Development
Anne Grambsch, Office of Research and Development
Michael Hadrick, Office of Air and Radiation
Beth Hassett-Sipple, Office of Air and Radiation
David Hrdy, Office of Chemical Safety and Pollution Prevention
Jyotsna Jagai, Office of Research and Development
Michael Kolian, Office of Air and Radiation
Toni Krasnic, Office of Chemical Safety and Pollution Prevention
Jade Lee-Freeman, Office of Water
Danelle Lobdell, Office of Research of Development
Phil Lorang, Office of Air and Radiation
Matthew Lorber, Office of Research and Development
David Miller, Office of Chemical Safety and Pollution Prevention
Patricia Murphy, Office of Research and Development
Maureen O'Neill, Region 2
Ted Palma, Office of Air and Radiation
Andrea Pfahles-Hutchens, Office of Chemical Safety and Pollution Prevention
Robin Schafer, Office of Solid Waste and Emergency Response
Andrew Simons, Office of General Counsel
Maryann Suero, Region 5
Nicolle Tulve, Office of Research and Development
Prentiss Ward, Region 3
Melanie Young, Office of Water
Reviewers from Other Agencies
Linda Abbott, United States Department of Agriculture
Lara Akinbami, Centers for Disease Control and Prevention, National Center for Health Statistics
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Authors, Contributors, and Reviewers
Peter Ashley, Department of Housing and Urban Development
John T. Bernert, Centers for Disease Control and Prevention, National Center for Environmental
Health
Benjamin Blount, Centers for Disease Control and Prevention, National Center for
Environmental Health
Laurie A. Brajkovich, California Department of Pesticide Regulation
Debra Brody, Centers for Disease Control and Prevention, National Center for Health Statistics
Antonia Calafat, Centers for Disease Control and Prevention, National Center for Environmental
Health
Basil Ibewiro, California Department of Pesticide Regulation
Lisa Marengo, Texas Department of State Health Services
Pauline Mendola, Centers for Disease Control and Prevention, National Center for Health
Statistics
Cynthia Ogden, Centers for Disease Control and Prevention, National Center for Health
Statistics
John Osterloh, Centers for Disease Control and Prevention, National Center for Environmental
Health
Jennifer Parker, Centers for Disease Control and Prevention, National Center for Health
Statistics
Patricia Pastor, Centers for Disease Control and Prevention, National Center for Health Statistics
Kenneth Schoendorf, Centers for Disease Control and Prevention, National Center for Health
Statistics
Children's Health Protection Advisory Committee, America's Children and the
Environment Task Group
Laura Anderko, Georgetown University
Lynda Knobeloch, Wisconsin Department of Health Services
Amy Kyle, University of California, Berkeley
Robert Leidich, BP Products North America Inc.
Melanie Marty, California Environmental Protection Agency
Elise Miller, Collaborative on Health and the Environment
Jerome Paulson, George Washington University
Jennifer Roberts, Exponent, Inc.
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Authors, Contributors, and Reviewers
External Peer Reviewers
Jennifer Adibi, University of California, San Francisco
Dana Barr, Emory University
Paloma Beamer, University of Arizona
Cynthia Bearer, University of Maryland
Alan Becker, Florida Agricultural and Mechanical University
Michelle Bell, Yale University
Deborah Bennett, University of California, Davis
Jason Booza, Wayne State University
Carla Campbell, Drexel University
Gang Chen, Penn State University
Timothy Church, University of Minnesota
Julianne Collins, Greenwood Genetic Center
Lucio Costa, University of Washington
Susan Duty, Simmons College/Harvard University
Diane Heck, New York Medical College
Susan Jobling, Brunei University
Kurunthachalam Kannan, New York State Department of Health
Catherine Karr, University of Washington
Judy LaKind, University of Maryland
Peter Langlois, Texas Department of State Health Services
Bruce Lanphear, Simon Fraser University
An Li, University of Illinois at Chicago
Morton Lippmann, New York University
Larry Lowry, University of Texas, Tyler
Alex Lu, Harvard University
Kristen Malecki, University of Wisconsin, Madison
Kathleen McCarty, Yale University
John Meeker, University of Michigan
Dawn Misra, Wayne State University
Vlasta Molak, Gaia Foundation/Gaia Unlimited
Ardythe Morrow, Cincinnati Children's Hospital Medical Center
Erica Phipps, Canadian Partnership of Children's Health and Environment
Gregory Pratt, Minnesota Pollution Control Agency
Beth Resnick, Johns Hopkins University
James Roberts, Medical University of South Carolina
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Authors, Contributors, and Reviewers
Leslie Rubin, Emory University
Barry Ryan, Emory University
Arnold Schecter, University of Texas, Dallas Regional Campus
Kellogg Schwab, Johns Hopkins University
Perry Sheffield, Mount Sinai School of Medicine
Martha Stanbury, Michigan Department of Community Health
Jennifer Straughen, Wayne State University
Michael Wilson, University of California, Berkeley
Catherine Yeckel, Yale University
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About this Report
About this Report
What is America's Children and the Environment?
America's Children and the Environment (ACE) is EPA's report presenting data on children's
environmental health. ACE brings together information from a variety of sources to provide
national indicators in the following areas: Environments and Contaminants, Biomonitoring, and
Health. Environments and Contaminants indicators describe conditions in the environment,
such as levels of air pollution. Biomonitoring indicators include contaminants measured in the
bodies of children and women of child-bearing age, such as children's blood lead levels. Health
indicators report the rates at which selected health outcomes occur among U.S. children, such
as the annual percentage of children who currently have asthma. Accompanying each indicator
is text discussing the relevance of the issue to children's environmental health and describing
the data used in preparing the indicator. Wherever possible, the indicators are based on data
sources that are updated in a consistent manner, so that indicator values may be compared
overtime.
This report is the third edition of ACE (referred to as ACES); previous editions of ACE were
published in 2000 and 2003. EPA has provided updated indicator values on its website on a
regular basis beginning in 2006, and will provide online updates for the indicators published in
this edition (see www.epa.gov/ace).
What are the purposes of America's Children and the Environment?
America's Children and the Environment has three principal objectives:
• First, it compiles data from a variety of sources to present concrete, quantifiable indicators
for key factors relevant to the environment and children's health in the United States.
• Second, it can inform discussions among policymakers and the public about how to improve
data on children's health and the environment.
• Third, it includes indicators that can be used by policymakers and the public to track trends
in children's environmental health, and ultimately to help identify and evaluate ways to
minimize environmental impacts on children.
This report is motivated by EPA's belief that it is valuable to be aware of, and to share with the
public, information on trends in children's environmental health. The purpose of ACE is to
compile information, and make it available to a broad audience, that can help identify areas
that warrant additional attention, potential issues of concern, and persistent problems. Some
of the indicators can also support efforts to evaluate whether past environmental policies and
actions have been effective. EPA hopes that the development and presentation of these
indicators will motivate continuing research, additional data collection, and, when appropriate,
necessary interventions.
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About this Report
The information in ACES is not intended to serve as a definitive basis for planning specific
policies or projects. EPA and other federal agencies rely on a wide range of technical
information to inform their activities on children's environmental health. Emerging and ongoing
research will help shape these efforts for years to come. The presentation of findings from the
scientific literature in ACES is not intended to constitute an authoritative summary or
conclusion on the weight of scientific evidence.
What are children's environmental health indicators?
For ACES, an indicator is defined as a quantitative depiction of an aspect of children's
environmental health that summarizes the underlying data in a relevant, understandable, and
technically appropriate manner. The data may represent measurements of environmental
conditions, of chemicals measured in the bodies of children and women of child-bearing age, or
of the frequency of certain childhood diseases and health outcomes. Federal data on children's
environmental health issues come from a variety of agencies and are often very detailed and
complex; ACE brings this information together into one report and summarizes the data in
graphics that convey the key information. The ACE indicators generally focus on presenting data
at the national scale in order to meet the three principal objectives described above.
Many indicators in this report provide a time series of data (i.e., a "trend" graph), to evaluate
whether conditions have changed over time. Other indicators provide a "snapshot" that focuses
on data from a single time period. These indicators may depict differences in conditions for
different population groups (defined by race/ethnicity or income), or they may provide data for
different children's health hazards for a single time period.
The World Health Organization defines environmental health as "all the physical, chemical, and
biological factors external to a person, and all the related factors impacting behaviors. It
encompasses the assessment and control of those environmental factors that can potentially
affect health."1 In concordance with this definition, use of the term "children's environmental
health" in ACES refers to external physical, chemical, and biological factors that are known to
affect children's health or may potentially affect children's health. The evidence of a
relationship between environmental exposure and children's health continues to evolve for
many of the indicators presented in this report. Inclusion of an indicator in this report does not
necessarily imply a known relationship between environmental exposure and children's health
effect. EPA aims to develop increasingly informative indicators of children's environmental
health as more data become available to reduce these uncertainties.
The ACES indicators are intended to be easy to understand and to cover a broad range of
topics. More extensive analyses are available for most of the datasets featured by ACES
indicators; links to the associated studies and reports will be provided on the ACE website.
Although the ACES indicators focus on national statistics, environmental exposures and health
may vary significantly across communities. Patterns of environmental exposure may vary due to
the nature and extent of pollutants found in each community. Patterns of health may vary
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About this Report
across communities due to demographic and socioeconomic characteristics. Links to online
resources with community-level information will be provided on the ACE website.
Why did EPA focus on indicators for children?
Under Executive Order 13045, EPA and other federal agencies are directed to "make it a high
priority to identify and assess environmental health risks and safety risks that may
disproportionately affect children."2 Environmental contaminants can affect children quite
differently than adults, both because children may be more highly exposed to contaminants,
and because they are often more vulnerable to the toxic effects of contaminants.
Children generally eat more food, drink more water, and breathe more air relative to their size
than adults do, and consequently may be exposed to relatively higher amounts of
environmental chemicals. Children's normal activities, such as putting their hands in their
mouths or playing on the ground, can result in exposures to chemicals that adults do not face.
In addition, some environmental contaminants may affect children disproportionately because
their bodies are not fully developed and their growing organs can be more easily harmed.
How is America's Children and the Environment organized?
After this introduction, ACES features four main sections: Environments and Contaminants,
Biomonitoring, Health, and Supplementary Topics. Each section presents information on a series
of children's environmental health topics, and at least one indicator is provided for each topic.
The Environments and Contaminants section presents information on chemicals and pollutants
in environmental media to which children are commonly exposed (through air, drinking water,
and food), along with other important aspects of children's environments. Topics addressed in
the Environments and Contaminants section include criteria air pollutants, hazardous air
pollutants, indoor environments, drinking water contaminants, chemicals in food,
contaminated lands, and climate change.
The Biomonitoring section presents information on selected chemicals measured in the blood
and urine of children and women of child-bearing age. Biomonitoring indicators for women
ages 16 to 49 years are included based on concern for potential adverse health effects in
children born to women who have been exposed to certain chemicals. Topics addressed in the
Biomonitoring section include lead, mercury, cotinine (a marker for exposure to environmental
tobacco smoke), perfluorochemicals (PFCs), polychlorinated biphenyls (PCBs), polybrominated
diphenyl ethers (PBDEs), phthalates, bisphenol A (BPA), and perchlorate.
The Health section presents information on diseases, conditions, and outcomes that may be
influenced by environmental exposures. Many factors contribute to children's health, including
genetic inheritance, nutrition, and exercise, among others. The adverse health consequences of
some environmental exposures may occur through interactions with other risk factors, and it is
often difficult to determine the extent to which the environment (or any other factor)
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contributes to children's health outcomes of concern. Topics addressed in the Health section
include respiratory diseases, childhood cancer, neurodevelopmental disorders, obesity, and
adverse birth outcomes.
The Supplementary Topics section presents topics for which adequate national data are not
available, but for which more targeted data collection efforts could be used to provide
measures illustrating additional children's environmental health issues of interest. Data sets
used for these measures are representative of particular locations (such as a single state)
and/or were surveys conducted a single time rather than on a continuing or periodic basis.
Since these data sets are lacking in certain key elements desirable for ACES indicators, data
presentations for the Supplementary Topics are referred to as "measures" rather than
"indicators." Topics addressed in this section include birth defects in Texas and contaminants in
schools and child care facilities.
How were the topics and indicators in the third edition of America's Children
and the Environment selected?
In choosing indicators for ACES, EPA considered a variety of factors, including public interest,
magnitude of prevalence and/or trend in prevalence, extent of exposure, severity of health
outcome, past EPA actions to address the issue, and research findings indicating or suggesting
that an environmental exposure may contribute to a children's health outcome. ACES includes
topics for which scientific evidence is sufficient to conclude there is a causal relationship
between exposure and health effects, as well as topics for which there is less extensive
scientific evidence. Inclusion of a topic in ACES, therefore, does not imply that a cause-effect
determination has been made.1
ACES includes updates and revisions to topics and indicators included in the 2003 ACE report, as
well as new topics and indicators developed for this edition. Although ACES addresses a
substantially expanded set of children's environmental health topics compared with the 2003
edition of this report, it is not intended to be inclusive of all children's environmental health issues.
The selection of topics involved generating a list of children's environmental health issues of
potential interest, evaluating availability of suitable databases relevant to those topics, and
considering indicators that might be derived from those databases. EPA obtained input from
members of EPA's Children's Health Protection Advisory Committee (CHPAC) on each stage of
this process, including input on the ultimate selection of topics and indicators presented in
ACES.3'4 Independent external peer reviewers provided their opinions to EPA regarding the
suitability of the indicators and other information provided for each topic. EPA revised the
report based on the peer review comments, and comments received from the public.
1 See "What is known about the role of the environment in contributing to adverse children's health outcomes?"
below for more information.
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Selection of a topic for inclusion in ACE depended, in part, on whether data appropriate for
indicator development were available. Available databases were considered in the context of
the following:
• Relevance to the topic of interest.
• Degree to which scientifically sound data collection methodologies and quality assurance
procedures were used.
• Availability of data documentation.
• Availability of raw data (individual measurements or survey responses).
• Degree to which the database can be used to characterize national patterns.
• Ongoing (continuous or periodic) data collection, with relatively recent data available.
• Comparability of target population, sample selection, and data collection methods across
time.
• Ability to stratify data by race/ethnicity, income, and location (region, state, county, or
other geographic unit).
The suitability of each database was determined through an overall weighing of these
considerations. Some databases ranked comparatively better than others with respect to each
of these considerations. For example, some databases contain the results of nationally
representative surveys that cannot be stratified geographically but are excellent in other
respects; inability to extract statistics for regions, states, or other geographic divisions does not
preclude the use of these databases in ACES. Similarly, some monitoring data sets are not
explicitly designed to be nationally representative; however, they may still be informative as
long as their limitations are understood.
ACES presents one or more indicators to illustrate status and/or trends for each selected topic
with a suitable database. In some cases, a topic is represented with multiple indicators that
portray different aspects of the underlying data or make use of different types of data.
Considerations that EPA used in developing specific indicators from each selected database
include some of the same factors used in selecting the database, as well as others, including:
• Utility of the indicator for portraying some aspect of children's environmental health.
• Sensitivity to changes in the condition of interest.
• Robustness (unaffected by changes in factors not relevant to the condition of interest).
• Degree to which the indicator offers an appropriate summary of the underlying data.
• Ability to be presented as population-based statistic (for example, the indicator takes the
form of "percentage of children affected," or as defined points in the population.
distribution of values, such as medians), particularly a national population-based statistic.
• Clarity.
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Indicators that do not satisfy all considerations may still be considered suitable; for example,
some indicators may lack data for presenting a trend over a number of years, but present useful
information for some relatively recent time period (a single year or set of years). To help guide
reader evaluations, text boxes are provided that summarize the characteristics of the data used
for each indicator.
What are the sources of data for the indicators in America's Children and the
Environment?
Federal agencies provided the data for most of the indicators. Data for the Environments and
Contaminants indicators are generally from data systems maintained by EPA and by state
environmental agencies. Data on indoor lead hazards are from surveys conducted by the U.S.
Department of Housing and Urban Development. Pesticide residue data are from the Pesticide
Data Program of the U.S. Department of Agriculture. Health and biomonitoring data are from
the National Center for Health Statistics in the Centers for Disease Control and Prevention.
Cancer data are from the National Cancer Institute. Child population data from the Census
Bureau were used for calculations in several of the Environments and Contaminants indicators.
Data for the Supplementary Topics measures are from more targeted data collection efforts
that illustrate some aspect of a children's environmental health issue of interest in the absence
of a more comprehensive data source. Childcare facility measures are derived from a national
study, and a study performed in North Carolina and Ohio. For schools, a measure on indoor
pesticide application is derived from data reported by California schools and collected by the
California Department of Pesticide Regulation. The data on birth defects are from the Texas
birth defects monitoring program. Data from individual states are not intended to describe
national conditions or conditions in other states.
What years are included in the America's Children and the Environment
indicators?
ACES aims to include indicators that present trends over at least the past 10 years; however, for
some indicators, data are not available for this length of time. When sufficient data are not
available to show changes over time, indicators present the most current data available,
frequently focusing the presentation on demographic comparisons of race/ethnicity and
income. Some topics include both a trend indicator and a separate indicator with demographic
comparisons using current data.
All ACES indicators incorporate the most current data that were available at the time of analysis.
For some indicators, additional data were released prior to the publication of ACES. Newer data
will be incorporated for the indicator updates provided online at www.epa.gov/ace.
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What groups of children are included in the America's Children and the
Environment indicators?
Census Bureau data indicate that there were 74.2 million children ages 17 years and younger in
the United States in 2010. The age range used for each indicator depends on data availability
and the nature of the topic being addressed. Each indicator clearly identifies the age range in
the title of the figure.
ACES presents (where possible) indicators for groups of children of different races and
ethnicities and for children living in households with various levels of income. In some cases,
these breakouts by race/ethnicity and family income are shown in the graphs, while in other
cases they are included in the data tables.
The specific race/ethnicity categories used for each indicator depend on the underlying data
source, and are further discussed in the introduction to each section of the report.
Many of the indicators also provide separate indicator values for children living in homes with
family income below the poverty level (shown in graphs and tables as < Poverty) and those in
homes at or above the poverty level (> Poverty). "Poverty level" is defined by the federal
government and is based on income thresholds that vary by family size and composition. In
2010, for example, the poverty threshold was $22,113 for a household with two adults and two
related children.5 Based on this federal definition, 22% of children were living below poverty
level in 2010, an increase from 18% of children in 2007.6
Why does America's Children and the Environment compare indicator values
by race/ethnicity and income?
Under Executive Order 12898,7 EPA (along with other federal agencies) is directed to "make
achieving environmental justice part of its mission by identifying and addressing, as
appropriate, disproportionately high and adverse human health or environmental effects of its
programs, policies, and activities on minority populations and low-income populations."
Comparing indicator values across these demographic groups helps identify differences in the
distributions of exposures and health outcomes, which are factors in investigating the potential
for disproportionate impacts.
Comparing indicator values by demographic groups is also in keeping with the goals of Healthy
People 2020, the federal government's program of objectives for improving the health of all
Americans. Among the overarching goals of Healthy People 2020 are to "achieve health equity,
eliminate disparities, and improve the health of all groups" and to "create social and physical
environments that promote good health for all."8 Healthy People 2020 defines a health
disparity as "a particular type of health difference that is closely linked with social, economic,
and/or environmental disadvantage. Health disparities adversely affect groups of people who
have systematically experienced greater obstacles to health based on their racial or ethnic
group; religion; socioeconomic status; gender; age; mental health; cognitive, sensory, or
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physical disability; sexual orientation or gender identity; geographic location; or other
characteristics historically linked to discrimination or exclusion."9 Presentation of ACE indicator
values by race/ethnicity and income groups provides information useful for investigating
possible health disparities and possible environmental contributors to health disparities.
Additionally, EPA's regulations implementing Title VI of the Civil Rights Act state, in part, "No
person shall be excluded from participation in, be denied the benefits of, or be subjected to
discrimination under any program or activity receiving EPA assistance on the basis of race,
color, [or] national origin" (40 C.F.R. 7.30). Where comparison data are available on a state-
specific basis, it may help EPA and its assistance recipients (for example, state environmental
agencies) assess whether discriminatory impacts are occurring.
What information is presented for each topic and indicator?
Presentation of each topic includes a discussion of the scope of the issue and a brief snapshot
of the relevant scientific literature regarding associations between exposures and health
effects. If an authoritative source has published conclusions regarding the strength of evidence
relevant to the topic, such as a determination of a cause-effect relationship between exposure
and outcome, these findings are summarized. In the absence of such a source, the discussion
describes selected literature and highlights significant sources of uncertainty, but this review
should not be considered either an evaluation of the available literature or a statement
regarding the strength of the evidence.
This is followed by an explanation of the indicator chosen to represent the topic, including a
discussion of the data source, a description of the data provided in the indicator, and
information to aid in interpreting the indicator, including data limitations.
Following this background text, one or more indicators are provided. Each indicator is
presented in a figure. A text box is provided to help readers understand the characteristics of
the data displayed. Bullet points that highlight key data points from the indicator are included.
Appendices to the report provide data tables for each indicator. Detailed explanations of the
methods for calculating each indicator are provided in the online materials available at
www.epa.gov/ace.
What is known about the role of environmental exposures in contributing to
adverse children's health outcomes?
Some environmental exposures have a well-established cause-effect relationship with
children's health, such as effects of lead exposure on childhood IQ and effects of certain air
pollutants on respiratory outcomes. For some other environmental exposures, there is
evidence suggestive of a relationship to children's health outcomes but not enough evidence to
conclude the existence of a cause-effect relationship; and for many other environmental
exposures there is very little information on potential health consequences of the exposure
levels typically experienced by children in the United States. Furthermore, for many of the
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children's health effects discussed in this report, our scientific knowledge regarding causes is
somewhat limited.
A major focus of environmental health research is to expand our understanding of the possible
role of environmental contaminant exposures, as well as other environmental risk factors, in
childhood diseases and disorders. Research is increasingly pointing to interactions of genetic
factors and environmental factors as critical to the process for most diseases.
Even when a clear relationship between exposure to a particular hazardous environmental
contaminant or factor has been documented, some children will have worse outcomes and
others will be unaffected or have outcomes that are less severe. Exposure characteristics—such
as the length of exposure, the magnitude of the exposure, the route of exposure and the
developmental stage when a child is exposed—explain much of the variation in outcome.
However, genetic variability in the population can mean that individuals vary greatly in how
their body metabolizes a chemical and in their susceptibility to diseases that may result from an
environmental exposure. In addition, variability in concurrent or prior exposures to other
environmental contaminants and to non-chemical stressors can also lead to substantial
variability of outcomes within an exposed population.10
A child's genetic inheritance can often play an important role in disease. However, as scientific
methods for examining the role of genetics in disease have advanced, it has become clear that
much of human chronic disease cannot be explained by genetic factors alone, and that
environmental factors (broadly defined to include nutrition, exercise, exposures to
environmental contaminants, and other factors) and their interactions with genetic factors also
play an important role in chronic disease.11"13
The effects of an environmental exposure on children's health often depend on the
developmental stage at which the exposure occurs. Different organ systems in a child's body go
through critical developmental stages at different times, from conception through the entire
period of fetal development, in infancy and early childhood, and continuing through
adolescence. Some chemical exposures can result in adverse effects if they occur during a
particular critical window, and may have different effects or no effect at all when occurring at a
different stage of development.14 For this reason, even some environmental exposures to
adults can be important for children's health, as research has found that the prenatal period is
the most sensitive developmental stage for adverse effects of some chemicals.15 In some cases,
the effects of a harmful exposure may not become evident until many years later; exposure
during early developmental stages may even contribute to the onset of chronic diseases in
adulthood.15
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About this Report
What types of scientific studies provide evidence about the potential
relationships between environmental exposures and children's health
outcomes?
Developing conclusive evidence that environmental factors cause or contribute to the incidence
of childhood health effects is difficult. Many health outcomes are hypothesized to be multi-
factorial, with contributions from genetics, underlying health conditions, and lifestyle, as well as
the social and physical environment. Scientific evidence linking the environment to health
outcomes consists primarily of laboratory assays, experimental studies in animals, and
epidemiological studies in humans. Each of these methods has limitations, but together they
can provide complementary evidence in assessing how exposures can influence the
development of health outcomes.
A major advantage of animal studies is that they are controlled experiments in which exposures
are imposed upon the study subjects and all other variables are held constant. In many cases,
animals can provide good models of human physiological systems and thus indicate how
humans might respond to exposures. However, it is not always straightforward to interpret
findings of animal studies and their meaning or importance for human health. Furthermore,
animal studies are often conducted using exposure levels much greater than those typically
experienced by humans, and some uncertainty exists as to whether the same effects would be
seen at lower exposure levels.
In contrast, observational epidemiological studies are advantageous because they evaluate the
relationship between environmental conditions and health outcomes in exposed human
populations. Since this type of study is not a controlled experiment, there may be factors
related to both the exposure and the health effect in the study population that can create false
associations, or mask true associations, between the exposure and the health effect.
Observational epidemiological studies provide the strongest evidence when they have been
replicated in multiple populations to minimize the likelihood that an association between
exposure and health outcomes occurred due to something other than a true causal
relationship.
Some epidemiological studies are conducted in samples of the U.S. general population, or in
other countries with similar exposure levels, and thus reflect exposures that occur on a routine
basis. Sometimes studies in the United States or in other countries may be focused on
communities that experience higher exposure levels than the rest of the country; these studies
would be considered to have greater-than-average exposures but are still within the range of
exposures occurring in the United States. In other cases, exposures in epidemiological studies
are conducted in populations with substantially higher exposure, such as workers exposed to
chemicals on the job, populations in other countries that have higher levels of pollution,
residents of communities where disasters or accidental poisoning incidents have occurred, or
populations in the United States or other industrialized countries before environmental
protection efforts to reduce exposure occurred. In such cases, some uncertainty exists as to
whether the same effects would be seen at lower exposure levels observed today.
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About this Report
An important additional consideration is the extent to which toxicological or epidemiological
studies are available for environmental contaminants and chemicals in commerce. For many
environmental exposures of interest, the epidemiological research is very limited and there are
significant gaps in the available animal testing data.
How are the findings of scientific studies regarding children's health and the
environment represented in America's Children and the Environment?
The level of knowledge regarding the relationship between environmental exposures and
health outcomes varies widely among the topics presented in this report. Some associations
between contaminants and health outcomes are supported by a large body of consistent
evidence from rigorously designed and conducted studies. In other cases, research findings may
suggest reason for potential concern but may not be sufficient to draw conclusions regarding
the nature or strength of the relationship between an environmental contaminant exposure
and a children's health outcome.
Where available, ACES relies on authoritative reviews of the scientific literature and reports
their conclusions regarding the strength of the evidence for a causal role of specific
environmental factors in the development of childhood diseases and disorders. Examples of
authoritative sources are the National Research Council, the Institute of Medicine, and the
National Toxicology Program." When such reviews are unavailable, selected findings from the
epidemiological literature that address the potential role of environmental factors in
contributing to an effect are summarized. Literature on animal studies is discussed in certain
cases when epidemiological data are lacking. These reviews of scientific information are
intended to summarize the concerns that have led to inclusion of the topic in this report. The
literature summaries are not intended as reviews of the literature determining the strength of
the evidence, which is an undertaking beyond the scope of this report.
How are children's environmental health indicators different from
epidemiological research?
The presentation of children's environmental health indicators in ACES is intended to
highlight issues of interest, describe indicator values over time, and describe indicator values
for different demographic groups. However, the indicators themselves are not intended as a
basis for reaching conclusions that an environmental factor is or is not related to a particular
children's health outcome. Comparison of trends in Health indicators to trends in
Environments and Contaminants or Biomonitoring indicators may suggest hypotheses for
further research, but their presentation here cannot be used to conclude that a causal
" The National Research Council and the Institute of Medicine are private, nonprofit institutions that provide expert
advice on science and health matters. The National Toxicology Program, part of the U.S. Department of Health and
Human Services, provides evaluations of substances of public health concern.
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About this Report
relationship may or may not exist. Indicators cannot account for the multiple factors that
should inform these judgments.
Epidemiological studies can be designed that consider both individual-level or community-
level exposures (or surrogates for exposures) and outcomes within the same population,
along with other factors such as the timing of exposure relative to the timing of outcome,
related variables that could influence the health outcome, and appropriate statistical models
of a hypothesized relationship.
ACES indicators do not incorporate these factors, and thus are not intended as a basis for
conclusions about associations between exposures and outcomes. Rather, the value of
indicators is in their ability to reveal trends (or absence of trends) and variations (or lack of
variation) within the population, which can then be used to identify areas for closer review.
Since they are based on ongoing data collection programs, the indicators can be updated
regularly and can be used to alert policy makers and the public when unexpected patterns
emerge from new data, or to provide an indication of whether recently adopted exposure
reduction interventions and actions are having an impact.
What is the difference between this report and an EPA risk assessment?
Human health risk assessment is the process used to estimate the nature and probability of
adverse health effects in populations who may be exposed to chemicals. A risk assessment
typically focuses in depth on a particular environmental contaminant to identify potential
adverse health outcomes, likely exposure pathways, the estimated magnitude of exposure,
and the likelihood of health outcomes occurring at different levels of exposure experienced
by a population.
The indicators in this report do not constitute a risk assessment. The indicators present
observed data on status and trends in environmental conditions, biomonitoring, and health
outcomes; they do not attempt to provide the information relating exposures and outcomes
provided in a risk assessment. The scope of a risk assessment involves a much more detailed
examination of the health effects literature and of exposure data, including estimation of the
relationship between particular levels of exposure and potential outcomes. The indicators in
this report should not be construed to indicate the level of risk to children's health from
exposures to environmental contaminants.
More information about risk assessment may be found at EPA's Risk Assessment Portal at
http://www.epa .gov/risk_assessment/.
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Key Findings
Key Findings
These Key Findings summarize the observations obtained from each of the indicators presented
in this report. Statistically significant trends or differences are identified by the terms "increase/'
"decrease," "higher," or "lower." Please see the body of the report for background helpful in
understanding and interpreting each of these findings, including definitions, descriptions of data
sets, and summaries of relevant scientific findings. The years for which data are available varies
across the indicators.
The evidence of a relationship between environmental exposure and children's health continues
to evolve for many of the indicators presented in this report. Inclusion of an indicator in this
report does not necessarily imply a known relationship between environmental exposure and
children's health effect.
Environments and Contaminants
Criteria Air Pollutants
• From 1999 to 2009, the proportion of children living in counties with measured pollutant
concentrations above the levels of one or more national ambient air quality standards
decreased from 75% to 59%. This includes both concentrations above the level of any
current short-term standard at least once during the year as well as average concentrations
above the level of any current long-term standards.
• In 2009, 6% of children lived in counties with measured ozone concentrations above the
level of the 8-hour ozone standard on more than 25 days. An additional 3% of children lived
in counties with measured concentrations above the level of the ozone standard between
11 and 25 days, and 12% of children lived in counties where concentrations were above the
level of the standard between 4 and 10 days.
• In 2009,1% of children lived in counties with measured fine particle (PIV^.s) concentrations
above the level of the 24-hour PM2.5 standard on more than 25 days. An additional 2% of
children lived in counties with measured concentrations above the level of this standard
between 11 and 25 days, and 1% of children lived in counties with measured concentrations
above the level of the 24-hour PM2.5 standard between 8 and 10 days.
• Based on categories from EPA's Air Quality Index, the percentage of children's days that
were designated as having "unhealthy" air quality decreased from 9% in 1999 to 3% in
2009. The percentage of children's days with "good" air quality increased from 41% in 1999
to 57% in 2009. The percentage of children's days with "moderate" air quality was
approximately constant at 21-23% from 1999 to 2007, and then decreased to 16% in 2009.
Hazardous Air Pollutants
• In 2005, nearly all children (99.9%) lived in census tracts in which hazardous air pollutant
(HAP) concentrations combined to exceed the l-in-100,000 cancer risk benchmark. Seven
percent of children lived in census tracts in which HAPs combined to exceed the l-in-10,000
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Key Findings
cancer risk benchmark. Fifty-six percent of children lived in census tracts in which at least
one HAP exceeded the benchmark for health effects other than cancer.
Indoor Environments
• In 2010, 6% of children ages 0 to 6 years lived in homes where someone smoked regularly,
compared with 27% in 1994.
• In 2005-2006,15% of children ages 0 to 5 years lived in homes with either an interior lead
dust hazard or an interior deteriorated lead-based paint hazard, compared with 22% in
1998-1999.
Drinking Water Contaminants
• The estimated percentage of children served by community drinking water systems that did
not meet all applicable health-based standards was 19% in 1993 and about 5% in 2001.
Since 2002, this percentage has fluctuated between 7% and 13%, with the most recent
estimate being 7% in 2009.
• Between 1993 and 2009, the estimated percentage of children served by community water
systems that had at least one monitoring and reporting violation fluctuated between about
11% and 23%, and was 13% in 2009.
Chemicals in Food
• In 1999, 81% of sampled apples had detectable organophosphate pesticide residues, and in
2009, 35% had detectable residues. In 2000, 10% of sampled carrots had detectable
organophosphate pesticide residues, and in 2007, 5% had detectable residues. In 2000, 21%
of sampled grapes had detectable organophosphate pesticide residues, and in 2009, 8% had
detectable residues. In 1998, 37% of sampled tomatoes had detectable organophosphate
pesticide residues, and in 2008, 9% had detectable residues.
Contaminated Lands
• As of 2009, approximately 6% of all children in the United States lived within one mile of a
Corrective Action or Superfund site that may not have had all human health protective
measures in place.
• Approximately 21% of all children living within one mile of a Corrective Action or Superfund
site that may not have had all human health protective measures in place were Black, while
15% of children in the United States as a whole are Black.
Biomonitoring
Lead
• The median concentration of lead in the blood of children between the ages of 1 and 5
years dropped from 15 micrograms per deciliter (u.g/dL) in 1976-1980 to 1.2 u.g/dL in 2009-
2010, a decrease of 92%. At the 95th percentile, blood lead levels dropped from 29 u.g/dL in
1976-1980 to 3.4 ug/dL in 2009-2010, a decrease of 88%.
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Key Findings
• The median blood lead level in Black non-Hispanic children ages 1 to 5 years in 2007-2010
was 1.6 |-ig/dL, higher than the level of 1.2 u.g/dL in White non-Hispanic children, Mexican-
American children, and children of "All Other Races/Ethnicities."
Mercury
• The median concentration of total mercury in the blood of women ages 16 to 49 years has
shown little change between 1999-2000 and 2009-2010, and was 0.8 micrograms per liter
(ug/L) in 2009-2010.
• Among women in the 95th percentile of exposure, the concentration of total mercury in
blood decreased from 7.4 u.g/L in 1999-2000 to 3.7 u.g/L in 2001-2002. From 2001-2002 to
2009-2010, the 95th percentile of total blood mercury remained between 3.7 and 4.5 u.g/L.
Cotinine
• The median level of cotinine (a marker of exposure to environmental tobacco smoke)
measured in blood serum of nonsmoking children ages 3 to 17 years dropped from 0.25
nanograms per milliliter (ng/mL) in 1988-1991 to 0.03 ng/mL in 2009-2010, a decrease of
88%. Cotinine values at the 95th percentile decreased by 34% from 1988-1991 to 2009-2010.
• The median level of cotinine measured in blood serum of nonsmoking women ages 16 to 49
years dropped from 3.2 ng/mL in 1988-1991 to 2.1 ng/mL in 2009-2010, a decrease of 86%.
Cotinine values at the 95th percentile decreased by 35% from 1988-1991 to 2009-2010.
Perfluorochemicals (PFCs)
• Between 1999-2000 and 2007-2008, median blood serum levels of perfluorooctane
sulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) in women ages 16 to 49 years
showed a decreasing trend; median levels of perfluorononanoic acid (PFNA) showed an
increasing trend; and median levels of perfluorohexane sulfonic acid (PFHxS) remained
relatively constant over time.
Polychlorinated Biphenyls (PCBs)
• In 2001-2004, the median level of polychlorinated biphenyls (PCBs), summing together four
selected PCBs, in blood serum of women ages 16 to 49 years was 30 nanograms per gram
(ng/g) lipid. Data are not yet available for comparing these PCB levels over time.
Polybrominated Diphenyl Ethers (PBDEs)
• The median concentration of polybrominated diphenyl ethers (PBDEs) in blood serum of
women ages 16 to 49 years was 44 ng/g lipid in 2003-2004. Data are not yet available for
comparing these PBDE levels over time.
Phthalates
• From 2001-2002 to 2007-2008, the median level of di-2-ethylhexyl phthalate (DEHP)
metabolites in urine of women ages 16 to 49 years varied between 41 u.g/L and 51 u.g/L, and
was 51 u.g/L in 2007-2008. From 1999-2000 to 2007-2008, the median level of dibutyl
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Key Findings
phthalate (DBF) metabolites in women ages 16 to 49 years varied between 27 u.g/L and 36
u.g/L, and was 36 u.g/L in 2007-2008. From 1999-2000 to 2007-2008, the median level of
butyl benzyl phthalate (BBzP) metabolites in women ages 16 to 49 years varied between 10
u.g/L and 14 u.g/L, and was 12 u.g/L in 2007-2008.
• From 2001-2002 to 2007-2008, the median level of DEHP metabolites in urine of children
ages 6 to 17 years varied between 45 u.g/L and 62 u.g/L, and was 45 u.g/L in 2007-2008.
From 1999-2000 to 2007-2008, the median level of DBF metabolites in children ages 6 to
17 years varied between 36 u.g/L and 42 u.g/L, and was 41 u.g/L in 2007-2008. The median
level of BBzP metabolite in children ages 6 to 17 years decreased from 25 u.g/L in 1999-
2000 to 16 ug/L in 2007-2008.
Bisphenol A (BPA)
• From 2003-2004 to 2009-2010, the median concentration of bisphenol A (BPA) in urine
among women ages 16 to 49 years varied between 2 u.g/L and 3 u.g/L. From 2003-2004 to
2009-2010, the concentration of BPA in urine at the 95th percentile varied between 10 u.g/L
and 16 u.g/L, and was 10 u.g/L in 2009-2010.
• Among children ages 6 to 17 years the median concentration of BPA in urine decreased
from 4 u.g/L in 2003-2004 to 2 u.g/L in 2009-2010. The concentrations of BPA in urine at the
95th percentile decreased from 16 ug/L in 2003-2004 to 10 u.g/L 2009-2010.
Perchlorate
• From 2001-2002 to 2007-2008, the median level of perchlorate in urine among women
ages 16 to 49 years was 3 u.g/L with little variation over time. Over the same period, the 95th
percentile varied between 13 and 17 u.g/L.
Health
Respiratory Diseases
• The proportion of children reported to currently have asthma has increased from 8.7% in
2001 to 9.4% in 2010.
• In 2007-2010, the percentages of Black non-Hispanic children and children of "All Other
Races" reported to currently have asthma, 16.0% and 12.4% respectively, were greater than
for White non-Hispanic children (8.2%), Hispanic children (7.9%), and Asian non-Hispanic
children (6.8%).
• The rate of emergency room visits for asthma decreased from 114 visits per 10,000 children
in 1996 to 103 visits per 10,000 children in 2008. Between 1996 and 2008, hospitalizations
for asthma and for all other respiratory causes decreased from 90 hospitalizations per
10,000 children to 56 hospitalizations per 10,000 children.
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Key Findings
Childhood Cancer
• The age-adjusted annual incidence of cancer increased from 1992-2009. The incidence
ranged from 153 to 161 cases per million children between 1992 and 1994 and from 172 to
175 cases per million children between 2007 and 2009.
• Childhood cancer mortality has decreased from 33 deaths per million children in 1992 to 24
deaths per million children in 2009.
• Leukemia was the most common cancer diagnosis for children from 2004-2006,
representing 28% of total cancer cases. Incidence of acute lymphoblastic (lymphocytic)
leukemia increased from 30 cases per million in 1992-1994 to 35 cases per million in 2004-
2006. The rate of acute myeloid (myelogenous) leukemia was 7 cases per million in 1992-
1994 and 9 cases per million in 2004-2006.
Neurodevelopmental Disorders
• From 1997 to 2010, the proportion of children ages 5 to 17 years reported to have ever
been diagnosed with attention-deficit/hyperactivity disorder (ADHD) increased from 6.3%
to 9.5%.
• In 2010, 8.6% of children ages 5 to 17 years had ever been diagnosed with a learning
disability. There was little change in this percentage between 1997 and 2010.
• The percentage of children ages 5 to 17 years reported to have ever been diagnosed with
autism increased from 0.1% in 1997 to 1.0% in 2010.
• In 2010, 0.7% of children ages 5 to 17 years were reported to have ever been diagnosed
with intellectual disability (mental retardation). There was little change in this percentage
between 1997 and 2010.
Obesity
• Between 1976-1980 and 2007-2008, the percentage of children identified as obese showed
an increasing trend. In 1976-1980, 5% of children ages 2 to 17 years were obese. This
percentage reached a high of 17% in 2007-2008. Between 1999-2000 and 2007-2008, the
percentage of children identified as obese remained between 15% and 17%.
• In 2005-2008, a higher percentage of Mexican-American and Black non-Hispanic children
were obese at 22% and 20%, respectively, compared with 14% of White non-Hispanic
children and 14% of children of "All Other Races/Ethnicities."
Adverse Birth Outcomes
• Between 1993 and 2008, the rate of preterm birth showed an increasing trend, ranging
from 11.0% in 1993 to its highest value of 12.8% in 2006.
• Between 1993 and 2008, the rate of term low birth weight for all races/ethnicities stayed
relatively constant, ranging between 2.5% and 2.8%.
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Key Findings
Supplementary Topics
The Supplementary Topics section presents topics for which adequate national data are not
available, but for which more targeted data collection efforts could be used to provide measures
illustrating additional children's environmental health issues of interest. Data sets used for these
measures are representative of particular locations (such as a single state) and/or were surveys
conducted a single time rather than on a continuing or periodic basis. Since these data sets are
lacking in certain key elements desirable for ACES indicators, data presentations for the
Supplementary Topics are referred to as "measures" rather than "indicators."
Birth Defects
• The rates for all categories of birth defects in Texas have increased or remained stable for
the period of 1999-2007. Some of the biggest increases were seen for musculoskeletal
defects, cardiac and circulatory defects, genitourinary defects, eye and ear defects, and
central nervous system defects.
Contaminants in Schools and Child Care Facilities
• The pesticides chlorpyrifos, c/s-permethrin, and diazinon were detected in all dust samples
collected at Ohio and North Carolina child care centers in 2000-2001. Chlorpyrifos and
diazinon were also detected in all indoor air samples collected at these child care centers.
• Dibutyl phthalate was detected in all indoor air and dust samples collected at Ohio and
North Carolina child care centers.
• Pyrethrin and pyrethroid insecticides accounted for the greatest volume of pesticide use in
California schools overall from 2002 to 2007.
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Environments and
Contaminants
Criteria Air Pollutants
Hazardous Air Pollutants
Indoor Environments
Drinking Water Contaminants
Chemicals in Food
Contaminated Lands
Climate Change
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Environments and Contaminants | Introduction
Introduction
Why is EPA tracking levels of contaminants and other aspects of children's
environments in America's Children and the Environment?
Pollutants or contaminants that can affect the health of children can be found in air, water, food,
and soil. This section describes contaminants in the air children breathe, the water they drink,
and the food they eat. This section also addresses the conditions of children's environments by
considering indoor environments, contaminated lands, and climate change. Trends over time can
indicate the successes and shortcomings of efforts to reduce potential exposures and also identify
opportunities for future action. Differences in the environmental conditions between geographic
areas or demographic groups can inform more targeted actions.
What Environments and Contaminants topics are included in America's
Children and the Environment, Third Edition (ACE3)7
Environments and Contaminants topics were selected for ACES based on: (1) research findings
identifying environmental contaminants or characteristics that may have adverse effects on
children's health; and (2) the availability of data suitable for constructing a national indicator.
EPA obtained input from its Children's Health Protection Advisory Committee to assist in
selecting topics from among the many contaminants and other aspects of the environment that
may affect children's health. The ACES Environments and Contaminants indicators address the
following topics:
• Criteria air pollutants
• Hazardous air pollutants
• Indoor environments
• Drinking water contaminants
• Chemicals in food
• Contaminated lands
• Climate change1
Data for all of the Environments and Contaminants indicators were obtained from surveys and
databases maintained by U.S. government agencies. These include the Air Quality System
(Environmental Protection Agency, EPA); National Air Toxics Assessment (EPA); National Health
Interview Survey (National Center for Health Statistics ); American Healthy Homes Survey
(Housing and Urban Development, HUD); National Survey of Lead and Allergens in Housing
1 Although climate change is addressed in this section, a climate change indicator is not currently presented. EPA is
currently developing a new children's environmental health indicator for climate change. The new indicator will
focus on the frequency of extreme heat events over time. EPA intends to complete development of this new
indicator in 2014, and it will be made available at www.epa.gov/ace when completed.
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Introduction I Environments and Contaminants
(HUD); Safe Drinking Water Information System (EPA); Pesticide Data Program (U.S.
Department of Agriculture); Comprehensive Environmental Response, Compensation, and
Liability Information System (EPA); and the Resource Conservation and Recovery Act
Information dataset (EPA). Although all of the data sources feature data collected across the
United States, some are not designed to produce estimates describing the nation overall. These
and other data limitations are described for each indicator presented. However, targeted
samples can provide important insight into environmental conditions and lead to improved
measurement over time.
Other environmental hazards that may potentially be of concern for children's health are not
addressed in this section. Examples of these additional environmental hazards include
contaminants in surface waters, ionizing radiation, and chemicals that may be present in parks
and playgrounds.
What can we learn from the Environments and Contaminants indicators?
For some of the selected Environments and Contaminants topics, health-based standards have
been established. By comparing data on contaminant levels against these standards, which
often include a margin of safety, it is possible to determine the percentage of children living in
areas where standards or targeted levels have been exceeded. For topics where health-based
standards do not exist, indicator values may still summarize conditions over time or the
conditions of different groups of children, such as by race/ethnicity or income level.
It is important to realize that children may be exposed to the same contaminant through a
variety of sources and pathways. For example, children can be exposed to lead by ingesting
dust, consuming drinking water, and breathing air that contains lead. Each Environments and
Contaminants indicator shown here only informs our understanding of potential exposure from
a single pathway. A separate Biomonitoring section of ACES presents indicators that report
levels of selected chemicals measured in blood and urine samples. The biomonitoring approach
provides an integrated measure of exposure from all possible sources and pathways. However,
biomonitoring data are not available for all chemicals and contaminants represented in the
Environments and Contaminants indicators. The Environments and Contaminants indicators
and the Biomonitoring indicators are complementary in that they represent different types of
information about children's potential environmental exposures.
What information is provided for each Environments and Contaminants topic?
An introduction section defines the topic and describes its relevance to children's health,
including a discussion of potential health concerns associated with exposures to the
contaminants or environmental conditions. The introduction is followed by a description of the
indicators, including a summary of the data available and a brief description of how each
indicator was calculated. One to three indicators, each a graphical presentation of the available
data, are included for each topic. Most of the indicators present time series data. Where data
over time are unavailable, the indicators present data for the most recent year available. Where
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Environments and Contaminants | Introduction
possible, the indicators incorporate information on race/ethnicity and income level. Beneath
each figure are explanatory bullet points highlighting key findings from the data presented in
the figure, along with key data from any supplemental data tables. References are provided for
each topic at the end of the report.
Data tables are provided in Appendix A. The tables include all indicator values depicted in the
indicator figures, along with additional data of interest not shown in the figures. Metadata
describing the data sources are provided in Appendix B. Documents providing details of how
the indicators were calculated are available on the ACE website (www.epa.gov/ace).
Many of the topics presented in the Environments and Contaminants indicators are addressed in
Healthy People 2020, which provides science-based, 10-year national objectives for improving
the health of all Americans. Appendix C provides examples of the alignment of the Environments
and Contaminants topics presented in ACES with objectives in Healthy People 2020.
How were the indicators calculated and presented?
Data files: The indicators were calculated using data files obtained from the government agency
websites or from government agency staff.
Population age groups: Most of the indicators used data for children ages 17 years and
younger. The indicators for indoor environments were restricted to younger ages because
younger children have been specifically identified as more susceptible to the effects of tobacco
smoke and lead exposure. The indicator for environmental tobacco smoke (E5) used data for
children ages 0 to 6 years. The indicator for interior lead hazards (E6) used data for children
ages 0 to 5 years.
Calculation of percentages: For most of the Environments and Contaminants topics, information
on environmental contaminants/characteristics was used to identify counties where one or
more environmental contaminants were above target levels established for the indicator. For
example, the calculation of percentages in Indicator El involved identifying counties with at least
one air pollutant measurement above the level of a National Ambient Air Quality Standard. The
population of children in counties with an environmental contaminant above the target level
was then calculated using census data, and divided by the total population of children to derive
the indicator value as a percentage of all children in the United States.
For the indoor environments topics, survey data were obtained from representative samples of
people (to estimate the percentage of children in homes with regular exposure to
environmental tobacco smoke) and homes (to estimate the percentage of children in homes
with lead hazards). Sample weights equal to the number of children in the U.S. population
represented by each sampled child were applied to yield estimates representing the U.S.
population of children. The indicator on chemicals in food reports the percentage of samples of
selected foods with detectable levels of pesticides.
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Introduction I Environments and Contaminants
Statistical testing: Statistical analysis has been applied to the two indicators derived from
probability-based sample data (the indoor environments indicators for environmental tobacco
smoke and lead) to evaluate differences over time or between demographic groups. Statistical
analysis has also been applied to the criteria pollutants data to evaluate trends over time. The
remaining environment and contaminant indicators do not readily lend themselves to statistical
analysis, due to the characteristics of the underlying databases."
" Standard errors for the indoor environments indicator values, which are derived from survey data, are provided
in a file available on the ACE website (www.epa.gov/ace). Standard errors could not be calculated for the
remaining Environments and Contaminants indicators.
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Environments and Contaminants | Criteria Air Pollutants
Criteria Air Pollutants
Air pollution contributes to a wide variety of adverse health effects. EPA has established
national ambient air quality standards (NAAQS) for six of the most common air pollutants-
carbon monoxide, lead, ground-level ozone, particulate matter, nitrogen dioxide, and sulfur
dioxide—known as "criteria" air pollutants (or simply "criteria pollutants"). The presence of
these pollutants in ambient air is generally due to numerous diverse and widespread sources of
emissions. The primary NAAQS are set to protect public health. EPA also sets secondary NAAQS
to protect public welfare from adverse effects of criteria pollutants, including protection against
visibility impairment, or damage to animals, crops, vegetation, or buildings.
As required by the Clean Air Act,1 EPA periodically conducts comprehensive reviews of the
scientific literature on health and welfare effects associated with exposure to the criteria air
pollutants.2"7 The resulting assessments serve as the basis for making regulatory decisions
about whether to retain or revise the NAAQS that specify the allowable concentrations of each
of these pollutants in the ambient air.8
The primary standards are set at a level intended to protect public health, including the health
of at-risk populations, with an adequate margin of safety. In selecting a margin of safety, EPA
considers such factors as the strengths and limitations of the evidence and related
uncertainties, the nature and severity of the health effects, the size of the at-risk populations,
and whether discernible thresholds have been identified below which health effects do not
occur. In general, for the criteria air pollutants, there is no evidence of discernible thresholds.2"7
The Clean Air Act does not require EPA to establish primary NAAQS at a zero-risk level, but
rather at a level that reduces risk sufficiently so as to protect public health with an adequate
margin of safety. In all NAAQS reviews, EPA gives particular attention to exposures and
associated health risks for at-risk populations. Standards include consideration of providing
protection for a representative sample of persons comprising at-risk populations rather than to
the most susceptible single person in such groups. Even in areas that meet the current
standards, individual members of at-risk populations may at times experience health effects
related to air pollution.9"13
Childhood is often identified as a susceptible lifestage in the NAAQS reviews, because children's
lungs and other organ systems are still developing, because they may have a preexisting disease
(e.g., asthma), and because they may experience higher exposures due to their activities,
including outdoor play.14"17 Evaluating the effects of criteria air pollutants in children has been a
central focus in several recent NAAQS reviews, including revisions of the lead,18 ozone,19 and
particulate matter20 standards to strengthen public health protection.
Some of the air quality standards are designed to protect the public from adverse health effects
that can occur after being exposed for a short time, such as hours to days. Other standards are
designed to protect people from adverse health effects that are associated with long-term
exposures (months to years). For example, the standard for ozone is based on pollutant
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concentrations measured over a short-term period of eight hours. By contrast, the standard for
lead considers average concentrations measured over a rolling three-month period. For fine
particulate matter (PIV^.s), annual and 24-hour standards work together to provide protection
against effects associated with long- and short-term exposures.
Health effects that have been associated with each of the criteria pollutants are summarized
below. This information is drawn primarily from EPA's assessments of the scientific literature
for the criteria pollutants.
Ozone
Ground-level ozone forms through the reaction of pollutants emitted by industrial facilities,
electric utilities, and motor vehicles; chemicals that are precursors to ozone formation can also
be emitted by natural sources, particularly trees and other plants.2 Ground-level ozone can pose
risks to human health, in contrast to the stratospheric ozone layer that protects the earth from
harmful wavelengths of solar ultraviolet radiation. Short-term exposure to ground-level ozone
can cause a variety of respiratory health effects, including inflammation of the lining of the
lungs, reduced lung function, and respiratory symptoms such as cough, wheezing, chest pain,
burning in the chest, and shortness of breath.2'13'21 Ozone exposure can decrease the capacity to
perform exercise.2 Exposure to ozone can also increase susceptibility to respiratory infection.
Exposure to ambient concentrations of ozone has been associated with the aggravation of
respiratory illnesses such as asthma, emphysema, and bronchitis, leading to increased use of
medication, absences from school, doctor and emergency department visits, and hospital
admissions. Short-term exposure to ozone is associated with premature mortality.2 Studies have
also found that long-term ozone exposure may contribute to the development of asthma,
especially among children with certain genetic susceptibilities and children who frequently
exercise outdoors.22"24 Long-term exposure to ozone can permanently damage lung tissue.
Particulate Matter
Particulate matter (PM) is a generic term for a broad class of chemically and physically diverse
substances that exist as discrete particles (liquid droplets or solids) over a wide range of sizes.
Particles originate from a variety of man-made stationary and mobile sources, as well as from
natural sources such as forest fires. Particles may be emitted directly, or may be formed in the
atmosphere by transformations of gaseous emissions such as oxides of sulfur (SOX), oxides of
nitrogen (NOX), and volatile organic compounds (VOCs). The chemical and physical properties of
PM vary greatly with time, region, meteorology, and the source of emissions. For regulatory
purposes, EPA distinguishes between categories of particles based on size, and has established
standards for fine and coarse particles. PMio, in general terms, is an abbreviation for particles
with an aerodynamic diameter less than or equal to 10 micrometers (jam), and represents
inhalable particles small enough to penetrate deeply into the lungs (i.e., thoracic particles).1
is composed of a coarse fraction referred to as PMi0-2.5 or as thoracic coarse particles (i.e.,
For comparison, the diameter of PM10 particles is 1/7 the diameter of an average human hair or less.
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particles with an aerodynamic diameter less than or equal to 10 u.m and greater than 2.5 u.m)
and a fine fraction referred to as PM2.5 or fine particles (i.e., particles with an aerodynamic
diameter less than or equal to 2.5 u.m). Thoracic coarse particles are emitted largely as a result
of mechanical processes and uncontrolled burning. Important sources include resuspended
dust (e.g., resuspended by cars, wind, etc.), industrial processes, construction and demolition
operations, residential burning, and wildfires. Fine particles are formed chiefly by combustion
processes (e.g., from power plants, gas and diesel engines, wood combustion, and many
industrial processes) and by atmospheric reactions of gaseous pollutants.
Although scientific evidence links harmful human health effects with exposures to both fine
particles and thoracic coarse particles, the evidence is much stronger for fine particles than for
thoracic coarse particles. Effects associated with exposures to both PM2.5 and PMi0-2.5 include
premature mortality, aggravation of respiratory and cardiovascular disease (as indicated by
increased hospital and emergency department visits), and changes in sub-clinical indicators of
respiratory and cardiac function. Such health effects have been associated with short- and/or
long-term exposure to PM." Exposures to PM2.5 are also associated with decreased lung
function growth, exacerbation of allergic symptoms, and increased respiratory symptoms.6
Children, older adults, individuals with preexisting heart and lung disease (including asthma),
and persons with lower socioeconomic status are considered to be among the groups most at
risk for effects associated with PM exposures.6 Information is accumulating and currently
provides suggestive evidence for associations between long-term PM2.5 exposure and
developmental effects such as low birth weight and infant mortality due to respiratory causes.6
Sulfur Dioxide
Fossil fuel combustion by electrical utilities and industry is the primary source of sulfur dioxide
in the United States.5 People with asthma are especially susceptible to the effects of sulfur
dioxide.5 Short-term exposures of asthmatic individuals to elevated levels of sulfur dioxide
while exercising at a moderate level may result in breathing difficulties, accompanied by
symptoms such as wheezing, chest tightness, or shortness of breath. Studies also provide
consistent evidence of an association between short-term sulfur dioxide exposures and
increased respiratory symptoms in children, especially those with asthma or chronic respiratory
symptoms. Short-term exposures to sulfur dioxide have also been associated with respiratory-
related emergency department visits and hospital admissions, particularly for children and
older adults.5
Nitrogen Dioxide
Nitric oxide (NO) and nitrogen dioxide (N02) are emitted by cars, trucks, buses, power plants,
and non-road engines and equipment. Emitted NO is rapidly oxidized into N02 in the
atmosphere.4 Exposure to nitrogen dioxide has been associated with a variety of health effects,
" For PM10-2.5, the evidence linking health effects to short-term (e.g., 24-hour) exposures is stronger than the
evidence for effects of long-term exposures.
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including respiratory symptoms, especially among asthmatic children, and respiratory-related
emergency department visits and hospital admissions, particularly for children and older adults.4
Lead
Historically, the major source of lead emissions to the air was combustion of leaded gasoline in
motor vehicles (such as cars and trucks). Following the elimination of leaded gasoline in the
United States by the mid-1990s, the remaining sources of lead air emissions have been industrial
sources, including lead smelting and battery recycling operations, and piston-engine small
aircraft that use leaded aviation gasoline.3 Lead accumulates in bones, blood, and soft tissues of
the body. Exposure to lead can affect development of the central nervous system in young
children, resulting in neurodevelopmental effects such as lowered IQand behavioral problems.3
Carbon Monoxide
Gasoline-fueled vehicles and other on-road and non-road mobile sources are the primary
sources of carbon monoxide (CO) in the United States.7 Exposure to carbon monoxide reduces
the capacity of the blood to carry oxygen, thereby decreasing the supply of oxygen to tissues
and organs such as the heart. People with several types of heart disease already have a reduced
capacity for pumping oxygenated blood to the heart, which can cause them to experience
myocardial ischemia (reduced oxygen to the heart), often accompanied by chest pain (angina),
when exercising or under increased stress. For these people, short-term CO exposure further
affects their body's already compromised ability to respond to the increased oxygen demands
of exercise or exertion. Thus people with angina or heart disease are identified as at greatest
risk from ambient CO. Other potentially at-risk populations include those with chronic
obstructive pulmonary disease, anemia, diabetes, and those in prenatal or elderly lifestages.7
The period of fetal development may be one of particular vulnerability for adverse health
effects resulting from maternal exposure to some criteria air pollutants. This may occur if
maternal exposure to air pollutants is transferred to the fetus during pregnancy; for example,
lead and PM have both been shown to cross the placenta and accumulate in fetal tissue during
gestation.3'6 In addition to the findings noted above regarding associations of prenatal PM
exposure and adverse birth outcomes (such as low birth weight), limited studies of prenatal
exposure to criteria air pollutants have reported that exposure to PM and oxides of nitrogen
and sulfur may increase the risk of developing asthma as well as worsen respiratory outcomes
among those children that do develop asthma.25"27 However, it is often difficult to distinguish
the effects of prenatal and early childhood exposure because exposure to air pollutants is often
very similar during both time periods.
Additional research indicates that exposure to pollution from traffic-related sources, a mix of
criteria air pollutants and hazardous air pollutants, may pose particular threats to a child's
respiratory system. Many studies have reported a correlation between proximity to traffic (or
to traffic-related pollutants) and occurrence of new asthma cases or exacerbation of existing
asthma and other respiratory symptoms, including reduced growth of lung function during
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childhood.25'28"35 A report by the Health Effects Institute concluded that living close to busy
roads appears to be an independent risk factor for the onset of childhood asthma.36 The same
report also concluded that the evidence was "sufficient" to infer a causal association between
exposure to traffic-related pollution and exacerbations of asthma in children.36 Some studies
have suggested that traffic-related pollutants may contribute to the development of allergic
disease, either by affecting the immune response directly or by increasing the concentration or
biological activity of the allergens themselves.37"39
Many of the effects of criteria air pollutants on children can be reduced by limiting outdoor
activities on high pollution days.40 Such avoidance measures can have their own adverse
impacts on children's health when they reduce opportunities for play and exercise.
The following three indicators provide different perspectives on children's exposures to criteria
air pollutants. Indicator El summarizes the percentages of children over time living in counties
where measured pollutant concentrations were above the levels of the short- and/or long-term
standards for each of the criteria air pollutants.1" Indicator E2 provides additional detail on the
frequency with which pollutant concentrations were above the levels of the ozone and 24-hour
PM2.5 standards in one year (2009). Indicator E3 focuses on the frequency with which children
were exposed to good, moderate, or unhealthy daily air quality, based on EPA's Air Quality Index.
111 For standards with averaging times less than or equal to 24 hours, Indicator El includes counties where
concentrations were above the level of the standards at least one day per year.
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Indicator El: Percentage of children ages 0 to 17 years living in counties with pollutant
concentrations above the level of the current air quality standards, 1999-2009
Indicator E2: Percentage of children ages 0 to 17 years living in counties with 8-hour
ozone and 24-hour PM2.5 concentrations above the levels of air quality standards, by
frequency of occurrence, 2009
About the Indicators: Indicators El and E2 present the percentage of children living in counties
where measured ambient concentrations of criteria pollutants were greater than the levels of the
Clean Air Act health-based standards at any time during a year. Indicator El presents results for each
criteria pollutant for each year. Indicator E2 presents more detailed information on the frequency
with which measured ambient ozone and fine particle (PM2.5) concentrations were greater than the
levels of the short-term standards for ozone and PM2.5 in 2009. The air quality data used in these
indicators are from an EPA database that compiles measurements of pollutants in ambient air from
around the country each year.
Air Quality System
State and local environmental agencies that monitor air quality submit their data to EPA. EPA
compiles the monitoring data in the national EPA Air Quality System (AQS) database.IV AQS
contains some monitoring data from the late 1950s and early 1960s, but there is not an
appreciable amount of data for lead until 1970, sulfur dioxide until 1971, nitrogen dioxide until
1974, carbon monoxide and ozone until 1975, and PMi0 until 1987. AQS also contains
monitoring data for PM2.5 beginning in 1999; PM2.5 was measured only infrequently prior to
1999. Indicators El and E2 are derived from analysis of air pollution data in AQS.
Air Quality Standards and Concentrations Above the Levels of the Standards
Under the Clean Air Act, EPA has established National Ambient Air Quality Standards (NAAQS)
for carbon monoxide, lead, ground-level ozone, particulate matter, nitrogen dioxide, and sulfur
dioxide. There are four basic elements of NAAQS that together serve to define each standard:
the definition of the pollutant/ the averaging time (e.g., annual average or 24-hour average),
the level, and the form of the standard (which defines the air quality statistic compared to the
level of the standard in determining whether an area attains the standard—for example, the
24-hour PM2.5 standard uses 98th percentile concentrations, averaged over three years). These
elements must be considered collectively in evaluating the health and welfare protection
afforded by the NAAQS.
IV Information on the AQS database is available at http://www.epa.gov/airdata/.
v In the development of NAAQS, the term "indicator" defines the chemical species or mixture that is to be
measured in determining whether an area attains the standard. To avoid confusion with the way in which
"indicator" is used throughout America's Children and the Environment, the term is not used in the following
paragraphs, except to refer to the ACE criteria pollutant indicators El, E2, and E3.
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Indicators El and E2 consider the first three elements of a NAAQS: the definition of the
pollutant, the averaging time, and the level of the standard. The indicators present percentages
of children living in areas with pollutant concentrations above the level of the current
standards, using the appropriate averaging time. The indicators do not consider the form of the
standard, which often includes considerations for multiple years of air quality data (e.g., 3
years), adjustments for missing data and less-than daily monitoring, and consideration for the
frequency and magnitude with which a standard level is exceeded. In considering the form of
the NAAQS, these standards are defined to allow some days to be above the level of the
standard while limiting the extent to which they are above the level of the standard.
Furthermore, determinations of attainment with the NAAQS are generally based on air quality
averaged over multiple years. Therefore, air quality in any one-year period, as presented in
Indicators El and E2, cannot be used to characterize whether air quality does or does not meet
the NAAQS. The analyses for Indicators El and E2 therefore differ from the analyses used by
EPA for the designation of "nonattainment areas" (locations that have not attained the
standard) for regulatory compliance purposes.41 Nonetheless, looking at air quality within a
given year, or across many individual years, provides important public health information.
For each of the years 1999-2009, Indicator El reflects comparisons of the monitoring data with
the levels of the current NAAQS. The indicator for all years therefore incorporates the 2006
revision of the level of the 24-hour PM2.5 standard20 from 65 u.g/m3 to 35 u.g/m3; the 2008
revision of the level of the eight-hour ozone standard19 from 0.08 ppm to 0.075 ppm;vl the 2008
revision of the level of the three-month standard18 for lead from 1.5 u.g/m3 to 0.15 u.g/m3; the
establishment of a new one-hour standard42 for nitrogen dioxide with a level of 100 ppb, issued
in 2010; and the establishment of a new one-hour standard43 for sulfur dioxide with a level of
75 ppb, issued in 2010. Note that EPA promulgated a revised annual PM2.5 standard in
December 2012, which has not been incorporated into this analysis. Table 1 in the Methods
documentation shows the criteria pollutant levels used for the purpose of this indicator to
determine whether concentrations were above the standard level for each pollutant/"
NAAQS are intended to provide public health protection, including providing protection for at-
risk populations, with an adequate margin of safety/1" EPA's selection of the current standards
Vl In January 2010, the EPA Administrator proposed to reconsider the ozone standard because she believed "that a
standard set as high as 0.075 would not be considered requisite to protect public health with an adequate margin
of safety, and that consideration of lower levels [was] warranted" (75 FR 2996, January 19, 2010). EPA is currently
conducting the next statutorily mandated periodic review of the ozone standards, which the Agency plans to
complete in 2014. See http://www.epa.gov/ttn/naaqs/standards/ozone/s_o3_index.html for more information on
the current and previous ozone NAAQS reviews.
v" All criteria pollutants are included in Indicator El, but for some pollutants with multiple primary standards
(reflecting different averaging times), only a single standard is included. For CO only the 8-hour standard is
included, because the 1-hour standard is rarely exceeded. For NO2 only the 1-hour standard is included, because
the annual standard is rarely exceeded.
vl" The legislative history of section 109 of the Clean Air Act indicates that a primary standard is to be set at "the
maximum permissible ambient air level... which will protect the health of an [sensitive] group of the population,"
and that for this purpose, "reference should be made to a representative sample of persons comprising the
sensitive group rather than to a single person in such a group" S. Rep. No. 91-1196, 91st Cong., 2d Sess. 10 (1970).
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for ozone, nitrogen dioxide, and sulfur dioxide were intended to protect against respiratory
effects in at-risk populations, including children. EPA's selection of the current standards for
particulate matter was based primarily on concerns for mortality and cardiovascular effects, as
well as respiratory effects. EPA's selection of the current standard for lead was intended to
reduce risks of neurodevelopmental effects in children. The standard for carbon monoxide is
intended primarily to protect against potential effects in people with heart disease. The Clean
Air Act does not require the EPA Administrator to establish a primary NAAQS at a zero-risk level
or at background concentration levels, but rather at a level that reduces risk sufficiently so as to
protect health with an adequate margin of safety. However, pollutant concentrations that are
lower than the levels of the standards are not necessarily without risk for all individuals. No
risk-free level of exposure has been determined for any of the criteria pollutants.
Data Presented in the Indicators
Indicator El presents the percentage of children living in counties with measured pollutant
concentrations above the level of a NAAQS for any of the criteria pollutants, for each year from
1999-2009.IX The indicator begins with data for 1999 because, as noted above, this was the first
year of widespread monitoring for PM2.5. In addition to presenting data for each of the criteria
pollutants separately, the indicator also presents the percentage of children living in counties
with measured concentrations above the level of a NAAQS for any criteria air pollutant (i.e.,
exceedance of standard levels for one or more criteria air pollutants).
Indicator El does not differentiate between counties in which concentrations were above
standard levels frequently or by a large margin, and areas in which concentrations were above
standard levels only rarely or by a small margin. It also assumes that air pollutant concentrations
are consistent throughout a county. Some pollutants, such as ozone and PM2.5, tend to be well
dispersed and generally have limited spatial variation within a county, whereas other pollutants
such as lead might have higher concentrations within relatively smaller areas. The indicator is
based on concentrations of individual pollutants compared with individual standard levels, and
does not reflect any combined effect of exposure to multiple criteria pollutants.
All children living in all counties are considered in the indicator; however, many counties do not
have air pollution monitors. Monitoring networks are typically designed to focus on areas that
are expected to have higher concentrations or that have larger populations. If any of the
unmonitored counties have concentrations above the levels of the NAAQS, Indicator El will
understate the percentage of children living in counties with concentrations above standard
levels. The indicator thus represents the percentage of all children who lived in counties with
confirmed pollutant concentrations above the levels of the standards each year, where
confirmation is provided by a valid monitor value in that year. The percentages of children in
unmonitored counties in 2009 range from about 30% for ozone and PM2.5 to about 50% for
lx For standards with averaging times less than or equal to 24 hours, Indicator El includes counties where
concentrations were above the level of the standards at least one day per year.
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o, carbon monoxide, sulfur dioxide and nitrogen dioxide, and about 80% for lead.x These
percentages have been fairly stable from 1999-2009, though there are some limited changes in
monitoring from year to year. Those limited changes in monitoring mean that there are some
small changes in data available for calculation of the indicator over time.
The supplemental data tables Ela and Elb show the percentage of children living in counties
with concentrations above the levels of the air quality standards in 2009 by race/ethnicity
(Table Ela) and family income (Table Elb).
Ambient concentrations were more frequently above the levels of the 8-hour ozone and the 24-
hour PM2.5 standards than the levels of the standards for other criteria pollutants. Indicator E2
provides information on the frequency with which concentrations were above the levels of
these two standards in 2009. Counties were classified by the number of days during 2009 that
measured pollutant concentrations were above the levels of the 8-hour ozone and 24-hour
PM2.5 standards. This indicator, therefore, shows the percentage of children living in counties in
which concentrations were measured above the levels of these two short-term standards a few
times, as well as the percentage in counties with more frequent measurements above the
levels of the standards. The percentage of children in counties without monitors for these two
pollutants in 2009 is also shown in Indicator E2. The data table for this indicator (Table E2) also
provides the same information for each year 1999-2009, using the current level of the
standards for each year's calculation.
Values in this indicator may be understated due to the fact that most monitors do not operate
every day. Ozone monitors operate daily during the ozone season, which lasts from 6 to 7
months in most locations but can be between 5 and 12 months (based on ranges of dates when
high temperatures associated with high ozone concentrations may occur). PM2.5 monitors
operate year round, but may collect measurements daily or every third or every sixth day. EPA
requires areas that measure concentrations within 5% of the 24-hour PM2.5 standard to monitor
daily. Monitors for other criteria pollutants operate year round.
Statistical Testing
Statistical analysis has been applied to Indicator El to evaluate trends over time in the
percentage of children living in counties with concentrations above the standard levels each
year. These analyses use a 5% significance level, meaning that a conclusion of statistical
significance is made only when there is no more than a 5% probability that the observed trend
occurred by chance (p < 0.05). The statistical analysis of trends over time is dependent on how
the annual values vary as well as on the number of annual values. For example, the statistical
test is more likely to detect a trend when data have been obtained over a longer period. It
should be noted that conducting statistical testing for multiple air quality standards increases
the probability that some trends identified as statistically significant may actually have occurred
by chance.
x EPA issued increased requirements for lead monitoring in December 2010.44
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A finding of statistical significance is useful for determining that an observed trend was unlikely
to have occurred by chance. However, a determination of statistical significance by itself does
not convey information about the magnitude of the increase or decrease in indicator values.
Furthermore, a lack of statistical significance means only that occurrence by chance cannot be
ruled out. Thus, a conclusion about statistical significance is only part of the information that
should be considered when determining the public health implications of trends.
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Indicator El
Percentage of children ages 0 to 17 years living in counties with pollutant
concentrations above the levels of the current air quality standards, 1999-2009
Any standard
Ozone (8-hour avg >7.5 ppb)
PM (24-hour avg >35
S03 (1-hour avg >75 ppb) x NO., (1-hour avg >100 ppb)
PM,, (annual avg>15
Lead
(3-month ayg >0.15 ug/m'J
Carbon monoxide (8-hour avg >9 ppm)
PM,n(24-hour avg >150 ug/rn
Data: U.S. Environmental Protection Agency, Office of Air and Radiation, Air Quality System
Note: EPA periodically reviews air quality standards and may change them based on updated scientific findings.
Measuring concentrations above the level of a standard is not equivalent to violating the standard. The level of
a standard may be exceeded on multiple days before the exceedance is considered a violation of the standard.
See text for additional discussion.
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Data characterization
Data for this indicator are obtained from EPA's database of air quality monitoring measurements.
Air pollution monitors are placed in locations throughout the country, with an emphasis on areas expected
to have higher pollutant concentrations or that have larger populations. Not all counties in the United
States have air pollution monitors, and the number of counties with monitors has changed over time.
Monitors generally tend to stay in the same location over many years, but there may be some limited
changes in the number or location of monitors providing data from year to year.
• From 1999 to 2009, the proportion of children living in counties with measured pollutant
concentrations above the levels of one or more national ambient air quality standards
decreased from 75% to 59%. This includes both concentrations above the level of any
current short-term standard at least once during the year as well as average concentrations
above the level of any current long-term standards.
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• The decreasing trend over the years 1999-2009 was statistically significant.
From 1999-2009, the percentage of children living in counties with measured ozone
concentrations above the level of the current 8-hour ozone standard at least one day during
the year decreased from 65% to 49%.
• The decreasing trend for ozone over the years 1999-2009 was statistically significant.
From 1999-2009, the percentage of children living in counties with measured PM2.5
concentrations above the level of the current 24-hour PM2.5 standard at least once per year
decreased from 55% to 32%. Over the same years, the percentage of children living in
counties with a measured annual average concentration above the level of the current
annual PM2.5 standard declined from 24% to 2%.
• The decreasing trends for PM2.5 were statistically significant.
From 1999-2009, the percentage of children living in counties with measured sulfur dioxide
concentrations above the level of the current one-hour standard for sulfur dioxide at least
one day per year declined from 31% to 11%. Over the same years, the percentage of
children living in counties with measured concentrations above the level of the current one-
hour standard for nitrogen dioxide at least one day per year decreased from 23% to 9%.
• The decreasing trends for both sulfur dioxide and nitrogen dioxide were statistically
significant.
In each year since 1999, between 1 and 5% of children lived in counties with measured
ambient lead concentrations above the level of the current three-month standard for lead.
In 2009, 8 counties with 4% of U.S. children reported concentrations above the level of the
three-month standard for lead.
In 2009, 3% of children lived in counties with measured PMioconcentrations above the level
of the current 24-hour standard for PMio at least one day per year, and no children lived in
counties with measured concentrations above the level of the current standard for carbon
monoxide.
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Indicator E2
Percentage of children ages 0 to 17 years living in counties with 8-hour ozone
and 24-hour PMz.s concentrations above the levels of air quality standards, by
frequency of occurrence, 2009
No monitoring data
1-3 days
11-25 days
Ozone
(8-hour standard)
No monitoring data
1-7 days
8-10 days
|ll-25days
16 or more days
PM
2.5
(24-hour standard)
Data: U.S. Environmental Protection Agency, Office of Air and Radiation, Air Quality System
Note: EPA periodically reviews air quality standards and may change them based on updated scientific
findings. Measuring concentrations above the level of a standard is not equivalent to violating the standard.
The level of a standard may be exceeded on multiple days before the exceedance is considered a violation
of the standard. See text for additional discussion.
America's Children and the Environment, Third Edition
Data characterization
Data for this indicator are obtained from EPA's database of air quality monitoring measurements.
Air pollution monitors are placed in locations throughout the country, with an emphasis on areas expected
to have higher pollutant concentrations or that have larger populations. Not all counties in the United
States have air pollution monitors.
Some air pollution monitors do not operate every day, so some days with pollutant concentrations above
the levels of the air quality standards may not be identified.
In 2009, 27% of children lived in counties with no monitoring data for ozone, and 30% lived in counties
with no monitoring data for PM2.s.
In 2009, 6% of children lived in counties with measured ozone concentrations above the
level of the 8-hour ozone standard on more than 25 days. An additional 3% of children lived
in counties with measured concentrations above the level of the ozone standard between
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11 and 25 days, and 12% of children lived in counties where concentrations were above the
level of the standard between 4 and 10 days.
In 2009,1% of children lived in counties with measured PM2.5 concentrations above the
level of the 24-hour PM2.5 standard on more than 25 days. An additional 2% of children lived
in counties with measured concentrations above the level of this standard between 11 and
25 days, and 1% of children lived in counties with measured concentrations above the level
of the 24-hour PM2.5 standard between 8 and 10 days.
In 1999, 23% of children lived in counties with measured ozone concentrations above the
level of the current 8-hour ozone standard on more than 25 days. An additional 27% of
children lived in counties with measured concentrations above the level of the ozone
standard between 11 and 25 days, and 11% of children lived in counties where
concentrations were above the level of the standard between 4 and 10 days. (See Table E2.)
In 1999, 6% of children lived in counties with measured PM2.5 concentrations above the
level of the current 24-hour PM2.5 standard more than 25 days. An additional 9% of children
lived in counties with measured concentrations above the level of this standard 11 and 25
days, and 3% of children lived in counties with measured concentrations above the level of
the 24-hour PM2.5 standard between 8 and 10 days. (See Table E2.)
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Environments and Contaminants | Criteria Air Pollutants
Indicator E3: Percentage of days with good, moderate, or unhealthy air quality for
children ages 0 to 17 years, 1999-2009
About the Indicator: Indicator E3 presents data from EPA's Air Quality Index (AQI). The AQI produces
a rating of the air quality for each county on each day, considering all monitoring results available on
that day for carbon monoxide, ozone, nitrogen dioxide, particulate matter, and sulfur dioxide. Air
quality in each county is considered to be "good," "moderate," or "unhealthy" based on comparison
of the monitored pollutant concentrations to breakpoints defined by the AQI. The indicator is
calculated by considering the number of children in counties with each rating for each day of the
year, then summing the number of children for all days in the year.
Air Quality Index
EPA's Air Quality Index (AQI)XI represents air quality for each individual day and is widely
reported in newspapers and other media outlets in metropolitan areas. The AQI is based on
daily measurements of up to five of the six air quality criteria pollutants (carbon monoxide,
ozone, nitrogen dioxide, particulate matter, and sulfur dioxide). The standard for lead is not
included in the AQI because it requires averaging concentrations over a three-month period,
and it can take several weeks to collect and analyze lead samples.
The specific pollutants considered in the AQI for each metropolitan area depend on the
pollutants monitored in that area each day. Each pollutant concentration is given a value on a
scale relative to the air quality standard for that pollutant. The daily AQI is based on the single
pollutant with the highest index value that day. An AQI value of 100 corresponds to the level of
the short-term (e.g., daily or hourly) NAAQS for each criteria pollutant. An AQI value of 50 is
defined either as the level of the annual standard, if one has been established (e.g., PM2.5, N02),
or as a concentration equal to one-half the value of the short-term standard used to define an
index value of 100 (e.g., CO).
EPA has divided the AQI scale into categories. Air quality is considered "good" (referred to as
"code green") if the AQI is between 0 and 50, posing little or no risk. Air quality is considered
"moderate" ("code yellow") if the AQI is between 51 and 100. Some pollutants at this level may
present a moderate health concern for a small number of individuals. Air quality is considered
"unhealthy for sensitive groups" if the AQI is between 101 and 150 (referred to as "code
orange"). On code orange days, members of at-risk populations such as children may
experience health effects, but the rest of the general population is unlikely to be affected. Air
quality is considered "unhealthy" if the AQI is between 151 and 200 ("code red"). The general
population may begin to experience health effects, and members of at-risk populations may
experience more serious health effects. Values of 201 to 300 are designated as "very
unhealthy" ("code purple"), while values of 301 to 500 are considered "hazardous" ("code
maroon"). Decisions about the pollutant concentrations at which to set the various AQI
Xl Available at http://www.airnow.gov/.
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breakpoints that delineate the various AQI categories draw directly from the underlying health
information that supports the reviews of the NAAQS.
For PM2.5, the AQI values used in preparing Indicator E3 were calculated with a 24-hour
concentration of 40 u.g/m3 used to define air quality as "unhealthy for sensitive groups" (i.e., an
AQI value of 100), rather than the level of the current 24-hour PM2.5 standard of 35 u.g/m3. As a
consequence, Indicator E3 likely overstates the days with moderate air quality and understates
the days with unhealthy air quality.""
Data Presented in the Indicator
Indicator E3 is based on the reported AQI for counties in the United States. EPA calculates an
AQI value each day in each county for five major air pollutants regulated by the Clean Air Act:
ozone, particulate matter, carbon monoxide, sulfur dioxide, and nitrogen dioxide. The highest
of these pollutant-specific AQI values is reported as the county's AQI value for that day.
Indicator E3 was developed by reviewing the AQI designation for each day for each county and
weighting the daily designations by the number of children living in each county. The
calculation, therefore, is a summation of the AQI values for all children in the United States,
based on county of residence, for each day of the year. For example, the number of days of
good air quality during the year is counted up for each child in the population based on the
daily air quality in the county where they live. The overall indicator reports the percentage of
children's days in each year considered to be of good (AQI 0-50; code green), moderate (AQI
51-100; code yellow), or unhealthy (AQI greater than 100; codes orange, red, purple, and
maroon combined) air quality.Xl" The percentage of children's days with no AQI value available
(representing the absence of monitoring data) are also reported in Indicator E3.
Whereas Indicator El presents an annual analysis of counties in which concentrations were
above the level of a standard for a pollutant, the AQI data used in Indicator E3 are based on the
concentrations for all pollutants for which an AQI has been established in each county over the
course of a year. The E3 method uses data on the air quality category for each day, rather than
simply reporting whether a county ever exceeds the standard for each pollutant during the
year. However, the AQI method has some limitations. The AQI is based on the single pollutant
with the highest value for each day; it does not reflect any combined effect of multiple
pollutants or the effects of pollutants that were not measured on a given day.
x" In December 2012, EPA promulgated a rule to change the AQI to use 35 u.g/m3 for defining the AQI value of 100
for PM2.s. Prior to this rule, although the AQI had not formally been changed, an EPA guidance document45
recommended use of 35 u.g/m3 for defining the AQI value of 100 for PM2.5. States have generally been using 35
u.g/m3 in calculating and reporting their daily AQI values.
Xl" As discussed above, an AQI value of 100 generally corresponds to the level of a short-term national ambient air
quality standard. When AQI values are above 100, air quality is considered to be unhealthy—at first for certain
sensitive groups of people (101 to 150), then for everyone as AQI values get higher.
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Indicator E3 starts in 1999 because this was the first year of widespread monitoring for PM2.5.
The indicator uses a consistent set of pollutant concentrations to define good, moderate, or
unhealthy air quality for all years shown, 1999-2009, but as noted above, the level of the
current 24-hour standard for PM2.5 has not been incorporated into calculation of the indicator.
Tables E3a and E3b show the percentage of children's days of exposure to good, moderate, or
unhealthy air quality in 2009 by race/ethnicity (Table E3a) and family income (Table E3b).
These calculations do not account for any possible variation in air quality within a county, and
thus may not fully reflect the variability in air quality among children of different
race/ethnicity and income.
Statistical Testing
Statistical analysis has been applied to Indicator E3 to evaluate trends over time in the
percentage of children's days of with good, moderate, or unhealthy air quality. These analyses
use a 5% significance level, meaning that a conclusion of statistical significance is made only
when there is no more than a 5% probability that the observed trend occurred by chance (p <
0.05). The statistical analysis of trends over time is dependent on how the annual values vary as
well as on the number of annual values. For example, the statistical test is more likely to detect
a trend when data have been obtained over a longer period.
A finding of statistical significance is useful for determining that an observed trend was
unlikely to have occurred by chance. However, a determination of statistical significance
trend over time does not imply anything about the magnitude of the increase or decrease in
indicator values. Furthermore, a lack of statistical significance means only that occurrence by
chance cannot be ruled out. Thus, a conclusion about statistical significance is only part of
the information that should be considered when determining the public health implications
of trends.
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Indicator E3
Percentage of days with good, moderate, or unhealthy air quality for children
ages 0 to 17 years, 1999-2009
No monitoring data
Moderate
Unhealthy
Data: U.S. Environmental Protection Agency, Office of Air and Radiation, Air Quality System
Note: Good, moderate, and unhealthy air quality are defined using EPA's Air Quality Index (AQI). The
health information that supports EPA's periodic reviews of the air quality standards informs decisions
on the AQI breakpoints and may change based on updated scientific findings. See text for additional discussion.
America's Children and the Environment, Third Edition
Data characterization
Data for this indicator are obtained from EPA's database of daily Air Quality Index (AQI) values for each
county in the United States.
Air pollution monitors are placed in locations throughout the country, with an emphasis on areas expected
to have higher pollutant concentrations or that have larger populations.
AQI values are based on daily monitoring data for up to five criteria air pollutants. Some counties do not
have monitors, and some monitors do not operate every day, so some days do not have AQI values.
For this indicator, the available monitoring data are used to assign a value of "good," "moderate,"
"unhealthy," or "no monitoring data" for each day in each U.S. county.
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The percentage of children's days that were designated as having "unhealthy" air quality
decreased from 9% in 1999 to 3% in 2009. The percentage of children's days with "good" air
quality increased from 41% in 1999 to 57% in 2009. The percentage of children's days with
"moderate" air quality was approximately constant at 21-23% from 1999 to 2007, and then
decreased to 16% in 2009.
• The 1999 to 2009 trends in "unhealthy," "good," and "moderate" air quality days were
statistically significant.
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Hazardous Air Pollutants | Environments and Contaminants
Hazardous Air Pollutants
Hazardous air pollutants (HAPs) are air contaminants, frequently referred to as "air toxics," that
are known or suspected to cause serious human health effects or adverse environmental
effects.1 The Clean Air Act identifies 187 substances as HAPs. Examples include benzene,
trichloroethylene, mercury, chromium, and dioxin. The "criteria" air pollutants such as ozone
and particulate matter are excluded from the HAPs list.1
HAPs are emitted into ambient air from a diverse range of facilities, businesses, and vehicles
that are grouped into three general categories: major sources, area sources, and mobile
sources. Major sources typically are large industrial facilities such as chemical manufacturing
plants, refineries, and waste incinerators. These sources may release air toxics from equipment
leaks, when materials are transferred from one location to another, or during discharge
through emission stacks or vents. Area sources typically are smaller stationary facilities such as
dry cleaners, auto body repair shops, and small manufacturing operations. Though emissions
from individual area sources often are relatively small, collectively they can be of concern-
particularly where large numbers of sources are located in heavily populated areas. Mobile
sources include both on-road sources, such as cars, light trucks, large trucks, and buses, and
non-road sources such as farm and construction equipment, lawn and garden equipment,
marine engines, aircraft, and locomotives. Some HAPs are also emitted from natural sources
such as volcanoes. Health effects associated with HAPs include cancer, asthma and other
respiratory ailments, birth defects, reproductive effects, and neurodevelopmental effects.2"9
In some cases, health concerns are based on studies of workers exposed to high levels of
particular HAPs on the job. For example, EPA has determined that HAPs such as benzene; 1,3-
butadiene; chromium; nickel; and vinyl chloride are carcinogenic to humans, based on findings
in occupational studies.10"14 Similarly, toluene diisocyanate exposure has been associated with
effects on the lung, and manganese exposure with neurological effects, in occupational
studies.15'16
A limited number of HAPs have also been studied in human populations that have been
exposed in their day-to-day lives. For examples, several studies have reported associations
between formaldehyde exposure (usually indoors at home or at school) and childhood asthma.3
In addition, a series of recent studies conducted in New York City reported that children of
women who were exposed to increased levels of polycyclic aromatic hydrocarbons (PAHs,
produced when gasoline and other materials are burned) during pregnancy are more likely to
have experienced adverse effects on neurological development (such as reduced intelligence
quotient (IQ) or behavioral problems6'7), as well as respiratory effects.17"19
1 Lead is an exception: it is regulated as a criteria pollutant, and "lead compounds" are included on the list of HAPs.
Note that criteria pollutants are discussed further in the Criteria Air Pollutants topic.
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For the majority of HAPs, however, there are no human epidemiological studies, or very few,
and concern for health effects is based on findings from animal studies. For example, many
HAPs, such as PAHs,20 acetaldehyde21 and carbon tetrachloride22 are considered likely to be
carcinogenic to human based primarily on evidence from long-term laboratory animal studies.
Although many HAPs are of concern due to their potential to cause cancer, a substantial
number of HAPs lack evidence of cancer—either because the relevant long-term studies have
not been conducted, or because studies have been conducted and do not indicate carcinogenic
potential. An example of a HAP that is not associated with cancer is acrolein; there are no
appropriate human or animal studies with which to assess the carcinogenic potential of
acrolein. However, acrolein has been identified as a HAP of particular concern for effects other
than cancer.23'24 Health concerns for acrolein include respiratory effects and irritation of the
eyes, nose, and throat, based on animal studies and on short-term studies of small groups of
humans intentionally exposed to high levels of acrolein.25
EPA relies on both monitoring and modeled data to characterize ambient air concentrations of
HAPs, and to estimate potential human exposure and risk of adverse health effects associated
with these toxics. EPA and state monitoring programs do not cover all the places where people
live in the United States. For this reason, the following indicator relies on modeled data from
the National Air Toxics Assessment.26 The indicator presents the percentage of children living in
census tracts with estimated HAP concentrations greater than benchmark comparison levels
derived from health effects information.
In addition to their presence in ambient air, many HAPs also have indoor sources, and the
indoor sources may frequently result in greater exposure than the presence of HAPs in ambient
air. Sufficient data are not available to develop an indicator considering the combined exposure
to HAPs from both indoor and outdoor sources; therefore the following indicator considers only
levels of HAPs in ambient air."
" Indoor sources of HAPs are further discussed in the Indoor Environments and Contaminants in Schools and Child
Care Facilities topics, and in several of the biomonitoring topics.
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Indicator E4: Percentage of children ages 0 to 17 years living in census tracts where
estimated hazardous air pollutant concentrations were greater than health
benchmarks in 2005
About the Indicator: Indicator E4 presents estimates of the percentage of children living in census
tracts with ambient hazardous air pollutant (HAP) concentrations greater than benchmark values
representing levels of concern for health effects. The HAP concentrations are computer model
estimates for 2005, representing all identified sources of HAP emissions, including factories and
motor vehicles. The health benchmarks are based on concerns for cancer and other adverse health
effects that may be associated with HAP exposure.
National Air Toxics Assessment
EPA's National Air Toxics Assessment (NATA) provides estimated concentrations of 181 HAPs in
ambient air for the year 2005. NATA is the most comprehensive resource on potential human
exposure to and risk of adverse health effects from HAPs in the United States. Monitoring data
are insufficient to characterize HAP concentrations across the country because of the limited
number of monitors, and because concentrations of many HAPs may vary considerably within a
metropolitan area or region.
Under NATA, EPA develops modeled estimates of ambient concentrations of HAPs using
estimated emissions data from major, area, onroad mobile, and non-road mobile sources.
These emissions data are collected and updated periodically, and are maintained in an
emissions inventory. The original NATA was developed using emissions data for the year 1996.
Since the initial release, EPA has developed additional estimates of ambient air concentrations
of HAPs using updated emissions inventories for 1999, 2002, and 2005. NATA's computer
modeling approach has the advantage of allowing estimation of HAP concentrations at
locations throughout the United States, rather than in just those locations that have HAP
monitors. However, compared with monitoring, the computer model requires estimating
quantities of HAP emissions, estimating locations of HAP emissions sources, and modeling the
dispersion of HAPs in the atmosphere after they have been emitted.
The most recent assessment developed estimated ambient concentrations of 179 air toxics for
the year 2005. A computer model provided estimates for every census tract in the United
States. The modeled estimates generally are consistent with the limited set of ambient air
toxics monitoring data, although at many locations the model estimates for some HAPs are
lower than measured concentrations.27 The 2005 NATA estimates do not reflect any changes in
emissions that may have occurred since 2005 due to new regulations, new technologies,
changes in economic activity, or changes in the vehicle fleet and vehicle miles traveled.
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Health Benchmarks for Hazardous Air Pollutants
Indicator E4 presents comparisons of modeled concentrations of HAPs in ambient air for 2005
with three health benchmark concentrations derived from scientific assessments conducted by
EPA and other environmental agencies.28 EPA uses the three benchmark risk levels to identify
HAPs that are of priority concern.29
Two benchmarks reflect potential cancer risks, at levels of l-in-100,000 risk and l-in-10,000
risk. If a particular hazardous air pollutant is present in ambient air at a l-in-100,000 benchmark
concentration, for example, it is estimated that one additional case of cancer would occur in a
population of 100,000 people exposed for a lifetime. The comparison to the cancer risk
benchmark incorporates data for all HAPs considered carcinogenic to humans, likely
carcinogenic to humans, or with suggestive evidence of carcinogenicity. The majority of HAPs
included in the comparison to the cancer risk benchmarks are considered "carcinogenic to
humans" or "likely carcinogenic to humans."30
The third benchmark concentration corresponds to the level at which exposure to the
hazardous air pollutant is estimated to be of minimal risk for adverse non-cancer health effects;
exposures above this benchmark may be associated with adverse health effects such as
respiratory or neurological effects. Due to variation in human response to HAP exposure and
uncertainty in the benchmark values, it is not necessarily the case that a person living in a
location where this benchmark is exceeded will experience adverse effects. It is also possible
that individuals may experience effects at levels below the benchmark level.
The health benchmarks are generally derived from laboratory animal studies, although for
some HAPs they are derived from human epidemiological studies of workers exposed on the
job. For some HAPs, even the animal studies are very limited and no benchmark has been
derived. Health benchmarks were available to assess 87 HAPs as cancer-causing agents and 105
HAPs as agents that cause adverse health effects other than cancer. Some HAPs had
benchmarks for both cancer and non-cancer health endpoints; a total of 141 air toxics were
used in calculating the indicator.
Because they are typically based on studies of adults or mature laboratory animals, the three
benchmarks generally reflect health risks to adults, rather than potential risks to children or
risks in adulthood stemming from childhood exposure. Benchmarks for non-cancer effects
incorporate assumptions that are based on adult respiratory physiology (i.e., breathing rates
and lung structure); benchmarks for some HAPs would be lower if they were adjusted for
children's respiratory physiology.31
Under a policy adopted in 2005, EPA adjusts risk estimates for certain carcinogens to account
for increased risks associated with exposures during early life.32 This adjustment has been
applied to the cancer benchmarks for PAHs, acrylamide, benzidine, and ethyl carbamate.
Benchmark values for other HAPs that are suspected carcinogens receive no adjustment for
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potential elevated risks from early-life exposures because they do not meet the criteria of the
EPA policy or lack sufficient data to support application of the adjustment.
Further, the benchmarks reflect risks of continuous exposure over the course of a lifetime.
Potential risks from higher concentrations experienced over a short amount of time (one day,
one hour, or less) may in some cases trigger immediate responses, such as asthma attacks or
effects on the central nervous system are not addressed by these benchmarks.
Finally, the benchmark values for HAP s are uncertain to varying degrees, due to data
limitations and the lag in time between when new studies become available and the
completion of updated assessments by EPA and other government agencies.
Data Presented in the Indicator
Indicator E4 presents the percentage of children living in census tracts where estimated 2005
HAP concentrations exceeded benchmark levels for cancer (at levels of l-in-100,000 risk and 1-
in-10,000 risk) and for other (non-cancer) adverse health effects. The indicator is calculated by
comparing the estimated HAP concentrations for each U.S. census tract in 2005 to each of the
benchmark concentrations. Census tracts are geographic areas within U.S. counties that vary in
size and generally have 1,500 to 8,000 residents, with a typical population of 4,000 residents.
The comparison to the cancer risk benchmark sums up data for all carcinogenic HAPs. The
comparison to the benchmark for other adverse health effects considers only individual HAPs;
that is, a county is considered to exceed this benchmark if the modeled concentration for any
single HAP exceeds the corresponding non-cancer benchmark for that HAP, but it does not
consider adverse effects of combinations of HAPs.
Available information indicates that the NATA estimates of ambient HAP concentrations tend to
be similar to or lower than actual HAP concentrations.27 To the extent that underestimation
occurs, the percentage of children living in census tracts exceeding the benchmark levels may
be understated. In addition, the indicator does not differentiate between census tracts in which
the benchmarks are exceeded by a large margin and those in which estimated HAP
concentrations are just above the benchmark concentrations. The indicator presents results
only for 2005, and does not compare results across assessment years, such as between 1999
and 2005, because each update of the assessment brings new improvements to methods. For
example, improvements to the emissions estimation methodologies made in the 2005
assessment were not applied to the earlier versions, so the ambient concentration estimates
are not entirely comparable between years.
Actual exposures may differ from ambient concentrations. Indoor concentrations of HAPs from
outdoor sources may be slightly lower than ambient concentrations, although they can be
significantly higher if any indoor sources are present.33"36 Levels of some hazardous pollutants
may be substantially higher inside cars and school buses,37"39 and those higher levels would
increase the risks.
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Environments and Contaminants | Hazardous Air Pollutants
In addition, this indicator only considers exposures to air toxics that occur by inhalation. For
many air toxics, dietary exposures are also important. Air toxics that are persistent in the
environment settle out of the atmosphere onto land and water, and then may accumulate in
fish and other animals in the food web. For HAPs that are persistent in the environment and
accumulate significantly in food, exposures through food consumption typically are greater
than inhalation exposures. HAPs for which food chain exposures are important include mercury,
dioxins, and PCBs.40"42
The comparison of ambient HAP concentrations in 2005 to the health benchmarks is not
equivalent to an estimate of risk to the population from chronic HAP exposure. Actual risks to
health depend on concentrations of HAPs in many environments over an extended period of
time. Ambient concentrations will change over time as the mix of sources changes (e.g., due to
businesses opening and closing), vehicle use changes (e.g., more cars and trucks traveling
longer distances), and regulatory controls are applied. In addition, children spend most of their
time indoors at home, at school, or at child care centers, and pollutant concentrations in indoor
environments may be greater or lesser than the modeled ambient concentrations.
In addition to the indicator presented in the figure, which is based on where children live, the
same statistics are calculated based on where children's schools are located (see data tables).
Exposures at school are an important consideration, as children spend an average of 33 hours
per week in school.43 The data tables also provide indicator values by race/ethnicity and
income, based on where children live.
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Data characterization
Data for this indicator are obtained from EPA's National Air Toxics Assessment computer model predictions
of hazardous air pollutant (HAP) concentrations in outdoor air.
The model produces estimates of HAP concentrations from emissions data for all census tracts in the
United States (census tracts typically have about 4000 residents each).
In 2005, nearly all children lived in census tracts in which HAP concentrations combined to
exceed the l-in-100,000 cancer risk benchmark.
Seven percent of children lived in census tracts in which HAPs combined to exceed the 1-in-
10,000 cancer risk benchmark. The pollutants that contributed most to this result were
formaldehyde, benzene, acetaldehyde, carbon tetrachloride, and hexavalent chromium.
Formaldehyde, benzene, and hexavalent chromium are considered to be carcinogenic to
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humans,5'10'13 and acetaldehyde and carbon tetrachloride are considered likely to be
carcinogenic to humans.21'22
• Fifty-six percent of children lived in census tracts in which at least one HAP exceeded the
benchmark for health effects other than cancer. In almost all cases, this result was
attributable to the pollutant acrolein, which is a respiratory irritant. More than 90% of
acrolein emissions are from wood-burning fires and mobile sources such as cars, trucks,
buses, planes, and construction equipment.
• Exposures to diesel particulate matter from diesel engine emissions are not included in this
indicator due to uncertainty regarding the appropriate values to use as cancer benchmarks.
Some studies have found that cancer risks from diesel particulate matter exceed those of
the HAPs considered in this indicator.44 Although EPA does not endorse any particular
cancer benchmark value for diesel particulate matter, if the State of California's benchmark
for diesel particulate matter were used in this analysis, 73% of children would live in census
tracts where HAP estimates combined to exceed the l-in-10,000 cancer risk benchmark.
• In 2005, all children's schools were located in census tracts where HAPs concentrations
combined to exceed the l-in-100,000 cancer risk benchmark. Six percent of children
attended schools in census tracts where the HAPs concentrations exceeded the higher l-in-
10,000 cancer risk benchmark.
• Fifty-seven percent of children attended schools that were located in census tracts where at
least one HAP exceeded the benchmark for health effects other than cancer.
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Indoor Environments I Environments and Contaminants
Indoor Environments
Children spend most of their time in indoor environments, including homes, schools, child care
facilities, and other buildings.1 The chemicals found indoors or measured in indoor air are
numerous and diverse. Hundreds of chemicals have been measured in indoor air, including
multiple pesticides, fragrance-related compounds, polychlorinated biphenyls (PCBs),
phthalates, combustion byproducts, carbon monoxide, benzene, formaldehyde, and other
compounds.2"4 Pollutants in indoor environments can come from many different sources,
including combustion sources such as furnaces, gas stoves, fireplaces, and cigarettes; building
materials and furnishings such as treated wood, paints, furniture, carpet, and fabrics; consumer
goods such as electronics and toys; cleaning products, pesticides, and other products used for
maintenance of the home or building; and products used for hobbies, science projects, arts and
crafts projects, and other activities.
Children may also be routinely exposed to chemical contaminants that accumulate in dust,
including lead, nicotine, pesticides, brominated flame retardants, phthalates, and
perfluorinated chemicals.3'5"9 Many pesticides and other chemicals that break down relatively
quickly outdoors are much more persistent and long-lasting indoors, where they are less
exposed to natural elements such as sunlight, moisture, and microorganisms that can
accelerate the breakdown of chemicals.10"12
Infants and small children may have the highest exposure to house dust contaminants due to
their frequent and extensive contact with floors, carpets, and other surfaces where dust
gathers, as well as their frequent hand-to-mouth activity. However, children of all ages (as well
as adults) are likely to be exposed to dust contaminants through hand-to-mouth activity1'13 and
other ingestion pathways, such as the settling of dust onto food and food preparation surfaces
in the kitchen.
The indoor environments of personal cars and school buses are also important to children's
exposure, as a child can spend up to an average of 84 minutes per day in a vehicle, depending
on his or her age.1 School bus cabins can have levels of fine particulate matter (PIV^.s) four
times higher than levels in ambient air.14 In addition, children riding school buses in urban areas
are likely to be exposed to elevated levels of benzene, formaldehyde, and other pollutants in
motor vehicle emissions. It is estimated that school buses commuting through congested urban
areas may contribute up to 30% of a child's daily exposure to diesel engine-related pollutants.15
Adult smoking in personal cars can have a significant impact on children's environmental
tobacco smoke exposures, as the air in smokers' cars tends to have significantly higher nicotine
concentrations than that in non-smokers' cars.16 Smoking in cars also leaves nicotine residues
that may linger in dust and surfaces within smokers' cars, leading to continued exposure even
after the practice of smoking within the car has ceased.17
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Environments and Contaminants | Indoor Environments
Pollutants in indoor environments can also come from outside sources. For example,
pollutants in outdoor air will penetrate to the indoor environment,18'19 and contaminants
from workplaces, streets, or lawns may be carried into the home on people's shoes or
clothing.20'21 Some contaminants in drinking water can enter indoor air through uses of hot
water such as showering.22'23 In areas where groundwater is contaminated, chemicals may
enter indoor environments via vapor intrusion.24'25 Radon, a gaseous radioactive element that
causes lung cancer, is found in soils and can enter homes through cracks in the foundation
and other entry points.26
Indoor air pollutants from biological sources such as mold; dust mites; pet dander (skin flakes);
and droppings and body parts from cockroaches, rodents, and other pests or insects are
commonly found in children's homes.27"30 These contaminants are important because they can
lead to allergic reactions, exacerbate existing asthma, and have been associated with the
development of respiratory symptoms.28"31
Two indoor environmental contaminants for which there is extensive evidence of children's
health effects are environmental tobacco smoke and lead. The following indicators present data
on environmental tobacco smoke and lead dust hazards in children's homes, because they are
well-established indoor hazards to children's health and because they have nationally
representative data available for more than one point in time. Other indoor environmental
hazards in children's homes generally lack nationally representative data necessary for
development of indicators that can identify any changes over time. Unlike many outdoor
pollutants, indoor pollutants are not regulated or systematically monitored in residential
settings, and data collection for indoor pollutants is much more limited. Indicator E5 presents
data on environmental tobacco smoke, based on national survey data of homes with young
children where someone smokes regularly. Indicator E6 presents data on lead dust hazards in
children's homes. Further information on these issues is provided in the following sections. In
addition, indoor environments in children's schools and in child care facilities are discussed in
the Supplementary Topics section of this report.
Environmental Tobacco Smoke
Environmental tobacco smoke (ETS), commonly referred to as secondhand smoke, is a complex
mixture of gases and particles and includes smoke from burning cigarettes, cigars, and pipe
tobacco (sidestream smoke), as well as exhaled mainstream smoke.32 There are at least 250
chemicals in ETS that are known to be toxic or carcinogenic, including acrolein, ammonia,
benzene, carbon monoxide, formaldehyde, hydrogen cyanide, nicotine, nitrogen oxides, and
sulfur dioxide.32'33 In 1992, EPA classified ETS as a known human carcinogen.34 Children can be
exposed to ETS in their homes or in places where people are allowed to smoke, such as some
restaurants in some locations throughout the United States.
According to the U.S. Surgeon General, there is no safe level of exposure to ETS, and breathing
even a small amount can be harmful to human health.32 The Surgeon General has concluded
that exposure to ETS causes sudden infant death syndrome (SIDS), acute lower respiratory
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infection, ear problems, and more severe asthma in children. Smoking by parents causes
respiratory symptoms and slows lung growth in their children.32 Young children appear to
more susceptible to the respiratory effects of ETS than are older children.29'34'35
The exposure of a pregnant woman to ETS can also be harmful to her developing fetus. The
Surgeon General has determined that exposure of pregnant women to ETS causes a small
reduction in mean birth weight, and that the evidence is suggestive (but not sufficient to infer
causation) of a relationship between maternal exposure to environmental tobacco smoke
during pregnancy and preterm delivery.32 In addition, the Surgeon General concluded the
evidence is suggestive but not sufficient to infer a causal relationship between prenatal and
postnatal exposure to ETS and childhood cancer.32
Exposure to ETS in the home is influenced by adult behaviors, including the decisions to smoke
at home and to allow visitors to smoke inside the home. Children living in homes with smoking
bans have significantly lower levels of cotinine (a biological marker of exposure to ETS) in urine
than children living in homes without smoking bans.36 Household smoking bans can significantly
decrease children's exposures to ETS, but do not completely eliminate them, especially in multi-
unit housing where ETS from other apartments may infiltrate through seepage in walls or
shared ventilation systems.37"39 Furthermore, children may be exposed to toxic residues that
remain from ETS in dust and on surfaces inside the home for weeks or months after smoke has
cleared from the air.6'40"43 These residues, referred to as "third-hand smoke," may be re-
emitted into the gas phase or may react with other compounds to form secondary
pollutants.40'43 The risk of exposure to third-hand smoke may be particularly high for infants,
due to their close proximity to contaminated objects such as blankets, carpets, and floor
surfaces, and their frequent hand-to-mouth activity.6
Parental smoking status inside the home greatly affects children's exposures to ETS, but
research suggests a difference in impact between maternal and paternal smoking. Maternal
smoking is associated with higher cotinine levels in children, and maternal smoking appears to
have a greater effect on lower respiratory illnesses than does paternal smoking.32
In recent years there has been a significant decline in children's exposures to ETS.44 This
reduction is in part attributable to a decline in the percentage of adults who smoke, and is likely
related to increased restrictions on smoking at workplaces and other public places, as well as
efforts to reduce the exposure of nonsmokers in homes.44 In 2010, an estimated 19.3% of
adults were current smokers, down from 24.7% in 1997.45'46 In addition, the prevalence of
smoke-free households increased from 43% of U.S. homes in 1992-1993 to 72% in 2003.47
Children living in homes with smoking bans have significantly lower levels of cotinine than
children living in homes without smoking bans.36 Recent studies also suggest that smoking bans
in workplaces and other public places can reduce the number of asthma-related emergency
room visits and hospitalizations, including among children when legal bans lead to an increase
in voluntary smoking bans in homes.48'49 However, despite the increasing numbers of adults
disallowing smoking in the home, approximately 34% of children live in a home with at least
one smoker as of 2009.50
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Lead in House Dust
The ingestion of lead-contaminated house dust, soil, and water is the primary pathway of
current childhood exposure to lead.51 Children have a greater risk of exposure to lead-
contaminated dust than that of adults, due to their frequent and extensive contact with floors,
carpets, and other surfaces where dust gathers, as well as their high rate of hand-to-mouth
activity. Additionally, lead-contaminated dust particles are more readily absorbed into the body
than soil or paint chips, and children's bodies absorb up to 10 times more ingested lead than
adults do as a result of their less-developed gastrointestinal pathways.52 Children living in
homes with higher levels of lead-contaminated dust tend to have higher blood lead levels.53"58
Lead dust is composed of fine particles of soil, paint, and other settled industrial or automotive
emissions from the outdoor and indoor air.59 Residences with deteriorated lead-based paint
tend to have higher levels of lead in house dust and the surrounding soil.51'60 Deteriorated lead-
based paint that is cracked, peeling, or chipped can be ingested directly by children or can mix
with and contaminate house dust, which can also be ingested.61 Normal wear as the result of
cleaning activities or repeated surface friction can lead to further deterioration and the release
of lead-based paint particles.62 Any house built before 1978 may contain lead-based paint. As of
the year 2000, approximately 38 million older housing units in the United States still contained
lead-based paint.51
Home maintenance and renovation activities that disturb lead-based paint, such as sanding,
scraping, cutting, and demolition, create hazardous lead dust and chips and have been
associated with higher levels of lead dust and blood lead in children.60'63 Beginning in April
2010, all contractors performing renovation, repair, and painting projects that disturb lead-
based paint in pre-1978 homes and child-occupied facilities, such as child care facilities and
preschools, must be certified and follow specific work practices to prevent lead
contamination.60 Lead-contaminated soil is another contributor to lead in house dust. Known
sources of lead in soil include historical airborne emissions from leaded gasoline use, emissions
from industrial sources such as smelters, and lead-based paint. Current sources of lead in
ambient air in the United States include smelters, ore mining and processing, lead acid battery
manufacturing, and coal combustion activities, such as electricity generation.58 Lead-
contaminated dust and soil from the outdoors can be transported into the home after
becoming airborne via soil resuspension, or can be tracked into the home by occupants or
family pets.52
The National Toxicology Program (NTP) has concluded that childhood lead exposure is
associated with reduced cognitive function.64 Children with higher blood lead levels generally
have lower scores on IQ tests55'65"70 and reduced academic achievement.64 The NTP has also
concluded that childhood lead exposure is associated with attention-related behavioral
problems (including inattention, hyperactivity, and diagnosed attention-deficit/hyperactivity
disorder) and increased incidence of problem behaviors (including delinquent, criminal, or
antisocial behavior).64
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Until recently, the Centers for Disease Control and Prevention (CDC) defined a blood lead level
of 10 micrograms per deciliter (u.g/dL) as "elevated." This definition was used to identify
children for blood lead case management.71'72 However, no level of lead exposure has been
identified that is without risk of deleterious health effects.58 CDC's Advisory Committee on
Childhood Lead Poisoning Prevention (ACCLPP) recommended in January 2012 that the 97.5th
percentile of children's blood lead distribution (currently 5 u.g/dL) be defined as "elevated" for
purposes of identifying children for follow up activities such as environmental investigations
and ongoing monitoring.73 CDC has adopted the ACCLPP recommendation.74 CDC specifically
notes that "no level of lead in a child's blood can be specified as safe,"75 and the NTP has
concluded that there is sufficient evidence for adverse health effects in children at blood lead
levels less than 5 u.g/dL.64
The current federal standards indicate that floor and window lead dust should not exceed 40
micrograms of lead per square foot (u.g/ft2)and 250 u.g/ft2, respectively, in order to protect
children from developing "elevated" blood lead levels as formerly defined by the CDC. EPA is
currently reviewing the lead dust standards to determine whether they should be lowered,
based on indications from more recent epidemiological studies that the current standards may
not be sufficiently protective of children.76
Childhood blood lead and house dust lead levels in the United States differ across groups in the
population, such as those defined by socioeconomic status, race/ethnicity,51'53'77 and
geographic location. Children living in poverty and Black non-Hispanic children tend to have
higher blood lead levels53'78 and higher levels of lead-contaminated dust in the home than do
White non-Hispanic children.77 Blood lead levels tend to be higher for children living in older
housing, because older housing units are more likely to contain lead-based paint.77'79
Additionally, housing in the Northeast and Midwest has twice the prevalence of lead-based
paint hazards compared with housing in the South and West,59 because of the older housing
stock in those areas.
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Indicator E5: Percentage of children ages 0 to 6 years regularly exposed to
environmental tobacco smoke in the home, by family income, 1994, 2005, and 2010
About the Indicator: Indicator E5 presents the percentage of children ages 0 to 6 years regularly
exposed to environmental tobacco smoke (ETS) in the home. The data are from a national survey
that collects health information from a representative sample of the population. The survey provides
data on children exposed to ETS in the home on four or more days per week for the years 1994,
2005, and 2010. The focus is on children ages 6 years and under because these younger children
have been specifically identified as more susceptible to the effects of tobacco smoke.
National Health Interview Survey
Comparable, nationally representative data on children living in homes where someone smokes
regularly come from the National Health Interview Survey (NHIS) for 1994, 2005, and 2010. The
NHIS is a large-scale household interview survey of a representative sample of the civilian
noninstitutionalized U.S. population, conducted by the National Center for Health Statistics. In
1994, interviews were conducted with household adults representing about 5,450 children ages
0 to 6 years, and ETS exposure information was reported for about 5,390 of those children. In
2005, interviews were conducted with household adults representing about 10,100 children
ages 0 to 6 years, and ETS exposure information was reported for about 7,800 of those children.
In 2010, interviews were conducted with household adults representing about 9,350 children
ages 0 to 6 years, and ETS exposure information was reported for about 6,900 of those children.
Questions related to smoking in the home are included in the NHIS only in selected years. In
1994, the NHIS asked, "Does anyone who lives here smoke cigarettes, cigars, or pipes anywhere
inside this home?" Similarly, in 2005 and 2010, the NHIS asked, "In a usual week, does ANYONE
who lives here, including yourself, smoke cigarettes, cigars, or pipes anywhere inside this
home?" If the answer was positive, participants were asked how many days per week smoking
usually occurred anywhere inside the home. The NHIS also included questions about smoking in
the home in the 1998 survey, but the questions used in 1998 provide data that are not directly
comparable to the 1994, 2005, and 2010 data.
Data Presented in the Indicator
Indicator E5 presents data from NHIS for the percentage of children ages 0 to 6 years living in
homes where someone smokes on a regular basis (defined as four days or more per week).
Studies have found that questionnaire data on smoking in the home are relatively accurate in
predicting serum levels of cotinine (a metabolite of nicotine used as a marker of ETS exposure)
in children,80'81 and researchers have used these data to associate ETS exposure with adverse
effects on childhood lung function and other health outcomes.32 However, comparisons of
questionnaire data with measures of serum cotinine in children suggest that questionnaires
may underestimate actual exposure to ETS, particularly in multi-unit housing or in cases where
visitors and other non-family members may smoke in the home.32'39'82"84
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While the indicator provides information on the presence and number of days per week of
smoking in the home, it does not indicate the intensity of smoking (e.g., the number of
cigarettes smoked in the home per day). Furthermore, children exposed to ETS at home fewer
than four days per week are not included in this indicator, but may also experience adverse
health effects since no level of exposure to ETS is without a risk to health.
We focus on children ages 0 to 6 years because these younger children have been specifically
identified as more susceptible to the effects of tobacco smoke and are targeted by the indicator
used in the federal government's Healthy People 2010 initiative.85 Children ages 6 years and
under also have less control over their environment and are likely to spend more time in close
proximity to adult caregivers.32 Children of all ages, however, may be affected by exposure to ETS.
The indicator presents data on children's exposures to ETS in the home for 1994, 2005, and
2010, based on family income level. Additional information regarding ETS exposures for
different race/ethnicity groups is presented in Table E5a.
Statistical Testing
Statistical analysis has been applied to the 2010 data to evaluate differences in indicator values
between demographic groups. These analyses use a 5% significance level, meaning that a
conclusion of statistical significance is made only when there is no more than a 5% probability
that the observed difference occurred by chance (p < 0.05). A finding of statistical significance
depends on the numerical difference in the indicator value between two groups, the number of
observations in each group, and various aspects of the survey design. For example, the
statistical test is more likely to detect a difference between two groups when data have been
obtained from a larger number of people in those groups. It should be noted that when
statistical testing is conducted for differences among multiple demographic groups (for
example, considering both race/ethnicity and income level), the large number of comparisons
involved increases the probability that some differences identified as statistically significant
may actually have occurred by chance.
A finding of statistical significance is useful for determining that an observed difference was
unlikely to have occurred by chance. However, a determination of statistical significance by
itself does not convey information about the magnitude of the difference in indicator values or
the potential difference in risk of associated health outcomes. Furthermore, a lack of statistical
significance means only that occurrence by chance cannot be ruled out. Thus a conclusion
about statistical significance is only part of the information that should be considered when
determining the public health implications of differences in indicator values.
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Indicator E5
Percentage of children ages 0 to 6 years regularly exposed to environmental
tobacco smoke in the home, by family income, 1994, 2005, and 2010
All
Incomes
< Poverty
Level
100-200%
of Poverty
Level
>200%
of Poverty
Level
Data: Centers for Disease Control and Prevention, National Center for Health Statistics,
National Health Interview Survey
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Data characterization
Data for this indicator are obtained from an ongoing annual survey conducted by the National Center for
Health Statistics.
Survey data are representative of the U.S. civilian noninstitutionalized population.
In 1994, 2005, and 2010, an adult survey participant in each sampled household was asked whether any
resident smokes inside the home and the number of days per week that smoking occurred.
i In 2010, 6% of children ages 0 to 6 years lived in homes where someone smoked regularly,
compared with 27% in 1994.
i Children living in homes with family incomes below the poverty level were more likely than
their peers at higher income levels to be living in homes where someone smoked regularly.
In 2010,10% of children below the poverty level lived in homes where someone smoked
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regularly, compared with 8% of children in homes with incomes between 100-200% of
poverty level, and 3% of children in homes with incomes at least twice the poverty level.
• The differences between children in homes with family incomes below the poverty level
and children in homes with family incomes at or above the poverty level were
statistically significant.
In 2010, 20% of White non-Hispanic children below poverty lived in homes where someone
smoked regularly, compared with 10% of Black non-Hispanic children and 2% of Hispanic
children living below poverty. (See Table E5a.) These differences were statistically
significant.
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Indicator E6: Percentage of children ages 0 to 5 years living in homes with interior lead
hazards, 1998-1999 and 2005-2006
About the Indicator: Indicator E6 shows the percentage of children ages 0 to 5 years who lived in
homes with interior lead-based paint hazards. The data are from two nationally representative
surveys of homes conducted in 1998-1999 and 2005-2006. The surveys involved collection of dust,
soil, and paint samples from homes and measurement of the lead levels in these samples. The focus
of the indicator is on children ages 0 to 5 years, due to the elevated exposures that occur during early
childhood and the sensitivity of the developing brain to the effects of lead.
NSLAH/AHHS
The United States Department of Housing and Urban Development (HUD) has conducted two
nationally representative surveys of housing in the United States to assess children's potential
household exposure to lead and other contaminants. The American Healthy Homes Survey
(AHHS) was conducted from 2005-2006 to update the National Survey of Lead and Allergens
in Housing (NSLAH), which was conducted from 1998-1999. AHHS also included
measurements of arsenic, pesticides, and mold; however, these substances were not
measured in the earlier NSLAH.
Samples of paint, dust, and soil were taken from 831 total housing units (184 units with
children ages 0 to 5 years) in NSLAH, and 1,131 total housing units (206 units with children ages
0 to 5 years) in AHHS. The lead sampling components of AHHS were designed to be very similar
to NSLAH so that results of the two studies could be compared.
Lead-Based Paint Hazards
Samples collected from the housing units surveyed in NSLAH and AHHS were analyzed to
determine their lead content. HUD then compared these measured lead levels to federal
guidelines to identify homes with lead-contaminated dust, deteriorated lead-based paint, and
lead-contaminated soil hazards.
EPA has established Residential Lead Hazard Standards under Title X of the Toxic Substances
Control Act (TSCA), section 403, for identifying lead-based paint hazards in all housing built
before 1978. These standards were adopted by HUD under the Lead Safe Housing Act, which
applies to all federally owned or assisted housing in the United States. According to these
regulations, a lead-based paint hazard is the presence of deteriorating lead-based paint, lead-
contaminated dust, or lead-contaminated soil above federal standards.
For lead-contaminated dust, there are separate standards for dust on the floor and dust on
windowsills. Floor dust samples should not have more than 40 micrograms of lead per square
foot (u.g/ft2) and window dust samples should not have more than 250 u.g/ft2.61'86
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Additionally, current federal standards qualify a significantly deteriorated lead-based paint
hazard as the deterioration of an area of lead-based paint greater than 20 square feet (exterior)
and 2 square feet (interior) for large-surface items, such as walls and doors; or damage to more
than 10% of the total surface area of small-surface components—such as windowsills,
baseboards, and trim—with lead-based paint.
The level of deterioration is an important variable in determining exposure. The presence of
lead-based paint alone is not necessarily indicative of a significant hazard; except during
renovations, maintenance, and similar disturbances, intact lead-based paint is believed to pose
very little risk to occupants.87 However, deteriorated lead-based paint that is cracked, peeling,
or chipped can be ingested directly by children or can contaminate house dust that can be
inhaled or ingested by children.61
Data Presented in the Indicator
Indicator E6 presents the percentage of children ages 0 to 5 years who lived in homes with
interior lead-based paint hazards, using data from NSLAH and AHHS and three hazard definitions.
The first hazard definition, "interior lead dust," presents the percentage of children ages 0 to 5
years living in homes with a lead dust hazard, based on the number of homes with dust
containing levels of lead that exceeded the levels defined by EPA's Residential Lead Hazard
Standards (established under Title X of TSCA, section 403). The second hazard definition,
"interior deteriorated lead-based paint," displays the percentage of children ages 0 to 5 years
who lived in homes with significantly deteriorated lead-based paint indoors as defined by EPA's
Residential Lead Hazard Standards. The last definition, "either interior lead dust or interior
deteriorated lead-based paint," represents the percentage of children living in homes with an
interior dust hazard, a deteriorated lead-based paint hazard, or both.
This indicator represents the potential for children's indoor exposure to lead based solely on
the percentage of children ages 0 to 5 years living in homes with levels of lead-based paint and
dust above federal standards. The indicator does not represent differences in paint lead levels,
paint deterioration levels, or the amount of lead in the dust above the standards. It also does
not account for the possibility that children living in homes with levels of lead-based paint and
dust below federal standards may still have some exposure to lead. Furthermore, while this
indicator focuses on children ages 0 to 5 years, older children may also experience health
effects from exposure to lead.
Survey records identify the race/ethnicity and income level of survey respondents; however,
estimates of lead hazards in the home for children ages 0 to 5 years broken out by
race/ethnicity and income are not statistically reliable, due to the relatively small number of
homes in each group. Therefore, the indicator provides data only for all children ages 0 to 5
years combined.
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Statistical Testing
Statistical analysis has been applied to Indicator E6 to evaluate differences over time in the
indicator values (for example, percentage of children living in homes with lead-contaminated
dust). These analyses use a 5% significance level, meaning that a conclusion of statistical
significance is made only when there is no more than a 5% probability that the observed
difference occurred by chance (p < 0.05). The statistical analysis depends on the numerical
difference in the indicator value over time, the number of observations in each time period,
and various aspects of the survey design. For example, the statistical test is more likely to
detect a change over time when data have been obtained from a larger number of people in
each time period.
A finding of statistical significance is useful for determining that an observed difference was
unlikely to have occurred by chance. However, a determination of statistical significance by
itself does not convey information about the magnitude of the difference in indicator values or
the potential difference in risk of associated health outcomes. Furthermore, a lack of statistical
significance means only that occurrence by chance cannot be ruled out. Thus a conclusion
about statistical significance is only part of the information that should be considered when
determining the public health implications of changes over time.
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Data characterization
Data for this indicator are obtained from two surveys of U.S. homes conducted by the Department of
Housing and Urban Development.
Surveyed homes were representative of permanently occupied, non-institutional housing units in the
United States in which children may live. Only surveyed homes with children ages 0 to 5 years were
included in calculation of this indicator.
Lead was measured in samples of paint and dust collected from the surveyed homes.
In 2005-2006, 13% of children ages 0 to 5 years lived in homes with an interior lead dust
hazard, compared with 16% in 1998-1999.
In 2005-2006,11% of children ages 0 to 5 years lived in homes with an interior deteriorated
lead-based paint hazard, compared with 12% in 1998-1999.
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In 2005-2006,15% of children ages 0 to 5 years lived in homes with either an interior lead
dust hazard or an interior deteriorated lead-based paint hazard, compared with 22% in
1998-1999.
Changes in percentages between the two surveys were not statistically significant.
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Drinking Water Contaminants | Environments and Contaminants
Drinking Water Contaminants
Drinking water sources may contain a variety of contaminants that, at elevated levels, have been
associated with increased risk of a range of diseases in children, including acute diseases such as
gastrointestinal illness, developmental effects such as learning disorders, endocrine disruption,
and cancer.1"3 Because children tend to take in more water relative to their body weight than
adults do, children are likely to have higher exposure to drinking water contaminants.
Drinking water sources include surface water, such as rivers, lakes, and reservoirs;4 and
groundwater aquifers, which are subsurface layers of porous soil and rock that contain large
collections of water.5 Groundwater and surface water are not isolated systems and are
continually recharged by each other as well as by rain and other natural precipitation.6
Several types of drinking water contaminants may be of concern for children's health. Examples
include microorganisms, (e.g., E. coli, Giardia, and noroviruses), inorganic chemicals (e.g., lead,
arsenic, nitrates, and nitrites), organic chemicals (e.g., atrazine, glyphosate, trichloroethylene,
and tetrachloroethylene), and disinfection byproducts (e.g., chloroform). EPA and the Food and
Drug Administration (FDA) are both responsible for the safety of drinking water. FDA regulates
bottled drinking water, while EPA regulates drinking water provided by public water systems.
EPA sets enforceable drinking water standards for public water systems, and unless otherwise
specified, the term "drinking water" in this text refers to water provided by these systems. The
drinking water standards include maximum contaminant levels and treatment technique
requirements for more than 90 chemical, radiological, and microbial contaminants, designed to
protect people, including sensitive populations such as children, against adverse health effects.2'7
Microbial contaminants, lead, nitrates and nitrites, arsenic, disinfection byproducts, pesticides,
and solvents are among the contaminants for which EPA has set health-based standards.
Microbial contaminants include bacteria, viruses, and protozoa that may cause severe
gastrointestinal illness.2 Children are particularly sensitive to microbial contaminants, such as
Giardia, Cryptosporidium, E. coli, and noroviruses, because their immune systems are less
developed than those of most adults.8"14
Drinking water is a known source of lead exposure among children in the United States,
particularly from corrosion of pipes and other elements of the drinking water distribution
systems.15"17 Exposure to lead via drinking water may be particularly high among very young
children who consume baby formula prepared with drinking water that is contaminated by
leaching lead pipes.15 The National Toxicology Program has concluded that childhood lead
exposure is associated with reduced cognitive function, reduced academic achievement, and
increased attention-related behavioral problems.18
Fertilizer, livestock manure, and human sewage can be significant contributors of nitrates and
nitrites in groundwater sources of drinking water.19'20 High levels of nitrates and nitrites can
cause the blood disorder methemoglobinemia (blue baby syndrome)21"23 and have been
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associated with thyroid dysfunction in children24'25 and pregnant women.24'26'27 Moderate
deficits in maternal thyroid hormone levels during early pregnancy have been linked to reduced
childhood IQ scores and other neurodevelopmental effects, as well as unsuccessful or
complicated pregnancies.28
Arsenic enters drinking water sources from natural deposits in the earth, which vary widely
from one region to another, or from agricultural and industrial sources where it is used as a
wood preservative and a component of fertilizers, animal feed, and a variety of industrial
products.29 Population studies of health effects associated with arsenic exposure have been
conducted primarily in countries such as Bangladesh, Taiwan, and Chile, where arsenic levels in
drinking water are generally much higher than in the United States due to high levels of
naturally occurring arsenic in groundwater.30 Long-term consumption of arsenic-contaminated
water has been associated with the development of skin conditions and circulatory system
problems, as well as increased risk of cancer of the bladder, lungs, skin, kidney, nasal passages,
liver, and prostate.29'31 In many cases, long-term exposure to arsenic begins during prenatal
development or childhood, which increases the risk of mortality and morbidity among young
adults exposed to arsenic long-term.32 A review of the literature concluded that epidemiological
studies of associations between exposure to arsenic and some adverse health outcomes
pertinent to children's health have mixed findings. These include studies of associations
between high levels of exposure to arsenic and abnormal pregnancy outcomes, such as
spontaneous abortion, still-births, reduced birth weight, and infant mortality, as well as
associations between early-life exposure to arsenic and increased incidence of childhood cancer
and reduced cognitive function.33
Water can contain microorganisms such as parasites, viruses, and bacteria; the disinfection of
drinking water to reduce water-borne infectious disease is one of the major public health
advances of the 20th century.34 The method by which infectious agents are removed or
chemically inactivated depends on the type and quality of the drinking water source and the
volume of water to be treated. Surface water systems are more exposed than groundwater
systems to weather and runoff; therefore, they may be more susceptible to contamination.4'35
Surface and groundwater systems use filtration and other treatment methods to physically
remove particles. Disinfectants, such as chlorine and chloramine, ultraviolet radiation, and
ozone are added to drinking water provided by public water systems to kill or neutralize
microbial contaminants.36 However, this process can produce disinfection byproducts, which
form when chemical disinfectants react with naturally occurring organic matter in water.37 The
most common of these disinfection byproducts are chloroform and other trihalomethanes.
Consumption of drinking water from systems in the United States and other industrialized
countries with relatively high levels of disinfection byproducts has been associated with bladder
cancer and developmental effects in some studies.38"41 Some individual epidemiological studies
have reported associations between the presence of disinfection byproducts in drinking water
and increased risk of birth defects, especially neural tube defects and oral clefts; however,
recent articles reviewing the body of literature determined that the evidence is too limited to
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make conclusions about a possible association between exposure to disinfection byproducts
and birth defects.38'42"45
Some of the most widely used agricultural pesticides in the United States, such as atrazine and
glyphosate, are also drinking water contaminants.46'47 Pesticides can enter drinking water
sources as runoff from crop production in agricultural areas and enter groundwater through
abandoned wells on farms.48Some epidemiological studies have reported associations between
prenatal exposure to atrazine and reduced fetal growth.49"52
The use of glyphosate, an herbicide used to kill weeds, has increased dramatically in recent
years because of the growing popularity of crops genetically modified to survive glyphosate
treatment.53 Previous safety assessments have concluded that glyphosate does not affect
fertility or reproduction in laboratory animal studies.54'55 However, more recent studies in
laboratory animals have found that male rats exposed to high levels of glyphosate, either
during prenatal or pubertal development, may suffer from reproductive problems, such as
delayed puberty, decreased sperm production, and decreased testosterone production.56'57
Very few epidemiological human studies have investigated effects of glyphosate exposure on
reproductive endpoints. In contrast to the results of animal studies, one such epidemiological
study of women living in regions with different levels of exposure to glyphosate found no
associations between glyphosate exposure and delayed time to pregnancy.58
A variety of other chemical contaminants can enter the water supply after use in industry.47
Examples include trichloroethylene and tetrachloroethylene (also known as perchloroethylene),
which are solvents widely used in industry as degreasers, dry cleaning agents, paint removers,
chemical extractors, and components of adhesives and lubricants.59"61 Potential health concerns
from exposure to trichloroethylene, based on limited epidemiological data and evidence from
animal studies, include decreased fetal growth and birth defects, particularly cardiac birth
defects.61 A study conducted in Massachusetts reported associations between birth defects and
maternal exposure to drinking water contaminated with high levels of tetrachloroethylene
around the time of conception.62 An additional study reported that older mothers or mothers
who had previously miscarried, and who were exposed to high levels of tetrachloroethylene in
contaminated drinking water, had a higher risk of delivering a baby with reduced birth weight.63
However, other studies did not find associations between maternal exposure to
tetrachloroethylene and pregnancy loss, gestational age, or birth weight.64'65 Studies in
laboratory animals indicate that mothers exposed to high levels of tetrachloroethylene can have
spontaneous abortion, and their fetuses can suffer from altered growth and birth defects.60
EPA has not determined whether standards are necessary for some drinking water
contaminants, such as personal care products. Personal care products, such as cosmetics,
sunscreens, and fragrances; and Pharmaceuticals, including prescription, over-the-the counter,
and veterinary medications, can enter water systems after use by humans or domestic
animals66 and have been measured at very low levels in drinking water sources.67 Many
concentrated animal feeding operations treat livestock with hormones and antibiotics, and can
be one significant source of Pharmaceuticals in water.35 Other major sources of
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Pharmaceuticals in water are human waste, manufacturing plants and hospitals, and other
human activities such as showering and swimming.66 Any potential health implications of long-
term exposure to levels of Pharmaceuticals and personal care products found in drinking water
are unclear.
Manganese is a naturally occurring mineral that can enter drinking water sources from rocks
and soil or from human activities.68 While manganese is an essential nutrient at low doses,
chronic exposure to high doses may be harmful, particularly to the nervous system. Many of
the reports on adverse effects from manganese exposure are based on inhalation exposures in
occupational settings. Fewer studies have examined health effects associated with oral
exposure to manganese.68 However, some recent epidemiological studies have reported
associations between long-term exposure to high levels of manganese in drinking water during
prenatal development or childhood and intellectual impairment; decreased non-verbal
memory, attention, and motor skills; hyperactivity; and other behavioral effects.69"73 Most
studies on the health effects of manganese have been conducted in countries where
manganese exposure is generally higher than in the United States. However, two individual
studies conducted in specific areas of relatively high manganese contamination in the United
States reported associations between prenatal or childhood manganese exposure and
problems with general intelligence, memory, and behavior.74'75 Although there is no health-
based regulatory standard for manganese in drinking water, EPA has set a voluntary standard
for manganese as a guideline to assist public water systems in managing their drinking water
for aesthetic considerations, such as taste, color and odor.7
Perchlorate is a naturally occurring and man-made chemical that has been found in surface and
groundwater in the United States.76"78 Perchlorate is used in the manufacture of fireworks,
explosives, flares, and rocket fuel.78 Perchlorate was detected in just over 4% of public water
systems in a nationally representative monitoring study conducted from 2001-2005.78 Some
infant formulas have been found to contain perchlorate, and the perchlorate content of the
formula is increased if it is prepared with perchlorate-contaminated water.79"82 Exposure to
elevated levels of perchlorate can inhibit iodide uptake into the thyroid gland, possibly
disrupting the function of the thyroid and potentially leading to a reduction in the production of
thyroid hormone.83'84 As noted above, thyroid hormones are particularly important for growth
and development of the central nervous system in fetuses and infants.
In January 2009, EPA issued an interim health advisory level to help state and local officials
manage local perchlorate contamination issues in a health-protective manner, in advance of a
final EPA regulatory determination.78'85 In February 2011, EPA decided to develop a federal
drinking water standard for perchlorate, based on the concern for effects on thyroid hormones
and the development and growth of fetuses, infants, and children.78 The process for developing
the standard will include receiving input from key stakeholders as well as submitting any formal
rule to a public comment process.
The two indicators that follow use the best nationally representative data currently available to
characterize the performance of water systems in meeting EPA's health-based drinking water
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standards and in reporting monitoring results over time. Indicator E7 estimates the percentage
of children served by community water systems that did not meet all applicable health-based
drinking water standards. Indicator E8 estimates the percentage of children served by systems
with violations of drinking water monitoring and reporting requirements. Monitoring and
reporting violations occur when a water system does not monitor, does not report monitoring
results, or was late in reporting results.86 Such violations in monitoring and reporting may mean
that some health-based violations were not reported; this could cause the percentages shown
in Indicator E7 to be underestimated.
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Indicator E7: Estimated percentage of children ages 0 to 17 years served by
community water systems that did not meet all applicable health-based drinking
water standards, 1993-2009
Indicator E8: Estimated percentage of children ages 0 to 17 years served by
community water systems with violations of drinking water monitoring and reporting
requirements, 1993-2009
About the Indicators: Indicators E7 and E8 estimate the percentage of children served by community
water systems that did not meet all health-based drinking water standards or failed to adhere to
monitoring and reporting requirements. The data are from an EPA database that compiles drinking
water violations reported by public water systems. Indicator E7 shows the estimated percentage of
children served by community water systems that did not meet health-based drinking water
standards in each year from 1993 to 2009. Indicator E8 shows the estimated percentage of children
served by community water systems that did not adhere to monitoring and reporting requirements
in each year.
SDWIS/FED
EPA's Safe Drinking Water Information System, Federal Version (SDWIS/FED) provides
information on violations of drinking water standards. Public drinking water systems in the
United States are required to monitor the presence of certain individual contaminants at
specific time intervals and locations to assess whether they are complying with drinking water
standards. These standards include Maximum Contaminant Levels (MCLs), which are numerical
limits on how much of a contaminant may be present in drinking water; as well as mandatory
treatment techniques and processes, such as those intended to prevent microbial
contamination of drinking water. When a violation of a drinking water standard is detected, the
public water system is required to report the violation to the state, which in turn reports to the
federal government. All health-based violations are compiled in SDWIS/FED. SDWIS/FED was
created in 1995 and includes data from various precursor database systems that have violation
and inventory data going back to 1976. SDWIS/FED also reports the number of people served
by each water system.
Health-Based Drinking Water Standard Violations
Indicator E7 presents statistics on violations of drinking water standards grouped into several
categories:
• The "Surface water treatment" category includes violations of requirements in the Surface
Water Treatment Rule and Interim Enhanced Surface Water Treatment Rule that specify the
type of treatment and maintenance activities that systems must use to prevent microbial
contamination of drinking water.
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• The "Chemical and radionuclide" category includes violations of the MCLs for organic and
inorganic chemicals, such as atrazine, glyphosate, trichloroethylene, tetrachloroethylene,
arsenic, cadmium, and mercury, in addition to radionuclide contaminants, such as radium
and uranium.
• The "Lead and copper" category includes violations of treatment technique requirements
for systems to control the corrosiveness of their water.2
• The "Total coliforms" category covers all violations of the MCL for total coliform bacteria,
which is an indicator of the presence of various fecal pathogens, including f.Co//.87'88
• The "Nitrate/nitrite" category takes account of all violations of the MCLs for nitrates and
nitrites.
The "Disinfectants and disinfection byproducts" category covers violations of standards for
several disinfectants—chlorine, chloramine, and chlorine dioxide—and disinfectant
byproducts—total trihalomethanes, haloacetic acids, chlorite, and bromate.89
Monitoring and Reporting Violations
Indicator E8 presents statistics on violations of monitoring and reporting requirements.
Monitoring and reporting violations occur when a water system does not monitor, does not
report monitoring results, or was late in reporting results.86 All monitoring and reporting
violations are compiled from SDWIS/FED.
Data Presented in the Indicators
Indicator E7 estimates the percentage of children ages 0 to 17 years served by community water
systems that did not meet all applicable health-based drinking water standards between 1993
and 2009. The indicator is calculated by identifying all community water systems with violations
in SDWIS/FED each year by state, then summing the number of people served by those systems
with violations. Census data for the number of children in each state are then used to adjust
these estimates of the total population served to estimate the percentage of children served by
systems with violations in relation to all children served by community water systems.
Indicator E8 estimates the percentage of children ages 0 to 17 years served by community
water systems with violations of drinking water monitoring and reporting requirements. This
indicator is based on data reported to SDWIS/FED for violations between 1993 and 2009.
Violations of monitoring and reporting requirements for Indicator E8 were grouped into the
same categories as in Indicator E7, except for the Nitrate/nitrite category.
For the most part, the indicator represents comparisons with a consistent set of standards over
the years 1993-2009, with some exceptions. Revisions to the surface water treatment standard
were finalized in 2002.89 A revised standard for radionuclides went into effect in 2003, and for
arsenic (included in the chemical and radionuclide category) in 2006.90 A new standard for
disinfection byproducts was implemented in 2002 for larger drinking water systems, and in
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2004 for smaller systems.91 The revisions to the surface water treatment standard were
significant enough to warrant a break in the trend lines for this category in Indicators E7 and E8
between 2001 and 2002. The break in the "any violation" trend line between 2001 and 2002 is
due to both the revision of the surface water standard and the implementation of the new
disinfection byproducts standard for large systems beginning in 2002. Revisions to other
standards had only minimal impacts on the indicator values. As new and revised drinking water
standards take effect, water system compliance with all applicable health-based standards
signifies higher levels of public health protection overtime.
Violations of health-based standards (as represented in Indicator E7) may be under-reported as
a result of monitoring and reporting violations. An EPA audit of drinking water data from 2002-
2004 found that only 62% of health-based standards violations were reported to SDWIS.86
Therefore, the data on systems reporting no violations of health based standards include a
number of systems that have not gathered or reported all of the required data needed to make
this determination.
Indicators E7 and E8 provide information about the extent to which contaminants in
community water systems reach levels that may be of concern for children. However, the
indicators do not provide a direct measure of children's exposure to drinking water
contaminants and do not give an indication about how drinking water violations are related to
health risks. A violation of a health-based standard represents a potential concern for children's
health, but the importance of any violation depends on the particular contaminant, the
magnitude and duration of the violation, and the extent of the violation within a system.
Indicator E7 does not reflect the extent to which a standard has been exceeded or the extent to
which a water system's distribution system may have been affected by a violation. The
indicator does not take into account the duration of a violation within any calendar year.
However, a violation that continues over an extended period of time is included in the indicator
for each calendar year in which it occurs. A large water system with a single violation of short
duration may significantly affect the indicator value for a single year.
The ability to examine children's potential exposure to contaminated drinking water is limited by
the type of information collected and stored in the SDWIS/FED database. States are not required
to report the actual contaminant levels measured to SDWIS/FED; instead, they report when
standards are not met. As a result, SDWIS/FED data cannot be used to analyze national or local
trends in contaminant concentrations, or to provide comparisons to the current health-based
standards across all years shown.1 EPA is working with states to develop a new drinking water
data system that will compile and make available actual measurements of contaminant levels.
1 EPA requires community water systems to provide annual drinking water quality reports to their customers.
These reports summarize the contaminants measured in each system's drinking water over the course of a year,
providing much more detail than the information reported to SDWIS. The drinking water quality reports for many
systems can be found at: http://water.epa.gov/lawsregs/rulesregs/sdwa/ccr/index.cfm.
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Indicators E7 and E8 are based on drinking water provided to residences served by community
water systems. Community water systems are public water systems that serve water to the
same residential population year-round.92 The indicators do not account for all sources of
children's drinking water. Some drinking water comes from other types of public water
systems, including those that may not serve residences, or may not operate year-round (e.g.,
schools, factories, office buildings, and hospitals that have their own water systems; gas
stations and campgrounds); and bottled water." 93~95
In addition, many homes are not served by community water systems and instead obtain their
drinking water from individual residential wells.93'96 EPA does not have the authority under the
Safe Drinking Water Act to regulate wells that serve fewer than 25 persons or 15 service
connections. Thus, the SDWIS/FED database does not contain data on non-public water
systems, such as privately owned household wells, that are not required to monitor or report
the quality of drinking water to EPA.94'97 In 2000, approximately 15% of the total U.S.
population was served by non-public water systems97 and more than 90,000 new domestic
wells are installed every year.98 Separate data collection activities have found that the
contaminants in untreated groundwater are generally at lower levels than the MCL; however,
more than 20% of wells sampled by the U.S. Geological Survey between 1991 and 2004
contained at least one contaminant at a level of potential health concern.99 Approximately 4%
of the 2,167 sampled wells exceeded the nitrate MCL, and 7% exceeded the arsenic MCL.99
Nitrate concentrations above the MCL were more frequently detected in agricultural regions
than any other land-use setting.99 Groundwater-sourced wells in rural and agricultural regions
may be at an increased risk for nitrate and nitrite contamination due to local fertilizer use and
animal waste runoff.100
Bottled water is regulated by the Food and Drug Administration.
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Indicator E7
Estimated percentage of children ages 0 to 17 years served by community
water systems that did not meet all applicable health-based drinking water
standards, 1993-2009
Any health-based standard
Any health-based standard
Total
coliforms
Chemical and
¥ radionuclide
(treatment
Lead
and copper
Disinfectants and
disinfection byproducts
Surface water
^treatment
1993 1995 1997 1999 2001 2003 2005 2007 2009
Data: U.S. Environmental Protection Agency, Office of Water, Safe Drinking Water Information
System, Federal Version
Note: Breaks in lines for "Any health-based standard" and "Surface water treatment" reflect
substantial regulatory changes implemented in 2002.
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Data characterization
Data for this indicator are obtained from EPA's database to which states are required to report public
water system violations of national drinking water standards.
All violations of health-based standards are supposed to be reported to the database; however, it is known
that not all violations are reported and the magnitude of underreporting is not known.
Some drinking water standards have been changed over time to increase the level of public health
protection; therefore, as noted on the figure, some types of violations in more recent years are not strictly
comparable to violations in earlier years.
Non-public drinking water systems, such as private wells, are not represented in the database. In 2000,
about 15% of the U.S. population was served by non-public water systems.
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The estimated percentage of children served by community drinking water systems that did
not meet all applicable health-based standards declined from 19% in 1993 to about 5% in
2001. Since 2002, this percentage has fluctuated between 7% and 13%, and was 7% in 2009.
The estimated percentage of children served by community drinking water systems that did
not meet surface water treatment standards varied substantially from 2002-2007, following
the adoption of new regulatory requirements. The percentage was more consistent from
2007-2009, and was 2% in 2009.
Total coliforms indicate the potential presence of harmful bacteria associated with
infectious illnesses. The estimated percentage of children served by community drinking
water systems that did not meet the health-based standard for total coliforms was about
10% in 1993 and about 3% in 2009.
A new standard for disinfection byproducts was adopted in 2001. The estimated percentage
of children served by community water systems that had violations of the disinfection
byproducts standard has declined steadily from 3% in 2003 to about 1% in 2009.
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Indicator E8
Estimated percentage of children ages 0 to 17 years served by community
water systems with violations of drinking water monitoring and reporting
requirements, 1993-2009
Disinfectants and disinfection byproducts
Chemical and
^radionuclide
urface water treatment
Lead
and copper
water treatment
1993 1995 1997 1999 2001 2003 2005 2007 2009
Data: U.S. Environmental Protection Agency, Office of Water, Safe Drinking Water Information
System, Federal Version
Note: Breaks in lines for "Any violation" and "Surface water treatment" reflect substantial
regulatory changes implemented in 2002.
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Data characterization
Data for this indicator are obtained from EPA's database to which states are required to report public
water system violations of national drinking water standards.
Not all violations of monitoring and reporting requirements are reported to the database, and the
magnitude of underreporting is not known.
Some drinking water standards have been changed over time to increase the level of public health
protection; therefore, as noted on the figure, some types of violations in more recent years are not strictly
comparable to violations in earlier years.
Non-public drinking water systems, such as private wells, are not represented in the database. In 2000,
about 15% of the U.S. population was served by non-public water systems.
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Between 1993 and 2009, the estimated percentage of children served by community water
systems that had at least one monitoring and reporting violation fluctuated between about
11% and 23%, and was 13% in 2009.
In 1993, approximately 6% of children served by community water systems lived in an area
with significant monitoring and reporting violations for lead and copper. This figure dropped
to about 3% in 2009.
The estimated percentage of children served by community water systems with a chemical
and radionuclide monitoring violation has varied between 4 and 9%, and was 4% in 2009.
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Environments and Contaminants | Chemicals in Food
Chemicals in Food
Children's diets are an important pathway for exposure to some environmental chemicals and
other contaminants. Children may be at a greater risk for exposures to contaminants because
they consume more food relative to their body weight than do adults. Additionally, children's
dietary patterns are often less varied than those of adults, suggesting that there are greater
opportunities for continuous exposure to a food borne contaminant than in adults.1
Food contamination can come from multiple sources, including antibiotics and hormones in
meat and dairy products, as well as microbial contamination that can lead to illness. An
estimated 48 million Americans suffer from food borne illnesses each year,2 and children under
age five have the highest incidence of most of these infections.3 Microbial contamination of
food is monitored and regulated by a number of federal agencies, including the Department of
Agriculture and the Food and Drug Administration.1 In addition, a wide variety of chemicals
from man-made sources may be found in or on foods, typically at low levels. Chemicals in foods
may come from application of pesticides to crops, from transport of industrial chemicals in the
environment, or from chemicals used in food packaging products. A number of persistent
environmental contaminants tend to accumulate in all types of animals, and are frequently
found in meat, poultry, fish, and dairy products. Other chemicals, such as perchlorate and a
variety of pesticides, are often found in fruits, vegetables, and other agricultural commodities.
Some chemicals in food, such as mercury and perchlorate, have naturally occurring as well as
man-made sources. The health risks from chemicals in food are dependent on both the actual
level of a chemical in the food as well as the amount of the food consumed by individuals.
Following this text, an indicator is presented for organophosphate pesticides in selected foods.
Many chemicals of concern in food lack sufficient data to generate reliable, nationally
representative indicators, particularly for children. Selected chemicals of concern for children's
health that are frequently found in foods are summarized below. Further details can be found
in the Biomonitoring section of this report for several of these chemicals, including
methylmercury, polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs),
phthalates, perfluorochemicals (PFCs), and perchlorate.
Methylmercury
Mercury is a naturally occurring element that is released to the environment from a variety of
sources, including the combustion of coal, the use of mercury in industrial processes, and from
breakage of products such as mercury thermometers and fluorescent lighting, as well as from
natural sources such as volcanoes. Mercury may enter water bodies through direct release or
through emissions to the atmosphere that are subsequently deposited to surface waters.
1 More information on microbial contaminants in food is available at
http://www.fda.gov/Food/ResourcesForYou/Consumers/ucml03263.htm, http://fsrio.nal.usda.gov/pathogen-
detection-and-monitoring, and
http://www.fsis.usda.gov/fact_sheets/Foodborne_lllness_&_Disease_Fact_Sheets/index.asp.
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Bacteria in water bodies convert the deposited mercury into methylmercury.4 Methylmercury
can be absorbed by small aquatic organisms that then are consumed by predators, including
fish.5 As each organism builds up methylmercury in its own tissues, and as smaller fish are
eaten by larger fish, concentrations of methylmercury can accumulate, particularly in large fish
with longer lifespans6"8 such as sharks and swordfish.9
EPA has determined that methylmercury is known to have neurotoxic and developmental effects
in humans.10 This conclusion is based on severe adverse effects observed in exposed populations
in two high-dose mercury poisoning events in Japan and Iraq. Some other studies of populations
with prenatal exposure to methylmercury through regular consumption of fish have reported
more subtle adverse effects on childhood neurological development.11"15 Although ingestion of
methylmercury in fish may be harmful, other compounds naturally present in many fish (such as
high quality protein and other essential nutrients) are extremely beneficial.
In particular, fish are an excellent source of omega-3 fatty acids, which are nutrients that
contribute to the healthy development of infants and children.16 Pregnant women are advised to
seek dietary sources of these fatty acids, including many species offish. However, the levels of
both methylmercury and omega-3 fatty acids can vary considerably by fish species. Thus, the type
of fish, as well as portion sizes and frequency of consumption are all important considerations for
health benefits offish and the extent of methylmercury exposure.16 For this reason, EPA and the
U.S. Food and Drug Administration (FDA) provide advisory information on fish consumption to
females who are pregnant, breastfeeding, or of childbearing age, and to young children. The
advisory encourages consumption of up to 12 ounces per week of a variety of fish and shellfish
that are lower in mercury, or, in the absence of a local advisory, consumption of up to 6 ounces
per week of fish caught from local waters and no other fish that week. EPA and FDA also
recommend that these categories of women and young children avoid consuming shark,
swordfish, tile fish, or king mackerel, because these species may contain high levels of
methylmercury.17 Fish that are high in omega-3 fatty acids and low in mercury are expected to
offer the greatest health benefits.9'16'18 EPA and FDA are currently working to update the fish
consumption advisory to incorporate the most current science regarding the health benefits of
fish consumption and the risks from methylmercury in fish. In 2011, the Departments of
Agriculture and Health and Human Services jointly released the 2010 Dietary Guidelines for
Americans, which recommended that pregnant or breastfeeding women should consume 8-12
ounces of seafood per week, but avoid consumption of the same high-mercury-containing fish
identified in EPA and FDA's advisory.19 More information regarding current fish advisories, and
links to lists offish and shellfish typically containing lower levels of mercury, can be found at
http://water.epa.gov/scitech/swguidance/fishshellfish/fishadvisories/general.cfmfttabs-4. Tribal
and state-specific fish advisories can be found at http://fishadvisoryonline.epa.gov/General.aspx.
Polychlorinated biphenyls
Polychlorinated biphenyls (PCBs) are a group of persistent chemicals used in electrical
transformers and capacitors for insulating purposes, in gas pipeline systems as a lubricant, and
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Environments and Contaminants | Chemicals in Food
in caulks and other building materials. The manufacture, sale, and use of PCBs were generally
banned by law in 1979, although EPA regulations have authorized their continued use in certain
existing electrical equipment. Due to their persistent nature, large reservoirs of previously
released PCBs remain in the environment. PCBs accumulate in fat tissue, so they are commonly
found in foods derived from animals. Consumption offish is a common source of PCB exposure,
but other foods with lower PCB levels that are consumed more frequently, including meat,
dairy, and poultry products, also contribute to PCB exposure.20'21 A study by the U.S.
Department of Agriculture found that levels of certain PCBs in beef and chicken declined
between 2002 and 2008, while levels in turkey and pork remained relatively constant during
the same years.22 Exposure to PCBs remains widespread;23'24 however, declining environmental
levels of PCBs suggest that children today are exposed to lower levels of PCBs compared with
children in previous generations.20'25"28
Prenatal exposure to PCBs has been associated with adverse effects on children's neurological
development and impaired immune response, primarily through studies of populations that
consume fish regularly.29"31 Although there is some inconsistency in the epidemiological
literature, several reviews of the literature have found that the overall evidence supports a
concern for effects of PCBs on children's neurological development.29'30'32"34 The Agency for
Toxic Substances and Disease Registry has determined that "Substantial data suggest that PCBs
play a role in neurobehavioral alterations observed in newborns and young children of women
with PCB burdens near background levels."20 Some studies have also detected associations
between childhood exposure and adverse health effects.30'35"37 In addition to PCBs, many other
organochlorine chemicals, including dioxins, dibenzofurans, and organochlorine pesticides, are
persistent and bioaccumulative and are frequently found in foods derived from animals.38
Polybrominated diphenyl ethers
Polybrominated diphenyl ethers (PBDEs) are a class of flame retardants used in many
applications, including furniture foam, small appliances, and electronic products. PBDEs are
intended to slow the ignition and rate of fire growth. Of three forms of PBDEs once used in the
United States (pentaBDE, octaBDE, and decaBDE), only the decaBDE form, used primarily in
televisions, personal computers, and other electrical appliances, is still in production.
Manufacturers of decaBDE have agreed to phase out all uses of the chemical by the end of
2013.39 However, products manufactured prior to the elimination of the pentaBDE and octaBDE
forms in 2004, and products manufactured prior to the phaseout of decaBDE in 2013, can
remain in use and contribute to the presence of PBDEs in the environment.
Like PCBs, PBDEs are persistent in the environment, accumulate in fat tissue, and have been
found in a variety of foods, including fish, meat, poultry, and dairy products as well as breast
milk.40"48 Exposure studies have concluded that the presence of PBDEs in house dust and in
foods are both important contributors to PBDE exposures for people of all ages, and that
exposures from house dust are generally greater than those from food.46'47'49"54 PBDE toxicity to
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Chemicals in Food I Environments and Contaminants
the developing nervous system as well as endocrine disruption have been identified as areas of
potential concern.40'55"59
Bisphenol A
Bisphenol A (BPA) is an industrial chemical used in the production of epoxy resins used as inner
liners of metallic food and drink containers to prevent corrosion. BPA is also used in the
production of polycarbonate plastics that may be used in food and drink containers. The
primary route of human exposure to BPA is through diet, when BPA migrates from food and
drink containers, particularly when a container is heated.60"62
Much of the scientific interest in BPA is related to published research suggesting that BPA may
be an endocrine disrupting chemical.63'64 Endocrine disrupters act by interfering with the
biosynthesis, secretion, action, or metabolism of naturally occurring hormones.63"65 BPA has
demonstrated developmental effects in laboratory animals at high doses, though the effects of
lower doses similar to typical human exposure levels are the subject of scientific debate.61'66"70
Based on a critical review of the existing scientific literature, in 2008 the National Toxicology
Program (NTP) determined that there was "some concern" (the midpoint on a five-level scale
ranging from "negligible" to "serious")" for effects of BPA on the brain, behavior, and prostate
gland in fetuses, infants, and children.61 Although there is uncertainty regarding the effects in
humans of BPA at typical exposure levels, several retailers and manufacturers have begun
phasing out baby products such as bottles and sippy cups that contain BPA. Several states have
also introduced legislation to ban or limit BPA in food containers and consumer products.
Additional studies by both government and non-government entities are being conducted to
provide additional information and address uncertainties about the safety of BPA.
Phthalates
Phthalates are a class of chemicals commonly used to increase the flexibility of plastics in a
wide array of consumer products, and have been used in food packaging.71"74 Some phthalates
have been found at higher levels in fatty foods such as dairy products, fish, seafood, and oils,
which are most likely to absorb phthalates.74 Phthalates in a mother's body can enter her
breast milk. Ingestion of that breast milk and infant formula containing phthalates may also
contribute to infant phthalate exposure.75 Certain phthalates are suspected endocrine
disrupters, and have shown a number of reproductive and developmental effects in laboratory
animal studies76"85 as well as some reported associations in human epidemiological studies.86"89
Perfluorochemicals
Perfluorochemicals (PFCs) are a group of chemicals used in a variety of consumer products,
including food packaging, and in the production on nonstick coatings on cookware.90'91 Long-
chain PFCs, including perfluorooctane sulfonic acid (PFOS) and perfluorooctanoic acid (PFOA),
More information on NTP concern levels is available at http://www.niehs.nih.gov/news/media/questions/sya-bpa.cfm.
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have already been or will be phased out by the chemical industry by 2015, although the
persistence of these chemicals means that they will remain in the environment for several years
despite reductions in emissions. While the routes of human exposure to PFCs are not fully
understood, two recent studies have identified food consumption as the primary exposure
pathway.92'93 RFC-treated food-contact packaging, such as microwave popcorn bags, may be a
source of RFC exposure.94'95 Heating these materials may cause PFCs to migrate into food, or
into the air where they may be inhaled.1" Meats may also be contaminated with PFCs due to
exposure of source animals to air, water, and feed contaminated with PFCs.95"97 PFCs have also
been detected in some plant-based foods.93 Studies in laboratory animals have demonstrated
reproductive and developmental toxicity of PFCs.98'99 Some human health studies have
reported associations between prenatal exposure to PFCs and a number of adverse birth
outcomes,100"103 while other studies have not.104'105
Perchlorate
Perchlorate is a naturally occurring and man-made chemical that has been detected in surface
water and groundwater in the United States.106"109 Perchlorate is used in the manufacture of
fireworks, explosives, flares, and rocket propellant.107'109 Perchlorate has been detected in
human breast milk, dairy products, as well as in leafy vegetables and other produce.108'110"115
Infant formulas have been found to contain perchlorate, and the perchlorate content of the
formula is increased if it is prepared with perchlorate-contaminated water.116"118
Exposure to high doses of perchlorate has been shown to inhibit iodide uptake into the thyroid
gland, thus possibly disrupting the function of the thyroid and potentially leading to a reduction
in the production of thyroid hormone.107'119'120 Thyroid hormones are particularly important for
growth and development of the central nervous system in fetuses and infants.121 Due to the
sensitivities of the developing fetus, perchlorate exposures among pregnant women, especially
those with preexisting thyroid disorders or iodide deficiency, carry the potential for risk of
adverse health effects.
Organophosphate Pesticides
Agricultural crops are frequently treated with pesticides to control insects and other pests that
may affect crop growth. Some of the most prevalent classes of pesticides used in growing food
crops are the carbamates, pyrethroids, and the organophosphates. After crops are harvested,
they may retain residues of these pesticides. Apples, corn, oranges, rice, and wheat are among
the agricultural commodities consumed in large amounts by children.
111 The U.S. Food and Drug Administration recently worked with several manufacturers to remove grease-proofing
agents containing C8 perfluorinated compounds from the marketplace. These manufacturers volunteered to stop
distributing products containing these compounds in interstate commerce for food-contact purposes as of October
1, 2011. For more information, see
http://www.fda.gov/Food/FoodlngredientsPackaging/FoodContactSubstancesFCS/ucm308462.htm.
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Organophosphates are one class of pesticides that are of concern for children's health.
Examples of organophosphate pesticides include chlorpyrifos, azinphos methyl, methyl
parathion, and phosmet. These pesticides are frequently applied to many of the foods
important in children's diets, and certain organophosphate pesticide residues can be detected
in small quantities on these foods. Organophosphates can interfere with the proper function of
the nervous system when exposure is sufficiently high.1'122 Childhood is a period of increased
vulnerability, because many children may have low capacity to detoxify organophosphate
pesticides through age 7 years.123 Recent studies have reported an association between
prenatal organophosphate exposure and childhood attention deficit/hyperactivity disorder
(ADHD) in U.S. communities with relatively high exposures to organophosphate pesticides,124 as
well as with exposures found within the general US population.125 Other recent studies have
reported associations between prenatal organophosphate pesticide exposures and a variety of
neurodevelopmental deficits in childhood, including reduced IQ, perceptual reasoning, and
memory.126"128 Since 1999, EPA has imposed restrictions on the use of the organophosphate
pesticides azinphos methyl, chlorpyrifos, and methyl parathion on certain food crops and
around the home, due largely to concerns about potential exposures of children.129"131
The 1996 Food Quality Protection Act required EPA to identify and assess the extent of dietary
pesticide exposure in the United States, and to determine whether there was a "reasonable
certainty of no harm" to vulnerable populations including infants and children.132 The U.S.
Department of Agriculture's Pesticide Data Program (PDP) provides data annually on pesticide
residues in food, with a specific focus on foods often consumed by children.133 Other
researchers have supplemented the PDP with their own analyses. A recent study measured
pesticide residues in 24-hour duplicate food samples of fruits, vegetables, and juices served to
children, and found that 14% of the samples contained at least one organophosphate
pesticide.134 Additional pesticide residue data are available from FDA's pesticide residue
monitoring program.135 A number of pesticide residues, along with a variety of other chemicals
in food, are also measured in FDA's Total Diet Study.136 When pesticide residue data are
combined with dietary consumption surveys, it can be possible to estimate pesticide exposure
from dietary intake.
Indicator E9 presents the percentage of samples of two fruits and two vegetables analyzed by
the USDA PDP that have detectable residues of organophosphate pesticides. This indicator
allows for a general comparison of the frequency of organophosphate detection over time for
four foods typically consumed by children, although data are not available on each fruit or
vegetable for every year.
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Indicator E9: Percentage of sampled apples, carrots, grapes, and tomatoes with
detectable residues of organophosphate pesticides, 1998-2009
About the Indicator: Indicator E9 presents the percentage of sampled apples, carrots, grapes, and
tomatoes that were found to contain detectable residues of organophosphate pesticides from 1998-
2009. These foods were selected because they are frequent components of children's diets, and
because data for these foods were available for multiple years. The data are from an analysis of
pesticide residues in foods conducted annually by the U.S. Department of Agriculture.
Pesticide Data Program
The U.S. Department of Agriculture (USDA) collects data on pesticide residues in food annually.
USDA's Pesticide Data Program (PDP), initiated in 1991, focuses on measuring pesticide
residues in foods that are important parts of children's diets, including apples, apple juice,
bananas, carrots, grapes, green beans, orange juice, peaches, pears, potatoes, and tomatoes.
Samples are collected from food distribution centers in 10 states across the country.137 The PDP
has a statistical design in which food samples are randomly selected from the national food
distribution system and reflect what is typically available to the consumer, including both
domestic and imported foods.137 Different foods are sampled each year. In its history, the PDP
has tested for more than 440 different pesticides.133 In 2009, the PDP analyzed fruit and
vegetables for 309 pesticides and related chemicals. Prior to analysis, the PDP processes
samples by following the preparations an average individual would use before consuming an
item. This includes washing fruits and vegetables, as well as removing inedible portions of a
food item. For example, tomatoes and grapes are washed with the stems and other materials
removed, while apples are washed and the stems and cores are removed.
Data Presented in the Indicator
Indicator E9 displays the percentage of apple, grape, carrot, and tomato samples with
detectable organophosphate pesticide residues reported by the PDP from 1998-2009. These
four foods were selected as those that were sampled by the PDP in at least five years from
1998-2009 and are among the 20 most-consumed foods identified in an analysis by EPA.138
Other foods not shown here may have either greater or lesser frequencies of organophosphate
pesticide residue detection than the four foods presented in this indicator.
The 43 organophosphates that were sampled in every one of the years 1998-2009 are included
in calculation of the indicator; 53 other organophosphates that were added to or dropped from
the program in these years are excluded so that the chart represents a consistent set of
pesticides for all years shown. Some aspects of trends in organophosphate residues could be
missed by the indicator if any organophosphates other than the 43 considered in the indicator
had substantial changes in use on the four selected foods during the years 1998-2009. For
example, a decrease in the percentage of detections of organophosphate residues may reflect
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an actual decrease in the use of organophosphate pesticides, but can definitively represent only
a decrease in the residues of the 43 OPs included in the indicator; it does not account for
potential substitution with other organophosphates or other types of pesticides.
The indicator also defines "detectable" based on the ability to measure residues in the PDF in
1998, so that introduction of more sensitive measurement techniques over time does not affect
the indicator and allows for direct comparison of data collected in previous years with those
collected today. This means that some produce samples analyzed in recent years with improved
detection technology would, for purposes of indicator calculation, be considered to have non-
detectable organophosphate residues based on comparison with the older, higher limit of
detection.IV
The fruits and vegetables shown in this indicator were each sampled in five to seven years
between 1998 and 2009. Gaps in the percentage of residue detections from year to year thus
represent missing information, rather than an absence of organophosphate residues.
This indicator is a surrogate for children's exposure to pesticides in foods: If the frequency of
detectable levels of pesticides in foods decreases, it is likely that exposures will decrease.
However, the indicator does not account for many additional factors that affect the risk to
children. For example, some organophosphates pose greater risks to children than others do,
and residues on some foods may pose greater risks than residues on other foods due to
differences in amounts consumed. The indicator also does not distinguish between residue
levels that are barely detectable and those that are much higher, which would pose a greater
concern for children's health. Finally, exposures to organophosphate pesticides may also occur
by pathways other than the diet, such as ingestion of pesticides present in house dust and
drinking water.
IV An alternate analysis of the data that considered all detectable residues, without holding the limit of detection
constant at 1998 levels, resulted in percentages of food samples with detectable organophosphate pesticide
residues very similar to those shown in the indicator.
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Indicator E9
Percentage of sampled apples, carrots, grapes, and tomatoes with detectable
residues of organophosphate pesticides, 1998-2009
Tomatoes
Data: U.S. Department of Agriculture, Pesticide Data Program
Note: Pesticide residues were measured only in selected years for each food.
Years without data represent missing values, rattier than absence of residues.
America's Children and the Environment, Third Edition
Data characterization
Data for this indicator are obtained from a U.S. Department of Agriculture program that measures
pesticide residues in food samples collected from 10 states.
Food samples are randomly selected from the national food distribution system and reflect what is
typically available to the consumer.
The types of foods sampled change overtime; so, for example, data for pesticide residues on apples are
not available every year.
The indicator is calculated using the measurement sensitivity as of 1998 for each year shown; more
sensitive measurement techniques have been incorporated overtime.
In 1999, 81% of sampled apples had detectable organophosphate pesticide residues. In
2009, 35% had detectable residues.
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In 2000,10% of sampled carrots had detectable organophosphate pesticide residues. In
2007, 5% had detectable residues.
In 2000, 21% of sampled grapes had detectable organophosphate pesticide residues. In
2009, 8% had detectable residues.
In 1998, 37% of sampled tomatoes had detectable organophosphate pesticide residues. In
2008, 9% had detectable residues.
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Environments and Contaminants | Contaminated Lands
Contaminated Lands
Accidents, spills, leaks, and improper disposal and handling of hazardous materials and wastes
have resulted in tens of thousands of contaminated sites across the United States. The nature
of the contaminants and the hazards they present vary greatly from site to site. These
contaminants include industrial solvents, petroleum products, metals, residuals from
manufacturing processes, pesticides, and radiological materials, as well as certain naturally
occurring substances such as asbestos. Contaminated lands can threaten human health and the
environment, in addition to hampering economic growth and the vitality of local communities.
The presence of contaminated soils in a particular location may or may not have health
consequences. Soils, unlike air and water, are not intentionally inhaled, absorbed, or ingested.
Contaminants diffuse more slowly through soil than through air or water, so contaminants are
rarely distributed uniformly across a contaminated site. Soils are a concern if children are
playing, attending school, or residing on or near to contaminated land. People and pets may
track contaminated soils and dusts into homes where infants and toddlers are playing. Some
contaminants may harm or penetrate the skin, and by touching or playing in soil children may
come into direct contact with them. Children may ingest soils through hand-to-mouth play or by
eating without first washing their hands after having touched contaminated soil. Soil dust may
be carried on the wind and inhaled into the lungs, where it can be very damaging. The optimal
approach to minimizing risks to children from contaminated soils is to prevent these exposures.
In addition, contaminated land may contribute to pollution of ground water, surface water,
ambient air, and foods, creating additional potential human exposure routes. For example,
consumption of fish caught at or near a contaminated site may increase risk of exposure to
contaminants from the site. The same is true of drinking water from contaminated ground- or
surface water sources. When drinking water sources are affected at EPA-tracked contaminated
sites, an alternate water supply may need to be provided, in some cases permanently.
Cleanup of contaminated lands may be conducted by EPA, other federal agencies, states, tribes,
municipalities, or the party responsible for the contamination. As of September 2011, EPA's
programs for assessing and cleaning up contaminated lands track roughly 22 million acres of
land across the United States, or nearly 1% of the entire U.S. land mass.1 EPA and its partners
conduct work on contaminated lands through federally mandated programs such as the
Superfund and Corrective Action programs. The Superfund program, implemented under the
Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA), aims to
clean up some of the most hazardous and highly polluted inactive commercial, industrial, and
residential properties in the country. The Corrective Action program, implemented under the
Resource Conservation and Recovery Act (RCRA), aims to control and clean up releases at
operating hazardous waste treatment, storage, and disposal facilities. EPA is also responsible
for other programs that focus on management of contaminated lands, including Brownfields,
underground storage tanks, and RCRA waste management and minimization programs.
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EPA prioritizes sites for cleanup using information from initial investigations regarding possible
threats to human health or the environment. EPA's primary concern is to protect people from
the most contaminated lands and to clean up these sites to a standard that is protective, and
that state, local, or tribal governments and communities deem appropriate based on the future
uses of the individual site. EPA and partner agencies work to contain possible routes for
exposure as soon as possible.2'3
When a potential pathway for exposure is identified, a process is normally initiated for the
pathway to be minimized or eliminated. For Superfund sites and for hazardous waste facilities
requiring Corrective Action, EPA or authorized state regulators assess contaminated media,
exposure pathways, risks from complete pathways, and the significance of any risks. If no
significant human health risks are identified, a determination is made that the site has all
human health protective measures in place. If significant human health risks are or may be
present, regulators choose site-specific controls (e.g., fencing, caps, containment walls) and
cleanup activities (e.g., excavation, groundwater treatment) necessary to reduce the risks.
If additional contamination or previously unrecognized pathways of exposure are identified, a
site that is designated as having all human health protective measures in place may lose that
designation until pathways of exposure are controlled.
When a site is designated as having all human health protective measures in place, known
pathways of exposure have been controlled, although additional cleanup work may remain.
These sites pose a reduced risk to children compared with most sites that have not yet been
designated as having all human health protective measures in place. However, there can be a
number of reasons why a site has not yet achieved that designation. For example, some sites
have not yet been adequately assessed, and it is thus unknown whether these sites pose
significant risk to human health.
This approach to managing potential exposures is based on identified presence of contaminants
and potential exposure pathways because there is often an absence of information identifying
actual children's exposures; however, there are notable exceptions where EPA and other
federal and state agencies have addressed documented exposures.4"10
Children who have been exposed to contaminants do not all experience the same health
outcomes. The magnitude and duration of an exposure, the pathway of exposure (ingestion,
inhalation, dermal), the stage of development at which a child is exposed, and differences in
genetic susceptibility all influence the variation in outcome from exposure. Even after exposure
characteristics and genetic factors have been taken into consideration, variation remains in
risks experienced by different individuals and different communities as a consequence of
exposures to contaminants. This variation may in part be explained through socio-cultural and
socioeconomic factors that have been associated with physical and psychological health,
including family income, unemployment, nutrition, education, housing and infrastructure, race,
gender, class, access to health services, social cohesion, participation in local decision-making,
exercise, and health-related behaviors (e.g., smoking, drug abuse).11"22
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Environments and Contaminants | Contaminated Lands
Of the many sociological determinants of health, the relationships between race/ethnicity and
health status and between lower levels of income and less optimal health are among the most
documented.23"26 Because these factors are related to many of the other sociological
determinants, they are frequently used as proxies for a larger set of factors. For these reasons,
the following indicators of children living in proximity to contaminated lands focus on
differences by race/ethnicity and family income level.
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Indicator E10: Percentage of children ages 0-17 years living within one mile of
Superfund and Corrective Action sites that may not have all human health protective
measures in place, 2009
Indicator Ell: Distribution by race/ethnicity and family income of children living near
selected contaminated lands in 2009, compared with the distribution by race/ethnicity
and income of children in the general U.S. population
About the Indicators: Indicators E10 and Ell present information about children living within one
mile of Superfund sites or RCRA Corrective Action sites that may not have had all human health
protective measures in place as of October 1, 2009. Site boundaries were estimated and a computer
mapping tool was used to identify all land areas within one mile of each of these sites. Data from the
2000 U.S. Census were then used to estimate the population of children living within these areas.
Indicator E10 provides information about U.S. children living within one mile of these selected sites,
including the percentage of children in proximity by race, ethnicity, and family income. Indicator Ell
compares the race/ethnicity profile of children living within one mile of these selected sites with the
profile for all children living in the United States.
Corrective Action and Superfund Sites
EPA's Office of Solid Waste and Emergency Response manages the RCRA Corrective Action
Program and the Superfund Program, and maintains inventories of sites in each program. The
Comprehensive Environmental Response, Compensation, and Liability Information System
(CERCLIS) database provides information on Superfund sites, and the Resource Conservation
and Recovery Act Information (RCRAInfo) database provides information on RCRA Corrective
Action sites. As of October 1, 2009 there were 1,653 Corrective Action and Superfund sites,
totaling more than 10 million acres, that may not have had all human health protective
measures in place.3 Of the 3,746 Corrective Action sites at that time, 1,297 fell into this
category. Of the 1,727 Superfund sites (which includes both sites that are on the National
Priorities List and sites that are not on the NPL but for which the Superfund program has some
responsibilities), a total of 356 fell into this category. The location and extent of each site are
characterized by the latitude and longitude of a single point within that site, and the area (total
acres) of the site, obtained from the official documentation for each site.1 A map displaying the
distribution of these sites across the country and their prevalence in urbanized areas is
available in the Methods document for this topic (available at www.epa.gov/ace).
Some of the largest sites that EPA oversees are federal facilities. Among the sites that may not
have had all human health protective measures in place in 2009, 47 Corrective Action sites and
62 Superfund sites are federal facilities.
1 Actual boundaries of the sites are available in digital form for only a few sites.
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Estimating Site Areas and Children's Proximity
For purposes of indicator calculation, the actual land area within each site was approximated
using the latitude/longitude and acreage information. A circle whose area equaled the site's
acreage was drawn around each site's latitude/longitude identification point. It is important to
note that these areas are not the actual site boundaries, and are not expected to reflect the
actual area of contamination. Contamination will likely be determined by factors such as the
release of waste, the contours of the land, and groundwater flow. Sites also have hotspots
(areas with high levels of contamination) and areas that have been remediated or were never
contaminated. The site boundaries are therefore likely to overestimate the area of a site that is
contaminated. Nonetheless, approximating the area of a site with a circle is a reasonable
assumption that provides the best available information for this analysis.
To identify land areas in proximity to the selected contaminated lands, a one-mile buffer was
drawn around the circle representing each site. Data on total child population, and population
by race and ethnicity, were collected from the 2000 Census for children living in Census blocks
whose center point was within the one-mile buffer boundary. Information on family income
levels (percentage above and below poverty level, by race and ethnicity) was extrapolated for
these blocks from Census block group data. Data from the 2000 census were used in order to
obtain necessary population race/ethnicity and income statistics at the local level; this
information is not available in the 2009 census estimates."
Data Presented in the Indicators
Each indicator presents a characterization of the population of children living within one mile of
Superfund or RCRA Corrective Action sites that may not have had all human health protective
measures in place as of October 1, 2009. Indicator E10 shows the percentage of children living
within one mile of a site, by race/ethnicity and family income. Indicator Ell shows the
proportion of children of each race and ethnicity among those living in proximity to the selected
sites, compared with the race/ethnicity proportions among all children in the United States. This
comparison is also made for children living in homes with incomes below poverty level. Tables of
values for these indicators at the state level are available in the Appendix to this document.
Data for seven race/ethnicity groups are presented in the indicators: White, Black, Asian,
American Indian or Alaska Native (AIAN), Native Hawaiian or Other Pacific Islander (NHOPI), All
Other Races, and Hispanic. The "All Other Races" category includes all other races not specified,
together with those individuals who report more than one race. Children of Hispanic ethnicity
may be of any race. Data presented by race do not include any designation of ethnicity; for
example, the indicator value labeled "Black" includes both Hispanic and non-Hispanic Black
children, and children who are Black and Hispanic are included in the indicator values for both
" A greater percentage of children were living in poverty in 2009 than in 2000; therefore, these calculations will
understate the proportion of children below poverty living in proximity to the selected contaminated lands in 2009.
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"Black" and "Hispanic" children. Three family income categories are presented in the indicators:
all incomes, below the poverty level, and greater than or equal to the poverty level.
Designation of sites that may not have all human health protective measures in place were
made for the first time in 2009; trend data are not reported because these designations were
not analyzed for purposes of this report in earlier years.1"
For purposes of these indicators, proximity to a site is used as a surrogate for potential
exposure to contaminants found at these sites. The indicators do not imply any specific
relationship between childhood illness and a child's proximity to a Superfund or Corrective
Action site. Information on amounts of environmental contamination, which would be a source
of exposure to children, is generally available for these sites, but information on the extent to
which children are actually exposed is not generally available. Because of the ways in which
children can be exposed to land contaminants and the potential for certain contaminants to
move into groundwater or to vaporize through soil, the proximity to contaminated sites may
increase the potential for exposure and the possible health consequences, but proximity to a
site does not mean that there will always be exposure. Nor does proximity to a site represent
risks of adverse health effects. The risk of exposure posed to children varies significantly across
all the different types of contaminated sites and the different activities of children on or near
the sites. Many sites do not pose risks outside of property boundaries.
These indicators present a high-end approximation of children at risk from the Corrective
Action and Superfund sites that may not have all human health protective measures in place,
but do not include children near the much larger universe of Brownfield sites, leaking
underground storage tanks, and sites addressed solely by state, tribal, and local authorities or
private companies. While the indicators include those RCRA Corrective Action sites assumed to
have the most potential for contamination, these sites represent only a subset of waste
treatment, storage, or disposal facilities currently regulated by EPA. The indicators also do not
capture the proportion of children living near contaminated sites that are yet to be identified.
Access to uncontrolled contamination remains the greatest risk of potential exposure, and risks
are most likely to have been greatest prior to intervention by EPA and partner agencies. The
ultimate cleanup of these sites best assures reduced health risks for children by eliminating the
possibility of exposure and promotes the health of their communities since cleanup opens the
way for sustainable redevelopment and revitalization opportunities.
111 These data cannot be compared to Indicator E9 from previous editions of America's Children and the
Environment. Previous versions considered only Superfund sites; represented each site as a single point, rather
than an area; and did not consider the status of human health protective measures put in place at the sites.
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Environments and Contaminants | Contaminated Lands
Indicator E10
Percentage of children ages 0 to 17 years living within one mile of Superfund
and Corrective Action sites that may not have all human health
protective measures in place, 2009
Incomes
All Races/Ethnicities
White
All American Indian/Alaska Native
Asian
Native Ha
AM Other Races
All Races/Ethnicities
At or White
Above
Am
Poverty Asian
AllOther Races
Hispanic
All Races/Ethnicities
White
Below
Poverty American Indian/Alaska
Asian
Level Native Hawaiia
All Other Races
Data: U.S. Environmental Protection Agency, Office of Solid Waste and Emergency Response,
CERCLIS and RCRAInfo
Note: Hispanic children may be of any race.
America's Children and the Environment, Third Edition
Data characterization
Data on Superfund and RCRA Corrective Action sites are reported by EPA regional offices and states, and
compiled in EPA's databases of information on contaminated sites.
Information for each site includes the site name, state in which the site is located, latitude, longitude,
estimated acreage, and site status.
Areas of known or suspected contamination may be less than the total acreage at each site.
i Approximately 6% of all children in the United States lived within one mile of a Corrective
Action or Superfund site that may not have had all human health protective measures in
place as of 2009.
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About 8% of Black children, 9% of Asian children, 9% of children of All Other Races, and 10%
of Native Hawaiian and Other Pacific Islander (NHOPI) children lived in proximity to the
designated sites. About 8% of Hispanic children, who may be of any race, lived in proximity
to the sites. In contrast, about 5% of White children and 5% of American Indian/Alaska
Native children lived in proximity to the designated sites.
About 8% of all children in the United States in families with incomes below the poverty
level lived within one mile of the designated sites, compared with about 5% of children
above the poverty level. The proportion of children below the poverty level in proximity to
the designated sites was generally greater than the proportion for those above poverty
level for each race and ethnicity; the only exception to this pattern was for American Indian
and Alaskan Native (AIAN) children.
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Indicator Ell
Distribution by race/ethnicity and family income of children living near
selected contaminated lands* in 2009, compared with the distribution
by race/ethnicity and income of children in the general U.S. population
All
Incomes
White ^H Black
^H NHOPI
AIAN ^^B Asian
All Other Races
Hispanic any race
Non-Hispanic any race
Children Near Sites
All U.S. Children
23.5%
Children Near Sites
All U.S. Children
Below
Poverty
Level
Children Near Sites
All U.S. Children
31.7%
Children Near Sites
All U.S. Children
Data: U.S. EPA, Office of Solid Waste and Emergency Response, CERCLIS
and RCRAInfo
Note: AIAN = American Indian/Alaska Native. NHOPI = Native Hawaiian or Other Pacific Islander.
Hispanic children may be of any race.
* Within one mile of Superfund and Corrective Action sites that may not have all human
health protective measures in place.
America's Children and the Environment, Third Edition
Data characterization
Data on Superfund and RCRA Corrective Action sites are reported by EPA regional offices and states, and
compiled in EPA's databases of information on contaminated sites.
Information for each site includes the site name, state in which the site is located, latitude, longitude,
estimated acreage, and site status.
Areas of known or suspected contamination may be less than the total acreage at each site.
Approximately 21% of all children living within one mile of a Corrective Action or Superfund
site that may not have had all human health protective measures in place were Black, while
15% of children in the United States as a whole are Black. Black children account for about
30% of all U.S. children in homes below poverty level; among children below poverty level
living within one mile of a designated site, about 38% were Black.
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Contaminated Lands I Environments and Contaminants
The percentages of Asian children, Hispanic children, and children of "All Other Races"
among children living close to the designated sites were also greater than the percentages
of these children in the entire U.S. population, considering all incomes and considering only
those in homes with incomes below poverty level.
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Environments and Contaminants | Climate Change
Climate Change
Climate change refers to any significant change in climate variables including temperature,
precipitation, or wind that lasts for decades or longer. It may include changes in variability of
average weather conditions or extreme weather conditions. Both human activities and natural
factors contribute to climate change. Human activities, such as burning fossil fuels; cutting
down forests; and developing land for farms, cities, and roads, release heat-trapping
greenhouse gases into the atmosphere. Natural causes, such as changes in the Earth's orbit, the
sun's intensity, the circulation of the ocean and the atmosphere, and volcanic activity,
contribute to climate change in a variety of ways.1
Climate change may increase children's exposure to extreme temperatures, polluted air and
water, extreme weather events, wildfires, infectious disease, allergens, pesticides, and other
chemicals. These exposures may affect children's health in a number of direct and indirect
ways. It is important to note that climate change will likely result in a mix of both positive and
negative health impacts. For example, warmer summers may increase the number of heat-
related injuries and deaths, while warmer winters may result in fewer cases of cold-related
injuries and deaths.2 The effects of climate change will also vary from one location to another
and will likely change over time as climate change continues.2'3 Furthermore, the human health
risks from climate change may be affected strongly by changes in health care advances and
accessibility, public health infrastructure, and technology.2'4"6
Direct effects of extreme temperatures are one area of concern, as climate change is expected
to increase the number and intensity of hot days, hot nights, and heat waves in the United
States.5'7'8 Heat exposure can result in heat rashes, heat stroke, heat exhaustion, and even
death; children may be especially at risk because they often spend more time outside than
adults do.2'9 Children's bodies are less effective at adapting to heat compared with those of
adults.10 Also, children may not feel the need to drink as urgently, which can lead to severe
dehydration and electrolyte imbalance.10'11 Humidity can further exacerbate heat stress in
children.10'11 Infants may be especially vulnerable to heat events in part because they depend
on adults for care and are unable to communicate thirst and discomfort.6'12'13 Caregivers can
help protect children from heat-related health effects.14
Many factors can modify the impact of heat exposure, including geographic location, income
level, and the built environment.15 Studies have shown that the temperature at which mortality
and morbidity (e.g., respiratory hospital admissions) can occur from heat exposure varies based
on location.16"18 Extreme heat exposure may have a greater impact on populations living in
regions that experience high temperatures less frequently, such as the Northwest and Midwest
United States. In warmer climates such as those in the South and Southwest United States, the
population may be acclimated to heat and area infrastructure is better designed to
accommodate high temperatures.13'19 A higher income allows families to adapt more easily to
meet the challenges of climate change compared with lower-income families, because they can
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Climate Change | Environments and Contaminants
afford the use of air conditioners and other cooling methods to create a more ideal and
comfortable environment.3
The urban built environment can both exacerbate and alleviate the effects of heat. For
example, high concentrations of buildings in urban areas cause what is known as the urban heat
island effect: generating as well as absorbing and releasing heat, resulting in urban centers that
are several degrees warmer than surrounding areas. Expanding the area of parks and green
spaces and increasing the density of trees in and around cities can help to reduce this effect.6
Warmer winters may have the effect of decreasing the number of cold-related deaths and
injuries.2'15 It is difficult to estimate the net changes in mortality due to climate change;
however, a recent assessment by the United States Global Change Research Program concluded
that increases in heat-related mortality due to climate change are unlikely to be compensated
by decreases in cold-related mortality.8
High temperatures, heat waves, and associated stagnant air masses can increase levels of air
pollution, specifically ground level ozone, fine particulate matter (PIV^.s), nitrogen oxides, and
sulfur oxides.2'6'8'9 These air pollutants can be harmful for children: they may contribute to the
development of new cases of asthma, aggravate preexisting cases of asthma, cause decrements
to lung function, increase respiratory symptoms such as coughing and wheezing, and increase
hospital admissions and emergency room visits for respiratory diseases.20"35 Because children
may spend a lot of time outdoors, often while exerting themselves for sports or play, they can
be especially vulnerable to the impacts of poor air quality.8
Climate change is likely to change the timing, frequency, and intensity of extreme weather
events, including heat waves, hurricanes, heavy rainfall, droughts, high coastal waters, and
storm surges.5'36 These events can cause traumatic injury and death, as well as emotional
trauma. Extreme weather events are also associated with increased risk of food- and water-
borne illnesses as sanitation, hygiene, and safe food and water supplies are often compromised
after these types of events.2 One study found that periods of heavy rainfall were associated
with increased emergency room visits for gastrointestinal illness among children.37 Heavy
rainfall may result in flooding, which can lead to contamination of water with dangerous
chemicals, heavy metals, or other hazardous substances from storage containers or from
preexisting chemical contamination already in the environment.2'36 Elevated temperatures and
low precipitation are also projected to increase the size and severity of wildfires. This can lead
to increased eye and respiratory illnesses and injuries, which include burns and smoke
inhalation.2 Extreme weather events can be especially dangerous for children because they are
dependent on adults for care and protection.7
A number of infectious diseases may be affected by climate change. The combined effects of
increased temperature and precipitation are projected to cause increases in some water-, food-,
and vector-borne illnesses. In general, increased temperature results in higher replication,
transmission, persistence, habitat range, and survival of bacterial pathogens (the effect on viral
pathogens is less clear), and produces a greater number of water- and food-borne parasitic
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Environments and Contaminants | Climate Change
infections.5'6'8 Climate change is also expected to expand or shift the habitat and range of
disease-carrying organisms, such as mosquitoes, ticks, and rodents.5 Changes in the geographic
distribution of disease-carrying organisms may alter the spread of vector-borne diseases such as
Lyme disease, West Nile virus and Dengue fever.5 Children may be at greater risk for these types
of infectious diseases as they spend more time outdoors compared with adults, where they
might contact disease-carrying organisms, and they have less-developed immune systems.14
Climate change, including changes in carbon dioxide (C02) concentrations and temperature,
may affect the growth and distribution of allergen-producing vegetation such as weeds,
grasses, and trees. Climate change has already caused an earlier onset of the U.S. spring pollen
season and a lengthened ragweed season.15'38 The aeroallergens (e.g., pollen) themselves might
be changed in terms of production, distribution, dispersion, and allergic potency.2'6'15 Exposure
to weed and grass pollen has been associated with exacerbation of children's asthma,
emergency room visits, and hospitalizations.39"41
Through various indirect pathways, climate change may lead to increasing levels and/or
frequencies of childhood exposure to harmful contaminants.6'14 Changes in temperature,
rainfall, and crop practices related to climate change are likely to affect exposure to pathogens,
pesticides, and other chemicals in a number of ways. Broader geographic distribution of pests
and increased growth of invasive weeds will likely lead to greater use of pesticides.6'8 Increased
precipitation and increased variability in precipitation are likely to increase pathogen and
contaminant levels in lakes and other surface waters.2'42 The distribution of chemicals in the
environment is likely to change: for example, an increase in ice melts caused by a warming
climate may release some past emissions of globally transported chemicals, such as
polychlorinated biphenyls (PCBs) and mercury, that have been trapped in polar ice.43'44
Increasing concentrations of these chemicals in the atmosphere, and subsequent deposition to
land and water, have the potential to increase concentrations of these chemicals in fish and
other foods derived from animals. Warmer water temperatures may also increase the release of
chemical contaminants from sediments, increasing their uptake in fish.2 Climate change may
result in children spending more time indoors. Buildings that are tightly sealed in response to
adverse weather conditions may result in increased exposure to contaminants from poor
ventilation and higher concentrations of indoor pollutants such as radon, environmental tobacco
smoke, and formaldehyde.45
Children are expected to be especially sensitive to the effects of climate change for a number of
reasons. Young children and infants are particularly vulnerable to heat-related illness and
death.6 Compared with adults, children have higher breathing rates, spend more time outside,
and have less developed respiratory tracts—all making children more sensitive to air pollutants.
Additionally, children have immature immune systems, meaning that they can experience more
serious impacts from infectious diseases.8 The greatest impacts are likely to fall on children in
poor families, who lack the resources, such as adequate shelter and access to air conditioning,
to cope with climate change.8
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Climate Change | Environments and Contaminants
EPA is currently developing a new children's environmental health indicator for climate change.
The new indicator will focus on the frequency of extreme heat events over time. EPA intends to
complete development of this new indicator in 2014, and it will be made available at
www.epa.gov/ace when completed.
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Biomonitoring
Lead 118
Mercury 127
Cotinine 135
Perfluorochemicals (PFCs) 144
Polychlorinated Biphenyls (PCBs) 151
Polybrominated Diphenyl
Ethers (PBDEs) 159
Phthalates 168
Bisphenol A (BPA) 180
Perchlorate 190
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Biomonitoring | Introduction
Introduction
What is biomonitoring?
In the field of human exposure assessment, biomonitoring refers to the measurement of
chemicals in human body fluids and tissues, such as blood, urine, breast milk, saliva, and hair.
Measurements of the levels of pollutants in children's bodies provide direct information about
their exposures to environmental contaminants. Measurements in women who may become
pregnant, currently are pregnant, or currently are breastfeeding provide information about
exposures that may affect conception, the fetus, or the developing child.
Biomonitoring measurements provide an estimate of the amount of a chemical absorbed into
the body from all pathways of exposure (for example, ingestion of drinking water, inhalation of
air), and thus give a cumulative estimate of the chemical burden that a person carries in their
body, sometimes referred to as a body burden. Biomonitoring can characterize differences in
exposure among groups within a population, and can characterize changes in population
exposure over time. Biomonitoring is an increasingly important element of epidemiological
research when evaluating whether chemical exposures are associated with adverse health
effects in humans.
What environmental chemicals are included in the Biomonitoring indicators
for America's Children and the Environment, Third Edition (ACE3)1
Biomonitoring topics were selected for ACES based on: (1) research that indicates an
association between exposure and children's health or suggests a potential association
between exposure and children's health; (2) significant public interest; and (3) the nature of the
biomonitoring data available (for example, range of ages for which data are available and
frequency of detection). EPA obtained input from its Children's Health Protection Advisory
Committee to assist in selecting topics from among the many chemicals with biomonitoring
data available. The ACES Biomonitoring indicators address the following topics:
• Lead
• Mercury
• Cotinine (a marker for environmental tobacco smoke exposure)
• Perfluorochemicals (PFCs)
• Polychlorinated biphenyls (PCBs)
• Polybrominated diphenyl ethers (PBDEs)
• Phthalates
• Bisphenol A(BPA)
• Perchlorate
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Introduction | Biomonitoring
For many of the chemicals addressed in this section, scientific findings have reported
associations between children's health and the mother's exposure during pregnancy. For this
reason, indicators for several of these topics present data for women of child-bearing age-
defined here as ages 16 to 49 years.
What data sources were used to develop the Biomonitoring indicators?
Biomonitoring data are generated by collecting samples of blood, urine or other biological
specimens from a group of individuals, then measuring the concentrations of selected
chemicals in those specimens. There are many scientific research efforts that collect
biomonitoring data in the United States, but only the National Health and Nutrition
Examination Survey (NHANES) conducted by the National Center for Health Statistics (NCHS)
measures chemicals in the blood and urine1 of a nationally representative sample of the U.S.
population. NHANES was therefore identified as the most suitable data source for all
Biomonitoring indicators presented in ACES. Summary statistics for more than 200 chemicals
measured in NHANES are reported in the Fourth National Report on Human Exposure to
Environmental Chemicals,1 and data files containing individual measurements for each chemical
are available from the NHANES website.2
Because NHANES is an ongoing, continuous survey that provides data over a number of years
using a consistent sample design and consistent methods of measurement, the biomonitoring
levels can be compared over time and across demographic groups. However, because of the
highly clustered sample design of the survey, multiple NHANES cycles should be combined to
yield sample sizes necessary for certain types of statistical analysis. NHANES is not designed to
provide detailed estimates for populations that are highly exposed to particular environmental
chemicals. In addition, military personnel and people who reside in institutions are excluded
from NHANES.
For most of the environmental chemicals currently measured in NHANES, data are available
starting in 1999 or more recently; measurement of lead and cotinine began earlier. Availability
of NHANES biomonitoring data for children varies by chemical and type of sample, and, in
general, biomonitoring data for young children are quite limited. For environmental chemicals
measured in urine, NHANES collects data from survey participants ages 6 years and older. For
most environmental chemicals measured in blood, NHANES collects data from survey
participants ages 12 years and older. Exceptions apply to three chemicals presented in this
section: measurements of lead and mercury in blood are conducted for all survey participants
ages 1 year and older, and measurements of cotinine in blood are conducted for all participants
ages 3 years and older. NHANES does not measure chemicals in breast milk, an important route
of exposure for infants, or in target organs where chemicals affect the body.
What can we learn from biomonitoring indicators?
Biomonitoring indicators in ACES provide summaries of biomonitoring measurements in blood
or urine specimens obtained from a nationally representative target population—either
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Biomonitoring | Introduction
children within a specified age range, or women of child-bearing age. For chemicals that are
persistent in the human body, biomonitoring measurements may be reflective of exposures
that have occurred over several months or years. For chemicals that are cleared from the body
more rapidly, a biomonitoring measurement may typically reflect exposures that have occurred
within the previous few days.
The Biomonitoring indicators prepared for ACES focus primarily on presenting biomonitoring
data collected over multiple years to evaluate whether there are any changes over time. The
biomonitoring indicator values are also compared across various race/ethnicity, income, or
age groups.
When health benchmarks are available, biomonitoring data may provide insights about the
percentage of a population at risk for adverse health effects; however, in most cases information
on health risks associated with levels of chemicals in blood or urine typical for the general
population is limited. For some chemicals, such as lead and cotinine, there is an extensive body of
literature demonstrating that adverse effects can occur in children with levels of exposure
commonly experienced in the general population. However, biomonitoring by itself does not
reveal whether any adverse effects have occurred in an individual or in the population.
Biomonitoring indicators present data for one chemical at a time, but biomonitoring studies
have found that individuals have multiple chemicals in their bodies.3"5 While the evidence is still
developing for the links between exposures to environmental chemicals and disease, a wide
variety of chemicals may act together to produce common adverse outcomes.6 Thus, even small
biological alterations caused by exposure to a single chemical in isolation may have important
effects when combined with exposure to other chemicals. The ACES Biomonitoring indicators
do not reflect this context of simultaneous or sequential exposure to multiple chemicals.
An important limitation of biomonitoring is that, by itself, it provides few clues as to the
source(s) of exposure. Data on environmental sources of the chemical are necessary to
separate contributions from air, water, food, and/or contaminated soil or dust.
What information is provided for each Biomonitoring topic?
For each topic, an introduction section explains the potential relevance of the chemical to
children's health, including a discussion of typical exposure pathways and scientific findings
concerning possible adverse health effects.
The introduction section is followed by a description of the indicators, including a summary of
the data available from NHANES for the specific chemical or chemical group and information on
how each indicator was calculated. One or two indicators, each presented as a graphical
representation of the available data, are included for each topic. Where data are available for a
sufficient number of years (at least three NHANES two-year cycles), the indicator presents a
time series. When time series data are not available, the indicator shows a comparison of the
most current biomonitoring data by race/ethnicity and income level.
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Introduction | Biomonitoring
All indicator figures present median (50th percentile) values; some time series figures also
provide 95th percentile values. The median is the value in the middle of the chemical's
distribution: half of the measured population has levels of the chemical in their urine or blood
that are greater than the median, and half has levels below the median. The 95th percentile is a
value representing the upper range of levels: 5% of the specified group has levels of the
chemical in their urine or blood that are greater than the 95th percentile. This value therefore
can be thought of as representing a high level relative to the rest of the population, but not a
maximum level.1
Beneath each figure is a description of the data source and explanatory bullet points
highlighting key findings from the data presented in the figure, along with key data from any
supplemental data tables. References are provided for each topic at the end of the report.
Data tables are provided in Appendix A. The tables include all indicator values depicted in the
indicator figures, along with additional data of interest not shown in the figures. Metadata
describing the data sources are provided in Appendix B. Documents providing details of how
the indicators were calculated are available on the ACE website (www.epa.gov/ace).
Many of the topics presented in the biomonitoring indicators are addressed in Healthy People
2020, which provides science-based, 10-year national objectives for improving the health of all
Americans. Appendix C provides examples of the alignment of the biomonitoring topics
presented in ACES with objectives in Healthy People 2020.
What race/ethnicity groups are used in reporting indicator values?
For each topic in the Biomonitoring section, indicator values are provided for defined
race/ethnicity groups—either in the indicator figures or in the data tables—for the following
races/ethnicities:
• White non-Hispanic
• Black non-Hispanic
• Mexican-American
• All Other Races/Ethnicities
1 Frequently, a small portion of the population may appear to have much higher levels of an environmental
chemical compared with everyone else. In these cases, percentiles in the lower portion of the distribution (below
the median) are generally less variable than those well above the median. In NHANES, estimates above the 95th
percentile are generally very uncertain due to the sample size, the survey design, and (for many measurements)
the substantially skewed distributions.
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Biomonitoring | Introduction
Values are provided for "Mexican-American" ethnicity rather than "Hispanic" ethnicity because
in all years up to 2006, NHANES was designed to provide statistically reliable estimates for
Mexican-Americans rather than all Hispanics."
The "All Other Races/Ethnicities" category includes all other races and ethnicities not specified,
together with those individuals who report more than one race. The limits of the sample design
and sample size often preclude statistically reliable estimates for smaller race/ethnicity
groups.1"
What income groups are used in reporting indicator values?
The ACES Biomonitoring indicators present values for income groups defined on the basis of
the federal poverty level. Poverty level is defined by the federal government, and is based on
income thresholds that vary by year, family size and composition. In 2010, for example, the
poverty threshold was $22,113 for a household with two adults and two related children.7 The
Biomonitoring indicators (in figures and/or data tables) provide data separately for individuals
in families with incomes below poverty level, and those in families with incomes at or above
poverty level.
How were the indicators calculated and presented?
Data files: All indicators were calculated from publicly available data files obtained from the
NHANES website. Files include values for the biomonitoring measurement, and information on
the sampled individual's age, sex, race/ethnicity, and income level (that is, the family income
divided by the poverty level). Each individual observation also has a sample weight that is used
in calculating population statistics; the weight equals the number of people in the U.S.
population represented by the particular observation.
Population age groups: Indicators of biomonitoring data in children used all data available for
children ages 17 years and younger, except for lead where the indicator focuses on children
ages 5 years and younger. Indicators of biomonitoring data in women of child-bearing age used
all available data for women ages 16 to 49 years. As noted above, indicators for women of
child-bearing age are included in ACES when there are concerns for children's health associated
with the mother's exposure during pregnancy. Adjustments were applied in calculating the
population distribution of women ages 16 to 49 years to incorporate birth rates specific to age
and race/ethnicity.8 These adjustments give greater weight to women of ages more likely to
give birth, and reduce the contribution to the calculated indicator values of women of ages less
likely to give birth (e.g., those ages 40 to 49 years). Without the birth rate adjustment, the
" NHANES now oversamples Hispanics instead of Mexican-Americans, beginning with NHANES 2007-2008.
Please see http://www.cdc.gov/nchs/nhanes/nhanes2007-2008/sampling_0708.htm/.
111 Separate estimates for Asians may be feasible for some biomonitoring measures in the future, as NHANES started
oversampling Asians in the 2011-2012 cycle.
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Introduction | Biomonitoring
indicator values would be calculated as if all women ages 16 to 49 years are equally likely to
give birth.IV
Calculation of 50th and 95th percentiles over specified time periods: For all ACES Biomonitoring
indicators, the 50th and 95th percentile values were selected as the indicator statistics to
represent the central tendency and upper end of the exposure distribution. Where data are
available for at least three 2-year NHANES survey periods, the indicator presentation focuses on
how the measured values have changed over time. If data are available for only one or two
NHANES survey periods, the indicator presentation focuses on demographic comparisons.
The 50th and 95th percentiles were also calculated for different population groups (defined by
race/ethnicity or income) for all chemicals considered in the indicators. A single two-year
NHANES cycle frequently will not include enough sampled individuals to provide statistically
reliable estimates for all population groups of interest. Four-year data sets were used to ensure
that there were a sufficient number of observations for each population group, using the two
most current two-year NHANES cycles reported for each chemical. All calculations incorporated
the NHANES sample weights.
Statistical considerations in presenting and characterizing the indicators: Statistical analysis has
been applied to the ACES Biomonitoring indicators to evaluate trends over time in indicator
values (for example, median concentration of lead in blood), or differences in indicator values
between demographic groups/These analyses use a 5% significance level, meaning that a
conclusion of statistical significance is made only when there is no more than a 5% probability
that the observed trend or difference occurred by chance (p < 0.05).
The statistical analysis of trends over time for an ACES Biomonitoring indicator is dependent on
how the indicator values vary overtime, the number of NHANES survey cycles with data
included in the analysis, the number and variability of measurements in each survey cycle, and
various aspects of the survey design. The evaluation of trends over time incorporates data from
each survey cycle within the time period reported (for example, 2001-2002, 2003-2004, 2005-
lvThe adjustment involves calculating age- and race/ethnicity-specific birth rates. Birth rates (i.e., average number
of births per woman annually) are derived for each single year of age (age 16, age 17, etc.) separately for each
race/ethnicity group (White non-Hispanic, Black non-Hispanic, Mexican-American, and "All Other
Races/Ethnicities"). The standard NHANES sample weight for each observation is then multiplied by the calculated
birth rate corresponding to the age and race/ethnicity of the sampled woman. This produces a birth rate-adjusted
weight that is applied in the same manner as standard NHANES sample weights. There may be multiple ways to
implement an adjustment to the data that accounts for birth rates by age. The National Center for Health Statistics
has not fully evaluated the method used in ACE, or any other method intended to accomplish the same purpose,
and has not used any such method in its publications. NCHS and EPA are working together to further evaluate the
birth rate adjustment method used in ACE and alternative methods.
v The approach used in ACES focuses on identifying statistical trends and differences in the 50th and 95th percentiles of
the NHANES biomonitoring data. Other approaches to analyzing trends in the NHANES biomonitoring data may focus
on different summary statistics, such as the geometric mean or the percentage of the population exceeding some
designated level. Assessment of trends in other summary statistics (such as the geometric mean) will not necessarily
lead to the same conclusions as assessments of trends in the 50th and 95th percentiles.
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Biomonitoring | Introduction
2006, 2007-2008, and 2009-2010). A finding of statistical significance for differences in
indicator values between demographic groups depends on the magnitude of the difference, the
number and variability of measurements in each group, and various aspects of the survey
design. For example, if two groups from the U.S. population have different median levels of a
chemical in blood or urine, the statistical test is more likely to detect a difference when samples
have been obtained from a larger number of people in those groups. Similarly, if there is low
variability in measured levels of the chemical within each group, then a difference between
groups is more likely to be detected. It should be noted that when statistical testing is
conducted for differences among multiple demographic groups (for example, considering both
race/ethnicity and income level), or for multiple chemicals, the large number of comparisons
involved increases the probability that some differences identified as statistically significant
may actually have occurred by chance.
A finding of statistical significance is useful for determining that an observed trend or difference
was unlikely to have occurred by chance. However, a determination of statistical significance by
itself does not convey information about the magnitude of the difference in chemical
concentrations or the potential difference in the risk of associated health outcomes.
Furthermore, a lack of statistical significance means only that occurrence by chance cannot be
ruled out. Thus, a conclusion about statistical significance is only part of the information that
should be considered when determining the public health implications of trends or differences
in indicator values.
In some cases, calculated indicator values have substantial uncertainty. Uncertainty in these
estimates is assessed by looking at the relative standard error (RSE), a measure of how large
the variability of the estimate is in relation to the estimate (RSE = standard error divided by
the estimate)/1 The estimate should be interpreted with caution if the RSE is at least 30% but
is less than 40%; a notation is provided for such estimates in the indicator figures and tables.
If the RSE is greater than 40%, the estimate is considered to have very large uncertainty and is
not reported/"
Vl Standard errors for all Biomonitoring indicator values are provided in a file available on the ACE website
(www.epa.gov/ace).
v" The RSE itself may also be uncertain for some estimates, particularly for values based on small samples, such as values
stratified by race/ethnicity or income and chemicals measured in a subsample of NHANES participants (rather than all
NHANES participants). Degrees of freedom is a statistical measure that provides an indication of this uncertainty.
Estimates with between 7 and 11 degrees of freedom have a notation stating that they should be interpreted with
caution. Estimates with fewer than 7 degrees of freedom were considered unreliable and are not reported.
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Lead | Biomonitoring
Lead
Lead is a naturally occurring metal used in the production of fuels, paints, ceramic products,
batteries, solder, and a variety of consumer products. The use of leaded gasoline and lead-
based paint was eliminated or restricted in the United States beginning in the 1970s, resulting
in substantial reductions in exposure to lead. However, children continue to be exposed to lead
due to the widespread distribution of lead in the environment. For example, children are
exposed to lead through the presence of lead-based paint in many older homes, the presence
of lead in drinking water distribution systems, and current use of lead in the manufacture of
some products.
In the United States, the major current source of early childhood lead exposure is lead-
contaminated house dust.1'2 Exposure to lead in house dust tends to be highest for young
children, due to their frequent and extensive contact with floors, carpets, window areas, and
other surfaces where dust gathers, as well as their frequent hand-to-mouth activity. A major
contributor to lead in house dust is deteriorated or disrupted lead-based paint.3"5 Housing units
constructed before 1950 are most likely to contain lead-based paint, but any housing unit
constructed before 1978 may also contain lead-based paint.6 As of 2000, approximately 15.5
million housing units in the United States had one or more lead dust hazards on either floors or
windowsills.7 New lead dust hazards occur when lead in house paint is released during home
renovation and remodeling activities.8'9
Two other contributors to lead in house dust are lead-contaminated soil and airborne lead.10"13
Known sources of lead in soil include historical airborne emissions of leaded gasoline, emissions
from industrial sources such as smelters, and lead-based paint.14'15 Current sources of lead in
ambient air in the United States include smelters, ore mining and processing, lead acid battery
manufacturing, and coal combustion activities such as electricity generation.15
Lead-contaminated house dust is not the only source of childhood lead exposure. Direct
contact with lead-contaminated soil,13 ingestion of lead-based paint chips,16 and inhalation of
lead in ambient air also contribute to childhood lead exposure. Drinking water is an additional
known source of lead exposure among children in the United States, particularly from corrosion
of pipes and other elements of the drinking water distribution systems.5'17'18 Exposure to lead
via drinking water may be particularly high among very young children who consume baby
formula prepared with drinking water that is contaminated by leaching lead pipes.17 Although
childhood exposure to lead in the United States typically occurs through contact with
contaminated environmental media; children may also be exposed through lead-contaminated
toys;5'19 jewelry;20 tobacco smoke;21 imported candies, spices, and condiments;5'22 and
imported folk remedies.23'24
Compared with adults, children's bodies typically absorb a much greater fraction of a given
amount of ingested lead. Once absorbed, most of the lead is stored in bones, where it can stay
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Biomonitoring | Lead
many years, while other lead goes into the blood and can be eliminated more quickly.
Elimination of lead from the body usually occurs through urine or feces.25
Childhood blood lead levels in the United States differ across groups in the population, such as
those defined by socioeconomic status and race/ethnicity.26 Children living in poverty and Black
non-Hispanic children tend to have higher blood lead levels27 and higher levels of lead-
contaminated dust in the home6 than do other children. Blood lead levels tend to be higher for
children living in older housing, most likely because older housing units are more likely to
contain lead-based paint.6'28 Blood lead levels may vary by nutritional status: conditions such as
iron deficiency have been associated with higher blood lead levels in children.15 In addition,
some children who have immigrated to the United States may have been exposed to lead in
their previous countries of residence. Foreign birth place and recent foreign residence have
both been positively associated with the risk of elevated blood lead levels among immigrant
children in the United States.27'29
Childhood blood lead levels in the United States have declined substantially since the 1970s.
The decline in blood lead levels is due largely to the phasing out of lead in gasoline between
1973 and 1995,30 and to the reduction in the number of homes with lead-based paint hazards.7
Some decline was also a result of regulations reducing lead levels in drinking water, as well as
legislation limiting the amount of lead in paint and restricting the content of lead in solder,
faucets, pipes, and plumbing, and the elimination of lead-soldered cans for food use.5 In the
United States, lead content is banned or limited in many products, including food and beverage
containers, ceramic ware, toys, Christmas trees, polyvinyl chloride pipes, vinyl mini-blinds, and
playground equipment.5 However, because trace levels of lead may be present in these
products, normal use may still result in lead exposure.5
The National Toxicology Program (NTP) has concluded that childhood lead exposure is
associated with reduced cognitive function.31 Children with higher blood lead levels generally
have lower scores on IQ tests32"38 and reduced academic achievement.31 In addition to the
effects on IQ and school performance, research on the effects of lead has increasingly been
addressing the effects of lead on behavior. The NTP has concluded that childhood lead
exposure is associated with attention-related behavioral problems (including inattention,
hyperactivity, and diagnosed attention-deficit/hyperactivity disorder) and increased incidence
of problem behaviors (including delinquent, criminal, or antisocial behavior).31 Studies have
reported that lead exposure in children may contribute to decreased attention,38"43
hyperactivity-impulsivity,44 and increased likelihood of attention-deficit/hyperactivity
disorder.44"52 Other adverse behavioral outcomes that have been associated with childhood
lead exposure in some studies include conduct disorders,53'54 increased risks of juvenile
delinquency and antisocial behaviors,55"57 higher total arrest rates, and arrest rates for violent
crimes in early adulthood.58'59 Socioeconomic status may also modify the effect of lead on these
cognitive and behavioral changes, resulting in stronger effects in children with lower
socioeconomic status.60'61
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Lead | Biomonitoring
Mothers who are exposed to lead can transfer lead to the fetus during pregnancy and to the child
while breast feeding.62'63 The NTP has concluded that there is "limited evidence" that prenatal
lead exposure is associated with cognitive and behavioral effects in children.31 The Centers for
Disease Control and Prevention (CDC) has recently published guidelines for screening pregnant
and lactating mothers for possible lead exposure to better protect the fetus.64
Many studies of the effects of lead focus on outcomes in children ages 5 years and younger.
This focus reflects scientific thinking that early childhood is when children tend to experience
peak exposures to lead, and also when they are most biologically susceptible to the effects of
lead. Increased susceptibility to the neurodevelopmental effects of lead in the first three years
of life is expected because this period is characterized by major growth and developmental
events in the nervous system.15 However, lead is toxic to individuals of all ages, and children
older than 5 years may also be susceptible to the neurodevelopmental effects of lead. Blood
lead measurements at various ages in early childhood have been found to be strongly
correlated with cognitive deficits,36 and some analyses have found that effects are more
strongly associated with blood lead levels at school age (i.e., 5- to 6-year-old children)
compared with levels measured earlier in life.65'66
Childhood lead exposures may also have lifelong effects. For instance, high childhood blood
lead concentrations are associated with significant region-specific brain volume loss in adults,
with greater effects seen in males.67'68 Childhood blood lead concentrations are also inversely
associated with intellectual functioning in young adulthood.69 In addition, lead stored in bones
has the potential to be released into the bloodstream later in life. Such is the case with
pregnant women, breastfeeding women, and elderly persons, as blood lead levels are
comparatively elevated in these populations.25'70'71 Finally, childhood exposures to lead may
contribute to a variety of neurological disorders and neurobehavioral effects in later life. 25'71~73
Until recently, CDC defined a blood lead level of 10 micrograms per deciliter (u.g/dL) as
"elevated"; this definition was used to identify children for blood lead case management.72'74
However, no level of lead exposure has been identified that is without risk of deleterious health
effects.15 CDC's Advisory Committee on Childhood Lead Poisoning Prevention (ACCLPP)
recommended in January 2012 that the 97.5th percentile of children's blood lead distribution
(currently 5 u.g/dL) be defined as "elevated" for purposes of identifying children for follow-up
activities such as environmental investigations and ongoing monitoring.75 CDC has adopted the
ACCLPP recommendation.76 CDC specifically notes that "no level of lead in a child's blood can
be specified as safe,"1 and the NTP has concluded that there is sufficient evidence for adverse
health effects in children at blood lead levels less than 5 u.g/dL.31
The following two indicators use the best nationally representative data available on blood lead
levels over time in children. Indicators Bl and B2 present blood lead concentrations for children
ages 1 to 5 years.
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Biomonitoring | Lead
Indicator Bl: Lead in children ages 1 to 5 years: Median and 95th percentile
concentrations in blood, 1976-2010
Indicator B2: Lead in children ages 1 to 5 years: Median concentrations in blood, by
race/ethnicity and family income, 2007-2010
About the Indicators: Indicators Bl and B2 present concentrations of lead in blood of U.S. children
ages 1 to 5 years. The data are from a national survey that collects blood specimens from a
representative sample of the population every two years, and then measures the concentration of
lead in the blood. Indicator Bl presents concentrations of lead in blood over time. Indicator B2 shows
how blood lead levels differ by race/ethnicity and family income.
NHANES
The National Health and Nutrition Examination Survey (NHANES) provides nationally
representative biomonitoring data for lead. NHANES is designed to assess the health and
nutritional status of the civilian noninstitutionalized U.S. population and is conducted by the
National Center for Health Statistics, part of the Centers for Disease Control and Prevention
(CDC). NHANES conducts interviews and physical examinations with approximately 10,000
people in each two-year year survey cycle. CDC's National Center for Environmental Health
measures concentrations of environmental chemicals in blood and urine samples collected
from NHANES participants. Summaries of the measured values for more than 200 chemicals are
provided in the Fourth National Report on Human Exposure to Environmental Chemicals.77
Lead
Indicators Bl and B2 present levels of lead in children's blood. Blood lead levels are reflective of
relatively recent exposure and, to a varying extent across individuals, may also incorporate
contributions of long-term lead exposures.15 All values are reported as micrograms of lead per
deciliter of blood (u.g/dL).
Concentrations of lead in the blood of children have been measured in NHANES beginning with
the 1976-1980 survey cycle (referred to as NHANES II). For 2009-2010, NHANES collected lead
biomonitoring data for 8,793 individuals ages 1 year and older, including 836 children ages 1 to
5. Lead was detected in 100% of all individuals sampled. The median blood lead level among all
NHANES participants in 2009-2010 was 1.1 u.g/dL and the 95th percentile was 3.3 u.g/dL
Data Presented in the Indicators
Indicator Bl presents median and 95th percentile concentrations of lead in blood over time for
children ages 1 to 5 years, using NHANES data from 1976-2010.
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Lead | Biomonitoring
Indicator B2 presents current median concentrations of lead in blood for children ages 1 to 5
years of different races/ethnicities and levels of family income, using NHANES data from 2007-
2008 and 2009-2010.
The data from two NHANES cycles are combined to increase the statistical reliability of the
estimates for each race/ethnicity and income group, and to reduce any possible influence of
geographic variability that may occur in two-year NHANES data. The current 95th percentiles of
blood lead by race/ethnicity and income are presented in the data tables.
Four race/ethnicity groups are presented in Indicator B2: White non-Hispanic, Black non-
Hispanic, Mexican-American, and "All Other Races/Ethnicities." The "All Other
Races/Ethnicities" category includes all other races and ethnicities not specified, together with
those individuals who report more than one race. The limits of the sample design and sample
size often prevent statistically reliable estimates for smaller race/ethnicity groups. The data are
also tabulated across three income categories: all incomes, below the poverty level, and greater
than or equal to the poverty level.
The sensitivity of measurement techniques has improved over the years spanned by Indicator
Bl, allowing increased detection of lower blood lead levels. These improvements do not affect
the comparability of the median or 95th percentiles overtime, since between 92 and 100% of
children have had detectable levels of lead in each NHANES cycle.
Additional information on how median and 95th percentile blood lead levels vary among
different age groups for children ages 1 to 17 years is presented in a supplementary data table.
Another data table provides median blood lead levels for the same race/ethnicity and income
groups in 1991-1994, for comparison with the more current data presented in Indicator B2.
The indicators focus on ages 1 to 5 years because this age range has been the focus for
research, data collection, and intervention due to the elevated exposures that occur during
early childhood and the sensitivity of the developing brain to the effects of lead. Blood lead
data for school-age children, whose neurological development is also affected by lead
exposure, are included in the data tables for this indicator.
Please see the Introduction to the Biomonitoring section for an explanation of the terms
"median" and "9!
these indicators.
"median" and "95th percentile," and information on the statistical significance testing applied to
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Biomonitoring | Lead
Data characterization
Data for this indicator are obtained from an ongoing continuous survey conducted by the National Center
for Health Statistics.
Survey data are representative of the U.S. civilian noninstitutionalized population.
Lead is measured in blood samples obtained from individual survey participants.
The median concentration of lead in the blood of children between the ages of 1 and 5
years dropped from 15 u.g/dL in 1976-1980 to 1.2 u.g/dL in 2009-2010, a decrease of 92%.
The concentration of lead in blood at the 95th percentile in children ages 1 to 5 years
dropped from 29 u.g/dL in 1976-1980 to 3.4 u.g/dL in 2009-2010, a decrease of 88%.
The largest declines in blood lead levels occurred from the 1970s to the 1990s, following the
elimination of lead in gasoline. The data show continuing declines in blood lead levels from
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Lead | Biomonitoring
1999-2000 through 2009-2010, when the primary focus of lead reduction efforts has been
on lead-based paint in homes.
These decreasing trends were all statistically significant, including the trend in both the
median and 95th percentile over the most recent 12 years (from 1999-2000 to 2009-2010).
In 2009-2010, median blood lead levels by age group were: 1.2 u.g/dL for age 1 year and age
2 years; 1.1 u.g/dL for ages 3 to 5 years; 0.8 u.g/dL for ages 6 to 10 years; 0.7 u.g/dL for ages
11 to 15 years; and 0.7 u.g/dL for ages 16 to 17. The 95th percentile blood lead levels were
4.2, 3.5, 2.8, 2.1, 1.7, and 1.4 u.g/dL, respectively, for ages 1, 2, 3 to 5, 6 to 10, 11 to 15, and
16 to 17 years. (See Table Bla.)
• The differences among age groups in median and 95th percentile blood lead levels were
statistically significant.
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Biomonitoring | Lead
Indicator B2
Lead in children ages 1 to 5 years: Median concentrations in blood,
by race/ethnicity and family income, 2007-2010
Incomes
All Races/Ethnicities
White non-Hispanic
ican-American
All Other Races/Ethnicities
All Races/Ethnicities
At or White non-Hispanic
Above
Poverty
Level
All Other Races/Ethnicities
All Races/Ethnicities
Below White non-Hispani
Poverty
Level
All Other Races/Ethnicities
Concentration of lead in blood (ng/dL)
Data: Centers for Disease Control and Prevention, National Center for Health Statistics
and National Center for Environmental Health, National Health and Nutrition Examination Survey
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*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
Data characterization
Data for this indicator are obtained from an ongoing continuous survey conducted by the National Center
for Health Statistics.
Survey data are representative of the U.S. civilian noninstitutionalized population.
Lead is measured in blood samples obtained from individual survey participants.
The median blood lead level in children ages 1 to 5 years in 2007-2010 was 1.3 ng/dL. The
median blood lead level in Black non-Hispanic children ages 1 to 5 years in 2007-2010 was
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Lead | Biomonitoring
1.6 |-ig/dL, higher than the level of 1.2 u.g/dL in White non-Hispanic children, Mexican-
American children, and children of "All Other Races/Ethnicities."
• The median blood lead level in Black non-Hispanic children was statistically significantly
higher than the median level for each of the remaining race/ethnicity groups.
The median blood lead level for children living in families with incomes below the poverty
level was 1.5 u.g/dL, and for children living in families at or above the poverty level it was 1.2
u.g/dL, a difference that was statistically significant.
The 95th percentile blood lead level among all children ages 1 to 5 years was 3.9 u.g/dL The
95th percentile blood lead level in Black non-Hispanic children ages 1 to 5 years in 2007-2010
was 5.8 u.g/dL, compared with 3.5 u.g/dL for White non-Hispanic children and children of "All
Other Races/Ethnicities," and 3.3 u.g/dL for Mexican-American children. (See Table B2a.)
• The 95th percentile blood lead level in Black non-Hispanic children was statistically
significantly higher than the 95th percentile for each of the remaining race/ethnicity
groups.
Among children ages 1 to 5 years in families with incomes below poverty level, the 95th
percentile blood lead was 4.7 u.g/dL, and among those in families at or above the poverty
level, it was 3.3 u.g/dL, a difference that was statistically significant after accounting for
differences by age, sex, and race/ethnicity. (See Table B2a.)
The 95th percentile blood lead levels in children ages 1 to 5 years were higher for those in
families with incomes below the poverty level compared with those at or above the poverty
level within each race/ethnicity group. Black non-Hispanic children in families with incomes
below the poverty level had the highest 95th percentile blood lead level, 6.8 u.g/dL, which
was 60% higher than for Black non-Hispanic children with families at or above the poverty
level. (See Table B2a.)
• The differences in 95th percentile blood lead levels between income groups were
statistically significant for Black non-Hispanic children and children of "All Other
Races/Ethnicities." The difference was also statistically significant for Mexican-American
children after accounting for differences by age and sex.
Between 1991-1994 and 2007-2010, median blood lead levels among Black non-Hispanic
children ages 1 to 5 years declined 63%: from 4.3 u.g/dL to 1.6 u.g/dL Over the same time
period, median blood lead levels among Mexican-American children ages 1 to 5 years
declined 61%: from 3.1 u.g/dL to 1.2 u.g/dL, and median blood lead levels among White non-
Hispanic children ages 1 to 5 years declined 48%: from 2.3 u.g/dL to 1.2 u.g/dL The
differences over time were statistically significant for each race/ethnicity. (See Table B2b.)
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Biomonitoring | Mercury
Mercury
Mercury is a metal that is liquid at room temperature. There are three major forms of mercury:
1) organic mercury; 2) non-elemental forms of inorganic mercury; and 3) elemental mercury.
Organic mercury, predominantly in the form of methylmercury, is found primarily in fish. Non-
elemental forms of inorganic mercury are found primarily in batteries, some disinfectants, and
some health products and creams. Lastly, elemental mercury is found in thermometers,
fluorescent bulbs, dental amalgam fillings, switches in certain automobiles (used for
convenience lighting in hoods and trunks, mostly in vehicles manufactured prior to 2003), and
other sources.1'2
Mercury is released from its natural form in the earth's crust as a result of both human
activities and natural processes. Coal-burning power plants are the largest source of mercury
emissions in the United States.3 Other sources of mercury emissions include the combustion of
waste and industrial processes that use mercury.3'4 When released into the atmosphere, either
from human activities or from non-human sources, such as volcanoes, mercury can travel long
distances on global air currents and can be deposited on land and water far from its original
source.4'5 In addition to these mercury emissions, there is concern that an increase in ice melts
caused by a warming climate may release some past mercury emissions that have been trapped
in polar ice.6 Moreover, mercury deposited on the surface in the Arctic vaporizes each spring
when the sunlight returns, causing increased concentrations in the atmosphere.7'8
Human exposure to elemental and inorganic mercury can occur at work, from accidental
mercury releases, through the use of products containing mercury, through ritual and folk
medicine uses of mercury, as well as dental restorations with mercury-silver amalgams.4'9'10
Sources of childhood exposure to elemental and inorganic mercury in the home include the
tracking of mercury into the home from the workplace by parents, mercury-containing devices
in the home, and very rarely from intentionally heating mercury in the home for the purpose of
extracting gold.11 In schools, the most common sources of exposure are elemental and
inorganic mercury stored in science laboratories, and mercury from broken instruments such as
thermometers; less common sources are certain mercury-containing gymnasium floors
manufactured between 1960 and 1980 found in some schools.11'12 The adverse health effects of
elemental and inorganic mercury exposure in childhood have not been extensively studied.
However, inhaling high concentrations of elemental mercury vapor can lead to lung problems,
neurobehavioral effects, mood changes, and tremors.9 Although elemental mercury vapor
emissions from dental amalgams are a major source of mercury exposure in the U.S. general
population, two prospective clinical trials in children have found no evidence of adverse effects
on IQ, memory, attention, or other neurological functions.13"15
Thimerosal is an organic mercury-containing preservative that is used in some vaccines to
prevent contamination and growth of harmful bacteria in vaccine vials. The presence of
thimerosal in many vaccines administered to infants led to concerns about possible effects on
children's neurological development, including a hypothesis that mercury in vaccines could be
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Mercury | Biomonitoring
a contributing factor to the incidence of autism. The Institute of Medicine has rejected the
hypothesis of a causal relationship between thimerosal-containing vaccines and autism.16 In
addition, two recent studies have concluded that prenatal and infant exposure to thimerosal-
containing vaccines is not related to increased risk of autism.17'18 Since 2001, thimerosal has
not been used in routinely administered childhood vaccines, with the exception of some
influenza vaccines.19
Methylmercury is another form of organic mercury, which may form when mercury is
deposited into water systems such as oceans, rivers, lakes, and wetlands; the mercury is
converted by bacteria and other microorganisms into methylmercury. Methylmercury then
bioaccumulates up the aquatic food web; fish that live long and feed on other fish (i.e.,
predatory fish) can accumulate high levels of methylmercury. The concentration of
methylmercury in the larger fish at the top of the food chain can reach levels a million times
higher than in the water.20 Consuming fish is the main way that people are exposed to
methylmercury. This includes fish commercially distributed in stores and restaurants as well as
those that people catch for consumption by their families and communities. Each person's
exposure depends on the amount of methylmercury in the fish that they eat and how often
they eat fish. These exposure levels are of particular importance for women of child-bearing
age because of the potential for prenatal exposure: methylmercury easily crosses the placenta
and blood-brain barrier.15 As such, the prenatal period is considered the most sensitive period
of exposure.15
EPA has determined that methylmercury is known to have neurotoxic and developmental
effects in humans.4 This determination was based on effects in people prenatally exposed to
extremely high levels of methylmercury during accidental mercury poisoning events in Japan
and Iraq. Severe adverse health effects observed in the prenatally exposed population included
cerebral palsy, intellectual disability (mental retardation), deafness, and blindness.15'21'22
Prospective cohort studies have been conducted in island populations where frequent fish
consumption leads to methylmercury exposure in pregnant women at levels much lower than
in the poisoning incidents but much greater than those typically observed in the United States.
These studies are designed to investigate possible associations of prenatal methylmercury
exposure with more subtle adverse neurodevelopmental effects than those observed in the
poisoning incidents. However, the expected beneficial impacts of prenatal fish consumption on
neurodevelopment can make it more difficult to detect such outcomes. Prenatal exposure to
mercury in these studies is represented by measurement of total mercury in blood or hair
samples obtained from a woman during pregnancy or at delivery. Results from such studies in
New Zealand and the Faroe Islands15'23"28 suggested that increased prenatal mercury exposure
due to maternal fish consumption was associated with decrements in attention, language,
memory, motor speed, and visual-spatial function (like drawing) during childhood. These
associations were not seen in initial results reported from a study in the Seychelles Islands.29
Further analyses of the Seychelles study population did find associations between prenatal
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Biomonitoring | Mercury
mercury exposure and some neurodevelopmental deficits, after researchers had accounted for
the developmental benefits offish consumption.30"32
More recent studies have been conducted in Massachusetts and New York City, with maternal
blood mercury levels within the range of typical levels in the U.S. general population.33"35 In
Massachusetts, total mercury in blood samples collected during the second trimester of
pregnancy was associated with reduced cognitive development in testing conducted at age 3
years, after adjusting for the positive effects offish/seafood consumption during pregnancy.34
In the New York study, total cord blood mercury was associated with decreased IQ scores in
testing conducted at age 4 years, after adjusting for the positive effects of fish/seafood
consumption during pregnancy.33
Findings of neurodevelopmental effects from early childhood methylmercury exposure are
more limited than for prenatal exposure, with several studies reporting mixed findings.25'36"39
Animal and epidemiological studies suggest that early life exposure to methylmercury
(including prenatal exposures) may also affect cardiovascular,40'41 immune,15'42'43 and
reproductive health.15
Although ingestion of methylmercury in fish may be harmful, other compounds naturally
present in many fish (such as high quality protein and other essential nutrients) are beneficial.
In particular, fish are an excellent source of omega-3 fatty acids, which are nutrients that
contribute to the healthy development of infants and children.44 Pregnant women are advised
to seek dietary sources of these fatty acids, including many species of fish. However, the levels
of both methylmercury and omega-3 fatty acids can vary considerably by fish species. Thus, the
type of fish, as well as portion sizes and frequency of consumption, are all important
considerations for health benefits offish and the extent of methylmercury exposure.
For these reasons, EPA and the U.S. Food and Drug Administration (FDA) issued a fish
consumption advisory in 2004 that advises young children and pregnant females to consume up
to 12 ounces a week of lower-mercury fish and shellfish, such as shrimp, canned light tuna,
salmon, pollock, and catfish, but to avoid any consumption of high-mercury-containing fish, such
as shark, swordfish, tile fish, or king mackerel.45 EPA and FDA are currently working to update the
fish consumption advisory to incorporate the most current science regarding the health benefits
offish consumption and the risks from methylmercury in fish. In 2011, the Departments of
Agriculture and Health and Human Services jointly released the 2010 Dietary Guidelines for
Americans, which recommended that pregnant or breastfeeding women should consume 8-12
ounces of seafood per week, but avoid consumption of the same high-mercury-containing fish
identified in the EPA-FDA advisory.46 In addition, many state health departments provide advice
regarding healthy sources of fish that are lower in mercury. Web links to state advice regarding
fish consumption can be found at http://www.epa.gov/waterscience/fish/states.htm (for an
example, see Washington state's "Eat Fish, Choose Wisely" available at
http://www.doh.wa.gov/ehp/oehas/fish/fishchart.htm). State advisories may address both store-
bought fish and fish caught by individuals in local lakes, rivers, and coastal waters.
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Because methylmercury exposure in pregnant women is a concern for children health, studies
have measured the level of mercury in women's bodies. Mercury can be measured in blood and
is often called "blood mercury." In most cases, total blood mercury is reported, and the
measurements do not distinguish methylmercury in blood from the other forms of mercury. In
the United States, and in populations where most mercury exposure comes from fish
consumption, the majority of total blood mercury is from methylmercury. Among women 16 to
49 years of age in the United States, levels of mercury in blood tend to be highest for Native
American, Pacific Islander, Asian American, and multi-racial women.47"49 A survey of adults in
New York City found that blood mercury levels were three times higher than the national levels.
Asian Americans in this study had higher blood mercury levels than other race/ethnicity
groups.50 Among women ages 16 to 49 years in the United States, blood mercury levels are
higher for those who eat fish more often or in higher quantities.51'47 Asian American
populations have been identified as high consumers of seafood compared with White non-
Hispanics or Black non-Hispanics.50
For women of all races, blood mercury levels tend to be higher in those women with higher
family incomes.48'50'52 Fish consumption rates are highest among women with relatively high
family incomes, and this higher rate offish consumption leads to increased blood mercury
levels.48'52 Concentrations of total mercury in blood among women also seem to vary with
geographic region, and potentially by coastal region. Based on data from 1999-2004, blood
mercury levels for women ages 16 to 49 years were higher in the Northeastern region of the
United States compared with other regions.48 Estimated mercury intake from fish consumption
also follows this observed pattern. Women living in coastal regions had blood mercury levels
higher than those living in noncoastal regions, and among coastal populations, the highest
blood mercury levels were reported for the Atlantic and Pacific coastal regions, followed by the
Gulf Coast and Great Lakes regions, respectively. Furthermore, subsistence populations
(individuals who sustain a portion of their diets by catching and eating fish from local waters),
or those who consume fish as a large portion of their diet because of taste preference or in the
pursuit of health benefits, may have elevated blood mercury levels, depending on the source
and species offish.4
The indicator that follows uses the best nationally representative data currently available on
blood mercury levels over time for women of child-bearing age. Indicator B3 presents median
and 95th percentile blood mercury levels for women ages 16 to 49 years.
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Biomonitoring | Mercury
Indicator B3: Mercury in women ages 16 to 49 years: Median and 95th percentile
concentrations in blood, 1999-2010
About the Indicator: Indicator B3 presents concentrations of mercury in blood of U.S. women ages
16 to 49 years. The data are from a national survey that collects blood specimens from a
representative sample of the population every two years, and then measures the concentration of
mercury in the blood. The indicator presents concentrations of mercury in blood over time. The focus
on women of child-bearing age is based on concern for potential adverse effects in children born to
women who have been exposed to mercury.
NHANES
The National Health and Nutrition Examination Survey (NHANES) provides nationally
representative biomonitoring data for mercury. NHANES is designed to assess the health and
nutritional status of the civilian noninstitutionalized U.S. population and is conducted by the
National Center for Health Statistics, part of the Centers for Disease Control and Prevention
(CDC). Interviews and physical examinations are conducted with approximately 10,000 people
in each two-year survey cycle. CDC's National Center for Environmental Health measures
concentrations of environmental chemicals in blood and urine samples collected from NHANES
participants. Summaries of the measured values for more than 200 chemicals are provided in
the Fourth National Report on Human Exposure to Environmental Chemicals.53
Mercury
Indicator B3 presents levels of mercury in blood of women of child-bearing age. Organic,
inorganic, and total mercury can be measured in blood.1 The concentration of total mercury in
blood is a marker of exposure to methylmercury in populations where fish consumption is the
predominant source of mercury exposure. Previous analysis shows that, in general,
methylmercury accounts for a large percentage of total mercury in blood among women of
child-bearing age in the United States.47 Total blood mercury is generally representative of
methylmercury exposures in the past few months.54'55 All values are reported as micrograms of
mercury per liter of blood (u.g/L).
Concentrations of total blood mercury have been measured in all NHANES participants ages 1
to 5 years and all female participants ages 16 to 49 years beginning with the 1999-2000 survey
cycle. Starting with the 2003-2004 survey cycle, NHANES measured blood mercury in all
participants ages 1 year and older.56 Separate measurements of inorganic blood mercury have
been reported starting with the 2003-2004 NHANES survey cycle.
1 NHANES also measures mercury levels in participant's urine samples, which is considered a more robust
determinant of body burden of mercury from long-term exposure, particularly for inorganic mercury.
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For 2009-2010, NHANES collected mercury biomonitoring data for 8,793 individuals ages 1 year
and older, including 1,871 women ages 16 to 49 years. Mercury was detected in 81% of all
individuals sampled. The frequency of mercury detection was 83% in women ages 16 to 49
years." The median blood mercury level among all NHANES participants in 2009-2010 was 0.8
u.g/L and the 95th percentile was 5.1 u.g/L.
Birth Rate Adjustment
Indicator B3 uses measurements of mercury in blood of women ages 16 to 49 years to
represent the distribution of mercury exposures to women who are pregnant or may become
pregnant. However, blood mercury levels increase with age,56 and women of different ages
have a different likelihood of giving birth. For example, in 2003-2004, women aged 27 years
had a 12% annual probability of giving birth, and women aged 37 years had a 4% annual
probability of giving birth.57 A birth rate-adjusted distribution of women's mercury levels is used
in calculating this indicator,1" meaning that the data are weighted using the age-specific
probability of a woman giving birth.58
Data Presented in the Indicators
Indicator B3 presents median and 95th percentile concentrations of mercury in blood over time
for women ages 16 to 49 years, using NHANES data from 1999-2010.
Additional information showing how median and 95th percentile blood mercury levels vary by
race/ethnicity and family income for women ages 16 to 49 years is presented in supplemental
data tables for these indicators. Data tables also display the median and 95th percentile blood
mercury levels for children ages 1 to 5 years over time and the median and 95th percentile
blood mercury levels for children ages 1 to 17 years for 2007-2010.
Please see the Introduction to the Biomonitoring section for an explanation of the terms
"median" and "95th percentile," a description of the race/ethnicity and income groups used in
the ACES biomonitoring indicators, and information on the statistical significance testing
applied to these indicators.
" The percentage for women ages 16 to 49 years is calculated with the birth rate adjustment described below.
111 There may be multiple ways to implement an adjustment to the data that accounts for birth rates by age. The
National Center for Health Statistics has not fully evaluated the method used in ACE, or any other method
intended to accomplish the same purpose, and has not used any such method in its publications. NCHS and EPA
are working together to further evaluate the birth rate adjustment method used in ACE and alternative methods.
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Biomonitoring | Mercury
Indicator B3
Mercury in women ages 16 to 49 years: Median and 95th percentile
concentrations in blood, 1999-2010
95th percentiie
Median
2003-
2004
Data: Centers for Disease Control and Prevention, National Center for Health Statistics
and National Center for Environmental Health, National Health and Nutrition Examination Survey
Note: To reflect exposures to women who are pregnant or may become pregnant, the estimates
are adjusted for the probability (by age and race/ethnicity) that a woman gives birth,
America's Children and the Environment, Third Edition
Data characterization
Data for this indicator are obtained from an ongoing continuous survey conducted by the National Center
for Health Statistics.
Survey data are representative of the U.S. civilian noninstitutionalized population.
Mercury is measured in blood samples obtained from individual survey participants.
The median concentration of total mercury in the blood of women ages 16 to 49 years has
shown little change between 1999-2000 and 2009-2010, and was 0.8 u.g/L in 2009-2010.
Among women in the 95th percentile of exposure, the concentration of total mercury in
blood decreased from 7.4 u.g/L in 1999-2000 to 3.7 u.g/L in 2001-2002. From 2001-2002 to
-th
2009-2010, the 95 percentile of total blood mercury remained between 3.7 and 4.5 u.g/L.
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Mercury | Biomonitoring
• The decrease in the 95th percentile levels of blood mercury between 1999-2000 and
2001-2002 was statistically significant. From 2001-2002 to 2009-2010 there was no
statistically significant change.
In 1999-2000, the 95th percentile total mercury level was 8 times the median level. For the
remaining years, the 95th percentile total mercury levels were about 5 times the median
levels.
For the years 2007-2010, women of "All Other Races/Ethnicities" had median blood
mercury levels of 1.3 u.g/L, compared with median mercury levels for the remaining
race/ethnicity groups of 0.6-0.8 u.g/L. (See Table B3a.)
• The median blood mercury level in women of "All Other Races/Ethnicities" was
statistically significantly higher than the median level for each of the remaining
race/ethnicity groups.
Among women in the 95th percentile of exposure, differences in total mercury in blood
were observed across race/ethnicity groups. For the years 2007-2010, White non-Hispanic
women had a blood mercury level of 3.7 u.g/L, Black non-Hispanics had 2.9 u.g/L, Mexican-
American women had 2.3 u.g/L, and women in the "All Other Races/Ethnicities" group had
6.7 ug/L (See Table B3b.)
• The differences between race/ethnicity groups were statistically significant after
accounting for differences by income level and age.
Among women in the 95th percentile of exposure, women living at or above the poverty
level had higher blood levels of total mercury (4.0 u.g/L) compared with women living below
poverty level (2.9 u.g/L), a difference that was statistically significant. (See Table B3b.)
The median and 95th percentile values for women of child-bearing age were about 2 to 4
times those of children ages 1 to 5 years. (See Table B3 and Table B3c.)
Among children ages 1 to 5 years in the 95th percentile of exposure, the concentration of
total mercury in blood showed a decreasing trend from 2.3 u.g/L in 1999-2000 to 1.3 u.g/L in
2009-2010. The median blood mercury level for children ages 1 to 5 years stayed relatively
constant for the same time period. (See Table B3c.)
• The decreasing trend in 95th percentile blood mercury levels in children was statistically
significant. There was no statistically significant change in median blood mercury levels
in children.
Among children ages 1 to 17 years, median and 95th percentile blood mercury levels
generally increased with age in 2007-2010, with higher blood mercury levels among
children ages 6 years and older. Children ages 16 to 17 years had a median level of mercury
in blood of 0.5 u.g/L and a 95th percentile of 2.8 u.g/L (See Table B3d.)
• The differences by age group were statistically significant at both the median and the
95th percentile.
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Biomonitoring | Cotinine
Cotinine
Environmental tobacco smoke (ETS), commonly referred to as secondhand smoke, is a complex
mixture of gases and particles and includes smoke from burning cigarettes, cigars, and pipe
tobacco (sidestream smoke), as well as exhaled mainstream smoke.1 There are at least 250
chemicals in ETS that are known to be toxic or carcinogenic, including acrolein, ammonia,
benzene, carbon monoxide, formaldehyde, hydrogen cyanide, nicotine, nitrogen oxides, and
sulfur dioxide.1'2 In 1992, EPA classified ETS as a known human carcinogen.3 Children can be
exposed to ETS in their homes or in places where people are allowed to smoke, such as some
restaurants in some locations throughout the United States.
According to the U.S. Surgeon General, there is no safe level of exposure to ETS, and breathing
even a small amount can be harmful to human health.1 The Surgeon General has concluded
that exposure to ETS causes sudden infant death syndrome (SIDS), acute lower respiratory
infection, ear problems, and more severe asthma in children. Smoking by parents causes
respiratory symptoms and slows lung growth in their children.1 Young children appear to be
more susceptible to the respiratory effects of ETS than are older children.3"5 It is also possible
that early-life exposures to ETS may lead to adverse health effects in adulthood. Exposure to
ETS in childhood has been reported to be associated with early emphysema in adulthood
among nonsmokers.6
The exposure of a pregnant woman to ETS can also be harmful to her developing fetus. The
Surgeon General has determined that exposure of pregnant women to ETS causes a small
reduction in mean birth weight and the evidence is suggestive (but not sufficient to infer
causation) of a relationship between maternal exposure to environmental tobacco smoke
during pregnancy and preterm delivery.1 In addition, the Surgeon General concluded the
evidence is suggestive but not sufficient to infer a causal relationship between prenatal and
postnatal exposure to ETS and childhood cancer.1
Exposure to ETS in the home is influenced by adult behaviors, including the decisions to smoke
at home and to allow visitors to smoke inside the home. Children living in homes with smoking
bans have significantly lower levels of cotinine (a biological marker of exposure to ETS) in urine
than children living in homes without smoking bans.7 Household smoking bans can significantly
decrease children's exposures to ETS, but do not completely eliminate them.8
In recent years there has been a significant decline in children's exposures to ETS.9 This
reduction is in part attributable to a decline in the percentage of adults who smoke. In 2010, an
estimated 19.3% of adults were current smokers, down from 24.7% in 1997.10'n In addition, the
prevalence of smoke-free households increased from 43% of U.S. homes in 1992-1993 to 72%
in 2003.12 However, despite the increasing numbers of adults disallowing smoking in the home,
approximately 34% of children live in a home with at least one smoker as of 2009.13 The
enactment of smoking bans in restaurants, bars, and other public places has led to a decrease
in ETS exposure for both children and adults.14 Recent studies suggest that smoking bans can
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Cotinine | Biomonitoring
reduce the number of asthma-related emergency room visits and hospitalizations and reduce
asthmatic symptoms, including persistent wheeze, wheeze-medication use, and chronic night
cough in children.15"18
Cotinine is considered the best biomarker of exposure to tobacco smoke for both active
smokers and those exposed to ETS.19 The two indicators that follow use the best nationally
representative data currently available on blood cotinine levels over time for women of child-
bearing age and children. Indicator B4 presents median and 95th percentile blood serum levels
of cotinine for children ages 3 to 17 years. Indicator B5 presents median and 95th percentile
blood serum levels of cotinine for women ages 16 to 49 years.
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Biomonitoring | Cotinine
Indicator B4: Cotinine in nonsmoking children ages 3 to 17 years: Median and 95th
percentile concentrations in blood serum, 1988-2010
Indicator B5: Cotinine in nonsmoking women ages 16 to 49 years: Median and 95th
percentile concentrations in blood serum, 1988-2010
About the Indicators: Indicators B4 and B5 present concentrations of cotinine in blood serum of U.S.
children ages 3 to 17 years and women ages 16 to 49 years. Cotinine is a marker of exposure to
environmental tobacco smoke (ETS). The data are from a national survey that collects blood
specimens from a representative sample of the population every two years, and then measures the
concentration of cotinine in the blood serum. Indicator B4 presents concentrations of cotinine in
children's blood serum over time and Indicator B5 presents concentrations of cotinine in women's
blood serum over time. The focus on both children and women of child-bearing age is based on
concern for potential adverse effects in children exposed to ETS and in children born to women who
have been exposed to ETS.
NHANES
The National Health and Nutrition Examination Survey (NHANES) provides nationally
representative biomonitoring data for cotinine. NHANES is designed to assess the health and
nutritional status of the civilian noninstitutionalized U.S. population and is conducted by the
National Center for Health Statistics, part of the Centers for Disease Control and Prevention
(CDC). Interviews and physical examinations are conducted with approximately 10,000 people
in each two-year survey cycle. CDC's National Center for Environmental Health measures
concentrations of environmental chemicals in blood and urine samples collected from NHANES
participants. Summaries of the measured values for more than 200 chemicals are provided in
the Fourth National Report on Human Exposure to Environmental Chemicals.19
Environmental Tobacco Smoke (ETS) and Cotinine
Indicators B4 and B5 present blood serum levels of cotinine as a marker of exposure to ETS.
Nicotine is a distinctive component of tobacco that is found in large amounts in tobacco smoke,
including ETS. Once nicotine enters the body, it is rapidly broken down in a matter of a few
hours into other chemicals. Cotinine is a primary breakdown product of nicotine, and has a
longer half-life. This characteristic makes cotinine a better indicator than nicotine of an
individual's exposure to ETS.20"22
Measurement of cotinine in blood serum is a marker for exposure to ETS in the previous few
days.23 Some studies have shown that, given the same exposure to tobacco smoke, cotinine
levels may differ by race/ethnicity and sex, and there may be genetic differences in the rate at
which cotinine is removed from the body.1'24"28
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Cotinine | Biomonitoring
These indicators present cotinine levels for non-tobacco-users only. Children and women who
were active smokers, as indicated by a relatively high serum cotinine level, were excluded from
these statistics. For these analyses, individuals with a serum cotinine level greater than 10
nanograms of cotinine per milliliter of serum (ng/mL) are considered active smokers, and all
individuals with cotinine levels below 10 ng/mL are considered nonsmokers.19 Active smokers
will almost always have serum cotinine levels above 10 ng/mL, and sometimes those levels will
be higher than 500 ng/mL.19'29 Nonsmokers who are exposed to typical levels of ETS have serum
cotinine levels of less than 1 ng/mL, whereas those nonsmokers with heavy exposure to ETS will
have serum cotinine levels between 1 and 10 ng/mL.19
Concentrations of cotinine in blood serum have been measured in NHANES participants ages 4
years and older for the 1988-1991 and 1991-1994 survey cycles, and then for ages 3 years and
older beginning with the 1999-2000 survey cycle.
For 2009-2010, NHANES collected cotinine biomonitoring data for 6,678 nonsmoking
individuals ages 3 years and older, including 2,191 children ages 3 to 17 years and 1,395 women
ages 16 to 49 years. Cotinine was detected in about 67% of all nonsmoking individuals sampled.
The frequency of cotinine detection was 71% in children ages 3 to 17 years and 66% in women
ages 16 to 49 years.1 The median blood serum cotinine level for all nonsmoking NHANES
participants in 2009-2010 was 0.03 ng/mL and the 95th percentile was 1.3 ng/mL.
Birth Rate Adjustment
Indicator B5 uses measurements of cotinine in blood serum of women ages 16 to 49 years to
represent the distribution of ETS exposures to women who are pregnant or may become
pregnant. For example, in 2003-2004, women aged 27 years had a 12% annual probability of
giving birth, and women aged 37 years had a 4% annual probability of giving birth.30 A birth
rate-adjusted distribution of women's cotinine levels is used in calculating this indicator,"
meaning that the data are weighted using the age-specific probability of a woman giving birth.31
Data Presented in the Indicators
Indicator B4 presents median and 95th percentile concentrations of cotinine in blood serum
over time as a marker of exposure to ETS among non-smoking children ages 3 to 17 years, using
NHANES data from 1988-2010.
Indicator B5 presents median and 95th percentile concentrations of cotinine in blood serum
over time as a marker of exposure to ETS among non-smoking women ages 16 to 49 years,
using NHANES data from 1988-2010.
1 The percentage for women ages 16 to 49 years is calculated with the birth rate adjustment described below.
" There may be multiple ways to implement an adjustment to the data that accounts for birth rates by age. The
National Center for Health Statistics has not fully evaluated the method used in ACE, or any other method
intended to accomplish the same purpose, and has not used any such method in its publications. NCHS and EPA
are working together to further evaluate the birth rate adjustment method used in ACE and alternative methods.
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Biomonitoring | Cotinine
Although the sensitivity of measurement techniques has improved over the years spanned by
Indicators B4 and B5, allowing increased detection of lower serum cotinine levels over time,
these improvements do not affect the comparability of the median or 95th percentiles overtime
since the majority of children and women have had detectable levels of cotinine in each
NHANES cycle.
Additional information showing how median and 95th percentile blood serum levels of cotinine
vary by race/ethnicity, family income, and age for children ages 3 to 17 years is presented in the
supplemental data tables for these indicators. Data tables also show how median and 95th
percentile blood serum levels of cotinine vary by race/ethnicity and family income for women
ages 16 to 49 years.
NHANES does not provide cotinine measurements for children under the age of 3 years (or
under age 4 years prior to 1999), who may be especially sensitive to the effects of ETS exposure.
Please see the Introduction to the Biomonitoring section for an explanation of the terms
"median" and "95th percentile," a description of the race/ethnicity and income groups used in
the ACES biomonitoring indicators, and information on the statistical significance testing
applied to these indicators.
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Cotinine | Biomonitoring
*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
Data characterization
Data for this indicator are obtained from an ongoing continuous survey conducted by the National Center
for Health Statistics.
Survey data are representative of the U.S. civilian noninstitutionalized population.
Cotinine is measured in blood samples obtained from individual survey participants.
The median level of cotinine measured in blood serum of nonsmoking children ages 3 to 17
years dropped from 0.25 ng/mL in 1988-1991 to 0.03 ng/mL in 2009-2010, a decrease of
88%. This decreasing trend was statistically significant.
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Biomonitoring | Cotinine
Cotinine values at the 95th percentile decreased by 34% from 1988-1991 to 2009-2010.
This trend was also statistically significant.
Children at the 95th percentile of cotinine levels had much higher levels than those at the
median. In 1988-1991, the 95th percentile cotinine level (3.2 ng/mL) was 13 times the
median level (0.25 ng/mL); in 2009-2010, the 95th percentile cotinine level (2.1 ng/mL) was
70 times the median level (0.03 ng/mL).
In every time period measured, children at the 95th percentile had higher levels of cotinine
in their blood than women at corresponding levels. (Compare with Indicator B5.)
Eighty-seven percent of nonsmoking children ages 4 to 17 years had detectable levels (at or
above 0.05 ng/mL) of cotinine in 1988-1991. Forty percent of nonsmoking children ages 3
to 17 years had levels at or above 0.05 ng/mL of cotinine in 2009-2010, although
improvements in laboratory methods made it possible to detect cotinine at lower
concentrations starting with the 2001-2002 survey cycle. (Data not shown.)
In 2007-2010, median concentrations of cotinine in blood for nonsmokers were
approximately 0.11 ng/mL for Black non-Hispanic children, 0.04 ng/mL for White non-
Hispanic children, and 0.02 ng/mL for Mexican-American children. The differences between
these race/ethnicity groups were statistically significant. (See Table B4a.)
In 2007-2010, the median concentration of cotinine in blood serum for nonsmoking
children living below the poverty level (0.14 ng/mL) was about 5 times the median for
nonsmoking children living at or above the poverty level (0.03 ng/mL). The differences
between income groups were statistically significant. (See Table B4a.)
In 2007-2010, 95th percentile concentrations of cotinine in blood for nonsmokers were 2.9
ng/mL for White non-Hispanic children and 2.6 ng/mL for Black non-Hispanic children, while
Mexican-American children had levels that were more than 3 times lower (0.8 ng/mL). (See
Table B4b.)
• The differences between levels for Mexican-American children and both White non-
Hispanic and Black non-Hispanic children were statistically significant.
For the years 2007-2010, median levels of cotinine in younger nonsmoking children ages 3
to 5 years and 6 to 10 years were 0.06 and 0.05 ng/mL, respectively, compared with 0.03
and 0.04 ng/mL in older nonsmoking children ages 11 to 15 years and 16 to 17 years,
respectively. (See Table B4c.)
• The differences between the levels for the four age groups were not statistically
significant.
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Cotinine | Biomonitoring
Indicator B5
Cotinine in nonsmoking women ages 16 to 49 years: Median and 95th
percentile concentrations in blood serum, 1988-2010
Median
95th percentile
V' V
4 * ' «. * '
Data: Centers for Disease Control and Prevention, National Center for Health Statistics
and National Center for Environmental Health, National Health and Nutrition Examination Survey
Note: To reflect exposures to women who are pregnant or may become pregnant, the estimates
are adjusted for the probability (by age and race/ethnicity) that a woman gives birth.
America's Children and the Environment, Third Edition
Data characterization
Data for this indicator are obtained from an ongoing continuous survey conducted by the National Center
for Health Statistics.
Survey data are representative of the U.S. civilian noninstitutionalized population.
Cotinine is measured in blood samples obtained from individual survey participants.
The median level of cotinine measured in blood serum of nonsmoking women of child-
bearing age dropped from 3.2 ng/mL in 1988-1991 to 2.1 ng/mL in 2009-2010, a decrease
of 86%. This decreasing trend was statistically significant.
Cotinine values at the 95th percentile decreased by 35% from 1988-1991 to 2009-2010.
This trend was also statistically significant.
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Biomonitoring | Cotinine
Women at the 95th percentile cotinine levels had much higher levels than those at the
median. In 1988-1991, the 95th percentile cotinine level (2.3 ng/mL) was 11 times the
median level (0.21 ng/mL); in 2009-2010, the 95th percentile cotinine level (1.5 ng/mL) was
50 times the median level (0.03 ng/mL).
In 2007-2010, median concentrations of cotinine in blood for nonsmoking women were
approximately 0.1 ng/mL for Black non-Hispanic women and 0.03 ng/mL for White non-
Hispanic women and Mexican-American women. (See Table B5a.)
• The difference between Black non-Hispanic women and Mexican-American women was
statistically significant. The difference between Black non-Hispanic and White non-
Hispanic women was not statistically significant after adjusting for age and income
differences.
Cotinine values at the 95th percentile were more than twice as high for nonsmoking women
living below the poverty level (3.5 ng/mL) as for nonsmoking women living at or above the
poverty level (1.4 ng/mL) in 2007-2010. The differences between income groups were
statistically significant. (See Table B5b.)
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Perfluorochemicals (PFCs) | Biomonitoring
Perfluorochemicals (PFCs)
Perfluorochemicals (PFCs) are a group of synthetic chemicals that have been used in many
consumer products.1 The structure of these chemicals makes them very stable, hydrophobic
(water-repelling), and oleophobic (oil-repelling). These unique properties have led to extensive
use of PFCs in surface coating and protectant formulations for paper and cardboard packaging
products; carpets; leather products; and textiles that repel water, grease, and soil. PFCs have
also been used in fire-fighting foams and in the production of nonstick coatings on cookware
and some waterproof clothes.1 Due in part to their chemical properties, some PFCs can remain
in the environment and bioconcentrate in animals.2"8 Data from human studies suggest that
some PFCs can take years to be cleared from the body.9"13
The PFCs with the highest production volumes in the United States have been perfluorooctane
sulfonic acid (PFOS) and perfluorooctanoic acid (PFOA).1 PFOS and PFOA are also two of the
most frequently detected PFCs in humans.14 Other PFCs include perfluorohexane sulfonic acid
(PFHxS), which is a member of the same chemical category as PFOS; and perfluorononanoic
acid (PFNA), which is a member of the same chemical category as PFOA.15 Chemicals within a
given PFC chemical category share similar chemical structures and uses. Although some studies
have addressed PFHxS and PFNA specifically, the majority of scientific research has focused on
PFOS and PFOA.15
In 2000, one of the principal perfluorochemical manufacturers, 3M, began phasing out the
production of PFOA, PFOS, and PFOS-related compounds. The 3M phaseout of PFOS and PFHxS
was completed in 2002, and its phaseout of PFOA was completed in 2008.16 In 2006, to address
PFOA production by other manufacturers, EPA launched the 2010/15 PFOA Stewardship
Program, with eight companies voluntarily agreeing to reduce emissions and product content of
PFOA, PFNA, and related chemicals by 95% no later than 2010. The industry participants also
committed to work toward eliminating emissions and product content of these chemicals by
2015.17 However, the fact that some of these chemicals may be persistent in the environment
and have a long half-life in humans means that they may continue to persist in the environment
and in people for many years, despite reductions in emissions.2"13 EPA is currently evaluating the
potential need for regulation of PFCs using the authorities of the Toxic Substances Control Act.15
The major sources of human exposure to PFCs are poorly understood, but may include food,
water, indoor and outdoor air, breast milk, and dust.4 Two recent studies pointed to food
consumption as the primary pathway of exposure to PFOS and PFOA for Americans and
Europeans.18'19 PFC-treated food-contact packaging, such as microwave popcorn bags,1 has been a
1 The U.S. Food and Drug Administration recently worked with several manufacturers to remove grease-proofing
agents containing C8 perfluorinated compounds from the marketplace. These manufacturers volunteered to stop
distributing products containing these compounds in interstate commerce for food-contact purposes as of
October 1, 2011. For more information, see
http://www.fda.gov/Food/FoodlngredientsPackaging/FoodContactSubstancesFCS/ucm308462.htm.
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Biomonitoring | Perfluorochemicals (PFCs)
source of RFC exposure.20 Meat and dairy products may also be contaminated with PFCs due to
exposure of source animals to air, water, and feed contaminated with PFCs,21"23 although a recent
study reported that PFCs were undetected in nearly all milk samples tested in the United States.24
In some areas, such as those near industrial facilities that either make or use PFCs, these
contaminants have been found at high levels in drinking water, groundwater, and/or surface
water.25"31 PFCs have been detected in human breast milk.32"36 PFCs have been measured in house
dust as well, with some perfluorochemicals, such as PFOS, PFOA, PFHxS, perfluorobutane sulfonic
acid (PFBuS), and perfluorohexanoic acid (PFHxA), found to be present in the majority of dust
samples examined.37"40 Infants and small children may be more highly exposed to the PFCs
present in house dust than adults are, due to their frequent and extensive contact with floors,
carpets, and other surfaces where dust gathers, as well as their frequent hand-to-mouth
activity.18'19'41'42 Children could have increased exposure to PFCs in carpet and carpet protectants,
due to the amount of time they spend lying, crawling, and playing on carpet.15'41 Limited available
data on levels of PFCs in children's blood suggest that the blood serum levels of most PFCs are
higher in children ages 3 to 11 years compared with other age groups.43'44
Some PFCs have been widely detected in pregnant women and in umbilical cord blood,
suggesting that the developing fetus can be exposed to PFCs while in the womb. However,
findings between studies vary. For example, PFOS and PFOA were detected in 99-100% of
blood samples collected from both pregnant and non-pregnant women in 2003-2004.45
Additionally, PFOS and PFOA were detected in 99% and 100% of umbilical cord blood samples,
respectively, collected from newborns in Baltimore.46 In another study conducted in Japan, the
level of PFOS circulating in a pregnant woman's blood was highly correlated with the level in
cord blood. However, PFOA was detected in maternal samples but was not detected in
umbilical cord samples in the Japanese study.47 Even though studies suggest that the
correlation between maternal and fetal exposure may vary, the ubiquitous presence of PFOS,
PFOA, and other PFCs in blood of women of child-bearing age and in umbilical cord blood may
indicate that fetal exposure to these chemicals is widespread.45'46'48
Some human health studies have found associations between prenatal exposure to PFOS or
PFOA and a range of adverse birth outcomes, such as low birth weight, decreased head
circumference, reduced birth length, and smaller abdominal circumference.49"52 However, there
are inconsistencies in the results of these studies, and two other studies did not find an
association between prenatal PFC exposure and birth weight.53'54 The participants in all of these
studies had PFC blood serum levels comparable to levels in the general population. Animal
studies echo these findings, though typically at levels much higher than what humans are
normally exposed to. Developmental and reproductive effects, including reduced birth weight,
decreased gestational length, structural defects, delays in postnatal growth and development,
increased neonatal mortality, and pregnancy loss have all been associated with prenatal rodent
exposure to PFOS and PFOA.55"65
Findings from a limited number of studies suggest that exposure to PFOS or PFOA may have
negative impacts on human thyroid function. However, there are inconsistencies in the findings
between these studies. Some studies have found that PFC exposures are associated with
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Perfluorochemicals (PFCs) | Biomonitoring
alterations in thyroid hormone levels, as well as an increased risk of thyroid disease in the
general public and in workers with occupational exposures.66"68 However, a recent study of
pregnant women with exposures comparable to those in the general population found that
increasing levels of PFOS, PFOA, and PFHxS were not associated with differences in thyroid
hormone levels.69 The results from animal studies have been more consistent. Multiple animal
studies have found that thyroid hormone levels are altered in animals exposed to
PFOS.57'62'63'65'70"74 One of these studies also found that PFOA-treated rats have altered thyroid
hormone levels.71 The health risks associated with maternal thyroid hormone disruption during
pregnancy may make this a cause for concern. Moderate deficits in maternal thyroid hormone
levels during early pregnancy have been linked to reduced childhood IQ scores and other
neurodevelopmental effects, as well as unsuccessful or complicated pregnancies.75
Both animal and some human studies have found an association between PFCs exposure and
cholesterol and/or triglyceride levels, although physiological differences between humans and
experimental animals may cause lipid levels to vary in opposite directions.76 Structurally, PFCs
resemble fatty acids and can bind to receptors that play key roles in lipid metabolism and fat
production.77 In animal studies involving various species, PFCs are associated with decreased
serum levels of these lipids;64'65'73 in contrast some human studies show an increase in blood
lipid levels with increased presence of PFCs, including PFOS, PFOA, PFHxS, and PFNA, while
other human studies show no change in lipid levels with PFC exposure.77"84 This could be a
potential concern for children, because the mother's body provides a source of cholesterol and
triglycerides to the developing fetus. Cholesterol and fatty acids support cellular growth,
differentiation, and adipose accumulation during fetal development.49'85 Finally, although
human studies have not looked at the associations between PFC exposure and the immune
system, animal studies have found an association between PFOS and PFNA exposure (in utero
and in adulthood) and immune suppression, including alterations in function and production of
immune cells and decreased lymphoid organ weights.86"88
The indicator that follows uses the best nationally representative data currently available on
blood serum levels of perfluorochemicals over time for women of child-bearing age. Indicator
B6 presents median blood serum levels of PFOS, PFOA, PFHxS, and PFNA for women ages 16 to
49 years.
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Biomonitoring | Perfluorochemicals (PFCs)
Indicator B6: Perfluorochemicals in women ages 16 to 49 years: Median
concentrations in blood serum, 1999-2008
About the Indicator: Indicator B6 presents concentrations of perfluorochemicals (PFCs) in blood
serum of U.S. women ages 16 to 49 years. The data are from a national survey that collects blood
specimens from a representative sample of the population every two years, and then measures the
concentration of PFCs in the blood serum. The indicator presents concentrations of PFCs in blood
serum over time. The focus on women of child-bearing age is based on concern for potential adverse
effects in children born to women who have been exposed to PFCs.
NHANES
The National Health and Nutrition Examination Survey (NHANES) provides nationally
representative biomonitoring data for PFCs. NHANES is designed to assess the health and
nutritional status of the civilian noninstitutionalized U.S. population and is conducted by the
National Center for Health Statistics, part of the Centers for Disease Control and Prevention
(CDC). Interviews and physical examinations are conducted with approximately 10,000 people
in each two-year survey cycle. CDC's National Center for Environmental Health measures
concentrations of environmental chemicals in blood and urine samples collected from NHANES
participants. Summaries of the measured values for more than 200 chemicals are provided in
the Fourth National Report on Human Exposure to Environmental Chemicals.2
Perfluorinated Compounds
Indicator B6 presents blood serum levels of four important PFCs: perfluorooctane sulfonic acid
(PFOS), perfluorooctanoic acid (PFOA), perfluorohexane sulfonic acid (PFHxS), and
perfluorononanoic acid (PFNA). These four PFCs were chosen because they are commonly
detected in humans, and the bulk of PFCs health effects research in both humans and
laboratory animals has focused on these contaminants—especially PFOS and PFOA.
PFCs bind to proteins in the serum of blood. Because PFCs remain in the human body for years,
blood serum levels of PFCs are reflective of long-term exposures to these contaminants. Serum
accounts for about half the weight of whole blood, so the blood serum concentration of PFCs is
about twice the concentration of PFCs in whole blood.89 The blood serum PFC levels for this
indicator are given in nanograms of PFC per milliliter of blood serum (ng/mL)."
Concentrations of 12 different PFCs, including PFOS, PFOA, PFHxS, and PFNA, have been
measured in blood serum from a representative subset of NHANES participants ages 12 years
" Most persistent organic pollutants (POPs) are lipophilic, meaning that they accumulate in fatty tissues; however,
this is not the case for PFCs, which are both hydrophobic (water-repelling), and oleophobic (oil-repelling). They
instead bind to proteins in the serum of blood. While blood levels of lipophilic POPs are commonly lipid-adjusted,
the PFC measurements in blood are not.
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Perfluorochemicals (PFCs) | Biomonitoring
and older beginning with the 1999-2000 survey cycle, although PFCs were not measured in the
2001-2002 cycle.
In 2007-2008, NHANES collected PFCs biomonitoring data for 2,100 individuals ages 12 years
and older, including 495 women ages 16 to 49 years. The four selected PFCs were detected in
99% to 100% of the individuals sampled in NHANES 2007-2008. The median and 95th percentile
of blood serum PFC levels for all NHANES participants in 2007-2008 were 14 ng/mL and 41
ng/mL, respectively, for PFOS; 4 ng/mL and 10 ng/mL, respectively, for PFOA; 2 ng/mL and 10
ng/mL, respectively, for PFHxS; 2 ng/mL and 4 ng/mL, respectively, for PFNA.
Birth Rate Adjustment
Indicator B6 uses measurements of PFCs in blood serum of women ages 16 to 49 years to
represent the distribution of PFC exposures to women who are pregnant or may become
pregnant. However, women of different ages have a different likelihood of giving birth. For
example, in 2003-2004, women aged 27 years had a 12% annual probability of giving birth, and
women aged 37 years had a 4% annual probability of giving birth.90 A birth rate-adjusted
distribution of women's PFC levels is used in calculating this indicator,1" meaning that the data
are weighted using the age-specific probability of a woman giving birth.91
Data Presented in the Indicator
Indicator B6 presents median concentrations of PFOS, PFOA, PFHxS, and PFNA in blood serum
over time for women ages 16 to 49 years, using NHANES data from 1999-2008 (excluding the
years 2001-2002).
Additional information on the 95th percentile blood serum levels of PFOS, PFOA, PFHxS, and
PFNA for women ages 16 to 49 years is presented in the supplemental data tables for this
indicator, along with information showing how median and 95th percentile blood serum levels
of PFCs in women of child-bearing age vary by race/ethnicity and family income.
Please see the Introduction to the Biomonitoring section for an explanation of the terms
"median" and "95th percentile," a description of the race/ethnicity and income groups used in
the ACES biomonitoring indicators, and information on the statistical significance testing
applied to these indicators.
111 There may be multiple ways to implement an adjustment to the data that accounts for birth rates by age. The
National Center for Health Statistics has not fully evaluated the method used in ACE, or any other method
intended to accomplish the same purpose, and has not used any such method in its publications. NCHS and EPA
are working together to further evaluate the birth rate adjustment method used in ACE and alternative methods.
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Biomonitoring | Perfluorochemicals (PFCs)
Indicator B6
Perfluorochemicals in women ages 16 to 49 years: Median concentrations
in blood serum, 1999-2008
1999-2000
2003-2004
2005-2006
2007-
PFHxS
Data: Centers for Disease Control and Prevention, National Center for Health Statistics
and National Center for Environmental Health, National Health and Nutrition Examination Survey
Note: To reflect exposures to women who are pregnant or may become pregnant, the estimates
are adjusted for the probability (by age and race/ethnicity) that a woman gives birth.
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Data characterization
Data for this indicator are obtained from an ongoing continuous survey conducted by the National Center
for Health Statistics.
Survey data are representative of the U.S. civilian noninstitutionalized population.
PFCs are measured in blood samples obtained from individual survey participants.
Between 1999-2000 and 2007-2008, median blood serum levels of PFOS in women of
child-bearing age declined from 24 ng/mL in 1999-2000 to 9 ng/mL in 2007-2008. Median
blood serum levels of PFOA in women of child-bearing age declined from 5 ng/mL in 1999-
2000 to 3 ng/mL in 2007-2008. These decreasing trends were statistically significant.
The median blood serum levels of PFHxS and PFNA were lower than those of PFOS and PFOA
in women of child-bearing age. Median levels of PFHxS have remained relatively constant
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Perfluorochemicals (PFCs) | Biomonitoring
over time. Between 1999-2000 and 2007-2008, median blood serum levels of PFNA showed
an increasing trend, from 0.5 ng/mL in 1999-2000 to 1.2 ng/mL in 2007-2008.
• The increasing trend in median PFNA levels was statistically significant.
The concentration of PFOS in blood serum at the 95th percentile in women of child-bearing
age showed a decreasing trend from 50 ng/mL in 1999-2000 to 23 ng/mL in 2007-2008.
The concentration of PFOA in blood serum at the 95th percentile in women of child-bearing
age remained relatively constant between 1999-2000 and 2007-2008. (See Table B6a.)
• The decreasing trend in 95th percentile PFOS levels was statistically significant.
For the years 2005-2008, women of child-bearing age living at or above poverty level had
higher median and 95th percentile concentrations of PFOS and PFOA in their blood serum
compared with women living below poverty level. (See Tables B6b and B6c.)
• The differences between income groups were statistically significant after adjustment
for differences in race/ethnicity and age.
For the years 2005-2008, median concentrations of PFOA were higher in White non-
Hispanic women of child-bearing age (3.5 ng/mL) compared with Black non-Hispanic women
(2.7 ng/mL), Mexican-American women (2.3 ng/mL), and women of "All Other
Races/Ethnicities" (2.4 ng/mL). (See Table B6b.)
• These differences in median PFOA concentrations by race/ethnicity were statistically
significant. The difference in median concentrations between White non-Hispanic and
Black non-Hispanic women was no longer statistically significant after accounting for
other demographic characteristics (differences in age and income).
In 2005-2008, median and 95th percentile concentrations of PFOS were lower in Mexican-
American women of child-bearing age at 7.4 ng/mL and 17.3 ng/mL, respectively, compared
with White non-Hispanic women at 11.4 ng/mL and 28.4 ng/mL, respectively, Black non-
Hispanic women at 11.2 ng/mL and 25.7 ng/mL, respectively, and women of "All Other
Races/Ethnicities" at 8.3 ng/mL and 24.9 ng/mL, respectively. (See Tables B6b and B6c.)
• These differences were statistically significant both with and without adjustment for
other demographic characteristics, with the following exceptions: the difference
between Mexican-American women and women of "All Other Races/Ethnicities" was
statistically significant at the median only after accounting for differences by age and
income; and was not statistically significant at the 95th percentile.
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Biomonitoring | Polychlorinated Biphenyls (PCBs)
Polychlorinated Biphenyls (PCBs)
Polychlorinated biphenyls (PCBs) are a family of industrial chemicals that were produced in the
United States from 1929 to 1979 and used primarily as insulating fluids in capacitors,
transformers, and other electrical equipment.1 PCBs were also used as plasticizers in many
paints, plastics, and rubber products, and had numerous applications in industry and building
construction.1
Each PCB has a common structure of a biphenyl molecule with 1 to 10 chlorine atoms attached;
each possible variant is called a congener. In theory, there could be as many as 209 PCB
congeners; however, a smaller number of congeners were found in manufactured PCB
mixtures, and measurements of PCBs in the environment and in human blood samples typically
target a subset of the congeners.2'3
The PCB congeners are sometimes separated into two categories, "dioxin-like" or "non-dioxin-
like," that are defined by structural differences and that act by different toxicological
mechanisms.4'5 The dioxin-like PCBs are structurally and toxicologically related to the chemical
2,3,7,8- tetrachlorodibenzo-p-dioxin, which has been studied very extensively in toxicological
and epidemiological research. However, both categories have been associated with adverse
health outcomes and it is unknown which congeners are the most potent, particularly for
outcomes most relevant to children's health.2'4
Manufacture, sale, and use of PCBs was generally banned in the United States in 1979,6 but EPA
regulations have authorized their continued use in certain equipment manufactured prior to
the ban. Due to their persistent nature, PCBs remain widely distributed in the environment, and
they are also present at many Superfund sites.2 The persistent nature of PCBs and their
distribution through the food chain has resulted in continuing human exposure. However,
dietary intake of PCBs and levels measured in blood serum have declined since the ban.2'7'8
Measured levels of PCBs in human blood decreased by an estimated 87% from 1973-2003,7 and
levels of PCB-153, one of the major PCB congeners, also showed significant decline from the
late 1980s to 2002.8 Although levels of PCBs in environmental samples have declined from their
peak, the rate of decline has slowed in recent years.9'10
A large body of health effects research comes from children born to mothers who were
exposed to high concentrations of a mixture of PCBs and polychlorinated dibenzofurans (a class
of dioxin-like chemicals) in accidental poisoning incidents in Taiwan and Japan. These prenatally
exposed children exhibited a number of adverse health effects, including neurodevelopmental
effects such as cognitive deficits, developmental delays, effects on motor skills, behavioral
effects, immunological effects, and skin alterations ranging from irritation to chloracne,2 a
potentially serious inflammatory condition.11"16
Following the poisoning incidents, several studies have been conducted to examine the effects
of PCBs at more typical exposure levels. Many of these studies have linked early-life exposure
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Polychlorinated Biphenyls (PCBs) | Biomonitoring
to PCBs with neurodevelopmental effects, such as lowered intelligence, and behavioral deficits,
including inattention and impulsive behavior.17"23 The observed effects have been most
frequently associated with exposure in the womb resulting from the mother having eaten food
contaminated with PCBs,24"29 but some studies have detected relationships between adverse
effects and PCB exposure during infancy and childhood.22'29"31 Although there is some
inconsistency in the epidemiological literature, several reviews of the literature have concluded
that the overall evidence supports a concern for effects of PCBs on children's neurological
development.16'30'32"34 The Agency for Toxic Substances and Disease Registry has determined
that "Substantial data suggest that PCBs play a role in neurobehavioral alterations observed in
newborns and young children of women with PCB burdens near background levels."2 Research
on dioxin-like chemicals in general also supports a concern for neurodevelopmental effects
from the dioxin-like PCBs.35 Similar outcomes have been observed in experimental animal
studies, including behavioral changes and learning deficits in rats and monkeys exposed to PCBs
in their diets.2'36
Prenatal PCB exposures have also been associated with immunological effects, such as
increased infections, in multiple epidemiological studies,37"43 with supporting evidence from the
literature on effects of dioxin-like chemicals.35 Possible other effects of exposure to PCBs—with
limited or inconclusive evidence—include preterm birth and low birthweight,16 as well as
effects on the timing of puberty in both boys and girls.44 PCBs are also considered "reasonably
anticipated to be human carcinogens," based on experimental animal studies.45
Biomonitoring data in U.S. children under 12 years of age is limited. One study of 6- to 9-year-
old girls from 2005-2007 in California and Ohio showed a median level of PCB-153, the
congener with the highest concentration, of 7.4 nanograms per gram of lipid (ng/g lipid). The
same congener was measured in a nationally representative sample of the U.S. population ages
12 years and older in 2003-2004. The median level of PCB-153 in males and females ages 12 to
19 years was 5.4 ng/g lipid and for adults ages 20 years and over the median level was 24.2
ng/g lipid.46'47
Due to the continued presence of PCBs in fish, especially salmon, meat, poultry, dairy products,
and breast milk,48 dietary intake is an important pathway of exposure for PCBs.2 In infants,
dietary intake is important since PCBs accumulate in the mother's body over many years and
are stored in the fat in breast milk,35 and breast-feeding infants are exposed to the PCBs in the
milk.49 PCBs can also cross the placental barrier to transfer prenatally from mother to fetus, and
PCBs have been measured in cord blood.2'50
Recent findings also suggest that the presence of PCBs in indoor dust and indoor air may
constitute an important exposure pathway for some portion of the population.51"54 The
importance of PCBs in indoor environments may be greater for toddlers than for adults and
children of other ages, because toddlers tend to have more contact with house dust.51 A study
of homes with unusually high indoor air concentrations of PCBs found that a PCB-containing
wood flooring finish applied in the 1950s and 1960s can be a major contributor to current
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Biomonitoring | Polychlorinated Biphenyls (PCBs)
elevations of PCBs in blood for people living in those homes.53 PCBs have been found in caulk in
some schools and other buildings constructed or renovated before the late 1970s, which may
contribute significantly to indoor air and dust levels of PCBs in those buildings.55'56 Many
schools have lighting systems containing PCBs that were produced before PCBs were banned.
While well-contained lighting systems pose little risk, the PCB-containing ballasts are only
expected to last 10-15 years. Existing ballasts from before the ban are past their life expectancy
and are at a greater risk for leaks and fires, resulting in a greater risk of PCB exposure.57 Finally,
the inadvertent presence of PCBs has been found in pigments that are currently manufactured
for use in paints, inks, textiles, paper, cosmetics, leather, and other materials.58'59
Blood levels of PCBs generally increase with age, because these chemicals are persistent.60'61
However, the decline in levels of PCBs in the environment and in foods over the past three
decades, suggests that young people today are exposed to lower levels of PCBs through the diet
than were previous generations.2'7'9'10
Although environmental levels of PCBs have been declining, there are concerns that some past
PCB emissions trapped in polar ice may be released to the environment in coming years with
increasing ice melts.62'63 Furthermore, environments where heavy PCB contamination
previously occurred continue to be remediated, which may dislodge or expose additional PCBs.
The Hudson River, contaminated with 1.3 million pounds of PCBs between 1947 and 1977, is
undergoing remediation to remove PCB-contaminated sediments. After Phase 1 of the
remediation in 2009 there was a short-term increase in the PCB levels in fish samples, but more
recent samples from 2010 did not have increased PCB concentrations.64'65
The following indicator presents the best nationally representative data on PCB levels in
women of child-bearing age. Indicator B7 presents median blood serum levels of PCBs for
women ages 16 to 49 years. Although data are available only for two two-year survey periods at
this time, the data provide a baseline that will be updated with PCB measurements over time
from subsequent survey cycles. No indicator is presented for PCBs in children due to the limited
availability of data.
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Polychlorinated Biphenyls (PCBs) | Biomonitoring
Indicator B7: PCBs in women ages 16 to 49 years: Median concentrations in blood
serum, by race/ethnicity and family income, 2001-2004
About the Indicator: Indicator B7 presents concentrations of PCBs in blood serum of U.S. women
ages 16 to 49 years. The data are from a national survey that collects blood specimens from a
representative sample of the population every two years, and then measures the concentration of
PCBs in the blood serum. The indicator presents comparisons of PCBs in blood serum for women of
different race/ethnicities, and for women of different income levels. The focus on women of child-
bearing age is based on concern for potential adverse effects in children born to women who have
been exposed to PCBs.
NHANES
The National Health and Nutrition Examination Survey (NHANES) provides nationally
representative biomonitoring data for PCBs. NHANES is designed to assess the health and
nutritional status of the civilian noninstitutionalized U.S. population and is conducted by the
National Center for Health Statistics, part of the Centers for Disease Control and Prevention
(CDC). Interviews and physical examinations are conducted with approximately 10,000 people
in each two-year survey cycle. CDC's National Center for Environmental Health measures
concentrations of environmental chemicals in blood and urine samples collected from NHANES
participants. Summaries of the measured values for more than 200 chemicals are provided in
the Fourth National Report on Human Exposure to Environmental Chemicals.46
PCB Congeners
Indicator B7 presents blood serum levels of PCBs in women of child-bearing age. There are 209
possible PCBs, referred to as "congeners," which are defined by the number of chlorine atoms
(from 1 to 10) and their position in the chemical structure. Most of these congeners were not
present in the manufactured PCB mixtures and have not been measured in environmental or
human samples.
PCB concentrations are measured in blood serum. PCBs are lipophilic, meaning that they tend
to accumulate in fat. Serum PCB concentrations are measured and expressed on a lipid-
adjusted basis, as these values better represent the amount of PCBs stored in the body
compared with unadjusted values.46 The indicator uses lipid-adjusted concentrations, meaning
that the concentration of PCBs in serum is divided by the concentration of lipid in serum. The
resulting units are nanograms of PCB per gram of lipid (ng/g lipid) in serum.1
Concentrations of PCBs in blood serum have been measured in a representative subset of
NHANES participants ages 12 years and older beginning with the 1999-2000 survey cycle.
1 Serum levels of PCBs can also be reported without lipid adjustment. Both the lipid-adjusted values and the
unadjusted "whole weight" values are reported in CDC's Fourth National Report on Human Exposure to
Environmental Chemicals.
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Biomonitoring | Polychlorinated Biphenyls (PCBs)
NHANES sampled for 34 PCB congeners in 2001-2002, and added 4 congeners in 2003-2004 for
a total of 38 congeners. Indicator B7 uses NHANES data on four specific congeners: PCBs 118,
138, 153, and 180. These four congeners are generally found at higher levels in the
environment—and in human blood samples—than other PCB congeners. This combination of
congeners has been frequently used to represent PCB exposure in the epidemiological studies
described above that identified children's health concerns for PCBs. PCBs 118, 138,153, and
180 were detected in the majority of samples for women ages 16 to 49 years in 2001-2002, and
in virtually all samples for this population group in 2003-2004.
Indicator B7 was calculated by summing together the measured values of the 4 selected
congeners for each woman 16 to 49 years sampled in NHANES; this approach is commonly used
in studies assessing levels of PCBs in human blood samples and environmental samples.2'30 If
the congener was not detected in a sample, a default value below the detection limit was
assigned for purposes of calculating the summed total." This assumption has a small impact on
the indicator values, because all four congeners were detected in most samples in the
combined four-year (2001-2004) data set.
In 2001-2004, a sum of measured PCBs 118, 138,153, and 180 is available from NHANES for
4,205 individuals ages 12 years and older, including 1164 women ages 16 to 49 years. The four
selected PCBs were detected in 81% of the individuals sampled in NHANES 2001-2004,"' and in
71% of women ages 16 to 49 years.IV The median sum of the four PCB congeners in blood serum
among all NHANES participants in 2001-2004 was 71 ng/g lipid and the 95th percentile sum was
316 ng/g lipid.
Birth Rate Adjustment
Indicator B7 uses measurements of PCBs in the blood of women ages 16 to 49 years to
represent the distribution of PCB exposures to women who are pregnant or may become
pregnant. However, women of different ages have a different likelihood of giving birth. For
example, in 2003-2004, women aged 27 years had a 12% annual probability of giving birth, and
women aged 37 years had a 4% annual probability of giving birth.66 A birth rate-adjusted
distribution of women's PCB levels is used in calculating this indicator/ meaning that the data
are weighted using the age-specific probability of a woman giving birth.67
" The default value used for non-detect samples is equal to the limit of detection divided by the square root of 2.
111 In 2003-2004, PCBs were detected in 100% of the individuals sampled. The detection frequency was lower in
2001-2002 due to use of less sensitive measurement techniques.
IV The percentage for women ages 16 to 49 years is calculated with the birth rate adjustment described below.
v There may be multiple ways to implement an adjustment to the data that accounts for birth rates by age. The
National Center for Health Statistics has not fully evaluated the method used in ACE, or any other method
intended to accomplish the same purpose, and has not used any such method in its publications. NCHS and EPA
are working together to further evaluate the birth rate adjustment method used in ACE and alternative methods.
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Polychlorinated Biphenyls (PCBs) | Biomonitoring
Data Presented in the Indicator
Indicator B7 presents median concentrations of PCBs in blood serum, computed as the sum of
PCBs 118, 138, 153, and 180, for women ages 16 to 49 years of different races/ethnicities and
levels of family income, using NHANES data from 2001-2002 and 2003-2004.
Data from 1999-2000 are not included in the indicator because less sensitive measurement
techniques were used in those years, and PCB levels could not be determined in a large
proportion of the blood samples. Improvements in measurement sensitivity were achieved in
2001-2002, with further improvements in 2003-2004 resulting in the detection of PCBs in a
majority of samples.61 The data from the 2001-2002 and 2003-2004 NHANES cycles are
combined to increase the statistical reliability of the estimates for each race/ethnicity and
income group, and to reduce any possible influence of geographic variability that may occur in
two-year NHANES data. No time series is shown because data from only two NHANES cycles are
too limited to depict possible changes over time.
Four race/ethnicity groups are presented in Indicator B7: White non-Hispanic, Black non-
Hispanic, Mexican-American, and "All Other Races/Ethnicities." The "All Other
Races/Ethnicities" category includes all other races and ethnicities not specified, together with
those individuals who report more than one race. The limits of the sample design and sample
size often prevent statistically reliable estimates for smaller race/ethnicity groups. The data are
also tabulated across three income categories: all incomes, below the poverty level, and greater
than or equal to the poverty level.
Additional information on how 95th percentile blood serum levels of PCBs vary by race/ethnicity
and family income for women ages 16 to 49 years is presented in the supplemental data tables
for this indicator
Please see the Introduction to the Biomonitoring section for an explanation of the terms
"median" and "95th percent
applied to these indicators.
"median" and "95th percentile," along with information on the statistical significance testing
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Biomonitoring | Polychlorinated Biphenyls (PCBs)
Indicator B7
PCBs in women ages 16 to 49 years: Median concentrations in blood serum,
by race/ethnicity and family income, 2001-2004
All Races/Ethnicities
White non-Hispa.
All
Incomes
All Other Races/Ethnicities
At or
Above
Poverty
Level
Below
Poverty
Level
All Races/Ethnicities
White non-His
Mexican-American
All Other Races/Ethnicities"
All Races/Ethnicities
Mexican-American
Concentration of four PCBs in serum (ng/g lipid)
Data: Centers for Disease Control and Prevention, National Center for Health Statistics
and National Center for Environmental Health, National Health and Nutrition Examination Survey
Note: To reflect exposures to women who are pregnant or may become pregnant, the estimates
are adjusted for the probability (by age and race/ethnicity) that a woman gives birth.
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*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
** The estimate is not reported because it has large uncertainty: the relative standard error, RSE, is 40% or greater (RSE =
standard error divided by the estimate), or the RSE cannot be reliably estimated.
Data characterization
Data for this indicator are obtained from an ongoing continuous survey conducted by the National Center
for Health Statistics.
Survey data are representative of the U.S. civilian noninstitutionalized population.
PCBs are measured in blood samples obtained from individual survey participants.
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Polychlorinated Biphenyls (PCBs) | Biomonitoring
In 2001-2004, the median level of PCBs in blood serum among women ages 16 to 49 years
(the sum of PCBs 118, 138,153 and 180) was 30 ng/g lipid.
Median PCB levels were higher for women with higher incomes than for women with lower
incomes, consistently for all race/ethnicity groups.
• After accounting for other demographic differences (i.e., differences in age profile), the
differences between income levels for each race/ethnicity group were not statistically
significant except for the differences for White non-Hispanic women.
Median PCB levels were lower among Mexican-American women than among women of
any other race/ethnicity group.
• These differences were statistically significant. After accounting for other demographic
differences (i.e., differences in income or age profile), the differences remained
statistically significant except for that between Mexican-American women and women
of "All Other Races/Ethnicities."
The 95th percentile concentration of PCBs among women ages 16 to 49 years was 106 ng/g
lipid. Among women of "All Other Races/Ethnicities," the 95th percentile PCB concentration
was substantially higher, at 245 ng/g lipid; the 95th percentile concentration among
Mexican-American women was substantially lower at 49 ng/g lipid. (See Table B7a.)
• These differences were statistically significant: the 95th percentile for women of "All
Other Races/Ethnicities" was greater than the value for each of the remaining
race/ethnicities; and the 95th percentile for Mexican-American women was less than the
value for each of the remaining race/ethnicities.
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Biomonitoring | Polybrominated Diphenyl Ethers (PBDEs)
Polybrominated Diphenyl Ethers (PBDEs)
Polybrominated diphenyl ethers (PBDEs) are a group of brominated flame retardant chemicals
that have been incorporated into a variety of manufactured products, including foam
cushioning used in furniture and plastics used in televisions and computers. Flame retardants
are intended to slow the rate of ignition and fire growth, allowing more time for people to
escape from a fire or extinguish it.
All PBDEs have a common structure of a diphenyl ether molecule, which may have from 1-10
bromine atoms attached; each particular PBDE variant is referred to as a congener. In theory,
there could be as many as 209 PBDE congeners, but a much smaller number of congeners are
commonly found in the commercial PBDE mixtures and in measurements of PBDEs in humans
and the environment.
Three commercial PBDE mixtures have been used in manufactured products since the 1960s
and 1970s, when these chemicals came into use,1 with each mixture made up of congeners
with varying degrees of bromination. The commercial pentabromodiphenyl ether (pentaBDE)
and octabromodiphenyl ether (octaBDE) mixtures have not been manufactured or imported in
the United States since 2004. The pentaBDE mixture, made up primarily of four- and five-
bromine congeners, was used almost entirely in flexible polyurethane foam in furniture,
mattresses, carpet padding, and automobile seats; and the octaBDE mixture, made up primarily
of seven- and eight-bromine congeners, was used in acrylonitrile-butadiene-styrene (ABS)
plastic for certain electric and electronic devices.
A third product, the commercial decabromodiphenyl ether (decaBDE) mixture, is still
manufactured and used in the United States. The decaBDE mixture, made up almost entirely of
the 10-bromine congener, has been used primarily in high-impact polystyrene (HIPS) plastic
that was frequently used to make the back part of television sets, and in other electronic
devices. However, there are indications that the use of decaBDE in electronic devices has
declined in recent years, particularly since restrictions on the use of decaBDE in electronics
were implemented in Europe beginning in 2008. DecaBDE is also used as a flame retardant on
certain types of textiles; in electrical products, including uses in vehicles and airplanes; and in
certain building materials. The major U.S. importers and manufacturers of decaBDE have
announced that this mixture will be phased out by the end of 2013.2 As use of PBDEs is
reduced, they are being replaced by other flame-retardant chemicals or by materials that are
inherently resistant to fire. EPA has conducted an assessment of alternatives to commercial
pentaBDE,3 and is conducting a similar assessment of alternatives to commercial decaBDE.4
PBDEs can be released into the environment at various points in their lifecycle, from their
production and application to consumer products to their release from discarded products in
landfills. Since PBDEs are not chemically bound to the products in which they are used, they can
easily migrate into the surrounding air, dust, soil, and water. Although production and use of
the commercial PBDE mixtures has been phased out (pentaBDE and octaBDE) or will soon be
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Polybrominated Diphenyl Ethers (PBDEs) | Biomonitoring
phased out (decaBDE), it is likely that PBDE congeners will continue to be present in the
environment for many years. This is because products previously manufactured with PBDEs
(e.g., sofas) will stay in use for many years. PBDEs will continue to be released from these
products while they are in use, and these releases may continue when the products are
disposed of or recycled. PBDEs are persistent in the environment, so even if there were no
further releases they would continue to be detected for many years.
Exposure studies, focusing on selected PBDE congeners that were most predominant in the
commercial mixtures or that are frequently measured in environmental samples, have
concluded that the presence of PBDEs in house dust and in foods are both important
contributors to PBDE exposures for people of all ages, and that exposures from house dust are
generally greater than those from food.1'5"11
Studies conducted in multiple locations have consistently found PBDEs in U.S. house dust at
levels greater than those found in other countries.12"14 This is likely due to greater use of PBDE-
containing products in homes in the United States than in other countries. Within the United
States, the highest levels of three frequently measured PBDE congeners in dust have been
found in California. The three congeners were all components of commercial pentaBDE
mixtures, and the authors of these studies observed that the elevated levels may be due to
California requirements for flame resistance in residential furniture that are not applicable in
other states.13'15 A study conducted in adults found a stronger association between direct
contact with PBDE-containing materials and PBDE blood levels than between PBDE-
contaminated house dust and PBDE blood levels.16
A second pathway of exposure to PBDEs is through diet. PBDEs are generally persistent
chemicals that accumulate in fat tissue, so they are commonly found in foods derived from
animals.17"19 Information about how PBDEs enter the food web is limited, but release from
manufacture of the PBDEs or of PBDE-containing products; release of PBDEs from products
while they are in use; and release from products when disposed of or recycled are all likely
contributors to PBDEs in the environment. PBDEs have been measured in a variety of
supermarket foods, with the highest levels found in fish and other foods of animal origin.18'20 A
California study found associations between pork and poultry consumption and the levels of
PBDEs measured in blood of children ages 2 to 5 years.13
Levels of PBDEs measured in blood are substantially greater in North America than in Europe
and Asia, a difference that appears to be due to the higher levels of PBDEs in house dust in
North America.7'12'21'22 Studies comparing archived and current samples of blood and pooled
serum from various locations in the United States have shown marked increases in PBDE levels
since the late 1970s.23'24
Early-life exposures to PBDEs may be elevated in a number of ways. A child's exposure to PBDEs
begins in the prenatal period, as PBDEs have been measured in cord blood, fetal blood, and
placental tissue25"27 and continues in early infancy due to the presence of PBDEs in breast
milk.11'22'28"31 Levels of PBDEs in breast milk are higher in North America than elsewhere,12 and
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estimated intakes of PBDEs are substantially greater for a breastfeeding infant than exposures
that occur during other life stages.6'22
Exposures are also elevated for young children up to age 7 years. While few studies have
measured concentrations of PBDEs in young children, one large study conducted in Australia
found that levels of PBDEs in blood are greatest for children ages 2 to 5 years, compared with
older children and adults.32 A study of 20 young children (ages 1.5 to 4 years) in various
locations throughout the United States found that their PBDE blood levels were consistently
higher than those of their mothers.33 A study of California children ages 2 to 5 years found PBDE
blood levels generally greater than those measured in California residents ages 12 to 60
years.13'15 A study of 7-year-old Mexican-American children living in California reported PBDE
blood levels that were three times the levels found in their mothers during pregnancy.34
The elevated exposures observed for young children are likely due to increased exposure to
house dust, based on several studies that have estimated exposures based on measured levels
of PBDEs in house dust, air, and food.6'7'9'35 Infants and small children may have the highest
exposure to PBDEs in house dust due to their frequent and extensive contact with floors,
carpets, and other surfaces where dust gathers, as well as their frequent hand-to-mouth
activity.36 However, children of all ages (as well as adults) are likely to be exposed to dust
contaminants through hand-to-mouth activity and other ingestion pathways, such as the
settling of dust onto food and food preparation surfaces in the kitchen, as well as inhalation
and absorption of PBDEs through the skin.1'9'22
Concerns about the health effects of PBDEs are based largely on laboratory animal studies,
along with findings of the limited number of human epidemiological studies that have been
conducted to date. A primary concern from the animal studies is for effects on the developing
brain and nervous system, including effects on learning, memory, and behavior.37"39 A study of
children in New York City found significant associations between children's prenatal exposure
to PBDEs and performance on IQ tests at ages up through 6 years.40 A second epidemiological
study conducted in the Netherlands found that prenatal exposure to PBDEs was associated with
reduced scores on some tests of neurological development and improved scores on other tests
at ages 5 to 6 years.41
PBDEs are suspected endocrine disrupters.37 Endocrine disrupters act by interfering with the
biosynthesis, secretion, action, or metabolism of naturally occurring hormones.42'43 Given the
importance of hormones in human physiology, there is concern in the scientific community
over the potential for endocrine disrupters to adversely affect children's health, particularly in
reproduction, early and adolescent development, and behavior.
Animal and human studies indicate that PBDEs may alter circulating levels of thyroid
hormones.37'44"47 Moderate deficits in maternal thyroid hormone levels during early pregnancy
have been linked to reduced childhood IQ scores and other neurodevelopmental effects, as well
as unsuccessful or complicated pregnancies.48 Animal studies have found that PBDE exposure at
critical stages of fetal development reduced levels of male hormones or caused other changes
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Polybrominated Diphenyl Ethers (PBDEs) | Biomonitoring
relevant to male reproductive development.37'47'49"51 An epidemiological study of boys born in
Denmark and Finland found that increased levels of PBDEs in breast milk were associated with
an increased risk of cryptorchidism (undescended testes),52 an effect that may be related to
hormone disruption during critical stages of development.53'54 Also, a study of Mexican
immigrant women in California found effects on fertility (increased time to pregnancy) with
increasing PBDE levels; this finding may be related to hormonal activity of PBDEs.55
The following indicator presents the best nationally representative data on PBDE levels in
women of child-bearing age. Indicator B8 presents median blood serum levels of PBDEs for
women ages 16 to 49 years. Although data are available only for a single two-year period at this
time, the data provide a baseline that will be updated with PBDE measurements over time from
subsequent survey cycles.
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Indicator B8: PBDEs in women ages 16 to 49 years: Median concentrations in blood
serum, by race/ethnicity and family income, 2003-2004
About the Indicator: Indicator B8 presents concentrations of PBDEs in blood serum of U.S. women
ages 16 to 49 years. The data are from a national survey that collects blood specimens from a
representative sample of the population every two years, and then measures the concentration of
PBDEs in the blood serum. The indicator presents comparisons of PBDEs in blood serum for women
of different race/ethnicities, and for women of different income levels. The focus on women of child-
bearing age is based on concern for potential effects in children born to women who have been
exposed to PBDEs.
NHANES
The National Health and Nutrition Examination Survey (NHANES) provides nationally
representative biomonitoring data for PBDEs. NHANES is designed to assess the health and
nutritional status of the civilian noninstitutionalized U.S. population and is conducted by the
National Center for Health Statistics, part of the Centers for Disease Control and Prevention
(CDC). Interviews and physical examinations are conducted with approximately 10,000 people
in each two-year survey cycle. CDC's National Center for Environmental Health measures
concentrations of environmental chemicals in blood and urine samples collected from NHANES
participants. Summaries of the measured values for more than 200 chemicals are provided in
the Fourth National Report on Human Exposure to Environmental Chemicals.56
PBDE Congeners
Indicator B8 presents blood serum levels of PBDEs in women of child-bearing age. There are 209
possible PBDEs, referred to as "congeners," which are defined by the number of bromine atoms
(from 1 to 10) and their position in the chemical structure. Each congener is assigned a specific
brominated diphenyl ether (BDE) number, such as BDE-47 (a tetrabromodiphenyl ether
congener - four bromine atoms). Most of these congeners have not been detected in the
manufactured PBDE mixtures and have not been measured in environmental or human samples.
PBDE concentrations are measured in blood serum. PBDEs are lipophilic, meaning that they
tend to accumulate in fat. Serum PBDEs concentrations are measured and expressed on a lipid-
adjusted basis, as these values better represent the amount of PBDEs stored in the body
compared with unadjusted values.56 The indicator uses lipid-adjusted concentrations, meaning
that the concentration of PBDEs in serum is divided by the concentration of lipid in serum. The
resulting units are nanograms of PBDE per gram of lipid (ng/g lipid) in serum.1
1 Serum levels of PBDEs can also be reported without lipid adjustment. Both the lipid-adjusted values and the
unadjusted "whole weight" values are reported in CDC's Fourth National Report on Human Exposure to
Environmental Chemicals.
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Concentrations of PBDEs in blood serum have been measured in a representative subset of
NHANES participants ages 12 years and older in the 2003-2004 survey cycle. NHANES sampled
for 10 PBDE congeners in 2003-2004, including those most frequently measured in
environmental and human samples. These include BDEs 17, 28, 47, 66, 85, 99, 100,153, 154,
and 183. Most of these 10 congeners were components of the pentaBDE mixture that was used
in polyurethane foam for furniture, mattresses, and automotive seating. Some of the congeners
measured in NHANES were components of the octaBDE mixture, used in plastics for some
household electric devices. The primary congener comprising the decaBDE formulation, BDE-
209, was not measured in NHANES in 2003-2004.
Indicator B8 was calculated by summing together the measured values of the 10 congeners for
each woman 16 to 49 years sampled in NHANES; this approach is commonly used in studies
assessing levels of PBDEs in human blood samples and environmental samples.1 Data are
insufficient at this time to assess and quantify differences in toxicity of the measured PBDE
congeners, or to inform approaches other than an unweighted summation of the 10 congeners.
If a congener was not detected in a particular blood sample, a default value below the detection
limit was assigned for purposes of calculating the summed total for the sampled individual." This
assumption has a small impact on the reported blood levels of PBDEs, because almost all women
sampled had values well above the detection limit for at least some congeners. BDEs 47, 100 and
153 were each detected in more than 90% of women ages 16 to 49 years.
In 2003-2004, a sum of the 10 measured PBDEs is available from NHANES for 2,040 individuals
ages 12 years and older, including 540 women ages 16 to 49 years. One or more PBDE
congeners were detected in 99% of the individuals sampled in NHANES 2003-2004, and in 99%
of women ages 16 to 49 years.1" The median sum of the ten PBDE congeners among NHANES
participants in 2003-2004 was 38 ng/g lipid and the 95th percentile sum was 307 ng/g lipid.
Birth Rate Adjustment
Indicator B8 uses measurements of PBDEs in blood of women ages 16 to 49 years to represent
the distribution of PBDE exposures to women who are pregnant or may become pregnant.
However, women of different ages have a different likelihood of giving birth. For example, in
2003-2004, women aged 27 years had a 12% annual probability of giving birth, and women
aged 37 years had a 4% annual probability of giving birth.57 A birth rate-adjusted distribution of
women's PBDE levels is used in calculating this indicator,lv meaning that the data are weighted
using the age-specific probability of a woman giving birth.58
" The default value used for non-detect samples is equal to the limit of detection divided by the square root of 2.
111 The percentage for women ages 16 to 49 years is calculated with the birth rate adjustment described below.
lv There may be multiple ways to implement an adjustment to the data that accounts for birth rates by age. The
National Center for Health Statistics has not fully evaluated the method used in ACE, or any other method
intended to accomplish the same purpose, and has not used any such method in its publications. NCHS and EPA
are working together to further evaluate the birth rate adjustment method used in ACE and alternative methods.
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Data Presented in the Indicator
Indicator B8 presents median concentrations of PBDEs in blood serum for women ages 16 to 49
years of different races/ethnicities and levels of family income, using NHANES data from 2003-
2004.v
Three race/ethnicity groups are presented in Indicator B8: White non-Hispanic, Black non-
Hispanic, and Mexican-American. The data are also tabulated across three income categories:
all incomes, below the poverty level, and greater than or equal to the poverty level.
Additional information on how median blood serum levels of PBDEs vary by race/ethnicity and
family income for children ages 12 to 17 years is presented in a supplemental data table for this
indicator.
Please see the Introduction to the Biomonitoring section for an explanation of the term
"median" and information on the statistical significance testing applied to this indicator.
v Unlike other biomonitoring indicators in this report, 95th percentile PBDE levels are not provided in a
supplementary table. This is because most 95th percentile PBDE values do not meet ACE statistical reliability
criteria. There is more uncertainty in 95th percentile estimates for PBDEs than for other chemicals because data are
only available for two years (2003-2004) at this time. Similarly, separate values are not provided considering both
race/ethnicity and income simultaneously, nor are values provided for the "All Other Races/Ethnicities" category,
because (with data from only one NHANES cycle available at this time) such estimates lack statistical reliability.
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Polybrominated Diphenyl Ethers (PBDEs) | Biomonitoring
Indicator B8
PBDEs in women ages 16 to 49 years: Median concentrations in blood serum,
by race/ethnicity and family income, 2003-2004
> Poverty
Family
Income
< Poverty
White non-Hispanic
Race/ B|acj( non-Hispanic
Ethnicity
Mexican-American*
Concentration of PBDEs in serum (ng/g lipid)
Data: Centers for Disease Control and Prevention, National Center for Health Statistics
and National Center for Environmental Health, National Health and Nutrition Examination Survey
Note: To reflect exposures to women who are pregnant or may become pregnant, the estimates
are adjusted for the probability (by age and race/ethnicity) that a woman gives birth.
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*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
Data characterization
Data for this indicator are obtained from an ongoing continuous survey conducted by the National Center
for Health Statistics.
Survey data are representative of the U.S. civilian noninstitutionalized population.
PBDEs are measured in blood samples obtained from individual survey participants.
The median concentration of PBDEs in blood serum of women ages 16 to 49 years was 44
ng/g lipid in 2003-2004.
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White non-Hispanic women and Black non-Hispanic women had the highest median PBDE
levels at 49 and 48 ng/g lipid, respectively.
• The differences by race/ethnicity were generally not statistically significant without
accounting for differences by age and income across race/ethnicity groups. After
accounting for differences by age and income across race/ethnicity groups, PBDE levels
in White non-Hispanic women were statistically significantly greater than levels in Black
non-Hispanic women. Also after adjustment, PBDE levels in Black non-Hispanic women
were statistically significantly greater than levels in Mexican-American women.
Among women of child-bearing age, there was little difference in median PBDE
concentrations in blood serum between income groups.
The median concentration of PBDEs in children ages 12 to 17 years overall was 53 ng/g lipid.
The median concentration of PBDEs for children with family incomes below the poverty level
was 63 ng/g lipid, and 50 ng/g lipid for children at or above poverty level. (See Table B8a.)
• The difference in median PBDE concentration between the income groups was not
statistically significant.
Among children ages 12 to 17, White non-Hispanic children and Black non-Hispanic children
had the lowest median PBDE levels at 48 and 50 ng/g lipid. Mexican-American children had
median PBDE levels of 63 ng/g lipid. (See Table B8a.)
• These differences by race/ethnicity were not statistically significant.
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Phthalates | Biomonitoring
Phthalates
Phthalates are a class of manufactured chemicals commonly used to increase the flexibility of
plastics in a wide array of consumer products. More than 470 million pounds of phthalates are
produced or imported in the United States each year.1
By far the most common use of phthalates is in the production of polyvinyl chloride (PVC)
products.2 PVC is the second most commonly used plastic in the world, and is present in pipes
and tubing, construction materials, packaging, electrical wiring, and thousands of consumer
goods.3'4 Phthalates are or have been used in wall coverings, tablecloths, floor tiles, furniture
upholstery, carpet backings, shower curtains, garden hoses, rainwear, pesticides, some toys,
shoes, automobile upholstery, food packaging, medical tubing, and blood storage bags.5"8
Phthalates are not strongly bound in these products and can therefore leach out.4"10 Some
phthalates are also present in cosmetics, nail polish, hair products, skin care products, and
some medications.4'6'7'11'12
The Consumer Product Safety Improvement Act of 2008 (CPSIA) banned the use of three
phthalates in toys and child care articles at concentrations greater than 0.1 percent: di-2-
ethylhexyl phthalate (DEHP), dibutyl phthalate (DBP), and butyl benzyl phthalate (BBzP). CPSIA
also restricts the use of di-isononyl phthalate (DINP), di-isodecyl phthalate (DIDP), and di- n-
octyl phthalate (DnOP) in toys that can be mouthed and child care articles. The Consumer
Product Safety Commission has also appointed a Chronic Hazard Advisory Panel to examine the
cumulative health risks of phthalates and phthalate substitutes, and to recommend whether to
continue the ban of DINP, DIDP, and DnOP and whether any other phthalates or phthalate
substitutes should be banned.1 As use of phthalates is reduced, they are being replaced by
other chemicals, such as di-isononylcyclohexane-l,2-dicarboxylate (DINCH) and di(2-ethylhexyl)
terephthalate (DEHT), that also increase the flexibility of plastics.13"15 EPA is planning to conduct
an assessment of alternatives to several phthalates.1
For most phthalates, the major route of exposure is food ingestion.4'16"19 However, personal
care product use and inhalation are major routes of exposure for certain phthalates.4"8'11'20
Some phthalates have been found at higher levels in fatty foods such as dairy products, fish,
seafood, and oils.8 Phthalates in a mother's body can enter her breast milk. Ingestion of that
breast milk and infant formula containing phthalates may also contribute to infant phthalate
exposure.21 The phthalates that may be present in dust can be ingested by infants and children
through hand-to-mouth activities.10'22 Finally, infants and small children can be exposed to
phthalates by sucking on toys and objects made with phthalate-containing plastics.10
Other minor routes of phthalate exposure include inhalation, drinking contaminated water, and
absorption through the skin.16'17 Phthalates can be released in small amounts to the air people
breathe inside homes or schools from the many consumer products that contain them.7'20
People living near phthalate-producing factories or hazardous waste sites may be exposed to
phthalates released into the air or ground water where they live.5'7'8 Individuals may be exposed
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Biomonitoring | Phthalates
to phthalates during the use of many personal care products containing phthalates, such as hair
products, cosmetics, and lotions.11'23'24 Phthalates in these products may be absorbed through
contact with the skin or may be inhaled if some of the product is present in the air.5 In addition,
certain medical devices, such as intravenous tubing or flexible bags containing blood,
medications, or nutritional products, contain phthalates. These can be a source of phthalate
exposure to children and women of child-bearing age when the tubing or bags are used to
administer medications, nutritional products, or blood to the individual. This can be a very
significant route of exposure, especially for premature infants in intensive care units.25"27
Phthalate exposures, assessed from urinary concentrations of phthalate metabolites (i.e.,
breakdown products), appear to be higher for children compared with adolescents and adults.
Studies of phthalate metabolites in children's urine are limited, but the few that have been
published have found children's urinary phthalate metabolite levels to be higher than levels in
adults and to decrease with age (i.e., younger children had more phthalate metabolites in their
urine than older children did).28"30 The exception is monoethyl phthalate (MEP), a metabolite of
diethyl phthalate, which has been found to be present in higher levels in adult urine compared
with children's urine.28 Levels of MEP are most likely associated with use of consumer products
that contain diethyl phthalate, such as detergents, soaps, cosmetics, shampoos, and perfumes.
5,28
Some phthalates are suspected endocrine disrupters.31"35 Endocrine disrupters act by
interfering with the biosynthesis, secretion, action, or metabolism of naturally occurring
hormones.32'36 Given the importance of hormones in human physiology, there is concern in the
scientific community over the potential for endocrine disrupters to adversely affect children's
health, particularly in reproduction, development, and behavior. Male laboratory animals
exposed to high doses of some phthalates have been known to display elements of "phthalate
syndrome," which includes infertility, decreased sperm count, cryptorchidism (undescended
testes), hypospadias (malformation of the penis in which the urethra does not open at the tip
of the organ), and other reproductive tract malformations.4 A number of animal studies have
reported associations between exposure to certain phthalates and changes in male hormone
production, altered sexual differentiation, and changes to reproductive organs, including
hypospadias.37"45 These findings in animal studies, although typically occurring at exposure
levels much higher than what the general population may be exposed to, suggest a potential
concern for health effects in children as well. The National Research Council has concluded that
prenatal exposure to certain phthalates produces reproductive tract abnormalities in male rats,
and also concluded that the same effects could plausibly occur in humans.4
There are only a limited number of human studies looking at the relationship between
phthalate exposure and hormonal and reproductive health changes. In one study, prenatal
exposure to some phthalates at typical U.S. population levels was associated with changes in
physical measures of the distance between the anus and the genitals (anogenital distance) in
male infants.46'47 A shorter anogenital distance has been associated with decreased fertility in
animal experiments48'49 and a recent human study reported that a shorter anogenital distance
in men was associated with decreased semen quality and low sperm count.50 Another study
reported an association between increased concentrations of phthalate metabolites in breast
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Phthalates | Biomonitoring
milk and altered reproductive hormone levels in newborn boys. The same study did not find an
association between breast milk phthalate metabolite concentrations and cryptorchidism.51
Exposure to some phthalates has been associated with neurodevelopmental problems in
children in some studies. Two studies of a group of New York City children ages 4 to 9 years
reported associations between prenatal exposure to certain phthalates and behavioral deficits,
including effects on attention, conduct, and social behaviors.52'53 Studies conducted in South
Korea of children ages 8 to 11 years reported that children with higher levels of certain
phthalate metabolites in their urine were more inattentive and hyperactive, displayed more
symptoms of attention-deficit/hyperactivity disorder (ADHD), and had lower IQ compared with
those who had lower levels.54'55The exposure levels in these studies are comparable to typical
exposures in the U.S. population.
A handful of studies have reported associations between prenatal exposure to some phthalates
and preterm birth, shorter gestational length, and low birth weight;56"59 however, one study
reported phthalate exposure to be associated with longer gestational length and increased risk
of delivery by Cesarean section.60
Finally, some researchers have hypothesized that phthalate exposure in homes may contribute
to asthma and allergies in children. Two research groups have conducted studies, primarily in
Europe, and reported associations between surrogates for potential phthalate exposure in the
home and risk of asthma and allergies in children.61 Examples of the exposure indicators and
outcomes considered in these studies include an association between some phthalates in
surface dust and increased risk of runny nose, eczema, and asthma,62 and increased risk of
bronchial obstruction associated with the presence of PVC in the home.63
The two indicators that follow use the best nationally representative data currently available on
urinary phthalate metabolite levels over time for women of child-bearing age and children. The
indicators focus on three important phthalates: di-2-ethylhexyl phthalate (DEHP), dibutyl
phthalate (DBF), and butyl benzyl phthalate (BBzP). These three phthalates were chosen
because their metabolites are commonly detected in humans and their potential connection to
adverse children's health outcomes is supported by the scientific literature summarized in the
following paragraphs.
DEHP is currently the only phthalate plasticizer used in PVC medical devices such as blood bags
and plastic tubing. DEHP is also currently used in flooring, wallpaper, and raincoats and has
been used in toys, auto upholstery, and food packaging.64 DBP is used primarily in latex
adhesives, cellulose plastics, dyes, and cosmetics and other personal care products.65 The
largest use of BBzP is in the production of PVC flooring materials, but it is also used in the
manufacture of automotive materials, artificial leather, and food conveyor belts.66'67
In 2006, the National Toxicology Program (NTP) concluded that there is "concern" for effects on
reproductive tract development in male infants less than one year old exposed to DEHP. In
addition, the NTP also concluded that there is "some concern" (the midpoint on a five-level
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Biomonitoring | Phthalates
scale ranging from "negligible" to "serious" concern)' for effects on reproductive tract
development in male children older than one year old exposed to DEHP, and also that there is
"some concern" for effects of prenatal DEHP exposure on reproductive tract development in
males. Concern was greater for males exposed to high levels of DEHP in the womb or early in
life. These conclusions were based primarily on findings from animal studies, as human data are
limited and were determined to be insufficient for evaluating the reproductive effects of
DEHP.64 Some studies have also reported associations of DEHP exposure with increased risk of
asthma and bronchial obstruction, increased risk of ADHD symptoms, and altered pregnancy
durations.55'56'58'60'62'63 Human health studies have reported associations between exposures to
DBP and altered reproductive hormone levels in newborn boys, and shifts in thyroid hormone
levels in pregnant women.51'68 Signs of feminization in young boys (as measured by reduced
anogenital distance), altered hormone levels in newborn boys, and increased risk of rhinitis and
eczema are health effects that have been associated with BBzP exposure in some
studies.46'47'51'62 The exposure levels in these studies are comparable to typical exposures in the
U.S. population. It is important to note that while the following indicators present data on
individual phthalate metabolites, evidence suggests that exposures to multiple phthalates may
contribute to common adverse outcomes. The National Research Council has concluded that
multiple phthalates may act cumulatively to adversely impact male reproductive development.4
Indicator B9 presents median concentrations of metabolites of DEHP, DBP, and BBzP in urine
for women ages 16 to 49 years. Indicator BIO presents median metabolite levels of the same
phthalates (DEHP, DBP, and BBzP) in urine for children ages 6 to 17 years.
1 More information on NTP concern levels is available at http://www.niehs.nih.gov/news/media/questions/sya-
bpa.cfm.
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Indicator B9: Phthalate metabolites in women ages 16 to 49 years: Median
concentrations in urine, 1999-2008
Indicator BIO: Phthalate metabolites in children ages 6 to 17 years: Median
concentrations in urine, 1999-2008
About the Indicators: Indicators B9 and BIO present concentrations of phthalate metabolites in urine
of U.S. women ages 16 to 49 years and children ages 6 to 17 years. The data are from a national
survey that collects urine specimens from a representative sample of the population every two years,
and then measures the concentration of phthalate metabolites in the urine. Indicator B9 presents
concentrations of phthalate metabolites in women's urine over time and Indicator BIO presents
concentrations of phthalate metabolites in children's urine over time. The focus on both women of
child-bearing age and children is based on concern for potential adverse effects in children born to
women who have been exposed to phthalates and in children exposed to phthalates.
NHANES
The National Health and Nutrition Examination Survey (NHANES) provides nationally
representative biomonitoring data for several phthalates. NHANES is designed to assess the
health and nutritional status of the civilian noninstitutionalized U.S. population and is
conducted by the National Center for Health Statistics, part of the Centers for Disease Control
and Prevention (CDC). Interviews and physical examinations are conducted with approximately
10,000 people in each two-year cycle. CDC's National Center for Environmental Health
measures concentrations of environmental chemicals in blood and urine samples collected
from NHANES participants. Summaries of the measured values for more than 200 chemicals are
provided in the Fourth National Report on Human Exposure to Environmental Chemicals.69
Phthalate Metabolites
Indicators B9 and BIO present urinary metabolite levels of three important phthalates: di-2-
ethylhexyl phthalate (DEHP), dibutyl phthalate (di-n-butyl phthalate and di-isobutyl phthalate)
(DBF), and butyl benzyl phthalate (BBzP).
In NHANES and many research studies, biomonitoring of phthalates is conducted by measuring
phthalate metabolites in urine rather than the phthalates themselves. This is because
phthalates may be present in the sampling and laboratory equipment used to study human
exposure levels, and contamination of samples could occur. Also phthalate metabolism is so
rapid that the parent phthalate may not appear in urine.5"8'16'70'71 Furthermore, the phthalate
metabolites, and not the parent phthalates, are generally considered to be the biologically
active molecules.5"8'16'72 Unlike other contaminants that have a tendency to accumulate in the
human body, phthalates are metabolized and excreted quickly, with elimination half-lives on
the order of hours.5"8'71 Therefore, phthalate metabolites measured in humans are indicative of
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Biomonitoring | Phthalates
recent exposures. All values are reported as micrograms of phthalate metabolites per liter of
urine (u.g/L).
Concentrations of phthalate metabolites, including those for DEHP, DBF, and BBzP, have been
measured in urine from a representative subset of NHANES participants ages 6 and older
beginning with the 1999-2000 survey cycle. For DEHP, three metabolites are included: mono-2-
ethylhexyl phthalate (MEHP), mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP), and mono-(2-
ethyl-5-hydroxyhexyl) phthalate (MEHHP)." The urinary levels of MEHP, MEOHP, and MEHHP
are summed together, as is common in phthalates research, to provide a more complete
picture of an individual's total DEHP exposure than is given by any individual metabolite.57'73"75
The primary urinary metabolites of DBP are mono-n-butyl phthalate (MnBP) and mono-isobutyl
phthalate (MiBP). The urinary levels of MnBP and MiBP were measured together for the
NHANES 1999-2000 survey cycle, but for the following years were measured separately.
Indicators B9 and BIO present the combined urinary levels of MnBP and MiBP for each survey
cycle. The primary urinary metabolite of BBzP is mono-benzyl phthalate (MBzP).
Calculation of the DEHP metabolite and DBP metabolite indicator values involves summing
together separate measured values (3 metabolites of DEHP, and 2 metabolites of DBP in the
survey cycles following 1999-2000). If a metabolite included in the sum was not detected in a
sample, a default value below the detection limit was assigned for purposes of calculating the
summed total.1"
In 2007-2008, NHANES collected phthalates biomonitoring data for 2,604 individuals ages 6
years and older, including 571 women ages 16 to 49 years and 690 children ages 6 to 17 years.
DEHP metabolites were detected in about 67% of all individuals sampled. The frequency of
DEHP metabolites detection was 75% in women ages 16 to 49 yearslv, and 69% in children ages
6 to 17 years. DBP metabolites and BBzP metabolite were detected in 98% of all individuals
sampled. The frequency of DBP metabolites detection was 98% in women ages 16 to 49 years,
and 99% in children ages 6 to 17 years. The frequency of BBzP metabolite detection was 97% in
women ages 16 to 49 years, and 99% in children ages 6 to 17 years. The median and 95th
percentile of phthalate levels in urine for all NHANES participants in 2007-2008 were 35 u.g/L
and 406 u.g/L, respectively, for DEHP; 29 u.g/L and 147 u.g/L, respectively, for DBP; and 12 u.g/L
and 82 u.g/L, respectively, for BBzP. The widespread detection of phthalate metabolites,
combined with the fact that phthalates have short half-lives, indicates that phthalate exposure
is widespread and relatively continuous.
" A fourth DEHP metabolite, mono(2-ethyl-5-carboxypentyl) phthalate (MECPP), is now measured in NHANES but
was not measured prior to 2003-2004. At least one other DEHP metabolite has been measured in laboratory
studies but is not measured in NHANES.
111 The default value used for non-detect samples is equal to the limit of detection divided by the square root of 2.
IV The percentage for women ages 16 to 49 years is calculated with the birth rate adjustment described below.
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Phthalates | Biomonitoring
Individual Variability in Urinary Measurements
NHANES data for phthalates are based on measurements made using a single urine sample for
each person surveyed. Due to normal changes in an individual's urinary output throughout the
day, this variability in urinary volume, among other factors related to the measurement of
chemicals that do not accumulate in the body,76 may mask differences between individuals in
levels of phthalates. Since phthalates do not appear to accumulate in bodily tissues, the
distribution of NHANES urinary phthalate levels may overestimate high-end exposures (e.g., at
the 95th percentile) as a result of collecting one-time urine samples.71'77'78 Many studies account
for differences in hydration levels by reporting the chemical concentration per gram of
creatinine. Creatinine is a byproduct of muscle metabolism that is excreted in urine at a
relatively constant rate, independent of the volume of urine, and can in some circumstances
partially account for the measurement variability due to changes in urinary output.79 However,
urinary creatinine concentrations differ significantly among different demographic groups, and
are strongly associated with an individual's muscle mass, age, sex, diet, health status
(specifically renal function), body mass index, and pregnancy status.80'81 Thus, these indicators
present the unadjusted phthalate concentrations so that any observed differences in
concentrations between demographic groups are not due to differences in creatinine excretion
rates. These unadjusted urinary levels from a single sample may either over- or underestimate
urinary levels for a sampled individual. However, for a representative group, it can be expected
that a median value based on single samples taken throughout the day will provide a good
approximation of the median for that group. Furthermore, due to the large number of subjects
surveyed, we expect that differences in the concentrations of phthalates that might be
attributed to the volume of the urine sample would average out within and across the various
comparison groups.
Birth Rate Adjustment
Indicator B9 uses measurements of phthalate metabolites in urine of women ages 16 to 49
years to represent the distribution of phthalate exposures to women who are pregnant or may
become pregnant. However, women of different ages have a different likelihood of giving birth.
For example, in 2003-2004, women aged 27 years had a 12% annual probability of giving birth,
and women aged 37 years had a 4% annual probability of giving birth.82 A birth rate-adjusted
distribution of women's phthalate metabolite levels is used in calculating this indicator/
meaning that the data are weighted using the age-specific probability of a woman giving birth.83
v There may be multiple ways to implement an adjustment to the data that accounts for birth rates by age. The
National Center for Health Statistics has not fully evaluated the method used in ACE, or any other method
intended to accomplish the same purpose, and has not used any such method in its publications. NCHS and EPA
are working together to further evaluate the birth rate adjustment method used in ACE and alternative methods.
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Biomonitoring | Phthalates
Data Presented in the Indicators
Indicator B9 presents median concentrations of DEHP, DBF, and BBzP metabolites in urine over
time for women ages 16 to 49 years, using NHANES data from 1999-2008.
Indicator BIO presents median concentrations of DEHP, DBF, and BBzP metabolites in urine
over time for children ages 6 to 17 years, using NHANES data from 1999-2008.
Additional information on the 95th percentile levels of urinary phthalates and how median
levels of phthalate metabolites vary by race/ethnicity and family income for women ages 16 to
49 years is presented in the supplemental data tables for this indicator. Data tables also display
the 95th percentile levels of phthalate metabolites and how median levels of phthalate
metabolites vary by race/ethnicity, family income and age for children ages 6 to 17 years.
NHANES only provides phthalate metabolite data for children ages 6 years and older, which
means that the indicator is not able to capture the exposure of premature infants, some of
whom may have high levels of phthalate exposure due to the use of medical equipment
containing phthalates; or young children, whose play and mouthing behaviors may increase
their exposure to phthalates in toys and house dust.
Please see the Introduction to the Biomonitoring section for an explanation of the terms
"median" and "95th percentile," a description of the race/ethnicity and income groups used in
the ACES biomonitoring indicators, and information on the statistical significance testing
applied to these indicators.
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Phthalates | Biomonitoring
Indicator B9
Phthalate metabolites in women ages 16 to 49 years: Median concentrations
in urine, 1999-2008
1999-
2000
2001-
2002
2003-
2004
2005-
2006
2007-
2008
0
Metabolites of
Metabolites of
Metabolite of
BBzP
Data: Centers for Disease Control and Prevention, National Center for Health Statistics
and National Center for Environmental Health, National Health and Nutrition Examination Survey
Note: To reflect exposures to women who are pregnant or may become pregnant, the estimates
are adjusted for the probability (by age and race/ethnicity) that a woman gives birth.
America's Children and the Environment, Third Edition
0 The estimate is not reported because the metabolites MEOHP and MEHHP were not measured in 1999-2000.
Data characterization
Data for this indicator are obtained from an ongoing continuous survey conducted by the National Center
for Health Statistics.
Survey data are representative of the U.S. civilian noninstitutionalized population.
Phthalate metabolites are measured in urine samples obtained from individual survey participants.
• From 2001-2002 to 2007-2008, the median level of DEHP metabolites in urine of women
ages 16 to 49 years varied between 41 u.g/L and 51 u.g/L, and was 51 u.g/L in 2007-2008.
There was no statistically significant trend in median DEHP metabolites over 2001-2002 to
2007-2008.
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From 1999-2000 to 2007-2008, the median level of DBF metabolites in urine of women
ages 16 to 49 years varied between 27 u.g/L and 36 u.g/L, and was 36 u.g/L in 2007-2008.
From 1999-2000 to 2007-2008, the median level of BBzP metabolites in urine of women
ages 16 to 49 years varied between 10 u.g/L and 14 u.g/L, and was 12 u.g/L in 2007-2008.
From 2001-2002 to 2007-2008, the concentration of DEHP metabolites in the 95th
percentile varied between 462 u.g/L and 578 u.g/L, and was 567 u.g/L in 2007-2008. There
was an increasing trend in the 95th percentile concentration of DBF metabolites in women
of child-bearing age, from 128 u.g/L in 2001-2002 to 160 u.g/L in 2007-2008. From 1999-
2000 and 2007-2008, the concentration of BBzP metabolite varied between 68 u.g/L and
100 u.g/L, and was 70 u.g/L in 2007-2008. (See Table B9a.)
• The increasing trend for DBF metabolites at the 95th percentile from 2001-2002 to
2007-2008 was statistically significant after accounting for differences by age,
race/ethnicity, and income.
The concentrations of DEHP metabolites in the 95th percentile ranged from 10 to 14 times
higher than the median levels presented in this graph. The concentrations of DBF
metabolites and BBzP metabolite in urine at the 95th percentile ranged from 4 to 7 times
higher than the median levels presented in this graph. (See Table B9 and B9a.)
For the years 2005-2008, Black non-Hispanic women of child-bearing age had higher
median concentrations of all the phthalate metabolites shown here compared with White
non-Hispanic women, Mexican-American women, and women of "All Other
Races/Ethnicities," although these differences were frequently not statistically significant.
(See Table B9b.)
Median levels of urinary phthalate metabolites varied by family income. Women living
below the poverty level had higher concentrations of phthalate metabolites in their urine
compared with women living at or above the poverty level. (See Table B9b.)
• The difference between income groups was statistically significant for the DBF
metabolites after accounting for differences by race/ethnicity or age profile above and
below poverty. The difference between income groups for the BBzP metabolite was
statistically significant before accounting for race/ethnicity and age. The difference
between income groups was not statistically significant for the DEHP metabolites.
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Phthalates | Biomonitoring
0 The estimate is not reported because the metabolites MEOHP and MEHHP were not measured in 1999-2000.
Data characterization
Data for this indicator are obtained from an ongoing continuous survey conducted by the National Center
for Health Statistics.
Survey data are representative of the U.S. civilian noninstitutionalized population.
Phthalate metabolites are measured in urine samples obtained from individual survey participants.
From 2001-2002 to 2007-2008, the median level of DEHP metabolites in urine of children
ages 6 to 17 years varied between 45 u.g/L and 62 u.g/L, and was 45 u.g/L in 2007-2008.
From 1999-2000 to 2007-2008, the median level of DBF metabolites in urine of children
ages 6 to 17 years varied between 36 u.g/L and 42 u.g/L, and was 41 u.g/L in 2007-2008.
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The median level of BBzP metabolite in urine of children ages 6 to 17 years decreased from
25 u.g/L in 1999-2000 to 16 u.g/L in 2007-2008. This decreasing trend was statistically
significant.
At the 95th percentile, there was an increasing trend in the concentration of DEHP
metabolites in children, from 387 u.g/L in 1999-2000 to 564 u.g/L in 2007-2008. From 1999-
2000 to 2007-2008, the concentration of DBF metabolites varied between 166 u.g/L and
191 u.g/L, and was 191 u.g/L in 2007-2008. The concentration of BBzP metabolites varied
between 104 u.g/L and 151 u.g/L, and was 107 u.g/L in 2007-2008. (See Table BlOa.)
• The increasing trend for DEHP metabolites from 1999-2000 to 2007-2008 was
statistically significant.
Among children ages 6 to 17 years, the concentration of DEHP metabolites in urine at the
95th percentile ranged from 7 to 12 times higher than the median levels presented in this
graph. The concentrations of metabolites of DBP and BBzP in the 95th percentile ranged
from 4 to 7 times higher than the median levels. (See Table BIO and BlOa.)
Children living below the poverty level had higher median concentrations of DBP
metabolites detected in their urine compared with children living at or above the poverty
level. Median concentrations of DEHP metabolites and BBzP metabolite were similar among
children living below the poverty level and children living at or above the poverty level. (See
Table BlOb.)
• The difference between income groups for DBP metabolites was statistically significant.
For the years 2005-2008, Mexican-American children had lower median concentrations of
all the phthalate metabolites shown here compared with White non-Hispanic children and
Black non-Hispanic children. (See Table BlOb.)
• Testing for differences by race/ethnicity found that Mexican-American children had
statistically significantly lower median concentrations of phthalate metabolites as
follows: for DEHP and BBzP, lower than both White non-Hispanic and Black non-Hispanic
children; for DBP, lower than Black non-Hispanic children, and lower than White non-
Hispanic children after accounting for differences in age, sex, and income.
Children ages 6 to 10 years had higher median levels of phthalate metabolites in their urine
compared to adolescents ages 16-17 years. These differences were relatively small for DEHP
metabolites and DBP metabolites but greater for BBzP metabolite. (See Table BlOc.)
• The age group differences for BBzP were statistically significant.
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Bisphenol A (BPA) | Biomonitoring
Bisphenol A (BPA)
Bisphenol A (BPA) is a high-volume industrial chemical used in the production of epoxy resins
and polycarbonate plastics. Polycarbonate plastics may be encountered in many products,
notably food and drink containers, while epoxy resins are frequently used as inner liners of
metallic food and drink containers to prevent corrosion. The use of BPA in food contact
materials is regulated by the U.S. Food and Drug Administration.1'2 BPA also serves as a coating
on some types of thermal paper that are often used as receipts from cash registers, automatic
teller machines, and other similar devices. It is used in the polyvinyl chloride (PVC) industries as
well as in metal foundries where it is used to make casts and moldings. The primary route of
human exposure to BPA is believed to be through diet, when BPA migrates from food and drink
containers.3"5 Migration is more likely to occur when the container is heated or washed.5'6 Other
possible sources of BPA exposure include air, dust, water, and dental sealants.3'5
Biomonitoring studies demonstrate that BPA exposure is prevalent in the United States, with
detectable levels of BPA present in 93% of tested urine samples.7 Because BPA is metabolized
quickly in the body,8 the high frequency of detection indicates that exposures are occurring
regularly within the U.S. population. Exposures to BPA of infants and children up to age 6 years
are estimated to be greater than BPA exposures in older children and adults.3
Much of the scientific interest in BPA is related to published research suggesting that BPA may
be an endocrine disrupting chemical.9'10 Endocrine disrupters act by interfering with the
biosynthesis, secretion, action, or metabolism of naturally occurring hormones.9'11 Given the
importance of hormones in human physiology, there is concern in the scientific community
over the potential for endocrine disrupters to adversely affect children's health, particularly in
reproduction, early and adolescent development, and behavior.9 BPA is described as a "weakly
estrogenic" chemical, because its affinity for binding to estrogen receptors is approximately
10,000-fold weaker than natural estrogen.12
Recent attention to the developmental effects of BPA is based on several laboratory studies
and a better understanding of the mechanisms by which BPA exerts an estrogenic effect.10'13"15
In animal studies, exposure to high levels of BPA during pregnancy or lactation resulted in
reduced birth weight, slowed growth, reduced survival, and delayed time to the onset of
puberty in offspring.16"19 Animal studies have also found that low-dose BPA exposure was
associated with insulin resistance.20'21 In addition, one study found that low-dose BPA exposure
in pregnant animals was associated with symptoms similar to gestational diabetes, suggesting
that BPA exposures may have adverse effects in pregnant women.22 Other studies have found
relationships between prenatal or early-life BPA exposure and neurological effects as well as
the development of breast and prostate cancer in adult animals.23"25 The effects of low-dose
exposure to BPA in lab animals are debated within the scientific community, with some
researchers finding no developmental effects, while others have identified behavioral and
neural effects, abnormal urinary tract development, development of lesions in the prostate
gland, and early onset of puberty in females.3'23'26"36 Differences in reported results on the
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Biomonitoring | Bisphenol A (BPA)
timing of puberty between low and high dose studies may be a result of dose differences, study
design, or species of animal.3 Based on a critical review of the existing scientific literature, in
2008 the National Toxicology Program (NTP) determined that there was "some concern" (the
midpoint on a five-level scale ranging from "negligible" to "serious")1 for effects of BPA on the
brain, behavior, and prostate gland in fetuses, infants, and children; "minimal concern" for
effects on the mammary gland and onset of puberty in females; and "negligible concern" for
fetal or neonatal mortality, birth defects, or reduced birth weight and growth.3
Epidemiological data on the effects of BPA in human populations are limited. Studies of the U.S.
general population have reported that adults with higher recent BPA exposure (as represented
by urinary BPA concentrations) are more likely to have coronary heart disease, diabetes,
immune dysfunction, and liver enzyme abnormalities.37"39 Some of these associations are
postulated to be due to non-estrogenic effects of BPA,38 although there is limited
understanding of the mechanisms by which BPA exposure may lead to an adverse health effect.
Studies of workers in China reported an association between exposure to high levels of BPA and
an increased risk of self-reported sexual dysfunction,40'41 and that BPA exposure to pregnant
workers was associated with decreased offspring birthweight.42 A study of children in Ohio
reported an association between prenatal BPA exposure, at levels typical for the general
population, and aggression and hyperactivity in 2-year-old children.43 Similar associations
between behavioral effects and BPA exposure have been seen in animal studies.3'44'45 However,
another study of prenatal BPA exposure conducted in New York City found no association
between prenatal BPA exposure and social behavior deficits in children at ages 7 to 9 years.46 In
2009, the National Institutes of Health announced that it would spend $30 million over two
years to better understand the link between low-dose BPA exposure and human health effects.
Studies have shown that detectable levels of BPA are present in human urine samples from all
age groups including infants, toddlers, children and adults.3'47"52 BPA has been identified in the
blood of pregnant women,53 and also can cross the placenta, potentially exposing the fetus.54
Previous studies have identified higher levels of BPA in the urine of children ages 6 to 11 years
compared with adults,47'49'50 and found that consumption of soda and school lunches was also
associated with higher urinary BPA concentrations.50 Infants and young children also have a
higher estimated daily intake of BPA compared with adults.3'48 Although less information is
available on BPA levels in infants than in older children, one study found that premature infants
in intensive care units had greater urinary BPA concentrations than those observed in other
infants or even older children, though the route of exposure for the premature infants is
unclear.55 Some laboratory animal studies have found that younger animals are less effective at
metabolizing BPA than older animals are; while it has been proposed that such findings may
apply to human infants and developing fetuses, this hypothesis is debated in the scientific
literature.3'36'52'56"61 One important part of ongoing research is to better understand how BPA is
absorbed, distributed, metabolized, and excreted by the body, and how those processes change
with age and with route of exposure.56"58'60"62 Interpretation of these data will allow us to
1 More information on NTP concern levels is available at http://www.niehs.nih.gov/news/media/questions/sya-
bpa.cfm.
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Bisphenol A (BPA) | Biomonitoring
understand how environmental exposure equates to the internal dose routinely measured in
biomonitoring studies.
The two indicators that follow use the best nationally representative data currently available on
urinary BPA levels over time for women of child-bearing age and children. Indicator Bll
presents median and 95th percentile concentrations of BPA in urine for women ages 16 to 49
years. Indicator B12 presents median and 95th percentile concentrations of BPA in urine for
children ages 6 to 17 years.
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Biomonitoring | Bisphenol A (BPA)
Indicator Bll: Bisphenol A in women ages 16 to 49 years: Median and 95th percentile
concentrations in urine, 2003-2010
Indicator B12: Bisphenol A in children ages 6 to 17 years: Median and 95th percentile
concentrations in urine, 2003-2010
About the Indicators: Indicators Bll and B12 present concentrations of bisphenol A (BPA) in urine of
U.S. women ages 16 to 49 years and children ages 6 to 17 years. The data are from a national survey
that collects urine specimens from a representative sample of the population every two years, and
then measures the concentration of total BPA in the urine. Indicator Bll presents concentrations of
BPA in women's urine over time and Indicator B12 presents concentrations of BPA in children's urine
over time. The focus on both women of child-bearing age and children is based on concern for
potential adverse effects in children born to women who have been exposed to BPA and in children
exposed to BPA.
NHANES
The National Health and Nutrition Examination Survey (NHANES) provides nationally
representative biomonitoring data for BPA. NHANES is designed to assess the health and
nutritional status of the civilian noninstitutionalized U.S. population and is conducted by the
National Center for Health Statistics, part of the Centers for Disease Control and Prevention
(CDC). Interviews and physical examinations are conducted with approximately 10,000 people
in each two-year survey cycle. CDC's National Center for Environmental Health measures
concentrations of environmental chemicals in blood and urine samples collected from NHANES
participants. Summaries of the measured values for more than 200 chemicals are provided in
the Fourth National Report on Human Exposure to Environmental Chemicals.63
Bisphenol A and its Metabolites
Indicators Bll and B12 present urinary levels of BPA in women of child-bearing age and
children. The reported measurements of BPA in urine represent "total BPA," which includes
both free BPA and non-estrogenic metabolites of BPA (only free BPA is considered active based
on measures of estrogenicity). Measured levels in the U.S. population may be composed
predominantly of these metabolites,64 but total BPA levels reflect previous exposure to the
biologically active form of BPA and there is debate in the scientific community over the
potential for conversion of non-estrogenic metabolites back to free BPA in various tissues.65
Recent work has also highlighted the potential for conversion of non-estrogenic metabolites of
BPA to the active form when crossing the placenta, increasing the relevance of total BPA
measurements to children's health.54'66 All values are reported as micrograms of BPA per liter of
urine (u.g/L).
Concentrations of BPA in urine have been measured in a representative subset of NHANES
participants ages 6 years and older beginning with the 2003-2004 survey cycle. In 2009-2010,
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Bisphenol A (BPA) | Biomonitoring
NHANES collected BPA biomonitoring data for 2,749 individuals ages 6 years and older,
including 608 women ages 16 to 49 years and 727 children ages 6 to 17 years. BPA was
detected in about 90% of all individuals sampled. The frequency of BPA detection was 92% in
women ages 16 to 49 years," and 92% in children ages 6 to 17 years. The median and 95th
percentile BPA levels in urine for all NHANES participants in 2009-2010 were 2 u.g/L and 10
u.g/L, respectively. The widespread detection of BPA, combined with the fact that BPA has a
short half-life, indicates that BPA exposure is widespread and relatively continuous.
Individual Variability in Urinary Measurements
NHANES data for BPA are based on measurements made using a single urine sample for each
person surveyed. Due to normal changes in an individual's urinary output throughout the day,
this variability in urinary volume, among other factors related to the measurement of chemicals
that do not accumulate in the body,67 may mask differences between individuals in levels of
BPA. Since BPA does not appear to accumulate in bodily tissues, the distribution of NHANES
urinary BPA levels may overestimate high-end exposures (e.g., at the 95th percentile) as a result
of collecting one-time urine samples.8'68'69 Many studies account for differences in hydration
levels by reporting the chemical concentration per gram of creatinine. Creatinine is a byproduct
of muscle metabolism that is excreted in urine at a relatively constant rate, independent of the
volume of urine, and can in some circumstances partially account for the measurement
variability due to changes in urinary output.70 However, urinary creatinine concentrations differ
significantly among different demographic groups, and are strongly associated with an
individual's muscle mass, age, sex, diet, health status (specifically renal function), body mass
index, and pregnancy status.71'72 Thus, these indicators present the unadjusted BPA
concentrations so that any observed differences in concentrations between demographic
groups are not due to differences in creatinine excretion rates. These unadjusted urinary levels
from a single sample may either over- or underestimate urinary levels for a sampled individual.
However, for a representative group, it can be expected that a median value based on single
samples taken throughout the day will provide a good approximation of the median for that
group. Furthermore, due to the large number of subjects surveyed, we expect that differences
in the concentrations of BPA that might be attributed to the volume of the urine sample would
average out within and across the various comparison groups.
Birth Rate Adjustment
Indicator Bll uses measurements of BPA in urine of women ages 16 to 49 years to represent
the distribution of BPA exposures to women who are pregnant or may become pregnant.
However, women of different ages have a different likelihood of giving birth. For example, in
2003-2004, women aged 27 had a 12% probability of giving birth, and women aged 37 had a
4% probability of giving birth.73 A birth rate-adjusted distribution of women's BPA levels is used
1 The percentage for women ages 16 to 49 years is calculated with the birth rate adjustment described below.
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Biomonitoring | Bisphenol A (BPA)
in calculating this indicator,1" meaning that the data are weighted using the age-specific
probability of a woman giving birth.74
Data Presented in the Indicators
Indicators Bll presents median and 95th percentile concentrations of BPA in urine over time for
women ages 16 to 49 years, using NHANES data from 2003-2010.
Indicator B12 presents median and 95th percentile concentrations of BPA in urine overtime for
children ages 6 to 17 years, using NHANES data from 2003-2010.
Additional information showing how the median and 95th percentile levels of BPA in urine vary
by race/ethnicity and family income for women ages 16 to 49 years is presented in
supplemental data tables for these indicators. Data tables also display information showing
how the median and 95th percentile levels of BPA in urine vary by race/ethnicity, family income,
and age for children ages 6 to 17 years.
Please see the Introduction to the Biomonitoring section for an explanation of the terms
"median" and "95th percentile," a description of the race/ethnicity and income groups used in
the ACES biomonitoring indicators, and information on the statistical significance testing
applied to these indicators.
111 There may be multiple ways to implement an adjustment to the data that accounts for birth rates by age. The
National Center for Health Statistics has not fully evaluated the method used in ACE, or any other method
intended to accomplish the same purpose, and has not used any such method in its publications. NCHS and EPA
are working together to further evaluate the birth rate adjustment method used in ACE and alternative methods.
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Bisphenol A (BPA) | Biomonitoring
Indicator Bll
Bisphenol A in women ages 16 to 49 years: Median and 95th percentile
concentrations in urine, 2003-2010
3- 16
95th percentile
Median
2007-
2008
Data: Centers for Disease Control and Prevention, National Center for Health Statistics
and National Center for Environmental Health, National Health and Nutrition Examination Survey
Note: To reflect exposures to women who are pregnant or may become pregnant, the estimates
are adjusted for the probability (by age and race/ethnicity) that a woman gives birth.
America's Children and the Environment, Third Edition
Data characterization
Data for this indicator are obtained from an ongoing continuous survey conducted by the National Center
for Health Statistics.
Survey data are representative of the U.S. civilian noninstitutionalized population.
BPA is measured in urine samples obtained from individual survey participants.
From 2003-2004 to 2009-2010, the median concentration of BPA in urine among women
ages 16 to 49 years varied between2 u.g/L and 3 u.g/L. There was no statistically significant
trend in median BPA levels over the years shown.
From 2003-2004 to 2009-2010, the concentrations of BPA in urine at the 95th percentile
varied between 10 u.g/L and 16 u.g/L, and was 10 u.g/L in 2009-2010. There was no
statistically significant trend in 95th percentile concentrations of BPA over the years shown.
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Biomonitoring | Bisphenol A (BPA)
Between 2003-2004 and 2009-2010, the concentrations of BPA in the 95th percentile
ranged from 5 to 6 times the median levels for women ages 16 to 49 years.
In 2007-2010, the median concentration of BPA in urine of Black non-Hispanic women was
about 4 u.g/L, which was higher than the median concentrations in White non-Hispanic
women, Mexican-American women, and women of "All Other Races/Ethnicities." The
differences between Black non-Hispanic women and women in other race/ethnicity groups
were statistically significant. (See Table Blla.)
Women living below the poverty level had higher median concentrations of BPA in urine
than those living at or above poverty level, a difference that was statistically significant. (See
Table Blla.)
Among White non-Hispanic women and women of "All Other Races/Ethnicities," those with
family incomes below poverty level had higher median concentrations of BPA in urine than
those at or above poverty level. The differences between the income groups were
statistically significant. (See Table Blla.)
Higher concentrations of BPA were observed in the urine of women below the poverty level
at the 95th percentile (15 u.g/L) compared with women at or above the poverty level
(11 u.g/L). This difference was statistically significant after adjustment for differences in age
and race/ethnicity. (See Table Bllb.)
White non-Hispanic women at the 95th percentile (10 u.g/L) had lower concentrations of
BPA in urine than Black non-Hispanic women (15 u.g/L) and Mexican-American women
(15 u.g/L). These differences were statistically significant after adjustment for differences in
age and income. (See Table Bllb.)
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Bisphenol A (BPA) | Biomonitoring
Data characterization
Data for this indicator are obtained from an ongoing continuous survey conducted by the National Center
for Health Statistics.
Survey data are representative of the U.S. civilian noninstitutionalized population.
BPA is measured in urine samples obtained from individual survey participants.
i Among children ages 6 to 17 years, the median concentration of BPA in urine of children
ages 6 to 17 years decreased from 4 u.g/L in 2003-2004 to 2 u.g/L in 2009-2010. The
concentration of BPA in urine at the 95th percentile decreased from 16 u.g/L in 2003-2004 to
10 u.g/L in 2009-2010. These decreasing trends were statistically significant.
i Between 2003-2004 and 2009-2010, the concentrations of BPA in the 95th percentile
ranged from 4 to 7 times the median levels for children ages 6 to 17 years.
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In 2007-2010, median concentrations of BPA in urine of Black non-Hispanic children ages 6
to 17 years were higher than in White non-Hispanic children, Mexican-American children,
and children of "All Other Races/Ethnicities." These differences were statistically significant.
(See Table B12a.)
BPA concentrations at the 95th percentile were similar for Black non-Hispanic, White-non
Hispanic, and Mexican-American children ages 6 to 17 years in 2007-2010. (See Table B12b.)
In 2007-2010, BPA concentrations were similar for age groups 6 to 10 years, 11 to 15 years,
and 16 to 17 years, both at the median and at the 95th percentile. (See Table B12c.)
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Perchlorate | Biomonitoring
Perchlorate
Perchlorate is a naturally occurring and man-made chemical that is used to manufacture
fireworks, explosives, flares, and rocket fuel.1'2 It is found naturally in groundwater and soils
throughout many regions in the United States and other arid regions of the world.3'4
Perchlorate is presumed to migrate into groundwater during the process of irrigation,5 and has
also been found in groundwater supplies near military and industrial facilities where
perchlorate was used.6 Perchlorate has been detected in surface water; dairy products; and in
some food crops, including lettuce, spinach, grapes, carrots, tomatoes, and other fruits and
vegetables, produced in the United States and internationally.5'7"12 Perchlorate has been
detected in some fertilizers produced in Chile; however, fertilizers appear to be a negligible
source of perchlorate in the United States.1'13"17 The numerous sources of perchlorate located
across the United States result in widespread exposures of perchlorate to the U.S. population.3'4
Perchlorate has been detected in human breast milk, urine, blood, amniotic fluid, and saliva.18"
23 A national study representative of the U.S. population ages 6 years and older found
perchlorate in the urine of 100% of the more than 5,000 people sampled; children had higher
median urinary levels compared with those of adults, including women of child-bearing age.3'24
Infants are exposed to perchlorate through both breast milk and formula, but those who are
fed breast milk may have higher exposures to perchlorate compared with those who are fed
cow- or soy-based formula.25 When comparing perchlorate doses (daily intakes per kilogram of
body weight, estimated from urine samples), infants less than 2 months of age experience
higher perchlorate doses compared with older infants, and estimated doses of perchlorate in
infants are more than twice as high as estimated doses for adults.3'25'26 A study conducted in
China found that blood samples of infants less than 1 year of age have higher mean perchlorate
values than blood samples of both older children and adults.27'28
Children might be directly exposed to perchlorate through perchlorate-contaminated water and
foods containing perchlorate. Surveys conducted by the U.S. Food and Drug Administration
have detected varying levels of perchlorate in many foods that may be consumed by both
women and young children. The surveys, conducted in 22 states, tested 27 different types of
food products and found the highest levels of perchlorate in spinach and tomatoes.12 Some
infant formulas have also been found to contain perchlorate, and the perchlorate content of
the formula is increased if it is prepared with perchlorate-contaminated water.29"32 However,
computer modeling studies have concluded that exposure to perchlorate from food
consumption is much greater than exposure from drinking water in the United States.33'34 These
modeled predictions are consistent with empirical studies that attribute the majority of
perchlorate intake dose in U.S. residents to food consumption.8'35"37
Exposure to high doses of perchlorate has been shown to block the uptake of iodide into the
thyroid gland.38'39 Exposure to perchlorate and other thyroid-disrupting chemicals is of
particular concern for women of child-bearing age, because thyroid hormones are important
for growth and development of the central nervous system in fetuses and infants.1'40"42 The
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Biomonitoring | Perchlorate
transfer of iodide from blood into the thyroid gland is an essential step in the synthesis of
thyroid hormones that regulate how the body uses energy; influence bone growth; and
influence the development of the brain, reproductive, and cardiovascular systems.43 When this
transfer of iodide into the thyroid gland is blocked, the thyroid may not have enough iodide to
make thyroid hormones. Reduction in a woman's thyroid hormone levels during the first and
second trimester puts the fetus at risk for impaired physical and mental development, with the
severity of the impairment depending upon the degree of hormone deficiency.40'41 Moderate
deficits in maternal thyroid hormone levels during early pregnancy have been linked to reduced
childhood IQ scores and other neurodevelopmental effects, as well as unsuccessful or
complicated pregnancies.44 Prenatal and newborn hypothyroidism (low thyroid hormone levels)
is a risk factor for intellectual disability (mental retardation) and other forms of impaired
neurodevelopment.45 In 2005-2008, approximately 38% of women ages 15 to 44 years in the
United States had insufficient iodine intake,46 potentially increasing the risk for effects on fetal
development from exposure to perchlorate.1
Associations between perchlorate exposure and thyroid hormones have been based on both
epidemiological and animal-based studies. Animal studies have shown that exposure to high
doses of perchlorate result in decreased thyroid hormone levels and physical alterations to the
thyroid gland,1 and have also found that these effects of perchlorate can be enhanced with
exposure to other chemicals that block uptake of iodide.47 In 2005, the National Research
Council (NRC) concluded that the available epidemiological evidence concerning non-medical
exposure to perchlorate did not indicate an association with thyroid disorders in adults or
infants, and was inadequate for assessing the potential for adverse associations between
prenatal perchlorate exposure and adverse neurodevelopmental outcomes in children.1 The
NRC also indicated that there was a lack of studies to evaluate potential effects of prenatal
perchlorate exposures in infants and children, particularly in vulnerable populations.1
Some further epidemiological research has been conducted since the NRC report was
completed. A study of urinary perchlorate and thyroid hormone levels in more than 11,000 U.S.
females ages 12 years and older in 2001-2002 found that increasing levels of perchlorate in
urine were associated with decreased thyroid hormone levels.26 Further analysis of this data set
found that tobacco smoke and perchlorate may interact to affect thyroid function at commonly
occurring perchlorate levels.48 In contrast, a study of first-trimester pregnant women identified
as iodine-deficient, and a long-term exposure study of women in early pregnancy and late
pregnancy in Chile, found that exposure to low levels of perchlorate did not result in decreased
levels of thyroid hormones.49'50
Other studies have evaluated relationships between drinking water perchlorate levels and
thyroid hormone levels in newborns. A study of California infants born in 1998 reported that
babies born to mothers in communities with higher drinking water perchlorate levels were
more likely to have elevated levels of thyroid stimulating hormone, which is an indication of
reduced thyroid hormone levels.51 An earlier study of the same population and other studies
have not found associations between drinking water perchlorate levels and neonatal thyroid
hormone function.50'52"56
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Perchlorate | Biomonitoring
In January 2009, EPA issued an interim health advisory level to help state and local officials
manage local perchlorate contamination issues in a health-protective manner, in advance of a
final EPA regulatory determination.2'57 In February 2011, EPA decided to develop a federal
drinking water standard for perchlorate, based on the concern for effects on thyroid hormones
and the development and growth of fetuses, infants, and children.2'58 The process for
developing the standard will include receiving input from key stakeholders as well as submitting
any formal rule to a public comment process. California and Massachusetts have both set their
own standards for perchlorate in drinking water.59 No standards exist for perchlorate in food.
The indicator that follows uses the best nationally representative data currently available on
urine perchlorate levels over time for women of child-bearing age. Indicator B13 presents
median and 95th percentile urinary perchlorate levels for women ages 16 to 49 years.
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Indicator B13: Perchlorate in women ages 16 to 49 years: Median and 95th percentile
concentrations in urine, 2001-2008
About the Indicators: Indicator B13 presents concentrations of perchlorate in urine of U.S. women
ages 16 to 49 years. The data are from a national survey that collects urine specimens from a
representative sample of the population every two years, and then measures the concentration of
perchlorate in the urine. The indicator presents concentrations of perchlorate in urine over time. The
focus on women of child-bearing age is based on concern for potential adverse effects in children
born to women who have been exposed to perchlorate.
NHANES
The National Health and Nutrition Examination Survey (NHANES) provides nationally
representative biomonitoring data for perchlorate. NHANES is designed to assess the health
and nutritional status of the civilian noninstitutionalized U.S. population and is conducted by
the National Center for Health Statistics, part of the Centers for Disease Control and Prevention
(CDC). Interviews and physical examinations are conducted with approximately 10,000 people
in each two-year cycle. CDC's National Center for Environmental Health measures
concentrations of environmental chemicals in blood and urine samples collected from NHANES
participants. Summaries of the measured values for more than 200 chemicals are provided in
the Fourth National Report on Human Exposure to Environmental Chemicals.24
Perchlorate
Indicator B13 presents urinary levels of perchlorate in women of child-bearing age. Perchlorate
passes quickly through the body unchanged and is excreted in urine, with an elimination half-
life on the order of hours.3 Therefore, perchlorate measured in humans is indicative of recent
exposures. All values are reported as micrograms of perchlorate per liter of urine (u.g/L).
Concentrations of perchlorate in urine have been measured in a representative subset of
NHANES participants ages 6 years and older in 2001-2002 and 2003-2004, and in all NHANES
participants ages 6 years and older in 2005-2006 and 2007-2008.19
For 2007-2008, NHANES collected perchlorate biomonitoring data for 7,629 individuals ages 6
years and older, including 1,608 women ages 16 to 49 years. Perchlorate was detected in 100%
of the individuals sampled in NHANES 2007-2008. The median and 95th percentile of urinary
perchlorate levels for all NHANES participants in 2007-2008 were 4 u.g/L and 17 u.g/L,
respectively. The widespread detection of perchlorate, combined with the fact that perchlorate
has a short half-life, indicates that perchlorate exposure is widespread and relatively continuous.
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Perchlorate | Biomonitoring
Individual Variability in Urinary Measurements
NHANES data for perchlorate are based on measurements made using a single urine sample for
each person surveyed. Due to normal changes in an individual's urinary output throughout the
day, this variability in urinary volume, among other factors related to the measurement of
chemicals that do not accumulate in the body,60 may mask differences between individuals in
levels of perchlorate. Since perchlorate does not appear to accumulate in bodily tissues, the
distribution of NHANES urinary perchlorate levels may over estimate high-end exposures (e.g.,
at the 95th percentile) as a result of collecting one-time urine samples.34'61'62 Many studies
account for differences in hydration levels by reporting the chemical concentration per gram of
creatinine. Creatinine is a byproduct of muscle metabolism that is excreted in urine at a
relatively constant rate, independent of the volume of urine, and can in some circumstances
partially account for the measurement variability due to changes in urinary output.63 However,
urinary creatinine concentrations differ significantly among different demographic groups, and
are strongly associated with an individual's muscle mass, age, sex, diet, health status
(specifically renal function), body mass index, and pregnancy status.64'65 Thus, this indicator
presents the unadjusted perchlorate concentrations so that any observed differences in
concentrations between demographic groups are not due to differences in creatinine excretion
rates. These unadjusted urinary levels from a single sample may either over- or underestimate
urinary levels for a sampled individual. However, for a representative group, it can be expected
that a median value based on single samples taken throughout the day will provide a good
approximation of the median for that group. Furthermore, due to the large number of subjects
surveyed, we expect that differences in the concentrations of perchlorate that might be
attributed to the volume of the urine sample would average out within and across the various
comparison groups.
Birth Rate Adjustment
Indicator B13 uses measurements of perchlorate in urine of women ages 16 to 49 years to
reflect the potential distribution of perchlorate exposures to women who are pregnant or may
become pregnant. However, women of different ages have a different likelihood of giving birth.
For example, in 2003-2004, women aged 27 years had a 12% annual probability of giving birth,
and women aged 37 years had a 4% annual probability of giving birth.66 A birth rate-adjusted
distribution of women's perchlorate levels is used in calculating this indicator,1 meaning that the
data are weighted using the age-specific probability of a woman giving birth.67
1 There may be multiple ways to implement an adjustment to the data that accounts for birth rates by age. The
National Center for Health Statistics has not fully evaluated the method used in ACE, or any other method
intended to accomplish the same purpose, and has not used any such method in its publications. NCHS and EPA
are working together to further evaluate the birth rate adjustment method used in ACE and alternative methods.
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Biomonitoring | Perchlorate
Data Presented in the Indicator
Indicator B13 presents median and 95th percentile concentrations of perchlorate in urine over
time for women ages 16 to 49 years, using NHANES data from 2001-2008.
Additional information showing how the median and 95th percentile levels of perchlorate in
urine vary by race/ethnicity and family income for women ages 16 to 49 years is presented in
supplemental data tables for these indicators. Data tables also display information on the
median and 95th percentile levels of perchlorate in urine for children ages 6 to 17 years,
including how levels vary by race/ethnicity, family income, and age.
NHANES does not collect urine samples from children less than 6 years of age, and thus cannot
assess the exposure of infants, who may be exposed to unhealthy levels of perchlorate due to
the presence of perchlorate in breast milk and some infant formula.18'20'21'31'32
Please see the Introduction to the Biomonitoring section for an explanation of the terms
"median" and "95th percentile," a description of the race/ethnicity and income groups used in
the ACES biomonitoring indicators, and information on the statistical significance testing
applied to these indicators.
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Perchlorate | Biomonitoring
Indicator B13
Perchlorate in women ages 16 to 49 years: Median and 95th percentile
concentrations in urine, 2001-2008
95th percentile*
Median
Data: Centers for Disease Control and Prevention, National Center for Health Statistics
and National Center for Environmental Health, National Health and Nutrition Examination Survey
Note: To reflect exposures to women who are pregnant or may become pregnant, the estimates
are adjusted for the probability (by age and race/ethnicity) that a woman gives birth.
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*The 95* percentile concentration for 2003-2004 is not reported because it has large uncertainty: the relative standard error,
RSE, is 40% or greater (RSE = standard error divided by the estimate).
Data characterization
Data for this indicator are obtained from an ongoing continuous survey conducted by the National Center
for Health Statistics.
Survey data are representative of the U.S. civilian noninstitutionalized population.
Perchlorate is measured in urine samples obtained from individual survey participants.
From 2001-2002 to 2007-2008, the median level of perchlorate in urine among women
ages 16 to 49 years was 3 u.g/L with little variation over time. Over the same period, the 95th
percentile varied between 13 and 17 u.g/L.
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Biomonitoring | Perchlorate
In 2005-2008, there was little variation in median or 95th percentile perchlorate levels by
race/ethnicity or income among women ages 16 to 49 years. (See Tables B13a and B13b.)
From 2001-2002 to 2007-2008, the median level of perchlorate among children ages 6 to 17
years was 5 u.g/L with little variation over time. The 95th percentile perchlorate level among
children increased from 15 u.g/L in 2001-2002 to 19 u.g/L in 2007-2008. (See Table B13c.)
• The increasing trend in children's 95th percentile perchlorate levels was statistically
significant.
The median perchlorate level among children ages 6 to 17 years was about 42% higher than
the level found in women of childbearing age in 2005-2008, while the 95th percentile level
among children ages 6 to 17 years was about 19% higher than in women of childbearing
age. (See Tables B13 and B13c.)
Differences in urinary perchlorate levels by race/ethnicity and income among children ages
6 to 17 years were relatively limited. (See Tables B13d and B13e.)
There were minimal differences in urinary perchlorate levels by age group among children
ages 6 to 17 years. (See Table B13f.)
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Health I Introduction
Introduction
Why is EPA tracking children's health outcomes in America's Children and the
Environment!
The central goal of efforts to protect children's environmental health is the reduction of
disease, disability, and mortality. Many different factors contribute to children's health,
including nutrition, prenatal and childhood exposure to toxins in the environment, genetics,
socioeconomic status, access to medical care, and exercise. Data on children's health outcomes
can provide important information about changes over time and differences between
demographic groups. In particular, monitoring children's health outcomes for which causes are
unknown or not well established can help stimulate hypotheses, some of which may point to
environmental factors, which then can be examined rigorously in future studies.
What health outcomes are included in America's Children and the
Environment, Third Edition (ACE3)7
Health outcomes were selected for ACES based on: (1) magnitude of prevalence and/or trend in
prevalence, and severity of health outcome; (2) research findings that indicate environmental
contaminants or characteristics may be contributing factors; and (3) the availability of
nationally representative data suitable for constructing an indicator. EPA obtained input from
its Children's Health Protection Advisory Committee to assist in selecting topics from among the
many diseases and health disorders that affect children. The ACES Health indicators address the
following topics:
• Respiratory diseases
• Childhood cancer
• Neurodevelopmental disorders
• Obesity
• Adverse birth outcomes
What data sources were used to develop the Health indicators?
Data for all of the selected health outcomes, with the exception of childhood cancer, were
based on surveys and registries conducted/maintained by the National Center for Health
Statistics (NCHS). These include the National Health Interview Survey (NHIS), National Hospital
Ambulatory Medical Care Survey (NHAMCS), National Hospital Discharge Survey (NHDS),
National Health and Nutrition Examination Survey (NHANES), and the National Vital Statistics
System (NVSS). Data on childhood cancer were obtained from the National Cancer Institute's
Surveillance, Epidemiology, and End Results (SEER) Program.
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Introduction | Health
NHIS and NHANES collect health information from a probability sample of the U.S. civilian,
noninstitutionalized population, and survey data are weighted to yield national estimates
describing this population. NHAMCS and NHDS collect patient visit information from a sample
of hospitals, and the survey data are weighted to estimate the rates of respiratory-related
emergency room visits and hospital admissions in the United States. NVSS is a registry that
captures virtually all births that occur in the United States, and thus does not rely on sampling.
The SEER program has attributes of both a survey and a registry. It is based on a collection of
registries located across the United States that record all tumors that occur in specific
geographical regions. The registry information is then used to estimate the occurrence of
cancer, including childhood cancer, for the entire country.
What can we learn from the Health indicators?
The indicators presented in this report focus on health outcome data collected over multiple
years, which allow determination of whether the reported prevalence or rate of each outcome
is increasing, decreasing, or not changing over time. An additional focus is whether particular
groups (defined by race/ethnicity and income) within the population are disproportionately
affected by a given health outcome. Such trends and comparisons can generate hypotheses and
help identify opportunities for future action.
The topic text provided before the indicators reviews the scientific evidence regarding
environmental factors and other factors contributing to the disease or disorder, providing
context that informs the interpretation of the indicators. For some of the selected health
outcomes, the scientific evidence suggests that environmental contaminants may play a role in
the development of the disease or disorder. For other health outcomes, available evidence is
less clear as to whether environmental contaminants are involved. The inclusion of the selected
health outcomes in this report does not imply that environmental contaminants or other
environmental factors definitely play a role in the selected health outcomes. It can be very
difficult to develop conclusive evidence that environmental factors cause or contribute to the
incidence of childhood health effects, and research is ongoing. Where available, we rely on
authoritative reviews of the literature and report their conclusions regarding the strength of
the evidence for a causal role of specific environmental factors in the development of childhood
diseases and disorders. When such reviews are unavailable, we summarize important findings
from individual studies that address the potential role of environmental factors in contributing
to an effect.
Furthermore, the inclusion of the selected health outcomes in this report does not imply that
environmental factors, in cases where they do play a role, are the only cause of the disease or
disorder. Most often, health outcomes are a result of multiple causes that may include genetics,
nutrition, and socioeconomic factors, as well as prenatal and childhood exposure to
environmental contaminants, and other environmental factors. The various factors may also
interact, such as a genetic predisposition that makes a person more susceptible to the effects of
an environmental exposure.
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Health I Introduction
In some instances, the indicators show that the prevalence of a health outcome is increasing
while important environmental exposures are decreasing. Although this could suggest that the
environmental exposures addressed in the indicators are unrelated to the health outcomes
being measured, it could also result from a lag between environmental improvements and
changes in related health outcomes, or changes in other important environmental exposures
that are not currently measured by the indicators in the report. The Health indicators are
therefore not intended as a basis for concluding that an environmental factor is or is not related
to a particular children's health outcome.
What information is provided for each Health topic?
An introduction section explains the relevance of the topic to children's environmental health,
including a description of the health outcomes and a discussion of evidence indicating or
suggesting that environmental agents may play a role in contributing to the outcomes. The
introduction is followed by a description of the indicators, including a summary of the data
available and brief information on how each indicator was calculated. Two to four indicators,
each a graphical presentation of the available data, are included for each topic. All Health topics
include an indicator that presents a time series. Some of the topics also include indicators that
show a comparison of the most current health outcome data by race/ethnicity and income
level. Beneath each figure are explanatory bullet points describing dataset characteristics and
key findings presented in the figure, along with key data from any supplemental data tables.
References are provided for each topic at the end of the report.
Data tables are provided in Appendix A. The tables include all indicator values depicted in the
indicator figures, along with additional data of interest not shown in the figures. Metadata
describing the data sources are provided in Appendix B. Documents providing details of how
the indicators were calculated are available on the ACE website (www.epa.gov/ace).
Many of the topics presented in the Health indicators are addressed in Healthy People 2020,
which provides science-based, 10-year national objectives for improving the health of all
Americans. Appendix C provides examples of the alignment of the Health topics presented in
ACES with objectives in Healthy People 2020.
What race/ethnicity groups are used in reporting indicator values?
For each topic in the Health section, indicator values are provided for defined race/ethnicity
groups—either in the indicator figures or in the data tables. The race/ethnicity groups vary to
some extent across the indicators, depending on the extent to which the data support reporting
indicator values for specific race/ethnicity groups. Where possible, the Health indicators
provide data for the following races/ethnicities:
• White non-Hispanic
• Black non-Hispanic
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Introduction | Health
• Hispanic1
• Asian or Pacific Islander
• American Indian or Alaska Native
Specific races/ethnicities for which the data support stratified group analysis are described in
the text preceding each Health indicator.
What income groups are used in reporting indicator values?
For indicators presenting the prevalence of asthma, neurodevelopmental disorders, and
obesity, indicator values are presented for income groups defined on the basis of the federal
poverty level. Poverty level is defined by the federal government, and is based on income
thresholds that vary by family size and composition. In 2010, for example, the poverty
threshold was $22,113 for a household with two adults and two related children.1 These Health
indicators (in figures and/or data tables) provide data separately for individuals in families with
incomes below poverty level, and those in families with incomes at or above poverty level.
Further detail is provided in the data tables by dividing those above poverty level into two
groups: 100-200% of poverty level, and greater than 200% of poverty level. The category of
incomes between the poverty level and twice the poverty level (sometimes referred to as "near
poor") represents households that have relatively low incomes but are not below the officially
defined poverty level, and is frequently used by NCHS in its reporting of health data.
For indicators of respiratory emergency room visits and hospitalization, childhood cancer, and
adverse birth outcomes, no income group comparisons can be provided because income data
are not collected for these data sets.
How were the indicators calculated and presented?
Data files: The indicators were calculated from publicly available data files obtained from the
NCHS and SEER websites. The files include various information such as survey responses (NHIS),
diagnosis codes (NHAMCS and NHDS), type of cancer (SEER), gestational age and birth weight
(NVSS), and body measurements (NHANES). Depending on the data set, the files may also
include information on age, sex, race/ethnicity, and income level (that is, family income above
or below poverty level). For the survey data, each individual observation also has a sample
weight that is used in calculating population statistics; the weight equals the number of people
in the U.S. population represented by the particular observation.
1 For the Obesity indicators, values are provided for "Mexican-American" ethnicity rather than "Hispanic" ethnicity
because in all years up to 2006, NHANES was designed to provide statistically reliable estimates for Mexican-
Americans rather than all Hispanics. NHANES now oversamples Hispanics instead of Mexican-Americans, beginning
with NHANES 2007-2008.
Please see http://www.cdc.gov/nchs/nhanes/nhanes2007-2008/sampling_0708.htm/.
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Health I Introduction
Population age groups: The age groups covered by the indicators differ among the Health
topics. The indicators for respiratory diseases used data for children ages 17 years and younger.
The indicators for childhood cancer used data for children ages 19 years and younger. The
indicators for neurodevelopmental disorders used data for children ages 5 to 17 years. The
indicators for adverse birth outcomes used data ascertained at birth. The indicators for obesity
used data for children ages 2 to 17 years.
Calculated prevalence or rate of occurrence for each health outcome: Depending on the nature
of the available data, some of the indicators present prevalence data while others express the
occurrence of health outcomes as a rate. The main difference between these two measures is
that prevalence presents data occurring at one point in time. These prevalence measures are
proportions, such as the percentage of children who currently have asthma or the percentage of
children classified as obese. Rates, on the other hand, express the number of events, such as
emergency room visits, hospital admissions, new cancer cases, or cancer deaths, that occur over
a definite time period (one year for all of the ACES indicators), per the population at risk for the
event. The population at risk is either all children or all births, depending on the indicator.
Statistical considerations in presenting and characterizing the indicators: Statistical analysis has
been applied to the ACES Health indicators to evaluate trends over time in indicator values (for
example, percentage of children with asthma) or differences in indicator values between
demographic groups. These analyses use a 5% significance level, meaning that a conclusion of
statistical significance is made only when there is no more than a 5% probability that the
observed trend or difference occurred by chance (p < 0.05).
The statistical analysis of trends over time for an ACES Health indicator is dependent on how
the indicator values vary over time, the number of survey years included in the analysis, the
number of observations in each survey year, and various aspects of the survey design. The
evaluation of trends over time incorporates annual data from each year within the time period
reported. A finding of statistical significance for differences in indicator values between
demographic groups depends on the magnitude of the difference, the number of observations
in each group, and various aspects of the survey design. For example, if the prevalence of a
health effect is different between two groups, the statistical test is more likely to detect a
difference when data have been obtained from a larger number of people in those groups. It
should be noted that when statistical testing is conducted for differences among multiple
demographic groups (for example, considering both race/ethnicity and income level), the large
number of comparisons involved increases the probability that some differences identified as
statistically significant may actually have occurred by chance.
A finding of statistical significance is useful for determining that an observed trend or difference
was unlikely to have occurred by chance. However, a determination of statistical significance by
itself does not convey information about the magnitude of the increase, decrease, or difference
in indicator values. Furthermore, a lack of statistical significance means only that occurrence by
chance cannot be ruled out. Thus, a conclusion about statistical significance is only part of the
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information that should be considered when determining the public health implications of
trends or differences in indicator values.
In some cases, calculated indicator values have substantial uncertainty. Uncertainty in these
estimates is assessed by looking at the relative standard error (RSE), a measure of how large the
variability of the estimate is in relation to the estimate (RSE = standard error divided by the
estimate)." The estimate should be interpreted with caution if the RSE is at least 30%; a
notation is provided for such estimates in the indicator figures and tables. If the RSE is greater
than 40%, the estimate is considered to have very large uncertainty and is not reported.1"
" Standard errors for all Health indicator values are provided in a file available on the ACE website
(www.epa.gov/ace).
111 For respiratory emergency room and hospital visits (Indicator H3), an estimate is also considered to have very
large uncertainty and is not reported if it is based on fewer than 30 sampled visits. For obesity (Indicators H10 and
Hll), values are not reported if the RSE cannot be reliably estimated.
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Respiratory Diseases
Respiratory diseases and illness, such as asthma, bronchitis, pneumonia, allergic rhinitis, and
sinusitis, can greatly impair a child's ability to function and are an important cause of missed
school days and limitations of activities. Symptoms associated with both mild and more severe
manifestations of these respiratory conditions, such as cough, wheeze, congestion, chest pain,
shortness of breath, respiratory distress, and death in the most extreme cases, are responsible
for substantial morbidity and a large cost burden to families and society.
Outdoor and indoor air pollution can adversely affect children's respiratory health.1"7 Studies
have shown that air pollution can exacerbate existing respiratory conditions such as asthma
and upper airway allergies.1'8"10 Increasing evidence suggests that exposure to certain air
pollutants may contribute to the onset of asthma in children, although studies relating to the
exacerbation of pre-existing asthma are more prevalent because they are easier to conduct.11"13
Air pollution also increases a child's risk of developing respiratory infections, most likely by
causing inflammation and/or impaired immune response.14"16
EPA sets health-based National Ambient Air Quality Standards for six air pollutants.17 These
pollutants, referred to as criteria air pollutants, are particulate matter (PM), ground-level
ozone, nitrogen oxides, sulfur oxides, carbon monoxide (CO), and lead. Four of these pollutants
have extensive evidence linking them to respiratory diseases in children (PM, ground-level
ozone, nitrogen oxides, and sulfur oxides). The evidence for respiratory effects is weaker for
CO, and lead has not been linked to adverse respiratory outcomes.
PM is associated with significant respiratory problems in children, including aggravated asthma;
exacerbation of allergic symptoms; reduced growth of lung function; and increased hospital
admissions, emergency room visits, and doctor visits for respiratory diseases, especially in
children with lung diseases such as asthma.6 Particulate air pollution has also been associated
with respiratory-related infant mortality, even at relatively low PM levels that are commonly
experienced in the United States.18'19
Short-term exposure to ground-level ozone can cause a variety of respiratory health effects,
including airway inflammation; reduced lung function; increased susceptibility to respiratory
infection; and respiratory symptoms such as cough, wheezing, chest pain, and shortness of
breath.3'20'21 Ozone exposure can decrease the capacity to perform exercise and has been
associated with the aggravation of respiratory illnesses such as asthma and bronchitis, leading
to increased use of medication, absences from school, doctor and emergency department
visits, and hospital admissions.3 Studies have also found that long-term ozone exposure may
contribute to the development of asthma, especially among children with certain genetic
susceptibilities and children who frequently exercise outdoors.22"24
Nitrogen dioxide (N02) is an odorless gas that can irritate the eyes, nose, and throat, and can
cause shortness of breath. EPA has concluded that exposure to N02can lead to increased
respiratory illnesses and symptoms, more severe asthma symptoms, and an increase in the
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number of emergency department visits and hospital admissions for respiratory causes,
especially asthma.4
Short-term exposures of persons with asthma to elevated levels of sulfur dioxide (S02) while
exercising at a moderate level may result in breathing difficulties, accompanied by symptoms
such as wheezing, chest tightness, or shortness of breath. Studies also provide consistent
evidence of an association between short-term S02 exposure and increased respiratory
symptoms in children, especially those with asthma or chronic respiratory symptoms. Short-
term exposures to S02 have also been associated with respiratory-related emergency
department visits and hospital admissions, particularly for children.5
Exposure to CO reduces the capacity of the blood to carry oxygen, thereby decreasing the
supply of oxygen to tissues and organs such as the heart. Research suggests correlations
between CO exposure and the exacerbation of asthma; however, CO levels are highly
correlated with other combustion-related pollutants, especially in locations near roads. Few
analyses clearly distinguish the contributions of CO from those of the larger traffic-related air
pollutant mixture, thus it is uncertain whether the observed health effects are truly attributable
to CO or whether they are due to other co-occurring air pollutants.7'10'25
In addition to the criteria air pollutants, EPA regulates 187 hazardous air pollutants (HAPs) that
are known or suspected to cause serious health effects or adverse environmental effects. For
many of these pollutants, information on health effects is scarce. HAPs that may be of
particular concern for the induction and exacerbation of asthma include acrolein,
formaldehyde, nickel, and chromium.26 Acrolein has been identified as a HAP of particular
concern for possible respiratory effects at levels commonly found in outdoor air in the United
States.27"29 Acrolein can cause respiratory irritation in individuals who do not have asthma.30
Pollution from traffic-related sources, a mix of criteria air pollutants and HAPs, appears to pose
particular threats to a child's respiratory system. Many studies have found a correlation
between proximity to traffic (or to traffic-related pollutants) and occurrence of new asthma
cases or exacerbation of existing asthma and other respiratory symptoms, including reduced
growth of lung function during childhood.11"13'31"36 A report by the Health Effects Institute
concluded that living close to busy roads appears to be an independent risk factor for the onset
of childhood asthma. The same report also concluded that the evidence was "sufficient" to
infer a causal association between exposure to traffic-related pollution and exacerbations of
asthma in children.37 Some studies have suggested that traffic-related pollutants may
contribute to the development of allergic disease, either by affecting the immune response
directly or by increasing the concentration or biological activity of the allergens themselves.38"40
Children can also be exposed to air pollution inside homes, schools, and other buildings. Indoor
air pollutants from biological sources such as mold; dust mites; pet dander (skin flakes); and
droppings and body parts from cockroaches, rodents, and other pests or insects, can lead to
allergic reactions, exacerbate existing asthma, and have been associated with the development
of respiratory symptoms.1'41'42 Furthermore, the Institute of Medicine concluded that exposure
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to dust mites can cause asthma in susceptible children, and exposure to cockroaches may cause
asthma in young children.1
PM and N02, discussed previously as outdoor air pollutants, also pollute indoor air when they
are emitted from gas stoves, gas or oil furnaces, fireplaces, wood stoves, and kerosene or gas
space heaters. Indoor concentrations of these combustion byproducts can reach very high
levels in developing countries where solid fuels are used extensively for cooking and home
heating, but may also affect the respiratory health of children in developed countries, especially
during the winter when use of fireplaces and space heaters is more common.43 Environmental
tobacco smoke (ETS), also known as secondhand smoke, is an air pollutant mixture that
includes particles and N02 as well as thousands of other chemicals. The Surgeon General has
concluded that exposure to ETS causes sudden infant death syndrome (SIDS), acute lower
respiratory infection, ear problems, and more severe asthma in children. Smoking by parents
causes respiratory symptoms and slows lung growth in their children.2
A number of air pollutants emitted indoors by a variety of household items such as building
materials and home furnishings, recently dry-cleaned clothes, cleaning supplies, and room
deodorizers, have been associated with respiratory symptoms and may play a role in the
exacerbation or development of childhood asthma.44'45 A recent systematic review of seven
studies concluded that there is a significant association between exposure to formaldehyde—a
chemical released from particle board, insulation, carpet, and furniture—and self-reported or
diagnosed asthma in children.46
Air pollutants can enter the bloodstream of pregnant women and cross the placenta to reach the
developing fetus; thus the period of fetal development may be a window of special vulnerability
for respiratory effects of some air pollutants. Studies indicate that prenatal exposure to ETS may
increase the risk of developing asthma during childhood and/or lead to impaired lung function,
especially among children with asthma.2'47"50Studies have also found that prenatal exposure to
polycyclic aromatic hydrocarbons (hazardous air pollutants found in diesel exhaust, ETS, and
smoke from burning organic materials) is associated with childhood respiratory illnesses and the
development of asthma, particularly when in combination with prenatal or postnatal exposure
to ETS.51"53 Limited studies of prenatal exposure to criteria air pollutants have found that
exposure to PM, CO, and oxides of nitrogen and sulfur may increase the risk of developing
asthma as well as worsen respiratory outcomes among those children who do develop
asthma.11'54'55 However, it is difficult to distinguish the effects of prenatal and early childhood
exposure because exposure to air pollutants is often very similar during both periods.
Asthma
Asthma is a chronic inflammatory disease of the airways. When children with asthma are
exposed to an asthma trigger, the airway walls become inflamed and secrete more mucus, and
the muscles around the airways tighten. This exaggerates the normal airway constriction that
occurs on exhalation, trapping air in the lungs and compromising normal oxygen exchange.
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These physiological changes can result in wheezing, coughing, difficulty in breathing, chest
tightness, and pain.
Asthma is one of the most common chronic diseases among children: in the year 2009, it
affected 7.1 million (or about 10% of) children in the United States.56 It is costly in both human
and monetary terms: estimated national costs of asthma in 2007 were $56 billion.57 The
percentage of children with asthma increased substantially from 1980-1996 and remains
high.58 Researchers do not completely understand why children develop asthma or why the
prevalence has increased.
Asthma is a complex disease with many factors, including genetic factors and environmental
factors, that interact to influence its development and severity. The percentage of children
reported to have current asthma differs by age, family history of asthma and allergies, racial
and ethnic group, and family income. Children of color and children of lower-income families
are more likely to be diagnosed with asthma. Because minority populations are more likely to
be of low socioeconomic status, it is difficult to establish whether racial/ethnic group is an
independent risk factor for the development of asthma. While some research has suggested
that variations in asthma prevalence among racial groups can be explained by socioeconomic
factors,59'60 another study suggested that the difference persists even after accounting for
socioeconomic factors.61 Other researchers have proposed that the greater prevalence of
asthma among Black children can be explained by their disproportionate presence in urban
environments.62
Children living in poverty are more likely to have poorly maintained housing, which can present
risk factors for asthma development and exacerbation. The Institute of Medicine concluded
that exposure to dust mites causes asthma in susceptible children, and that cockroaches may
cause asthma in young children.1 Research suggests that lower-income children are more likely
to live in homes with high levels of cockroach allergens and homes where someone smokes
regularly.63"66 A nationally representative survey of allergens in U.S. housing reported higher
levels of dust mite allergen in bedding from lower-income families.67 Household mouse allergen
was also found at higher concentrations in low-income homes, mobile homes, and older
homes.68 In addition, total dust weight itself has been found to contribute to respiratory
symptoms, including asthma and wheeze. Households with lower income, older homes,
household pets, a smoker in the house, and less frequent cleaning are more likely to have
higher dust weight levels.69 Furthermore, children living in poverty may also face barriers to
medical care, have less access to routine medical care and instructions for asthma
management, or may be less likely to use asthma control medications.70"76 These factors may
increase asthma morbidity, as evidenced by increased asthma symptoms among those
diagnosed with the disease.
Asthma indicators provide data on the percentage of children who have asthma as well as
health outcomes for children with asthma. Indicators HI and H2 focus on the prevalence of
asthma among children. Indicator HI provides the best nationally representative data available
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on prevalence of asthma over time among children ages 0 to 17 years. It provides two
measures of asthma prevalence by year, from 1997-2010: current asthma prevalence and
asthma attack prevalence. While the former measure reports on the percentage of children
who have asthma each year, the latter measure presents data on children who had asthma
attacks in the past year, and thus represents outcomes for children with asthma by identifying
the proportion of children with ongoing or uncontrolled symptoms. Indicator H2 provides the
best nationally representative data available to compare the prevalence of current asthma
among children 0 to 17 years by race/ethnicity and family income for the years 2007-2010.'
Emergency Room Visits and Hospitalizations for Respiratory Diseases
Children who visit emergency rooms or are hospitalized for respiratory diseases (including
asthma and upper and lower respiratory infections such as bronchiolitis and pneumonia)
usually represent the most severe cases of respiratory disease. Although only a fraction of
children with respiratory diseases are admitted to the hospital, asthma is the third leading
cause of hospitalization for children in the United States and bronchiolitis is the leading cause
of acute illness and hospitalization in infants.77'78
Emergency room visits and hospital admissions for respiratory diseases can be related to a
number of factors. These factors include exposure to asthma triggers, lack of access to primary
health care, lack of or inadequate insurance, inadequate instructions for asthma management,
or inadequate compliance with given instructions.79"83 Changes in emergency room visits and
hospital admissions over time may also reflect changes in medical practices, asthma therapy,
and access to and use of care.84'85
For children with existing respiratory conditions, exposure to air pollution from indoor and
outdoor sources can trigger the onset of symptoms and lead to difficulty in breathing, increased
use of medication, school absenteeism, visits to the doctor's office, and respiratory-related
hospitalizations and trips to the emergency room.3"6
Studies have suggested that exacerbation of asthma from exposure to air pollution can be more
severe among people with low income compared with other populations,86'87 and that the gap
between Black and White children in both hospitalizations and deaths from asthma appears to
be growing.88"90 The asthma death rate among Black non-Hispanic children with asthma was 4.9
times higher than the rate for White non-Hispanic children with asthma in 2004-2005.88
Asthma is the leading cause of emergency room visits, hospitalizations, and missed school days
in New York City's poorest neighborhoods.91 In Maryland, the rate of children's emergency
room visits for asthma is twice as high for Baltimore City (an area with a relatively high
percentage of lower income and Black children) than for any other jurisdiction.92
1 State-specific asthma information can be found in the CDC report, The State of Childhood Asthma, United States,
1980-2005, located at http://www.cdc.gov/nchs/data/ad/ad381.pdf.
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Indicator H3 provides the best nationally representative data available on the frequency with
which children experienced asthma or respiratory symptoms resulting in an emergency room
visit or hospitalization for the years 1996-2008. This indicator highlights the most severe cases
of respiratory illness among children ages 0 to 17 years. Indicator H3 includes further
information on health outcomes for children with asthma, in addition to the asthma attack
prevalence information in Indicator HI, by reporting on trends in children's hospitalizations and
emergency room visits due to asthma.
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Indicator HI: Percentage of children ages 0 to 17 years with asthma, 1997-2010
Indicator H2: Percentage of children ages 0 to 17 years reported to have current
asthma, by race/ethnicity and family income, 2007-2010
About the Indicators: Indicators HI and H2 present the percentage of children ages 0 to 17 years
with asthma. The data are from a national survey that collects health information from a
representative sample of the population each year. Indicator HI shows how children's asthma rates
have changed over time. Indicator H2 shows how children's asthma rates vary by race/ethnicity and
family income level.
National Health Interview Survey
The National Health Interview Survey (NHIS) provides nationally representative data on the
prevalence of childhood asthma in the United States each year. NHIS is a large-scale household
interview survey of a representative sample of the civilian noninstitutionalized U.S. population,
conducted by the National Center for Health Statistics (NCHS). The interviews are conducted in
person at the participants' homes. From 1997-2005, interviews were conducted for
approximately 12,000-14,000 children annually. From 2006-2008, interviews were conducted
for approximately 9,000-10,000 children per year. In 2009 and 2010, interviews were
conducted for approximately 11,000 children per year.
With a major survey redesign implemented in 1997, the measurement of childhood asthma
prevalence in NHIS was changed to reporting the percentage of children ever diagnosed with
asthma (lifetime asthma prevalence) and children ever diagnosed with asthma that also had an
asthma attack in the previous 12 months (asthma attack prevalence). The data are obtained by
asking a parent or other knowledgeable household adult questions regarding the child's health
status. NHIS asks "Has a doctor or other health professional ever told you that your child has
asthma?" If the answer is YES to this question, NHIS then asks (1) "Does your child still have
asthma?" and (2) "during the past 12 months, has your child had an episode of asthma or an
asthma attack?" The question "Does your child still have asthma?" was introduced in 2001 and
identifies children who were previously diagnosed with asthma and who currently have asthma
(current asthma prevalence). Some children may have asthma when they are young and
experience fewer symptoms as they get older, or their asthma may be well controlled through
medication and by avoiding triggers of asthma attacks. In such cases, children may currently
have asthma but may not have experienced any attacks in the previous year.
Data Presented in the Indicators
Indicator HI presents two different measures of asthma prevalence using data from the NHIS:
current asthma and asthma attack prevalence. Indicator HI provides the annual estimates of
asthma prevalence for all children 0 to 17 years of age for the years 1997-2010. Indicator H2
reports on the percentage of children ages 0 to 17 years reported to have current asthma, by
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race/ethnicity and family income, in 2007-2010. NHIS is also the source of data for this
indicator. The 2007, 2008, 2009 and 2010 data are combined for this indicator in order to
increase the statistical reliability of the estimates for each race/ethnicity and income group.
For Indicator H2, five race/ethnicity groups are presented: White non-Hispanic, Black non-
Hispanic, Asian non-Hispanic, Hispanic, and "All Other Races." The "All Others Races" category
includes all other races not specified, together with those individuals who report more than one
race. The limits of the sample design and sample size often prevent statistically reliable
estimates for smaller race/ethnicity groups. The data are also tabulated for three income
groups: all incomes, below the poverty level, and greater than or equal to the poverty level.
These prevalence data are based on a survey respondent reporting that asthma has been
diagnosed by a health care provider. Accuracy of responses and access to health care providers
may vary among population groups.93'94
In addition to the data shown in Indicator HI, a supplemental table shows data for the
percentage of children who had asthma in the past 12 months (asthma period prevalence), for
the years 1980-1996. Estimates for asthma period prevalence are not directly comparable to
any of the three prevalence estimates collected since 1997 because of changes in the NHIS
survey questions. The data table for Indicator H2 shows the prevalence of current asthma for
an expanded set of race/ethnicity categories, including Mexican-American and Puerto Rican. A
supplemental data table shows the prevalence of current asthma by age and sex for the years
2007-2010.
Please see the Introduction to the Health section for discussion of statistical significance testing
applied to these indicators.
Other Estimates of Asthma Prevalence
In addition to NHIS, other NCHS surveys provide data on asthma prevalence. A telephone-based
survey conducted in 2007 by NCHS along with state and local governments found that 11% of
high school students currently had asthma.95 The 2007 National Survey of Children's Health
(NSCH) found that nationwide 9.0% of children ages 0 to 17 years currently had asthma, which
is very similar to the estimate from NHIS for 2007. The 2007 NSCH also provides information at
the state level: South Dakota has the lowest asthma rates, with only 5.2% of children currently
having asthma. The District of Columbia has the highest asthma rates, with 14.4% of children
currently having asthma.96
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Indicator HI
Percentage of children ages 0 to 17 years with asthma, 1997-2010
Current asthma prevalence
Asthma attack prevalence
2000 2002 2004 2006 2008 2010
Data: Centers for Disease Control and Prevention, National Center for Health Statistics,
National Health Interview Survey
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Data characterization
Data for this indicator are obtained from an ongoing annual survey conducted by the National Center for
Health Statistics.
Survey data are representative of the U.S. civilian noninstitutionalized population.
A parent or other knowledgeable adult in each sampled household is asked questions regarding the child's
health status, including if they have ever been told the child has asthma, if the child has had an asthma
attack in the past year, and if the child currently has asthma.
The proportion of children reported to currently have asthma increased from 8.7% in 2001
to 9.4% in 2010.
In 2010, 5.7% of all children were reported to have had one or more asthma attacks in the
previous 12 months. There was little change in this rate between 1997 and 2010.
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In 2001, 61.7% of children with current asthma had one or more asthma attacks in the
previous 12 months, and by 2010 this figure had declined to 58.3%."The decreasing trend
from 2001 to 2010 was statistically significant. (See Table Hlc.)
Between 1980 and 1995 the percentage of children who had asthma in the past 12 months
increased from 3.6% in 1980 to 7.5% in 1995. Methods for measurement of childhood
asthma changed in 1997, so earlier data cannot be compared to the data from 1997-2010.
(See Table Hlb.)
1 See indicator H3 for further information on outcomes for children with asthma.
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Indicator H2
Percentage of children ages 0 to 17 years reported to have current asthma,
by race/ethnicity and family income, 2007-2010
All Races/Ethnicities
White non-Hispanic
All
Incomes Asian non-Hispa
Hispanic
All Other Races
All Races/Ethnicities
Ator White non-Hispanic
Above Black non-Hi
Poverty Asjan non.
Level Hispanic
All Other Races
All Races/Ethnicities
Below White non-Hispanic
Poverty
Level
Hispanic
All Other Races
Data: Centers for Disease Control and Prevention, National Center for Health Statistics,
National Health Interview Survey
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** Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, is 40% or
greater (RSE = standard error divided by the estimate).
Data characterization
Data for this indicator are obtained from an ongoing annual survey conducted by the National Center for
Health Statistics.
Survey data are representative of the U.S. civilian noninstitutionalized population.
A parent or other knowledgeable adult in each sampled household is asked questions regarding the child's
health status, including if they have ever been told the child has asthma, if the child has had an asthma
attack in the past year, and if the child currently has asthma.
In 2007-2010, 9.4% of all children were reported to currently have asthma.
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Among children living in families with incomes below the poverty level, 12.2% were
reported to currently have asthma. Among children living in families with incomes at the
poverty level and higher, 8.7% were reported to currently have asthma. This difference was
statistically significant.
In 2007-2010, the percentages of Black non-Hispanic children and children of "All Other
Races" reported to currently have asthma, 16.0% and 12.4% respectively, were greater than
for White non-Hispanic children (8.2%), Hispanic children (7.9%), and Asian non-Hispanic
children (6.8%).
• The differences in current asthma prevalence among Black non-Hispanic or "All Other
Races" children, compared with current asthma prevalence among Hispanic, White non-
Hispanic, or Asian non-Hispanic children, were statistically significant. These differences
by race/ethnicity also hold true when considering only children below poverty level and
only children at or above poverty level.
Among Hispanic children, about 1 in 4 Puerto Rican children (23.3%) living in families with
incomes below the poverty level were reported to currently have asthma. The rate of
reported current asthma for Mexican-American children living in families with incomes
below the poverty level is 6.6%. This difference was statistically significant. (See Table H2.)
Among boys, 10.7% were reported to have current asthma compared with 8.0% of girls. This
difference was statistically significant. (See Table H2a.)
Among children ages 0 to 5 years, 7.1% were reported to have current asthma compared
with 10.0% of children ages 6 to 10 years and 11.0% of children ages 11 to 17 years. The
difference in current asthma by age group was statistically significant. (See Table H2a.)
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Indicator H3: Children's emergency room visits and hospitalizations for asthma and
other respiratory causes, ages 0 to 17 years, 1996-2008
About the Indicator: Indicator H3 presents information about the number of children's emergency
room visits and hospitalizations for asthma and other respiratory causes. The data are from two
national surveys that collect information from hospitals each year. Indicator H3 shows how the
rates of children's emergency room visits and hospitalizations for respiratory causes have changed
overtime.
National Hospital Ambulatory Medical Care Survey and National Hospital
Discharge Survey
The National Hospital Ambulatory Medical Care Survey (NHAMCS) and the National Hospital
Discharge Survey (NHDS), conducted by the National Center for Health Statistics of the Centers
for Disease Control and Prevention, provide national data on emergency room visits and
hospitalizations. The NHAMCS has collected data for physician diagnoses for visits to hospital
emergency rooms and outpatient departments beginning in the year 1992, while the NHDS
reports physician diagnoses for discharges from hospitals beginning in the year 1965. The
diagnoses in both surveys include asthma and a number of other respiratory conditions. Both
surveys exclude federal and military hospitals and report patient demographic information.
Data Presented in the Indicators
Indicator H3 uses data from NHAMCS and NHDS to display emergency room visits and
hospitalizations for asthma and other respiratory conditions including bronchitis, pneumonia,
and influenza. The top line in each graph represents the total number of children's emergency
room visits or hospitalizations for asthma and all other respiratory causes, followed by lines for
asthma and for all respiratory causes other than asthma. Indicator H3 presents annual survey
results from 1996-2008. 1996 was selected as the initial year for the indicator because not all
of the needed hospitalization data for earlier years are available online. The indicator provides
data through 2008 because it is the most recent year for which data from both NHAMCS and
NHDS are available.
In addition to the data shown in the Indicator H3 graph, supplemental tables show the annual
average rates of children's emergency room visits and hospitalizations for asthma and all other
respiratory causes, asthma, and all respiratory causes other than asthma (composed of the
following subcategories: upper respiratory conditions, pneumonia or influenza, and other lower
respiratory conditions besides asthma) by age and race/ethnicity for the years 2005-2008. For
emergency room visits, five race/ethnicity groups are presented: White non-Hispanic, Black
non-Hispanic, American Indian/Alaska Native non-Hispanic, Asian and Pacific Islander non-
Hispanic, and Hispanic. For hospitalizations, race only is reported; the two groups presented are
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White and Black. The supplemental tables do not include income data, since neither of these
surveys includes the patient's income or family income.
Please see the Introduction to the Health section for discussion of statistical significance testing
applied to these indicators.
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Indicator H3
Children's emergency room visits and hospitalizations for asthma and other
respiratory causes, ages 0 to 17 years, 1996-2008
Asthma and all
other respiratory
causes
= 500
All respiratory causes
other than asthma
Asthma and all other
respiratory causes
All respiratory causes
other than asthma
Emergency room visits
Hospitalizations
1996 1998 2000 2002 2004 2006 2008 1996 1998 2000 2002 2004 2006 2008
Data: Centers for Disease Control and Prevention, National Center for Health Statistics,
National Hospital Ambulatory Medical Care Survey (emergency room visits) and National
Hospital Discharge Survey (hospitalizations)
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Data characterization
Data for this indicator are obtained from two ongoing annual surveys conducted by the National Center for
Health Statistics.
Survey data are representative of U.S. population visits to emergency rooms and stays at non-federal
hospitals.
The surveys collect data on physician diagnoses of patients in sampled hospitals, including diagnoses of
asthma and other respiratory conditions.
Emergency Room Visits
• In 2008, the rate of emergency room visits for asthma and all other respiratory causes was
619 visits per 10,000 children. The rate of emergency room visits for asthma alone was 103
visits per 10,000 children, and the rate for all respiratory causes other than asthma was 517
visits per 10,000 children.
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• The rate of emergency room visits for asthma decreased from 114 visits per 10,000 children
in 1996 to 103 visits per 10,000 children in 2008. This decreasing trend was statistically
significant.
• Children's emergency room visits for asthma and all other respiratory causes vary widely by
race/ethnicity. For the years 2005-2008, Black non-Hispanic children had a rate of 1,240
emergency room visits per 10,000 children, while Hispanic children had a rate of 672
emergency room visits per 10,000 children, American Indian/Alaska Native non-Hispanic
children had a rate of 536 emergency room visits per 10,000 children, White non-Hispanic
children had a rate of 487 emergency room visits per 10,000 children, and Asian and Pacific
Islander non-Hispanic children had a rate of 371 emergency room visits per 10,000 children.
(See Table H3a.)
• The difference in rates of emergency room visits between Black non-Hispanic children
and emergency room visits for each of the other race/ethnicity groups was statistically
significant.
• Children's emergency room visits for asthma and all other respiratory causes vary widely by
age. For the years 2005-2008, infants less than 12 months of age had a rate of 2,142
emergency room visits per 10,000 children, while children 16 to 17 years of age had a rate
of 338 emergency room visits per 10,000 children. The differences between age groups
were statistically significant. (See Table H3b.)
Hospitalizations
• Between 1996 and 2008, hospitalizations for asthma and for all other respiratory causes
decreased from 90 hospitalizations per 10,000 children to 56 hospitalizations per 10,000
children. Between 1996 and 2008, hospitalizations for asthma alone decreased from 30 per
10,000 children to 16 per 10,000 children, and hospitalizations for all other respiratory
causes decreased from 60 per 10,000 children to 40 per 10,000 children. These decreasing
trends were statistically significant.
• Children's hospitalizations for asthma and all other respiratory causes vary widely by race. For
the years 2005-2008, Black children had a rate of 84 hospitalizations for asthma and other
respiratory causes per 10,000 children, while White children had a rate of 52 hospitalizations
per 10,000 children. This difference was statistically significant. (See Table H3c.)
• Children's hospitalizations for asthma and all other respiratory causes vary widely by age.
For the years 2005-2008, infants less than 12 months of age had a rate of 396
hospitalizations per 10,000 children, while children 16 to 17 years of age had a rate of 13
hospitalizations per 10,000 children. The differences between age groups were statistically
significant. (See Table H3d.)
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Health I Childhood Cancer
Childhood Cancer
Cancer is not a single disease, but includes a variety of malignancies in which abnormal cells
divide in an uncontrolled manner. These cancer cells can invade nearby tissues and can migrate
by way of the blood or lymph systems to other parts of the body.1 The most common childhood
cancers are leukemias (cancers of the white blood cells) and cancers of the brain or central
nervous system, which together account for more than half of new childhood cancer cases.2
Cancer in childhood is rare compared with cancer in adults, but still causes more deaths than
any factor, other than injuries, among children from infancy to age 15 years.2 The annual
incidence of childhood cancer has increased slightly over the last 30 years; however, mortality
has declined significantly for many cancers due largely to improvements in treatment.2'3 Part of
the increase in incidence may be explained by better diagnostic imaging or changing
classification of tumors, specifically brain tumors.4 However, the President's Cancer Panel
recently concluded that the causes of the increased incidence of childhood cancers are not fully
understood, and cannot be explained solely by the introduction of better diagnostic techniques.
The Panel also concluded that genetics cannot account for this rapid change. The proportion of
this increase caused by environmental factors has not yet been determined.5
The causes of cancer in children are poorly understood, though in general it is thought that
different forms of cancer have different causes. According to scientists at the National Cancer
Institute, established risk factors for the development of childhood cancer include family
history, specific genetic syndromes (such as Down syndrome), high levels of radiation, and
certain pharmaceutical agents used in chemotherapy.4'6 A number of studies suggest that
environmental contaminants may play a role in the development of childhood cancers. The
majority of these studies have focused on pesticides and solvents, such as benzene. According
to the President's Cancer Panel, "the true burden of environmentally induced cancer has been
grossly underestimated."5
The development of cancer, or carcinogenesis, is a multistep process leading to the
uncontrolled growth and division of cells. This process can begin with an inherited genetic
mutation or DNA damage initiated by an exogenous agent, such as exposure to a carcinogenic
chemical or radiation. Additionally, many external influences, such as environmental exposures
or nutrition, can alter gene expression without changing the DNA sequence.7 These alterations,
referred to as epigenetic changes, can promote alterations in the expression of genes important
for controlling cell growth and division.8'9 Because the initiation of carcinogenesis is a multistep
process, multiple factors are thought to contribute to the development of cancer.9 Newer
research suggests that childhood cancer may be caused by a combination of genetic
predisposition and environmental exposure.10"16
Different types of cancer affect children at different ages. This pattern may reflect the different
types of exposures and windows of vulnerability experienced by children as they grow older,
and the time between the initiation of cancer and its clinical presentation. Children can be
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Childhood Cancer | Health
affected by exposures that occur during different developmental stages, such as during infancy
and early childhood. Scientific evidence suggests that early childhood cancers may be related to
exposure in the womb, or even to parents' exposures prior to conception.17"21 Furthermore,
recent studies suggest that susceptibility to some cancers that arise later in adulthood also may
be determined while in the womb.7
Leukemia is the most common form of cancer in children. According to the Centers for Disease
Control and Prevention, adults and children who undergo chemotherapy and radiation therapy
for cancer treatment; take immune suppressing drugs; or have certain genetic conditions, such
as Down syndrome; are at a higher risk of developing acute leukemia.22 Multiple review articles
have concluded that ionizing radiation from sources such as x-rays is associated with an
increased risk of leukemia.23"25 CT scans are also an increasing source of ionizing radiation
exposure to children,26 and may be associated with an increased risk of childhood leukemia.27
Further, studies have consistently shown an approximately 40% increased risk of childhood
leukemia after maternal exposure to ionizing radiation during pregnancy.18'23"25 These
confirmed risk factors, however, explain less than 10% of the incidence of childhood leukemia,
meaning that the cause is unknown in at least 90% of leukemia cases.18
Associations between proximity to extremely low frequency electromagnetic radiation, such as
radiation from electrical power lines, and childhood leukemia have been investigated for many
years.5 Some studies suggest an effect on cancer risk, while others do not.28'29 At this time, a
variety of national and international organizations have concluded that the link between
exposure to extremely low frequency electromagnetic fields and cancer is controversial or
weak.4'5 Radon is a naturally occurring radioactive element that has been associated with lung
cancer; some studies have also found an association between childhood leukemia and radon
while other studies have not.4'30"32 A recent study also reported an association between
naturally occurring gamma radiation and childhood leukemia.33
Pesticides, solvents, hazardous air pollutants, motor vehicle exhaust, and environmental
tobacco smoke have been studied for a potential role in childhood leukemia. Numerous studies
have examined the link between parents' (parental), prenatal, and childhood exposures to
pesticides and childhood leukemia, and several meta-analyses of these studies have found
associations between pesticide exposure and childhood leukemia in both residential and
occupational settings.20'34"46 Recent literature has also suggested an association between
childhood exposures to multiple hazardous air pollutants and leukemia.47"49 A study exploring
the relationship between childhood leukemia and hazardous air pollutants (HAPs) in outdoor air
found an increased risk for childhood leukemia in census tracts with the highest concentrations
of a group of 25 potentially carcinogenic HAPs, including several solvents.48 Several other
studies have found associations between leukemia and surrogate measures of exposure to
motor vehicle exhaust, including residential proximity to traffic and gas stations.18'50"53
However, other studies conducted in California and Denmark did not find an association
between these proxy measures of motor vehicle exhaust and childhood leukemia,54"57 and
review studies have concluded that the overall evidence for a relationship is inconclusive.18'58
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Health I Childhood Cancer
According to the U.S. Surgeon General, there is also suggestive evidence that prenatal and
postnatal exposure to environmental tobacco smoke can lead to leukemia in children.59
Cancers of the nervous system, including brain tumors, are the second most common form of
cancer in children. Known risk factors for childhood brain tumors include radiation therapy and
certain genetic syndromes, although these factors explain only a small portion of cases.6 Some
studies have also reported an association between prenatal exposure to ionizing radiation and
brain tumors while a few smaller studies have not.25'60'61 Other research reports that head CT
scans may be associated with an increased risk of brain tumors in children.27 Research also
suggests that parental, prenatal, and childhood exposure to pesticides may lead to brain
tumors in children.43'45'46 There is suggestive evidence linking prenatal and postnatal exposure
to environmental tobacco smoke and childhood brain tumors, according to the U.S. Surgeon
General.59 Many studies have examined whether there is an association between cellular phone
use and brain cancer. Some of these studies have found an association between cellular phone
use and some types of brain cancer, while other studies have found no association.62"69 Because
the use of cellular phones by children has only recently become more common, no long-term
epidemiological studies of cancer related to cellular phone use by children are available.5
Lymphomas, which affect a child's lymph system, are another common form of childhood
cancer. The cause of most cases of childhood lymphoma is unknown, but it is clear that children
with compromised immune systems are at a greater risk of developing lymphomas.6 Extensive
review studies have found suggestive associations between parental, prenatal, and childhood
exposure to pesticides and childhood lymphomas.43'46 The U.S. Surgeon General has concluded
that there is also suggestive evidence linking prenatal and postnatal exposure to environmental
tobacco smoke and childhood lymphomas.59
Other childhood cancers that have been associated with environmental exposures include
thyroid cancer, Wilms' tumor (a type of kidney cancer), Ewing's sarcoma (a cancer of the bone
or soft tissue), and melanoma. Some research has reported an increased risk of thyroid cancer
in childhood or early adulthood from exposure to ionizing radiation.70"72 Much of the evidence
for this association comes from studies of individuals in areas with high ionizing radiation
exposure due to the Chernobyl accident in eastern Europe. While the only known causal factors
for Wilms' tumor and Ewing's sarcoma are certain birth defects and genetic conditions, there is
limited research indicating that exposure to pesticides may also be a causal factor in the
development of Wilms' tumor and Ewing's sarcoma in children.36'46'73 Although childhood
melanoma is rare, the incidence of melanoma is increasing in children, especially in
adolescents. Environmental factors associated with melanoma include sunburns, especially in
childhood, and increased exposure to ultraviolet (UV) radiation.74"76 Depletion of the ozone
layer causes more ultraviolet radiation to reach the earth's surface. Even though the use of
ozone depleting compounds has been largely phased out and the ozone layer will eventually be
restored, higher levels of ultraviolet radiation reaching the earth's surface will persist for many
years to come.77'78 Finally, the increased rates of melanoma in adolescent girls and young
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Childhood Cancer | Health
women may reflect increased UV exposure from sunbathing or from the widespread practice of
indoor tanning.79'80
The two indicators that follow provide the best nationally representative data available on
cancer incidence and mortality among U.S. children over time. Indicator H4 presents cancer
incidence and mortality for children ages 0 to 19 years for the period 1992-2009. Indicator H5
presents cancer incidence, by cancer type, for children ages 0 to 19 years for the period 1992-
2006. Changes in childhood cancer mortality are most likely reflective of changes in treatment
options, rather than environmental exposures. However, showing childhood cancer mortality
rates in conjunction with childhood cancer incidence rates highlights the magnitude and
severity of childhood cancer and indicates the proportion of children that survive.
Indicator H4 provides an indication of broad trends in childhood cancer over time, while Indicator
H5 provides more detailed information about the incidence of specific types of cancer in children.
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Health I Childhood Cancer
Indicator H4: Cancer incidence and mortality for children ages 0 to 19 years, 1992-
2009
Indicator H5: Cancer incidence for children ages 0 to 19 years by type, 1992-2006
About the Indicators: Indicators H4 and H5 present information about the number of new childhood
cancer cases and the number of deaths caused by childhood cancer. The childhood cancer case data
come from a program that collects information from tumor registries located in specific geographic
regions around the country each year. The childhood cancer death data come from a national
database of vital statistics that collects data on numbers and causes of all deaths each year. Indicator
H4 shows how the rates of all new childhood cancers and all childhood cancer deaths have changed
over time, and Indicator H5 shows how the rates of specific types of childhood cancers have changed
overtime.
SEER
The National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) Program has
provided data on cancer incidence, survival, and prevalence since 1973. SEER obtains its cancer
case data from tumor registries in various locations throughout the United States and its cancer
mortality data from a national database of vital statistics that collects data on numbers and
causes of all deaths each year. Each of the tumor registries collects information for all tumors
within a specified geographic region. The sample population covered by the SEER tumor
registries is comparable to the general U.S. population in terms of poverty and education.
However, the population covered by the SEER tumor registries tends to be more urban and has
a higher proportion of foreign-born persons compared with the general U.S. population.81
Since its initiation in 1973, the SEER program has expanded to include a greater number of
tumor registries. Currently, the SEER program includes data from 18 tumor registries, but
complete data from all 18 registries are only available beginning with the year 2000. SEER data
are available from 13 different tumor registries that provide data starting in 1992, and
represent geographic areas containing 13.8% of the total U.S. population.82 The registries
include the Alaska Native, Atlanta, Connecticut, Detroit, Hawaii, Iowa, Los Angeles, New
Mexico, Rural Georgia, San Francisco-Oakland, San Jose-Monterey, Seattle-Puget Sound, and
Utah tumor registries.
Data Presented in the Indicators
Childhood cancer incidence refers to the number of new childhood cancer cases reported for a
specified period of time. Childhood cancer incidence is shown in Indicator H4 and Indicator H5
as the number of childhood cancer cases reported per million children for one year. The
incidence rate is age-adjusted, meaning that each year's incidence calculation uses the age
distribution of children from the year 2000. For example, 25.3% of all U.S. children were
between the ages of 5 and 9 years in 2000, and this percentage is assumed to be the same for
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Childhood Cancer | Health
each year from 1992 to 2009. This age adjustment ensures that differences in cancer rates over
time are not simply due to changes in the age composition of the population. Indicator H4 also
shows childhood cancer mortality as the number of deaths per million children for each year.
SEER reports the incidence data by single year of age, but reports mortality data in five age
groups for children under the age of 20: under 1 year, 1-4, 5-9,10-14, and 15-19 years. For
this reason, both indicators use data for all children 0 to 19 years of age, in contrast to the
other indicators in this report that define children as younger than age 18 years.
Trends in the total incidence of childhood cancer, as shown by Indicator H4, are useful for
assessing the overall burden of cancer among children. However, broad trends mask changes in
the frequency of specific types of cancers that often have patterns that diverge from the overall
trend. Moreover, environmental factors may be more likely to contribute to some childhood
cancers than to others. Indicator H5 shows trends in incidence for specific types of childhood
cancers.
Some types of childhood cancers are very rare, and as such the yearly incidence is particularly
low and variable. Due to this fact, Indicator H5 shows the incidence of individual childhood
cancers in groupings of three years. Each bar in the graph represents the annual number of
cases of that specific cancer diagnosed per million children, calculated as the average number
of cases per year divided by the average population of children (in millions) per year for each
three-year period.
The SEER cancer incidence data for the 13 longer-established registries, instead of all 18, were
used to develop the H4 and H5 indicators because this allowed for more comprehensive trend
analysis while still covering a substantial portion of the population. Indicator H4 begins with the
earliest available SEER13 incidence data from 1992 and ends with 2009. Childhood cancer
mortality data for 1992 to 2009 are also used for indicator H4. Indicator H5 presents data for
the series of three-year periods beginning in 1992 and ending in 2006. In addition to the data
shown in the Indicator H4 graph, supplemental tables show childhood cancer incidence and
mortality by race/ethnicity and sex, as well as childhood cancer incidence by age group. These
data tables use data from the three most current years shown in Indicator H4, which are 2007-
2009. Combining three years of data allows for more statistically reliable estimates by
race/ethnicity, sex, and age group. Five race/ethnicity groups are used in the supplemental
tables for Indicator H4: White non-Hispanic, Black non-Hispanic, American Indian/Alaska Native
non-Hispanic, Asian or Pacific Islander non-Hispanic, and Hispanic. In addition to the data
shown in the Indicator H5 graph, a supplemental table shows childhood cancer incidence by
cancer type and age group.
Please see the Introduction to the Health section for discussion of statistical significance testing
applied to these indicators.
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Health I Childhood Cancer
Data characterization
Cancer incidence data for this indicator are obtained from a database of 13 regional tumor registries
located throughout the country, maintained by the National Cancer Institute.
The population covered by the 13 registries is comparable to the general U.S. population regarding poverty
and education, but is more urban and has more foreign-born persons.
Cancer mortality data for this indicator are obtained from a database of all death certificates in the United
States; cause of death is recorded on the death certificates.
The age-adjusted annual incidence of cancer ranged from 153 to 161 cases per million
children between 1992 and 1994 and from 172 to 175 cases per million children between
2007 and 2009. This increasing trend from 1992-2009 was statistically significant.
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Childhood Cancer | Health
Childhood cancer mortality decreased from 33 deaths per million children in 1992 to 24
deaths per million children in 2009, a statistically significant decreasing trend.
Childhood cancer incidence and mortality rates were generally higher for boys than for girls.
In 2007-2009, rates of cancer incidence and mortality for boys were 183 cases per million
and 26 deaths per million, compared with 163 cases per million and 22 deaths per million
for girls. These differences by sex were statistically significant for cancer incidence (after
adjustment for age and race/ethnicity) and cancer mortality. (See Tables H4a and H4b.)
In 2007-2009, the difference in cancer incidence between boys and girls was not consistent
for all races/ethnicities. No statistically significant difference in cancer incidence by sex was
seen among Black non-Hispanic children or Asian or Pacific Islander non-Hispanic children.
Among American Indian and Alaska Native non-Hispanic children, cancer incidence was
greater for girls than for boys, although this difference was not statistically significant. Cancer
incidence was greater for boys than for girls and statistically significant (after adjustment for
age) among White non-Hispanic children and Hispanic children. (See Table H4a.)
In 2007-2009, childhood cancer incidence was highest among White non-Hispanic children
at 188 cases per million. Hispanic children had an incidence rate of 169 cases per million,
Asian and Pacific Islander non-Hispanic children had an incidence rate of 152 cases per
million, American Indian and Alaska Native non-Hispanic children had an incidence rate of
137 cases per million, and Black non-Hispanic children had an incidence rate of 133 cases
per million. (See Table H4a.)
• The cancer incidence rate for White non-Hispanic children was statistically significantly
higher than the rates of each of the other race/ethnicity categories after accounting for
differences by age and sex. The cancer incidence rate for Black non-Hispanic children
was also statistically significantly lower than the rates for Hispanic children and Asian
and Pacific Islander non-Hispanic children after adjustment for differences by age and
sex. The cancer incidence rate for Asian and Pacific Islander non-Hispanic was also
statistically significantly lower than the rate for Hispanic children after adjustment for
differences by age and sex. The remaining differences between race/ethnicity groups
were not statistically significant.
Childhood cancer incidence rates vary by age. In 2007-2009, children under 5 and those of
ages 15 to 19 years experienced the highest incidence rates of cancer at approximately 208
and 232 cases per million, respectively. Children ages 5 to 9 years and 10 to 14 years had
lower incidence rates at 117 and 139 cases per million, respectively. These differences
among age groups were statistically significant. (See Table H4c.)
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Health I Childhood Cancer
Data characterization
Data for this indicator are obtained from a database of 13 regional tumor registries located throughout the
country, maintained by the National Cancer Institute.
The population covered by the 13 registries is comparable to the general U.S. population regarding poverty
and education, but is more urban and has more foreign-born persons.
Leukemia, which includes acute lymphoblastic leukemia and acute myeloid leukemia, was
the most common cancer diagnosis for children from 2004-2006, representing 28% of total
cancer cases. Incidence of acute lymphoblastic (lymphocytic) leukemia was 30 cases per
million in 1992-1994 and 35 cases per million in 2004-2006. The rate of acute myeloid
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Childhood Cancer | Health
(myelogenous) leukemia was 7 cases per million in 1992-1994 and 9 cases per million in
2004-2006.
• The increasing trend for incidence of acute lymphoblastic leukemia was statistically
significant after accounting for differences by age, sex, and race/ethnicity. The trend for
acute myeloid leukemia was not statistically significant.
Central nervous system tumors represented 18% of childhood cancers in 2004-2006. The
incidence of central nervous system tumors was 27 cases per million in 2004-2006, with no
statistically significant trend for 1992-2006.
Lymphomas, which include Hodgkin's lymphoma, non-Hodgkin's lymphoma, and Burkitt's
lymphoma, represented 14% of childhood cancers in 2004-2006. Incidence of Hodgkin's
lymphoma was 12 cases per million in 1992-1994 and 11 per million in 2004-2006. There
were approximately 7 cases of non-Hodgkin's lymphoma per million children in 1992-1994
and 9 per million in 2004-2006. Incidence of Burkitt's lymphoma remained constant from
1992-2006 (2 cases per million children). The increasing trend in the incidence rate of non-
Hodgkin's lymphoma was statistically significant, while there was no statistically significant
trend in the incidence rate of Hodgkin's lymphoma or Burkitt's lymphoma.
Between the years 1992 and 2006, increasing trends in the incidence of soft tissue sarcomas,
malignant melanomas, and hepatoblastomas were statistically significant, as was the
decreasing trend in the incidence of Wilms' tumor (tumors of the kidney). There was no
statistically significant trend in the incidence rate of thyroid carcinomas, other and
unspecified carcinomas, germ cell tumors, osteosarcomas, Ewing's sarcomas, or
neuroblastomas.
• The increasing trend in the incidence rate of hepatoblastomas was statistically
significant after accounting for differences by age, sex, and race/ethnicity.
Different types of cancer affect children at different ages. The incidence of neuroblastomas
and Wilms' tumor (tumors of the kidney) was highest for young children (ages 0 to 4 years).
Leukemias occur in all age groups, but the incidence is highest among 0- to 4-year-olds. The
incidence of Hodgkin's and non-Hodgkin's lymphomas, thyroid carcinomas, malignant
melanomas, other and unspecified carcinomas, germ cell tumors, and osteosarcomas was
higher in those 15 to 19 years old. Differences among age groups were statistically
significant for each of these cancer types. (See Table H5a.)
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Health | Neurodevelopmental Disorders
Neurodevelopmental Disorders
Neurodevelopmental disorders are disabilities associated primarily with the functioning of the
neurological system and brain. Examples of neurodevelopmental disorders in children include
attention-deficit/hyperactivity disorder (ADHD), autism, learning disabilities, intellectual
disability (also known as mental retardation), conduct disorders, cerebral palsy, and
impairments in vision and hearing. Children with neurodevelopmental disorders can experience
difficulties with language and speech, motor skills, behavior, memory, learning, or other
neurological functions. While the symptoms and behaviors of neurodevelopmental disabilities
often change or evolve as a child grows older, some disabilities are permanent. Diagnosis and
treatment of these disorders can be difficult; treatment often involves a combination of
professional therapy, Pharmaceuticals, and home- and school-based programs.
Based on parental responses to survey questions, approximately 15% of children in the United
States ages 3 to 17 years were affected by neurodevelopmental disorders, including ADHD,
learning disabilities, intellectual disability, cerebral palsy, autism, seizures, stuttering or
stammering, moderate to profound hearing loss, blindness, and other developmental delays, in
2006-2008.1 Among these conditions, ADHD and learning disabilities had the greatest
prevalence. Many children affected by neurodevelopmental disorders have more than one of
these conditions: for example, about 4% of U.S. children have both ADHD and a learning
disability.2 Some researchers have stated that the prevalence of certain neurodevelopmental
disorders, specifically autism and ADHD, has been increasing over the last four decades.3"7 Long-
term trends in these conditions are difficult to detect with certainty, due to a lack of data to
track prevalence over many years as well as changes in awareness and diagnostic criteria.
However, some detailed reviews of historical data have concluded that the actual prevalence of
autism seems to be rising.4'8"10 Surveys of educators and pediatricians have reported a rise in
the number of children seen in classrooms and exam rooms with behavioral and learning
disorders.11"13
Genetics can play an important role in many neurodevelopmental disorders, and some cases of
certain conditions such as intellectual disability are associated with specific genes. However,
most neurodevelopmental disorders have complex and multiple contributors rather than any
one clear cause. These disorders likely result from a combination of genetic, biological,
psychosocial and environmental risk factors. A broad range of environmental risk factors may
affect neurodevelopment, including (but not limited to) maternal use of alcohol, tobacco, or
illicit drugs during pregnancy; lower socioeconomic status; preterm birth; low birthweight; the
physical environment; and prenatal or childhood exposure to certain environmental
contaminants.14"21
Lead, methylmercury, and PCBs are widespread environmental contaminants associated with
adverse effects on a child's developing brain and nervous system in multiple studies. The
National Toxicology Program (NTP) has concluded that childhood lead exposure is associated
with reduced cognitive function, including lower intelligence quotient (IQ) and reduced
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Neurodevelopmental Disorders | Health
academic achievement.22The NTP has also concluded that childhood lead exposure is
associated with attention-related behavioral problems (including inattention, hyperactivity, and
diagnosed attention-deficit/hyperactivity disorder) and increased incidence of problem
behaviors (including delinquent, criminal, or antisocial behavior).22
EPA has determined that methylmercury is known to have neurotoxic and developmental
effects in humans.23 Extreme cases of such effects were seen in people prenatally exposed
during two high-dose mercury poisoning events in Japan and Iraq, who experienced severe
adverse health effects such as cerebral palsy, mental retardation, deafness, and blindness.24"26
Prospective cohort studies have been conducted in island populations where frequent fish
consumption leads to methylmercury exposure in pregnant women at levels much lower than
in the poisoning incidents but much greater than those typically observed in the United States.
Results from such studies in New Zealand and the Faroe Islands suggest that increased prenatal
mercury exposure due to maternal fish consumption was associated with adverse effects on
intelligence and decreased functioning in the areas of language, attention, and memory.26"32
These associations were not seen in initial results reported from a similar study in the
Seychelles Islands.33 However, further studies in the Seychelles found associations between
prenatal mercury exposure and some neurodevelopmental deficits after researchers had
accounted for the developmental benefits of fish consumption.34"36 More recent studies
conducted in the United States have found associations between neurodevelopmental effects
and blood mercury levels within the range typical for U.S. women, after accounting for the
beneficial effects offish consumption during pregnancy.32'37'38
Several studies of children who were prenatally exposed to elevated levels of polychlorinated
biphenyls (PCBs) have suggested linkages between these contaminants and
neurodevelopmental effects, including lowered intelligence and behavioral deficits such as
inattention and impulsive behavior.39"44Studies have also reported associations between PCB
exposure and deficits in learning and memory.39'45 Most of these studies found that the effects
are associated with exposure in the womb resulting from the mother having eaten food
contaminated with PCBs,46"51 although some studies have reported relationships between
adverse effects and PCB exposure during infancy and childhood.45'51"53 Although there is some
inconsistency in the epidemiological literature, several reviews of the literature have found that
the overall evidence supports a concern for effects of PCBs on children's neurological
development.52'54"58 The Agency for Toxic Substances and Disease Registry has determined that
"Substantial data suggest that PCBs play a role in neurobehavioral alterations observed in
newborns and young children of women with PCB burdens near background levels."59 In
addition, adverse effects on intelligence and behavior have been found in children of women
who were highly exposed to mixtures of PCBs, chlorinated dibenzofurans, and other pollutants
prior to conception.60"63
A wide variety of other environmental chemicals have been identified as potential concerns for
childhood neurological development, but have not been as well studied for these effects as
lead, mercury, and PCBs. Concerns for these additional chemicals are based on both laboratory
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Health | Neurodevelopmental Disorders
animal studies and human epidemiological research; in most cases, the epidemiological studies
are relatively new and the literature is just beginning to develop. Among the chemicals being
studied for potential effects on childhood neurological development are organophosphate
pesticides, polybrominated diphenyl ether flame retardants (PBDEs), phthalates, bisphenol A
(BPA), polycyclic aromatic hydrocarbons (PAHs), arsenic, and perchlorate. Exposure to all of
these chemicals is widespread in the United States for both children and adults.64
Organophosphate pesticides can interfere with the proper function of the nervous system when
exposure is sufficiently high.65 Many children may have low capacity to detoxify organophosphate
pesticides through age 7 years.66 In addition, recent studies have reported an association
between prenatal organophosphate exposure and childhood ADHD in a U.S. community with
relatively high exposures to organophosphate pesticides,67 as well as with exposures found within
the general U.S. population.68 Other recent studies have described associations between prenatal
organophosphate pesticide exposures and a variety of neurodevelopmental deficits in childhood,
including reduced IQ, perceptual reasoning, and memory.69"71
Studies of certain PBDEs have found adverse effects on behavior, learning, and memory in
laboratory animals.72"74 A recent epidemiological study in New York City reported significant
associations between children's prenatal exposure to PBDEs and reduced performance on IQ
tests and other tests of neurological development in 6-year-old children.75 Another study in the
Netherlands reported significant associations between children's prenatal exposure to PBDEs
and reduced performance on some neurodevelopmental tests in 5- and 6-year-old children,
while associations with improved performance were observed for other tests.76
Two studies of a group of New York City children ages 4 to 9 years reported associations
between prenatal exposure to certain phthalates and behavioral deficits, including effects on
attention, conduct, and social behaviors.77'78 Some of the behavioral deficits observed in these
studies are similar to those commonly displayed in children with ADHD and conduct disorder.
Studies conducted in South Korea of children ages 8 to 11 years reported that children with
higher levels of certain phthalate metabolites in their urine were more inattentive and
hyperactive, displayed more symptoms of ADHD, and had lower IQ compared with those who
had lower levels.79'80 The exposure levels in these studies are comparable to typical exposures
in the U.S. population.
In 2008, the NTP concluded that there is "some concern" for effects of early-life (including
prenatal) BPA exposure on brain development and behavior, based on findings of animal
studies conducted at relatively low doses.81 An epidemiological study conducted in Ohio
reported an association between prenatal exposure to BPA and effects on children's behavior
(increased hyperactivity and aggression) at age 2 years.82 Another study of prenatal BPA
exposure in New York City reported no association between prenatal BPA exposure and social
behavior deficits in testing conducted at ages 7 to 9 years.78
A series of recent studies conducted in New York City has reported that children of women who
were exposed to increased levels of polycyclic aromatic hydrocarbons (PAHs, produced when
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gasoline and other materials are burned) during pregnancy are more likely to have experienced
adverse effects on neurological development (for example, reduced IQ and behavioral
problems).83'84
Early-life exposure to arsenic has been associated with measures of reduced cognitive function,
including lower scores on tests that measure neurobehavioral and intellectual development, in
four studies conducted in Asia; however there are some inconsistencies in the findings of these
studies.85 These findings are from countries where arsenic levels in drinking water are generally
much higher than in the United States due to high levels of naturally occurring arsenic in
groundwater.86
Perchlorate is a naturally occurring and man-made chemical that has been found in drinking
water87 and foods88'89 in the United States. Exposure to elevated levels of perchlorate inhibits
iodide uptake into the thyroid gland, thus possibly disrupting the function of the thyroid and
potentially leading to a reduction in the production of thyroid hormone.90'91 Moderate deficits
in maternal thyroid hormone levels during early pregnancy have been linked to reduced
childhood IQ scores and other neurodevelopmental effects.92"94
Interactions of environmental contaminants and other environmental factors may combine to
increase the risk of neurodevelopmental disorders. For example, exposure to lead may have
stronger effects on neurodevelopment among children with lower socioeconomic status.21'95
A child's brain and nervous system are vulnerable to adverse impacts from pollutants because
they go through a long developmental process beginning shortly after conception and
continuing through adolescence.96'97 This complex developmental process requires the precise
coordination of cell growth and movement, and may be disrupted by even short-term
exposures to environmental contaminants if they occur at critical stages of development. This
disruption can lead to neurodevelopmental deficits that may have an effect on the child's
achievements and behavior even when they do not result in a diagnosable disorder.
Attention-Deficit/Hyperactivity Disorder (ADHD)
Attention-deficit/hyperactivity disorder (ADHD) is a disruptive behavior disorder characterized
by symptoms of inattention and/or hyperactivity-impulsivity, occurring in several settings and
more frequently and severely than is typical for other individuals in the same stage of
development.98 ADHD can make family and peer relationships difficult, diminish academic
performance, and reduce vocational achievement.
As the medical profession has developed a greater understanding of ADHD through the years,
the name of this condition has changed. The American Psychiatric Association adopted the
name "attention deficit disorder" in the early 1980s and revised it to "attention-
deficit/hyperactivity disorder" in 1987.99 Many children with ADHD have a mix of inattention
and hyperactivity/impulsivity behaviors, while some may display primarily hyperactive behavior
traits, and others display primarily inattentive traits. It is possible for an individual's primary
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symptoms of ADHD to change over time.20 Children with ADHD frequently have other disorders,
with parents reporting that about half of children with ADHD have a learning disability and
about one in four have a conduct disorder.2'100
Other disorders, including anxiety disorders, depression, and learning disabilities, can be
expressed with signs and symptoms that resemble those of ADHD. A diagnosis of ADHD
requires a certain amount of judgment on the part of a doctor, similar to diagnosis of other
mental disorders. Despite the variability among children diagnosed with the disorder and the
challenges involved in diagnosis, ADHD has good clinical validity, meaning that impaired
children share similarities, exhibit symptoms, respond to treatment, and are recognized with
general consistency across clinicians.20
A great deal of research on ADHD has focused on aspects of brain functioning that are related
to the behaviors associated with ADHD. Although this research is not definitive, it has found
that children with ADHD generally have trouble with certain skills involved in problem-solving
(referred to collectively as executive function). These skills include working memory (keeping
information in mind while briefly doing something else), planning (organizing a sequence of
activities to complete a task), response inhibition (suppressing immediate responses when they
are inappropriate), and cognitive flexibility (changing an approach when a situation changes).
Children with ADHD also generally have problems in maintaining sustained attention to a task
(referred to as vigilance), and/or maintaining readiness to respond to new information
(referred to as alertness).20'101'102
While uncertainties remain, findings to date indicate that ADHD is caused by combinations of
genetic and environmental factors. 20'103~106 Much of the research on environmental factors has
focused on the fetal environment. Maternal smoking during pregnancy has been associated
with increased risk of ADHD in the child in numerous studies, however, this continues to be an
active area of research as scientists consider whether other factors related to smoking (e.g.,
genetic factors, maternal mental health, stress, alcohol use, and low birth weight) may be
responsible for associations attributed to smoking.17'19'107 Findings regarding ADHD and
maternal consumption of alcohol during pregnancy are considered more limited and
inconsistent.19'20 Preterm birth and low birth weight have also been found to increase the
likelihood that a child will have ADHD.16'18'20 Psychosocial adversity (representing factors such
as low socioeconomic status and in-home conflict) in childhood may also play a role in ADHD.108
The potential role of environmental contaminants in contributing to ADHD, either alone or in
conjunction with certain genetic susceptibilities or other environmental factors, is becoming
better understood as a growing number of studies look explicitly at the relationship between
ADHD and exposures to environmental contaminants.
Among environmental contaminants known or suspected to be developmental neurotoxicants,
lead has the most extensive evidence of a potential contribution to ADHD. A number of recent
epidemiological studies (all published since 2006, with data gathered beginning in 1999 or more
recently) conducted in the United States and Asia have reported relationships between
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increased levels of lead in a child's blood and increased likelihood of ADHD.55'109"115 In most of
these studies, blood lead levels were comparable to levels observed currently in the United
States. The potential contribution of childhood lead exposure to the risk of ADHD may be
amplified in children of women who smoked cigarettes during pregnancy.110 In addition, several
studies have reported relationships between blood lead levels and the aspects of brain
functioning that are most affected in children with ADHD, including sustained attention,
alertness, and problem-solving skills (executive functions, specifically cognitive flexibility,
working memory, planning, and response inhibition).22'44'55'116"119 Similar results have been
observed in laboratory animal studies.55'96'120"122 The NTP has concluded that childhood lead
exposure is "associated with increased diagnosis of attention-related behavioral problems."22
Although no studies evaluating a potential association between PCBs and ADHD itself have been
published, a study in Massachusetts reported a relationship between levels of PCBs measured in
cord blood and increased ADHD-like behaviors observed by teachers in children at ages 7 to 11
years. PCB levels in this study were generally lower than those measured in other epidemiological
studies of PCBs and childhood neurological development.40 Other research findings also suggest
that PCBs may play a role in contributing to ADHD. Several studies in U.S. and European
populations, most having elevated exposure to PCBs through the diet, have found generally
consistent associations with aspects of brain function that are most affected in children with
ADHD, including alertness and problem-solving skills (executive functions, specifically response
inhibition, working memory, cognitive flexibility, and planning).54'55 Studies in laboratory animals
have similar findings regarding the mental functions affected by PCB exposure.55'96
Studies of other environmental chemicals reporting associations with ADHD or related
outcomes have been published in recent years, but findings tend to be much more limited than
for lead and PCBs. Findings for phthalates and organophosphate pesticides were noted above.
In addition, three studies have reported associations between ADHD or impulsivity and
concentrations of certain perfluorinated chemicals measured in the blood of children.123"125
Studies of mercury have produced generally mixed findings of associations with ADHD or
related symptoms and mental functions.29'111'118'126"128
Learning Disability
Learning disability (or learning disorder) is a general term for a neurological disorder that
affects the way in which a child's brain can receive, process, retain, and respond to information.
A child with a learning disability may have trouble learning and using certain skills, including
reading, writing, listening, speaking, reasoning, and doing math, although learning disabilities
vary from child to child. Children with learning disabilities usually have average or above-
average intelligence, but there are differences in the way their brains process information.129
As with many other neurodevelopmental disorders, the causes of learning disabilities are not
well understood. Often learning disabilities run in the family, suggesting that heredity may play
a role in their development. Problems during pregnancy and birth, such as drug or alcohol use
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during pregnancy, low birth weight, lack of oxygen, or premature or prolonged labor, may also
lead to learning disabilities.130
As is the case with other neurodevelopmental outcomes, there are generally many more
studies of lead exposure that are relevant to learning disabilities than for other environmental
contaminants. Several studies have found associations between lead exposure and learning
disabilities or reduced classroom performance that are independent of IQ_119<120<131-133
Exposures to lead have been associated with impaired memory and difficulties or impairments
in rule learning, following directions, planning, verbal abilities, speech processing, and
classroom performance in children.22'119'131'134"137 Other findings that may indicate contributions
from environmental contaminants to learning disabilities include a study that found
associations of both maternal smoking during pregnancy and childhood exposure to
environmental tobacco smoke with parent report of a child with a learning disability
diagnosis;138 associations of prenatal mercury exposure with dysfunctions in children's language
abilities and memory,29'30 and associations of prenatal PCB exposure with poorer concentration
and memory deficits compared with unexposed children.39'45
Autism Spectrum Disorders
Autism spectrum disorders (ASDs) are a group of developmental disabilities defined by
significant social, communication, and behavioral impairments. The term "spectrum disorders"
refers to the fact that although people with ASDs share some common symptoms, ASDs affect
different people in different ways, with some experiencing very mild symptoms and others
experiencing severe symptoms. ASDs encompass autistic disorder and the generally less severe
forms, Asperger's syndrome and pervasive developmental disorder-not otherwise specified
(PDD-NOS). Children with ASDs may lack interest in other people, have trouble showing or
talking about feelings, and avoid or resist physical contact. A range of communication problems
are seen in children with ASDs: some speak very well, while many children with an ASD do not
speak at all. Another hallmark characteristic of ASDs is the demonstration of restrictive or
repetitive interests or behaviors, such as lining up toys, flapping hands, rocking his or her body,
or spinning in circles.139
To date, no single risk factor sufficient to cause ASD has been identified; rather each case is
likely to be caused by the combination of multiple genetic and environmental risk factors.140"142
Several ASD research findings and hypotheses may imply an important role for environmental
contaminants. First, there has been a sharp upward trend in reported prevalence that cannot
be fully explained by factors such as younger ages at diagnosis, migration patterns, changes in
diagnostic criteria, inclusion of milder cases, or increased parental age.8'9'143"146 Also, the
neurological signaling systems that are impaired in children with ASDs can be affected by
certain environmental chemicals. For example, several pesticides are known to interfere with
acetylcholine (Ach) and y-aminobutyric acid (GABA) neurotransmission, chemical messenger
systems that have been altered in certain subsets of autistic individuals.147 Some studies have
reported associations between certain Pharmaceuticals taken by pregnant women and
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increased incidence of autism, which may suggest that there are biological pathways by which
other chemical exposures during pregnancy could increase the risk of autism.148
Furthermore, some of the identified genetic risk factors for autism are de novo mutations,
meaning that the genetic defect is not present in either of the parents' genes, yet can be found
in the genes of the child when a new genetic mutation forms in a parent's germ cells (egg or
sperm), potentially from exposure to contaminants.140'142'149'150 Many environmental
contaminants have been identified as agents capable of causing mutations in DNA, by leading
to oxidative DNA damage and by inhibiting the body's normal ability to repair DNA damage.151
Some children with autism have been shown to display markers of increased oxidative stress,
which may strengthen this line of reasoning.152"154 Many studies have linked increasing paternal
and maternal age with increased risk of ASDs.144'146'155"157The role of parental age in increased
autism risk might be explained by evidence that shows advanced parental age can contribute
significantly to the frequency of de novo mutations in a parent's germ cells.151'158'159 Advanced
parental age signifies a longer period of time when environmental exposures may act on germ
cells and cause DNA damage and de novo mutations. Finally, a recent study concluded that the
role of genetic factors in ASDs has been overestimated, and that environmental factors play a
greater role than genetic factors in contributing to autism.141 This study did not evaluate the
role of any particular environmental factors, and in this context "environmental factors" are
defined broadly to include any influence that is not genetic.
Studies, limited in number and often limited in research design, have examined the possible
role that certain environmental contaminants may play in the development of ASDs. A number
of these studies have focused on mercury exposures. Earlier studies reported higher levels of
mercury in the blood, baby teeth, and urine of children with ASDs compared with control
children;160"162 however, another more recent study reported no difference in the blood
mercury levels of children with autism and typically developing children.163 Proximity to
industrial and power plant sources of environmental mercury was reported to be associated
with increased autism prevalence in a study conducted in Texas.164
Thimerosal is a mercury-containing preservative that is used in some vaccines to prevent
contamination and growth of harmful bacteria in vaccine vials. Since 2001, thimerosal has not
been used in routinely administered childhood vaccines, with the exception of some influenza
vaccines.165 The Institute of Medicine has rejected the hypothesis of a causal relationship
between thimerosal-containing vaccines and autism.166
Some studies have also considered air pollutants as possible contributors to autism. A study
conducted in the San Francisco Bay Area reported an association between the amount of
certain airborne pollutants at a child's place of birth (mercury, cadmium, nickel,
trichloroethylene, and vinyl chloride) and the risk for autism, but a similar study in North
Carolina and West Virginia did not find such a relationship.167'168 Another study in California
reported that mothers who lived near a freeway at the time of delivery were more likely to
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have children diagnosed with autism, suggesting that exposure to traffic-related air pollutants
may play a role in contributing to ASDs.169
Finally, a study in Sweden reported an increased risk of ASDs in children born to families living
in homes with polyvinyl chloride (PVC) flooring, which is a source of certain phthalates in indoor
environments.170
Intellectual Disability (Mental Retardation)
The most commonly used definitions of intellectual disability (also referred to as mental
retardation) emphasize subaverage intellectual functioning before the age of 18, usually
defined as an IQ less than 70 and impairments in life skills such as communication, self-care,
home living, and social or interpersonal skills. Different severity categories, ranging from mild to
severe retardation, are defined on the basis of IQ scores.171'172
"Intellectual disability" is used as the preferred term for this condition in the disabilities sector,
but the term "mental retardation" continues to be used in the contexts of law and public policy
when designating eligibility for state and federal programs.171
Researchers have identified some causes of intellectual disability, including genetic disorders,
traumatic injuries, and prenatal events such as maternal infection or exposure to alcohol.172'173
However, the causes of intellectual disability are unknown in 30-50% of all cases.173 The causes
are more frequently identified for cases of severe retardation (IQ less than 50), whereas the
cause of mild retardation (IQ between 50 and 70) is unknown in more than 75% of cases.174'175
Exposures to environmental contaminants could be a contributing factor to the cases of mild
retardation where the cause is unknown. Exposure to high levels of lead and mercury have
been associated with intellectual disability.23'176"178 Furthermore, lead, mercury, and PCBs all
have been found to have adverse effects on intelligence and cognitive functioning in
children,22'26'43'52'179 and recent studies have reported associations of a number of other
environmental contaminants with childhood IQ deficits, including organophosphate
pesticides,69"71 PBDEs,75 phthalates,79 and PAHs.83'180 Exposure to environmental contaminants
that reduce IQ has the potential to increase the proportion of the population with IQ less than
70, thus increasing the incidence of intellectual disability in an exposed population.181"183
Indicators in this Section
The four indicators that follow provide the best nationally representative data available on the
prevalence of neurodevelopmental disorders among U.S. children over time. The indicators
present the number of children ages 5 to 17 years reported to have ever been diagnosed with
ADHD (Indicator H6), learning disabilities (Indicator H7), autism (Indicator H8), and intellectual
disability (Indicator H9). These four conditions are examples of neurodevelopmental disorders
that may be influenced by exposures to environmental contaminants. Intellectual disability and
learning disabilities are disorders in which a child's cognitive or intellectual development is
affected, and ADHD is a disorder in which a child's behavioral development is affected. Autism
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spectrum disorders are disorders in which a child's behavior, communication, and social skills
are affected.
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Indicator H6: Percentage of children ages 5 to 17 years reported to have attention-
deficit/hyperactivity disorder, by sex, 1997-2010
Indicator H7: Percentage of children ages 5 to 17 years reported to have a learning
disability, by sex, 1997-2010
Indicator H8: Percentage of children ages 5 to 17 years reported to have autism,
1997-2010
Indicator H9: Percentage of children ages 5 to 17 years reported to have intellectual
disability (mental retardation), 1997-2010
About the Indicators: Indicators H6, H7, H8, and H9 present information about the number of
children who are reported to have ever been diagnosed with four different neurodevelopmental
disorders: attention-deficit/hyperactivity disorder (ADHD), learning disabilities, autism, and
intellectual disability. The data come from a national survey that collects health information from a
representative sample of the population each year. The four indicators show how the prevalence of
children's neurodevelopmental disorders has changed over time, and, when possible, how the
prevalence differs between boys and girls.
National Health Interview Survey
The National Health Interview Survey (NHIS) provides nationally representative data on the
prevalence of ADHD, learning disabilities, autism, and intellectual disability (mental retardation)
in the United States each year. NHIS is a large-scale household interview survey of a
representative sample of the civilian noninstitutionalized U.S. population, conducted by the
National Center for Health Statistics (NCHS). The interviews are conducted in person at the
participants' homes. From 1997-2005, interviews were conducted for approximately 12,000-
14,000 children annually. From 2006-2008, interviews were conducted for approximately
9,000-10,000 children per year. In 2009 and 2010, interviews were conducted for
approximately 11,000 children per year. The data are obtained by asking a parent or other
knowledgeable household adult questions regarding the child's health status. NHIS asks "Has a
doctor or health professional ever told you that had Attention
Deficit/Hyperactivity Disorder (ADHD) or Attention Deficit Disorder (ADD)? Autism? Mental
Retardation?" Another question on the NHIS survey asks "Has a representative from a school or
a health professional ever told you that had a learning disability?"
Data Presented in the Indicators
The following indicators display the prevalence of ADHD, learning disabilities, autism, and
intellectual disability among U.S. children, for the years 1997-2010. Diagnosing
neurodevelopmental disorders in young children can be difficult: many affected children may
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not receive a diagnosis until they enter preschool or kindergarten. For this reason, the
indicators here show children ages 5 to 17 years. Where data are sufficiently reliable, the
indicators provide separate prevalence estimates for boys and girls.
Although the NHIS provides national-level data on the prevalence of neurodevelopmental
disorders over a span of many years, NHIS data could underestimate the prevalence of
neurodevelopmental disorders. Reasons for underestimation may include late identification of
affected children and the exclusion of institutionalized children from the NHIS survey
population. A diagnosis of a neurodevelopmental disorder depends not only on the presence of
particular symptoms and behaviors in a child, but on concerns being raised by a parent or
teacher about the child's behavior, as well as the child's access to a doctor and the accuracy of
the doctor's diagnosis. Further, the NHIS relies on parents reporting that their child has been
diagnosed with a neurodevelopmental disorder, and the accuracy of parental responses could
be affected by cultural and other factors.
Long-term trends in these conditions are difficult to detect with certainty due to a lack of data
to track prevalence over many years, as well as changes in awareness and diagnostic criteria,
which could explain at least part of the observed increasing trends.184"186 The NHIS questions
also do not assess whether a child currently has a disorder; instead, they provide data on
whether a child has ever been diagnosed with a disorder, regardless of their current status.
Survey responses for learning disabilities may be more uncertain than for the other three
disorders presented. Whereas survey respondents are asked whether the child has been
diagnosed with ADHD, autism, or intellectual disability (mental retardation) by a health
professional, for learning disabilities an affirmative response may also include a school
representative. It is possible that some parents may respond "yes" to the question regarding
learning disabilities based on informal comments made at school, rather than a formal
evaluation to determine whether the child has any specific learning disability; similarly, they
may give a "yes" answer for children with diagnosed disorders that are not learning disabilities.
For example, parents of children with intellectual disability might also respond "yes" to the
learning disability question, thinking that any learning problems may apply, even though
intellectual disability and learning disabilities are distinct conditions.2
Because autism is the only autism spectrum disorder (ASD) referred to in the survey, it is not
clear how parents of children with other ASDs, i.e., Asperger's syndrome and PDD-NOS, may
have responded. The estimates shown by Indicator H8 could represent underestimates of ASD
prevalence if parents of children with Asperger's syndrome and PDD-NOS did not answer yes to
the NHIS questions about autism.
In addition to the data shown in the indicator graphs, supplemental tables provide information
regarding the prevalence of neurodevelopmental disorders for different age groups and
prevalence by race/ethnicity, sex, and family income. These comparisons use the most current
four years of data available. The data from four years are combined to increase the statistical
reliability of the estimates for each race/ethnicity, sex, and family income group. The tables
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include prevalence estimates for the following race/ethnicity groups: White non-Hispanic, Black
non-Hispanic, Asian non-Hispanic, Hispanic, and "All Other Races." The "All Others Races"
category includes all other races not specified, together with those individuals who report more
than one race. The limits of the sample design and sample size often prevent statistically
reliable estimates for smaller race/ethnicity groups. The data are also tabulated for three
income groups: all incomes, income below the poverty level, and greater than or equal to the
poverty level.
Please see the Introduction to the Health section for discussion of statistical significance testing
applied to these indicators.
Other Estimates of ADHD and Autism Prevalence
In addition to NHIS, other NCHS studies provide data on prevalence of ADHD and ASDs among
children. The National Survey of Children's Health (NSCH), conducted in 2003 by NCHS, found
that 7.8% of children ages 4 to 17 years had ever been diagnosed with ADHD. The same survey,
when conducted again in 2007, found that 9.5% of children ages 4 to 17 years had ever been
diagnosed with ADHD.7 Both estimates are somewhat higher than the ADHD prevalence
estimates from the NHIS for those years. The 2007 NSCH also estimates that 7.2% of children
ages 4 to 17 years currently have ADHD. The 2007 NSCH also provides information at the state
level: North Carolina had the highest rate, with 15.6% of children ages 4 to 17 years having ever
been diagnosed with ADHD; the rate was lowest in Nevada, at 5.6%.7
In 2002 and 2006, the Centers for Disease Control and Prevention performed thorough data
gathering in selected areas to examine the prevalence of ASDs in eight-year-old children. The
ASD prevalence estimate for 2002 was 0.66%, or 1 in 152 eight-year-old children, and the
estimate for 2006 was 0.9%, or 1 in 110 eight-year-old children.8'187 The 2007 NSCH also provides
an estimate of 1.1% of children ages 3 to 17 years reported to have ASDs, or about 1 in 90.188
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Indicator H6
Percentage of children ages 5 to 17 years reported to have
attention-deficit/hyperactivity disorder, by sex, 1997-2010
2000 2002 2004 2006 2008 2010
Data: Centers for Disease Control and Prevention, National Center for Health Statistics,
National Health Interview Survey
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Data characterization
Data for this indicator are obtained from an ongoing annual survey conducted by the National Center for
Health Statistics.
Survey data are representative of the U.S. civilian noninstitutionalized population.
A parent or other knowledgeable adult in each sampled household is asked questions regarding the child's
health status, including if they have ever been told the child has Attention Deficit/Hyperactivity Disorder
(ADHD).
From 1997 to 2010, the proportion of children ages 5 to 17 years reported to have ever
been diagnosed with attention-deficit/hyperactivity disorder (ADHD) increased from 6.3%
to 9.5%.
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• The increasing trend was statistically significant for children overall, and for both boys
and girls considered separately.
For the years 2007-2010, the percentage of boys reported to have ADHD (12.4%) was
higher than the rate for girls (5.7%). This difference was statistically significant. (See Table
H6a.)
In 2007-2010, 11.6% of children of "All Other Races," 10.7% of White non-Hispanic children,
10.2% of Black non-Hispanic children, 4.8% of Hispanic children, and 1.7% of Asian non-
Hispanic children were reported to have ADHD. (See Table H6b.)
• These differences were statistically significant, after accounting for the influence of
other demographic differences (i.e., differences in age, sex, and family income), with
two exceptions: there was no statistically significant difference between children of "All
Other Races" and White non-Hispanic children, or between children of "All Other Races"
and Black non-Hispanic children.
In 2007-2010, 11.3% of children from families living below the poverty level were reported
to have ADHD compared with 8.6% of children from families living at or above the poverty
level. This difference was statistically significant. (See Table H6b.)
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Indicator H7
Percentage of children ages 5 to 17 years reported to have a learning
disability, by sex, 1997-2010
2000 2002 2004 2006 2008 2010
Data: Centers for Disease Control and Prevention, National Center for Health Statistics,
National Health Interview Survey
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Data characterization
Data for this indicator are obtained from an ongoing annual survey conducted by the National Center for
Health Statistics.
Survey data are representative of the U.S. civilian noninstitutionalized population.
A parent or other knowledgeable adult in each sampled household is asked questions regarding the child's
health status, including if they have ever been told the child has a learning disability.
In 2010, 8.6% of children ages 5 to 17 years had ever been diagnosed with a learning
disability. There was little change in this percentage between 1997 and 2010.
For the years 2007-2010, the percentage of boys reported to have a learning disability
(10.9%) was higher than for girls (6.6%). This difference was statistically significant. (See
Table H7a.)
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The reported prevalence of learning disability varies by race and ethnicity. The highest
percentages of learning disability are reported for children of "All Other Races" (11.2%),
Black non-Hispanic children (10.2%), and White non-Hispanic children (9.3%). By comparison,
7.2% of Hispanic children are reported to have a learning disability, and Asian non-Hispanic
children have the lowest prevalence of learning disability, at 2.7%. (See Table H7b.)
• The prevalence of learning disability reported for Hispanic children and for Asian non-
Hispanic children were lower than for the remaining race/ethnicity groups, and these
differences were statistically significant. The difference in prevalence between Hispanic
and Asian non-Hispanic children was also statistically significant.
For the years 2007-2010, the percentage of children reported to have a learning disability
was higher for children living below the poverty level (12.6%) compared with those living at
or above the poverty level (7.9%), a statistically significant difference. (See Table H7b.)
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Indicator H8
Percentage of children ages 5 to 17 years reported to have autism, 1997-2010
2000 2002 2004 2006 2008 2010
Data: Centers for Disease Control and Prevention, National Center for Health Statistics,
National Health Interview Survey
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* The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate).
Data characterization
Data for this indicator are obtained from an ongoing annual survey conducted by the National Center for
Health Statistics.
Survey data are representative of the U.S. civilian noninstitutionalized population.
A parent or other knowledgeable adult in each sampled household is asked questions regarding the child's
health status, including if they have ever been told the child has autism.
• The percentage of children ages 5 to 17 years reported to have ever been diagnosed with
autism rose from 0.1% in 1997 to 1.0% in 2010.This increasing trend was statistically
significant.
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For the years 2007-2010, the rate of reported autism was more than three times higher in
boys than in girls, 1.5% and 0.4%, respectively. This difference was statistically significant.
(See Table H8a.)
The reported prevalence of autism varies by race/ethnicity. The highest prevalence of
autism is for children of "All Other Races" (1.7%) and White non-Hispanic children (1.1%).
Autism prevalence was lower among Asian non-Hispanic children (0.8%), Black non-Hispanic
children (0.7%), and Hispanic children (0.6%). (See Table H8b.)
• The prevalence of autism for both White non-Hispanic children and children of "All
Other Races" was statistically significantly different from the prevalence for both Black
non-Hispanic children and Hispanic children.
For the years 2007-2010, the prevalence of autism was similar for children living below the
poverty level and those living at or above the poverty level. (See Table H8b.)
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Indicator H9
Percentage of children ages 5 to 17 years reported to have intellectual
disability (mental retardation), 1997-2010
2000 2002 2004 2006 2008 2010
Data: Centers for Disease Control and Prevention, National Center for Health Statistics,
National Health Interview Survey
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Data characterization
Data for this indicator are obtained from an ongoing annual survey conducted by the National Center for
Health Statistics.
Survey data are representative of the U.S. civilian noninstitutionalized population.
A parent or other knowledgeable adult in each sampled household is asked questions regarding the child's
health status, including if they have ever been told the child has mental retardation.
i In 2010, 0.7% of children ages 5 to 17 years were reported to have ever been diagnosed
with intellectual disability (mental retardation). There was little change in this percentage
between 1997 and 2010.
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Health | Neurodevelopmental Disorders
In 2007-2010, the percentage of boys reported to have intellectual disability (0.9%) was
higher than for girls (0.6%). This difference was statistically significant. (See Table H9a.)
In 2007-2010, there was little difference by race/ethnicity in the reported prevalence of
intellectual disability. (See Table H9b.)
In 2007-2010, 1.2% of children from families with incomes below the poverty level were
reported to have intellectual disability, compared with 0.7% of children from families at or
above the poverty level, a statistically significant difference. (See Table H9b.)
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Obesity | Health
Obesity
Obesity is the term used to indicate the high range of weight for an individual of given height
that is associated with adverse health effects.1 Definitions of overweight and obesity for adults
are based on set cutoff points directly related to an individual's body mass index (BMI, weight
in kilograms divided by the square of height in meters). Essential to this definition is that a high
degree of body weight be associated with a large amount of body fat. The BMI is correlated to
body fat, but BMI varies with age and sex in children more than it does in adults. Thus the
designation of a child or adolescent (ages 2 to 19 years) as either overweight or obese is based
on comparing his or her BMI to a sex- and age-specific reference population (the CDC growth
charts). Children and adolescents between the 85th and 94th percentiles of BMI-for-age are
considered overweight; those greater than or equal to the 95th percentile are considered obese.
The percentiles used to identify children as overweight or obese are fixed, and based on data
collected from 1963-1980 (or, for children ages 2 to 6 years, data from 1963-1994).1"3
The prevalence of excessive body weight in the United States population has been increasing
for several decades, though it has stabilized over the last several years.4"7 BMI is the most
common screening measure used to determine whether an individual may be overweight or
obese. The BMI does not measure body fat directly, but is used as a surrogate measure since it
correlates with direct measures of body fat, especially at high BMI levels, and is inexpensive and
easy to obtain in a clinical setting. The significance of a child being overweight is complicated by
the BMI's inability to distinguish between differences in mass due to muscle or due to the
unhealthy accumulation of fatty tissue. A recent study found that less than half of "overweight"
children had excess body fat, and that there are differences among race/ethnicity groups in the
amount of body fat for a given BMI in children.8 Among children with an elevated BMI, some
may have excess body fat, and others may be incorrectly identified as overweight because they
have a higher amount of mass attributed to nonfatty tissue. Despite the limitations imposed by
measuring the BMI, a rise in the prevalence of overweight children is cause for concern, since
overweight children are more likely to become overweight or obese adults.9"11
Obesity has rapidly become a serious public health concern in the United States, and is
associated with several adverse health effects in childhood and later in life, including
cardiovascular disease risk factors (which includes hypertension and altered lipid levels),12"22
cancer,15'23'24 psychological stress,25"28 asthma,29"31 and diabetes.32"37 Some studies have found a
relationship between obesity and early onset of puberty and early menarche in girls,38"40
although other research has found differences in the timing of puberty even after controlling
for BMI in the population.41
to early puberty is unclear.
for BMI in the population.41 As such, the extent to which the obesity epidemic may contribute
An emerging body of research suggests there may be common biological mechanisms
underlying a cluster of adverse health effects (obesity, hypertension, altered lipid levels, and
other metabolic abnormalities) referred to as metabolic syndrome. While the clinical utility of a
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diagnosis of metabolic syndrome is debated in the medical literature,42"44 the term describes an
area of active research, and prospective data demonstrate the relevance of metabolic
syndrome in obese children for both type 2 diabetes45 and cardiovascular disease.46 Metabolic
syndrome has been identified in obese children and adolescents, and studies suggest a
developmental origin of the condition.47"49 The consideration of obesity and metabolic effects
as a group is supported by findings in laboratory animals, where early-life exposure to certain
organophosphate pesticides can disrupt adult lipid metabolism, induce weight gain, and cause
other metabolic responses that mimic those seen in diabetes and obesity.50"52 Given these
relationships, obesity and other health conditions related to metabolism are discussed below.
Obesity is due primarily to an imbalance between caloric intake and activity. Increased caloric
intake and reduced physical activity are likely the major drivers of obesity in children.
Researchers are also investigating whether exposures to certain environmental chemical
exposures may play a contributing role in childhood obesity.53'54 These chemicals, which are
referred to as obesogens, are thought to be capable of disrupting the human body's regulation
of metabolism and the accumulation of fatty tissue.55 Studies have also reported associations
between exposure to certain chemicals and diabetes in adults. Diabetes (Type 2) results from
the body's inability to regulate blood sugar levels with insulin in response to dietary intake, and
is positively associated with the increasing rates of obesity seen in the U.S. population.56 Excess
body weight is a risk factor for Type 2 diabetes. In the past, Type 2 diabetes has been diagnosed
almost exclusively in adult populations, but it is now being diagnosed in youth—although with
low prevalence (0.25%).56"59 However, the clinical designation of prediabetes (elevated blood
glucose levels that do not meet the diagnostic criteria for diabetes) is prevalent in obese youth.35
While the possible contribution of chemical exposures to obesity is not clear, a number of
animal and cellular studies provide some evidence that environmental chemical exposures may
contribute to obesity and diabetes. Studies finding associations between chemical exposures
and obesity in children are limited. A recent study reported that prenatal exposure to high
levels of hexachlorobenzene was associated with increased BMI and weight in children at 6.5
years.60 Another recent study in Belgium, at relatively high exposure levels within the general
population, reported an association between prenatal exposure to DDE (the primary metabolite
of the pesticide DDT) and BMI, as well as an association between exposure to polychlorinated
biphenyls (PCBs) and increased BMI during early childhood.61 In adults, associations have been
reported between diabetes and both PCBs and dioxins at levels of exposure seen in the U.S.
population.62'63 A study of adult occupational exposures to organochlorine and
organophosphate pesticides reported an increased risk of diabetes in exposed workers.64
However, other studies have reported no association between these exposures and markers of
obesity or diabetes.65"68 Several animal and cellular studies suggest that endocrine-disrupting
chemicals (including bisphenol A, diethylstilbestrol, and tributyltin) may contribute to increased
weight and diabetes.69"73 After reviewing these findings, scientists at a National Toxicology
Program-sponsored workshop concluded that existing research provides evidence of plausibility
(varying from "suggestive" to "strong" evidence) that several environmental chemicals could
contribute to obesity and/or diabetes.74 For example, scientists concluded that the available
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data support the biological plausibility that exposure to a number of classes of pesticides may
affect risk factors for obesity and diabetes. The National Institutes of Health Strategic Plan for
Obesity Research and the White House Task Force on Childhood Obesity Report to the
President also acknowledge a potential relationship between environmental exposures and
obesity and cite the need for further research.75'76
Research has also considered a role for air pollution in childhood obesity and diabetes. In one
recent study, adult mice fed a high-fat diet and exposed to concentrated particulate air
pollution (PM2.5) experienced an increase in blood glucose levels and insulin resistance, which
are precursors of diabetes.77 Other studies in animals and children have reported that obesity
may result in greater susceptibility to the adverse effects of airborne pollutants such as PM2.5
and ozone, including airway inflammation, cardiovascular effects, and increased deposition of
particles in the lungs.30'78'79 Air pollution may contribute to childhood obesity by limiting the
number of days when air quality is appropriate for outdoor recreational activity, particularly in
children with pre-existing respiratory conditions such as wheeze and asthma.80 Animal studies
further suggest that diet-induced obesity may increase susceptibility to the effects of
environmental toxicants such as PCBs, dioxins, and acrylamide.81"83
Other environmental factors are thought to contribute to the increasing rates of overweight
and obesity seen in the U.S. population. The term "built environment" is used to describe the
physical elements of the environment for a population.84'85 Multiple reviews of the literature
have concluded that several properties of the built environment, including the extent of urban
sprawl, housing density, access to food outlets, and access to recreational facilities, may be
associated with overweight and obesity and/or levels of physical activity in children.84"90 The
relationship between characteristics of the built environment and obesity is likely more
significant in children than adults, because children are less able to leave their local
environment without the help of an adult.91'92 Built environments that promote exercise
through the inclusion of nearby recreational areas and walkable communities, and those that
provide healthy eating options through reducing the number of fast food restaurants while
providing access to fresh produce, are thought to reduce the frequency of obesity in
children.84'85'93 "Green" environments that contain a greater number of natural environments
and features such as parks, trees, and nature trails, may contribute to increased levels of
physical activity in children that can reduce rates of obesity.94
Socioeconomically disadvantaged populations are more likely to be located in built
environments with characteristics that promote lifestyles that increase rates of obesity in
children.95"97 However, a child living in a suburban community with a higher socioeconomic
status may spend greater amounts of time commuting in a car rather than walking, which may
also contribute to a sedentary lifestyle that promotes obesity.98'99 Factors contributing to the
prevalence of obesity may differ among environments. Previous research had suggested that
differences in obesity rates in rural or urban environments were small.100'101 However, other
recent studies have identified a higher prevalence of obesity in rural compared to urban
environments.87'102 The complex interplay of behavioral, environmental, and physiological
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factors and the disparities in pediatric obesity observed in the population add to the difficulty in
identifying effective interventions.
The following indicators present the best nationally representative data on obesity in the U.S.
child population. The first indicator shows the prevalence of obesity among children ages 2 to 17
years from 1976-2008. The second indicator presents the current prevalence of obesity by
race/ethnicity and family income, using data from 2005-2008. Together these indicators
highlight basic trends and current status in prevalence of childhood obesity in the United States.
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Indicator H10: Percentage of children ages 2 to 17 years who were obese, 1976-2008
Indicator Hll: Percentage of children ages 2 to 17 years who were obese, by
race/ethnicity and family income, 2005-2008
About the Indicators: Indicators H10 and Hll present the prevalence of obesity in U.S. children ages
2 to 17 years. The data are from a national survey that measures weight and height in a
representative sample of the U.S. population every two years. Indicator H10 shows the trend in
obesity prevalence from 1976-2008. Indicator Hll presents comparisons of current obesity rates in
children of different race/ethnicities and income levels, using data for 2005-2008.
NHANES
The National Health and Nutrition Examination Survey (NHANES) provides data on childhood
obesity in the United States. NHANES is a nationally representative survey of the health and
nutritional status of the civilian noninstitutionalized U.S. population, conducted by the National
Center for Health Statistics. Interviews and physical examinations are conducted with
approximately 10,000 people in each two-year year survey cycle. Height and weight are
measured for survey participants of all ages.
Obesity and BMI
Determination of obesity in children is based on the calculation of body mass index (BMI),
which is correlated with body fat.103 First, the BMI is calculated by dividing an individual's
weight in kilograms by the square of his or her height in meters. For children and teenagers in
the United States, the BMI number is then compared with an age- and sex-specific reference
population based on the 2000 CDC growth charts. These charts are based on national data
collected from 1963-1994 for children 2 through 6 years of age and from 1963-1980 for
children ages 7 years and older.2 These growth charts apply to all racial and ethnic groups, and
were obtained from nationally representative surveys. Children and teenagers with BMIs at or
above the 95th percentile on the growth charts are classified as obese.1'3
Data Presented in the Indicators
Indicator H10 presents the percentage of children ages 2 to 17 years who were obese from
NHANES surveys conducted from 1976 through 2008. Indicator Hll presents the current
prevalence of childhood obesity by race/ethnicity and family income using the 2005-2006 and
2007-2008 surveys combined. The data from two NHANES cycles are combined to increase the
statistical reliability of the estimates for each race/ethnicity and income group, and to reduce
any possible influence of geographic variability that may occur in two-year NHANES data. Four
race/ethnicity groups are presented in Indicator Hll: White non-Hispanic, Black non-Hispanic,
Mexican-American, and "All Other Races/Ethnicities." The "All Other Races/Ethnicities"
category includes all other races and ethnicities not specified, together with those individuals
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who report more than one race. The limits of the sample design and sample size often prevent
statistically reliable estimates for smaller race/ethnicity groups. The data are also tabulated
across three income categories: all incomes, below the poverty level, and greater than or equal
to the poverty level.
Please see the Introduction to the Health section for discussion of statistical significance testing
applied to these indicators.
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Indicator H10
Percentage of children ages 2 to 17 years who were obese, 1976-2008
1988- 1991-
1991 1994
1999- 2001- 2003- 2005- 2007-
2000 2002 2004 2006 2008
Data: Centers for Disease Control and Prevention, National Center for Health Statistics,
National Health and Nutrition Examination Survey
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Data characterization
Data for this indicator are obtained from an ongoing continuous survey conducted by the National Center
for Health Statistics.
Survey data are representative of the U.S. civilian noninstitutionalized population.
Height and weight are measured in individual survey participants.
i Between 1976-1980 and 2007-2008, the percentage of children identified as obese showed
an increasing trend. In 1976-1980, 5% of children ages 2 to 17 years were obese. This
percentage reached a high of 17% in 2007-2008. Between 1999-2000 and 2007-2008, the
percentage of children identified as obese remained between 15% and 17%.
• From 1976-2008, the increasing trend in prevalence of obese children was statistically
significant for children overall, and for children of each race/ethnicity (See Table H10)
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Health | Obesity
and age group (Table HlOa). From 1999-2008, the trends were not statistically
significant for each of these groups.
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Obesity | Health
Indicator H11
Percentage of children ages 2 to 17 years who were obese, by race/ethnicity
and family income, 2005-2008
All
Incomes
At or
Above
Poverty
Level
All Races/Ethnicities
White non-Hispan
-American
All Other Races/Ethnicities
All Races/Ethnicities
White non-Hispanic
Below
Poverty
Level
All Other Races/Ethnicities
All Races/Ethnicities
White non-Hispanic
All Other Races/Ethnicities
Data: Centers for Disease Control and Prevention, National Center for Health Statistics,
National Health and Nutrition Examination Survey
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Data characterization
Data for this indicator are obtained from an ongoing continuous survey conducted by the National Center
for Health Statistics.
Survey data are representative of the U.S. civilian noninstitutionalized population.
Height and weight are measured in individual survey participants.
In 2005-2008,16% of children ages 2 to 17 years were classified as obese.
In 2005-2008, a higher percentage of Mexican-American and Black non-Hispanic children
were obese at 22% and 20%, respectively, compared with 14% of White non-Hispanic
children and 14% of children of "All Other Races/Ethnicities."
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• The greater prevalence of obesity among Mexican-American and Black non-Hispanic
children, compared with the lower prevalence among White non-Hispanic children and
children of "All Other Races/Ethnicities," was statistically significant.
Among children overall, the prevalence of obesity was greater in children with family
incomes below poverty level than in those above poverty level. However, when accounting
for differences by race/ethnicity as well as poverty status, children of "All Other
Races/Ethnicities" were the only group to have a statistically significant association between
low family income and higher prevalence of obesity.
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Adverse Birth Outcomes | Health
Adverse Birth Outcomes
The period of gestation is a crucial determinant of an infant's health and survival for years to
come. Two measures that may be used to understand the quality of an infant's gestation are 1)
length of gestation (pregnancy length) and 2) birth weight. Normal term pregnancies last
between 37 and 41 completed weeks, allowing for more complete development of an infant's
organs and systems.1 Preterm birth is defined as a live birth before 37 completed weeks of
gestation.1 Birth weight is determined by two factors: length of gestation and fetal growth (the
rate at which an infant develops and increases in size). Low birth weight infants are defined as
weighing less than 2,500 grams (about 5 pounds, 8 ounces).2 Infants may be born with a low
birth weight because they were born early, because their growth while in utero has been
restricted, or both. Because they have had sufficient time to develop, infants born at term with
low birth weight are usually considered growth restricted. Because birth weight alone does not
always indicate whether an infant's fetal growth has been restricted, other measurements such
as birth length, head circumference, and abdominal circumference are also used.
Other adverse birth outcomes that are not discussed here include post-term birth, high birth
weight, neonatal mortality, and birth defects, a specific group of adverse birth outcomes that
include structural and functional abnormalities.
Preterm and low birth weight infants are at greater risk for mortality and a variety of health and
developmental problems. As a result, the birth of a preterm or low birth weight infant can have
significant emotional and economic effects on the infant's family.3 Conditions related to
preterm birth and low birth weight are the second leading cause of infant death in the United
States (after birth defects).4 The infant mortality rate for low birth weight infants is about 25
times that of the infant mortality rate for normal weight babies. Likewise, the infant mortality
rate for late preterm babies (34-36 weeks of gestation) is about three times the infant
mortality rate for term babies, and the infant mortality rate for very preterm babies (less than
32 weeks of gestation) is 75 times that of term babies.4 Preterm infants may experience
complications such as acute respiratory, gastrointestinal, immunologic, and central nervous
system problems. Longer-term effects of preterm birth, including motor, cognitive, visual,
hearing, behavioral, social-emotional, health, and growth problems, may not become apparent
for years and may persist throughout a child's life into adulthood. It is important to recognize
that not all infants born before 37 completed weeks have the same risk of adverse health
outcomes. As gestational age decreases, the risk of morbidity and mortality increases greatly.
Also, recent research suggests that even early term births, those at 37 or 38 weeks, are at
increased risk of respiratory and other adverse neonatal outcomes.5"7
Because many of the effects of low birth weight are due to being born immature and
unprepared for life outside the womb, morbidities associated with low birth weight often
overlap with those of preterm birth. Low birth weight infants are more likely to have
underdeveloped lungs and breathing problems; heart problems (which can lead to heart
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Health I Adverse Birth Outcomes
failure); immature and improperly functioning livers; too many or too few red blood cells
(polycythemia or anemia); inadequate body fat, leading to trouble maintaining a normal body
temperature; feeding problems; and increased risk of infection.2 Furthermore, the process of
growth restriction may exert its own negative effects aside from often producing low birth
weight infants. Data suggest that fetuses with a declining growth rate may make adaptations,
such as preserving brain growth, in order to survive adverse intrauterine conditions. Such
adaptations can have physiological costs, and may have effects on fetal brain development,
cardiac and renal function, and adult health.8 The theory of fetal origins of adult disease
postulates that certain types of chemical, nutritional, or stress-related exposures in utero can
alter the programming of fetal cells in ways that are not apparent at birth, but are predictive of
disease risk later in life. Birth weight and measures of growth restriction are used as proxies for
these changes and have been associated with diseases in adulthood, including cardiovascular
disease, obesity, metabolic disorders, and cancer.9
For many years, the rates of both preterm birth and low birth weight have been increasing;10
however, starting in 2006 this pattern seems to be partially reversing as the rate of preterm
birth is now declining. A number of factors may contribute to increasing rates of preterm birth
and low birth weight, including increases in maternal age, rates of multiple births (e.g., twins,
triplets), use of early Cesarean sections and labor inductions, changes in neonatal technology,
and use of assisted reproductive technologies (e.g., in vitro fertilization).3 Multiple births run a
higher risk of preterm birth and low birth weight, and the rates of multiple births have
increased in recent decades. The rate of twin births increased 70% from 1980-2004, but has
been essentially stable since that time. The rate of triplet and higher-order births increased
400% from 1980 to 1998, but since that time has been trending downward.11 Advances in
medical technology that allow for resuscitation of infants born at increasingly early gestational
ages may also contribute to the increase in percentage of births that are preterm, since many of
those infants would not have survived previously and thus would have be characterized as fetal
deaths. Other factors linked to preterm birth and low birth weight include birth defects; chronic
maternal health problems (e.g., high blood pressure); maternal use of tobacco, alcohol, and
illicit drugs; maternal and fetal infections; placental problems; inadequate maternal weight
gain; and socioeconomic factors (e.g., low income and poor education).12"16
Rates of low birth weight and preterm birth can vary greatly by maternal race/ethnicity. Black
women have consistently had higher rates of preterm and low birth weight babies.17 While it
has been suggested that race is a proxy for differences in socioeconomic status (SES), most
studies that have controlled for differences in SES continue to find persistent birth outcomes
differences between Black and White women.17"20 Similarly, studies that have adjusted for
other risk factors, such as risky behavior during pregnancy and use of prenatal care, have found
these persistent Black-White differences in birth outcomes as well.4'21'22
While maternal characteristics and obstetric practices play an important role in preterm birth
and low birth weight, other factors—including environmental contaminants—may also
contribute to adverse birth outcomes.23 A growing number of studies have examined the
possible role that exposure to environmental contaminants may play in the causation of
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Adverse Birth Outcomes | Health
preterm birth and low birth weight. The evidence is particularly strong for environmental
tobacco smoke (ETS) and lead. The Surgeon General has determined that exposure of pregnant
women to ETS causes a small reduction in mean birth weight, and that the evidence is
suggestive (but not sufficient to infer causation) of a relationship between maternal exposure
to environmental tobacco smoke during pregnancy and preterm delivery.24 The National
Toxicology Program has concluded that maternal exposure to lead is known to cause reduced
fetal growth, and that there is limited evidence of an association with preterm birth.25
In recent years, the potential effects of common air pollutants on adverse birth outcomes have
received more attention. A number of large epidemiological studies (many with 10,000+
participants) from several countries have identified potential links between elevated levels of
exposure to particulate matter (PM), sulfur dioxide (S02), nitrogen dioxide (N02), and carbon
monoxide (CO) exposure and outcomes such as decreased fetal growth, low birth weight, and
preterm birth.26"40 Several of these studies have identified such links to adverse birth outcomes
even in regions with relatively low ambient air pollution levels.27'29'33'36 In such epidemiological
studies, researchers make an effort, when data are available, to adjust for other factors that
may also lead to an increased risk of low birth weight or preterm birth, such as mother's age,
smoking status, race, and income.41 Articles reviewing the findings from these studies have
generally concluded that these air pollutants likely have an adverse effect on birth outcomes,
although methodological inconsistencies across studies have made definitive conclusions
difficult.42"45 In addition, studies have reported associations between elevated levels of
exposure to airborne polycyclic aromatic hydrocarbons (PAHs), generated largely by fossil fuel
combustion, and reduced birth weight and fetal growth restriction, especially when in
combination with ETS exposure.46"49 Other studies have reported associations between living in
proximity to traffic during pregnancy and increased risk of preterm birth and low birth weight,
although an extensive review study concluded that there is inadequate and insufficient
evidence to infer a causal relationship.50"54
In addition to air pollutants, several other environmental chemicals have been studied for
possible roles in contributing to adverse birth outcomes. A handful of studies with typical
population-level exposure levels have reported associations between prenatal exposure to
some phthalates and preterm birth, shorter gestational length, and low birth weight; however,
one study reported phthalate exposure to be associated with longer gestational length and
increased risk of delivery by Cesarean section.55"59
A limited number of studies suggest that prenatal exposure to another class of chemicals,
polychlorinated biphenyls (PCBs), may lead to preterm birth and low birth weight or otherwise
restrict fetal growth.60"63 One study examining women from the Danish National Birth Cohort
reported that elevated exposure to PCBs from fatty fish consumption was associated with lower
birth weight. The study found that infants born to highly exposed women weighed, on average,
about 5.5 ounces less than infants born to women with relatively low PCB exposure.64 Another
study looked at a historical cohort of women who were pregnant prior to the 1979 ban of PCBs,
and did not observe any relation between levels of PCB exposure and low birth weight or
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Health I Adverse Birth Outcomes
shorter pregnancy length.65 Some human health studies have reported associations between
prenatal exposure to perfluorinated compounds (PFCs)—particularly perfluorooctane sulfonic
acid (PFOS) and perfluorooctanoic acid (PFOA)—and a range of adverse birth outcomes, such as
low birth weight, decreased head circumference, reduced birth length, and smaller abdominal
circumference.66"70 However, there are inconsistencies in the results of these studies, and two
other studies did not find an association between prenatal PFC exposure and birth weight.71'72
The participants in all of these studies had PFC blood serum levels comparable to levels in the
general population. Studies of disinfection byproducts in drinking water as possible causes of
adverse birth outcomes are also conflicting, with recent evidence indicating that there may be
no effect on preterm birth.73"75 Studies of arsenic in drinking water and birth outcomes have
produced similarly mixed results.76"78 For the following environmental contaminants, there is
some evidence from animal studies and a limited number of studies in humans of possible
associations with adverse birth outcomes, particularly reduced fetal growth: benzene,79
herbicides,80 bisphenol A (BPA),81 dioxins and dioxin-like chemicals,82 and manganese.83
This section presents two indicators of adverse birth outcomes: Indicator H12 presents the rate
of preterm birth, and Indicator HIS presents the rate of term low birth weight. These two
indicators were chosen because for each there is a wealth of quality data available.
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Indicator H12: Percentage of babies born preterm, by race/ethnicity, 1993-2008
Indicator H13: Percentage of babies born at term with low birth weight, by
race/ethnicity, 1993-2008
About the Indicator: Indicator H12 shows the percentage of babies born preterm, and Indicator H13
shows the percentage of babies who are born at term with low birth weight. Both graphs show
separate lines for the different race/ethnicity groups. The data come from a national data system
that collects data from birth certificates for virtually every baby born in the United States each year.
Indicators H12 and H13 show the change in preterm and term low birth weight over time.
The National Vital Statistics System
The National Vital Statistics System (NVSS), operated by the National Center for Health
Statistics (NCHS), provides national data on gestational ages and birth weights. The NVSS data
are provided through contracts between the NCHS and vital registration systems operated in
each state, which are legally responsible for the registration of vital events including births,
deaths, marriages, divorces, and fetal deaths. The collection and publication of this information
is mandated by federal law. Together NCHS and the states have developed standard forms and
procedures to use for the data collection. The NVSS captures virtually all of the births occurring
in the United States. The most current NVSS data available are for 2008.
Birth certificates provide information on characteristics of both the infant and his/her parents,
including the weight of the infant and the length of gestation. Length of gestation is recorded in
completed weeks, so for example a pregnancy of 36 weeks and 6 days would be recorded as 36
weeks, and would therefore be considered preterm.3 Pregnancy duration is most often
estimated from the date of a woman's last menstrual period. Many factors, including age, levels
of physical activity, and body mass, can cause variation in menstrual cycle timing, making this
method of estimating gestational length subject to some error.3 NVSS data report pregnancy
duration based on a clinical estimation, often determined using ultrasound, if information on
last menstrual period is unavailable or is inconsistent with the reported birth weight. Because
ultrasound measurements tend to give lower gestational age estimates than last menstrual
period,3 the slight increase in use of ultrasound data in recent years could contribute to any
increase in the rate of preterm birth.
Data Presented in the Indicators
Indicator H12 displays the trend in the percentage of preterm births for all births (singletons, as
well as multiples), with a separate line for each maternal race/ethnicity group and a single line
for all maternal races and ethnicities combined for the years 1993-2008.
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Indicator HIS displays the trend in the percentage of low birth weight births at term among all
births (singletons, as well as multiples), with a separate line for each maternal race/ethnicity
group and a single line for all maternal races and ethnicities combined for the years 1993-2008.
Presentation of low birth weight data for only term births (babies with a gestational age of 37
completed weeks or more) is intended to identify trends in growth restriction separate from
trends in gestational duration. This indicator does not include all infants with low birth weight,
nor does it include all infants who are growth-restricted; therefore, it is designed as a
surveillance tool and not as a way to identify a group of infants that are particularly at risk for
adverse health effects.
Five maternal race/ethnicity groups are presented in these indicators: White non-Hispanic,
Black non-Hispanic, Hispanic, American Indian/Alaska Native non-Hispanic, and Asian Pacific
Islander non-Hispanic. Prior to the year 1993, not all states recorded Hispanic origin on birth
certificates; for this reason, both Indicator H12 and H13 begin with data from 1993. Birth
certificates do not include information on family or maternal income, so it is not possible to
examine differences or trends by income level.
The indicator graphs show data for all births, singletons and multiples combined. The rates for
singletons and multiples are provided in supplemental data tables. Additional supplemental
tables highlight differences in rates of preterm birth and term low birth weight by age of the
mother.
Please see the Introduction to the Health section for discussion of statistical significance testing
applied to these indicators. The NVSS records virtually all births in the United States—
approximately 4 million per year. Because of this very large sample size, differences in birth
outcomes that appear to be small in magnitude may be found to be statistically significant.
Extensive research has been conducted with NVSS data to assess the presence of statistically
significant trends and demographic differences, including analyses with much more detail than
the one conducted here.23'84'85
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Indicator H12
Percentage of babies born preterm, by race/ethnicity, 1993-2008
Black non-Hispanic
American Indian/Alaska Native
non-Hispanic
White non-Hispanic
Asian or Pacific Islander
non-Hispanic
1996 1998 2000 2002 2004 2006 2008
Data: Centers for Disease Control and Prevention, National Center for Health Statistics,
National Vital Statistics System
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Data characterization
Data from this indicator are obtained from a database maintained by the National Center for Health
Statistics.
The database collects information from birth certificates for virtually all births in the United States.
Length of gestation is recorded on each birth certificate.
Between 1993 and 2008, the rate of preterm birth showed an increasing trend, ranging
from 11.0% in 1993 to its highest value of 12.8% in 2006. This increasing trend was
statistically significant.
In 2008, Black non-Hispanic women had the highest rate of preterm birth, compared with
women of other races/ethnicities. More than 1 in 6 infants born to Black non-Hispanic
women were born prematurely in that year.
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Health I Adverse Birth Outcomes
• The difference between the rate of preterm birth for Black non-Hispanic women and the
rates for the other race/ethnicity groups was statistically significant.
Between 1993 and 2008, the preterm birth rate showed an increasing trend for each
race/ethnicity group except Black non-Hispanic women. The preterm birth rate for Black
non-Hispanic women stayed relatively constant, ranging between 17% and 19%.
• The increasing trend in the rate of preterm birth was statistically significant for White
non-Hispanic, Hispanic, American Indian/Alaska Native non-Hispanic, and Asian or
Pacific Islander non-Hispanic women.
The preterm birth rate varies depending on the age of the mother. Women ages 20 to 39
years have the lowest rate of preterm birth, compared with women under 20 years and
women 40 years and older. The rates of preterm birth for women ages 20 to 39 years and
women 40 years and older showed an increasing trend between 1993 and 2008; however,
the increase for women ages 20 to 39 years was smaller. (See Table H12a.)
• The differences between the preterm birth rates for the different age groups were
statistically significant. The increasing trends in the rate of preterm birth for women
ages 20 to 39 years and women 40 years and older were statistically significant as well.
Twins, triplets, and other higher-order multiple birth babies are more than 5 times as likely
to be born preterm compared with singleton babies (60.4% vs. 10.6% in 2008). The preterm
birth rates for both singletons and multiples showed an increasing trend from 1993 to 2008;
however, the increase for multiples was larger than for singletons. (See Table H12b.)
• The increasing trend for both singleton and multiple births was statistically significant.
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Adverse Birth Outcomes | Health
Indicator H13
Percentage of babies born at term with low birth weight, by race/ethnicity,
1993-2008
Black non-Hispanic
Asian or Pacific Islander non-Hispanic
White non-Hispanic
American Indian/Alaska Native
non-Hispanic
1996 1998 2000 2002 2004 2006 2008
Data: Centers for Disease Control and Prevention, National Center for Health Statistics,
National Vital Statistics System
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Data characterization
Data from this indicator are obtained from a database maintained by the National Center for Health
Statistics.
The database collects information from birth certificates for virtually all births in the United States.
Birth weight and length of gestation are recorded on each birth certificate.
Between 1993 and 2008, the rate of term low birth weight for all races/ethnicities stayed
relatively constant, ranging between 2.5% and 2.8%. The rates of term low birth weight for
infants born to White non-Hispanic mothers and Asian or Pacific Islander non-Hispanic
mothers showed increasing trends between 1993 and 2008, while the rates of term low
birth weight for infants born to mothers of the other race/ethnicity groups stayed relatively
constant.
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Health I Adverse Birth Outcomes
The rate of term low birth weight varies by race/ethnicity. In 2008, the rate was highest for
infants born to Black non-Hispanic mothers, and next highest for infants born to Asian or
Pacific Islander non-Hispanic mothers. The rate of term low birth weight is lowest for infants
born to White non-Hispanic mothers, Hispanic mothers, and American Indian/Alaska Native
non-Hispanic mothers.
• The rate of term low birth weight for Black non-Hispanic women was statistically
significantly higher than for all other race/ethnicity groups. The rate of term low birth
weight for Asian or Pacific Islander non-Hispanic women was significantly lower than for
Black non-Hispanic women but significantly higher than the other race/ethnicity groups.
Term low birth weight rates vary by the age of the mother. In 2008, women ages 20 to 39
years had the lowest rate of term low birth weight infants, while women under 20 years had
the highest rate of term low birth weight infants. These differences were statistically
significant. (See Table H13a.)
Between 1993 and 2008, the rate of term low birth weight for women 40 years and older
showed an increasing trend, ranging from 2.9% to 3.4%. This increasing trend was
statistically significant. (See Table H13a.)
Twins, triplets, and other higher-order multiple birth babies are more than 5 times as likely
to be born at term with low birth weight compared with singleton babies (12.6% vs. 2.4% in
2008). The rate of term low birth weight for singleton and multiple babies stayed relatively
constant over the period of 1993-2008. (See Table H13b.)
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Supplementary Topics | Introduction
Introduction
The three main sections of America's Children and the Environment, Third Edition (ACES)
present environment and contaminant, biomonitoring, and health indicators derived from data
sources of national interest, updated on a regular basis. Some topics of interest for children's
environmental health do not have suitable national data sources. For some of these topics,
ACES Supplementary Topics measures have been developed using data sets from a single state,
or produced by one-time studies that have not been repeated. The data presentations in this
section are referred to as "measures" rather than "indicators" because they are lacking in at
least one key characteristic desired for ACES indicators.
Measures have been prepared for two Supplementary Topics in ACES:
• Birth Defects
• Contaminants in Schools and Child Care Facilities
The birth defects topic includes a measure summarizing data from the Texas Birth Defects
Registry. The contaminants in schools and child care facilities topic includes three measures of
conditions in educational environments. Contaminants in child care facilities are represented by
measures drawn from EPA's Children's Total Exposure to Persistent Pesticides and Other
Persistent Organic Pollutants (CTEPP) Study, conducted in North Carolina and Ohio, and the
First National Environmental Health Survey of Child Care Centers, a federal government study
of a nationally representative sample of child care facilities. Contaminants in schools are
represented by a measure calculated using a database on pesticide application in schools from
the California Department of Pesticide Regulation.
For each Supplementary Topic, an introduction section explains the relevance of the topic to
children's environmental health. The introduction section is followed by a description of the
measures, including a summary of the data and information on how each measure was
calculated. The measures are then presented in graphical form. Beneath each figure are
explanatory bullet points describing dataset characteristics and key findings from the data
presented in the figure, along with key data from any supplemental data tables. References are
provided for each topic at the end of the report.
Data tables are provided in Appendix A. The tables include all values depicted in the
Supplementary Topics figures, along with additional data of interest not shown in the figures.
Metadata describing the data sources are provided in Appendix B. Documents providing details
of how the measures were calculated are available on the ACE website (www.epa.gov/ace).1
1 Detailed methods documents are not provided for Measures S2 and S3 (contaminants in child care facilities)
because all values were taken directly from published sources.
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Introduction | Supplementary Topics
The topics presented in this section are addressed in Healthy People 2020, which provides
science-based, 10-year national objectives for improving the health of all Americans. Appendix
C provides examples of the alignment of the ACES Supplementary Topics with objectives in
Healthy People 2020.
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Supplementary Topics | Birth Defects
Birth Defects
The term "birth defects" covers a range of structural and chromosomal abnormalities that
occur while the baby is developing in the mother's body.1'2 A birth defect may affect how the
body looks, works, or both. Some birth defects can be detected before birth, others can be
detected when the baby is born, and others may not be detected until some time has passed
after birth.
Birth defects are the leading cause of infant death in the first year of life, accounting for about
20% of infant deaths in 2005.3 Infants who do survive with a birth defect often have lifelong
disabilities, such as intellectual disability, heart problems, or difficulty in performing everyday
activities such as walking.
Some birth defects are inherited. Others have known risk factors that can be avoided such as
prenatal exposure of the fetus to certain Pharmaceuticals (such as Accutane® or Thalidomide);
exposure to alcohol; maternal smoking, and insufficient folate in a woman's diet.3"5 For
example, birth defects resulting from fetal alcohol syndrome are prevented when a woman
does not consume alcohol during pregnancy, and reported cases of neural tube defects such as
spina bifida and anencephaly have been shown to decrease following mandatory folic acid
fortification of cereal grain products.6'7 About 60-70% of birth defects have unknown causes,
but research suggests that some defects could be modified or caused by environmental factors,
possibly in conjunction with genetic factors.3'8"10 Several environmental contaminants cause
birth defects when pregnant women are exposed to high concentrations. Mercury poisoning in
Minamata, Japan resulted in birth defects such as deafness and blindness.11 Prenatal exposures
to high concentrations of polychlorinated biphenyls (PCBs) and related chemicals have resulted
in skin alterations, including chloracne, a potentially serious inflammatory condition.12
However, any possible relationship between exposures to lower concentrations of these or
other environmental contaminants and birth defects is less clear.
A number of epidemiological studies have evaluated the relationship between environmental
and occupational exposures to chemicals and birth defects. The majority of studies consider the
relationship of birth defects to exposures to specific types of environmental contaminants,
including solvents, pesticides, drinking water disinfection byproducts, endocrine disrupting
chemicals, and air pollutants. Some studies consider other scenarios in which individuals may
have elevated exposures without measuring or estimating exposure to any particular
substances. These studies evaluate factors such as occupational category, or residence near a
contaminated site or industrial facility.
Several studies have evaluated the relationship between maternal and paternal solvent exposure
and birth defects. An extensive review of the literature concluded that the evidence linking neural
tube defects to paternal exposures to solvents was suggestive of an association, although not
strong enough to draw a conclusion regarding a causal relationship.10 A meta-analysis that
included multiple studies of women's occupational exposure to organic solvents reported an
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Birth Defects | Supplementary Topics
increased risk for birth defects such as heart defects and oral cleft defects in children born to
exposed women.13 In a recent study conducted in Massachusetts, women who were exposed to
drinking water contaminated with the solvent tetrachloroethylene around the time of conception
were reported to have an increased risk of giving birth to a child with a birth defect.14
Multiple studies have suggested an association between maternal and paternal exposure to
pesticides (both before and after conception) and increased risk of offspring having or dying
from birth defects.15"31 A subsequent review study that evaluated many of these individual
studies together, however, concluded that the data are inadequate at this time to confirm an
association between pesticide exposure and the risk of birth defects.10
Disinfection byproducts in drinking water have also been linked to birth defects in some
epidemiological studies. Disinfection byproducts are formed when organic material found in
source water reacts with chemicals (primarily chlorine) used in treatment of drinking water to
control microbial contaminants. Some individual epidemiological studies have reported
associations between the presence of disinfection byproducts in drinking water and increased risk
of birth defects, especially neural tube defects and oral clefts; however, recent articles reviewing
the body of literature determined that the evidence is too limited to make conclusions about a
possible association between exposure to disinfection byproducts and birth defects.10'32"35
Some studies have also reported associations between exposure to endocrine disrupting
chemicals and urogenital malformations in newborn boys, such as cryptorchidism
(undescended testes) and hypospadias (abnormally placed urinary opening).19'22'36"44 An analysis
of a large national database showed a significant increase in the incidence of congenital penile
anomalies, particularly hypospadias, from 1988-2000.45 According to studies by the Centers for
Disease Control and Prevention, the prevalence of hypospadias in the United States has
doubled in recent decades.46 This considerable increase, combined with evidence of an
association between endocrine-disrupting contaminants and urogenital birth defects in animal
studies, has led to the hypothesis that environmental exposures are a contributing factor.47
However, a review study recently concluded that there is inadequate evidence at this time of
associations between male genital birth defects and exposure to environmental contaminants
such as pesticides, PCBs, wood preservatives, and phthalates.10
A limited number of studies have investigated the relationship between birth defects and
prenatal exposure to air pollution, specifically carbon monoxide, ozone, particulate matter,
nitrogen dioxide, and sulfur dioxide.48"57 Most of these studies have focused on cardiac and oral
cleft birth defects. A recent pooled analysis of these studies reported statistically significant
associations between nitrogen dioxide, sulfur dioxide and particulate matter and certain cardiac
birth defects.58 No statistically significant associations were found between any of the
pollutants and oral cleft defects.
Since the discovery of extensive environmental contamination in the Love Canal community in
New York State in the 1970s, there has been increased awareness that contaminated sites can
be associated with negative birth outcomes, including birth defects.59'60 Multiple epidemiological
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Supplementary Topics | Birth Defects
studies conducted over the last 25 years have found possible associations between residence
near contaminated sites and an increased risk of birth defects, particularly neural tube defects
and congenital heart defects.38'61"64 Studies have also reported associations between residence
near hazardous waste sites or active industrial facilities and chromosomal birth defects.65'66 The
majority of these studies use maternal proximity to sites of interest in order to classify exposure
and do not distinguish between specific types of contaminant exposures; however, a few studies
have reported associations between birth defects and sites that emit heavy metals or
solvents.64'65 Some studies have suggested that the greatest impact may be for mothers residing
within a half mile of a contaminated site.61'67 Studies comparing Superfund sites undergoing
assessment or remediation to active industrial facilities reporting toxic chemical releases
reported no association between birth defect rates and proximity to Superfund sites, but did
report significant associations with proximity to the active industrial sites.65'68 A recent study of
birth defect records for children born to mothers living with proximity to any of 154 Superfund
cleanup sites reported an overall reduced incidence of birth defects.69
The process of fetal development is intensely complicated, requiring the precise coordination of
cell division, growth, and movement. During the process of fetal development there are critical
periods of susceptibility or vulnerability, at which point exposure to environmental
contaminants may be especially damaging.70 For example, two air pollution epidemiology
studies found that the first two months of gestation are a particularly vulnerable period, during
which exposure to air pollutants may cause birth defects of the heart and oral clefts.52'56
Similarly, studies hypothesizing a role for pesticide exposure in birth defects have reported that
conception during the spring is a risk factor for birth defects.25'29'71 Agricultural use of certain
pesticides is at its highest during spring, potentially leading to increased exposures that could
contribute to the observed seasonal pattern in the incidence of birth defects.25'29'71 These types
of studies are useful for generating hypotheses for future research investigating the
relationship between environmental exposures and the development of birth defects.
There is currently no unified national monitoring system for birth defects. Information on
prevalence of birth defects comes from birth certificates and from state birth defects
monitoring systems. Many birth defects can be observed shortly after delivery and are recorded
on birth certificates. A national-scale indicator could be constructed using birth certificate data,
but would miss any birth defect that is not immediately recognized and recorded at birth.
Comparisons of birth defects recorded on birth certificates and birth defect registries have
indicated that typically, less than half of birth defects are recorded on birth certificates.72'73
Most states have some type of birth defects monitoring program, although the type of tracking
varies widely among the states. As of 2008, 45 states had some type of existing birth defects
monitoring program.74 A small portion of these states have the most complete type of tracking
system, which includes actively researching medical records for birth defects and following
children through at least the first year of life. The remaining states have some type of
monitoring program, but do not have all the aspects of a complete surveillance system. The
National Birth Defects Prevention Network has pooled data from several state registries to
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Birth Defects | Supplementary Topics
derive prevalence estimates for a subset of 21 selected birth defects for the years 1999-2001
and 2004-2006.75
The Texas monitoring program, which has monitored birth defects since 1995, is considered
one of the most complete in the nation.76 Data from the T<
birth defects are presented in this section, as an example.
one of the most complete in the nation.76 Data from the Texas registry for several categories of
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Supplementary Topics | Birth Defects
Measure SI: Birth defects in Texas, 1999-2007
About the Measure: Measure SI presents information about the number of infants born with birth
defects in Texas. The data come from a registry of birth defects for the state of Texas, which compiles
data on any birth defects identified in the first year after each child is born. The Texas Registry staff
routinely review medical records at all hospitals and birthing centers where babies are delivered or
treated to identify birth defects. Measure SI shows how the rates of different types of birth defects
have changed overtime. The rates of birth defects in Texas are not necessarily representative of
those in other states.
The Texas Birth Defects Registry
The Texas Birth Defects Epidemiology and Surveillance Branch of the Texas Department of State
Health Services provides information on birth defects in the state of Texas. The Texas program
began monitoring the Houston/Galveston and South Texas areas in 1995 and expanded so that
beginning in 1999, it covered the entire state. The Texas monitoring program covers
approximately 380,000 births each year, which represents almost 10% of all births in the United
States. In addition to live births, the Texas monitoring program also covers birth defects
occurring in a fetal death or pregnancy termination. The Texas monitoring program reports a
wide array of birth defects.
Although most states have a birth defects monitoring program in place, the comprehensiveness
of these programs varies. Texas's birth defects monitoring program is one of the most complete
in the nation, using high-quality active surveillance methods to examine a wide range of birth
defects throughout a child's first year of life.76 Specifically, the Texas Registry staff employ
robust approaches to collecting, verifying, and ascertaining cases of birth defects such as
routinely visiting all hospitals and birthing centers where babies are delivered or treated to
individually review logs, discharge lists, and medical records.77 As a result, a joint review by the
Trust for America's Health and the National Birth Defects Prevention Network of the birth
defects tracking activities in all 50 states assigned the Texas Registry their highest grade
ranking, based on a number of criteria such as the ability to carry out tracking and the resources
devoted to the task.76 Although the Texas Registry data are of high quality, the rates and types
of birth defects in Texas are not necessarily representative of those in other states.
Comparing the Texas Birth Defects Registry with Other Data Sources
To examine whether the rate of birth defects in Texas is similar to the rate for the country as a
whole, it is useful to compare birth defect rates from birth certificates. Birth certificates record
only those birth defects apparent at birth, and do not represent defects that become apparent
after some time. Most states report birth defects on birth certificates using the standard birth
certificate format recommended by the National Center for Health Statistics. The birth certificate
reported rates of birth defects for Texas are generally similar to the nationwide rates.78
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Birth Defects | Supplementary Topics
Comparing the Texas Birth Defects Registry data to the birth certificate data for Texas reveals
that the active surveillance strategies detect a far greater number of birth defects than can be
detected at an infant's birth. For specific birth defects that could be directly compared, the
Texas monitoring program typically detects two to three times the number of birth defects
reported on birth certificates, demonstrating the importance of tracking birth defects that are
not observed at the time of delivery.77'78 Texas birth certificates list potential birth defects for
clinicians to choose from when recording the details of an infant's birth. An analysis by the
Texas Birth Defects Registry found that birth certificates identify these listed birth defects only
15% of the time that they occur. Furthermore, of those birth defects listed on Texas birth
certificates, the most obvious birth defects, such as spina bifida and cleft palate, are only
identified 36-42% of the time.73
As mentioned previously, there is currently no unified national monitoring system for birth
defects. However, CDC, in collaboration with the National Birth Defects Prevention Network,
pools data from states with active and passive monitoring programs to estimate national
prevalence rates for several selected birth defects. The pooled data set currently accounts for
about 30% of births nationwide.75
Data Presented in the Measure
Measure SI displays the number of birth defects per 10,000 live births for the state of Texas.
Measure SI shows data for 1999-2007 and groups birth defects by structural categories. A
supplemental data table for this measure provides information showing how birth defect rates
vary by race/ethnicity.1
Trends in the rates of birth defects may be influenced by differences in clinical practice. For
example, increasing trends in the prevalence of some birth defects could represent more
accurate recording of birth defects and/or better diagnosis of subtle defects due to the use of
more sensitive examinations and technology.79"82 Trends for specific birth defects may also be
masked when grouping birth defects by structural categories. For example, anencephaly is
included in the structural category of central nervous system defects. Incidence of central
nervous system birth defects overall in Texas increased from 1999-2007, but the incidence of
anencephaly defects specifically appear to be decreasing in the same years.83
Statistical Testing
Statistical analysis has been applied to Measure SI to evaluate trends over time or differences
between demographic groups in the prevalence of birth defects. These analyses use a 5%
significance level, meaning that a conclusion of statistical significance is made only when there
is no more than a 5% probability that the observed trend or difference occurred by chance (p <
0.05). The statistical analysis of trends over time is dependent on how the values in the
1 95% confidence intervals for the birth defects rates are provided in a file available on the ACE website
(www.epa.gov/ace).
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Supplementary Topics | Birth Defects
measure vary over time as well as on the number of time periods. For example, the statistical
test is more likely to detect a trend when data have been obtained over a longer period. A
finding of statistical significance for differences between demographic groups depends on the
magnitude of the difference and the number of observations in each group. It should be noted
that conducting statistical testing for multiple categories of birth defects increases the
probability that some trends or differences identified as statistically significant may actually
have occurred by chance.
A finding of statistical significance is useful for determining that an observed trend or difference
was unlikely to have occurred by chance. However, a determination of statistical significance by
itself does not convey information about the magnitude of the increase, decrease, or
difference. Furthermore, a lack of statistical significance means only that occurrence by chance
cannot be ruled out. Thus a conclusion about statistical significance is only part of the
information that should be considered when determining the public health implications of
trends or differences in the prevalence of birth defects.
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Birth Defects | Supplementary Topics
Data characterization
Data for this measure are obtained from the Texas Birth Defects Registry.
The Registry employs robust surveillance methods to monitor all births in Texas and identify cases of birth
defects.
The Registry represents almost 10% of all births in the United States, but the rates and types of birth
defects in Texas are not necessarily representative of those in other states.
Musculoskeletal defects are the most common type of birth defect in Texas, with 165 cases
per 10,000 live births for the years 2005-2007. The second most common type of birth
defect in Texas is cardiac and circulatory, with 158 cases per 10,000 live births for the years
2005-2007.
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Supplementary Topics | Birth Defects
The rates for all categories of birth defects in Texas have increased or remained stable for
the period of 1999-2007. Some of the biggest increases were seen for musculoskeletal
defects, cardiac and circulatory defects, genitourinary defects, eye and ear defects, and
central nervous system defects.
• The increases were statistically significant for musculoskeletal defects, cardiac and
circulatory defects, genitourinary defects, eye and ear defects, gastrointestinal defects,
and central nervous system defects.
The prevalence of birth defects varies by race/ethnicity for most of the anatomical categories
examined. Compared with White non-Hispanics, Black non-Hispanics had lower rates of
musculoskeletal, genitourinary, eye and ear, gastrointestinal, chromosomal, and oral cleft
birth defects, and these differences were statistically significant. There were no statistically
significant differences between Black non-Hispanics and White non-Hispanics in rates of
cardiac and circulatory, central nervous system, and respiratory birth defects. (See Table Sla.)
Compared with White non-Hispanics, Hispanics had higher rates of cardiac and circulatory,
eye and ear, and respiratory defects, whereas rates of musculoskeletal and genitourinary
birth defects were lower. These differences were statistically significant. There were no
statistically significant differences between Hispanics and White non-Hispanics in rates of
gastrointestinal, central nervous system, chromosomal, and oral cleft defects. (See Table Sla.)
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Contaminants in Schools and Child Care Facilities | Supplementary Topics
Contaminants in Schools and Child Care Facilities
The indoor and outdoor environmental quality of schools and child care facilities plays an
important role in affecting children's health and academic performance. Depending on the type
of facility and its particular characteristics (i.e., age, usage, and maintenance), children may be
exposed to contaminants from a variety of indoor and outdoor sources. Potential indoor
exposure sources include building materials and furnishings (such as paint, treated wood,
furniture, carpet, and fabrics), products used for building maintenance (such as cleaning
products and pesticides), and products used for hobbies, science projects, and arts and crafts
projects or within the learning environment (such as paint, markers, and correction fluid).
Potential outdoor exposure sources include air pollution from nearby traffic and industry. In
addition to these specific exposures, children may also experience unsatisfactory
environmental conditions such as inadequate lighting, ventilation, indoor air quality, or noise
control.1 These exposures potentially impact the comfort and health of students, which may
adversely affect their academic performance and increase their risk of both short- and long-
term health problems.2"4
These potential exposures are of particular concern because children generally spend most of
their active, awake time at schools and child care facilities. Children are especially sensitive to
contamination, for several reasons. First, children are biologically more vulnerable than adults
since their bodies are still growing and developing.5"7 Second, children's intake of air and food is
proportionally greater than that of adults. For example, relative to body weight, a child may
breathe up to twice as much air as adults do; this increases their sensitivity to indoor air
pollutants.8 In particular for younger children, the inhalation and ingestion of contaminated
dust is a major route of exposure due to their frequent and extensive contact with floors,
carpets, and other surfaces where dust gathers, such as windowsills, as well as their high rate of
hand-to-mouth activity.8 Lastly, children have many years of future life in which to develop
disease associated with exposure.7
School and child care environments share many characteristics influencing children's exposure
to indoor environmental contaminants, such as the sources and types of potential
environmental contaminants. Both environments also tend to house a large number of
occupants in a small confined space, so that without proper ventilation a large number of
children can be at risk for potential exposure to indoor contaminants.9 However, there are also
a number of important differences between the two. Children in child care facilities are
generally much younger than those in schools, sometimes as young as a few weeks old. The
behaviors of very young children (e.g., crawling, hand-to-mouth activity) increase their
exposure to contaminants in dust, on surfaces, or in toys and other objects.6'10 Younger children
may also spend more time in child care facilities, some as many as 10 hours per day, 5 days a
week.11'12 Also, compared with schools, child care facilities can be located in a much wider
variety of settings, including office buildings, individual homes, and religious buildings. As a
result, the indoor and outdoor environments can differ widely between child care facilities and
may not be directly under the control of those running the child care itself. Furthermore, child
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Supplementary Topics | Contaminants in Schools and Child Care Facilities
care facilities are more often operated independently, while schools are frequently part of a
school district with centralized facilities management. This has important implications for
strategies to address environmental issues in these facilities.
Building upkeep characteristics are extremely important, because the design, construction, and
current condition of school and child care center facilities can contribute to children's exposure
to environmental contaminants.13"17 Age, level of deterioration, and ventilation efficiency are
key characteristics that determine a building's indoor environmental quality. Many substances
are released into the indoor environment as a result of deterioration of the building from old
age, poor maintenance, or through improperly managed removal and renovation processes.15'18
Children may be exposed to a variety of contaminants in school and child care settings, such as
lead, asbestos, polychlorinated biphenyls (PCBs), pesticides, brominated flame retardants,
phthalates, and perfluorinated chemicals. Exposure to indoor contaminants can occur through
multiple routes, such as dermal (through the skin), inhalation, and direct and indirect ingestion.
These types of indoor environmental contaminants have been associated with a variety of
adverse health outcomes, as well as outcomes related to educational performance for which
impaired health is a suspected cause.19'20 These adverse health effects may be short-term
(headache, dizziness, nausea, allergy attacks, or respiratory problems) or longer-term and more
serious (asthma, neurodevelopmental effects, or cancer).21 Children exposed to indoor air
pollution also miss more days of school due to illness.14'22 A child's overall academic performance
can suffer as a result of such an illness or absence.23 For example, exposure to indoor air
pollutants has been associated with decreased concentration and poor testing outcomes.24"26
There is evidence that many schools and child care facilities in the United States have significant
and serious problems with indoor environmental contaminants,27 and certain groups of
children are especially susceptible to such exposures.28 Children with allergies, asthma, and
other respiratory problems are especially susceptible to the effects of indoor air pollution.
Asthma attacks and allergies are often triggered by indoor allergens (pollen, dust, cockroaches),
as well as by mold.29
Lead
Lead is a pervasive and serious environmental health threat for children in the United
States.30'31 The most common sources of lead exposure in schools and child care environments
are lead-based paint, lead dust, and lead-contaminated soil in outdoor play areas.32 This is a
particular concern for young children, due to their frequent and extensive contact with floors,
carpets, window areas, and other surfaces where dust gathers, as well as their frequent hand-
to-mouth activity.33 A nationally representative sample of licensed child care facilities in 2001
estimated that approximately 14% of these facilities in the United States have significant lead-
based paint hazards. Most of these are facilities in older buildings: 26% of facilities located in a
building built before 1960 were found to have lead-based paint hazards, compared with 4% in
newer buildings. n
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Additional sources of lead may include lead in drinking water, lead-contaminated products
(such as toys, books, and jewelry), and outdoor air from nearby industry.33"35The ingestion and
inhalation of lead-contaminated dust are the primary pathways of childhood exposure to
lead.36 The National Toxicology Program has concluded that childhood lead exposure is
associated with reduced cognitive function, reduced academic achievement, and increased
attention-related behavioral problems.30 Studies have reported associations of childhood
37-44
exposure to lead with behavioral problems such as attention-deficit/hyperactivity disorder,
increased likelihood of school absenteeism and of dropping out of high school,45 increased risks
of juvenile delinquency and antisocial behaviors,46"49 higher total arrest rates, and arrest rates
for violent crimes in early adulthood.50'51
Polychlorinated Biphenyls (PCBs)
PCBs are a family of industrial chemicals used primarily as cooling or insulating fluids for
electrical equipment or as additives to paints, plastics, and rubber products.20 While the
manufacture of PCBs was banned in 1979, PCBs continue to be present in products and
materials produced before the ban. Many schools in the United States have lighting systems
containing PCBs. When contained in the lighting systems, PCBs pose very little health risk or
environmental hazard.52 However, lighting systems degrade as they age, increasing the risk of
PCB leaks or even fires, which pose health and environmental hazards. In December 2010, EPA
issued guidance recommending that schools take steps to reduce potential exposures to PCBs
from these types of older lighting fixtures.53 PCBs are also found in caulk and paint used in
building structures before 1980,54'55 which may mobilize into the surroundings from removal
efforts, natural weathering, or deterioration over time, and contribute significantly to PCB
levels in indoor air and dust in schools.56'57 Although there is some inconsistency in the
epidemiological literature, several reviews of the literature have concluded that the overall
evidence supports a concern for adverse effects of PCBs on children's neurological
development.58"62
Asbestos
Asbestos is a naturally occurring mineral fiber that has been used in building materials as an
insulator and fire retardant.63 The production and use of building materials containing asbestos
is currently limited by law in the United States,64 but many older schools and other buildings
may have asbestos-containing materials that were previously allowed in construction. The
Asbestos Hazard Emergency Response Act provides rules for the management of asbestos in
schools.65 Under this law, some asbestos-containing products are removed when found, but
most often it is recommended that they are "managed-in-place"—i.e., maintaining and
managing the contaminated material to reduce potential exposure. Properly managed asbestos
that has not been disturbed poses little health risk to students. However, if asbestos-containing
materials are disturbed or begin to deteriorate, they can release hazardous fibers into the air
and water. Long-term exposure to these fibers can lead to lung cancer, asbestosis (lung
scarring), or mesothelioma (cancer of the lung cavity lining).66'67 These diseases require a long
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time to develop following exposure, putting children at greater risk of disease development
later in life.
Other Indoor Contaminants
Cleaning products and maintenance activities in schools and child care facilities are significant
sources of exposure to chemical contaminants. Many conventional cleaning supplies contain
harmful chemicals that have been associated with various health effects, including asthma and
cancer.68 Additionally, maintenance activities, from routine cleaning to renovation, can cause
dust and particulate matter to become airborne, leading to increased opportunity for inhalation
and ingestion of contaminated particles.69
Children also may be exposed to a variety of other hazardous chemicals in these environments,
such as glues, paints, and other art supplies; mercury from older thermometers; a range of
chemicals in chemistry labs; lead acid in batteries and other automotive and trade shop
supplies; formaldehyde in pressed wood furniture, flooring, carpets, curtains, and cleaning
products; volatile organic compounds (VOCs) in paints, aerosol sprays and fresheners, cleaning
supplies, and building materials and furnishings; and the wide variety of toxic chemicals found
in environmental tobacco smoke.70 These and other chemicals commonly found in indoor air
have been associated with a range of short-term effects, such as eye, lung, and skin irritation;
headaches; nausea; fatigue; and a range of long-term health effects, from chronic lung irritation
to cancer, depending on the specific chemical.
In addition to these direct sources of potential exposure, inefficient or malfunctioning heating,
ventilation, and air conditioning (HVAC) systems may increase the risks of adverse health
effects or even become an additional source for indoor contaminant exposures. First, failing to
provide sufficient circulation and filtration of the indoor air mixed with fresh outdoor air can
lead to an accumulation of existing air pollutants to dangerous levels.9'71 This includes increased
levels of the chemical contaminants already discussed, as well as other environmental
contaminants such as particulate matter and allergens such as cockroach allergen, rodent
dander, or pollen.72 Second, failing to adequately control moisture and temperature levels can
trigger the growth of dust mites and mold, which thrive in damp, warm environments.19'72
Exposure to these are known to cause asthma or trigger asthma attacks.73'74 Inefficient HVAC
capabilities are of particular concern in temporary classroom structures, such as trailers and
portable classrooms, which have been associated with poor indoor air quality due to a
combination of inadequate ventilation along with use of toxic building materials. A state-wide
survey of permanent and portable classrooms in California found that, on average, portable
classrooms had worse indoor air quality than permanent ones did, including less efficient or
improperly functioning HVAC systems; higher levels of indoor air formaldehyde, particulate
matter, polycyclic aromatic hydrocarbons (PAHs), and humidity; and temperatures above and
below thermal comfort standards during warm and cool seasons, respectively.75
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School Siting
School siting (selecting a site, or location, for a new school) is a complex process that often
requires assessment of several considerations, such as whether to renovate an old school or to
build a new one, cost of land and location preparation, and the availability of infrastructure
including roads and utilities. EPA has recently developed voluntary guidelines for school siting
as a way to support states, tribes, communities, local officials, and the public in understanding
and appropriately considering environmental and public health factors when making school
siting decisions. These siting guidelines address issues such as the special vulnerabilities of
children to hazardous substances or pollution exposures, modes of transportation available to
students and staff, the efficient use of energy, and the potential use of the school as an
emergency shelter.17
School locations may have underlying causes of potential exposure, such as site contamination,
neighborhood emission sources, or indoor air quality problems.17 Radon, a naturally occurring
gas, can seep into buildings from soil. A nationwide survey of radon levels in schools estimates
that nearly one in five schools has at least one schoolroom with a short-term radon level above
the level at which EPA recommends that schools take action.76 Additionally, children attending
schools near highways or industrial sources may be exposed to various air pollutants such as
ozone, particulate matter, carbon monoxide, VOCs, and lead. These potential exposures may
pose either short-term or long-term health risks to children who utilize school facilities.17
Pesticides in Schools and Child Care Facilities
Pesticides are used in the indoor and outdoor environment to prevent, destroy, repel, or
otherwise control pests such as rodents, insects, unwanted plants, and microbials (such as
bacteria). They can be sold in many different forms, such as sprays, powders, crystals, or balls,
and thus their application inside or outside of schools and child care facilities may lead to
several potential routes of exposure for children. For example, application of pesticides in the
indoor environment has been shown to contaminate untreated surfaces, including kitchen
counters and toys,77'83 indoor air,7"9'83-87 and dust.84'88'92
Once applied, pesticide residues may take anywhere from a few hours to several months or
years to completely break down (degrade). Pesticide residues in the indoor environment are
less exposed to factors, such as sunlight, that enable their degradation, and therefore are more
persistent than those pesticide residues in the outdoor environment.82'93'94 This persistence
means that pesticide exposures can remain a potential concern for a long period of time, even
if the area is no longer being treated. For example, an assessment of pesticide residues in dust
of inner city homes found a high prevalence of the pesticide chlorpyrifos two to three years
after its indoor use was banned.90 DDT also continues to be measured in indoor dust several
decades after its use was banned in the United States.91'92'95'96 Furthermore, the persistence of
pesticides in the environment after application creates not only an opportunity for children to
be exposed directly to the residues, but also the potential for residue migration, leading to
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contamination of untreated areas.82'97 As a result, exposures may occur long after application
and through a variety of routes such as inhalation and indirect ingestion of dust.77
Outdoor pesticide applications on school property, as well as on nearby agricultural fields,
lawns, or house perimeters, may contaminate nearby schools and child care facilities.77 Several
studies demonstrate increased levels of pesticides in indoor air82'98 and dust95'98 following
pesticide applications in an adjacent outdoor area. This often occurs when outdoor air
contaminated with pesticide residues mixes with the indoor air (through natural drifting into
the building or being brought in through HVAC systems), or residue particles are tracked in on
the shoes and clothing of people entering the building.80'82'95'98'79
Few studies have evaluated pesticide exposures in the school environment. Some states have
conducted studies of pesticide occurrence in their schools. A comprehensive survey of public K-
12 classrooms was conducted by the state of California between October 2001 and February
2002.99 The California study found residues of both available and restricted-use pesticides in all
floor dust samples, and concluded that pesticides enter classrooms either during application or
by being tracked in on clothing or shoes from outdoors. Pesticides detected in more than 80%
of the samples include cis- and trans-permethrin, chlorpyrifos, and piperonyl butoxide. The First
National Environmental Health Survey of Child Care Centers evaluated potential pesticide
exposures in child care facilities, and reported that 75% of licensed child care facilities had at
least one pesticide application in the past year.97 The study detected numerous
organophosphate and pyrethroid pesticides in indoor floor wipe samples. Chlorpyrifos,
diazinon, and permethrin were detected in more than 67% of the tested centers.97
Several studies have reported associations between exposure to pesticides in early life and
adverse health effects such as cancer and neurodevelopmental disorders. Childhood leukemia
in particular has been associated with childhood exposures to pesticides.100"104 Permethrin and
resmethrin, which both belong to the commonly used class of pesticides known as pyrethroids,
were recently classified by EPA as "likely to be carcinogenic to humans."104 Childhood
exposures to organophosphate pesticides have been associated with various adverse
neurodevelopmental effects.105"107 Exposure to herbicides and/or other pesticides in the first
year of life has been associated with higher risk of asthma.108
The short- and long-term health effects of exposure to pesticides in the school environment are
largely unknown, due to a lack of data. Between 1993 and 1996, there were 2,300 pesticide-
related exposures reported to poison control centers that involved individuals at schools,
resulting in 329 people seen in health care facilities, 15 hospitalized, and 4 treated in intensive
care units.109 Data on the long-term effects of pesticide exposure in schools are not available.109
Currently, there is no federal law on pesticide use in the school environment. However, at least
35 states have adopted laws on pesticide use in schools.110 The state laws are generally focused
on the adoption of certain types of practices that eliminate or minimize the use of hazardous
pesticides: adoption of Integrated Pest Management (IPM) programs, prohibiting when and
where pesticides can be applied, requiring signs before and after indoor and outdoor pesticide
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application, requiring prior written notification to parents and staff for pesticide use, and
establishing restricted buffer zones to address chemicals drifting into school yards and
buildings. Strategies such as restrictions on the use of pesticides and adoption of IPM have
been shown to be effective at reducing human exposure.87'111'112
There is no national system for compiling data on the amount of pesticides used in schools.109
Some states require reporting on pesticide use in schools. The state of Louisiana requires
schools to submit a written record of "restricted use" pesticides used annually.113 In the state of
New York, commercial applicators are required by a 1996 law to report the amount of each
specific pesticide used and the location where it was applied. Also, six states—Arizona,
California, Connecticut, Massachusetts, New Hampshire, and New Mexico—require commercial
applicators to report the amount of specific pesticides used.109
Measures in This Section
Data on school or child care environmental exposures are not systematically collected. Over the
years, there have been few national and state-specific surveys or assessments to acquire
information on environmental hazards in educational facilities. The following two measures
provide data on the use or presence of pesticides and other chemicals of concern indoors in
schools and child care facilities. Measures S2 and S3 present data on detectable levels of
pesticides and other contaminants in a regional and national sample of child care centers.
Measure S4 presents data on the amount of pesticides applied in schools in California.
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Measure S2: Percentage of environmental and personal media samples with
detectable pesticides in child care facilities, 2001
Measure S3: Percentage of environmental and personal media samples with
detectable industrial chemicals in child care facilities, 2001
About the Measures: Measures S2 and S3 present information about the types of contaminants that
were detected in child care facilities. The data come from two different studies. One study collected
information from selected child care facilities in Ohio and North Carolina, while the other study
collected information from child care facilities throughout the United States. The measures show
how frequently different contaminants were detected in various media samples (e.g., indoor air,
dust) taken at the testing locations.
CTEPP Study and the First National Environmental Health Survey of Child Care
Centers
Measures S2 and S3 present data on the relative potential exposures of children to a variety
of pesticides and other contaminants found in child care centers. The measures are based on
data from two different federal studies: the Children's Total Exposure to Persistent Pesticides
and Other Persistent Organic Pollutants (CTEPP) Study and the First National Environmental
Health Survey of Child Care Centers. Data shown in these measures were obtained directly
from these sources:
Tulve, N.S., P.A. Jones, M.G. Nishioka, R.C. Fortmann, C.W. Croghan, J.Y. Zhou, A. Fraser,
C. Cave, and W. Friedman. 2006. Pesticide Measurements from the First National
Environmental Health Survey of Child Care Centers Using a Multi-Residue GC/MS
Analysis Method. Environmental Science and Technology 40(20) 6269-6274.
Morgan, M.K., L.S. Sheldon, C.W. Croghan, J.C. Chuang, R.A. Lordo, N.K. Wilson, C. Lyu,
M. Brinkman, N. Morse, Y.L. Chou, C. Hamilton, J.K. Finegold, K. Hand, and S.M. Gordon.
2004. A Pilot Study of Children's Total Exposure to Persistent Pesticides and Other
Persistent Organic Pollutants (CTEPP), Appendix I and Appendix J. Research Triangle
Park, NC: U.S. Environmental Protection Agency, http://www.epa.gov/heasd/ctepp/.
The CTEPP study investigated the potential exposures of 257 preschool children, ages 1.5 to 5
years, and their primary adult child care providers to more than 50 anthropogenic chemicals,
including pesticides, PAHs, PCBs, phthalates, and phenols. This regional study was conducted by
EPA at 29 child care centers in North Carolina and Ohio in 2000-2001. Environmental (indoor
and outdoor air, carpet house dust, and soil) and personal (hand wipe, solid and liquid food,
drinking water, and urine) samples were collected for each child in the study at home and at
the child care center over a 48-hour period.114
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The First National Environmental Health Survey of Child Care Centers was conducted by the U.S.
Department of Housing and Urban Development, the Consumer Product Safety Commission,
and EPA in 2001. Indoor and outdoor environmental media samples (surface wipes and soil
samples) from a nationally representative sample of 168 child care centers were tested for lead,
allergens, and pesticides. No personal samples were collected.
Data Presented in the Measures
Measure S2 presents the percentage of environmental and personal media samples (indoor air,
hand wipe, dust, and floor wipe samples) taken from selected regional and national child care
facilities with detectable pesticides. Measure S3 presents the percentage of environmental and
personal media samples (indoor air, hand wipe, and dust samples) taken from selected regional
child care facilities with detectable industrial chemicals. The "Regional Data" in the first graph
and all data in the second graph are derived from the CTEPP study, and reflect the percentage
of media samples with detectable pesticides and chemical residues. The chemicals were each
measured in 42-43 indoor air and dust samples collected from child care centers in Ohio and
North Carolina, and the chemicals were measured in hand wipe samples collected from 60-61
children attending those child care centers. The "National Data" in the first graph are derived
from The First National Environmental Health Survey of Child Care Centers, and reflect the
percentage of 168 floor wipe samples with detectable chemical residues. The level that is
detectable is determined by the capabilities of the sampling and testing equipment used in a
study; therefore, it cannot be completely ruled out that contaminants are present at lower
levels in samples classified as being below the detection limit. Both measures are based on
whether the contaminant is detected or not detected, and thus provide an indication of
potential for exposure, but they do not provide data on concentrations of the chemicals or
levels of exposure.
The "indoor air" category reflects children's potential exposure to airborne chemicals through
inhalation. The "hand wipes" category is based on sampling for the presence of chemicals on
children's hands. Due to children's high levels of hand-to-mouth activity, hand wipe data
indicate potential exposure via ingestion.8 The "dust" category captures contaminants that
accumulate in dust on various indoor surfaces, and reflects potential inhalation exposure to
contaminants if dust is resuspended in the air, as well as indirect ingestion if dust contaminates
items that children put in their mouths, such as food, toys, and their hands.
The specific pesticides shown in Measure S2 are pentachlorophenol, an organochlorine
pesticide that has been used in the past in some paints, and in industrial and agricultural
practices, but which is now limited to use in wood railroad ties and utility poles; chlorpyrifos, an
organophosphate insecticide used previously indoors against cockroaches, fleas, and termites,
and currently used on farms to control pests on animals and crops and in warehouses, factories,
and food processing plants; c/s-permethrin, a synthetic pyrethroid used to kill and repel
domestic insects; and diazinon, an organophosphate pesticide with current agricultural uses
and previous residential uses.
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The industrial chemicals shown in Measure S3 are PCB-52, polycyclic aromatic hydrocarbons
(PAHs, represented in the measure with data for the PAH benzo[b]fluoranthene), dibutyl
phthalate, and bisphenol A. While the manufacture of PCBs was banned in 1979, PCBs continue
to be present in electrical equipment and some building materials, such as caulk, produced
before the ban. Several PCBs were measured in the CTEPP study; data for PCB-52 are displayed
in the graph because it is one of the PCBs most frequently detected in the study, and thus gives
an indication of potential for exposure to PCBs in general. Benzo[b]fluoranthene is one of
several PAHs measured in the CTEPP study. Mixtures of PAHs are produced when carbon-based
fuels are burned. Data for benzo[b]fluoranthene are displayed in the graph because it is one of
the PAHs most frequently detected in the study, and thus gives an indication of potential for
exposure to PAHs in general. Dibutyl phthalate is a chemical commonly used in adhesives,
plastics, and personal care products. Bisphenol A is a high-volume industrial chemical used in
the production of epoxy resins and polycarbonate plastics. Polycarbonate plastics may be
encountered in many products, notably food and drink containers, while epoxy resins are
frequently used as inner liners of metallic food and drink containers to prevent corrosion.
Many of these pesticides and industrial chemicals are no longer available or have highly
restricted uses. Manufacture of PCBs and PCB-containing equipment and materials was banned
in 1979, though equipment and materials manufactured with PCBs prior to the ban remain in
use. Pentachlorophenol has not been used other than as a wood preservative since 1987.
Indoor application of chlorpyrifos, and any use at schools, was restricted beginning in 2001. All
indoor uses of diazinon were banned in 2001.
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Data characterization
National data for this measure were obtained from a federal government study of a nationally
representative sample of 168 child care centers. Pesticides were measured in environmental samples
collected from the child care centers.
Regional data for this measure were obtained from an EPA study of 29 child care centers in Ohio and North
Carolina. Pesticides were measured in environmental samples collected from the child care centers and
from the hands of children in the centers.
Chlorpyrifos, c/s-permethrin, and diazinon were detected in all of the dust samples collected
at Ohio and North Carolina child care centers included in the CTEPP study in 2000-2001.
Chlorpyrifos and diazinon were also detected in all of the indoor air samples collected at
these child care centers.
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• Pesticide residues were detected least often in the hand wipe samples collected at the
selected Ohio and North Carolina child care centers, but chlorpyrifos and c/s-permethrin
were detected in more than half of the hand wipe samples.
• The national level floor wipe sampling found chlorpyrifos most frequently, in 89% of samples.
C/s-permethrin and diazinon were also detected frequently, in 72% and 67% of floor wipe
samples, respectively. (Pentachlorophenol was not examined in the national study.)
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Measure S3
Percentage of environmental and personal media samples with detectable
industrial chemicals in child care facilities, 2001
Dibutyl Phthalate
Indoor
Air Polycyclic Aromatic Hydrocarbons
Bisphenol A
Dibutyl Phthalate
Wipes Polycyclic Aromatic Hydrocarbons
Dibutyl Phthalate
Polycyclic Aromatic Hydrocarbons
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Data: Children's Total Exposure to Pesticides and Other Persistent Organic Pollutants
Study
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Data characterization
Data for this measure were obtained from an EPA study of 29 child care centers in Ohio and North Carolina.
Chemicals were measured in environmental samples collected from the child care centers and from the
hands of children in the centers.
Of the chemicals shown in this measure, dibutyl phthalate was the most frequently
detected in indoor air and dust samples collected at Ohio and North Carolina child care
centers included in the CTEPP study in 2000-2001.
Dibutyl phthalate and PAHs (represented by benzo[b]fluoranthene) were detected in 100%
of the dust samples. PCB-52 and bisphenol A were detected in 65% and 62% or dust
samples, respectively.
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• Dibutyl phthalate, PAHs, and bisphenol A were detected in more than 60% of hand wipe
samples, while PCB-52 was detected in less than 10% of these samples.
• Dibutyl phthalate was detected in all of the indoor air samples and PCB-52 was detected in
almost all (98%) of the samples. PAHs were detected in slightly less than half of the indoor air
samples, while bisphenol A was detected in slightly more than half of the indoor air samples.
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Measure S4: Pesticides used inside California schools by commercial applicators,
2002-2007
About the Measure: Measure S4 presents information about pesticides used inside California
schools. The data for this measure come from the California Department of Pesticide Regulation,
which collects data on all commercial pesticide application in California schools. The measure shows
how the application amounts of different pesticide categories have changed over the years.
California Schools Pesticide Use Reporting Database
The California Department of Pesticide Regulation collects data on all commercial pesticide
application in California schools. In the year 2000, California passed the Healthy Schools Act of
2000, which required all public child care facilities and school sites to report pesticide use on
school sites by pest control businesses.115 Schools are required to report pesticide use at least
once per year, and all schools are required to maintain records of their reports on-site for four
years. The California Healthy Schools Act requires reporting for application of pesticides to the
buildings or structures (including attics and crawl spaces), playgrounds, athletic fields, school
vehicles, or any other area of school property, indoors and outdoors, visited or used by pupils.115
The law does not apply to products used as self-contained baits or traps; gels or pastes used as
crack-and-crevice treatments; pesticides exempted from regulation by EPA; or antimicrobial
pesticides, including sanitizers and disinfectants. All other pesticides must be reported.
Data Presented in the Measure
Measure S4 displays the annual amount (pounds per year) of pesticides used inside California
schools and child care facilities by commercial applicators. The measure presents data for the
indoor applications of pesticides for all years for which data are available: 2002-2007. Although
the measure presents data for schools and child care facilities, nearly all of the data reported
are from schools.
The measure presents the amount of pesticides applied in California schools and child care
facilities, in pounds per year, with pesticides grouped into seven categories: pyrethrin and
pyrethroid insecticides, organophosphate insecticides, other insecticides, herbicides, fumigants,
rodenticides, and miscellaneous pesticides. Most use of the "other insecticides" category inside
of California schools is accounted for by imidacloprid, which is marketed for indoor termite and
cockroach control. Most of the "miscellaneous pesticides" category use inside of schools is
accounted for by a borate compound used as a fungicide and insecticide.
Routinely collected pesticide use data can provide helpful information about the types of
pesticides used and the extent of such use, including changes over time. However, these data
do not indicate the extent of pesticide exposure experienced by children in California schools.
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Data characterization
Data for this measure are obtained from a reporting database maintained by the California Department of
Pesticide Regulation.
Reporting is required for all pesticide applications by pest control companies at all school and childcare
facilities in California.
Pesticide reports are submitted to the database at least annually and report all pesticide application on
any area of school or childcare facility property visited or used by pupils.
i Pyrethrin and pyrethroid insecticides accounted for the greatest volume of pesticide use in
California schools overall from 2002 to 2007, although there was greater use of herbicides
in 2003, and of the "other" insecticides category and fumigants in 2004.
i The application of pyrethrin and pyrethroid insecticides, and organophosphate insecticides
inside California schools has decreased since 2002.
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Refere,
About This Report
Environments and Contaminants
Criteria Air Pollutants
Hazardous Air Pollutants
Indoor Environments
Drinking Water Contaminants
Chemicals in Food
Contaminated Lands
Climate Change
Biomonitoring
Introduction
Lead
Mercury
Cotinine
Perfluorochemicals (PFCs)
Polychlorinated Biphenyls (PCBs)
Polybrominated Diphenyl Ethers (PBDEs)
Phthalates
Bisphenol A(BPA)
Perchlorate
Health
Introduction
Respiratory Diseases
Childhood Cancer
Neurodevelopmental Disorders
Obesity
Adverse Birth Outcomes
Supplementary Topics
Birth Defects
Contaminants in Schools and
Child Care Facilities
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References | About This Report
About This Report
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pyrethroid pesticides in urban public housing. Journal of Exposure Science and Environmental Epidemiology 18 (2):167-74.
91. Colt, J.S., J. Lubin, D. Camann, S. Davis, J. Cerhan, R.K. Severson, W. Cozen, and P. Hartge. 2004. Comparison of pesticide levels in carpet dust
and self-reported pest treatment practices in four US sites. Journal of Exposure Analysis and Environmental Epidemiology 14 (l):74-83.
92. Stout, D.M., 2nd, K.D. Bradham, P.P. Egeghy, P.A. Jones, C.W. Croghan, PA Ashley, E. Pinzer, W. Friedman, M.C. Brinkman, M.G.
Nishioka, etal. 2009. American Healthy Homes Survey: a national study of residential pesticides measured from floor wipes.
Environmental Science & Technology 43 (12):4294-300.
93. Berger-Preip, E., A. Preip, K. Sielaff, M. Raabe, B. Ilgen, and K. Levsen. 1997. The behavior of pyrethroids indoors: A model study.
Indoor Air 7:248-261.
94. Weschler, C.J. 2009. Changes in indoor pollutants since the 1950s. Atmospheric Environment 43 (1):153-169.
95. Harnly, M.E., A. Bradman, M. Nishioka, T.E. McKone, D. Smith, R. McLaughlin, G. Kavanagh-Baird, R. Castorina, and B. Eskenazi. 2009.
Pesticides in dust from homes in an agricultural area. Environmental Science & Technology 43 (23):8767-74.
96. Morgan, M.K., et al. 2004. A Pilot Study of Children's Total Exposure to Persistent Pesticides and Other Persistent Organic Pollutrants
(CTEPP) Volume I and II. Research Triangle Park, NC: U.S. EPA, Office of Research and Development.
http://www.epa.gov/heasd/ctepp/ctep p_report.pdf.
97. Tulve, N.S., P.A. Jones, M.G. Nishioka, R.C. Fortmann, C.W. Croghan, J.Y. Zhou, A. Fraser, C. Cavel, and W. Friedman. 2006. Pesticide
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98. Morgan, M.K., D.M. Stout, P.A. Jones, and D.B. Barr. 2008. An observational study of the potential for human exposures to pet-borne
diazinon residues following lawn applications. Environmental Research 107 (3):336-42.
99. California Department of Health Services and California Air Resources Board. 2004. Report to the California Legislature:
Environmental Health Conditions in California's Portable Classrooms. Sacramento, CA: California Department of Health Services, California
Air Resources Board, http://www.arb.ca.gov/research/apr/reports/13006.pdf.
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Supplementary Topics | References
Contaminants in Schools and Child Care Facilities (continued)
100. Carozza, S.E., B. Li, K. Elgethun, and R. Whitworth. 2008. Risk of childhood cancers associated with residence in agriculturally intense
areas in the United States. Environmental Health Perspectives 116 (4):559-65.
101. Daniels, J.L., A.F. Olshan, and DA Savitz. 1997. Pesticides and childhood cancers. Environmental Health Perspectives 105 (10):1068-77.
102. Ma, X., P.A. Buffler, R.B. Gunier, G. Dahl, M.T. Smith, K. Reinier, and P. Reynolds. 2002. Critical windows of exposure to household
pesticides and risk of childhood leukemia. Environmental Health Perspectives 110 (9):955-60.
103. Turner, M.C., D.T. Wigle, and D. Krewski. 2010. Residential pesticides and childhood leukemia: a systematic review and meta-
analysis. Environmental Health Perspectives 118 (1):33-41.
104. U.S. Environmental Protection Agency. 2008. Chemicals Evaluated for Carcinogenic Potential by the Office of Pesticide Programs.
Washington, DC: U.S. EPA, Office of Pesticide Programs.
105. Bouchard, M.F., D.C. Bellinger, R.O. Wright, and M.G. Weisskopf. 2010. Attention-deficit/hyperactivity disorder and urinary
metabolites of organophosphate pesticides. Pediatrics 125 (6):el270-7.
106. Eskenazi, B., A.R. Marks, A. Bradman, K. Harley, D.B. Barr, C. Johnson, N. Morga, and N.P. Jewell. 2007. Organophosphate pesticide
exposure and neurodevelopment in young Mexican-American children. Environmental Health Perspectives 115 (5):792-8.
107. Lovasi, G.S., J.W. Quinn, V.A. Rauh, P.P. Perera, H.F. Andrews, R. Garfinkel, L. Hoepner, R. Whyatt, and A. Rundle. 2011. Chlorpyrifos
Exposure and Urban Residential Environment Characteristics as Determinants of Early Childhood Neurodevelopment. American Journal
of Public Health 101 (1):63-70.
108. Salam, M.T., Y.F. Li, B. Langholz, and F.D. Gilliland. 2004. Early-life environmental riskfactors for asthma: findings from the
Children's Health Study. Environmental Health Perspectives 112 (6):760-5.
109. U.S. General Accounting Office. 1999. Pesticides: Use, Effects, and Alternatives to Pesticides in Schools. Washington, DC: U.S. General
Accounting Office, http://www.gao.gov/archive/2000/rc00017.pdf.
110. Owens, K. 2010. Schooling of state pesticide laws: 2010 update. Pesticides and You 29 (3):9-20.
111. Mir, D.F., Y. Finkelstein, and G.D. Tulipano. 2010. Impact of integrated pest management (IPM) training on reducing pesticide
exposure in Illinois childcare centers. Neurotoxicology 31 (5):621-626.
112. Williams, M.K., A. Rundle, D. Holmes, M. Reyes, L.A. Hoepner, D.B. Barr, D.E. Camann, P.P. Perera, and R.M. Whyatt. 2008. Changes in
pest infestation levels, self-reported pesticide use, and permethrin exposure during pregnancy after the 2000-2001 U.S. Environmental
Protection Agency restriction of organophosp hates. Environmental Health Perspectives 116 (12):1681-8.
113. Beyond Pesticides. 2010. State and Local School Pesticide Policies. Beyond Pesticides. Retrieved July 8, 2010 from
http://www.beyondpesticides.org/schools/schoolpolicies/index.htm.
114. Wilson, N.K., J.C. Chuang, R. lachan, C. Lyu, S.M. Gordon, M.K. Morgan, H. Ozkaynak, and L.S. Sheldon. 2004. Design and sampling
methodology for a large study of preschool children's aggregate exposures to persistent organic pollutants in their everyday
environments./ounia/ of Exposure Analysis and Environmental Epidemiology 14 (3):260-274.
115. California Department of Pesticide Regulation. 2010. The Healthy Schools Act of 2000 (AB2260) Frequently Asked Questions.
Retrieved September 22 from http://apps.cdpr.ca.gov/schoolipm/overview/faq2000.cfm.
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America's Children and the Environment | Third Edition
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ppendixA: Data Tables
Environments and Contaminants
Criteria Air Pollutants
Hazardous Air Pollutants
Indoor Environments
Drinking Water Contaminants
Chemicals in Food
Contaminated Lands
Biomonitoring
Lead
Mercury
Cotinine
Perfluorochemicals (PFCs)
Polychlorinated Biphenyls (PCBs)
Polybrominated Diphenyl Ethers (PBDEs)
Phthalates
Bisphenol A(BPA)
Perchlorate
Health
Respiratory Diseases
Childhood Cancer
Neurodevelopmental Disorders
Obesity
Adverse Birth Outcomes
Supplementary Topics
Birth Defects
Contaminants in Schools and
Child Care Facilities
References
America's Children and the Environment | Third Edition A-1
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Appendices | Appendix A: Data Tables
Appendix A: Data Tables
Environments and Contaminants
Criteria Air Pollutants
Table El: Percentage of children ages 0 to 17 years living in counties with pollutant concentrations
above the levels of the current air quality standards, 1999-2009*
1999-2004
Pollutant
Any standard
Ozone (8-hour)
PM2.5 (24-hour)
Sulfur dioxide (1-hour)
PM2.5 (annual)
Nitrogen dioxide (1-hour)
PM10 (24-hour)
Carbon monoxide (8-hour)
Lead (3-month)
1999
74.9
65.2
55.0
31.1
24.2
23.2
7.9
5.7
2.3
2000
76.1
64.9
62.5
28.8
29.6
19.4
6.3
4.4
1.6
2001
76.3
66.3
60.8
26.6
24.7
17.4
6.0
0.7
2.2
2002
75.9
66.1
60.9
25.6
20.9
18.9
4.8
4.1
1.2
2003
77.4
67.8
56.8
21.6
19.1
17.5
7.8
<0.1
1.6
2004
73.8
61.6
56.0
20.5
16.4
16.3
5.2
0.1
1.2
2005-2009
Pollutant
Any standard
Ozone (8-hour)
PM2.5 (24-hour)
Sulfur dioxide (1-hour)
PM2.5 (annual)
Nitrogen dioxide (1-hour)
PM10 (24-hour)
Carbon monoxide (8-hour)
Lead (3-month)
2005
75.9
66.2
60.2
20.9
24.3
13.9
5.0
0.2
1.6
2006
72.9
65.3
45.7
16.6
12.5
12.5
5.1
0.3
1.2
2007
74.4
64.1
53.6
15.5
16.1
10.9
12.5
0.1
5.0
2008
69.2
59.2
37.1
16.7
7.3
12.6
4.0
0.2
5.0
2009
58.6
48.9
32.2
11.4
2.1
8.7
2.8
0.0
4.2
DATA: U.S. Environmental Protection Agency, Office of Air and Radiation, Air Quality System
* EPA periodically reviews air quality standards and may change them based on updated scientific findings. Measuring
concentrations above the level of a standard is not equivalent to violating the standard. The level of a standard may be
exceeded on multiple days before the exceedance is considered a violation of the standard. See the indicator text for additional
discussion. The indicator is calculated with reference to the current levels of the air quality standards for all years shown. Note
that EPA promulgated a revised annual PM2.5 standard in December 2012, which has not been incorporated into this analysis.
America's Children and the Environment | Third Edition
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Appendix A: Data Tables | Appendices
Table Ela: Percentage of children ages 0 to 17 years living in counties with pollutant concentrations
above the levels of the current air quality standards, by race/ethnicity, 2009*
Pollutant
Any standard
Ozone (8-hour)
PM2.5 (24-hour)
Sulfur dioxide
(1-hour)
PM2.s (annual)
Nitrogen dioxide
(1-hour)
PM10 (24-hour)
Carbon monoxide
(8-hour)
Lead (3-month)
All Races/
Ethnicities
58.6
48.9
32.2
11.4
2.1
8.7
2.8
0.0
4.2
White non-
Hispanic
51.9
40.9
24.0
9.9
1.1
4.0
2.5
0.0
2.0
Black American Asian or Pacific
non- Indian/Alaska Native Islander non-
Hispanic non-Hispanic Hispanic Hispanic
62.7
52.2
34.0
17.4
0.8
9.8
0.9
0.0
2.6
38.1
29.5
19.8
5.2
1.7
2.8
5.8
0.0
1.2
70.0
60.7
47.7
10.2
2.7
12.8
1.8
0.0
8.2
71.4
65.2
48.8
11.5
5.3
19.4
4.8
0.0
10.0
DATA: U.S. Environmental Protection Agency, Office of Air and Radiation, Air Quality System
* EPA periodically reviews air quality standards and may change them based on updated scientific findings. Measuring
concentrations above the level of a standard is not equivalent to violating the standard. The level of a standard may be
exceeded on multiple days before the exceedance is considered a violation of the standard. See the indicator text for additional
discussion. The indicator is calculated with reference to the current levels of the air quality standards for all years shown. Note
that EPA promulgated a revised annual PM2.5 standard in December 2012, which has not been incorporated into this analysis.
Table Elb: Percentage of children ages 0 to 17 years living in counties with pollutant concentrations
above the levels of the current air quality standards, by family income, 2009*
| > Poverty (Detail)
Pollutant
Any standard
Ozone (8-hour)
PM2.5 (24-hour)
Sulfur dioxide
(1-hour)
PM2.5 (annual)
Nitrogen dioxide
(1-hour)
PM10 (24-hour)
Carbon monoxide
(8-hour)
Lead (3-month)
All Incomes
58.6
48.9
32.2
11.4
2.1
8.7
2.8
0.0
4.2
< Poverty
Level
59.0
49.9
36.5
12.5
3.1
12.2
2.6
0.0
5.7
> Poverty 1
Level
58.6
48.7
31.3
11.1
1.9
8.1
2.8
0.0
3.9
100-200% of
Poverty Level
56.3
47.2
32.9
11.2
2.6
10.1
3.1
0.0
4.9
> 200% of
Poverty Level
59.3
49.3
30.8
11.1
1.6
7.4
2.7
0.0
3.6
DATA: U.S. Environmental Protection Agency, Office of Air and Radiation, Air Quality System
* EPA periodically reviews air quality standards and may change them based on updated scientific findings. Measuring
concentrations above the level of a standard is not equivalent to violating the standard. The level of a standard may be
exceeded on multiple days before the exceedance is considered a violation of the standard. See the indicator text for additional
discussion. The indicator is calculated with reference to the current levels of the air quality standards for all years shown. Note
that EPA promulgated a revised annual PM2.5 standard in December 2012, which has not been incorporated into this analysis.
America's Children and the Environment | Third Edition
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Appendices | Appendix A: Data Tables
Table E2: Percentage of children ages 0 to 17 years living in counties with 8-hour ozone and 24-hour
PM2.5 concentrations above the levels of air quality standards, by frequency of occurrence, 2009*
Ozone (8-hour)
1999-2005
No days with
concentrations
above the standard
1-3 days
4-10 days
11-25 days
26 or more days
No monitoring data
2006-2009
No days with
concentrations
above the standard
1-3 days
4-10 days
11-25 days
26 or more days
No monitoring data
1999
2.9
4.6
10.8
26.7
23.2
31.8
2006
6.4
10.6
24.8
19.6
10.4
28.3
2000
4.4
9.6
22.9
16.2
16.2
30.7
2007
8.0
11.2
19.8
25.9
7.2
28.0
2001
4.2
6.9
16.2
29.5
13.7
29.6
2008
13.6
18.6
23.9
8.5
8.2
27.2
2002 2003 2004 2005
4.6 3.7 9.4 5.1
6.7 8.7 22.8 9.3
9.6 28.5 21.0 17.7
21.5 18.1 10.0 28.1
28.4 12.5 7.8 11.2
29.2 28.4 29.0 28.7
2009
24.3
27.7
11.8
3.0
6.4
26.8
PM, 5 (24-hour)
1999-2005
No days with
concentrations
above the standard
1-7 days
8-10 days
11-25 days
26 or more days
No monitoring data
2006-2009
No days with
concentrations
above the standard
1-7 days
8-10 days
11-25 days
26 or more days
No monitoring data
1999
13.4
36.3
3.3
9.2
6.2
31.6
2006
25.4
34.9
6.5
1.0
1.8
30.4
2000
10.6
41.5
2.5
11.2
7.2
27.0
2007
17.5
38.4
1.8
10.2
1.9
30.2
2001
12.5
39.1
1.7
12.6
7.4
26.8
2008
33.9
29.3
4.8
1.3
1.0
29.7
2002 2003 2004 2005
12.9 16.4 14.6 11.1
37.5 37.4 40.0 41.9
4.3 3.8 5.3 4.7
11.1 9.8 8.3 10.7
7.8 5.4 2.2 2.4
26.5 27.2 29.6 29.1
2009
38.4
28.4
0.8
1.9
0.9
29.6
DATA: U.S. Environmental Protection Agency, Office of Air and Radiation, Air Quality System
* EPA periodically reviews air quality standards and may change them based on updated scientific findings. Measuring
concentrations above the level of a standard is not equivalent to violating the standard. The level of a standard may be
exceeded on multiple days before the exceedance is considered a violation of the standard. See the indicator text for additional
discussion. The indicator is calculated with reference to the current levels of the air quality standards for all years shown.
America's Children and the Environment | Third Edition
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Appendix A: Data Tables | Appendices
Table E3: Percentage of days with good, moderate, or unhealthy air quality for children ages 0 to 17
years, 1999-2009
Pollution Level
1999-2005
Good
Moderate
Unhealthy
No monitoring data
2006-2009
Good
Moderate
Unhealthy
No monitoring data
1999
41.2
22.1
8.8
27.9
2006
48.9
20.5
5.0
25.7
2000
43.2
23.3
7.2
26.3
2007
48.6
20.5
4.9
26.0
2001
44.0
23.3
7.0
25.7
2008
51.9
18.3
3.7
26.0
2002
45.5
21.6
7.6
25.3
2009
56.6
15.5
2.8
25.1
2003
47.1
21.5
6.0
25.4
2004
49.4
20.4
4.8
25.4
2005
47.7
21.2
5.7
25.4
DATA: U.S. Environmental Protection Agency, Office of Air and Radiation, Air Quality System
NOTE: Good, moderate, and unhealthy air quality are defined using EPA's Air Quality Index (AQI). The health information that
supports EPA's periodic reviews of the air quality standards informs decisions on the AQI breakpoints and may change based on
updated scientific findings. See text for additional discussion.
Table E3a: Percentage of days with good, moderate, or unhealthy air quality for children ages 0 to 17
years, by race/ethnicity, 2009
Pollution Level
Good
Moderate
Unhealthy
No monitoring data
All Races/
Ethnicities
56.6
15.5
2.8
25.1
White non-
Hispanic
54.5
12.1
1.6
31.8
Black non-
Hispanic
60.8
16.0
1.9
21.3
American Indian/
Alaska Native
50.3
11.6
1.7
36.5
Asian or
Pacific Islander
65.4
20.1
4.5
10.0
Hispanic
57.3
23.2
6.0
13.5
DATA: U.S. Environmental Protection Agency, Office of Air and Radiation, Air Quality System
NOTE: Good, moderate, and unhealthy air quality are defined using EPA's Air Quality Index (AQI). The health information that
supports EPA's periodic reviews of the air quality standards informs decisions on the AQI breakpoints and may change based on
updated scientific findings. See text for additional discussion.
Table E3b: Percentage of days with good, moderate, or unhealthy air quality for children ages 0 to 17
years, by family income, 2009
| > Poverty (Detail)
Pollution Level
Good
Moderate
Unhealthy
No monitoring data
All Incomes
56.6
15.5
2.8
25.1
< Poverty
Level
53.6
16.9
3.6
26.0
> Poverty
Level
57.2
15.3
2.6
24.9
100-200% of
Poverty Level
52.8
15.9
3.2
28.1
> 200% of
Poverty Level
58.7
15.1
2.4
23.8
DATA: U.S. Environmental Protection Agency, Office of Air and Radiation, Air Quality System
NOTE: Good, moderate, and unhealthy air quality are defined using EPA's Air Quality Index (AQI). The health information that
supports EPA's periodic reviews of the air quality standards informs decisions on the AQI breakpoints and may change based on
updated scientific findings. See text for additional discussion.
America's Children and the Environment | Third Edition
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Appendices | Appendix A: Data Tables
Hazardous Air Pollutants
Table E4: Percentage of children ages 0 to 17 years living in census tracts where estimated hazardous
air pollutant concentrations were greater than health benchmarks in 2005
Health Benchmark
Cancer, one in 100,000
Cancer, one in 10,000
Other health effects
99.9
6.6
56.4
DATA: U.S. Environmental Protection Agency, National Air Toxics Assessment
Table E4a: Percentage of schoolchildren attending schools in census tracts where estimated hazardous
air pollutant concentrations were greater than health benchmarks in 2005
Health Benchmark
Cancer, one in 100,000
100.0
Cancer, one in 10,000
Other health effects
6.2
56.6
DATA: U.S. Environmental Protection Agency, National Air Toxics Assessment
Table E4b: Percentage of children ages 0 to 17 years living in census tracts where the cancer risk from
estimated hazardous air pollutant concentrations was at least one in 10,000 in 2005, by race/ethnicity
and family income
1 Race/ Ethnicity
All Races/Ethnicities
White
Black
Asian
American Indian/Alaska Native
Native Hawaiian or Other Pacific Islander
Hispanic
All Other Racest
All Incomes
6.6
4.1
7.2
14.4
4.1
8.2
16.2
17.0
< Poverty Level
9.3
6.5
7.4
21.1
3.5
9.1
16.9
19.9
> Poverty Level
5.9
3.7
7.0
13.5
4.4
7.8
15.9
16.0
DATA: U.S. Environmental Protection Agency, National Air Toxics Assessment
NOTE: Race categories include children of Hispanic ethnicity. Hispanic children may be of any race.
t The "All Other Races" category includes all other races not specified, together with those individuals who report more than
Table E4c: Percentage of children ages 0 to 17 years living in census tracts where the non-cancer risk
from estimated hazardous air pollutant concentrations exceeded health benchmarks in 2005, by
race/ethnicity and family income
1 Race/ Ethnicity
All Races/Ethnicities
White
Black
Asian
American Indian/Alaska Native
Native Hawaiian or Other Pacific Islander
Hispanic
All Other Racest
All Incomes
56.4
49.3
72.9
81.4
32.1
57.2
68.7
70.3
< Poverty Level
57.3
46.0
71.8
84.4
28.0
57.1
63.8
68.5
> Poverty Level
56.2
50.0
73.5
81.0
34.2
57.3
70.8
71.0
America's Children and the Environment | Third Edition
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Appendix A: Data Tables | Appendices
DATA: U.S. Environmental Protection Agency, National Air Toxics Assessment
NOTE: Race categories include children of Hispanic ethnicity. Hispanic children may be of any race.
t The "All Other Races" category includes all other races not specified, together with those individuals who report more than
one race.
Indoor Environments
Table E5: Percentage of children ages 0 to 6 years regularly exposed to environmental tobacco smoke
in the home, by family income, 1994, 2005, and 2010
All Incomes < Poverty Level 100-200% of Poverty Level > 200% of Poverty Level
1994
2005
2010
27.3
8.4
37.1
14.6
32.7
11.7
18.5
4.7
6.1
10.2
8.1
3.0
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey
Table E5a: Percentage of children ages 0 to 6 years regularly exposed to environmental tobacco smoke
in the home, by race/ethnicity and family income, 2010
Race/ Ethnicity
All Races/Ethnicities
(n=6,890)
White non-Hispanic
(77=2,662;
All Incomes
(n=6,890)
6.1
7.5
< Poverty
Level
^7=2,072)
10.2
19.9
> Poverty
Level
(n=4,818)
4.7
5.2
> Poverty (Detail)
100-200% of > 200% of
Poverty Level Poverty Level
(n=l,787) (n=3,030)
8.1
11.5
3.0
3.1
Black or African-
American non-Hispanic
(n=l,049)
8.5
10.4
7.0
7.8
6.3
Asian non-Hispanic
(n=381)
Hispanic
(n=2,492)
Mexican
(n=l,687)
Puerto Rican
fa =209;
All Other Racest (n=306)
American
Indian/Alaska Native
non-Hispanic (n=22)
NA**
2.2
2.2
4.8*
9.5
NA**
NA**
2.5*
2.6*
NA**
13.7*
NA**
NA**
2.1
1.9*
NA**
8.3*
NA**
NA**
2.5*
NA**
NA**
2.5*
NA**
NA**
1.6*
NA**
NA**
NA**
NA**
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey
t The "All Other Races" category includes all other races not specified, together with those individuals who report more than
one race.
* The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate).
**Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, is 40% or
greater (RSE = standard error divided by the estimate).
America's Children and the Environment | Third Edition
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Appendices | Appendix A: Data Tables
Table E6: Percentage of children ages 0 to 5 years living in homes with interior lead hazards, 1998-
1999 and 2005-2006
1998-1999
2005-2006
Interior Lead Dust
16.2
12.5
Interior Deteriorated
Lead-Based Paint
11.9
10.6
Either Interior Lead Dust
or Interior Deteriorated
Lead-Based Paint
21.6
14.6
DATA: U.S. Department of Housing and Urban Development, National Survey of Lead and Allergens in Housing, American
Healthy Homes Survey
NOTE: Lead hazards are defined here by current federal standards indicating that floor and window lead dust should not exceed
40 micrograms of lead per square foot (|ag/ft2) and 250 Mg/ft2, respectively, in order to protect children from developing
"elevated" blood lead levels as defined by the CDC at the time the standards were issued. EPA is currently reviewing the lead
dust standards to determine whether they should be lowered.
Drinking Water Contaminants
Table E7: Estimated percentage of children ages 0 to 17 years served by community water systems
that did not meet all applicable health-based drinking water standards, 1993-2009
1993-1997
Type of standard violated
Any health-based standard
Total coliforms
Surface water treatment*
Lead and coppert
Chemical and radionuclide
Nitrate/nitrite
1993
19.2
10.1
6.3
2.8
1.1
0.3
1994
15.7
8.6
5.5
1.7
0.9
0.1
1995
10.7
4.0
4.1
1.9
1.3
0.2
1996
9.7
4.2
3.7
1.8
0.8
0.2
1997
9.4
3.5
3.4
1.8
1.0
0.4
1998-2003
Type of standard violated
Any health-based standard
Total coliforms
Surface water treatment*
Disinfectants and disinfection byproducts
Lead and coppert
Chemical and radionuclide
Nitrate/nitrite
1998
8.2
2.9
2.8
NA*
1.5
0.9
0.6
1999
7.6
3.1
2.4
NA*
1.4
0.7
0.3
2000
8.1
2.9
3.2
NA*
1.2
0.8
0.5
2001
5.1
2.1
1.3
NA*
1.1
0.7
0.2
2002
11.8
2.5
6.3
1.5
0.8
0.8
0.2
2003
8.4
3.0
1.5
3.0
0.6
0.8
0.3
2004-2009
Type of standard violated
Any health-based standard
Total coliforms
Surface water treatment*
Disinfectants and disinfection byproducts
Lead and coppert
Chemical and radionuclide
Nitrate/nitrite
2004
10.4
3.5
3.3
2.6
0.9
1.1
0.1
2005
12.6
3.3
5.2
2.6
0.8
0.9
0.1
2006
10.6
2.3
5.0
1.6
0.4
1.2
0.5
2007
7.8
2.4
2.6
1.4
0.4
1.2
0.2
2008
6.7
2.3
1.5
1.4
0.5
1.1
0.1
2009
7.4
2.5
2.0
1.3
0.8
1.1
0.1
DATA: U.S. Environmental Protection Agency, Office of Water, Safe Drinking Water Information System Federal Version
* "Surface water treatment" includes violations of the Surface Water Treatment Rule and of the Interim Enhanced Surface
Water Treatment Rule.
America's Children and the Environment | Third Edition
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Appendix A: Data Tables | Appendices
t Lead and copper represents the lead and copper rule, which is a set of standards and implementation measures.
t The standard for disinfectants and disinfection byproducts was first implemented in 2002.
NOTE: A new standard for disinfection byproducts was implemented beginning in 2002 for larger drinking water systems and
2004 for smaller systems.1 Revisions to the standard for surface water treatment took effect in 2002.2 A revised standard for
radionuclides went into effect in 2003.B A revised standard for arsenic went into effect in 2006.4 No other revisions to the
standards have taken effect during the period of trend data.
Table E8: Estimated percentage of children ages 0 to 17 years served by community water systems
with violations of drinking water monitoring and reporting requirements, 1993-2009
1993-1997
Type of standard violated
Any violation
Chemical and radionuclide
1993
19.4
7.9
1994
14.1
5.9
1995
12.6
6.3
1996
10.8
4.8
1997
10.5
4.3
Lead and copper
Total coliforms
Surface water treatment
6.4
3.8
3.0
5.5
5.8
4.4
1.9
1.1
0.4
3.4
3.7
0.3
3.9
3.6
0.3
1998-2003
Type of standard violated
Any violation
Chemical and radionuclide
Lead and copper
Total coliforms
Disinfectants and disinfection byproducts
Surface water treatment*
1998
16.6
6.3
7.3
4.0
NAt
0.3
1999
15.6
5.7
7.3
3.5
NAt
0.8
2000
14.8
4.8
7.9
3.1
NAt
0.4
2001
16.8
6.4
6.9
4.4
NAt
0.3
2002
20.6
8.2
6.5
2.7
1.8
3.3
2003
19.1
8.2
6.7
4.3
1.7
2.6
2004-2009
Type of standard violated
Any violation
Chemical and radionuclide
Lead and copper
Total coliforms
Disinfectants and disinfection byproducts
Surface water treatment*
2004
19.6
7.6
7.4
4.7
6.5
2.9
2005
22.5
6.8
8.0
4.4
6.5
3.8
2006
20.6
7.9
8.0
4.7
4.7
2.4
2007
22.1
8.8
7.7
4.4
5.6
2.1
2008
19.2
5.6
7.4
4.1
3.5
2.4
2009
13.4
4.1
3.1
3.1
3.5
1.2
DATA: U.S. Environmental Protection Agency, Office of Water, Safe Drinking Water Information System Federal Version
* "Surface water treatment" includes violations of the Surface Water Treatment Rule and of the Interim Enhanced Surface
Water Treatment Rule.
t The standard for disinfectants and disinfection byproducts was first implemented in 2002.
NOTE: A new standard for disinfection byproducts was implemented beginning in 2002 for larger drinking water systems and
2004 for smaller systems.1 Revisions to the standard for surface water treatment took effect in 2002.2 A revised standard for
radionuclides went into effect in 2003.B A revised standard for arsenic went into effect in 2006.4 No other revisions to the
standards have taken effect during the period of trend data.
America's Children and the Environment | Third Edition
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Appendices | Appendix A: Data Tables
Chemicals in Food
Table E9: Percentage of sampled apples, carrots, grapes, and tomatoes with detectable residues of
organophosphate pesticides, 1998-2009
1998
Apples NA
Carrots NA
Grapes NA
Tomatoes 37.4
1999
80.7
NA
NA
29.9
2000
54.9
10.3
20.6
NA
2001
49.3
6.2
14.8
NA
2002
45.5
8.3
NA
NA
2003
NA
NA
NA
14.6
2004
50.5
NA
16.5
11.8
2005
45.0
NA
16.2
NA
2006
NA
3.5
NA
NA
2007
NA
5.4
NA
9.7
2008
NA
NA
NA
9.5
2009
34.7
NA
7.7
NA
DATA: U.S. Department of Agriculture, Pesticide Data Program
NOTE: For purposes of indicator calculation, only the 43 organophosphate pesticides measured by the pesticide data program
in each year 1998-2009 were considered, so that indicator data are comparable over time. "NA" indicate that the food was not
sampled by the Pesticide Data Program in a particular year. Improvements in measurement technology increase the capability
to detect pesticide residues in more recent samples. In this analysis, limits of detection are held constant so that indicator data
are comparable over time. A separate analysis found that actual detections of pesticide residues were similar or only slightly
greater than the values shown in this table.
Contaminated Lands
Table E10: Percentage of children ages 0 to 17 years living within one mile of Superfund and
Corrective Action sites that may not have all human health protective measures in place, 2009
Race/ Ethnicity
All Races/Ethnicities
White
Black
American Indian/Alaska Native
Asian
Native Hawaiian or Other Pacific Islander
Hispanic
All Other Racest
All Incomes
5.8
4.7
8.1
5.1
8.6
10.4
8.0
8.5
< Poverty Level
7.7
5.9
9.6
3.7
10.5
11.8
8.5
9.3
> Poverty Level
5.4
4.6
7.4
5.5
8.3
10.2
7.8
8.3
DATA: U.S. Environmental Protection Agency, Office of Solid Waste and Emergency Response, CERCLIS, and RCRAInfo
NOTE: Race categories include children of Hispanic ethnicity. Hispanic children may be of any race.
t The "All Other Races" category includes all other races not specified, together with those individuals who report more than
one race.
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Appendix A: Data Tables | Appendices
Table Ell: Distribution by race/ethnicity and family income of children living near selected
contaminated lands* in 2009, compared with the distribution by race/ethnicity and income of
children in the general U.S. population
Race/ Ethnicity
White
Black
American Indian/
Alaska Native
Asian
Native Hawaiian or
Other Pacific Islander
All Other Racest
Hispanic
Population
Children living near selected sites
All children
Children living near selected sites
All children
Children living near selected sites
All children
Children living near selected sites
All children
Children living near selected sites
All children
Children living near selected sites
All children
Children living near selected sites
All children
All Incomes
55.6
68.6
21.1
15.1
1.0
1.2
5.1
3.4
0.3
0.2
17.0
11.6
23.5
17.1
< Poverty Level
36.0
47.3
37.6
30.1
0.8
1.7
3.5
2.6
0.2
0.1
21.8
18.1
31.7
28.7
DATA: U.S. Environmental Protection Agency, Office of Solid Waste and Emergency Response, CERCLIS, and RCRAInfo
*Within one mile of Superfund and Corrective Action sites that may not have all human health protective measures in place.
NOTE: Race categories include children of Hispanic ethnicity. Hispanic children may be of any race.
t The "All Other Races" category includes all other races not specified, together with those individuals who report more than
America's Children and the Environment | Third Edition
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Appendices | Appendix A: Data Tables
Biomonitoring
Lead
Table Bl: Lead in children ages 1 to 5 years: Median and 95 percentile concentrations in blood, 1976-
2010
1 Blood lead concentration (ug/dL)
Median
95th percentile
1976-
1980
15.0
29.0
1988-
1991
3.5
12.1
1991-
1994
2.6
9.7
1999-
2000
2.2
7.0
2001-
2002
1.6
5.8
2003-
2004
1.6
5.1
2005-
2006
1.4
3.8
2007-
2008
1.4
4.1
2009-
2010
1.2
3.4
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
Table Bla: Lead in children ages 1 to 17 years: Blood lead concentrations by age group, 2009-2010
1 Blood lead concentration (ug/dL)
Median
95th percentile
All ages
0.8
2.2
Age
lyear
1.2
4.2
Age
2 years
1.2
3.5
Ages 3 to 5
years
1.1
2.8
Ages 6 to
10 years
0.8
2.1
Ages 11 to
15 years
0.7
1.7
Ages 16 to
17 years
0.7
1.4
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
Table B2. Lead in children ages 1 to 5 years: Median concentrations in blood, by race/ethnicity and
family income, 2007-2010
Median blood lead concentration (ug/dL)
All Incomes^ < Poverty Level > Poverty Level
Race/ Ethnicity
All Races/Ethnicities
(n=l,653)
White Non-Hispanic
(n=536)
Black Non-Hispanic
(n=338)
Mexican-American
(n=490)
All Other Races/Ethnicitiest
(n=289)
(n=l,653)
1.3
1.2
1.6
1.2
1.2
(n=642)
1.5
1.5*
1.7*
1.3
1.6
(n=898)
1.2
1.2
1.4
1.1
1.1
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
t The "All Other Races/Ethnicities" category includes all other races or ethnicities not specified, together with those individuals
who report more than one race.
t Includes sampled individuals for whom income information is missing.
*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
America's Children and the Environment | Third Edition
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Appendix A: Data Tables | Appendices
Table B2a. Lead in children ages 1 to 5 years: 95th percentile concentrations in blood, by race/ethnicity
and family income, 2007-2010
Race/ Ethnicity
All Races/Ethnicities
(n=l,653)
White non-Hispanic
(n=536)
Black non-Hispanic
(n=338)
Mexican-American
(n=490)
All Other Races/Ethnicitiest
(n=289)
95th
percentile blood lead concentration (ug/dL)
All Incomes^ < Poverty Level
(n=l,653) (n=642)
3.9 4.7
3.5
5.8
3.3
3.5
4.5*
6.8*
4.1
4.2
> Poverty Level
(n=898)
3.3
3.4
4.2
3.2
2.7
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
t The "All Other Races/Ethnicities" category includes all other races or ethnicities not specified, together with those individuals
who report more than one race.
t Includes sampled individuals for whom income information is missing.
*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
Table B2b. Lead in children ages 1 to 5 years: Median concentrations in blood, by race/ethnicity and
family income, 1991-1994
Median blood lead concentration (ug/dL)
Race/ Ethnicity (n=2,367)
All Races/Ethnicities
(n=2,367)
White Non-Hispanic
(n=623)
Black Non-Hispanic
(n=773)
Mexican-American
(n=822)
All Other Races/Ethnicitiest
(n=149)
^•^^^^
3.2* 2.1
5.1 3.5
3.7 2.6
NA** 2.0*
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
t The "All Other Races/Ethnicities" category includes all other races or ethnicities not specified, together with those individuals
who report more than one race.
t Includes sampled individuals for whom income information is missing.
*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
** Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, is 40% or
greater (RSE = standard error divided by the estimate), or the RSE cannot be reliably estimated.
America's Children and the Environment | Third Edition
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Appendices | Appendix A: Data Tables
Mercury
Table B3: Mercury in women ages 16 to 49 years: Median and 95
1999-2010
th
percentile concentrations in blood,
1 Concentration of mercury in blood (ug/L)
Median
95th percentile
1999-2000
0.9
7.4
2001-2002
0.7
3.7
2003-2004
0.8
4.5
2005-2006
0.8
4.0
2007-2008
0.7
3.7
2009-2010
0.8
4.2
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTE: To reflect exposures to women who are pregnant or may become pregnant, the estimates are adjusted for the
probability (by age and race/ethnicity) that a woman gives birth. The intent of this adjustment is to approximate the
distribution of exposure to pregnant women. Results will therefore differ from a characterization of exposure to adult women
without consideration of birth rates.
Table B3a. Mercury in women ages 16 to 49 years: Median concentrations in blood, by race/ethnicity
and family income, 2007-2010
Median concentration of mercury in blood (ug/L)
Race/ Ethnicity
All Races/Ethnicities
(n=3,456)
White non-Hispanic
(n=l,430)
Black non-Hispanic
(n=665)
Mexica n-America n
(n=722)
All Other Races/Ethnicitiest
(n=639)
All Incomes*
(n=3,456)
0.7
0.7
0.8
0.6
1.3
< Poverty Level
(n=915)
0.6
0.5
0.8
0.6
0.8
> Poverty Level
(n=2,261)
0.8
0.7
0.9
0.7
1.5
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTE: To reflect exposures to women who are pregnant or may become pregnant, the estimates are adjusted for the probability (by
age and race/ethnicity) that a woman gives birth. The intent of this adjustment is to approximate the distribution of exposure to
pregnant women. Results will therefore differ from a characterization of exposure to adult women without consideration of birth
rates.
t The "All Other Races/Ethnicities" category includes all other races or ethnicities not specified, together with those individuals
who report more than one race.
t Includes sampled individuals for whom income information is missing.
America's Children and the Environment | Third Edition
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Appendix A: Data Tables | Appendices
rth ,
Table B3b. Mercury in women ages 16 to 49 years: 95 percentile concentrations in blood, by
race/ethnicity and family income, 2007-2010
1 95th percentile concentration of mercury in blood (ug/L)
Race/ Ethnicity
All Races/Ethnicities
(n=3,456)
White non-Hispanic
(n=l,430)
Black non-Hispanic
(n=665)
Mexican-American
(n=722)
All Other Races/Ethnicitiest
(n=639)
All Incomes^
(n=3,456)
3.9
3.7
2.9
2.3
6.7
< Poverty Level
(n=915)
2.9
2.9
2.3
1.9
NA**
> Poverty Level
(11=2,261)
4.0
3.7
3.3
2.4
6.5
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTE: To reflect exposures to women who are pregnant or may become pregnant, the estimates are adjusted for the
probability (by age and race/ethnicity) that a woman gives birth. The intent of this adjustment is to approximate the
distribution of exposure to pregnant women. Results will therefore differ from a characterization of exposure to adult women
without consideration of birth rates.
t The "All Other Races/Ethnicities" category includes all other races or ethnicities not specified, together with those individuals
who report more than one race.
t Includes sampled individuals for whom income information is missing.
** Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, is 40% or
greater (RSE = standard error divided by the estimate), or the RSE cannot be reliably estimated.
Table B3c: Mercury in children ages 1 to 5 years: Median and 95th percentile concentrations in blood,
1999-2010
Concentration of mercury in blood (ug/L)
Median
95th percentile
1999-2000
0.3
2.3
HH
HH
•H
HH
2009-2010
0.2
1.3
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
rth
Table B3d: Mercury in children ages 1 to 17 years: Median and 95 percentile concentrations in blood,
by age group, 2007-2010
1 Concentration of mercury in blood (ug/L)
Median
95th percentile
All ages
0.4
1.9
Age
lyear
0.2
1.2
Age
2 years
0.2
1.3
Ages 3 to
5 years
0.2
1.4
Ages 6 to
10 years
0.4
1.7
Ages 11 to
15 years
0.4
2.2
Ages 16 to
17 years
0.5
2.8
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
America's Children and the Environment | Third Edition
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Appendices | Appendix A: Data Tables
Cotinine
rth ,
Table B4: Cotinine in nonsmoking children ages 3 to 17 years: Median and 95 percentile
concentrations in blood serum, 1988-2010
1 Concentration of cotinine in serum (ng/mL) 1
Median
95th percentile
1988-
1991
0.25
3.2
1991-
1994
0.21
3.2
1999-
2000
0.11
3.1
2001-
2002
0.06*
3.2
2003-
2004
0.10
3.2
2005-
2006
0.05
2.3
2007-
2008
0.05
2.6
2009-
2010
0.03
2.1
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTE: Based on children ages 3 to 17 years with serum cotinine < 10 ng/mL (ages 4 to 17 years for 1988-1991 and 1991-1994).
*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
Table B4a. Cotinine in nonsmoking children ages 3 to 17 years: Median concentrations in blood serum,
by race/ethnicity and family income, 2007-2010
1 Median concentration of cotinine in serum (ng/mL)
Race/ Ethnicity
All Races/Ethnicities
(n=4,284)
White non-Hispanic
(n=l,310)
Black non-Hispanic
(n=955)
Mexican-American
(n=l,229)
All Other Races/Ethnicitiest
(n=790)
All Incomes*
(n=4,284)
0.04
0.04
0.11
0.02
0.03
< Poverty Level
(11=1,323)
0.14
NA**
0.38
0.03
0.09
> Poverty Level
(n=2,648)
0.03
0.04
0.06
0.02
0.02
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTE: Based on children ages 3 to 17 years with serum cotinine < 10 ng/mL.
t The "All Other Races/Ethnicities" category includes all other races or ethnicities not specified, together with those individuals
who report more than one race.
t Includes sampled individuals for whom income information is missing.
** Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, is 40% or
greater (RSE = standard error divided by the estimate), or the RSE cannot be reliably estimated.
America's Children and the Environment | Third Edition
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Appendix A: Data Tables | Appendices
Table B4b. Cotinine in nonsmoking children ages 3 to 17 years: 95
serum, by race/ethnicity and family income, 2007-2010
th
percentile concentrations in blood
1 95th percentile concentration of cotinine in serum (ng/mL)
Race/ Ethnicity
All Races/Ethnicities
(n=4,284)
White non-Hispanic
(n=l,310)
Black non-Hispanic
(n=955)
Mexican-American
(n=l,229)
All Other Races/Ethnicitiest
(n=790)
All Incomes^
(n=4,284)
2.5
2.9
2.6
0.8
1.5
< Poverty Level
(11=1,323)
4.1
5.8
3.0
0.9*
NA**
> Poverty Level
(n=2,648)
2.0
2.3
2.3
0.7*
0.7*
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTE: Based on children ages 3 to 17 years with serum cotinine < 10 ng/mL.
t The "All Other Races/Ethnicities" category includes all other races or ethnicities not specified, together with those individuals
who report more than one race.
t Includes sampled individuals for whom income information is missing.
*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
** Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, is 40% or
greater (RSE = standard error divided by the estimate), or the RSE cannot be reliably estimated.
Table B4c: Cotinine in nonsmoking children ages 3 to 17 years: Median and 95th percentile
concentrations in blood serum, by age group, 2007-2010
1 Concentration of cotinine in serum (ng/mL)
Median
95th percentile
All ages
0.04
2.5
Ages 3 to
5 years
0.06
2.9
Ages 6 to
10 years
0.05
2.5
Ages 11 to
15 years
0.03
2.3
Ages 16 to
17 years
0.04
2.9
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
Table B5: Cotinine in nonsmoking women ages 16 to 49 years: Median and 95th percentile
concentrations in blood serum, 1988-2010
1 Concentration of cotinine in serum (ng/mL)
Median
95th percentile
1988-
1991
0.21
2.3
1991-
1994
0.15
2.1
1999-
2000
0.06
1.7
2001-
2002
0.04
1.6
2003-
2004
0.04
2.2
2005-
2006
0.04
1.5
2007-
2008
0.04
1.9
2009-
2010
0.03
1.5
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
America's Children and the Environment | Third Edition
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Appendices | Appendix A: Data Tables
NOTES:
• Based on women ages 16 to 49 years with serum cotinine ^ 10 ng/mL.
• To reflect exposures to women who are pregnant or may become pregnant, the estimates are adjusted for the
probability (by age and race/ethnicity) that a woman gives birth. The intent of this adjustment is to approximate the
distribution of exposure to pregnant women. Results will therefore differ from a characterization of exposure to adult
women without consideration of birth rates.
Table B5a. Cotinine in nonsmoking women ages 16 to 49 years: Median concentrations in blood
serum, by race/ethnicity and family income, 2007-2010
1 Median concentration of cotinine in serum (ng/mL)
Race/ Ethnicity
All Races/Ethnicities
(n=2,601)
White non-Hispanic
(n=949)
Black non-Hispanic
(n=475)
Mexica n-America n
(n=654)
All Other Races/Ethnicitiest
(n=523)
All Incomes^
(n=2,601)
0.03
0.03
0.10
0.03
0.03
< Poverty Level
(n=583)
0.05
NA**
0.33
0.04
0.03*
> Poverty Level
(11=1,781)
0.03
0.03
0.06
0.02
0.03
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTES:
• Based on women ages 16 to 49 years with serum cotinine ^ 10 ng/mL.
• To reflect exposures to women who are pregnant or may become pregnant, the estimates are adjusted for the
probability (by age and race/ethnicity) that a woman gives birth. The intent of this adjustment is to approximate the
distribution of exposure to pregnant women. Results will therefore differ from a characterization of exposure to adult
women without consideration of birth rates.
t The "All Other Races/Ethnicities" category includes all other races or ethnicities not specified, together with those individuals
who report more than one race.
t Includes sampled individuals for whom income information is missing.
*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
America's Children and the Environment | Third Edition
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Appendix A: Data Tables | Appendices
rth ,
Table B5b. Cotinine in nonsmoking women ages 16 to 49 years: 95 percentile concentrations in blood
serum, by race/ethnicity and family income, 2007-2010
1 95th percentile concentration of cotinine in serum (ng/mL)
Race/ Ethnicity
All Races/Ethnicities
(n=2,601)
White non-Hispanic
(n=949)
Black non-Hispanic
(n=475)
Mexican-American
(n=654)
All Other Races/Ethnicitiest
(n=523)
All Incomes^
(n=2,601)
1.6
1.4
3.4
1.6*
NA**
< Poverty Level
(n=583)
3.5
3.7*
8.3
2.5
NA**
> Poverty Level
(11=1,781)
1.4
1.0
3.0
NA**
NA**
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTES:
• Based on women ages 16 to 49 years with serum cotinine ^ 10 ng/mL.
• To reflect exposures to women who are pregnant or may become pregnant, the estimates are adjusted for the
probability (by age and race/ethnicity) that a woman gives birth. The intent of this adjustment is to approximate the
distribution of exposure to pregnant women. Results will therefore differ from a characterization of exposure to adult
women without consideration of birth rates.
t The "All Other Races/Ethnicities" category includes all other races or ethnicities not specified, together with those individuals
who report more than one race.
t Includes sampled individuals for whom income information is missing.
*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
** Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, is 40% or
greater (RSE = standard error divided by the estimate), or the RSE cannot be reliably estimated.
Perfluorochemicals (PFCs)
Table B6. Perfluorochemicals in women ages 16 to 49 years: Median concentrations in blood serum,
1999-2008
1 Median concentration of PFCs in serum (ng/mL) 1
Year
1999-2000
2003-2004
2005-2006
2007-2008
PFOS
23.8
14.6
11.6
8.7
PFOA
4.6
3.0
2.9
3.2
PFHxS
1.3
1.4
1.2
1.1
PFNA
0.5
0.8
0.8
1.2
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTES:
PFOS = perfluorooctane sulfonic acid, PFOA = perfluorooctanoic acid, PFHxS = perfluorohexane sulfonic acid, and PFNA =
perfluorononanoic acid.
America's Children and the Environment | Third Edition
-------
Appendices | Appendix A: Data Tables
• To reflect exposures to women who are pregnant or may become pregnant, the estimates are adjusted for the
probability (by age and race/ethnicity) that a woman gives birth. The intent of this adjustment is to approximate the
distribution of exposure to pregnant women. Results will therefore differ from a characterization of exposure to adult
women without consideration of birth rates.
Table B6a. Perfluorochemicals in women ages 16 to 49 years: 95th percentile concentrations in blood
serum, 1999-2008
1 95th percentile concentration of PFCs in serum (ng/mL) 1
Year
1999-2000
2003-2004
2005-2006
2007-2008
PFOS
50.1
42.2
27.8
22.8
PFOA
8.4
8.4
6.4
7.9
PFHxS
4.9
7.1*
5.4
4.9
PFNA
1.3
NA**
2.2
3.2
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTES:
• PFOS = perfluorooctane sulfonic acid, PFOA = perfluorooctanoic acid, PFHxS = perfluorohexane sulfonic acid, and PFNA =
perfluorononanoic acid.
• To reflect exposures to women who are pregnant or may become pregnant, the estimates are adjusted for the
probability (by age and race/ethnicity) that a woman gives birth. The intent of this adjustment is to approximate the
distribution of exposure to pregnant women. Results will therefore differ from a characterization of exposure to adult
women without consideration of birth rates.
*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
** Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, is 40% or
greater (RSE = standard error divided by the estimate), or the RSE cannot be reliably estimated.
America's Children and the Environment | Third Edition
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Appendix A: Data Tables | Appendices
Table B6b. Perfluorochemicals in women ages 16 to 49 years: Median concentrations in blood serum,
by race/ethnicity and family income, 2005-2008
Median concentration of PFCs in serum (ng/mL)
1/1
O
LL.
Q.
$
LL.
Q_
l/l
X
LL.
Q.
<
LL.
Q.
Race /Ethnicity
All Races/Ethnicities (n=l,121)
White non-Hispanic (n=453)
Black non-Hispanic (n=255)
Mexican-American (n=272)
All Other Races/Ethnicitiest (n=141)
All Races/Ethnicities (n=l,121)
White non-Hispanic (n=453)
Black non-Hispanic (n=255)
Mexican-American (n=272)
All Other Races/Ethnicitiest (n=141)
All Races/Ethnicities (n=l,121)
White non-Hispanic (n=453)
Black non-Hispanic (n=255)
Mexican-American (n=272)
All Other Races/Ethnicitiest (n=141)
All Races/Ethnicities (n=l,121)
White non-Hispanic (n=453)
Black non-Hispanic (n=255)
Mexican-American (n=272)
All Other Races/Ethnicitiest (n=141)
All Incomes^
(11=1,121)
10.1
11.4
11.2
7.4
8.3
3.1
3.5
2.7
2.3
2.4
1.2
1.3
1.1
0.9
0.8
1.0
1.1
1.1
0.8
1.1
< Poverty Level
(n=278)
8.1
8.1*
NA**
8.1*
NA**
2.7
3.3*
NA**
2.1*
NA**
1.0
1.1*
NA**
0.9*
NA**
1.0
1.0*
NA**
0.9*
NA**
> Poverty Level
(n=780)
11.0
11.6
11.2
7.3
10.5
3.2
3.5
2.6
2.4
2.6
1.2
1.3
1.1
1.0
1.1
1.0
1.1
1.2
0.8
1.2
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTES:
• PFOS = perfluorooctane sulfonic acid, PFOA = perfluorooctanoic acid, PFHxS = perfluorohexane sulfonic acid, and PFNA =
perfluorononanoic acid.
• To reflect exposures to women who are pregnant or may become pregnant, the estimates are adjusted for the
probability (by age and race/ethnicity) that a woman gives birth. The intent of this adjustment is to approximate the
distribution of exposure to pregnant women. Results will therefore differ from a characterization of exposure to adult
women without consideration of birth rates.
t The "All Other Races/Ethnicities" category includes all other races or ethnicities not specified, together with those individuals
who report more than one race.
t Includes sampled individuals for whom income information is missing.
*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
** Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, is 40% or
greater (RSE = standard error divided by the estimate), or the RSE cannot be reliably estimated.
America's Children and the Environment | Third Edition
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Appendices | Appendix A: Data Tables
rth
Table B6c. Perfluorochemicals in women ages 16 to 49 years: 95 percentile concentrations in blood
serum, by race/ethnicity and family income, 2005-2008
95th percentile concentration of PFCs in serum (ng/mL)
1/1
O
LL.
Q.
3
LL.
Q.
l/l
X
LL.
Q.
<
LL.
Q.
Race/ Ethnicity
All Races/Ethnicities (n=l,121)
White non-Hispanic (n=453)
Black non-Hispanic (n=255)
Mexican-American (n=272)
All Other Races/Ethnicitiest (n=141)
All Races/Ethnicities (n=l,121)
White non-Hispanic (n=453)
Black non-Hispanic (n=255)
Mexican-American (n=272)
All Other Races/Ethnicitiest (n=141)
All Races/Ethnicities (n=l,121)
White non-Hispanic (n=453)
Black non-Hispanic (n=255)
Mexican-American (n=272)
All Other Races/Ethnicitiest (n=141)
All Races/Ethnicities (n=l,121)
White non-Hispanic (n=453)
Black non-Hispanic (n=255)
Mexican-American (n=272)
All Other Races/Ethnicitiest (n=141)
All Incomes^
(11=1,121)
25.7
28.4
25.7
17.3
24.9
7.5
8.1
6.5
5.5
5.8
5.1
5.6
4.2
4.6
2.1
2.8
2.9
NA**
2.3
2.8
< Poverty Level
(n=278)
22.6
23.9*
NA**
17.3*
NA**
5.6
5.8*
NA**
5.4*
NA**
5.4
6.0*
NA**
4.0*
NA**
2.7
2.0*
NA**
2.3*
NA**
> Poverty Level
(n=780)
27.8
28.4
25.7
16.4
31.0
7.8
8.1
6.1
5.6
5.8
5.1
5.6
3.7
5.2
2.1
2.6
2.7
2.3
2.0
2.8
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTES:
• PFOS = perfluorooctane sulfonic acid, PFOA = perfluorooctanoic acid, PFHxS = perfluorohexane sulfonic acid, and PFNA =
perfluorononanoic acid.
• To reflect exposures to women who are pregnant or may become pregnant, the estimates are adjusted for the
probability (by age and race/ethnicity) that a woman gives birth. The intent of this adjustment is to approximate the
distribution of exposure to pregnant women. Results will therefore differ from a characterization of exposure to adult
women without consideration of birth rates.
t The "All Other Races/Ethnicities" category includes all other races or ethnicities not specified, together with those individuals
who report more than one race.
t Includes sampled individuals for whom income information is missing.
*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
** Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, is 40% or
greater (RSE = standard error divided by the estimate), or the RSE cannot be reliably estimated.
America's Children and the Environment | Third Edition
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Appendix A: Data Tables | Appendices
Polychlorinated Biphenyls (PCBs)
Table B7. PCBs in women ages 16 to 49 years: Median concentrations in blood serum, by
race/ethnicity and family income, 2001-2004
1 Median concentration of PCBs in serum (ng/g lipid) 1
Race/ Ethnicity
All Races/Ethnicities
(n=l,164)
White non-Hispanic
(n=477)
Black non-Hispanic
(n=281)
Mexican-American
(n=305)
All Other Races/Ethnicitiest
(n=101)
All Incomes^
(n=l,164)
30.1
33.6
32.2
18.0
31.6
< Poverty Level
(n=299)
25.8
29.0*
30.3*
16.1*
NA**
> Poverty Level
(n=810)
31.8
34.8
37.4
18.9
38.0*
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTES:
• Values below the limit of detection are assumed equal to the limit of detection divided by the square root of 2.
• To reflect exposures to women who are pregnant or may become pregnant, the estimates are adjusted for the
probability (by age and race/ethnicity) that a woman gives birth. The intent of this adjustment is to approximate the
distribution of exposure to pregnant women. Results will therefore differ from a characterization of exposure to adult
women without consideration of birth rates.
t The "All Other Races/Ethnicities" category includes all other races or ethnicities not specified, together with those individuals
who report more than one race.
t Includes sampled individuals for whom income information is missing.
*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
** Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, is 40% or
greater (RSE = standard error divided by the estimate), or the RSE cannot be reliably estimated.
America's Children and the Environment | Third Edition
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Appendices | Appendix A: Data Tables
rth
Table B7a. PCBs in women ages 16 to 49 years: 95 percentile concentrations in blood serum, by
race/ethnicity and family income, 2001-2004
1 95th percentile concentration of PCBs in serum
Race/ Ethnicity
All Races/Ethnicities
(n=l,164)
White non-Hispanic
(n=477)
Black non-Hispanic
(n=281)
Mexican-American
(n=305)
All Other Races/Ethnicitiest
(n=101)
All Incomes^
(n=l,164)
106.2
108.7
101.8
49.1
245.2
< Poverty Level >
(n=299)
87.6
87.6*
74.3*
NA**
NA**
(ng/g lipid)
Poverty Level
(n=810)
111.3
114.6
118.0
58.1
191.3*
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTES:
• Values below the limit of detection are assumed equal to the limit of detection divided by the square root of 2.
• To reflect exposures to women who are pregnant or may become pregnant, the estimates are adjusted for the
probability (by age and race/ethnicity) that a woman gives birth. The intent of this adjustment is to approximate the
distribution of exposure to pregnant women. Results will therefore differ from a characterization of exposure to adult
women without consideration of birth rates.
t The "All Other Races/Ethnicities" category includes all other races or ethnicities not specified, together with those individuals
who report more than one race.
t Includes sampled individuals for whom income information is missing.
*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
** Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, is 40% or
greater (RSE = standard error divided by the estimate), or the RSE cannot be reliably estimated.
America's Children and the Environment | Third Edition
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Appendix A: Data Tables | Appendices
Polybrominated Diphenyl Ethers (PBDEs)
Table B8. PBDEs in women ages 16 to 49 years: Median concentrations in blood serum, by
race/ethnicity and family income, 2003-2004
Race/ Ethnicity
All Races/Ethnicities
(n=540)
White non-Hispanic
(n=233)
Median concentration of PBDEs in serum (ng/g lipid)
44.2
48.9
Black non-Hispanic
(n=132)
Mexican-American
(n=131)
All Other Races/Ethnicitiest
(n=44)
Income
All Incomes*
(n=540)
< Poverty Level
(n=156)
> Poverty Level
(n=352)
47.6*
41.0*
NA*
44.2
41.8
43.9
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTES:
• Values below the limit of detection are assumed equal to the limit of detection divided by the square root of 2.
• To reflect exposures to women who are pregnant or may become pregnant, the estimates are adjusted for the
probability (by age and race/ethnicity) that a woman gives birth. The intent of this adjustment is to approximate the
distribution of exposure to pregnant women. Results will therefore differ from a characterization of exposure to adult
women without consideration of birth rates.
t The "All Other Races/Ethnicities" category includes all other races or ethnicities not specified, together with those individuals
who report more than one race.
t Includes sampled individuals for whom income information is missing.
*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
** Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, is 40% or
greater (RSE = standard error divided by the estimate), or the RSE cannot be reliably estimated.
America's Children and the Environment | Third Edition
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Appendices | Appendix A: Data Tables
Table B8a. PBDEs in children ages 12 to 17 years: Median concentrations in blood serum, by
race/ethnicity and family income, 2003-2004
Race/ Ethnicity
All Races/Ethnicities (n=464)
White non-Hispanic (n=114)
Black non-Hispanic (n=176)
Median concentration of PBDEs in serum (ng/g lipid)
52.9
47.5*
50.4*
Mexican-American (n=145)
All Other Races/Ethnicitiest (n=29)
62.9*
NA**
Income
All Incomes* (n=464)
< Poverty Level (n=147)
52.9
62.6
> Poverty Level (n=304)
49.8
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTE: Values below the limit of detection are assumed equal to the limit of detection divided by the square root of 2.
t The "All Other Races/Ethnicities" category includes all other races or ethnicities not specified, together with those individuals
who report more than one race.
t Includes sampled individuals for whom income information is missing.
*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
** Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, is 40% or
greater (RSE = standard error divided by the estimate), or the RSE cannot be reliably estimated.
Phthalates
Table B9: Phthalate metabolites in women ages 16 to 49 years: Median concentrations in urine, 1999-2008
Median concentration of phthalate metabolites in urine (ug/L) 1
DEHP metabolites
DBP metabolites1
BBzP metabolite
1999-2000
0_
32.6
13.8
2001-2002
41.9
26.7
13.6
2003-2004
44.5
32.1
12.3
2005-2006
40.6
32.2
9.9
2007-2008
50.6
36.3
12.4
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTES:
• DEHP = di-2-ethylhexyl phthalate, DBP = dibutyl phthalate(di-n-butyl phthalate and di-isobutyl phthalate), and BBzP =
butyl benzyl phthalate.
• Values below the limit of detection are assumed equal to the limit of detection divided by the square root of 2.
• To reflect exposures to women who are pregnant or may become pregnant, the estimates are adjusted for the
probability (by age and race/ethnicity) that a woman gives birth. The intent of this adjustment is to approximate the
distribution of exposure to pregnant women. Results will therefore differ from a characterization of exposure to adult
women without consideration of birth rates.
0 The estimate is not reported because the DEHP metabolites MEOHP and MEHHP were not measured in 1999-2000.
1 The primary urinary metabolites of DBP (di-n-butyl phthalate and di-isobutyl phthalate) are mono-n-butyl phthalate (MnBP)
and mono-isobutyl phthalate (MiBP). The urinary levels of MnBP and MiBP were measured together for the NHANES 1999-
2000 survey cycle, but for the following years were measured separately. Indicators B9 and BIO present the combined urinary
levels of MnBP and MiBP for each survey cycle.
America's Children and the Environment | Third Edition
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Appendix A: Data Tables | Appendices
rth ,
Table B9a: Phthalate metabolites in women ages 16 to 49 years: 95 percentile concentrations in
urine, 1999-2008
1 95th percentile concentration of phthalate metabolites in urine (ug/L) 1
DEHP metabolites
DBP metabolites
BBzP metabolite
1999-2000
0
NA**
73.9
2001-2002
577.9*
128.2
99.7
2003-2004
462.2
139.6
67.8
2005-2006
521.3*
144.9
67.5
2007-2008
567.2
160.2
70.5
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTES:
• DEHP = di-2-ethylhexyl phthalate, DBP = dibutyl phthalate (di-n-butyl phthalate and di-isobutyl phthalate), and BBzP =
butyl benzyl phthalate.
• Values below the limit of detection are assumed equal to the limit of detection divided by the square root of 2.
• To reflect exposures to women who are pregnant or may become pregnant, the estimates are adjusted for the
probability (by age and race/ethnicity) that a woman gives birth. The intent of this adjustment is to approximate the
distribution of exposure to pregnant women. Results will therefore differ from a characterization of exposure to adult
women without consideration of birth rates.
• Phthalates do not accumulate in bodily tissues; thus, the distribution of NHANES urinary phthalate metabolite levels
may overestimate high-end exposures as a result of collecting one-time urine samples rather than collecting urine for a
longer time period.5"7
*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
** Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, is 40% or
greater (RSE = standard error divided by the estimate), or the RSE cannot be reliably estimated.
0 The estimate is not reported because the DEHP metabolites MEOHP and MEHHP were not measured in 1999-2000.
America's Children and the Environment | Third Edition
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Appendices | Appendix A: Data Tables
Table B9b. Phthalate metabolites in women ages 16 to 49 years: Median concentrations in urine by
race/ethnicity and family income, 2005-2008
Median concentration of phthalate metabolites in urine (ug/L)
DEHP
metabolites
DBP
metabolites
IBBzP
metabolite
Race /Ethnicity
All Races/Ethnicities (n=l,187)
White non-Hispanic (n=456)
Black non-Hispanic (n=291)
Mexican-American (n=283)
All Other Races/Ethnicitiest
(n=157)
All Races/Ethnicities (n=l,187)
White non-Hispanic (n=456)
Black non-Hispanic (n=291)
Mexican-American (n=283)
All Other Races/Ethnicitiest
(n=157)
All Races/Ethnicities (n=l,187)
White non-Hispanic (n=456)
Black non-Hispanic (n=291)
Mexican-American (n=283)
All Other Races/Ethnicitiest
(n=157)
All Incomes^
(11=1,187)
43.9
46.5
58.0
35.5
43.3
33.2
29.9
48.3
39.9
31.4
10.9
10.7
14.3
11.5
5.8*
< Poverty Level
(n=289)
48.0
NA**
49.8*
44.8*
40.5*
37.3
38.6*
41.2*
32.0*
29.5*
13.3
13.4*
14.5*
10.7*
11.9*
> Poverty Level
(n=824)
41.7
41.7
65.2
32.3
44.6
31.9
27.5
51.6
46.5
31.4
10.4
35.6
14.6
10.4
4.2*
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTES:
• DEHP = di-2-ethylhexyl phthalate, DBP = dibutyl phthalate (di-n-butyl phthalate and di-isobutyl phthalate), and BBzP =
butyl benzyl phthalate.
• Values below the limit of detection are assumed equal to the limit of detection divided by the square root of 2.
• To reflect exposures to women who are pregnant or may become pregnant, the estimates are adjusted for the
probability (by age and race/ethnicity) that a woman gives birth. The intent of this adjustment is to approximate the
distribution of exposure to pregnant women. Results will therefore differ from a characterization of exposure to adult
women without consideration of birth rates.
t The "All Other Races/Ethnicities" category includes all other races or ethnicities not specified, together with those individuals
who report more than one race.
t Includes sampled individuals for whom income information is missing.
*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
** Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, is 40% or
greater (RSE = standard error divided by the estimate), or the RSE cannot be reliably estimated.
America's Children and the Environment | Third Edition
-------
Appendix A: Data Tables | Appendices
Table BIO: Phthalate metabolites in children ages 6 to 17 years: Median concentrations in urine,
1999-2008
1 Median concentration of phthalate metabolites in urine (ug/L)
DEHP metabolites
DBP metabolites
BBzP metabolite
1999-2000
0
37.9
24.8
2001-2002
56.9
36.3
22.4
2003-2004
59.5
39.7
22.1
2005-2006
62.4
41.8
18.5
2007-2008
45.2
41.3
16.3
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTES:
• DEHP = di-2-ethylhexyl phthalate, DBP = dibutyl phthalate (di-n-butyl phthalate and di-isobutyl phthalate), and BBzP =
butyl benzyl phthalate.
• Values below the limit of detection are assumed equal to the limit of detection divided by the square root of 2.
0 The estimate is not reported because the DEHP metabolites MEOHP and MEHHP were not measured in 1999-2000.
Table BlOa: Phthalate metabolites in children ages 6 to 17 years: 95th percentile concentrations in
urine, 1999-2008
95th percentile concentration of phthalate metabolites in urine (ug/L)
DEHP metabolites
DBP metabolites
BBzP metabolite
1999-2000
0_
165.7
122.3
2001-2002
387.4
175.1
143.1
2003-2004
455.6
191.4
151.1
2005-2006
524.5
166.2
104.0
2007-2008
563.9
190.9
107.1
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTES:
• DEHP = di-2-ethylhexyl phthalate, DBP = dibutyl phthalate (di-n-butyl phthalate and di-isobutyl phthalate), and BBzP =
butyl benzyl phthalate.
• Values below the limit of detection are assumed equal to the limit of detection divided by the square root of 2.
• Phthalates do not accumulate in bodily tissues; thus, the distribution of NHANES urinary phthalate metabolite levels
may overestimate high-end exposures as a result of collecting one-time urine samples rather than collecting urine for a
longer time period.5"7
0 The estimate is not reported because the DEHP metabolites MEOHP and MEHHP were not measured in 1999-2000.
America's Children and the Environment | Third Edition
-------
Appendices | Appendix A: Data Tables
Table BlOb. Phthalate metabolites in children ages 6 to 17 years: Median concentrations in urine, by
race/ethnicity and family income, 2005-2008
Median concentration of phthalate metabolites in urine (ug/L)
DEHP
metabolites
DBP
metabolites
BBzP
metabolite
Race /Ethnicity
All Races/Ethnicities (n=l,586)
White non-Hispanic (n=435)
Black non-Hispanic (n=465)
Mexican-American (n=487)
All Other Races/Ethnicitiest
(n=199)
All Races/Ethnicities (n=l,586)
White non-Hispanic (n=435)
Black non-Hispanic (n=465)
Mexican-American (n=487)
All Other Races/Ethnicitiest
(n=199)
All Races/Ethnicities (n=l,586)
White non-Hispanic (n=435)
Black non-Hispanic (n=465)
Mexican-American (n=487)
All Other Races/Ethnicitiest
(n=199)
All Incomes^
(n=l,586)
54.0
57.9
55.1
44.4
48.1
41.8
40.9
47.2
38.5
41.0
17.4
18.2
19.0
13.7
15.2
< Poverty Level
(n=453)
57.3
58.9*
52.2*
53.4
NA**
49.9
54.1*
46.6*
43.5
NA**
18.7
19.4*
23.1*
14.1
NA**
> Poverty Level
(n=l,056)
53.0
58.1
56.9
38.4
47.7
40.2
40.3
48.2
33.7
39.8
17.1
18.0
18.4
13.3
12.7
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTES:
• DEHP = di-2-ethylhexyl phthalate, DBP = dibutyl phthalate (di-n-butyl phthalate and di-isobutyl phthalate), and BBzP =
butyl benzyl phthalate.
• Values below the limit of detection are assumed equal to the limit of detection divided by the square root of 2.
t The "All Other Races/Ethnicities" category includes all other races or ethnicities not specified, together with those individuals
who report more than one race.
t Includes sampled individuals for whom income information is missing.
*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
** Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, is 40% or
greater (RSE = standard error divided by the estimate), or the RSE cannot be reliably estimated.
Table BlOc: Phthalate metabolites in children ages 6 to 17 years: Median concentrations in urine by
age group, 2005-2008
Median concentration of phthalate metabolites in urine (ug/L)
DEHP metabolites
DBP metabolites
BBzP metabolite
All ages
54.0
41.8
17.4
Ages 6 to
10 years
57.1
41.4
20.1
Ages 11 to
15 years
53.6
43.8
16.5
Ages 16 to
17 years
51.1
38.2
13.5
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
America's Children and the Environment | Third Edition
-------
Appendix A: Data Tables | Appendices
NOTES:
• DEHP = di-2-ethylhexyl phthalate, DBP = dibutyl phthalate (di-n-butyl phthalate and di-isobutyl phthalate), and BBzP =
butyl benzyl phthalate.
• Values below the limit of detection are assumed equal to the limit of detection divided by the square root of 2.
Bisphenol A (BPA)
Table Bll: Bisphenol A in women ages 16 to 49 years: Median and 95th percentile concentrations in
urine, 2003-2010
Concentration of BPA in urine (ug/L)
Median
2003-2004
3.1
2005-2006
2.0
2007-2008
2.5
2009-2010
2.1
95 percentile
15.9
9.8
15.1
9.7
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTES:
• To reflect exposures to women who are pregnant or may become pregnant, the estimates are adjusted for the
probability (by age and race/ethnicity) that a woman gives birth. The intent of this adjustment is to approximate the
distribution of exposure to pregnant women. Results will therefore differ from a characterization of exposure to adult
women without consideration of birth rates.
• BPA does not appear to accumulate in bodily tissues; thus the distribution of NHANES urinary BPA levels may
overestimate high-end exposures as a result of collecting one-time urine samples rather than collecting urine for a
longer time period.6"8
Table Blla: Bisphenol A in women ages 16 to 49 years: Median concentrations in urine, by
race/ethnicity and family income, 2007-2010
1 Median concentration of BPA in urine (ug/L)
Race/ Ethnicity
All Races/Ethnicities
(n=l,179)
White non-Hispanic
(n=499)
Black non-Hispanic
(n=242)
Mexican-American
(n=227)
All Other Races/Ethnicitiest
(n=211)
All Incomes*
(n=l,179)
2.3
2.1
3.7
2.3
2.1
< Poverty Level
(n=329)
3.0
3.3
3.3*
2.2*
3.1*
> Poverty Level
(n=755)
2.1
2.0
4.2
2.3
1.8
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTES:
To reflect exposures to women who are pregnant or may become pregnant, the estimates are adjusted for the
probability (by age and race/ethnicity) that a woman gives birth. The intent of this adjustment is to approximate the
distribution of exposure to pregnant women. Results will therefore differ from a characterization of exposure to adult
women without consideration of birth rates.
The reported measurements of BPA in urine include both BPA itself and biologically inactive metabolites of BPA.
America's Children and the Environment | Third Edition
-------
Appendices | Appendix A: Data Tables
t The "All Other Races/Ethnicities" category includes all other races or ethnicities not specified, together with those individuals
who report more than one race.
t Includes sampled individuals for whom income information is missing.
*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
Table Bllb: Bisphenol A in women ages 16 to 49 years: 95th percentile concentrations in urine, by
race/ethnicity and family income, 2007-2010
1 95th percentile concentration of BPA in urine (ug/L)
Race/ Ethnicity
All Races/Ethnicities
(11=1,179)
White non-Hispanic
(n=499)
Black non-Hispanic
(n=242)
Mexica n-America n
(n=227)
All Other Races/Ethnicitiest
(n=211)
All Incomes^
(11=1,179)
12.2
9.7
15.1
14.7
NA**
< Poverty Level
(n=329)
14.5
NA**
14.8*
NA**
23.0*
> Poverty Level
(n=755)
10.6
8.1
15.1
17.8
NA**
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTES:
• To reflect exposures to women who are pregnant or may become pregnant, the estimates are adjusted for the
probability (by age and race/ethnicity) that a woman gives birth. The intent of this adjustment is to approximate the
distribution of exposure to pregnant women. Results will therefore differ from a characterization of exposure to adult
women without consideration of birth rates.
• The reported measurements of BPA in urine include both BPA itself and biologically inactive metabolites of BPA.
• BPA does not appear to accumulate in bodily tissues; thus the distribution of NHANES urinary BPA levels may
overestimate high-end exposures as a result of collecting one-time urine samples rather than collecting urine for a
longer time period.6"8
t The "All Other Races/Ethnicities" category includes all other races or ethnicities not specified, together with those individuals
who report more than one race.
t Includes sampled individuals for whom income information is missing.
*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
** Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, is 40% or
greater (RSE = standard error divided by the estimate), or the RSE cannot be reliably estimated.
America's Children and the Environment | Third Edition
-------
Appendix A: Data Tables | Appendices
rth
Table B12: Bisphenol A in children ages 6 to 17 years: Median and 95 percentile concentrations in
urine, 2003-2010
1 Concentration of BPA in urine (ug/L)
Median
95th percentile
2003-2004
4.0
16.0
2005-2006
2.4
16.5
2007-2008
2.4
12.2
2009-2010
2.0
9.7
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTE: BPA does not appear to accumulate in bodily tissues; thus the distribution of NHANES urinary BPA levels may
overestimate high-end exposures as a result of collecting one-time urine samples rather than collecting urine for a longer time
i 6-8
period.
Table B12a: Bisphenol A in children ages 6 to 17 years: Median concentrations in urine, by
race/ethnicity and family income, 2007-2010
Median concentration of BPA in urine (ug/L)
Race/ Ethnicity
All Races/Ethnicities
(n=l,417)
White non-Hispanic
(n=425)
Black non-Hispanic
(n=343)
Mexica n-America n
(n=379)
All Other Races/Ethnicitiest
(n=270)
All Incomes*
(n=l,417)
2.2
2.1
2.8
2.1
1.8
< Poverty Level
(n=426)
2.4
2.7*
3.1*
2.0
1.9*
> Poverty Level
(n=873)
2.1
2.0
2.7
2.2
2.0
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTE: The reported measurements of BPA in urine include both BPA itself and biologically inactive metabolites of BPA.
t The "All Other Races/Ethnicities" category includes all other races or ethnicities not specified, together with those individuals
who report more than one race.
t Includes sampled individuals for whom income information is missing.
*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
America's Children and the Environment | Third Edition
-------
Appendices | Appendix A: Data Tables
rth ,
Table B12b: Bisphenol A in children ages 6 to 17 years: 95 percentile concentrations in urine, by
race/ethnicity and family income, 2007-2010
1 95th percentile concentration of BPA in urine (ug/L)
Race/ Ethnicity
All Races/Ethnicities
(n=l,417)
White non-Hispanic
(n=425)
Black non-Hispanic
(n=343)
Mexican-American
(n=379)
All Other Races/Ethnicitiest
(n=270)
All Incomes^
(11=1,417)
11.9
12.2
12.6
12.3
9.1
< Poverty Level
(n=426)
10.4
10.4*
NA**
6.9
4.7*
> Poverty Level
(n=873)
12.2
12.2
12.4
15.6*
9.1
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTES:
• The reported measurements of BPA in urine include both BPA itself and biologically inactive metabolites of BPA.
• BPA does not appear to accumulate in bodily tissues; thus the distribution of NHANES urinary BPA levels may
overestimate high-end exposures as a result of collecting one-time urine samples rather than collecting urine for a
longer time period.6"8
t The "All Other Races/Ethnicities" category includes all other races or ethnicities not specified, together with those individuals
who report more than one race.
t Includes sampled individuals for whom income information is missing.
*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
** Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, is 40% or
greater (RSE = standard error divided by the estimate), or the RSE cannot be reliably estimated.
Table B12c: Bisphenol A in children ages 6 to 17 years: Median and 95th percentile concentrations by
age group, 2007-2010
Concentration of BPA in urine (ug/L)
Median
95th percentile
All ages
2.2
11.9
Ages 6 to
10 years
2.1
10.4
Ages 11 to
15 years
2.2
12.2
Ages 16 to
17 years
2.2
12.2
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTES:
• The reported measurements of BPA in urine include both BPA itself and biologically inactive metabolites of BPA.
• BPA does not appear to accumulate in bodily tissues; thus the distribution of NHANES urinary BPA levels may
overestimate high-end exposures as a result of collecting one-time urine samples rather than collecting urine for a
longer time period.6"8
America's Children and the Environment | Third Edition
-------
Appendix A: Data Tables | Appendices
Perchlorate
rth
Table B13. Perchlorate in women ages 16 to 49 years: Median and 95 percentile concentrations in
urine, 2001-2008
1 Concentration of perchlorate in urine (ug/L)
Median
95th percentile
2001-2002
3.3
15.0
2003-2004
2.9
NA**
2005-2006
3.2
13.0
2007-2008
3.4
16.5
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTES:
• To reflect exposures to women who are pregnant or may become pregnant, the estimates are adjusted for the
probability (by age and race/ethnicity) that a woman gives birth. The intent of this adjustment is to approximate the
distribution of exposure to pregnant women. Results will therefore differ from a characterization of exposure to adult
women without consideration of birth rates.
• Perchlorate does not appear to accumulate in bodily tissues; thus, the distribution of NHANES urinary perchlorate levels
may overestimate high-end exposures as a result of collecting one-time urine samples rather than collecting urine for a
longer time period.6'7'9
** Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, is 40% or
greater (RSE = standard error divided by the estimate), or the RSE cannot be reliably estimated.
Table B13a. Perchlorate in women ages 16 to 49 years: Median concentrations in urine, by
race/ethnicity and family income, 2005-2008
Median concentration of perchlorate in urine (ug/L)
Race/ Ethnicity
All Races/Ethnicities (n=3,529)
White Non-Hispanic (n=l,365)
Black Non-Hispanic (n=858)
Mexican-American (n=843)
All Other Races/Ethnicitiest (n=463)
All Incomes*
(77=3,529;
3.3
3.2
3.5
3.6
3.3
< Poverty Level
(n=861)
3.4
3.2
3.5
3.5
3.6
> Poverty Level
(n=2,453)
3.2
3.2
3.5
3.5
3.0
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTE: To reflect exposures to women who are pregnant or may become pregnant, the estimates are adjusted for the
probability (by age and race/ethnicity) that a woman gives birth. The intent of this adjustment is to approximate the
distribution of exposure to pregnant women. Results will therefore differ from a characterization of exposure to adult women
without consideration of birth rates.
t The "All Other Races/Ethnicities" category includes all other races or ethnicities not specified, together with those individuals
who report more than one race.
t Includes sampled individuals for whom income information is missing.
America's Children and the Environment | Third Edition
-------
Appendices | Appendix A: Data Tables
rth
Table B13b. Perchlorate in women ages 16 to 49 years: 95 percentile concentrations in urine, by
race/ethnicity and family income, 2005-2008
1 95th percentile concentration of perchlorate in urine (ug/L)
Race/ Ethnicity
All Races/Ethnicities
(n=3,529)
White Non-Hispanic
(n=l,365)
Black Non-Hispanic
(n=858)
Mexican-American
(n=843)
All Other Races/Ethnicitiest
(n=463)
All Incomes^
(11=3,529)
14.5
13.2
16.5
16.0
14.7
< Poverty Level
(n=861)
14.4
14.2
14.5*
16.5
13.1
> Poverty Level
(11=2,453)
14.4
13.2
19.4
15.3
14.7
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTES:
• To reflect exposures to women who are pregnant or may become pregnant, the estimates are adjusted for the
probability (by age and race/ethnicity) that a woman gives birth. The intent of this adjustment is to approximate the
distribution of exposure to pregnant women. Results will therefore differ from a characterization of exposure to adult
women without consideration of birth rates.
• Perchlorate does not appear to accumulate in bodily tissues; thus, the distribution of NHANES urinary perchlorate levels
may overestimate high-end exposures as a result of collecting one-time urine samples rather than collecting urine for a
longer time period.6'7'9
t The "All Other Races/Ethnicities" category includes all other races or ethnicities not specified, together with those individuals
who report more than one race.
t Includes sampled individuals for whom income information is missing.
*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
Table B13c. Perchlorate in children ages 6 to 17 years: Median and 95th percentile concentrations in
urine, 2001-2008
1 Concentration of perchlorate in urine (ug/L)
Median
95th percentile
2001-2002
4.9
15.0
2003-2004
4.5
16.0
2005-2006
4.6
14.9
2007-2008
4.8
18.6
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTE: Perchlorate does not appear to accumulate in bodily tissues; thus, the distribution of NHANES urinary perchlorate levels
may overestimate high-end exposures as a result of collecting one-time urine samples rather than collecting urine for a longer
time period.6'7'9
America's Children and the Environment | Third Edition
-------
Appendix A: Data Tables | Appendices
Table B13d. Perchlorate in children ages 6 to 17 years: Median concentrations in urine, by
race/ethnicity and family income, 2005-2008
1 Median concentration of perchlorate in urine (ug/L)
Race/ Ethnicity
All Races/Ethnicities
(n=4,638)
White Non-Hispanic
(n=l,282)
Black Non-Hispanic
(n=l,383)
Mexican-American
(n=l,397)
All Other Races/Ethnicitiest
(n=576)
All Incomes^
(n=4,638)
4.7
4.9
4.4
4.9
4.1
< Poverty Level
(n=l,294)
4.5
4.7
4.2
4.7
3.9*
> Poverty Level
(n=3,096)
4.8
4.9
4.5
5.0
4.4
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
t The "All Other Races/Ethnicities" category includes all other races or ethnicities not specified, together with those individuals
who report more than one race.
t Includes sampled individuals for whom income information is missing.
*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
Table B13e. Perchlorate in children ages 6 to 17 years: 95th percentile concentrations in urine, by
race/ethnicity and family income, 2005-2008
95th percentile concentration of perchlorate in urine (ug/L)
Race/ Ethnicity
All Races/Ethnicities
(n=4,638)
White Non-Hispanic
(11=1,282)
Black Non-Hispanic
(11=1,383)
Mexican-American
(n=l,397)
All Other Races/Ethnicitiest
(n=576)
All
Incomes^
(n=4,638)
17.2
17.6
17.5
15.6
16.9
< Poverty
Level
(n=l,294)
16.0
16.0
15.4
15.9
16.9*
> Poverty
Level
(n=3,096)
17.5
17.7
17.7
15.4
16.9
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTE: Perchlorate does not appear to accumulate in bodily tissues; thus, the distribution of NHANES urinary perchlorate levels
may overestimate high-end exposures as a result of collecting one-time urine samples rather than collecting urine for a longer
time period.6'7'9
t The "All Other Races/Ethnicities" category includes all other races or ethnicities not specified, together with those individuals
who report more than one race.
t Includes sampled individuals for whom income information is missing.
America's Children and the Environment | Third Edition
-------
Appendices | Appendix A: Data Tables
*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
Table B13f: Perchlorate in children ages 6 to 17 years: Median and 95th percentile concentrations by
age group, 2005-2008
1 Concentration of perchlorate in urine (ug/L) 1
Median
95th percentile
All ages
4.7
17.2
Ages 6 to
10 years
4.9
17.1
Ages 11 to
15 years
4.7
17.5
Ages 16 to
17 years
4.4
16.7
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
NOTE: Perchlorate does not appear to accumulate in bodily tissues; thus, the distribution of NHANES urinary perchlorate levels
may overestimate high-end exposures as a result of collecting one-time urine samples rather than collecting urine for a longer
time period.6'7'9
America's Children and the Environment | Third Edition
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Appendix A: Data Tables | Appendices
Health
Respiratory Diseases
Table HI: Percentage of children ages 0 to 17 years with asthma, 1997-2010
1997-2003 1
Asthma attack prevalence
Current asthma prevalence*
1997
5.5
1998
5.3
1999
5.3
2000
5.5
2001
5.7
8.7
2002
5.8
8.3
2003
5.5
8.5
2004-2009
Asthma attack prevalence
Current asthma prevalence*
2004
5.5
8.5
2005
5.2
8.9
2006
5.6
9.3
2007
5.2
9.1
2008
5.6
9.4
2009
5.5
9.6
2010
5.7
9.4
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey
NOTE: Data represent responses to the following survey questions: "Has a doctor or other health professional ever told you
that had asthma?" and if yes, "During the past 12 months, has had an episode of asthma or an
asthma attack?" For 2001-2010 the survey included the question: "Does still have asthma?" Responses are
provided by a parent or other knowledgeable household adult.
t This survey question was first asked in 2001.
Table Hla: Percentage of children ages 0 to 17 years with current asthma, 2001-2010, by sex
All children
Boys
Girls
All children
Boys
Girls
2001
8.7
9.9
7.5
2006
9.3
11.0
7.5
2002
8.3
9.5
7.2
2007
9.1
9.7
8.5
2003
8.5
9.5
7.5
2008
9.4
11.4
7.4
2004
8.5
10.2
6.7
2009
9.6
11.3
7.9
2005
8.9
10.0
7.8
2010
9.4
10.5
8.2
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey
NOTE: Data represent responses to the following survey questions: "Has a doctor or other health professional ever told you
that had asthma?" and if yes, "During the past 12 months, has had an episode of asthma or an
asthma attack?" For 2001-2010 the survey included the question: "Does still have asthma?" Responses are
provided by a parent or other knowledgeable household adult.
Table Hlb: Percentage of children ages 0 to 17 years with asthma, 1980-1996t
1980-1987
Asthma in the past 12 months
1980
3.6
1981
3.7
1982
4.1
1983 1984 1985
4.5 4.3 4.8
1986
5.1
1987
5.3
1988-1996
Asthma in the past 12 months
1988
5.0
1989
6.1
1990
5.8
1991 1992 1993 1994
6.4 6.3 7.2 6.9
1995
7.5
1996
6.2
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey
t The survey questions for asthma changed in 1997; data before 1997 cannot be directly compared to data in 1997 and later,
and are thus shown in this separate table. For 1980 to 1996, the asthma survey question was "Did have asthma
in the past 12 months?"
America's Children and the Environment | Third Edition
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Appendices | Appendix A: Data Tables
Table Hlc: Percentage of children ages 0 to 17 years with current asthma who reported an asthma
attack in the past 12 months, 2001-2010
2001-2008
Asthma attack prevalence among
those with current asthma
2009-2010
2001 2002 2003 2004 2005 2006 2007 2008
61.7 64.9 62.7 61.2 56.7 56.1 54.8 57.2
2009 2010
Asthma attack prevalence among 53.9 58.3
those with current asthma
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey
NOTE: Data represent responses to the following survey questions: "Has a doctor or other health professional ever told you
that had asthma?" and if yes, "During the past 12 months, has had an episode of asthma or an
asthma attack?" For 2001-2010 the survey included the question: "Does still have asthma?" Responses are
provided by a parent or other knowledgeable household adult.
Table H2: Percentage of children ages 0 to 17 years reported to have current asthma by race/ethnicity
and family income, 2007-2010
> Poverty Level (Detail)
Race/ Ethnicity
All
(n= 40,569)
White non-Hispanic
(n= 17,692)
Black or African-American non-
Hispanic
(n= 6,628)
Asian non-Hispanic
(n = 2,255)
Hispanic
(n= 12,343)
Mexican
(n= 8,114)
Puerto Rican
(n=l,116)
All Other Racest
(n= 1,651)
American Indian or Alaska
Native non-Hispanic
(n=219)
All
(n = 40,569)
9.4
8.2
16.0
6.8
7.9
7.0
16.5
12.4
10.7
< Poverty
Level
(n= 8,160)
12.2
10.6
18.8
NA**
8.7
6.6
23.3
15.5
13.0*
>Poverty
Level
(n= 32,409)
8.7
7.9
14.4
7.2
7.5
7.2
12.6
11.4
NA**
100-200% of
Poverty Level
(n= 9,603)
9.9
9.6
15.0
5.7*
7.3
6.5
15.3
14.8
NA**
> 200% of
Poverty Level
(n = 22,806)
8.2
7.5
13.9
7.7
7.8
8.0
11.0
9.7
NA**
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey
t The "All Other Races" category includes all other races not specified, together with those individuals who report more than
one race.
* The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate).
** Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, is 40% or
greater (RSE = standard error divided by the estimate).
America's Children and the Environment | Third Edition
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Appendix A: Data Tables | Appendices
Table H2a: Percentage of children ages 0 to 17 years reported to have current asthma by age and sex,
2007-2010
All children
Ages 0 to
17 years
9.4
Ages 0 to
5 years
7.1
Ages 6 to
10 years
10.0
Ages 11 to
17 years
11.0
Boys
10.7
8.8
11.9
11.7
Girls
8.0
5.2
8.1
10.3
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey
Table H3: Children's emergency room visits and hospitalizations for asthma and other respiratory
causes, ages 0 to 17 years, 1996-2008
1996-1999
Emergency Room Visits
Asthma and all other respiratory causes
All respiratory causes other than asthma
Upper respiratory
Pneumonia or influenza
Other lower respiratory
Asthma
Hospitalizations
Asthma and all other respiratory causes
All respiratory causes other than asthma
Upper respiratory
Pneumonia or influenza
Other lower respiratory
Asthma
1996
636.4
521.9
408.4
56.3
57.2
114.4
90.3
59.9
28.9
29.6
1.4
30.4
Rate per 10,000 children
1997 1998
631.5
519.4
409.3
52.0
58.0
112.1
102.2
69.1
37.2
30.6
1.3
33.1
654.7
530.3
426.0
58.0
46.3
124.4
86.3
61.4
27.6
33.1
0.7
25.0
1999
619.9
515.4
403.0
58.8
53.6
104.5
101.4
72.5
39.5
32.0
1.0
28.9
2000-2003
Emergency Room Visits
Asthma and all other respiratory causes
All respiratory causes other than asthma
Upper respiratory
Pneumonia or influenza
Other lower respiratory
Asthma
Hospitalizations
Asthma and all other respiratory causes
All respiratory causes other than asthma
Upper respiratory
Pneumonia or influenza
Other lower respiratory
Asthma
2000
622.7
521.8
428.1
54.1
39.7
100.9
84.6
57.3
32.5
23.9
1.0
27.2
Rate per 10,000 children
2001 2002
624.0
532.3
426.8
63.3
42.2
91.7
85.0
61.0
33.7
26.6
NA**
24.0
721.1
621.3
494.4
79.8
47.1
99.9
86.7
62.1
33.6
27.8
0.6
24.6
2003
740.2
644.8
499.1
94.3
51.5
95.4
89.6
61.1
29.8
30.2
1.2
28.4
America's Children and the Environment | Third Edition
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Appendices | Appendix A: Data Tables
2004-2007
Emergency Room Visits
Asthma and all other respiratory causes
All respiratory causes other than asthma
Upper respiratory
Pneumonia or influenza
Other lower respiratory
Asthma
Hospitalizations
Asthma and all other respiratory causes
All respiratory causes other than asthma
Upper respiratory
Pneumonia or influenza
Other lower respiratory
Asthma
2004
528.8
426.0
331.6
56.9
37.4
102.8
80.4
55.8
30.5
24.2
1.1
24.6
Rate per 10,000 children
2005 2006
639.8
537.8
441.3
62.6
33.9
102.1
72.8
52.5
25.8
26.4
0.4*
20.3
584.3
504.1
396.9
61.1
46.1
80.2
66.3
47.3
23.5
22.9
0.9
18.9
2007
625.1
538.5
416.2
87.6
34.6
86.6
61.4
42.3
23.1
18.9
NA**
19.1
2008
Emergency Room Visits
Asthma and all other respiratory causes
All respiratory causes other than asthma
Upper respiratory
Pneumonia or influenza
Other lower respiratory
Asthma
Hospitalizations
Asthma and all other respiratory causes
All respiratory causes other than asthma
Upper respiratory
Pneumonia or influenza
Other lower respiratory
Asthma
2008
619.1
516.6
388.2
91.3
37.1
102.6
56.0
39.9
19.1
20.3
NA**
16.2
Rate per 10,000 children
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Hospital Ambulatory Medical
Care Survey and National Hospital Discharge Survey
* The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate).
** Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, exceeds 40%
(RSE = standard error divided by the estimate) or there are fewer than 30 sampled hospitalizations.
America's Children and the Environment | Third Edition
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Appendix A: Data Tables | Appendices
Table H3a: Children's emergency room visits for asthma and other respiratory causes, by
race/ethnicity, ages 0 to 17 years, 2005-2008
Rate per 10,000 children
All
(n=5,366)
White non-Hispanic
(11=2,248)
2005
639.8
484.8
2006
584.3
442.3
2007
625.1
518.8
2008 2005-2008
619.1 617.1
500.9
486.6
Black non-Hispanic
(11=1,557)
1,242.7 1,276.0 1,183.5 1,258.0 1,240.1
American Indian/Alaska Native non-
Hispanic (n=33)
Asian and Pacific Islander non-Hispanic
(n=179)
NA**
409.4*
NA**
404.7
NA**
341.8*
NA**
333.1*
536.2
371.4
Hispanic
(n=l,331)
788.9
600.4
656.4
646.7
671.5
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Hospital Ambulatory Medical
Care Survey
* The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate).
** Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, exceeds 40%
(RSE = standard error divided by the estimate) or there are fewer than 30 sampled emergency room visits.
Table H3b: Children's emergency room visits for asthma and other respiratory causes, by age,
2005-2008
Rate per 10,000 children
Ages 0 to 18 years
Ages 0 to 1 year
Age lyear
Age 2 years
Ages 3 to 5 years
Ages 6 to 10 years
Ages 11 to 15 years
Ages 16 to 17 years
2005
639.8
2,344.8
1,884.3
1,081.9
778.4
391.6
252.6
333.2
2006
584.3
2,040.5
1,696.4
957.2
668.1
384.1
251.0
310.2
2007
625.1
2,098.3
1,823.1
1,015.0
719.8
389.5
276.7
362.9
2008
619.1
2,090.4
1,727.5
972.7
751.9
382.7
268.3
346.1
2005-2008
617.1
2,142.1
1,782.3
1,006.3
729.5
387.0
262.0
338.2
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Hospital Ambulatory Medical
Care Survey
Table H3c: Children's hospitalizations for asthma and other respiratory causes, by race,t ages 0 to 17
years, 2005-2008
All* (n=18,088)
White (n=9,213)
B\ack(n=4,154)
2005
72.8
61.7
Rate per 10,000 children
2006 2007 2008 2005-2008
66.3 61.4 56.0 64.1
56.5 47.7 42.7 52.1
94.1
91.6
78.0
72.3
84.0
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Hospital Discharge Survey
t Estimates for ethnicity not available. Race categories include children of Hispanic ethnicity.
t Includes races other than White and Black.
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Appendices | Appendix A: Data Tables
Table H3d: Children's hospitalizations for asthma and other respiratory causes, by age, 2005-2008
Rate per 10,000 children
Ages 0 to 18 years
Ages 0 to 1 year
Age lyear
Age 2 years
Ages 3 to 5 years
Ages 6 to 10 years
Ages 11 to 15 years
Ages 16 to 17 years
2005
72.8
477.2
232.7
115.9
70.1
33.0
15.3
8.7
2006
66.3
399.6
211.9
112.2
68.2
28.8
13.8
15.0
2007
61.4
364.8
173.5
117.9
53.9
29.0
17.2
13.9
2008
56.0
344.3
152.2
89.7
53.3
27.6
13.1
14.1
2005-2008
64.1
395.5
191.9
108.8
61.3
29.6
14.9
12.9
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Hospital Discharge Survey
Childhood Cancer
Table H4: Cancer incidence and mortality for children ages 0 to 19 years, 1992-2009
1992-1997
Incidence
Mortality
1992
158.4
33.1
1993
161.4
32.6
Age-adjusted rate
1994
153.3
31.2
per million children
1995
154.8
29.8
1996
160.9
28.7
1997
154.4
28.8
1998-2003
Incidence
Mortality
1998
164.1
27.5
1999
158.0
28.0
Age-adjusted rate
2000
162.3
28.2
per million children
2001
166.6
27.5
2002
171.9
28.0
2003
156.6
27.4
2004-2009
Incidence
Mortality
2004
167.2
27.2
2005
174.6
26.6
Age-adjusted rate
2006
157.5
24.6
per million children
2007
172.3
24.9
2008
172.5
24.4
2009
175.4
23.5
DATA: National Cancer Institute, Surveillance, Epidemiology, and End Results (SEER) Program
Table H4a: Cancer incidence for children ages 0 to 19 years by race/ethnicity and sex, 2007-2009
Age-adjusted rate per million children
All Races/Ethnicities (n=5,974)
White non-Hispanic (n=2,963)
Black non-Hispanic (n=574)
American Indian/Alaska Native non-Hispanic (n=69)
Asian or Pacific Islander non-Hispanic (n=560)
Hispanic (n=l,717)
Male
183.3
199.7
137.2
120.8
155.7
181.9
Female
163.0
175.2
129.5
152.6
147.5
156.1
All
173.4
187.8
133.4
136.8
151.7
169.3
DATA: National Cancer Institute, Surveillance, Epidemiology, and End Results (SEER) Program
America's Children and the Environment | Third Edition
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Appendix A: Data Tables | Appendices
Table H4b: Cancer mortality for children ages 0 to 19 years by race/ethnicity and sex, 2007-2009
Age-adjusted rate per million children
All Races/Ethnicities (n=6,071)
White non-Hispanic (n=3,384)
Male
26.1
25.8
Female
22.4
21.7
All
24.3
23.8
Black non-Hispanic (n=900)
25.6
23.4
24.5
American Indian/Alaska Native non-Hispanic (n=55)
23.6
20.5
22.1
Asian or Pacific Islander non-Hispanic (n=248)
Hispanic (n=l,386)
26.0
16.5
21.3
27.9
25.4
26.7
DATA: National Cancer Institute, Surveillance, Epidemiology, and End Results (SEER) Program
Following the recommendations of the National Cancer Institute, the mortality rates for all the groups except for "All
races/ethnicities" excluded data from the following states, which had large numbers with unknown ethnicity: North Dakota and
South Carolina. See http://seer.cancer.gov/seerstat/variables/mort/origin_recode_1990+/mdex.html.
Table H4c: Cancer incidence for children 0 to 19 years by age, 2007-2009
Ages 0 to 4 years
Age-adjusted rate per million children
207.6
Ages 5 to 9 years
Ages 10 to 14 years
Ages 15 to 19 years
Ages 0 to 19 years
116.9
139.0
232.3
173.4
DATA: National Cancer Institute, Surveillance, Epidemiology, and End Results (SEER) Program
Table H5: Cancer incidence for children ages 0 to 19 years, by type, 1992-2006
Age-adjusted rate per million children
Acute lymphoblastic leukemia
Central nervous system tumors
Germ cell tumors
Soft tissue sarcomas
Hodgkin's lymphoma
Acute myeloid leukemia
Non-Hodgkin's lymphoma
Neuroblastoma
Malignant melanoma
Thyroid carcinoma
Osteosarcoma
Wilms' tumor
Other and unspecified carcinomast
Ewing's sarcoma
Burkitt's lymphoma
Hepatoblastoma
1992-1994
29.5
28.7
11.3
10.2
12.3
7.3
7.4
7.4
4.4
5.2
4.9
5.7
3.8
3.2
2.0
1.1
1995-1997
32.3
26.8
11.5
11.5
11.6
7.7
7.2
7.7
4.7
5.2
4.8
5.8
3.9
2.3
1.9
1.2
1998-2000
33.4
26.9
10.8
12.0
12.2
8.3
7.7
6.9
4.7
6.2
4.8
5.5
3.9
2.2
2.3
1.8
2001-2003
32.4
29.6
12.0
11.5
11.2
8.0
9.0
7.3
5.8
6.1
5.3
4.7
3.6
2.5
2.4
1.5
2004-2006
34.5
27.0
12.6
12.3
10.8
8.5
8.8
8.0
5.7
5.5
4.5
4.4
3.3
2.8
2.2
1.7
DATA: National Cancer Institute, Surveillance, Epidemiology, and End Results (SEER) Program
t "Other and unspecified carcinomas" represents all carcinomas and other malignant epithelial neoplasms other than thyroid
carcinoma and malignant melanoma.
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Appendices | Appendix A: Data Tables
Table H5a: Cancer incidence rates per million children for malignant cancers by age and type, 2004-2006
Age-adjusted rate per million children
Acute lymphoblastic leukemia
Central nervous system tumors
Germ cell tumors
Soft-tissue sarcomas
Hodgkin's lymphoma
Acute myeloid leukemia
Non-Hodgkin's lymphoma
Neuroblastoma
Malignant melanoma
Thyroid carcinoma
Osteosarcoma
Wilms' tumor
Other and unspecified carcinomast
Ewing's sarcoma
Burkitt's lymphoma
Hepatoblastoma
Ages 0 to
4 years
66.3
35.1
7.5
11.1
NA**
13.2
3.2
28.5
0.9*
NA**
NA**
13.4
NA**
NA**
1.5
6.9
Ages 5 to
9 years
33.6
30.4
2.9
7.1
4.1
4.6
5.2
2.8
1.7
1.6
2.6
3.8
NA**
1.6
2.6
NA**
Ages 10 to
14 years
22.8
23.2
9.2
12.8
12.0
7.3
10.5
1.4
4.3
4.6
7.3
NA**
3.5
3.5
2.4
NA**
Ages 15 to
19 years
17.0
19.7
30.8
18.3
26.0
9.0
15.9
NA**
15.5
15.5
7.9
NA**
9.0
5.1
2.2
NA**
Ages 0 to
19 years
34.5
27.0
12.6
12.3
10.8
8.5
8.8
8.0
5.7
5.5
4.5
4.4
3.3
2.8
2.2
1.7
DATA: National Cancer Institute, Surveillance, Epidemiology, and End Results (SEER) Program
t "Other and unspecified carcinomas" represents all carcinomas and other malignant epithelial neoplasms other than thyroid
carcinoma and malignant melanoma.
* The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate).
** Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, is 40% or
greater (RSE = standard error divided by the estimate).
Neurodevelopmental Disorders
Table H6: Percentage of children ages 5 to 17 years reported to have attention-deficit/hyperactivity
disorder, by sex, 1997-2010
All children
Boys
6.3
9.5
6.7
9.6
6.4
9.6
7.5
10.6
Girls
3.0
3.7
3.0
4.2
All children
All children
7.2
7.4
8.1
8.5
7.2
8.1
8.3
Boys
Girls
10.3
3.9
2005
11.6
4.4
2006
10.3
4.0
2007
11.5
4.8
2008
9.1
Boys
Girls
•
All children
Boys
Girls
10.4
4.4
9.8
13.2
12.3
4.5
9.5
12.5
11.2
4.8
12.5
5.5
6.1
6.2
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Appendix A: Data Tables | Appendices
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey
NOTE: Data represent responses to the survey question: "Has a doctor or health professional ever told you that
had Attention Deficit/Hyperactivity Disorder (ADHD) or Attention Deficit Disorder (ADD)?" Responses are provided by a parent
or other knowledgeable household adult.
Table H6a: Percentage of children reported to have attention-deficit/hyperactivity disorder, by age
and sex, 2007-2010
All children
Boys
Ages 5 to
17 years
9.1
12.4
Ages 5 to
10 years
6.7
8.9
Ages 11 to
17 years
11.1
15.3
Girls
5.7
4.4
6.7
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey
NOTE: Data represent responses to the survey question: "Has a doctor or health professional ever told you that
had Attention Deficit/Hyperactivity Disorder (ADHD) or Attention Deficit Disorder (ADD)?" Responses are provided by a parent
or other knowledgeable household adult.
Table H6b: Percentage of children ages 5 to 17 years reported to have attention-deficit/hyperactivity
disorder, by race/ethnicity and family income, 2007-2010
All races/ethnicities
(n=28,880)
White non-Hispanic
(n=12,917)
Black or African-American
non-Hispanic
(n=4,830)
All Incomes
(n =28,880)
9.1
10.7
< Poverty
Level
(n=5,418)
11.3
16.5
> Poverty
Level
(n=23,462)
8.6
10.1
> Poverty Level (Detail)
100-200% of > 200% of Poverty
Poverty Level Level
(n=6,703) (n=16,759)
10.2
14.3
7.9
9.0
10.2
13.3
8.5
9.7
7.8
Asian non-Hispanic
(n=l,589)
Hispanic
(n=8,450)
Mexican
(n=5,545)
Puerto Rican
^=794;
All Other Racest
(n=l,094)
1.6
4.8
4.2
10.1
11.6
NA**
5.6
4.9
12.7
16.2
1.9
4.4
3.8
8.7
10.2
NA**
4.8
4.3
10.3
14.9
2.0
4.1
3.2
7.7
7.8
American Indian or Alaska
Native non-Hispanic
(n=165)
9.9*
NA*
7.1*
NA*
NA*
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey
NOTE: Data represent responses to the survey question: "Has a doctor or health professional ever told you that
had Attention Deficit/Hyperactivity Disorder (ADHD) or Attention Deficit Disorder (ADD)?" Responses are provided by a parent
or other knowledgeable household adult.
t The "All Other Races" category includes all other races not specified, together with those individuals who report more than
one race.
America's Children and the Environment | Third Edition
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Appendices | Appendix A: Data Tables
* The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate).
** Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, is 40% or
greater (RSE = standard error divided by the estimate).
Table H7: Percentage of children ages 5 to 17 years reported to have a learning disability, by sex,
1997-2010
All children
Boys
Girls
All children
Boys
Girls
All children
Boys
Girls
All children
Boys
Girls
1997
8.7
11.4
6.0
2001
8.6
11.0
6.1
2005
7.8
9.7
5.8
2009
9.1
11.7
6.5
1998
8.2
10.4
5.9
2002
9.2
11.5
6.7
2006
8.6
10.8
6.4
2010
8.6
10.1
7.1
1999
8.1
11.0
5.0
2003
8.3
10.2
6.3
2007
8.4
10.8
5.8
2000
8.7
10.9
6.4
2004
8.8
10.6
6.9
2008
9.1
11.2
6.9
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey
NOTE: Data represent responses to the survey question: "Has a representative from a school or a health professional ever told
you that had a learning disability?" Responses are provided by a parent or other knowledgeable household
adult.
Table H7a: Percentage of children reported to have a learning disability, by age and sex, 2007-2010
••
All children
Boys
Girls
Ages 5 to
17 years
8.8
10.9
6.6
Ages 5 to
10 years
7.5
9.3
5.6
Ages 11 to
17 years
9.9
12.4
7.4
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey
NOTE: Data represent responses to the survey question: "Has a representative from a school or a health professional ever told
you that had a learning disability?" Responses are provided by a parent or other knowledgeable household
adult.
America's Children and the Environment | Third Edition
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Appendix A: Data Tables | Appendices
Table H7b: Percentage of children ages 5 to 17 years reported to have
race/ ethnicity and family income, 2007-2010
a learning disability, by
| > Poverty Level (Detail)
All races/ethnicities
(n=28,889)
White non-Hispanic
(77=32,929;
Black or African-American
non-Hispanic
(n=4,830)
Asian non-Hispanic
(n=l,594)
Hispanic
(n=8,445)
Mexican
(n=5,542)
Puerto Rican
^=792;
All Other Racest
(n=l,091)
American Indian or Alaska
Native non-Hispanic
(n=163)
All Incomes
(n=28,889)
8.8
9.3
10.2
2.7
7.2
7.1
10.8
11.2
13.9
< Poverty
Level
(n=5,414)
12.6
17.1
13.6
NA**
8.7
7.9
14.5
15.8
NA**
> Poverty
Level
(n=23,475)
7.9
8.4
8.3
2.9
6.6
6.7
8.6
9.8
12.0*
100-200% of
Poverty Level
(n=6,700)
10.3
11.7
10.9
NA**
7.7
7.6
11.1
16.2
NA**
> 200% of
Poverty Level
(n=16,775)
7.0
7.6
6.5
3.2
5.4
5.7
7.2
6.6
NA**
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey
NOTE: Data represent responses to the survey question: "Has a representative from a school or a health professional ever told
you that had a learning disability?" Responses are provided by a parent or other knowledgeable household
adult.
t The "All Other Races" category includes all other races not specified, together with those individuals who report more than
one race.
* The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate).
** Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, is 40% or
greater (RSE = standard error divided by the estimate).
Table H8: Percentage of children ages 5 to 17 years reported to have autism, 1997-2010
All children
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey
NOTE: Data represent responses to the survey question: "Has a doctor or health professional ever told you that
had Autism?" Responses are provided by a parent or other knowledgeable household adult.
America's Children and the Environment | Third Edition
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Appendices | Appendix A: Data Tables
* The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate).
Table H8a: Percentage of children reported to have autism, by age and sex, 2007-2010
All children
Boys
Girls
Ages 5 to
17 years
1.0
Ages 5 to 10
1.1
Ages 11 to
17 years
0.8
1.5
1.7
1.3
0.4
0.5
0.3
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey
NOTE: Data represent responses to the survey question: "Has a doctor or health professional ever told you that
had Autism?" Responses are provided by a parent or other knowledgeable household adult.
Table H8b: Percentage of children ages 5 to 17 years reported to have autism, by race/ethnicity and
family income, 2007-2010
All races/ethnicities
(n= 28,919)
White non-Hispanic
(n= 12,938)
All Incomes
(n= 28,919)
1.0
1.1
< Poverty
Level
(n= 5,425)
1.0
> Poverty Level (Detail)
> Poverty 100-200% of > 200% of
Level Poverty Level Poverty Level
(n = 23,494) (n = 6,703) (n = (16,792)
0.9
1.8
1.0
0.8
1.1
1.0
1.0
Black or African-American
non-Hispanic
(n = 4,840)
Asian non-Hispanic
(n = 1,594)
Hispanic
(n = 8,452)
0.7
NA*
0.9
1.0*
0.8
0.8*
0.6
NA*
0.7*
0.8
0.5
NA**
NA**
0.9*
0.5
Mexican
(n = 5,547)
0.5
0.8
0.4
0.3*
0.4*
Puerto Rican
(n = 793)
All Other Racest
(n= 1,095)
0.9*
1.7*
NA**
NA**
NA**
1.7*
NA**
NA**
NA**
NA**
American Indian or Alaska
Native non-Hispanic
(n=165)
NA*
NA*
NA*
NA*
NA*
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey
NOTE: Data represent responses to the survey question: "Has a doctor or health professional ever told you that
had Autism?" Responses are provided by a parent or other knowledgeable household adult.
t The "All Other Races" category includes all other races not specified, together with those individuals who report more than
one race.
* The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate).
** Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, is 40% or
greater (RSE = standard error divided by the estimate).
America's Children and the Environment | Third Edition
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Appendix A: Data Tables | Appendices
Table H9: Percentage of children ages 5 to 17 years reported to have intellectual disability (mental
retardation), 1997-2010
All children
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey
NOTE: Data represent responses to the survey question: "Has a doctor or health professional ever told you that
had Mental Retardation?" Responses are provided by a parent or other knowledgeable household adult.
Table H9a: Percentage of children reported to have intellectual disability (mental retardation), by age
and sex, 2007-2010
All children
Boys
Ages 5 to
17 years
0.8
Ages 5 to
10 years
0.6
Ages 11 to
17 years
0.9
0.9
0.8
1.0
Girls
0.6
0.5
0.7
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey
NOTE: Data represent responses to the survey question: "Has a doctor or health professional ever told you that
had Mental Retardation?" Responses are provided by a parent or other knowledgeable household adult.
Table H9b: Percentage of children ages 5 to 17 years reported to have intellectual disability (mental
retardation), by race/ethnicity and family income, 2007-2010
< Poverty > Poverty
All Incomes Level Level
(n = 28,920) In = 5,423) In = 23,497)
> Poverty Level (Detail)
100-200% of > 200% of
Poverty Level Poverty Level
In =6,705) In =16,791)
(n= 28,920)
White non-Hispanic
(n= 12,939)
0.8
0.7
1.2
1.4*
0.7
0.6
1.0
1.0
0.6
0.5
Black or African-American
non-Hispanic
(n = 4,836)
1.0
1.2"
0.9
1.1*
0.7*
Asian non-Hispanic
(n = 1,594)
Hispanic
(n =8,456)
Mexican (n = 5,549)
Puerto Rican (n = 795)
All Other Racest (n = 1,095)
American Indian or Alaska
Native non-Hispanic
(n=165)
0.7*
0.8
0.8
0.6*
0.8*
NA**
NA**
1.0*
1.1*
NA**
NA**
NA**
0.7*
0.7
0.6
NA**
NA**
NA**
NA**
0.9
1.0
NA**
NA**
NA**
0.7*
0.4
0.2*
NA**
NA**
NA**
America's Children and the Environment | Third Edition
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Appendices | Appendix A: Data Tables
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Interview Survey
NOTE: Data represent responses to the survey question: "Has a doctor or health professional ever told you that
had Mental Retardation?" Responses are provided by a parent or other knowledgeable household adult.
t The "All Other Races" category includes all other races not specified, together with those individuals who report more than
one race.
* The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate).
** Not available. The estimate is not reported because it has large uncertainty: the relative standard error, RSE, is 40% or
greater (RSE = standard error divided by the estimate).
Obesity
Table H10. Percentage of children ages 2 to 17 years who were obese, 1976-2008
All Races/Ethnicities
White non-Hispanic
Black non-Hispanic
Mexica n-America n
All Other
Races/Ethnicitiest
1976-
1980
5.4
4.7
7.3
10.7*
6.5
1988-
1991
9.4
8.8
11.2
13.3
6.9*
1991-
1994
11.0
9.7
13.4
15.6
11.3*
1999-
2000
13.8
10.5*
18.2
20.7
17.5
2001-
2002
15.2
13.4
17.9
19.6
16.4
2003-
2004
16.8
15.7
19.7
19.4
16.0
2005-
2006
15.3
13.0
20.1
22.7
12.3
2007-
2008
16.9
15.4
19.9
21.0
16.3
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics and National Center for Environmental
Health, National Health and Nutrition Examination Survey
t The "All Other Races/Ethnicities" category includes all other races or ethnicities not specified, together with those individuals
who report more than one race.
*The estimate should be interpreted with caution because the standard error of the estimate is relatively large: the relative
standard error, RSE, is at least 30% but is less than 40% (RSE = standard error divided by the estimate), or the RSE may be
underestimated.
Table HlOa. Percentage of children who were obese, by age group, 1976-2008
2-5
years
6-10
years
11-15
years
16-17
years
2-17
years
1976-
1980
4.7
6.2
5.5
4.8
5.4
1988-
1991
7.3
10.1
9.1
12.3
9.4
1991-
1994
7.1
12.7
13.2
8.8
11.0
1999-
2000
10.4
14.3
15.9
13.4
13.8
2001-
2002
10.5
16.0
17.0
16.3
15.2
2003-
2004
13.6
17.3
18.0
18.1
16.8
2005-
2006
10.9
14.5
18.1
17.9
15.3
2007-
2008
10.1
19.3
19.5
18.2
16.9
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health and Nutrition
Examination Survey
America's Children and the Environment | Third Edition
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Appendix A: Data Tables | Appendices
Table Hll. Percentage of children ages 2-17 who were obese, by race/ethnicity and family income,
2005-2008
Race/ Ethnicity
All Races/Ethnicities
(n=6,654)
White non-Hispanic
(n=l,915)
Black non-Hispanic
(n=l,874)
All Incomes*
(n=6654)
16.1
< Poverty Level
(n=l,955)
19.9
> Poverty Level
(n=4,314)
15.1
> Poverty (Detail)
100-200% of > 200% of
Poverty Level Poverty Level
(n=l,691) (n=2,623)
18.4
13.8
: 14.2
20.0
17.4
19.7
13.7
19.9
17.9
21.6
12.5
18.8
Mexica n-America n
(n=2,012)
21.9
22.3
21.6
21.0
22.3
All Other
Races/Ethnicitiest
(n=853)
14.5
22.7
11.9
11.9
11.9
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health and Nutrition
Examination Survey
t The "All Other Races/Ethnicities" category includes all other races or ethnicities not specified, together with those individuals
who report more than one race.
t Includes sampled individuals for whom income information is missing.
Adverse Birth Outcomes
Table H12: Percentage of babies born preterm, by race/ethnicity, 1993-2008
1993-2000
All races/
ethnicities
White non-
Hispanic
Black or African-
American non-
Hispanic
Asian or Pacific
Islander non-
Hispanic
American Indian
or Alaska Native
non-Hispanic
Hispanic
Mexican
Puerto Rican
Unknown
ethnicity
1993
11.0
9.1
18.6
10.0
12.3
11.0
10.6
13.3
10.1
1994
11.0
9.3
18.2
10.1
12.0
10.9
10.6
13.4
11.0
1995
11.0
9.4
17.8
9.9
12.4
10.9
10.6
13.4
10.5
1996
11.0
9.5
17.5
10.0
11.9
10.9
10.5
13.2
9.8
1997
11.4
9.9
17.6
10.2
12.2
11.2
10.8
13.7
10.7
1998
11.6
10.2
17.6
10.3
12.2
11.4
11.0
13.9
10.5
1999
11.8
10.5
17.6
10.4
12.7
11.4
11.1
13.7
10.5
2000
11.6
10.4
17.4
9.9
12.6
11.2
11.0
13.5
10.8
America's Children and the Environment | Third Edition
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Appendices | Appendix A: Data Tables
2001-2008
All
races/ethnicities
White non-
Hispanic
Black or African-
American non-
Hispanic
Asian or Pacific
Islander non-
Hispanic
American Indian
or Alaska Native
non-Hispanic
Hispanic
Mexican
Puerto Rican
Unknown
ethnicity
2001
11.9
10.8
17.6
10.3
13.2
11.4
11.2
13.7
11.3
2002
12.1
11.0
17.7
10.4
13.0
11.6
11.4
14.0
11.2
2003
12.3
11.3
17.8
10.4
13.5
11.8
11.7
13.8
12.8
DATA: Centers for Disease Control and Prevention, National
Table H12a. Percentage of babies born preterm,
2004
12.5
11.5
17.9
10.5
13.7
12.0
11.8
14.0
12.8
2005
12.7
11.7
18.4
10.7
14.2
12.1
11.8
14.3
13.2
2006
12.8
11.7
18.5
10.9
14.3
12.2
11.8
14.4
13.1
Center for Health Statistics, National Vital
by mother's age, 1993-2008
2007
12.7
11.5
18.3
10.8
14.1
12.3
11.9
14.5
13.6
2008
12.3
11.1
17.5
10.6
13.8
12.1
11.6
14.1
13.9
Statistics System
1993-2000 1
Ages < 20 years
Ages 20 to
39 years
Ages 40+ years
1993
14.3
10.4
13.2
1994
14.2
10.5
13.7
1995
13.8
10.5
13.7
1996
13.6
10.5
13.8
1997
13.8
10.9
14.4
1998
14.0
11.2
14.9
1999
14.1
11.3
15.2
2000
13.9
11.2
15.1
2001-2008 1
Ages < 20 years
Ages 20 to
39 years
Ages 40+ years
2001
14.1
11.6
15.6
2002
14.0
11.7
16.0
2003
14.3
12.0
16.3
DATA: Centers for Disease Control and Prevention, National
Table H12b. Percentage of babies born preterm,
2004
14.5
12.1
16.6
2005
14.7
12.4
16.8
2006
14.8
12.4
17.0
2007
14.6
12.3
17.2
2008
14.1
12.0
17.1
Center for Health Statistics, National Vital Statistics System
by all births, singletons, and multiples, 1993-2008
1993-2000 1
1993
All births 11.0
Singletons
9.9
Multiples 53.1
1994
11.0
9.9
54.0
1995
11.0
9.8
54.6
1996
11.0
9.7
55.6
1997
11.4
10.0
57.3
1998
11.6
10.1
58.4
1999
11.8
10.3
59.4
2000
11.6
10.1
58.7
2001-2008 1
All births
Singletons
Multiples
DATA: Centers for Disease
2001
11.9
10.4
59.4
Control
2002
12.1
10.4
60.1
and Prevention,
2003
12.3
10.6
61.2
National
2004
12.5
10.8
61.4
2005
12.7
11.0
62.1
Center for Health Statistics,
2006
12.8
11.1
61.9
National Vital
2007
12.7
11.0
61.6
2008
12.3
10.6
60.4
Statistics System
America's Children and the Environment | Third Edition
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Appendix A: Data Tables | Appendices
Table HIS: Percentage of babies born at term with low birth weight, by race/ ethnicity, 1993-2008
1993-2000
All races/ethnicities
White non-Hispanic
Black or African-American
non-Hispanic
Asian or Pacific Islander non-
Hispanic
American Indian or Alaska
Native non-Hispanic
Hispanic
Mexican
Puerto Rican
Unknown ethnicity
1993
2.6
2.1
4.6
2.9
2.4
2.4
2.3
3.4
2.5
1994
2.6
2.2
4.5
3.0
2.3
2.4
2.2
3.2
2.6
1995
2.6
2,
4,
3,
2,
2,
2,
3,
2,
,2
,5
,1
,3
,3
,2
,3
,4
1996
2.6
2.
4.
3.
2.
2.
2.
3.
2.
2
4
1
3
3
2
3
4
1997 1998
2.6 2.5
2.2
4.3
3.0
2.3
2.4
2.2
3.3
2.4
2.1
4.3
3.1
2.4
2.3
2.2
3.4
2.2
1999
2.5
2,
4,
3,
2,
2,
2,
3,
2,
,1
,3
,0
,4
,3
,1
,1
,5
2000
2.5
2.1
4.3
3.1
2.2
2.3
2.2
3.2
2.2
2001-2008
All races/ethnicities
White non-Hispanic
Black or African-American
non-Hispanic
Asian or Pacific Islander non-
Hispanic
American Indian or Alaska
Native non-Hispanic
Hispanic
Mexican
Puerto Rican
Unknown ethnicity
2001
2.5
2.2
4.2
3.1
2.4
2.3
2.2
3.2
2.2
2002
2.6
2.2
4.3
3.2
2.4
2.3
2.2
3.2
2.3
2003
2.6
2,
4,
3,
2,
2,
2,
3,
2,
,2
,4
,2
,5
,4
,2
,4
,5
2004
2.7
2.
4.
3.
2.
2.
2.
3.
2.
3
5
2
6
4
3
2
6
2005
2.7
2.3
4.5
3.2
2.5
2.4
2.3
3.3
2.3
2006
2.7
2.3
4.5
3.3
2.5
2.5
2.4
3.4
2.8
2007
2.7
2,
4,
3,
2,
2,
2,
3,
2,
,3
,5
,2
,4
,4
,2
,4
,9
2008
2.8
2.4
4.6
3.3
2.4
2.4
2.3
3.3
3.1
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Vital Statistics System
Table H13a. Percentage of babies born at term with low birth weight, by mother's age, 1993-2008
1993-2000 •
1993
< 20 years 3.4
20-39 years 2.5
40+ years 2.9
1994
3.5
2.5
3.1
1995
3.5
2.4
3.1
1996
3.6
2.5
3.1
1997
3.6
2.4
3.1
1998
3.5
2.4
3.0
1999
3.5
2.4
3.1
2000
3.5
2.4
3.2
2001-2008 •
2001
< 20 years 3.5
20-39 years 2.4
40+ years 3.2
2002
3.5
2.4
3.2
2003
3.6
2.5
3.2
2004
3.7
2.5
3.4
2005
3.7
2.5
3.4
2006
3.7
2.6
3.4
2007
3.6
2.6
3.3
2008
3.7
2.6
3.4
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Vital Statistics System
America's Children and the Environment | Third Edition
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Appendices | Appendix A: Data Tables
Table H13b. Percentage of babies born at term with low birth weight, by all births, singletons, and
multiples, 1993-2008
1993-2000
All births
Singletons
Multiples
1993
2.6
2.3
13.4
1994
2.6
2.3
13.0
1995
2.6
2.3
13.1
1996
2.6
2.3
13.0
1997
2.6
2.3
12.3
1998
2.5
2.2
12.1
1999
2.5
2.2
11.9
2000
2.5
2.2
12.0
2001-2008
All births
Singletons
Multiples
2001
2.5
2.2
12.2
2002
2.6
2.3
12.1
2003
2.6
2.3
12.0
2004
2.7
2.3
12.0
2005
2.7
2.3
12.0
2006
2.7
2.4
12.3
2007
2.7
2.4
12.3
2008
2.8
2.4
12.6
DATA: Centers for Disease Control and Prevention, National Center for Health Statistics, National Vital Statistics System
America's Children and the Environment | Third Edition
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Appendix A: Data Tables | Appendices
Supplementary Topics
Birth Defects
Table SI: Birth defects in Texas, 1999-2007
Musculoskeletal
Cardiac and Circulatory
Genitourinary
Eye and Ear
Gastrointestinal
Central Nervous System
Respiratory
Chromosomal
Oral Cleft
1999-2001
131.1
118.4
91.7
45.2
51.5
30.5
23.5
23.0
17.0
2002-2004
148.1
137.4
105.1
57.5
51.0
33.6
24.1
22.8
16.2
2005-2007
164.8
157.9
118.4
62.1
57.8
40.7
25.3
23.9
16.9
DATA: Texas Birth Defects Registry
Table Sla: Birth defects in Texas, 2005-2007, by race/ethnicity
Cases per 10.000 live births
Musculoskeletal
Cardiac and Circulatory
Genitourinary
Eye and Ear
Gastrointestinal
Central Nervous System
Respiratory
Chromosomal
Oral Cleft
White non-Hispanic
(n=414,420)
171.6
154.6
132.2
60.1
60.2
41.8
23.1
23.5
18.1
Black non-Hispanic
(n=134,427)
163.2
151.1
115.1
48.0
46.1
43.7
23.4
19.9
11.1
Hispanic
(n=594,073)
162.1
164.5
109.6
67.3
60.2
39.5
27.6
25.3
17.5
Other non-Hispanic
(77=45,327;
142.6
125.8
120.2
52.4
39.5
35.8
20.5
18.2
15.7
DATA: Texas Birth Defects Registry
Contaminants in Schools and Child Care Facilities
Table S2: Percentage of environmental and personal media samples with detectable pesticides in child
care facilities, 2001
Indoor Air
(Regional Data)
Hand Wipes
(Regional Data)
Dust
(Regional Data)
Floor Wipes
(National Data)
Pentachlorophenol
83.2
20.0
95.2
NA
Chlorpyrifos
100.0
65.0
100.0
89.0
c/s-Permethrin
40.3
86.5
100.0
72.0
Diazinon
100.0
48.3
100.0
67.0
America's Children and the Environment | Third Edition
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Appendices | Appendix A: Data Tables
DATA: Children's Total Exposure to Pesticides and Other Persistent Organic Pollutants Study (Regional Data); First National
Environmental Health Survey of Child Care Centers (National Data)
NOTE: Data are from both national and regional sources, and are identified accordingly. Regional data are from samples
collected in North Carolina and Ohio only.
Table S3: Percentage of environmental and personal media samples with detectable industrial
chemicals in child care facilities, 2001
^•H
Indoor Air
Hand Wipes
Dust
Dibutyl Phthalate
100.0
75.0
100.0
PCB-52
97.6
8.3
65.1
Polycyclic Aromatic
Hydrocarbons
45.3
65.0
45.3
Bisphenol A
59.7
95.2
62.3
DATA: Children's Total Exposure to Pesticides and Other Persistent Organic Pollutants Study
NOTE: Regional data, from samples collected in North Carolina and Ohio only.
Table S4: Pesticides used inside California schools by commercial applicators, 2002-2007
unds of Pesticide Applied
Pyrethrin and Pyrethroid Insecticides
Organophosphate Insecticides
Other Insecticides
2002
9,452
919
2003
2,515
244
2004
2,430
39
2005
2,274
119
2006
2,556
36
2007
1,794
70
2,125
2,037
4,883
Herbicides
Fumigants
Rodenticides
Miscellaneous Pesticides
295
4,031
613
651
556
3,890
2,205
1,099
392
641
1,174
149
142
701
249
589
219
0.4
0.7
120
434
52
121
88
76
124
DATA: California Department of Pesticide Regulation, Schools Pesticide Use Reporting Database
America's Children and the Environment | Third Edition
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Appendix A: Data Tables | Appendices
References
1. U.S. Environmental Protection Agency. 2010. Fact Sheet on the Federal Register Notice for Stage 1 Disinfectants and Disinfection
Byproducts Rule. U.S. EPA, Office of Water. Retrieved January 10, 2011 from
http://water.epa.gov/lawsregs/rulesregs/sdwa/stagel/factsheet.cfm.
2. U.S. Environmental Protection Agency. 2010. Fact Sheet on the Interim Enhanced Surface Water Treatment Rule. U.S. EPA, Office of
Water. Retrieved January 10, 2011 from http://water.epa.gov/lawsregs/rulesregs/sdwa/ieswtr/factsheet.cfm.
3. U.S. Environmental Protection Agency. 2001. Radionuclides Rule: A Quick Reference Guide. Washington, DC: U.S. EPA, Office of Water.
EPA 816-F-01-003. http://www.epa.gov/ogwdw/radionuclides/pdfs/qrg_radionuclides.pdf.
4. U.S. Environmental Protection Agency. 2009. Technical Fact Sheet: Final Rule for Arsenic in Drinking Water. U.S. EPA, Office of Water.
Retrieved January 10, 2011 from http://water.epa.gov/lawsregs/rulesregs/sdwa/arsenic/regulations_techfactsheet.cfm.
5. Anderson, W.A., L. Castle, M.J. Scotter, R.C. Massey, and C. Springall. 2001. A biomarker approach to measuring human dietary exposure
to certain phthalate diesters. Food Additives and Contaminants 18 (12):1068-74.
6. Mendez, W., E. Dederick, and J. Cohen. 2010. Drinking water contribution to aggregate perchlorate intake of reproductive-age women
in the United States estimated by dietary intake simulation and analysis of urinary excretion data. Journal of Exposure Science and
Environmental Epidemiology 20 (3):288-97.
7. Preau, J.L., Jr., L.Y. Wong, M.J. Silva, L.L. Needham, and A.M. Calafat. 2010. Variability over 1 week in the urinary concentrations of
metabolites of diethyl phthalate and di(2-ethylhexyl) phthalate among eight adults: an observational study. Environmental Health
Perspectives 118 (12):1748-54.
8. Volkel, W., T. Colnot, G.A. Csanady, J.G. Filser, and W. Dekant. 2002. Metabolism and kinetics of bisphenol a in humans at low doses
following oral administration. Chemical Research in Toxicology 15 (10):1281-7.
9. Crump, K.S., and J.P. Gibbs. 2005. Benchmark calculations for perchlorate from three human cohorts. Environmental Health Perspectives
113 (8):1001-8.
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Appendix B: Metadata
Air Quality System (AQS)
American Healthy Homes
Survey (AHHS)
California School Pesticide Use
Reporting Database
Census: American Community
Survey Data
Census: Decennial Data
Census: Intercensal and
Postcensal Data
EPA Superfund Program and the
RCRA Corrective Action Program
Site Information
National Air Toxics Assessment
(NATA)
National Health and Nutrition
Examination Survey (NHANES)
National Health Interview
Survey (NHIS)
National Hospital Ambulatory
Medical Care Survey (NHAMCS)
National Hospital Discharge
Survey (NHDS)
National Survey of Lead and
Allergens in Housing (NSLAH)
National Vital Statistics
System (NVSS)
Pesticide Data Program (POP)
Safe Drinking Water Information
System Federal Version (SDWIS/FED)
Surveillance, Epidemiology, and
End Results (SEER) Program
Texas Birth Defects Registry
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Appendices | Appendix B: Metadata
Appendix B: Metadata
Air Quality System (AQS)
(Used for Indicators El, E2, and E3)
The U.S. Environmental Protection Agency compiles air quality monitoring
data in the Air Quality System (AQS). Ambient air concentrations are
measured at a national network of more than 4,000 monitoring stations and
are reported by state, local, and tribal agencies to EPA AQS.
U.S. Environmental Protection Agency, Office of Air Quality Planning and
Standards.
Concentrations are measured at a national network of more than 4,000
monitoring stations and are reported by state, local, and tribal agencies to
EPA AQS.
Brief description of the data set
Who provides the data set?
How are the data gathered?
What documentation is
available describing data
collection procedures?
What types of data relevant for
children's environmental health
indicators are available from
this database?
The Ambient Monitoring Technology Information Center (AMTIC) at
http:/www.epa.gov/ttn/amtic/ contains information and files on ambient air
quality monitoring programs, details on monitoring methods, relevant
documents and articles, information on air quality trends and federal
regulations related to ambient air quality monitoring. The Air Trends site at
http:/www.epa.gov/airtrends contains information on air quality trends. The
Green Book site at http:/www.epa.gov/air/oaqps/greenbk contains
information on nonattainment areas.
Relevant data include measured ambient air pollutant concentrations (lead,
carbon monoxide, ozone, PM10, PM2.s, sulfur dioxide, and nitrogen dioxide),
Air Quality Index, and monitor information (location, monitoring objective).
What is the spatial
representation of the database
(national or other)?
National. However, not all counties are represented since not all counties
have air pollution monitors.
Are raw data (individual
measurements or survey
responses) available?
Individual hourly or daily measurements by monitor and pollutant are
available.
How are database files
obtained?
Are there any known data
quality or data analysis
concerns?
Raw data:
http:/www.epa.gov/ttn/airs/aqsdatamart/basic_info.htm.
http:/www.epa.gov/ttn/airs/airsaqs/detaildata/downloadaqsdata.htm.
Annual summary data (includes annual means and maxima):
http://www.epa.gov/ttn/airs/aqsdatamart/.
For some indicators additional annual summary data were compiled by EPA
staff. This includes annual maximum rolling three-month average lead
concentrations, county maximum PM2.5 annual means using OAQPS data
completeness and weighted average calculations, PM2.5 exceedance count
data, and air quality index data.
Individual measurements of questionable validity or attributed to exceptional
events (e.g., forest fires) are flagged. Monitoring data are not collected in
some counties for some pollutants.
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Appendix B: Metadata | Appendices
Air Quality System (AQS)
(Used for Indicators El, E2, and E3)
What documentation is
available describing quality
assurance procedures?
http:/www.epa.gov/ttn/amtic/quality.html.
http:/www.epa.gov/airprogm/oar/oaqps/qa/index.html.
For what years are data
available?
What is the frequency of data
collection?
1970-present. AQS contains some monitoring data from the late 1950s and
early 1960s, but there is not an appreciable amount of data for lead until 1970,
sulfur dioxide until 1971, nitrogen dioxide until 1974, carbon monoxide and
ozone until 1975, and PM10 until 1987. AQS also contains monitoring data for
PM2.5 beginning with 1999; PM2.5 was measured only infrequently prior to 1999.
Hourly or daily. Less frequent monitoring occurs at some monitors (e.g., every
three or six days for PM or only in the ozone season for ozone).
What is the frequency of data
release?
AIRNow releases ozone and PM2.5 data hourly. Raw data are updated by
states approximately monthly. Annual summary data are updated quarterly.
Are the data comparable across
time and space?
Can the data be stratified by
race/ethnicity, income, and
location (region, state, county
or other geographic unit)?
Counties without air quality monitors cannot be compared with counties with
air quality monitors, and some counties are monitored more extensively than
others. Although monitor locations and monitoring frequencies change, the
network is reasonably stable. An exception occurred for PM2.5 in 1999 as the
new monitoring network was built up.
The data can be stratified by region, state, county, and metropolitan area.
American Healthy Homes Survey (AHHS)
(Used for Indicator E6)
Brief description of the
data set
A nationally representative sample of homes was selected for this survey. AHHS
measured levels of lead, lead hazards, and allergens in homes nationwide. AHHS
also surveyed additional potential health hazards such as arsenic, pesticides, and
molds. The lead and arsenic data included the levels of lead in paint, dust and soil,
and arsenic in dust and soil, and levels of paint deterioration.
Who provides the data set? U.S. Department of Housing and Urban Development (HUD).
How are the data
gathered?
What documentation is
available describing data
collection procedures?
Data were collected from participants in private and public residences. A 3-stage
cluster sample was used to select a nationally representative sample of 1,131
homes. Samples were collected via surface wipes from four common living areas,
homeowner vacuum bags, and soil samples from outside the home. Lead testing
in paint was conducted using a portable X-Ray Fluorescence (XRF) instrument.
Demographic and other information was collected using a questionnaire. All
samples and survey information were collected during a single day.
http://www.hud.gov/offices/lead/NHHC/presentations/R-
15_Findings_from_AHH_survey.pdf. Slide four and five of the presentation.
American Healthy Homes Survey, Draft Final Report. June, 2009.
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Appendices | Appendix B: Metadata
American Healthy Homes Survey (AHHS)
(Used for Indicator E6)
What types of data
relevant for children's
environmental health
indicators are available
from this database?
What is the spatial
representation of the
database (national or
other)?
Relevant environmental contaminant data include measurements of lead paint,
lead dust, lead in soils, mold, allergens/endotoxins in dust, arsenic in soil, indoor
moisture measurements, and indoor pesticide residues.
Other relevant information found in this database includes housing type and age,
demographic information on residents (age, race, income group, ethnicity),
electrical safety, structural stability, moisture, pest control, ventilation, injury
prevention, fire safety, deterioration of carpet, and plumbing facilities.
National.
Are raw data (individual
measurements or survey
responses) available?
Not currently.
How are database files
obtained?
Are there any known data
quality or data analysis
concerns?
HUD provided data files directly to EPA for purposes of developing an indicator
for America's Children and the Environment.
Summary tables are available in "American Healthy Homes Survey, Final Report,
Lead and Arsenic Findings," June 2009.
http://portal.hud.gov/hudportal/documents/huddoc?id=AHHS_REPORT.pdf.
None reported.
What documentation is
available describing quality
assurance procedures?
"American Healthy Homes Survey, Final Report, Lead and Arsenic Findings,"
June 2009.
http://portal.hud.gov/hudportal/documents/huddoc?id=AHHS_REPORT.pdf
For what years are data
available?
2005/2006.
What is the frequency of
data collection?
Data were collected once, from June 2005 to March 2006.
What is the frequency of
data release?
The final report was released in April 2011 and can be found at
http://portal.hud.gov/hudportal/documents/huddoc?id=AHHS_REPORT.pdf.
Are the data comparable
across time and space?
Can the data be stratified
by race/ethnicity, income,
and location (region, state,
county or other geographic
unit)?
As a one-time survey, time comparisons within the AHHS are not possible, but
AHHS results can be compared with the earlier NSLAH survey (1999-2000).
Geographic comparisons should be possible using the raw data, since the same
data were collected at all homes. The Final Report gives some comparisons
between the four Census regions.
The data can be stratified by residents' age, race, and ethnicity, Data can also be
stratified by household income, census region, year of home construction, and by
the housing type (rented or owned). However, estimates of lead hazards in the
home for children ages 0 to 5 years broken out by race/ethnicity and income are
not statistically reliable, due to the relatively small number of homes in each group.
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Appendix B: Metadata | Appendices
California School Pesticide Use Reporting Database
(Used for Measure S4)
Brief description of the
data set
A California state-wide database containing the records of pesticide use in
California schools and child day care facilities. The records include only pesticides
applied by licensed commercial pest management services. Each record contains
the name of the school, name of the pesticide product, registration number of
the pesticide product, sites of application inside or outside the school, amount of
product applied, unit of the measure, and the application date and time. A
supplementary dataset giving the percentages of active ingredients in each
pesticide product was also obtained from the California Department of Pesticide
Regulation (DPR).
Who provides the data set? California Department of Pesticide Regulation.
How are the data
gathered?
What documentation is
available describing data
collection procedures?
What types of data
relevant for children's
environmental health
indicators are available
from this database?
As per California pesticide regulations, all businesses engaged in pest control are
required to report pesticide use at school sites using a prescribed form to the
DPR. More information is available at:
http://www.cdpr.ca.gov/docs/legbills/6624fin.pdf.
The form that pest control companies use to report the pesticide use at school
sites is available at:
http://www.cdpr.ca.gov/docs/enforce/prenffrm/prenfll7.pdf.
The data reported by pest control companies are aggregated by the DPR and
provided for the general public.
Relevant information includes the amount and type of pesticides used at school
sites in California by commercial applicators. This information is relevant to
determine exposure of school children to pesticides during their time spent inside
the school.
What is the spatial
representation of the
database (national or
other)?
State (California).
Are raw data (individual
measurements or survey
responses) available?
How are database files
obtained?
Yes. The database contains all instances of pesticide use at school sites that are
reported to the DPR. The raw data can be obtained directly from DPR.
The supplementary data files with data on the contents of each pesticide product
are available for download at:
http://www.cdpr.ca.gov/docs/label/prodtables.htm.
The database files are obtained from DPR through email correspondence.
Are there any known data
quality or data analysis
concerns?
The specific gravity for some pesticides is not reported. The amounts used in
different school locations are not reported or reported as zero. The database
excludes non-commercial pesticide applications such as by school staff.
What documentation is
available describing QA
procedures?
Not available.
For what years are data
available?
2002 - present.
What is the frequency of
data collection?
All instances of pesticide use at school and child day care sites by pest
management companies need to be reported. The DPR aggregates these data on
yearly basis.
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Appendices | Appendix B: Metadata
California School Pesticide Use Reporting Database
(Used for Measure S4)
What is the frequency of Yearly.
data release?
Are the data comparable
across time and space?
Pesticide use can be compared between years or between schools.
Can the data be stratified
by race/ethnicity, income,
and location (region, state,
county or other geographic
unit)?
Data can be stratified only by county or at the individual school or child day care
facility level. No demographic data are included in this database, although school
ID codes are available so that these data can be matched with California or
federal school population data.
Census: American Community Survey Data
(Used for Indicator E4)
Brief description of the
data set
Who provides the data set?
How are the data
gathered?
What documentation is
available describing data
collection procedures?
What types of data relevant
for children's
environmental health
indicators are available
from this database?
What is the spatial
representation of the
database (national or
other)?
Are raw data (individual
measurements or survey
responses) available?
How are database files
obtained?
The U.S. Census Bureau collects detailed population data for a sample of the
United States population and provides information for 1-, 3-, and 5-year
averages.
U.S. Census Bureau.
The American Community Survey collects detailed population information for a
sample of the United States population using a mail survey and/or personal
interviews.
http://www.census.gov/acs/www/data_documentation/summary_file/
http://www.census.gov/acs/www/data_documentation/documentation_main/
Relevant information includes populations by year or group of years, county,
census tract, census block group, race, ethnicity, age, and sex.
National.
Not publicly released.
http://www. census. gov/acs/www/data_documentation/data_via_ftp/ (all
available data tables)
Are there any known data
quality or data analysis
concerns?
http://factfinder2.census.gov/faces/nav/jsf/pages/index.xhtml (selected data
tables)
All data are based on a sample and not the entire census. 1-year estimates are
only available for areas with populations above 65,000, are less reliable but more
current than 3-year or 5-year estimates, and provide the least detailed
information. 3-year estimates are only available for areas with populations above
20,000. 5-year estimates are available for all areas, are more reliable but less
current than 1-year or 3-year estimates, and provide the most detailed
information.
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Appendix B: Metadata | Appendices
Census: American Community Survey Data
(Used for Indicator E4)
What documentation is
available describing quality
assurance procedures?
http://factfinder2.census.gov/faces/nav/jsf/pages/index.xhtml
For what years are data
available?
1-year ACS files are released annually, beginning with 2002 data.
3-year ACS files are released annually, beginning with 2005-2007 data.
5-year ACS files are released annually, beginning with 2005-2009 data.
What is the frequency of
data collection?
Every year.
What is the frequency of
data release?
Every year.
Are the data comparable
across time and space?
Populations for counties, census tracts, or census block groups may not be
comparable between years or periods due to boundary changes.
Can the data be stratified
by race/ethnicity, income,
and location (region, state,
county or other geographic
unit)?
The data can be stratified by race, ethnicity, region (state, county, census tract,
census block group, MSA, urban area), and income. Stratifications by age,
race/ethnicity, and income combined are only available for census tracts in the 5-
year data and for higher geographies in the 1- and 3-year data.
Census: Decennial Data
(Used for Indicators El, E2, E3, E10, Ell)
Brief description of the
data set
The U.S. Census Bureau collects detailed population data for the entire United
States every 10 years.
Who provides the data set? U.S. Census Bureau.
How are the data
gathered?
What documentation is
available describing data
collection procedures?
The decennial census collects detailed population information for the entire
United States every 10 years using a mail survey and/or personal interviews. In
1990, 2000, and 2010 the entire population was asked a small set of questions
(including age, sex, race, and ethnicity). In 1990 and 2000 about one in six
households were also asked more detailed questions (including income).
http://factfinder2.census.gov/faces/nav/jsf/pages/index.xhtml
What types of data relevant
for children's
environmental health
indicators are available
from this database?
Relevant data include populations (by year, county, census tract, census block
group, census block,) race, ethnicity, age, sex, and income (not for 2010 and not
for census blocks).
What is the spatial
representation of the
database (national or
other)?
National.
Are raw data (individual
measurements or survey
responses) available?
Not publicly released.
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Appendices | Appendix B: Metadata
Census: Decennial Data
(Used for Indicators El, E2, E3, E10, Ell)
How are database files
obtained?
Are there any known data
quality or data analysis
concerns?
What documentation is
available describing quality
assurance procedures?
http://factfinder2.census.gov/faces/nav/isf/pages/index.xhtml (county and
national populations)
http://geolytics.com/USCensus,Census-2000-Products,Categories.asp (2000
census blocks)
Populations by county, race, and income level are not released for combinations
with populations below 100 or where the estimate is based on a sample of 50 or
less. Income data are based on a sample and not the entire census. Census block
locations are given by the census block centroid (geographical center) which does
not account for the shape and size of the census block.
http://factfinder2.census.gov/faces/nav/jsf/pages/index.xhtml
For what years are data
available?
1990, 2000, 2010.
What is the frequency of
data collection?
Every 10 years.
What is the frequency of
data release?
Every 10 years.
Are the data comparable
across time and space?
Can the data be stratified
by race/ethnicity, income,
and location (region, state,
county or other geographic
unit)?
Detailed race data for different decades are not comparable due to changing race
group definitions, such as the treatment of respondents with multiple races.
Comparisons between populations below reporting thresholds are not possible.
Populations for some smaller regions (census blocks, block groups, tracts, and
occasionally counties) are not comparable for different decades due to boundary
changes.
Data can be stratified by race, ethnicity, and location (region, state, county,
census tract, census block group, census block, MSA, urban area). Income data
are available from the American Community Survey (2005 and later) and from
samples from the 1990 and 2000 censuses.
Census: Intercensal and Postcensal Data
(Used for Indicators El, E2, E3, E7, E8, E12, H3)
Brief description of the data set
Who provides the data set?
The U.S. Census Bureau collects detailed population data for the entire
United States every 10 years. These data are combined with birth, death,
migration, and net international immigration data to estimate populations for
the years between (intercensal) or after (postcensal) censuses.
U.S. Census Bureau.
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Appendix B: Metadata | Appendices
Census: Intercensal and Postcensal Data
(Used for Indicators El, E2, E3, E7, E8, E12, H3)
How are the data gathered?
What documentation is
available describing data
collection procedures?
The decennial census collects detailed population information for the entire
United States every 10 years using a mail survey and/or personal interviews.
Intercensal data estimate populations between censuses by combining the
decennial census data from the two censuses with birth, death, migration, and
net international immigration data. Postcensal data estimate populations after
a census by combining the decennial census data from the previous census
with birth, death, migration, and net international immigration data. For the
2000s, bridged race estimates of populations in four single race categories
were calculated using a statistical regression model with person-level and
county-level covariates to estimate the proportion of people in a given
detailed multiple race category that would select each single race category.
http://www.cdc.gov/nchs/nvss/bridged race.htm (US census populations
with bridged race categories)
http://www.census.gov/popest/data/historical/index.html
What types of data relevant for
children's environmental health
indicators are available from
this database?
Relevant data include populations by year, county, race, ethnicity, age, and
sex.
What is the spatial
representation of the database
(national or other)?
National.
Are raw data (individual
measurements or survey
responses) available?
Not publicly released.
How are database files
obtained?
http://www.cdc.gov/nchs/nvss/bridged_race.htm (US census populations
with bridged race categories)
http://www.census.gov/popest/data/historical/index.html (population
estimates)
Are there any known data
quality or data analysis
concerns?
Due to the uncertainties in the statistical methods used to estimate
intercensal and postcensal populations, the population counts at the more
detailed geographical or demographic stratification levels are less precise.
What documentation is
available describing quality
assurance procedures?
http://www.census.gov/popest/methodology/2009-stco-char-meth.pdf
(methods for bridged race categories including consistency with other
population estimates).
For what years are data
available?
1977-present.
What is the frequency of data
collection?
Varies.
What is the frequency of data
release?
Monthly, quarterly, or annually.
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Appendices | Appendix B: Metadata
Census: Intercensal and Postcensal Data
(Used for Indicators El, E2, E3, E7, E8, E12, H3)
Are the data comparable across
time and space?
Can the data be stratified by
race/ethnicity, income, and
location (region, state, county
or other geographic unit)?
Postcensal data for each calendar year between the census and the current
year are updated annually using information on the components of
population change. Since the components of population change data are
revised (e.g., a preliminary natality file is replaced with a final natality file),
and since estimation methodologies are improved, population estimates
from different annual updates are not comparable. For example, the year
2007 population estimates from the 2008 and 2009 series are not the same
because the population change estimates for the years 2001 to 2007 used in
the 2008 series were updated for the 2009 series, and the estimation
methodologies were also revised (e.g., for international migration and for the
effects of hurricanes Katrina and Rita). Race data for different decades may
not be comparable due to changing race group definitions.
Data can be stratified by race, ethnicity, and location (region, state, county).
Income data are available from the American Community Survey (2005 and
later) and from the 1990 and 2000 censuses.
EPA Superfund Program and the RCRA Corrective Action Program Site
Information
(Used for Indicators E10 and Ell)
Brief description of the
data set
Who provides the data
set?
A list of all Superfund sites and RCRA Corrective Action sites that may not have all
human health protective measures in place. The list includes the site name, state in
which the site is located, whether the site is a federal facility, latitude, longitude,
and the acreage.
The U.S. Environmental Protection Agency, Office of Solid Waste and Emergency
Response, Superfund Program and the RCRA Corrective Action Program provide
data from two independent databases.
Superfund site information is reported in the Comprehensive Environmental
Response, Compensation, and Liability Information System (CERCLIS) Database.
CERCLIS includes lists of involved parties and site status (e.g., Human Exposure Under
Control, Ground Water Migration Under Control, and Site Wide Ready for Anticipated
Use) and the measures Construction Completion and Final Assessment Decisions.
Information on RCRA Corrective Action sites is maintained in the Resource
Conservation and Recovery Act Information (RCRAInfo) Database. RCRAInfo includes
site status (e.g., Human Exposure Under Control) among other types of data. For both
programs, status designation of Human Exposure Under Control was used as the
milestone to determine that a site has all human health protective measures in place.
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Appendix B: Metadata | Appendices
EPA Superfund Program and the RCRA Corrective Action Program Site
Information
(Used for Indicators E10 and Ell)
How are the data
gathered?
What documentation is
available describing data
collection procedures?
Acreage and latitude/longitude information in RCRAInfo is collected from a variety
of sources, such as RCRA permit applications, owners or operators, or public
documents. Acreage and latitude/longitude information in CERCLIS is obtained
from Preliminary Assessment reports, Site Inspection reports, Records of Decision,
Five Year Reviews, or other official site documents.
Acreage in RCRAInfo refers to the entire site. In CERCLIS, there are a number of
types of acreage data. The CERCLIS field labeled "property boundary acreage" was
used for calculation of Indicators E10 and Ell. Although not meant to serve as
estimates of the contaminated acres for Superfund sites, this information is similar
to the acreage in RCRAInfo for Corrective Action facilities.
For Corrective Action facilities, updates and progress are recorded by Regional or
authorized State program staff as milestones are achieved. As Superfund site
information changes, the CERCLIS database is updated by EPA regional offices.
EPA undertook a one-time effort to collect site acreage starting in 2007. These data
are updated whenever more accurate information is obtained.
Not applicable.
What types of data
relevant for children's
environmental health
indicators are available
from this database?
Relevant data include latitude, longitude, and estimated acres for contaminated
sites.
What is the spatial
representation of the
database (national or
other)?
National; each relevant site in the United States is individually identified.
Are raw data (individual
measurements or survey
responses) available?
Latitude/longitude and acreage are available for each site.
How are database files
obtained?
Requests for datasets from CERCLIS or RCRAInfo must be made to EPA offices.
Summary information on individual Corrective Action or Superfund sites can be
found at:
http://www.epa.gov/osw/hazard/correctiveaction/facility/index.htm
and
http://cfpub.epa.gov/supercpad/cursites/srchsites.cfm
respectively.
Some of the information in CERCLIS and RCRAInfo (name, address, cleanup
progress) is also available on the EPA webpages "Envirofacts" and "Cleanups in My
Community," http://www.epa.gov/enviro/ and http://iaspub.epa.gov/Cleanups/.
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Appendices | Appendix B: Metadata
EPA Superfund Program and the RCRA Corrective Action Program Site
Information
(Used for Indicators E10 and Ell)
Are there any known data The site latitude and longitude specify a point at the site, which could represent the
quality or data analysis location of the site entry point or of some other area within the site.
concerns. Actual geographic boundaries of each site (or contaminated areas on each site) are
not available in digital form. In absence of geographic boundaries, CERCLIS
boundary acres and RCRAInfo site acreage were used to estimate entire site area,
fenceline to fenceline. No effort was made to approximate site shape. It is not
specified if all site acres are areas of suspected contamination or areas of known
contamination. Thus, the area used to represent each site is larger than the area of
actual, known contamination.
The "all human health protective measures in place" designation indicates that
there is no complete pathway for human exposures to unacceptable levels of
contamination, based on current site conditions. Sites lacking this designation are
of three types: sites where a possible exposure route has been identified, sites that
have not been fully assessed, or sites that have not been reviewed for the
designation. Thus, sites that may not have all human health protective measures in
place include both sites where there is a possible route of human exposure and
sites where there may be no existing exposure routes.
What documentation is
available describing
quality assurance
procedures?
Not applicable.
For what years are data
available?
What is the frequency of
data collection?
Data represent site status, including designation of all human health protective
measures in place, as of October 2009. Designations are not available for earlier
years.
Data collection frequency varies. Information is updated as site information
changes.
What is the frequency of
data release?
Data are released on a yearly basis.
Are the data comparable
across time and space?
Can the data be stratified
by race/ethnicity,
income, and location
(region, state, county or
other geographic unit)?
Acres used to describe site area are collected differently for sites in each program
(see above). Procedures applied within each program will be consistent over time.
Contamination level and exposure potential will vary across sites.
This site list does not contain information on race/ethnicity or income. The data can
be stratified by location, specifically by state. Additionally, the latitude and
longitude are provided for each site, which allows for more exact location
stratifications and for linkage to Census data on local population demographics.
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Appendix B: Metadata | Appendices
National Air Toxics Assessment (NATA)
(Used for Indicator E4)
Brief description of the
data set
Who provides the data
set?
The National Air Toxics Assessment is EPA's ongoing comprehensive evaluation of
air toxics in the United States. NATA provides estimates of the risk of cancer and
other serious health effects from inhaling air toxics in order to inform both national
and more localized efforts to identify and prioritize air toxics, emission source
types, and locations that are of greatest potential concern in terms of contributing
to population risk.
U.S. Environmental Protection Agency, Office of Air Quality Planning and
Standards.
How are the data
gathered?
What documentation is
available describing data
collection procedures?
Emissions inventory data for individual HAPs are collected from data reported by
large individual facilities (point sources) and estimated for area and mobile sources
using various emissions inventory models. The compiled inventory is called the
National Emissions Inventory. Ambient concentrations are estimated using an air
dispersion model. Population exposures are estimated based on a screening-level
inhalation exposure model.
See http:/www.epa.gov/nata2005 for detailed description of NATA organization
and data collection practices.
What types of data
relevant for children's
environmental health
indicators are available
from this database?
Relevant data include modeled ambient concentrations, exposure concentrations,
cancer risks, and non-cancer hazard indices for each HAP in each county and each
census tract.
What is the spatial
representation of the
database (national or
other)?
National.
Are raw data (individual
measurements or survey
responses) available?
Modeled ambient and exposure concentrations for each HAP in each county and
census tract are available.
How are database files
obtained?
http://www.epa.gov/ttn/atw/nata2005/tables.html.
Are there any known data
quality or data analysis
concerns?
NATA results provide answers to questions about emissions, ambient air
concentrations, exposures and risks across broad geographic areas (such as
counties, states, and the nation) at a moment in time. These assessments are
based on assumptions and methods that limit the range of questions that can be
answered reliably. The results cannot be used to identify exposures and risks for
specific individuals, or even to identify exposures and risks in small geographic
regions. These estimates reflect chronic exposures resulting from the inhalation of
the air toxics emitted and do not consider exposures that may occur indoors or as a
results of exposures other than inhalation (i.e., dermal or ingestion). Methods used
in NATA were peer reviewed by EPA's Science Advisory Board; the SAB report is
available at http://www.epa.gov/ttn/atw/sab/sabreptl201.pdf.
What documentation is
available describing
quality assurance
procedures?
See http:/www.epa.gov/nata2005 and.
http://www.epa.gov/ttn/atw/nata2005/05pdf/nata_tmd.pdf
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Appendices | Appendix B: Metadata
National Air Toxics Assessment (NATA)
(Used for Indicator E4)
For what years are data
available?
1996, 1999, 2002, 2005.
What is the frequency of
data collection?
Approximately every three years.
What is the frequency of
data release?
Approximately every three years.
Are the data comparable
across time and space?
Can the data be stratified
by race/ethnicity, income,
and location (region,
state, county or other
geographic unit)?
Data for different NATA assessments are not comparable across time due to
improvements in the estimated national emissions inventory, increases in the
numbers of modeled HAPs, and improvements in the health data information. Data
may not be comparable over space due to quality differences in emissions
inventory reporting.
Data can be stratified by state, county, and census tract; when combined with
census data, NATA estimates can be stratified by race/ethnicity and income.
National Health and Nutrition Examination Survey (NHANES)
(Used in Indicators Bl, B2, B3, B4, B5, B6, B7, B8, B9, BIO, Bll, B12, B13, H10, and Hll)
Brief description of the
data set
Who provides the data
set?
The National Health and Nutrition Examination Survey (NHANES) is a program of
studies designed to assess the health and nutritional status of the civilian
noninstitutionalized population of the United States, using a combination of
interviews, physical examinations, and laboratory analysis of biological specimens.
Centers for Disease Control and Prevention, National Center for Health Statistics.
How are the data
gathered?
What documentation is
available describing data
collection procedures?
Laboratory data are obtained by analysis of blood and urine samples collected from
survey participants at NHANES Mobile Examination Centers. Health status is
assessed by physical examination. Demographic and other survey data regarding
health status, nutrition, and health-related behaviors are collected by personal
interview, either by self-reporting or, for children under 16 and some others, as
reported by an informant.
See http://www.cdc.gov/nchs/nhanes.htm for detailed survey and laboratory
documentation by survey period.
What types of data
relevant for children's
environmental health
indicators are available
from this database?
Relevant data include concentrations of environmental chemicals (in urine, blood,
and serum), body measurements, health status (as assessed by physical
examination, laboratory measurements, and interview responses), and
demographic information.
What is the spatial
representation of the
database (national or
other)?
NHANES sampling procedures provide nationally representative data. Analysis of
data for any other geographic area (region, state, etc.) is possible only by special
arrangement with the NCHS Research Data Center, and such analyses may not be
representative of the specified area.
Are raw data (individual
measurements or survey
responses) available?
Individual laboratory measurements and survey responses are generally available.
Individual survey responses for some questions and some measurements are not
publicly released.
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Appendix B: Metadata | Appendices
National Health and Nutrition Examination Survey (NHANES)
(Used in Indicators Bl, B2, B3, B4, B5, B6, B7, B8, B9, BIO, Bll, B12, B13, H10, and Hll)
How are database files
obtained?
http://www.cdc.gov/nchs/nhanes.htm.
Are there any known data
quality or data analysis
concerns?
What documentation is
available describing
quality assurance
procedures?
For what years are data
available?
What is the frequency of
data collection?
What is the frequency of
data release?
Some environmental chemicals have large percentages of values below the
detection limit. Data gathered by interview, including demographic information,
and responses regarding health status, nutrition, and health-related behaviors are
self-reported, or (for individuals age 16 years and younger) reported by an adult
informant. In some cases, the size of a particular sample is too small in an
individual 2-year survey cycle to produce statistically reliable estimates; this can be
addressed by combining two or more consecutive 2-year survey cycles.
http://www.cdc.gov/nchs/nhanes.htm
includes detailed documentation on laboratory and other quality assurance
procedures. Data quality information is available at
http://www.cdc.gov/nchs/about/policy/quality.htm.
Some data elements were collected in predecessors to NHANES beginning in 1959;
collection of data on environmental chemicals began with measurement of blood
lead in NHANES II, 1976-1980. The range of years for measurement of
environmental chemicals varies; apart from lead and cotinine (initiated in NHANES
III), measurement of environmental chemicals began with 1999-2000 or later
NHANES.
Data are collected on continuous basis, but are grouped into NHANES cycles:
NHANES II (1976-1980); NHANES III phase 1 (1988-1991); NHANES III phase 2
(1991-1994); and continuous two-year cycles beginning with 1999-2000 and
continuing to the present.
Data are released in two-year cycles (e.g. 1999-2000); particular data sets from a
two-year NHANES cycle are released as available.
Are the data comparable
across time and space?
Can the data be stratified
by race/ethnicity, income,
and location (region,
state, county or other
geographic unit)?
Detection limits can vary across time, affecting some comparisons. Some
contaminants are not measured in every NHANES cycle. Within any NHANES two-
year cycle, data are generally collected and analyzed in the same manner for all
sampling locations.
Data are collected to be representative of the U.S. population based on age, sex,
and race/ethnicity. The public release files allow stratification by these and other
demographic variables, including family income range and poverty income ratio.
Data cannot be stratified geographically except by special arrangement with the
NCHS Research Data Center.
National Health Interview Survey (NHIS)
(Used for Indicators E5, HI, H2, H6, H7, H8, and H9)
Brief description of the
data set
Who provides the data
set?
The National Health Interview Survey (NHIS) collects data on a broad range of
health topics through personal household interviews. The results of NHIS provide
data to track health status, health care access, and progress toward achieving
national health objectives.
Centers for Disease Control and Prevention, National Center for Health Statistics.
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Appendices | Appendix B: Metadata
National Health Interview Survey (NHIS)
(Used for Indicators E5, HI, H2, H6, H7, H8, and H9)
How are the data
gathered?
What documentation is
available describing data
collection procedures?
Data are obtained using a health questionnaire through a personal household
interview. Interviewers obtain information on health history and demographic
characteristics, including age, household income, and race and ethnicity from
respondents, or from a knowledgeable household adult for children age 17 years
and younger.
See http://www.cdc.gov/nchs/nhis.htm for detailed survey documentation by
survey year.
What types of data
relevant for children's
environmental health
indicators are available
from this database?
Relevant data include health history (e.g., asthma, mental health, childhood
illnesses), smoking in residences (for selected years), demographic information, and
health care use and access information.
What is the spatial
representation of the
database (national or
other)?
NHIS sampling procedures provide nationally representative data, and may also be
analyzed by four broad geographic regions: North, Midwest, South and West.
Analysis of data for any other smaller geographic areas (state, etc.) is possible only
by special arrangement with the NCHS Research Data Center.
Are raw data (individual
measurements or survey
responses) available?
How are database files
obtained?
Data for each year of the NHIS are available for download and analysis
(http://www.cdc.gov/nchs/nhis/nhis_questionnaires.htm). Annual reports from the
NHIS are also available (http://www.cdc.gov/nchs/nhis/nhis_products.htm) as are
interactive data tables (http://www.cdc.gov/nchs/hdi.htm). The files available for
download generally contain individual responses to the survey questions; however,
for some questions the responses are categorized Some survey responses are not
publicly released.
Raw data: http://www.cdc.gov/nchs/nhis.htm.
Are there any known data
quality or data analysis
concerns?
What documentation is
available describing
quality assurance
procedures?
Data are self-reported, or (for individuals age 17 years and younger) reported by a
knowledgeable household adult, usually a parent. Responses to some demographic
questions (race/ethnicity, income) are statistically imputed for survey participants
lacking a reported response.
http://www.cdc.gov/nchs/data/series/sr_02/sr02_130.pdf provides a summary of
quality assurance procedures.
For what years are data
available?
What is the frequency of
data collection?
Data from the NHIS are available from 1957-present. Availability of data addressing
particular issues varies based on when questions were added to the NHIS. The
survey is redesigned on a regular basis; many questions of interest for children's
environmental health indicators were modified or first asked with the redesign that
was implemented in 1997. For environmental tobacco smoke (regular smoking in
the home), comparable data are available for 1994, 2005, and 2010.
Continuous throughout the year.
What is the frequency of Annually.
data release?
Are the data comparable
across time and space?
Survey design and administration are consistent across locations and from year to
year. Many questions were revised or added in 1997, so data for prior years may
not be comparable to data from 1997 to present.
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Appendix B: Metadata | Appendices
National Health Interview Survey (NHIS)
(Used for Indicators E5, HI, H2, H6, H7, H8, and H9)
Can the data be stratified
by race/ethnicity, income,
and location (region,
state, county or other
geographic unit)?
Data can be stratified by race, ethnicity, income, and region (four regions only).
National Hospital Ambulatory Medical Care Survey (NHAMCS)
(Used for Indicator H3)
Brief description of the
data set
Who provides the data
set?
The National Hospital Ambulatory Medical Care Survey (NHAMCS) is designed to
collect information on the services provided in hospital emergency and outpatient
departments and in ambulatory surgery centers.
Centers for Disease Control and Prevention, National Center for Health Statistics.
How are the data
gathered?
What documentation is
available describing data
collection procedures?
Sampled hospitals are noninstitutional general and short-stay hospitals located in all
states and Washington DC, but exclude federal, military, and Veteran's
Administration hospitals. Data from sampled visits are obtained on the
demographic characteristics, expected source(s) of payments, patients' complaints,
physician's diagnoses, diagnostic and screening services, procedures, types of
health care professionals seen, and causes of injury.
See http://www.cdc.gov/nchs/ahcd/ahcd_data_collection.htm#nhamcs_collection
for data collection documentation.
What types of data
relevant for children's
environmental health
indicators are available
from this database?
Relevant data include physicians' diagnoses for ambulatory visits to hospital
emergency rooms and outpatient departments as well as demographic information.
What is the spatial
representation of the
database (national or
other)?
Are raw data (individual
measurements or survey
responses) available?
How are database files
obtained?
NHAMCS sampling procedures provide nationally representative data, and may also
be analyzed by four broad geographic regions: North, Midwest, South and West. In
addition the database identifies whether or not the hospital is in an MSA. Analysis
of data for any other geographic area (state, patient or facility zip code) is possible
only by special arrangement with the NCHS Research Data Center.
Data for each year of the NHAMCS are available for download and analysis
(http://www.cdc.gov/nchs/ahcd/ahcd_questionnaires.htm). Annual reports from
the NHAMCS are also available
(http://www.cdc.gov/nchs/ahcd/ahcd_products.htm) as are interactive data tables
(http://www.cdc.gov/nchs/hdi.htm).
http://www.cdc.gov/nchs/ahcd/ahcd_questionnaires.htm.
Are there any known data
quality or data analysis
concerns?
Responses to some demographic and other questions (birth year, sex, race,
ethnicity, immediacy of being seen) are statistically imputed for survey participants
lacking a reported response.
What documentation is
available describing
quality assurance
procedures?
http://www.cdc.gov/nchs/ahcd/ahcd_questionnaires.htm summarizes the quality
assurance procedures.
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Appendices | Appendix B: Metadata
National Hospital Ambulatory Medical Care Survey (NHAMCS)
(Used for Indicator H3)
For what years are data
available?
1992-present.
What is the frequency of
data collection?
Continuously throughout the year.
What is the frequency of Annually.
data release?
Are the data comparable Changes to some survey questions or to the set of possible responses make their
across time and space? responses non-comparable for different time periods (e.g., reason for visit). Some
diagnosis codes are not comparable from year to year due to annual revisions to the
International Classification of Diseases (ICD-9).
Can the data be stratified
by race/ethnicity, income,
and location (region,
state, county or other
geographic unit)?
Data can be stratified by race, ethnicity, and region (four regions only). For 2006
and later, data can also be stratified by median income, % below poverty, % with
college degree or higher level of education, and urban/rural classification for
patient's zip code (the zip code itself is not included in the public release version).
National Hospital Discharge Survey (NHDS)
(Used for Indicator H3)
Brief description of the
data set
Who provides the data
set?
The National Hospital Discharge Survey (NHDS) is an annual probability survey that
collects information on the characteristics of inpatients discharged from non-
federal short-stay hospitals in the United States.
Centers for Disease Control and Prevention, National Center for Health Statistics.
How are the data
gathered?
What documentation is
available describing data
collection procedures?
Sampled hospitals are short-stay general or children's general hospitals located in
all states and Washington DC, with an average length of stay of fewer than 30 days
and six or more beds staffed for patients use. Federal, military, and Veteran's
Administration hospitals are excluded, as are hospital units of institutions. Data
from sampled hospital discharges are obtained on the demographic characteristics
and physician's diagnoses.
See http://www.cdc.gov/nchs/nhds/nhds_collection.htm for data collection
documentation.
What types of data
relevant for children's
environmental health
indicators are available
from this database?
Relevant data include physician's diagnoses for discharges from hospitals, as well
as demographic information.
What is the spatial
representation of the
database (national or
other)?
NHDS sampling procedures provide nationally representative data, and may also be
analyzed by four broad geographic regions: North, Midwest, South and West.
Analysis of data for any other geographic area (state, patient zip code) is possible
only by special arrangement with the NCHS Research Data Center.
Are raw data (individual
measurements or survey
responses) available?
Individual hospital discharge data are available. Some survey responses are not
publicly released.
How are database files
obtained?
http://www.cdc.gov/nchs/nhds/nhds_questionnaires.htm.
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Appendix B: Metadata | Appendices
National Hospital Discharge Survey (NHDS)
(Used for Indicator H3)
Are there any known data The survey is designed to represent in-patient discharges to short-stay general or
quality or data analysis children's general hospitals, excluding federal and military hospitals. Data are
concerns? obtained from a detailed complex survey sampling scheme including samplings of
hospitals and discharges within hospitals. Survey responses must be appropriately
weighted using the provided analysis weights to obtain national estimates. The
public release version includes coefficients for variance estimation equations for
approximate variance estimation. The available data are for discharges and not
admissions. Some age and sex values were imputed.
What documentation is
available describing
quality assurance
procedures?
http://www.cdc.gov/nchs/data/series/sr_01/sr01_039.pdf includes a description
of the quality assurance procedures.
For what years are data
available?
1965-present.
What is the frequency of
data collection?
Continuously throughout the year.
What is the frequency of Annually.
data release?
Are the data comparable
across time and space?
Some diagnosis codes are not comparable from year to year due to annual
revisions to the International Classification of Diseases (ICD-9).
Can the data be stratified
by race/ethnicity, income,
and location (region,
state, county or other
geographic unit)?
Data can be stratified by race and region (four regions only). NHDS does not
release information on Hispanic ethnicity or income of patients due to high non-
response rates for these items. Although race is reported, there are also high non-
response rates for race.
National Survey of Lead and Allergens in Housing (NSLAH)
(Used for Indicator E6)
Brief description of the
data set
Who provides the data
set?
A nationally representative sample of homes was selected for this survey. NSLAH
measured levels of lead, lead hazards, allergens, and endotoxins in homes
nationwide. The lead data included the levels of lead in paint, dust and soil, and
levels of paint deterioration.
National Institute of Environmental Health Sciences (NIEHS) and U.S. Department
of Housing and Urban Development (HUD).
How are the data
gathered?
A nationally representative sample of 1,984 housing units in which children could
reside was drawn from 75 primary sampling units (metropolitan statistical areas
or counties), and 831 eligible housing units were recruited and completed a
survey. Measurements of lead paint and dust were gathered from the surveyed
homes in specific rooms; soil lead was gathered from the surveyed homes
through core sampling.
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Appendices | Appendix B: Metadata
National Survey of Lead and Allergens in Housing (NSLAH)
(Used for Indicator E6)
What documentation is
available describing data
collection procedures?
What types of data
relevant for children's
environmental health
indicators are available
from this database?
What is the spatial
representation of the
database (national or
other)?
National Survey of Lead and Allergens in Housing. Final Report. Volume I. Analysis
of Lead Hazards. April 2001. At
http://www.nchh.Org/Portals/0/Contents/Article0312.pdf.
National Survey of Lead and Allergens in Housing. Draft Final Report. Volume II.
Design and Methodology. March 2001.
Relevant information includes lead-based paint hazards in housing (prevalence,
deteriorated, loadings), dust lead, soil lead (children's play areas, yard), indoor
allergens (dust mite, cockroach, cat, dog, mouse, Alternaria), endotoxins, race,
ethnicity, age, sex, income, asthma and allergies health history, housing
characteristics (building age; heating, cooling, and cooking equipment), pets, and
pests. Pesticide data were not collected.
National.
Are raw data (individual
measurements or survey
responses) available?
Not currently.
How are database files
obtained?
Are there any known data
quality or data analysis
concerns?
Data have not been publicly released. HUD provided data files directly to EPA for
purposes of developing an indicator for America's Children and the Environment.
Summary tables are obtained from:
National Survey of Lead and Allergens in Housing. Final Report. Volume I. Analysis
of Lead Hazards. April 2001. At
http://www.nchh.Org/Portals/0/Contents/Article0312.pdf.
NSLAH data summaries are also available in "American Healthy Homes Survey,
Final Report, Lead and Arsenic Findings," June 2009, Draft Final Report (not yet
publicly released).
http://www.nchh.Org/Portals/0/Contents/Article0312.pdf.
Chapter 7 of the study report outlines sources of error in data collection and analysis.
Concerns include: response rate, non-response bias, and measurement errors.
What documentation is
available describing
quality assurance
procedures?
http://www.nchh.Org/Portals/0/Contents/Article0312.pdf.
Chapter 7, sections 7.4 ("Quality of Field Data Collection") and section 7.5 ("Paint
Testing Quality Assurance"), pages 7-32 through 7-36.
For what years are data
available?
The main field study (survey and in-home lead) was conducted in 1998-1999, with
an augmentation of the soil sampling in 2000.
What is the frequency of
data collection?
Data were collected once, from 1998-1999, with an augmentation of the soil
sampling in 2000.
What is the frequency of
data release?
Raw data have not been publicly released. The report was published in April 2001.
Are the data comparable
across time and space?
As a one-time survey, time comparisons within the NSLAH are not possible, but
NSLAH results can be compared with the later AHHS survey (2005-2006).
Geographic comparisons should be possible using the raw data, since the same
data were collected at all homes.
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Appendix B: Metadata | Appendices
National Survey of Lead and Allergens in Housing (NSLAH)
(Used for Indicator E6)
Can the data be stratified
by race/ethnicity, income,
and location (region,
state, county or other
geographic unit)?
Data can be stratified by residents' age, race, ethnicity, and household income,
as well as by census region. Data can also be stratified by year of home
construction, and by the housing type (rented or owned). However, estimates of
lead hazards in the home for children ages 0 to 5 years broken out by
race/ethnicity and income are not statistically reliable, due to the relatively small
number of homes in each group.
National Vital Statistics System (NVSS)
(Used for Indicators H12 and HIS)
Brief description of the
data set
Who provides the data
set?
The National Vital Statistics System (NVSS) collects and disseminates data on
births, deaths, marriages, divorces, and fetal deaths from vital event registration
systems. The results of NVSS provide nearly complete data to track these vital
statistics nationwide.
Centers for Disease Control and Prevention, National Center for Health Statistics.
How are the data
gathered?
Data are obtained from birth, death, marriage and divorce certificates collected by
the various jurisdictions legally responsible for registration of these events.
What documentation is
available describing data
collection procedures?
See http://www.cdc.gov/nchs/data_access/Vitalstatsonline.htm for user's guides
by calendar year.
What types of data
relevant for children's
environmental health
indicators are available
from this database?
Relevant data include births, deaths, marriages, divorces, demographic
information, cause of mortality, and state and county (data prior to 2004 only).
Birth data include birth order, period of gestation, method of delivery, birth
weight, abnormal conditions of the newborn, and congenital abnormalities.
What is the spatial
representation of the
database (national or
other)?
Nearly complete national registration data have been collected since 1985. State
and county locations are recorded until 2004.
Are raw data (individual
measurements or survey
responses) available?
How are database files
obtained?
Data for each calendar year are available for download and analysis from
(http://www.cdc.gov/nchs/data_access/Vitalstatsonline.htm) with records for each
birth, death, marriage, or divorce certificate.
Annual and monthly reports from the NVSS are available
(http://www.cdc.gov/nchs/nvss/nvss_products.htm).
Raw NVSS data are also available from the National Bureau of Economic Research
at http://www.nber.org/data/ftdemographic
Personal identification data (e.g., names) is not available.
Raw data:
http://www.cdc.gov/nchs/data_access/Vitalstatsonline.htm
and http://www.nber.org/data/ftdemographic.
Queriable, less detailed data set including births, deaths, and fetal deaths, with
broad response categories: CDC WONDER at http://wonder.cdc.gov
Prebuilt or user-built birth data tables are available at
http://www.cdc.gov/nchs/VitalStats.htm.
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Appendices | Appendix B: Metadata
National Vital Statistics System (NVSS)
(Used for Indicators H12 and H13)
Are there any known data
quality or data analysis
concerns?
What documentation is
available describing
quality assurance
procedures?
For approximately 0.5% of the birth records, the mother's race was not stated and
in those cases the mother's race was statistically imputed. From 2003, some states
allowed reporting of multiple races, and in those cases the multiple race was
bridged to a primary race using statistical methods.
See http://www.cdc.gov/nchs/data_access/Vitalstatsonline.htm for user's guides
by calendar year.
For what years are data
available?
Online data: Births 1968-2009. Mortality multiple cause 1968-2009. Fetal death
1982-2006.
What is the frequency of
data collection?
Continuous.
What is the frequency of Annually.
data release?
Are the data comparable
across time and space?
Can the data be stratified
by race/ethnicity, income,
and location (region,
state, county or other
geographic unit)?
Some response variables have response categories that have changed over time.
Cause of mortality International Classification of Diseases coding systems have
changed over time. Birth certificate categories changed between the 1989 and
2003 versions of the birth certificates.
Data can be stratified by race and ethnicity. State and county data are complete
prior to 1989, contain county and city information only for counties with
populations above 100,000 for 1989 to 2004, and contain no location information
from 2005 forward. There are no income data.
Pesticide Data Program (POP)
(Used for Indicator E9)
Brief description of the
data set
Who provides the data
set?
The Pesticide Data Program (POP), initiated in 1991, focuses on measuring
pesticide residues in foods that are important parts of children's diets, including
apples, apple juice, bananas, carrots, grapes, green beans, orange juice, peaches,
pears, potatoes, and tomatoes. Samples are collected from food distribution
centers in 10 states across the country. Different foods are sampled each year and
then analyzed in various state and federal laboratories for the presence of residues
of about 300 pesticides and similar chemicals.
U.S. Department of Agriculture, Agricultural Marketing Service.
How are the data
gathered?
What documentation is
available describing data
collection procedures?
Food and water samples are collected by the participating states. Food samples are
prepared as if for consumption (washed, peeled, etc.). The pesticide residues are
measured at state and federal laboratories, and compiled into a database managed
by US DA.
Standard operating procedures, including data collection, are described here:
http://www.ams.usda.gov/AMSvl.O/ams.fetchTemplateData.do?template=Templa
teG&topNav=&leftl\lav=ScienceandLaboratories&page=PDPProgramSOPs&descript
ion=PDP+Standard+Operating+Procedures+(SOPs)&acct=pestcddataprg.
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Appendix B: Metadata | Appendices
Pesticide Data Program (POP)
(Used for Indicator E9)
What types of data
relevant for children's
environmental health
indicators are available
from this database?
Relevant data include pesticide residue concentrations measured in samples of
fruits, vegetables, grains, and other food and drink products, particularly foods
most likely consumed by infants and young children.
What is the spatial
representation of the
database (national or
other)?
National. In 2009, sampling services for food samples were provided by 10 states
(California, Colorado, Florida, Maryland, Michigan, New York, Ohio, Texas,
Washington, and Wisconsin). Approximately half of the U.S. population resides in
these 10 states.
Are raw data (individual
measurements or survey
responses) available?
Individual food and drink sample data are available.
How are database files
obtained?
Are there any known data
quality or data analysis
concerns?
Data files are freely available from:
http://www.ams.usda.gOV/AMSvl.0/ams.fetchTemplateData.do?template=Template
G&topNav=&leftNav=ScienceandLaboratories&page=PDPDownloadData/Reports&d
escription=Download+PDP+Data/Reports&acct=pestcddataprg.
Detection limits vary by pesticide, laboratory, commodity and over time. The list of
commodities sampled varies from year to year. The set of pesticides analyzed has
generally expanded over time.
What documentation is
available describing
quality assurance
procedures?
http://www.ams. usda.gov/AMSvl.0/ams.fetchTemplateData.do?template=Templa
teG&topNav=&leftNav=ScienceandLaboratories&page=PDPProgramSOPs&descript
ion=PDP+Standard+Operating+Procedures+(SOPs)&acct=pestcddataprg
includes documentation on quality assurance/quality control.
For what years are data
available?
1992-present.
What is the frequency of Annually.
data collection?
What is the frequency of Annually.
data release?
Are the data comparable
across time and space?
Can the data be stratified
by race/ethnicity, income,
and location (region,
state, county or other
geographic unit)?
Detection limits vary by pesticide, laboratory, commodity and over time. The list of
commodities sampled varies considerably from year to year. The set of pesticides
analyzed has also varied with time.
Data can be stratified by state where sample is collected and state or country of
origin.
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Appendices | Appendix B: Metadata
Safe Drinking Water Information System Federal Version (SDWIS/FED)
(Used for Indicators E7 and E8)
Brief description of the
dataset
Who provides the data
set?
SDWIS/FED is EPA's national database that manages and collects public water system
information from states, including reports of drinking water standard violations,
reporting and monitoring violations, and other basic information, such as water
system location, type, and population served.
(http://water.epa.gov/scitech/datait/databases/drink/sdwisfed/basicinformation.cfm )
U.S. Environmental Protection Agency, Office of Ground Water and Drinking Water.
How are the data
gathered?
What documentation is
available describing data
collection procedures?
Violation data for all public water systems are provided by states and EPA regions.
Public water systems are required to follow treatment and reporting requirements, to
measure contaminant levels, and to report violations of standards.
Information is available at
http://water.epa.gov/scitech/datait/databases/drink/sdwisfed/basicinformation.cfm
What types of data
relevant for children's
environmental health
indicators are available
from this database?
Relevant data include violations of national standards for drinking water—due to
contaminant levels exceeding allowable levels, violations of treatment requirements,
or violations of monitoring and reporting requirements—and total population served
by each public water system.
What is the spatial
representation of the
database (national or
other)?
SDWIS/FED includes data for all public water systems in the United States.
Are raw data (individual
measurements or survey
responses) available?
Separate reports for each violation of drinking water standards or monitoring and
reporting requirements for individual public water systems are available; measured
contaminant levels are not available in SDWIS/FED.
How are database files
obtained?
Are there any known data
quality or data analysis
concerns?
What documentation is
available describing
quality assurance
procedures?
For what years are data
available?
SDWIS/FED violation and inventory data were obtained from OGWDW staff who
compiled the data into a dataset listing the water system, state, violation type and
code, chemical contaminant code, violation dates, and the population served
The estimated number of people served by each public water system is approximate.
Estimates are updated when there is a significant change in a water system's
population. Some water systems serve more than one state (the primary state is
reported) and water systems often serve more than one county. Many people obtain
drinking water from more than one public water system. Although the data are largely
accurate, EPA is aware of underreporting of some violation data in SDWIS/FED. Several
states have recently found and corrected significant errors in their violation databases.
EPA routinely evaluates drinking water programs by conducting data verification
audits, which evaluate state compliance decisions and reporting to SDWIS/FED. Every
three years, the agency prepares summary evaluations based on the data
verification. These evaluations are available at:
http://www.epa.gov/safewater/databases/sdwis/datareliability.html.
1976-present.
What is the frequency of Quarterly.
data collection?
What is the frequency of Quarterly.
data release?
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Appendix B: Metadata | Appendices
Safe Drinking Water Information System Federal Version (SDWIS/FED)
(Used for Indicators E7 and E8)
Are the data comparable
across time and space?
Can the data be stratified
by race/ethnicity, income,
and location (region,
state, county or other
geographic unit)?
Violations across time are often not comparable because of changes in regulations and
changes in drinking water standards (maximum contaminant levels), and variability over
time in monitoring and reporting violations. Data may not be geographically
comparable due to variations in state enforcement and database quality.
Data can be stratified by state and county, with some uncertainty because boundaries
of public water systems do not coincide with state and county boundaries. The state
and county reported in SDWIS/FED are the primary state and county served by the
water system. Data cannot be stratified by demographic characteristics because
SDWIS/FED reports only the total population served by a public water system,
without any demographic information.
Surveillance, Epidemiology, and End Results (SEER) Program
(Used for Indicators H4 and H5)
Brief description of the
data set
Who provides the data
set?
The Surveillance, Epidemiology, and End Results (SEER) program is an authoritative
source of information on cancer incidence and mortality in the United States. SEER
collects and publishes cancer data from a set of 17 population-based regional
cancer registries located throughout the country.
National Cancer Institute.
How are the data
gathered?
What documentation is
available describing data
collection procedures?
Data on all diagnosed cancer cases in the geographical area for a cancer registry
are compiled each year and submitted to SEER. Mortality data for all causes of
death in the entire US are collected by the National Center for Health Statistics.
Population data are provided by the Census Bureau.
See http://seer.cancer.gov/index.html for detailed description of SEER organization
and data collection practices.
What types of data
relevant for children's
environmental health
indicators are available
from this database?
Relevant data include cancer incidence and mortality (including cancer type, tumor
site, tumor morphology, and stage at diagnosis, first course of treatment, and
follow-up for vital status), demographic information, and state and county.
What is the spatial
representation of the
database (national or
other)?
Are raw data (individual
measurements or survey
responses) available?
The most recent SEER database for cancer incidence has 18 population-based
cancer registries in 14 states and covers 28% of the U.S. population. A subset of the
current SEER includes 13 population-based cancer registries in 10 states and covers
14% of the U.S. population. The registries include: the Alaska Native, Atlanta,
Connecticut, Detroit, Hawaii, Iowa, Los Angeles, New Mexico, Rural Georgia, San
Francisco-Oakland, San Jose-Monterey, Seattle-Puget Sound, and Utah tumor
registries. These data are taken to represent cancer incidence for the entire United
States. See below for further discussion. The SEER database also includes national
mortality data for all causes of death from the National Vital Statistics System.
Yes.
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Appendices | Appendix B: Metadata
Surveillance, Epidemiology, and End Results (SEER) Program
(Used for Indicators H4 and H5)
How are database files http://seer.cancer.gov/data/access.html includes various methods of accessing
obtained? SEER data. Raw data for each person can be obtained. For ACE, annual summary
cancer incidence and mortality rate data were obtained using SEER*Stat software
available from the same website.
The population covered by SEER is comparable to the general U.S. population with
regard to measures of poverty and education. The SEER population tends to be
somewhat more urban and has a higher proportion of foreign-born persons than
the general U.S. population. Cancer mortality data for North Dakota and South
Carolina have significant percentages of persons with unknown ethnicity.
http://seer.cancer.gov/qi/index.html provides information on SEER quality
improvement.
Are there any known data
quality or data analysis
concerns?
What documentation is
available describing
quality assurance
procedures?
For what years are data
available?
Data are available from the original 9 SEER registries from 1973-present, but over
time the coverage of SEER has increased to cover more individuals and geographic
regions. See below for further discussion.
What is the frequency of Annually.
data collection?
What is the frequency of Annually.
data release?
Are the data comparable
across time and space?
The national coverage has increased over time from 9 to 18 cancer registries. Time
comparisons should be between the same set of registries. Thus, long-term trend
comparisons use SEER 9 (the original 9 registries) beginning with 1973 and cover
the smallest percentage (9.5% in 2000) of the U.S. population. The full set of
registries (SEER 18) has the broadest coverage (28%), but provides data only from
the year 2000 forward. SEER 13 covers 14% of the population and provides data
from 1992 forward. Population coverage varies by state.
Over time the cancer classifications used by SEER have changed. As scientific
knowledge has improved, some cancers that were once more generally classified
are now given a more exact definition. However, with each annual update SEER
updates the current and previous years' data to reflect the latest classification
scheme. The one exception would be for conditions that are now classified as
malignant cancers but were not previously and were therefore not registered by
the SEER cancer registries for earlier years. This applies only to a limited number of
rare tumor types, so it is not expected to contribute to changes in cancer incidence
overtime.
Can the data be stratified The data can be stratified by race and ethnicity, as well as median county income.
by race/ethnicity, income, Incidence data within the given SEER registry can be geographically stratified by state
and location (region, and county Mortality data can be geographically stratified by state and county.
state, county or other
geographic unit)?
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Appendix B: Metadata | Appendices
Texas Birth Defects Registry
(Used for Measure SI)
Brief description of the
data set
Who provides the data
set?
Since 1994, the Texas Birth Defects Epidemiology and Surveillance Branch has
maintained the Texas Birth Defects Registry, a population-based birth defects
surveillance system. Through multiple sources of information, the Registry
monitors all births in Texas (approximately 380,000 each year) and identifies cases
of birth defects. The Texas Registry staff routinely visit all hospitals and birthing
centers where affected babies are delivered or treated. There they review logs and
discharge lists to find potential cases, and then review medical records of the
potential cases to identify actual cases with birth defects.
Texas Department of State Health Services.
How are the data
gathered?
What documentation is
available describing data
collection procedures?
The Texas Birth Defects Registry uses active surveillance:
• Does not require reporting by hospitals or medical professionals.
• Trained program staff regularly visit medical facilities.
• Have legislative authority to review all relevant records.
• Review log books, hospital discharge lists, and other records to identify
potential cases.
• Review medical charts for potential cases to identify those with birth
defects.
• Program staff use medical charts for each potential birth defect identified.
Records in the birth defect registry are matched to birth certificates and fetal death
certificates filed with the Vital Statistics Unit of Texas DSHS to gather demographic
data.
Methods report available at:
http://www.dshs.state.tx.us/birthdefects/Data/99-04_Methods.pdf.
What types of data
relevant for children's
environmental health
indicators are available
from this database?
Relevant data include the following birth defects: central nervous system defects;
ear and eye defects; cardiac and circulatory defects; respiratory defects; oral clefts;
gastrointestinal defects; genitourinary defects, including hypospadias;
musculoskeletal defects; and chromosomal defects.
What is the spatial
representation of the
database (national or
other)?
Prior to 1999: selected health service regions of Texas. 1999 onward: entire state
of Texas.
Are raw data (individual
measurements or survey
responses) available?
Raw data for 1996-2007 are available through special request.
How are database files
obtained?
Routinely published tabulations of data for 1995-2007 (by birth defect, overall and
broken down by selected demographic factors) can be accessed at:
http://www.dshs.state.tx.us/birthdefects/Data/reports.shtm.
A queriable database of data for 1999-2006, where users can design their own
tabulations, can be found at: http://soupfin.tdh.state.tx.us/bdefdoc.htm.
Other tabulations or raw data are also available through 2007, by written request.
Go to http://www.dshs.state.tx.us/birthdefects/Data/reports.shtm and click on
"Birth Defects Data Request and Access Policy."
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Appendices | Appendix B: Metadata
Texas Birth Defects Registry
(Used for Measure SI)
Are there any known data
quality or data analysis
concerns?
What documentation is
available describing
quality assurance
procedures?
For what years are data
available?
Registry only includes birth defects diagnosed within one year of delivery (with the
exception of fetal alcohol syndrome). Secondly, diagnoses made outside Texas or in
Texas facilities that staff members do not have access to are excluded.
Due to flooding during June 2001, several hospitals in Houston lost medical
records. An estimated 50 fetuses and infants were born during this time with
diagnosed birth defects at the affected hospitals.
Data collected from medical records are subject to differences in clinical practice.
An article in Birth Defects Research Part A: Clinical and Molecular Teratology
highlights quality issues:
Miller, E. 2006. Evaluation of the Texas Birth Defects Registry: An active
surveillance system. Birth Defects Research Part A: Clinical and Molecular
Teratology. 76(11): 787-792.
See: http://www3.interscience.wiley.com/journal/113455770/abstract.
1996-2007.
What is the frequency of Ongoing.
data collection?
What is the frequency of
data release?
Annual.
Are the data comparable
across time and space?
Can the data be stratified
by race/ethnicity, income,
and location (region,
state, county or other
geographic unit)?
Yes, generally. However, data from different locations may not be comparable due
to differences in clinical practice. Identification of some birth defects may change
over time as more sensitive examinations and technologies lead to more accurate
recording of birth defects and/or better diagnosis of subtle defects. Prior to 1999,
only certain regions were included in the registry.
Using the interactive data query system
(http://soupfin.tdh.state.tx.us/bdefdoc.htm), data can be stratified by mother's
race/ethnicity, mother's age group, infant's sex, and geographical unit (statewide,
public health region, county, and border residence status.)
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America's Children and the Environment | Third Edition
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Appendix C: Alignment of
ACE3 Indicators with Healthy
People 2020 Objectives
Environments and Contaminants
Criteria Air Pollutants
Hazardous Air Pollutants
Indoor Environments
Drinking Water Contaminants
Chemicals in Food
Contaminated Lands
Biomonitoring
Lead
Mercury
Cotinine
Perfluorochemicals (PFCs)
Polychlorinated biphenyls (PCBs)
Polybrominated diphenyl ethers (PBDEs)
Phthalates
Bisphenol A(BPA)
Perchlorate
Health
Respiratory Diseases
Childhood Cancer
Neurodevelopmental Disorders
Obesity
Adverse Birth Outcomes
Supplementary Topics
Birth Defects
Contaminants in Schools and
Child Care Facilities
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Appendices | Appendix C: Healthy People 2020 Objectives
Appendix C: Alignment of ACES Indicators with
Healthy People 2020 Objectives
Healthy People 2020 (www.healthypeople.gov), an initiative of the U.S. Department of Health
and Human Services, provides science-based, 10-year national objectives for improving the
health of all Americans. This appendix provides examples of the alignment of the topics and
indicators presented in America's Children and the Environment, Third Edition (ACES) with
Healthy People 2020 objectives.
Objectives in Healthy People 2020 are organized by topic area; the table below provides a key
to the topic area acronyms used in the objective titles.
EH Environmental Health
TU Tobacco Use
RD Respiratory Disease
MICH Maternal Infant and Child Health
NWS Nutrition and Weight Status
PA Physical Activity
Environments and Contaminants
Criteria Air Pollutants
ACES Indicators
• El: Percentage of children ages 0 to 17 years living in counties with pollutant concentrations
above the level of the current air quality standards, 1999-2009
• E2: Percentage of children ages 0 to 17 years living in counties with 8-hour ozone and 24-
hour PM2.5 concentrations above the levels of air quality standards, by frequency of
occurrence, 2009
• E3: Percentage of days with good, moderate, or unhealthy air quality for children ages 0 to
17 years, 1999-2009
Healthy People 2020 Objective
• EH-1: Reduce the number of days the Air Quality Index (AQI) exceeds 100
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Appendix C: Healthy People 2020 Objectives | Appendices
Hazardous Air Pollutants
ACES Indicator
• E4: Percentage of children ages 0 to 17 years living in census tracts where estimated
hazardous air pollutant concentrations were greater than health benchmarks in 2005
Healthy People 2020 Objective
• EH-3: Reduce air toxic emissions to decrease the risk of adverse health effects caused by
airborne toxics
• EH-3.1: Mobile sources
• EH-3.2: Area sources
• EH-3.3: Major sources
Indoor Environments
ACES Indicators
• E5: Percentage of children ages 0 to 6 years regularly exposed to environmental tobacco
smoke in the home, by family income, 1994, 2005, and 2010
• E6: Percentage of children ages 0 to 5 years living in homes with interior lead hazards,
1998-1999 and 2005-2006
Healthy People 2020 Objectives
• TU-11: Reduce the proportion of nonsmokers exposed to secondhand smoke
• TU-11.1: Children aged 3 to 11 years
• EH-8: Reduce blood lead levels in children
• EH-8.1: Eliminate elevated blood lead levels in children
• EH-8.2: Reduce the mean blood lead levels in children
• EH-18: Reduce the number of U.S. homes that are found to have lead-based paint or related
hazards
• EH-18.1: Reduce the number of U.S. homes that are found to have lead-based paint
• EH-18.2: Reduce the number of U.S. homes that have paint-lead hazards
• EH-18.3: Reduce the number of U.S. homes that have dust-lead hazards
Drinking Water Contaminants
ACES Indicators
• E7: Estimated percentage of children ages 0 to 17 years served by community water
systems that did not meet all applicable health-based drinking water standards, 1993-2009
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Appendices | Appendix C: Healthy People 2020 Objectives
• E8: Estimated percentage of children ages 0 to 17 years served by community water
systems with violations of drinking water monitoring and reporting requirements,
1993-2009
Healthy People 2020 Objectives
• EH-4: Increase the proportion of persons served by community water systems who receive a
supply of drinking water that meets the regulations of the Safe Drinking Water Act
• EH-5: Reduce waterborne disease outbreaks arising from water intended for drinking
among persons served by community water systems
Chemicals in Food
ACES Indicator
• E9: Percentage of sampled apples, carrots, grapes, and tomatoes with detectable residues
of organophosphate pesticides, 1998-2009
Healthy People 2020 Objective
• None
Contaminated Lands
ACES Indicators
• E10: Percentage of children ages 0-17 years living within one mile of Superfund and
Corrective Action sites that may not have all human health protective measures in place, 2009
• Ell: Distribution by race/ethnicity and family income of children living near selected
contaminated lands in 2009, compared with the distribution by race/ethnicity and income
of children in the general U.S. population
Healthy People 2020 Objective
• EH-9: Minimize the risks to human health and the environment posed by hazardous sites
Biomonitoring
Lead
ACES Indicators
• Bl: Lead in children ages 1 to 5 years: Median and 95th percentile concentrations in blood,
1976-2010
• B2: Lead in children ages 1 to 5 years: Median concentrations in blood, by race/ethnicity
and family income, 2007-2010
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Appendix C: Healthy People 2020 Objectives | Appendices
Healthy People 2020 Objectives
• EH-8: Reduce blood lead levels in children
• EH-8.1: Eliminate elevated blood lead levels in children
• EH-8.2: Reduce the mean blood lead levels in children
• EH-16.7: Inspect drinking water outlets for lead
• EH-17: (Developmental) Increase the proportion of persons living in pre-1978 housing that
has been tested for the presence of lead-based paint or related hazards
• EH-17.1: (Developmental) Increase the proportion of pre-1978 housing that has been
tested for the presence of lead-based paint
• EH17.2: (Developmental) Increase the proportion of pre-1978 housing that has been
tested for the presence of paint-lead hazards
• EH-17.3: (Developmental) Increase the proportion of pre-1978 housing that has been
tested for the presence of lead in dust
• EH-17.4: (Developmental) Increase the proportion of pre-1978 housing that has been
tested for the presence of lead in soil
• EH-18: Reduce the number of U.S. homes that are found to have lead-based paint or related
hazards
• EH-18.1: Reduce the number of U.S. homes that are found to have lead-based paint
• EH-18.2: Reduce the number of U.S. homes that have paint-lead hazards
• EH-18.3: Reduce the number of U.S. homes that have dust-lead hazards
• EH-18.4: Reduce the number of U.S. homes that have soil-lead hazards
• EH-20: Reduce exposure to selected environmental chemicals in the population, as
measured by blood and urine concentrations of the substances or their metabolites
• EH-20.3: Lead
• EH-22: Increase the number of States, Territories, Tribes, and the District of Columbia that
monitor diseases or conditions that can be caused by exposure to environmental hazards
• EH-22.1: Lead poisoning
Mercury
ACES Indicator
• B3: Mercury in women ages 16 to 49 years: Median and 95th percentile concentrations in
blood, 1999-2010
Healthy People 2020 Objectives
• EH-20: Reduce exposure to selected environmental chemicals in the population, as
measured by blood and urine concentrations of the substances or their metabolites
• EH-20.4: Mercury, children aged 1 to 5 years
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Appendices | Appendix C: Healthy People 2020 Objectives
• EH-20.5: Mercury, females aged 16 to 49 years
• EH-22: Increase the number of States, Territories, Tribes, and the District of Columbia that
monitor diseases or conditions that can be caused by exposure to environmental hazards
• EH-22.3: Mercury poisoning
Cotinine
ACES Indicators
• B4: Cotinine in nonsmoking children ages 3 to 17 years: Median and 95th percentile
concentrations in blood serum, 1988-2010
• B5: Cotinine in nonsmoking women ages 16 to 49 years: Median and 95th percentile
concentrations in blood serum, 1988-2010
Healthy People 2020 Objectives
• TU-11: Reduce the proportion of nonsmokers exposed to secondhand smoke
• TU-11.1 Children aged 3 to 11 years
• TU-13: Establish laws in States, District of Columbia, Territories, and Tribes on smoke-free
indoor air that prohibit smoking in public places and worksites
• TU-13.6 Commercial daycare centers
• TU-13.11 Vehicles with children
Perfluorochemicals (PFCs)
ACES Indicator
• B6: Perfluorochemicals in women ages 16 to 49 years: Median concentrations in blood
serum, 1999-2008
Healthy People 2020 Objective
• None
Polychlorinated biphenyls (PCBs)
ACES Indicator
• B7: PCBs in women ages 16 to 49 years: Median concentrations in blood serum, by
race/ethnicity and family income, 2001-2004
Healthy People 2020 Objective
• EH-20: Reduce exposure to selected environmental chemicals in the population, as
measured by blood and urine concentrations of the substances or their metabolites.
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Appendix C: Healthy People 2020 Objectives | Appendices
• EH-20.12 PCB 153, representative of nondioxin-like PCBs.
• EH-20.13 PCB 126, representative of dioxin-like PCBs.
Polybrominated diphenyl ethers (PBDEs)
ACES Indicator
• B8: PBDEs in women ages 16 to 49 years: Median concentrations in blood serum, by
race/ethnicity and family income, 2003-2004
Healthy People 2020 Objective
• EH-20: Reduce exposure to selected environmental chemicals in the population, as
measured by blood and urine concentrations of the substances or their metabolites
• EH-20.18: BDE 47 (2,2',4,4'-tetrabromodiphenyl ether)
Phthalates
ACES Indicators
• B9: Phthalate metabolites in women ages 16 to 49 years: Median concentrations in urine,
1999-2008
• BIO: Phthalate metabolites in children ages 6 to 17 years: Median concentrations in urine,
1999-2008
Healthy People 2020 Objective
• EH-20: Reduce exposure to selected environmental chemicals in the population, as
measured by blood and urine concentrations of the substances or their metabolites
• EH-20.17: Mono-n-butyl phthalate
Bisphenol A (BPA)
ACES Indicators
• Bll: Bisphenol A in women ages 16 to 49 years: Median and 95th percentile concentrations
in urine, 2003-2010
• B12: Bisphenol A in children ages 6 to 17 years: Median and 95th percentile concentrations
in urine, 2003-2010
Healthy People 2020 Objective
• EH-20: Reduce exposure to selected environmental chemicals in the population, as
measured by blood and urine concentrations of the substances or their metabolites
• EH-20.15: Bisphenol A
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Appendices | Appendix C: Healthy People 2020 Objectives
Perchlorate
ACES Indicator
• B13: Perchlorate in women ages 16 to 49 years: Median and 95th percentile concentrations
in urine, 2001-2008
Healthy People 2020 Objective
• EH-20: Reduce exposure to selected environmental chemicals in the population, as
measured by blood and urine concentrations of the substances or their metabolites.
• EH-20.16: Perchlorate
Health
Respiratory Diseases
ACES Indicators
• HI: Percentage of children ages 0 to 17 years with asthma, 1997-2010
• H2: Percentage of children ages 0 to 17 years reported to have current asthma, by
race/ethnicity and family income, 2007-2010
• H3: Children's emergency room visits and hospitalizations for asthma and other respiratory
causes, ages 0 to 17 years, 1996-2008
Healthy People 2020 Objectives
• RD-1: Reduce asthma deaths
• RD-1.1: Children and adults under age 35 years
• RD-2: Reduce hospitalizations for asthma
• RD-2.1: Children under age 5 years
• RD-3: Reduce hospital emergency department visits for asthma
• RD-3.1: Children under age 5 years
• RD-4: Reduce activity limitations among persons with current asthma
• RD-5: Reduce the proportion of persons with asthma who miss school or work days
• RD-5.1: Reduce the proportion of children aged 5 to 17 years with asthma who miss
school days
• RD-6: Increase the proportion of persons with current asthma who receive formal patient
education
• RD-7: Increase the proportion of persons with current asthma who receive appropriate
asthma care according to National Asthma Education and Prevention Program (NAEPP)
guidelines
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Appendix C: Healthy People 2020 Objectives | Appendices
• RD-7.1: Persons with current asthma who receive written asthma management plans
from their health care provider
• RD-7.2: Persons with current asthma with prescribed inhalers who receive instruction
on their use
• RD-7.3: Persons with current asthma who receive education about appropriate
response to an asthma episode, including recognizing early signs and symptoms or
monitoring peak flow results
• RD-7.4: Increase the proportion of persons with current asthma who do not use more
than one canister of short-acting inhaled beta agonist per month
• RD-7.5: Persons with current asthma who have been advised by a health professional to
change things in their home, school, and work environments to reduce exposure to
irritants or allergens to which they are sensitive
• RD- 7.6: (Developmental) Persons with current asthma who have had at least one
routine follow-up visit in the past 12 months
• RD- 7.7: (Developmental) Persons with current asthma whose doctor assessed their
asthma control in the past 12 months
• RD-8: Increase the numbers of States, Territories, and the District of Columbia with a
comprehensive asthma surveillance system for tracking asthma cases, illness, and disability
at the State level
Childhood Cancer
ACES Indicators
• H4: Cancer incidence and mortality for children ages 0 to 19 years, 1992-2009
• H5: Cancer incidence for children ages 0 to 19 years by type, 1992-2006
Healthy People 2020 Objectives
• C-l: Reduce the overall cancer death rate
• C-12: Increase the number of central, population-based registries from the 50 States and
the District of Columbia that capture case information on at least 95 percent of the
expected number of reportable cancers
• C-20: Increase the proportion of persons who participate in behaviors that reduce their
exposure to harmful ultraviolet (UV) irradiation and avoid sunburn
• C-20.1: (Developmental) Reduce the proportion of adolescents in grades 9 through 12
who report sunburn
• C-20.3: Reduce the proportion of adolescents in grades 9 through 12 who report using
artificial sources of ultraviolet light for tanning
• C-20.5: Increase the proportion of adolescents in grades 9 through 12 who follow
protective measures that may reduce the risk of skin cancer
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Appendices | Appendix C: Healthy People 2020 Objectives
• ECBP-4: Increase the proportion of elementary, middle, and senior high schools that
provide school health education to promote personal health and wellness in the following
areas: hand washing or hand hygiene; oral health; growth and development; sun safety and
skin cancer prevention; benefits of rest and sleep; ways to prevent vision and hearing loss;
and the importance of health screenings and checkups
• ECBP-4.4: Sun safety or skin cancer prevention
Neurodevelopmental Disorders
ACES Indicators
• H6: Percentage of children ages 5 to 17 years reported to have attention-
deficit/hyperactivity disorder, by sex, 1997-2010
• H7: Percentage of children ages 5 to 17 years reported to have a learning disability, by sex,
1997-2010
• H8: Percentage of children ages 5 to 17 years reported to have autism, 1997-2010
• H9: Percentage of children ages 5 to 17 years reported to have intellectual disability (mental
retardation), 1997-2010
Healthy People 2020 Objectives
• EMC-2.4: Increase the proportion of parents who receive information from their doctors or
other health care professionals when they have a concern about their children's learning,
development, or behavior
• MICH-29: Increase the proportion of young children with an Autism Spectrum Disorder
(ASD) and other developmental delays who are screened, evaluated, and enrolled in early
intervention services in a timely manner
• MICH-29.1: Increase the proportion of young children who are screened for an Autism
Spectrum Disorder (ASD) and other developmental delays by 24 months of age
• MICH-29.2: Increase the proportion of children with an ASD with a first evaluation by 36
months of age
• MICH-29.3: Increase the proportion of children with an ASD enrolled in special services
by 48 months of age
• MICH-29.4: (Developmental) Increase the proportion of children with a developmental
delay with a first evaluation by 36 months of age
• MICH-29.5: (Developmental) Increase the proportion of children with a developmental
delay enrolled in special services by 48 months of age
Obesity
ACES Indicators
• H10: Percentage of children ages 2 to 17 years who were obese, 1976-2008
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Appendix C: Healthy People 2020 Objectives | Appendices
• Hll: Percentage of children ages 2 to 17 years who were obese, by race/ethnicity and
family income, 2005-2008
Healthy People 2020 Objectives
• NWS-5: Increase the proportion of primary care physicians who regularly measure the body
mass index of their patients
• NWS-5.2: Increase the proportion of primary care physicians who regularly assess body
mass index (BMI) for age and sex in their child or adolescent patients
• NWS-10: Reduce the proportion of children and adolescents who are considered obese.
• NWS-10.1: Children aged 2 to 5 years
• NWS-10.2: Children aged 6 to 11 years
• NWS-10.3: Adolescents aged 12 to 19 years
• PA-13: (Developmental) Increase the proportion of trips made by walking
• PA-13.2: Children and adolescents aged 5 to 15 years, trips to school of 1 mile or less
• PA-14: (Developmental) Increase the proportion of trips made by bicycling
• PA-14.2: Children and adolescents aged 5 to 15 years, trips to school of 2 miles or less
• PA-11: Increase the proportion of physician office visits that include counseling or
education related to physical activity
• PA-11.2: Increase the proportion of physician visits made by all child and adult patients
that include counseling about exercise
• PA-15: (Developmental) Increase legislative policies for the built environment that enhance
access to and availability of physical activity opportunities
Adverse Birth Outcomes
ACES Indicators
• H12: Percentage of babies born preterm, by race/ethnicity, 1993-2008
• H13: Percentage of babies born at term with low birth weight, by race/ethnicity, 1993-2008
Healthy People 2020 Objectives
• MICH-9: Reduce preterm births
• MICH-9.1: Total preterm births
• MICH-9.2: Late preterm or live births at 34 to 36 weeks of gestation
• MICH-9.3: Live births at 32 to 33 weeks of gestation
• MICH-9.4: Very preterm or live births at less than 32 weeks of gestation
• MICH-8: Reduce low birth weight (LBW) and very low birth weight (VLBW)
• MICH-8.1: Low birth weight (LBW)
• MICH-8.2: Very low birth weight (VLBW)
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Appendices | Appendix C: Healthy People 2020 Objectives
Supplementary Topics
Birth Defects
ACES Measure
• SI: Birth defects in Texas, 1999-2007
Healthy People 2020 Objective
• MICH-28: Reduce occurrence of neural tube defects
• MICH-28.1: Reduce the occurrence of spina bifida
• MICH-28.2: Reduce occurrence of anencephaly
Contaminants in Schools and Child Care Facilities
ACES Measures
• S2: Percentage of environmental and personal media samples with detectable pesticides in
child care facilities, 2001
• S3: Percentage of environmental and personal media samples with detectable industrial
chemicals in child care facilities, 2001
• S4: Pesticides used inside California schools by commercial applicators, 2002-2007
Healthy People 2020 Objective
• EH-16: Increase the proportion of the Nation's elementary, middle, and high schools that
have official school policies and engage in practices that promote a healthy and safe
physical school environment
• EH-16.1: Have an indoor air quality management program
• EH-16.4: Reduce exposure to pesticides by using spot treatments and baiting rather
than widespread application of pesticide
• EH-16.5: Reduce exposure to pesticides by marking areas to be treated with pesticides
• EH-16.6: Reduce exposure to pesticides by informing students and staff prior to
application of the pesticide
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