CHAPTER 5 

HUMAN HEALTH 

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HEALTH CHAPTER CONTENTS 

5.1 INTRODUCTION ........................................................................................................................5-5

5.1.1 The Environmental Public Health Paradigm ...................................................................5-6

Establishing Linkages Between Environmental Contaminants and Health Outcomes....5-7

5.1.2 Overview of the Data .......................................................................................................5-8

5.1.3 Organization of This Chapter...........................................................................................5-9

5.2 WHAT ARE THE TRENDS IN HEALTH STATUS IN THE UNITED STATES?.................5-11

5.2.1 Introduction....................................................................................................................5-11

5.2.2 Indicators .......................................................................................................................5-12

INDICATOR: General Mortality.................................................................................5-13

INDICATOR: Life Expectancy at Birth ......................................................................5-17

INDICATOR: Infant Mortality....................................................................................5-19

5.2.3 Discussion......................................................................................................................5-22

What These Indicators Say About Trends in U.S. Health Status...................................5-22

Limitations, Gaps, and Challenges ................................................................................5-24

5.3 WHAT ARE THE TRENDS IN HUMAN DISEASE AND CONDITIONS FOR WHICH 

ENVIRONMENTAL CONTAMINANTS MAY BE A RISK FACTOR, INCLUDING 

ACROSS POPULATION SUBGROUPS AND GEOGRAPHIC REGIONS? ..........................5-25

5.3.1 Introduction....................................................................................................................5-25

5.3.2 Indicators .......................................................................................................................5-29

INDICATOR: Cancer Incidence..................................................................................5-31

INDICATOR: Childhood Cancer Incidence................................................................5-35

INDICATOR: Cardiovascular Disease Prevalence and Mortality...............................5-37

INDICATOR: Chronic Obstructive Pulmonary Disease Prevalence and Mortality....5-43

INDICATOR: Asthma Prevalence ..............................................................................5-48

INDICATOR: Infectious Diseases Associated with Environmental Exposures or 

Conditions......................................................................................................................5-53

INDICATOR: Birth Defects Rates and Mortality .......................................................5-58

INDICATOR: Low Birthweight..................................................................................5-62

INDICATOR: Preterm Delivery..................................................................................5-65

5.3.3 Discussion......................................................................................................................5-67

What These Indicators Say About Trends in Diseases and Conditions for Which 

Environmental Contaminants May Be a Risk Factor.....................................................5-67

Limitations, Gaps, and Challenges ................................................................................5-68

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5.4 WHAT ARE THE TRENDS IN HUMAN EXPOSURE TO ENVIRONMENTAL 

CONTAMINANTS, INCLUDING ACROSS POPULATION SUBGROUPS AND 

GEOGRAPHIC REGIONS?.......................................................................................................5-72

5.4.1 Introduction....................................................................................................................5-72

5.4.2 Indicators .......................................................................................................................5-74

INDICATOR: Blood Lead Level.................................................................................5-76

INDICATOR: Blood Mercury Level...........................................................................5-79

INDICATOR: Blood Cadmium Level.........................................................................5-82

INDICATOR: Blood Persistent Organic Pollutants Level ..........................................5-85

INDICATOR: Urinary Pesticide Level .......................................................................5-94

INDICATOR: Urinary Phthalate Level.....................................................................5-100

5.4.3 Discussion....................................................................................................................5-105

What These Indicators Say About Trends in Exposure to Environmental 

Contaminants ...............................................................................................................5-105

Limitations, Gaps, and Challenges ..............................................................................5-105

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5.1 INTRODUCTION 

The health of the human population can be influenced by many factors, one of which is exposure to 

environmental contamination. Protecting human health from the effects of environmental contaminants is 

therefore an integral part of EPA’s mission. Protecting, sustaining, or restoring the health of people and 

communities is central to EPA’s various research and regulatory programs. EPA examines the human 

health impacts of contamination in air, in water, and on the land. Thorough study of adverse health effects 

associated with environmental exposures enable the Agency to evaluate harmful levels of exposure and 

issue guidelines for the safe production, handling, and management of hazardous substances. 

As described in Chapters 2 through 4, people are exposed to environmental contaminants in a variety of 

ways, and many contaminants are known to be or suspected of causing human disease. Identifying the 

extent to which human exposures may be occurring or may have occurred and measures of health 

outcomes possibly influenced by environmental exposures is important in determining where further 

study or public health interventions may be necessary. For example, a high or increasing rate of a 

particular cancer for which a hazardous substance in the environment is believed to be a contributing 

factor is of interest. Similarly, the presence or patterns of elevated levels of environmental contaminants 

as measured in human tissue through biomonitoring is also of interest. In addition, tracking health 

condition and exposures across various segments of the population such as gender, race or ethnicity, or 

geographic location helps to identify differences across subgroups and guide public health decisions and 

strategies. 

In this chapter, EPA seeks to assess trends in human disease and exposure that may be associated with 

environmental factors on a national scale. Health outcome and biomonitoring indicators are presented to 

address three fundamental questions: 

• What are the trends in health status in the United States? Here the report uses several 

general health outcome indicators (life expectancy, infant mortality, and general mortality) to 

provide a broad picture of health in the United States. Trends in these indicators provide a 

general context for understanding trends in specific diseases and conditions that may be 

linked with the environment. 

• What are the trends in human disease and conditions for which environmental 

contaminants may be a risk factor, including across population subgroups and geographic 

regions? This question looks at the occurrence of diseases and conditions that are known or 

suspected to be caused to some degree or exacerbated by exposures to environmental 

contaminants. This chapter uses a spectrum of indicators for health outcomes such as cancer, 

asthma, and birth outcomes to address this question. Both morbidity and mortality statistics 

are considered. 

• What are the trends in human exposure to environmental contaminants, including across 

population subgroups and geographic regions? Data on trends in exposure levels provide an 

opportunity to evaluate the extent to which environmental contaminants are present in human 

tissue, independent of the occurrence of specific diseases or conditions. To address this 

question, this chapter focuses on biomonitoring indicators (or biomarkers of exposure) for 

environmental contaminants such as lead, mercury, and pesticides. 

These ROE questions are posed without regard to whether indicators are available to answer them. This 

chapter presents the indicators available to answer these questions, and also points out important gaps 

where nationally representative data are lacking. 

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This chapter is not intended to be exhaustive in addressing these questions, nor is it intended to be a risk 

assessment or epidemiological study. Rather, it provides an overview of selected indicators of human 

disease and exposure over space and time based on key data sources with sufficiently robust design and 

quality assurance. 

The indicators used here are based on data sets representative of the national population; they are not 

based on data from targeted populations or tied to specific exposures or releases. Therefore, these data 

sets cannot and should not be used to draw conclusions about linkages or causal relationships between a 

particular health outcome or contaminant; nor is it possible to directly link the health outcome or 

biomonitoring indicators to any of the indicators of emissions or ambient pollutants in air, land, or water 

presented in earlier chapters of this report. Though the chapter does not assess quantitative relationships 

between the measures of environmental contaminants and diseases, it does present some qualitative 

discussion of the research that has examined some of these relationships. 

5.1.1 The Environmental Public Health Paradigm 

The relationship among and between environmental pollution, exposure, and disease is complex. 

Development of disease is multi-faceted. Relationships between environmental exposures and various 

health outcomes can only be established through well-designed epidemiological, toxicological, and 

clinical studies. An understanding of these factors is critical to providing the proper context for this 

chapter. 

The environmental public health paradigm shown in Exhibit 5-1 illustrates the broad continuum of factors 

or events that may be involved in the potential development of human disease following exposure to an 

environmental contaminant. This series of events serves as the conceptual basis for understanding and 

evaluating environmental health. The exhibit illustrates that for adverse health effects to occur (clinical 

disease or death) many things have to happen. A contaminant must be released from its source, reach 

human receptors (via air, water, land), enter the human body (via inhalation, ingestion, or skin contact), 

and be present within the body at sufficient doses within individuals to cause biological changes that may 

ultimately result in an observed adverse health effect. 

The paradigm, however, is a linear, schematic depiction of a process that is complex and multi-factorial. 

Exposure to an environmental contaminant or stressor is rarely the sole cause of an adverse health 

outcome. Environmental exposure is just one of several factors that may contribute to disease occurrence 

or to the severity of a preexisting disease. Other factors include, for example, diet, exercise, alcohol 

consumption, individual genetic makeup, medications, and other pre-existing diseases. It is known that 

asthma, for example, can be triggered by environmental insult, but environmental exposures are not the 

“cause” of all asthma attacks. In addition, different contaminants can be a risk factor for the same disease. 

Taking the same example, outdoor air pollution and certain indoor air pollutants, such as environmental 

tobacco smoke, can both exacerbate asthma symptoms. Further, susceptibility to disease is different for 

each person; some individuals may experience effects from certain ambient exposure levels while others 

may not. 

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Each block in Exhibit 5-11

 can have indicators associated with it. As shown, aspects of Chapters 2 

through 4 may address contaminant formation, release, transport, and transformation in the environment. 

Those chapters present indicators for the presence of contaminants or other stressors affecting air, water, 

and land, sometimes at locations in which people may be exposed. Measurements of ambient exposure 

levels are different than the biomonitoring indicators (biomarkers of exposures) introduced in this chapter. 

Other types of biomarkers exist (e.g., biomarkers of susceptibility and biomarkers of effect); because 

national-scale data do not exist for these biomarkers, they are not covered in this chapter at this time. 

The presence of a contaminant in the environment or within human tissue alone does not mean disease 

will occur. Furthermore, identification of diseases for which environmental contaminants are risk factors 

does not mean exposure has occurred or contributed to that disease. However, extensive and collaborative 

data collection and research efforts across the scientific community continue to strengthen our 

understanding of the relationships between environmental exposures and disease. 

Establishing Linkages Between Environmental Contaminants and Health 

Outcomes 

Scientific research has helped identify linkages between exposure to environmental contaminants and 

certain diseases, conditions, or other health outcomes. Examples include radon and lung cancer; arsenic 

and cancer in several organs; lead and nervous system disorders; disease-causing bacteria such as E. coli 

O157:h7 and gastrointestinal illness and death; and particulate matter and aggravation of cardiovascular 

and respiratory diseases. Such relationships between exposure and disease have been established through 

well-designed epidemiological studies with a defined or specified population (e.g., geographic location, 

susceptible populations, occupational exposures) and known environmental exposures. 

1 Adapted from: Sexton, K., S.G. Selevan, D.K. Wagener, and J.A. Lybarger. 1992. Estimating human exposures to 

environmental pollutants: availability and utility of existing databases. Arch. Environ. Health 47(6):398-407. 

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The causes of many diseases and other health conditions are not well established. In some cases 

environmental contaminants are considered important risk factors. In other cases, available data suggest 

that environmental exposures are important, but definitive proof is lacking. Developing conclusive 

evidence that environmental contaminants cause or contribute to the incidence of adverse health effects 

can be difficult, however, particularly for those effects occurring in a relatively small proportion of the 

population or effects with multiple causes. In cases where exposure to an environmental contaminant 

results in a relatively modest increase in the incidence of a disease or disorder, a large sample size for the 

study would be needed to detect a true relationship. In addition, there may be factors that are related to 

both the exposure and the health effect—confounding factors—that can make it difficult to detect a 

relationship between exposure to environmental contaminants and disease. In many cases, findings from 

studies in humans and/or laboratory animals may provide suggestive (rather than conclusive) evidence 

that exposures to environmental contaminants contribute to the incidence of a disease or disorder. 

EPA relies on the possible linkages established through the types of studies highlighted above to identify 

environmental contaminants and health outcomes of potential Agency interest (e.g., the indicators used in 

this chapter). To reiterate, however, the national-scale ROE indicators do not directly link exposure with 

outcome and cannot be used to demonstrate causal relationships. However, when combined with other 

information, such as environmental monitoring data and data from toxicological, epidemiological, or 

clinical studies, these indicators can be an important key to improve the understanding of the relationship 

between environmental contamination and health outcomes. 

5.1.2 Overview of the Data 

EPA draws on many resources and partnerships with other federal, state, and local agencies for the health 

data and statistical reports that underlie the health outcome and biomonitoring indicators used in this 

chapter. This report uses three key types of data sources, each with its own strengths and limitations: 

• Vital statistics data. Vital statistics of interest for health include births, deaths, and fetal 

deaths. Vital statistics data used in this report include the Centers for Disease Control and 

Prevention (CDC’s) National Center for Health Statistics’ (NCHS’) National Vital Statistics 

System. 

• Data collected from living human subjects. This includes both questionnaire-based 

information (e.g., NCHS’ National Health Interview Survey [NHIS], a nationwide survey to 

collect data on personal and demographic characteristics, illnesses, and other topics) and 

biological specimens (such as the NCHS’ National Health and Nutrition Examination Survey 

[NHANES], which collects and measures some chemicals in blood and urine samples). This 

report focuses on data collection activities with a national focus and that use a probabilitybased sampling design. 

• Data from surveillance activities. These include data from active surveillance activities such 

as the National Cancer Institute’s (NCI’s) Surveillance, Epidemiology, and End Results 

(SEER) Program, which collects and publishes cancer incidence and survival data from 

population-based cancer registries. It also includes data from more passive collection 

systems, such as CDC’s National Notifiable Disease Surveillance System, which provides 

information about diseases that health providers must report to state or local public health 

officials. 

This report also takes advantage of several published documents that present and summarize in one place 

the findings from many data collection activities (e.g., NCHS’ Healthy People 2010 Database). In 

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addition, it uses some databases that provide a single point of access to a variety of reports and numeric 

public health data and ways to conduct analyses of those data (e.g., CDC’s electronic database CDC 

WONDER). 

The data sources used provide statistics across time, geographic areas, and/or subpopulations such as age 

groups, races, and ethnicities. Identifying possible differences among population subgroups, as well as 

evidence of whether any differences are narrowing or widening, may reveal trends needing study or 

intervention. This type of trend analysis is consistent with national public health goals aimed at 

eliminating health disparities across various groups (e.g., racial and ethnic groups, low-income 

populations).2

 It addresses a continuing concern that minority and/or economically disadvantaged 

communities frequently may be exposed disproportionately to environmental exposures and related 

illnesses. Statistics for populations that may be particularly susceptible to environmental contaminants, 

such as children and pregnant women, are also examined. However, the type and level of subpopulation 

breakdown varies across data sets, sometimes making consistent presentation of this information difficult. 

Standards that specify the way in which race and ethnicity statistics are reported across federal agencies 

were revised in 1997. The standards, which became effective in 2003, expand the race and ethnicity 

categories for which data are collected and are aimed at increasing comparability of data among federal 

data systems. As vital records used to support federal data systems continue to be revised and come into 

compliance with the 1997 requirements, future data reporting and comparisons will be more 

straightforward. 

This chapter presents health statistics, including race and ethnicity subgroup information, as reported 

within the original data source documents or databases. The presentation of observed changes— 

temporally, spatially, or across subgroups—is descriptive, not quantitative. No statistical testing was 

performed (e.g., tests of statistical significance). 

This chapter presents only data that meet the ROE indicator definition and criteria (see Chapter 1, 

Introduction). Note that non-scientific indicators, such as administrative and economic indicators, are not 

included in this definition. Thorough documentation of the indicators data sources and metadata can be 

found online at <insert URL>. All indicators were peer-reviewed during an independent peer review 

process (see <insert URL> for more information). Readers should not infer that the indicators included 

reflect the complete state of the knowledge on trends in health and exposure related to environmental 

exposures. Many other data sources, publications, site-specific research projects, and epidemiological 

studies have contributed greatly to the current understanding of health and exposure trends, but are not 

used because they do not meet some aspect of the ROE indicator criteria. 

5.1.3 Organization of This Chapter 

The rest of this chapter is organized into sections corresponding to the three questions EPA seeks to 

answer about trends in human health and exposure. Each section introduces the question and its 

importance, presents the national indicators selected to help answer the question, and discusses what the 

indicators, taken together, say about the question. Each section concludes by highlighting the major 

challenges to answering the question and identifying important gaps and limitations. 

2

 U.S. Department of Health and Human Services. 2000. Healthy people 2010: understanding and improving health. 

Second ed. Washington, DC: U.S. Government Printing Office. <http://www.health.gov/healthypeople/> 

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The table below shows the indicators used to answer each of the questions in this chapter and where they 

are found. 

Table 5.1.1. Human Health—ROE Questions and Indicators 

Question Indicator Name Section Page # 

What are the trends in health status in 

the United States? 

General Mortality (N) 

Life Expectancy at Birth (N) 

Infant Mortality (N) 

5.2.2 5-13 

5.2.2 5-17 

5.2.2 5-19 

What are the trends in human disease 

and conditions for which 

environmental contaminants may be a 

risk factor including across population 

subgroups and geographic regions? 

Cancer Incidence (N) 

Childhood Cancer Incidence (N) 

Cardiovascular Disease Prevalence 

(N) and Mortality (N/R) 

Chronic Obstructive Pulmonary 

Disease Prevalence (N) and 

Mortality (N/R) 

Asthma Prevalence (N) 

Infectious Diseases Associated 

with Environmental Exposures 

or Conditions (N) 

Birth Defects Rates and Mortality 

(N) 

Low Birthweight (N) 

Preterm Delivery (N) 

5.3.2 5-31 

5.3.2 5-35 

5.3.2 5-37 

5.3.2 5-43 

5.3.2 5-48 

5.3.2 5-53 

5.3.2 5-58 

5.3.2 5-62 

5.3.2 5-65 

What are the trends in human 

exposure to environmental 

contaminants including across 

population subgroups and geographic 

regions? 

Blood Lead Level (N) 

Blood Mercury Level (N) 

Blood Cadmium Level (N) 

Blood Persistent Organic Pollutants 

Level (N) 

Blood Cotinine Level (N) 

Urinary Pesticide Level (N) 

Urinary Phthalate Level (N) 

5.4.2 5-76 

5.4.2 5-79 

5.4.2 5-82 

5.4.2 5-85 

2.4.2 2-114 

5.4.2 5-94 

5.4.2 5-100 

N = National Indicator 

N/R = National Indicator displayed at EPA Regional scale 

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5.2 WHAT ARE THE TRENDS IN HEALTH STATUS IN THE UNITED STATES? 

5.2.1 Introduction 

An overarching goal of public health agencies is to increase quality and years of healthy life and to 

eliminate health disparities. Tracking historical trends in general health status can help identify where 

interventions have improved the health of a population or where interventions may be needed (e.g., 

exploring causative factors and preventive measures). For example, a key concern for EPA is what 

possible environmental factors could be contributing to the diseases or conditions that are the leading 

causes of death in the United States. Tracking overall health in the United States therefore provides 

important context for the next section of this chapter, which examines specific acute and chronic diseases 

and conditions that may be linked with exposures to environmental contaminants. 

The topics covered are broad and not intended to represent specific diseases or conditions related to the 

environment. Environmental contaminants from air, water, and land can influence the overall health of a 

nation; however, many factors other than the environment also influence the health of a population, such 

as socio-demographic attributes, behavioral and genetic risk factors, level of preventive care, and quality 

of and access to health care. 

As defined by the World Health Organization (WHO), health is a state of complete physical, mental, and 

social well-being, and not the mere absence of disease or infirmity.

3

 The health status of a population can 

be measured by a wide range of factors: birth and death rates, life expectancy, quality of life, morbidity 

from specific diseases, risk factors, use of ambulatory care and inpatient care, accessibility of health 

personnel and facilities, financing of health care, health insurance coverage, and many other factors.4 

While no single set of measures can completely characterize the health of a large and diverse population, 

the CDC and other health agencies worldwide consistently have viewed life expectancy and mortality 

data as indicators of overall population health because they represent the cumulative effects of social and 

physical environmental factors, behavioral and genetic risk factors, and the level and quality of health 

care. These data include the leading causes of mortality (among both infants and the general population), 

which provide a broad perspective on the diseases and conditions that are having the greatest impact on 

the nation’s health. Infant mortality is a particularly useful measure of health status, because it indicates 

both the current health status of the population and predicts the health of the next generation.5

 It reflects 

the overall state of maternal health as well as the quality and accessibility of primary health care available 

to pregnant women and infants. 

3 World Health Organization. 1946. Preamble to the constitution of the World Health Organization as adopted by the 

International Health Conference, New York, 19-22 June, 1946; signed on 22 July 1946 by the representatives of 61 

States (Official Records of the World Health Organization, no. 2, p. 100) and entered into force on 7 April 1948. 

<http://w3.whosea.org/aboutsearo/pdf/const.pdf> 

4

U.S. Department of Health and Human Services. 2000. Healthy people 2010: understanding and improving health. 

Second ed. Washington, DC: U.S. Government Printing Office. <http://www.health.gov/healthypeople/> 

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 National Center for Health Statistics. 2001. Healthy people 2000 final review. Hyattsville, MD: Public Health 

Service. <http://www.cdc.gov/nchs/data/hp2000/hp2k01-acc.pdf> 

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Tracking health status using such indicators provides information on changing or emerging trends. At the 

beginning of the 20th century, the population of the United States was characterized by a low standard of 

living, poor hygiene, and poor nutrition; communicable diseases and acute conditions were major causes 

of most premature deaths. Over the course of the century, public health measures such as improved 

sanitation and drinking water treatment led to a dramatic decrease in deaths due to infectious diseases and 

a marked increase in life expectancy. As the population has aged, chronic diseases such as heart disease 

and cancer have become the leading causes of death.6

 These diseases may require a different approach to 

prevention, detection, and treatment compared to the infectious and acute illnesses more common in the 

past. 

5.2.2 Indicators 

Other agencies such as the CDC routinely assess the state of the nation’s health. EPA has drawn on the 

comprehensive data collection efforts and assessments conducted by these agencies in addressing this 

question. Three indicators are used to assess the trends in health status in the United States (Table 5.2.1). 

Life expectancy at birth is the number of years a newborn would expect to live if that person experienced 

the mortality schedule existing at the time of birth. Infant mortality is the number of infants who die 

before their first birthday. General mortality represents the number of all deaths nationwide and provides 

information on the leading causes of death. Mortality is also tracked using years of potential life lost, or 

the number of years “lost” by people in a population who die prematurely of a stated cause. These 

indicators are interrelated—e.g., declines in mortality result in increased life expectancy, and shifts in life 

expectancy are often used to describe changes in mortality; changes in infant mortality are reflected in 

general mortality as well. 

Where possible, the indicators for this question track health status among subpopulations (e.g., by gender, 

race, ethnicity). Generally, differences in mortality and life expectancy between black and white 

Americans have been tracked for the past several decades, in some cases as far back as the 1930s. A 

broader spectrum of race and ethnic group breakdowns is available for these indicators in more recent 

years, including American Indian/Alaskan Native, Asian or Pacific Islander, and Hispanic origin. 

Subpopulation data are presented to the extent practicable under What the Data Show and/or within 

indicator exhibits. 

Table 5.2.1. ROE Indicators of Trends in Health Status in the United States 

NATIONAL INDICATORS LOCATION 

General Mortality 5.2.2 – p. 5-13 

Life Expectancy at Birth 5.2.2 – p. 5-17 

Infant Mortality 5.2.2 – p. 5-19 

6

 National Center for Health Statistics. 2001. Healthy people 2000 final review. Hyattsville, MD: Public Health 

Service. <http://www.cdc.gov/nchs/data/hp2000/hp2k01-acc.pdf> 

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INDICATOR: General Mortality 

Overall mortality is a key measure of health in a population. Two measures of mortality are cause-specific 

mortality and years of potential life lost (YPLL). All-cause mortality counts the total number of deaths 

due to any cause within a specified year, whereas cause-specific mortality statistics count the number of 

deaths due to a particular cause in a specified year. YPLL is defined as the number of years between the 

age at death and a specified age; that is, the total number years which are “lost” by persons in the 

population who die prematurely of a stated cause. Ranking the causes of death can provide a description 

of the relative burden of cause-specific mortality (NCHS, 2005). 

This indicator is based on mortality data recorded in the National Vital Statistics System (NVSS), which 

registers virtually all deaths nationwide from death certificate data. YPLL is calculated by subtracting the 

age at death from a selected age (e.g., 65, 75, 85), then summing the individual YPLL across each cause 

of death (CDC, 2006). Sixty-five was selected as the age for this indicator to focus on deaths more likely 

to be attributable to preventable causes and less influenced by increasing age. The temporal coverage of 

the data is from 1933 to 2003 and data are collected from all 50 States and the District of Columbia. 

What the Data Show 

As noted in 2003 Draft ROE, an increase in the 

number of deaths in the United States has been 

observed over the last few decades, reflecting the 

increase in the size and aging of the population. The 

number of deaths continued to increase in 2001, 2002, 

and 2003 where 2,416,425; 2,443,387; and 2,448,288 

deaths, respectively, were recorded, an increase 

compared to 1999 (2,391,399 deaths). However, the 

age-adjusted all cause mortality rates have declined 

yearly since 1980 (except in years of influenza 

outbreaks in 1983, 1985, 1988, 1993, and 1999) with 

the most recent available rate of 832.7 deaths per 

100,000 people in 2003. Exhibit 5-2 provides some 

historical perspective on trends in the age-adjusted 

mortality rates between 1940 and 2003, showing that 

age-adjusted rates were nearly twice as high in 1940 as 

they were in 2000. The largest declines in “all cause 

mortality” rates since 1990 has occurred among black 

males compared with white males and black and white 

females. 

The rank order of the leading causes of death has remained the same since 1999, as reported in 2003 Draft 

ROE. Exhibits 5-3 and 5-4 present the leading causes of mortality and YPLL for 2003, respectively. The 

three leading causes of death were heart disease, cancer, and stroke, accounting for about 60 percent of all 

deaths. The YPLL ranking is different, with unintentional injuries, cancer, and heart disease comprising 

the top three for this measure 

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During 2003, heart disease was the leading cause of death across the reported racial and ethnic groups and 

this was generally the case after further stratifying by race/ethnicity and gender. For Asians or Pacific 

Islanders, however, cancer (malignant neoplasms) was the leading cause of death. In addition, diabetes 

was ranked as the fourth leading cause of death among blacks and American Indian/Alaska Natives (both 

sexes), which was a higher ranking than for most of the other racial and ethnic groups. (Data not shown). 

Indicator Limitations 

• Cause of death rankings denote the most frequently occurring causes of death among those 

causes eligible to be ranked. The rankings do not necessarily denote the causes of death of 

greatest public health importance. Further, rankings of cause-specific mortality could change 

depending on the defined list of causes that are considered and, more specifically, the types of 

categories and subcategories that are used for such rankings (NCHS, 2005). 

• Mortality rates are based on underlying cause-of-death as entered on a death certificate by a 

physician. Incorrect coding and low rates of autopsies that confirm the cause of death may 

occur. Additionally, some individuals may have had competing causes of death. “When more 

than one cause or condition is entered by the physician, the underlying cause is determined by 

the sequence of conditions on the certificate, provisions of the ICD [International 

Classification of Diseases], and associated selection rules and modifications” (CDC, n.d.). 

Consequently, some misclassification of reported mortality might occur as a result of these 

uncertainties, as well as the underreporting of some causes of death. 

Data Sources 

Mortality rates were obtained from vital statistics reports published by CDC’s National Center for Health 

Statistics (NCHS, 2001, 2006). Data in the NCHS reports are based in part on unpublished work tables, 

available on the NCHS web site at http://www.cdc.gov/nchs/deaths.htm. Leading cause of death and 

YPLL data were extracted from CDC’s Web-Based Injury Statistics Query and Reporting System 

(WISQARS) (CDC, 2006) (http://www.cdc.gov/ncipc/wisqars/). The underlying data in WISQARS come 

from CDC/NCHS annual mortality data files. 

References 

CDC (Centers for Disease Control and Prevention). 2006. National Center for Injury Prevention and 

Control. Web-based Injury Statistics Query and Reporting System (WISQARS) [online]. Leading causes 

of death and years of potential life lost (YPLL) reports, 1999-2003. Accessed 2006. 

<http://webappa.cdc.gov/sasweb/ncipc/leadcaus.html> 

<http://webappa.cdc.gov/sasweb/ncipc/ypll10.html> 

CDC (Centers for Disease Control and Prevention). n.d. CDC WONDER: Help page for compressed 

mortality file. <http://wonder.cdc.gov/wonder/help/cmf.html> 

NCHS (National Center for Health Statistics). 2006. Deaths: final data for 2003. National Vital Statistics 

Reports 54(13). April 19. <http://www.cdc.gov/nchs/data/nvsr/nvsr54/nvsr54_13.pdf> 

NCHS (National Center for Health Statistics). 2005. Deaths: leading causes for 2002. National Vital 

Statistics Reports 53(17). <http://www.cdc.gov/nchs/data/nvsr/nvsr53/nvsr53_17.pdf> 

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NCHS (National Center for Health Statistics). 2001. Age-adjusted death rates; trend data based on the 

year 2000 standard population. National Vital Statistics Reports 49(9). 

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INDICATOR: Life Expectancy at Birth 

Life expectancy at birth is often used to appraise the overall health of a given population (NCHS, 2005). 

Changes in life expectancy over time are commonly used to describe trends in mortality. Life expectancy 

is the average number of years at birth a person could expect to live if current mortality trends were to 

continue for the rest of that person's life. 

This indicator is based on data from the National Vital Statistics System (NVSS), which registers 

virtually all deaths and births nationwide. The temporal coverage of the data is from 1933 to 2003 and 

data are collected from all 50 States and the District of Columbia. 

9 What the Data Show

10 Exhibit 5-5 presents the historical trends in life 

11 expectancy for the entire population as well as by 

12 gender and race (black and white) between 1940 and 

13 2003 showing an upward trend in life expectancy in the 

14 United States over time. Life expectancy at birth has 

increased throughout the 20th and now into the 21st 15 

16 century. The overall life expectancy was a record high 

17 in 2003 at 77.5 years, a slight increase from 77.0 years 

18 in 2000, 77.2 years in 2001, and 77.3 in 2002. This 

19 follows seven consecutive years of increases. 

20 Life expectancy continues to increase for both males 

21 (73.9 years in 1999 to 74.8 years in 2003) and females 

22 (79.4 years in 1999 to 80.1 years in 2003). The gap in 

23 life expectancy between males and females widened 

24 from 2.0 years to 7.8 years between 1900 and 1979. 

25 Recently, this gap narrowed for the year 2000 and 

26 remained relatively constant through 2003 with a 

27 difference of 5.3-5.4 years between males and females. 

28 (Data not shown.)

29 The increase in life expectancy among blacks reported for 1999 continued in 2001, 2002, and 2003 at 

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72.2, 72.3, 72.7 years, respectively. The difference in life expectancy between the black and white 

populations was 5.3 years in 2003. In 2003, white females continued to have the highest life expectancy at 

80.5 years, followed by black females at 76.1 years, white males at 75.3 years and black males at 69.0 

years (Exhibit 5-5). 

Indicator Limitations

• Life expectancy at birth is strongly influenced by infant and child mortality rates. It is 

important to consider such influences when making comparisons among subgroups since 

differences in life expectancy among certain subgroups may be mostly attributed to 

differences in prenatal care and other important determinants of infant and child mortality. 
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Data Sources 

The annual life expectancy data used for this indicator were obtained from life tables published by CDC’s 

National Center for Health Statistics (NCHS, 2006a). NCHS also publishes life expectancy data in its 

annual “deaths: final data” reports (e.g., NCHS, 2006b); however, these reports generally provide yearby-year breakdowns beginning in 1975. NCHS life table reports provide annual data back to before 1940. 

Life table methodologies used to calculate life expectancies are presented in each of these NCHS reports. 

References 

NCHS (National Center for Health Statistics). 2006a. United States life tables. National Vital Statistics 

Reports 54(14). Table 12. April 19. http://www.cdc.gov/nchs/data/nvsr/nvsr54/nvsr54_14.pdf

NCHS (National Center for Health Statistics). 2006b. Deaths: final data for 2003. National Vital Statistics 

Reports 54(13). Table 8. April 19. <http://www.cdc.gov/nchs/data/nvsr/nvsr54/nvsr54_13.pdf> 

NCHS (National Center for Health Statistics). 2005. Health, United States, 2005, with chartbook on 

trends in the health of Americans. DHHS Publication No. 2005-1232. Hyattsville, MD. 

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INDICATOR: Infant Mortality 

Infant mortality is a particularly useful measure of health status because it indicates both current health 

status of the population and predicts the health of the next generation (NCHS, 2001). Infant mortality in 

the United States is defined as the death of an infant from time of live birth to the age of 1 year. It does 

not include still births. Overall infant mortality is comprised of neonatal (<28 days after birth) and 

postneonatal (28 days to 11 months after birth) deaths. 

This indicator presents infant mortality for the U.S. based on mortality data from the National Vital 

Statistics System (NVSS) based on death certificate data. The NVSS registers virtually all deaths and 

births nationwide with data coverage from 1933 to 2003 and from all 50 states and the District of 

Columbia. 

What the Data Show 

In 2001, 2002, and 2003, a total of 27,568; 28,034; and 

28,025 deaths, respectively, occurred in infants under 1 

year of age. As reported in 2003 Draft ROE, the infant 

mortality rate in 1999 was 7.1 per 1,000 live births, the 

lowest ever recorded in the U.S. (Hoyert et al., 2001). 

This trend continued in 2001 with an infant mortality 

rate of 6.8 per 1,000 live births. However, data for 2002 

and 2003 suggest a slight increase in the infant 

mortality rate, reported as 7.0 and 6.9 per 1,000 live 

births, respectively. Exhibit 5-6 presents the national 

trends in infant mortality between 1940 and 2003 for 

all infant deaths as well as infant deaths by gender and 

race (black and white). A striking decline has occurred 

during this time period with overall infant mortality 

rates dropping from nearly 50 deaths per 1,000 live 

births in 1940 to just under 7 deaths per 1,000 live 

births in 2003. Infant mortality rates were highest 

among black males and lowest among white females, 

although this gap has been decreasing over time. 

The infant mortality rate for blacks decreased from 

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14.6 per 1,000 live births in 1999 to 14.0 per 1,000 live births in 2003. However, this is still twice the rate 

compared to white infants, which ranged from 5.7-5.8 per 1,000 live births between 1999 and 2003. 

Infant mortality rates among Hispanic infants have changed little since 1999. In 2003, the infant mortality 

the same rate as reported in 1999 (NCHS, 2006). (Data not shown.) 

In the U.S. in 2003, the 10 leading causes of infant mortality accounted for nearly 69 percent of all infant 

deaths with the subgroup consisting of congenital anomalies (i.e., congenital malformations, 

deformations, and chromosomal abnormalities) having the highest rate at 1.4 per 1,000 live births. This 

category alone accounts for approximately 20 percent of all infant deaths in 2003 (Exhibit 5-7). 

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Congenital anomalies were generally ranked highest among the different racial groups. However, the 

leading cause of infant mortality among blacks was short gestation and low birth weight followed by 

congenital anomalies. There were few differences in the leading causes of infant mortality between 

Hispanics and non-Hispanics. In addition, CDC reports a substantial difference in the leading causes of 

death during the neonatal versus the postneonatal periods. Disorders related to short gestation were the 

leading cause of death for neonates and sudden infant death syndrome (SIDS) was the leading cause of 

death for postneonates (CDC, 2005). (Data not shown.) 

Indicator Limitations 

• Cause of death rankings denote the most frequently occurring causes of death among those 

causes eligible to be ranked. The rankings do not necessarily denote the causes of death of 

greatest public health importance. Further, rankings of cause-specific mortality could change 

depending on the defined list of causes that are considered and, more specifically, the types of 

categories and subcategories that are used for such rankings (NCHS, 2005) 

• Mortality rates are based on underlying cause-of-death as entered on a death certificate by a 

physician. Incorrect coding and low rates of autopsies that confirm the cause of death may 

occur. Additionally, some individuals may have had competing causes of death. “When more 

than one cause or condition is entered by the physician, the underlying cause is determined by 

the sequence of conditions on the certificate, provisions of the ICD [International 

Classification of Diseases], and associated selection rules and modifications” (CDC, n.d.). 

Consequently, some misclassification of reported mortality might occur as a result of these 

uncertainties, as well as the underreporting of some causes of death. 

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Data Sources 

Infant mortality data were obtained from a published report by CDC’s National Center for Health 

Statistics (NCHS, 2006), which provides annual natality data back to 1975 and decadal data for 1940, 

1950, 1960, and 1970. Data in the NCHS report are based in part on unpublished work tables, available 

on the NCHS web site at http://www.cdc.gov/nchs/deaths.htm. Leading cause of infant death data were 

extracted from CDC’s Web-Based Injury Statistics Query and Reporting System (WISQARS) (CDC, 

2006) (http://www.cdc.gov/ncipc/wisqars/). The underlying data in WISQARS come from CDC/NCHS 

annual mortality data files. 

References 

CDC (Centers for Disease Control and Prevention). 2006. National Center for Injury Prevention and 

Control: Web-Based Injury Statistics Query and Reporting System (WISQARS) [online]. Leading causes 

of death reports, 1999-2003. Accessed 2006. <http://webapp.cdc.gov/sasweb/ncipc/leadcaus.html> 

CDC (Centers for Disease Control and Prevention). 2005. QuickStats: leading causes of neonatal and 

postneonatal deaths—United States, 2002. MMWR 54(38):966. 

<http://www.cdc.gov/mmwr/preview/mmwrhtml/mm5438a8.htm> 

CDC (Centers for Disease Control and Prevention). n.d. CDC WONDER: Help page for compressed 

mortality file. <http://wonder.cdc.gov/wonder/help/cmf.html> 

NCHS (National Center for Health Statistics). 2006. Deaths: final data 2003. National Vital Statistics 

Reports 54(13). April 19. <http://www.cdc.gov/nchs/data/nvsr/nvsr54/nvsr54_13.pdf> 

NCHS (National Center for Health Statistics). 2005. Deaths: leading causes for 2002. National Vital 

Statistics Reports 53(17). <http://www.cdc.gov/nchs/data/nvsr/nvsr53/nvsr53_17.pdf> 

NCHS (National Center for Health Statistics). 2001. Healthy people 2000 final review. Hyattsville, MD: 

Public Health Service. <http://www.cdc.gov/nchs/data/hp2000/hp2k01-acc.pdf> 

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5.2.3 Discussion 

What These Indicators Say About Trends in U.S. Health Status 

ROE indicators used to answer this question show that the overall health of the nation has continued to 

improve. The three leading causes of death across all age groups—heart disease, cancer, and stroke— 

remain unchanged since 1999. In contrast, a ranking by years of potential life lost, which weighs more 

heavily deaths at an earlier age, places unintentional injuries, cancer, and heart disease as the top three 

(General Mortality indicator, p. 5-13). Although men and women in many other countries have longer life 

expectancies, general mortality rates in the United States continue to decline, and life expectancy 

continues a long-term upward trend (Life Expectancy indicator, p. 5-17). See the sidebar on the next page 

for an overview of health status in the United States compared to the rest of the world. 

The decline in the all-cause mortality rate since 1940 has been driven largely by declines in deaths from 

heart disease, stroke, and unintentional injuries. These trends have been linked in part to the resources 

devoted to health education, public health programs, health research, and health care, and the impact of 

these efforts on controlling disease. For example, public campaigns about smoking and the use of 

cholesterol-lowering drugs have contributed to a decline in the death rate from heart disease. Efforts to 

improve motor vehicle safety as well as safety in homes and workplaces have helped to lower death rates 

from unintentional injuries. New medical treatments have resulted in a decline in the death rate from 

HIV.7 

Infant mortality (p. 5-19), like the other two indicators, shows a long-term decline, likely due to 

widespread application of advances in medical knowledge (such as the introduction of synthetic 

surfactant for preterm infants and widespread public education about infant sleep position).8

 However, 

infant mortality in the United States remains among the highest in the industrialized world, and in 2002 a 

slight increase in rate was reported for the first time since 1958. This rate dropped back slightly in 2003. 

This recent rise in infant mortality is attributed to an increase in neonatal deaths (infants less than 28 days 

old), particularly deaths of infants within the first week of life.9 

7

 National Center for Health Statistics. 2005. Health, United States, 2005, with chartbook on trends in the health of 

Americans. DHHS publication no. 2005-1232. Hyattsville, MD. p. 3. 

8

 National Center for Health Statistics. 2001. Healthy people 2000 final review. Hyattsville, MD: Public Health 

Service. p. 206. <http://www.cdc.gov/nchs/data/hp2000/hp2k01-acc.pdf> 

9

 National Center for Health Statistics. 2005. Health, United States, 2005, with chartbook on trends in the health of 

Americans. DHHS publication no. 2005-1232. Hyattsville, MD. p. 66. 

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Worldwide Comparisons in Health Status 

The following comparisons are based on the most current statistics for each of the three indicators 

used to study U.S. health status. The WHO calculates its statistics to ensure comparability across 

data sets; the statistics may not fully match those generated by individual countries and reported in 

other reports. 

Life Expectancy. According to the World Health Organization (WHO), in 2003, the United States 

ranked 34th in terms of life expectancy for males and 35th for females of the 192 WHO member 

states.1

 Japan reports the highest life expectancy (82 years, compared to the U.S life expectancy of 

77 years reported by WHO). 

Leading Causes of Death. The leading causes of death reported in the United States in 2002 were 

heart disease, cancer, and stroke. Worldwide, cardiovascular diseases accounted for the largest 

percentage of deaths, followed by infectious and parasitic diseases and cancer.2 

Infant mortality. In 2002, the United States ranked 28th among the 37 countries, territories, cities, or 

geographic areas with at least 1 million population considered to have completed counts of live births 

and infant deaths as indicated in the United Nations Demographic Yearbook.

3 The U.S. infant 

mortality rate for the same time period (7.0 per 1,000 live births) was approximately 2-3 times higher 

than the lowest rates reported worldwide (e.g., in Hong Kong the rate was 2.3, Sweden the rate was 

2.8, Singapore the rate was 2.9, and Japan the rate was 3.0, per 1,000 live births). 

1

 WHO. 2005. World Health Report. See Statistical Annex Table 1. http://www.who.int/entity/whr/2005/annex/annex1.xls 

2 WHO 2005. WHO Statistical Information System (WHOSIS). Estimates of numbers of deaths by sex, cause and WHO 

mortality sub-region for 2002. http://www3.who.int/whosis/burden/estimates/2002/2002subregion/dth14_2002.zip

3

National Center for Health Statistics (NCHS). 2005. Health, United States, 2005, with chartbook on trends in the health of 

Americans. Hyattsville, Maryland. DHHS Publication No. 2005-1232. Table 25. http://www.cdc.gov/nchs/data/hus/hus05.pdf. 

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Despite a generally improving picture of the nation’s health, racial and ethnic disparities in health status 

persist. For example, though the nation’s infant mortality rate has decreased, the infant death rate for 

black infants is still more than double that of whites. In 2003, the gap in life expectancy between the 

black and white populations is 5.3 years, though this gap has been narrowing.10 Differences in death rates 

also exist between black and white populations. Observed differences are believed to be the result of a 

complex interaction of genetic variations, environmental factors, and specific health behaviors.11 

Differences also exist between men and women. Based on 2003 data, men have a life expectancy 5.4 

years less than that of women and have higher death rates for each of the 10 leading causes of death. 

10 National Center for Health Statistics. 2005. Health, United States, 2005, with chartbook on trends in the health of 

Americans. DHHS publication no. 2005-1232. Hyattsville, MD. pp. 11-12. 

11 U.S. Department of Health and Human Services. 2000. Healthy people 2010: understanding and improving health. 

Second ed. Washington, DC: U.S. Government Printing Office. <http://www.health.gov/healthypeople/> 

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However, women have shown increased death rates over the past decade in areas where men have 

experienced improvements, such as lung cancer.12

Limitations, Gaps, and Challenges 

The indicators are important and widely accepted measures of population health status. However, the 

selected indicators cannot be expected to fully answer the question on trends in general U.S. health status. 

Limitations and information gaps are highlighted here. 

The indicators provide a broad measure of health status and include many variables that are not related to 

the environment. No conclusions, therefore, can or should be drawn about the role of exposure to 

environmental contaminants using these indicators alone. While declining mortality rates and increasing 

life expectancy suggest improving health status, these indicators do not address other aspects of health, 

such as morbidity, perceived well-being, or quality of life. 

The use of mortality data presents some limitations, largely related to uncertainties associated with the use 

of death certificate data. First, correct coding of the underlying cause of death and confirmation by 

autopsy may not occur. Second, uncertainties in intercensal population estimates can affect conclusions 

about trends in data sets. In addition, improved data on the health status of population subgroups— 

particularly across race and ethnic groups—would allow better characterization of potential trends across 

different groups. Accurate identification of health disparities will require improved data collection and the 

use of standardized data. For example, problems of race and Hispanic-origin classification can affect 

Hispanic death rates and the comparison of rates across the Hispanic and non-Hispanic populations.13 

12 National Center for Health Statistics. 2005. Health, United States, 2005, with chartbook on trends in the health of 

Americans. DHHS publication no. 2005-1232. Hyattsville, MD. pp. 11-12. 

13 National Center for Health Statistics. 2006. Deaths: final data 2003. National Vital Statistics Reports 54(13). April 

19. <http://www.cdc.gov/nchs/data/nvsr/nvsr54/nvsr54_13.pdf> 

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5.3 WHAT ARE THE TRENDS IN HUMAN DISEASE AND CONDITIONS FOR 

WHICH ENVIRONMENTAL CONTAMINANTS MAY BE A RISK FACTOR, 

INCLUDING ACROSS POPULATION SUBGROUPS AND GEOGRAPHIC 

REGIONS? 

5.3.1 Introduction 

As discussed throughout this report, numerous human diseases and conditions have been linked with 

exposures to environmental contaminants, some more strongly than others. Identifying diseases that 

might be associated with environmental contaminants, and determining the existing data sources available 

for them, is a key part of the effort to better characterize links between environmental exposures and 

adverse health outcomes. 

Tracking overall rates of disease in the nation, independent of exposure, enables the evaluation of disease 

patterns and emerging trends. It may identify diseases, conditions, and possible risk factors that warrant 

further study or intervention and can help identify where policies or interventions have been successful. 

Because the United States has a diverse population, an important component of such an analysis is 

identifying disparities among people of differing races and ethnicities, genders, education and income 

levels, and geographic locations. 

EPA has selected those human diseases and conditions with well-established associations with exposures 

to environmental contaminants and for which national data are available, recognizing again that in most 

cases risk factors are multi-factorial. The diseases and conditions addressed in this question are associated 

with the contaminant sources covered by the questions in the three media chapters (Chapters 2, 3, and 4) 

of this report. As described in Section 5.1, however, this question is not intended to tie human diseases 

and conditions to specific changes in the environment being measured at the national level. Covered 

health outcomes fall into the following five broad categories: cancer, cardiovascular disease, respiratory 

disease, infectious disease, and birth outcome. The reasons for the inclusion of each are highlighted 

below. 

Cancer 

The term “cancer” refers to diseases in which abnormal cells divide without control, losing their ability to 

regulate their own growth, control cell division, and communicate with other cells. Cancer is the second 

leading cause of death in the United States (General Mortality indicator, p. 5-13). More than one in three 

people will develop cancer and nearly one in four will die of it.14,15 In response, scientists continue to 

explore the role that the exposure to environmental contaminants may play, along with other possible risk 

factors, in the initiation and development of cancer. Some environmental exposures are known risk 

factors for certain types of cancers. Examples include radon and lung cancer and arsenic and skin cancer. 

Though many types of cancer may be related to environmental exposures, associations are not always 

clear because the etiology of cancer is complex and influenced by a wide range of factors. Exposures may 

include environmental contaminants in air, water, and soil but also result from exposure to sunlight, 

14 American Cancer Society. 2005. Cancer facts and figures 2005. Atlanta. 

<http://www.cancer.org/downloads/STT/CAFF2005f4PWSecured.pdf> 

15 National Toxicology Program. 2004. Report on carcinogens. Eleventh ed. U.S. Department of Health and Human 

Services, Public Health Service. <http://ntp.niehs.nih.gov/ntp/roc/toc11.html> 

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workplace exposures, and drugs. Other factors may increase individual cancer risk, such as age, genetics, 

existence of infectious diseases, and socioeconomic factors that may affect exposure and susceptibility. 

Childhood cancers are dissimilar from cancers in adults and are therefore tracked separately. They affect 

different anatomic sites and may be of embryonic origin. Though overall cancer incidence rates are 

relatively lower in children compared to adults, childhood cancers are the third leading cause of death in 

children age 1-19 years.16 Children may be particularly susceptible to exposures in utero or during early 

childhood because systems are rapidly developing and affected by evolving hormonal systems.17 As with 

many adult cancers, the causes of childhood cancers are unknown for the most part; environmental 

influences may be a factor and have been the subject of extensive research. 

Cardiovascular Disease 

More than one-fourth of the U.S. population lives with a cardiovascular disease, with more than 6 million 

hospitalizations each year.18 Coronary heart disease and stroke, two of the major types of cardiovascular 

disease, rank as the first and third leading causes of death, respectively (General Mortality indicator, p. 5­

13), and are leading causes of premature and permanent disabilities. Known risk factors include smoking, 

high blood pressure, high blood cholesterol, diabetes, physical inactivity, and poor nutrition. Outdoor air 

pollution and environmental tobacco smoke are also known risk factors for cardiovascular disease. 

Particulate matter, for example, has been demonstrated to be a likely causal factor in both cardiovascular 

disease morbidity and mortality. Environmental tobacco smoke has been shown to be a risk factor for 

coronary heart disease morbidity and mortality and may contribute to stroke.19,20,21 

Respiratory Disease 

Chronic obstructive pulmonary disease (COPD) and asthma are two prevalent chronic respiratory diseases 

in the United States. COPD is a group of diseases characterized by airflow obstruction, resulting in 

breathing-related symptoms and encompasses chronic obstructive bronchitis and emphysema.22,23 COPD 

16 National Center for Health Statistics. 2004. Deaths: final data for 2002. National Vital Statistics Reports 53(5). 

<http://www.cdc.gov/nchs/data/nvsr/nvsr53/nvsr53_05.pdf> 

17 Anderson, L.M., B.A. Diwan, N.T. Fear, and E. Roman. 2000. Critical windows of exposure for children’s health: 

cancer in human epidemiological studies and neoplasms in experimental animal models. Environ. Health. Perspect. 

108(Suppl 3):573-594. 

18 Centers for Disease Control and Prevention. 2005. Preventing heart disease and stroke. Addressing the nation’s 

leading killers—at a glance. Revised August 2005. 

19 National Cancer Institute. 1999. Smoking and tobacco control monograph 10: health effects of exposure to 

environmental tobacco smoke. <http://cancercontrol.cancer.gov/tcrb/monographs/10/m10_complete.pdf> 

20 U.S. EPA. 2005. Review of the national ambient air quality. Standards for particulate matter: policy assessment of 

scientific and technical information. OAQPS Staff Paper. 

21 U.S. EPA. 2004. Air quality criteria for particulate matter. Volumes I (EPA/600/P-99/002aF) and II (EPA/600/P99/002bF). National Center for Environmental Assessmen–RTP Office, Office of Research and Development. 

22 Mannino, D.M. 2002. COPD epidemiology, prevalence, morbidity and mortality, and disease heterogeneity. Chest 

121:121S-126S. 

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is the fourth leading cause of death in the United States and is the leading cause of hospitalization in U.S. 

adults, particularly in older adults. It represents a major cause of morbidity, mortality, and disability.

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Asthma continues to receive attention in both children and adults. Asthma prevalence increased nearly 74 

percent during 1980-1996.25 

Epidemiological and clinical studies have shown that ambient and indoor air pollution are risk factors in 

several respiratory health outcomes, including reported symptoms (nose and throat irritation), acute onset 

or exacerbation of existing disease (e.g., asthma), and deaths. Environmental contaminants such as dust 

mites, pets, mold, and other allergens are considered important triggers for asthma.26 In addition, the 

relationship between environmental tobacco smoke and diseases of the respiratory tract has been studied 

extensively in humans and in animals; environmental tobacco smoke has been shown to produce a variety 

of upper and lower respiratory tract disorders.27 

Infectious Diseases 

Infectious diseases are acute illnesses caused by bacteria, protozoa, fungi, and viruses. Food and water 

contaminated with pathogenic microorganisms are the major environmental sources of gastrointestinal 

illness. Though well-established systems for reporting food- and waterborne cases exist, data reported 

through these largely voluntary programs must be interpreted with caution because many factors can 

influence whether an infectious disease is recognized, investigated, and reported. Changes in the number 

of cases reported could reflect actual changes or simply changes in surveillance and reporting. In addition, 

many milder cases of gastrointestinal illnesses go unreported or are not diagnosed, making it difficult to 

estimate the number of people affected every year. 

The discovery of bacterial contamination of drinking water as the cause of many cases of gastrointestinal 

illness represents one of the great public health success stories of the 20th century. Waterborne diseases 

such as typhoid fever and cholera were major health threats across the United States at the beginning of 

the 20th century. Deaths due to diarrhea-like illnesses, including typhoid, cholera, and dysentery, 

represented the third largest cause of death in the nation at that time. These types of diarrheal deaths 

dropped dramatically once scientists identified the bacteria responsible, elucidated how these bacteria 

were transmitted to and among humans in contaminated water supplies, and developed effective water 

treatment methods to remove pathogens from water supplies. 

23 Barnes, P.J. 2000. Chronic obstructive pulmonary disease. Review article. N. Engl. J. Med. 343(4):269-280. 

24 Mannino, D.M., D.M. Homa, L.J. Akinbami, et al. 2002. Chronic obstructive pulmonary disease surveillance— 

United States, 1971-2000. In: Surveillance Summaries. MMWR 51(SS06):1-16. 

25 Mannino, D.M., D.M. Homa, L.J. Akinbami, et al. 2002. Surveillance for asthma—United States, 1980-1999. In: 

Surveillance Summaries. MMWR 51(SS-1):1-13. 

26 U.S. Institute of Medicine. 2000. Clearing the air. Asthma and indoor air exposures. Washington, DC: National 

Academy Press. 

27 State of California. 2005. Proposed identification of environmental tobacco smoke as a toxic air contaminant. Part 

B: health effects assessment for environmental tobacco smoke. As approved by the Scientific Review Panel on June 

24, 2005. California Environmental Protection Agency, Office of Environmental Health Hazard Assessment. 

<http://www.arb.ca.gov/regact/ets2006/ets2006.htm> 

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In addition to being of food- or waterborne origin, infectious disease can be airborne, arthropod-borne 

(spread by mosquitoes, ticks, fleas, etc.), or zoonotic (spread by rodents, dogs, cats, and other animals). 

Legionellosis can be contracted from naturally-occurring bacteria found in water and spread through 

poorly maintained artificial water systems (e.g., air conditioning, ventilation systems). Arthropod-borne 

diseases, including Lyme disease, Rocky Mountain Spotted Fever, and West Nile Virus, can be contracted 

from certain ticks and mosquitoes that acquire bacteria or viruses by biting an infected mammal or bird. 

Birth Outcomes 

Birth defects are structural anomalies that are present in the fetus at birth, including those resulting from 

chromosomal abnormalities. They affect approximately one out of 33 babies born each year in the United 

States and remain the leading cause of infant mortality (Infant Mortality indicator, p. 5-19). Serious, 

adverse effects on health, development, and functional ability may be experienced by individuals born 

with birth defects.28 Birth defects have been linked with a variety of possible risk factors that can affect 

normal growth and development—genetic or chromosomal aberrations, as well as environmental factors 

such as exposure to chemicals; exposure to viruses and bacteria; and use of cigarettes, drugs, or alcohol 

by the mother. Because the causes of most birth defects are unknown, public concern exists about 

possible environmental links to birth defects. 

Low birthweight delivery and preterm birth are considered important risk factors for infant mortality and 

birth defects. Low birthweight infants have a significantly increased risk of infant death, and those who 

survive are more likely to experience long-term developmental disabilities.29 Multiple birth babies have a 

low birthweight rate of more than 50 percent, compared to approximately 6 percent among singletons, 

among whom the low birth weight rate rose only 1 percent from 1989-1998.30 To eliminate the effect that 

multiple births may have on birth outcomes, this report presents data for singleton births only. 

Environmental exposures are being investigated for possible associations with birth outcomes such as low 

birthweight, preterm births, and infant mortality. Some of the risk factors for low birthweight infants born 

at term include maternal smoking, weight at conception, and nutrition and weight gain during 

pregnancy.

31 Specific examples of known or suspected environmental contaminant influences on these 

birth outcomes include environmental tobacco smoke, air pollution, and lead. Environmental tobacco 

smoke is associated with increased risk of low birthweight, preterm delivery, and sudden infant death 

syndrome.

32 Associations between air pollution and fetal growth and infant mortality have been 

28 Centers for Disease Control and Prevention. 2006. Improved national prevalence estimates for 18 selected major 

birth defects—United States, 1999-2001. MMWR 54(51&52):1301-1305. 

29 National Center for Health Statistics. 2005. Health, United States, 2005, with chartbook on trends in the health of 

Americans. DHHS publication no. 2005-1232. Hyattsville, MD. p. 11. 

30 National Center for Health Statistics. 2001. Healthy people 2000 final review. Hyattsville, MD: Public Health 

Service. p. 208. <http://www.cdc.gov/nchs/data/hp2000/hp2k01-acc.pdf> 

31 U.S. Department of Health and Human Services. 2000. Healthy people 2010: understanding and improving health. 

Second ed. Washington, DC: U.S. Government Printing Office. <http://www.health.gov/healthypeople/> 

32 State of California. 2005. Proposed identification of environmental tobacco smoke as a toxic air contaminant. Part 

B: health effects assessment for environmental tobacco smoke. As approved by the Scientific Review Panel on June 

24, 2005. California Environmental Protection Agency, Office of Environmental Health Hazard Assessment. 

<http://www.arb.ca.gov/regact/ets2006/ets2006.htm> 

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documented, but more evidence is needed to establish causal relationships between air pollution and 

preterm birth.33 Several studies also have identified lead as a risk factor for preterm delivery.

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Researchers continue to examine possible associations between other contaminants as birth outcome risk 

factors, such as pesticides, polycyclic aromatic hydrocarbons, among others. 

5.3.2 Indicators 

EPA has selected indicators of health outcomes for which environmental exposures may be a risk factor 

and for which nationally representative data are available. Nine indicators were selected to address the 

question (Table 5.3.1)—two for cancer (including the leading sites of cancer in adults and children), one 

for cardiovascular disease (including coronary heart disease, stroke, and hypertension), two related to 

respiratory disease (including asthma and chronic lung conditions such as bronchitis and emphysema), 

one for infectious diseases (comprised of multiple diseases and conditions), and three for birth outcomes. 

The indicators used to answer this question are drawn from CDC’s vital statistics and surveillance data, 

including the CDC WONDER Mortality Database, Summary of Notifiable Diseases, NCHS’s National 

Vital Statistics Reports, Summary Health Statistics for the U.S., and National Health Interview Survey, as 

well as the National Cancer Institute’s (NCI’s) Surveillance, Epidemiology, and End Results (SEER) 

Database. The time frames covered generally range back to the 1970s for mortality and incidence data 

and to the mid-1990s for prevalence data. 

In answering this question, both disease morbidity (incidence or prevalence) and mortality (resulting 

death) statistics are used. Depending on the health outcome of interest, both measures can provide useful 

insights about trends in disease. Both morbidity and mortality statistics are influenced by a number of 

factors, however, such as the accuracy of reporting mechanisms, and issues related to access to, quality 

of, and advances in medical care. An overall understanding of the disease measures and associated 

statistics used to answer this question is important.35 

33 Sram R.J., B. Binkova, J. Dejmek, and M. Bobak. 2005. Ambient air pollution and pregnancy outcomes: a review 

of the literature. Environ. Health. Perspect. 113(4):375-382. 

34 Agency for Toxic Substances and Disease Registry. 2005. Toxicological profile for lead (update). Draft for public 

comment. Atlanta, GA: U.S. Department of Health and Human Services, Public Health Service. 

35 Both morbidity and mortality can be measured using occurrences or rates. Occurrences represent frequency 

counts, while rates enable a comparison across populations. Rates are ratios that calculate the frequency of cases (of 

disease, condition, outcome) divided by the size of the defined population for a specified time period. Usually some 

constant (generally a multiplier of the power 10) is applied to convert the rate to a whole number. 

Morbidity data are often used to describe the incidence and prevalence of a disease or condition. Both incidence and 

prevalence are often expressed as a rate per 1,000 persons over a particular time period. Incidence refers to the 

number of new cases of a disease or condition in a population during a specified time period. Prevalence refers to 

the total number of people with a given disease or condition in a population at a specified point in time. 

Mortality is generally expressed as a rate and is defined as the proportion of the population who die of a disease or 

condition during a specified time period. The rate is usually calculated for a calendar year and is often expressed per 

100,000 persons. 

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Where possible, breakouts of population subgroups are provided, such as race, ethnicity, age, and gender. 

Subpopulation data are presented to the extent practicable under What the Data Show, within text or 

shown in indicator figures. For cardiovascular and respiratory diseases, mortality statistics are provided 

for each of the 10 EPA Regions. For cancer, data for the most frequently diagnosed cancer sites in adults 

and children, along with overall cancer rates, are used to answer the question. 

Table 5.3.1. ROE Indicators of Trends in Human Disease and Conditions for Which Environmental 

Contaminants May Be a Risk Factor Including Across Population Subgroups and Geographic 

Regions 

NATIONAL INDICATORS LOCATION 

Cancer Incidence 5.3.2 – p. 5-31 

Childhood Cancer Incidence 5.3.2 – p. 5-35 

Cardiovascular Disease Prevalence and Mortality (N/R) 5.3.2 – p. 5-37 

Chronic Obstructive Pulmonary Disease Prevalence and Mortality (N/R) 5.3.2 – p. 5-43 

Asthma Prevalence 5.3.2 – p. 5-48 

Infectious Diseases Associated with Environmental Exposures or 

Conditions 

5.3.2 – p. 5-53 

Birth Defects Rates and Mortality 5.3.2 – p. 5-58 

Low Birthweight 5.3.2 – p. 5-62 

Preterm Delivery 5.3.2 – p. 5-65 

N/R = National Indicator displayed at EPA Regional scale 

Incidence, prevalence, and mortality statistics may be used to compare the rates of disease at two or more points in 

time, across different populations (ages, gender, racial/ethnic groups), or between different geographic areas. In 

general, disease incidence, prevalence, and mortality increase with age. For this reason, when comparing different 

populations, the data must be adjusted to account for the age differences between the populations. The adjusted data, 

called “age-adjusted rates,” are used where possible in answering this question. Age-adjusted rates are weighted 

sums of age-specific rates and calculated using standard population factors (In this report, the 2000 U.S. standard 

population was used). Unadjusted rates are referred to as “crude” rates. 

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1 INDICATOR: Cancer Incidence

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The term “cancer” is used to characterize diseases in which abnormal cells divide without control. A 

cancerous cell loses its ability to regulate its own growth, control cell division, and communicate with 

other cells. Cancer cells can invade nearby tissues and can spread through the bloodstream and lymphatic 

system to other parts of the body (NCI, n.d.). The risk of developing cancer increases with age and the 

environment (as broadly defined), genetic predisposition, certain viruses, and socioeconomic factors may 

all play a role in the development and progression of the disease. 

For the U.S. population, age-adjusted cancer incidence rates for all sites combined have been stable since 

1992 (Edwards et al., 2005). Nevertheless, cancer continues to be the second leading cause of death in the 

United States, accounting for about 23 percent of all deaths in 2003 (General Mortality indicator, p. 5-13) 

(NCHS, 2006). Many different types of cancer exist. These may develop in various organs and tissues 

within the body and contributing causal factors may vary depending on the cancer site and type. 

Therefore, tracking rates for individual cancer sites is more meaningful when evaluating cancer trends. 

The contribution of environmental factors to the development of various cancers has been and continues 

to be a major focus of research. Factors including individual food and beverage preferences, use of 

tobacco products, exposure to natural and medical radiation (including sunlight), workplace exposures, 

and pharmaceutical use as well as exposure to substances in the air, water and soil all may contribute 

individually (additive) or synergistically (i.e., an effect greater than the sum of each factor acting alone) to 

the development of cancer (NTP, 2004). Only in a small number of cases, however, is it known what 

specific environmental factor(s) or condition(s) are responsible for the onset and development of cancers 

(NTP, 2004).

This indicator presents cancer incidence rates for the U.S. population using data collected through the 

National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) Program. The SEER 

Program collects and publishes cancer incidence and 

survival data from 14 population-based cancer 

registries and three supplemental registries covering 

approximately 26 percent of the U.S. population. The 

10 most commonly diagnosed cancer sites presented 

are based on 2003 data compiled from SEER. Site 

classifications (e.g., lung and bronchus; colon and 

rectum) were compared to the American Cancer 

Society’s “leading sites” classification to ensure 

consistency in how data are presented (ACS, 2003). 

What the Data Show

Although a slow steady increase in cancer incidence 

occurred between 1973 and 1992 peaking in 1992 with 

an age-adjusted cancer incidence of 510 cases per 

100,000, overall incidence rates appear to have 

stabilized over the last ten years (Exhibit 5-8). Some 

differences exist in incidence rates across age, gender, 

and racial groups. During 2003, those age 65 and older 

had the highest incidence rates (2,109.1 cases per 

100,000) compared to all other age categories (data not 
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shown). Total (all sites combined) cancer incidence rates are higher for males compared to females and 

for black males compared to white males (Exhibit 5-8). The age-adjusted cancer incidence rate in 2003 

for black males was 650.4 cases per 100,000 compared to 541.3 cases per 100,000 for white males; 

among females, the age-adjusted cancer incidence rate in 2003 was 417.3 cases per 100,000 for white 

females compared to 397.6 cases per 100,000 among black females, showing a slight decrease from 2002. 

Exhibit 5-9 shows the differences between the top ten cancer sites in males and females. For both, the top 

three cancers represent over half of all newly identified cancer cases in 2003. Among the most notable 

differences is the rate of urinary bladder cancer among males (36.4 cases per 100,000), which is more 

than three times that of females (9.4 cases per 100,000). Melanoma of the skin is also higher among males 

(23.0 cases per 100,000) than females (15.8 cases per 100,000). Thyroid cancer appears as the seventh 

leading cancer in females (14.0 cancers per 100,000), but is not among the top ten for males (4.6 cases per 

100,000). 

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Among males, prostate cancer incidence rates increased dramatically between 1986 and the early 1990s, 

with a decline in rates between 1992 and 1995. This increase is likely due to the introduction of serum 

prostate-specific antigen (PSA) testing for the early detection and screening of prostate cancer (Hankey et 

al., 1999). The other four leading cancers (colon and rectum, lung and bronchus, urinary bladder, and 

non-Hodgkin’s lymphoma) have either been relatively stable or have showed a small decline over the last 

decade (Exhibit 5-10). 

Recent trends (i.e., since 1995) among the less prevalent site-specific cancers in males show small 

increases in the incidence rates for melanoma of the skin (melanoma), which ranged from 20.2 (1995) to 

24.1 (2001) cases per 100,000, and cancers of the kidney and renal pelvis (kidney), which ranged from 

15.0 (1997) to 17.6 (2002) cases per 100,000. Slightly decreasing rates were observed for leukemia, 

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which ranged from 17.5 (1995) to 15.4 (2003) cases per 

100,000, and cancers of the oral cavity and pharynx 

(oral cavity), which ranged from 17.6 (1996) to 15.2 

(2003) cases per 100,000. (Data not shown.). 

As shown in Exhibit 5-11, among females, breast 

cancer remains the leading cancer and rates have 

generally increased for much of the reporting period. 

While lung cancer among males has slowly declined 

over the past decade, the rate among women has 

increased over the last decade and has become the 

second leading cancer among men and women in 2003. 

The incidence rate of colon cancer among women 

slowly increased between 1973 and 1985 and has 

slowly declined since. The incidence of uterine (corpus 

uteri) cancer in females was relatively stable since 1986 

with a small decrease in more recent years, ranging 

from 25.4 (1997) to 23.3 (2003) cases per 100,000. The 

incidence rate of non-Hodgkin’s lymphoma has 

exhibited a slow increase since 1973. 

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Recent trends in cancer incidence rates among the less prevalent site-specific cancers in females showed 

increases for melanoma, which ranged from 13.7 (1995) to 16.2 (2001) cases per 100,000 and thyroid 

cancer, which ranged from 8.9 (1995) to 14.0 (2003) cases per 100,000. Incidence rates decreased for 

cancers of the ovary, which ranged from 14.7 (1997) to 13.2 (2003) cases per 100,000. (Data not shown.) 

Indicator Limitations 

• SEER data cover approximately 26 percent 

of the U.S. population, though it is 

designed to be representative of the entire 

U.S. population. 

• Incidence data generated from SEER are 

updated annually. There may be changes in 

the numerator (e.g., revised counts of 

newly identified cases) or denominator 

(i.e., revised population counts) numbers 

that result in small changes in the overall 

incidence rates for the same year 

depending on when a query is run within 

the SEER database. For example, the 

SEER database queried in 2005 generating 

incidence rates for the year 2000 may 

provide different incidence rates than the 

database queried in 2004 for the same year 

(i.e., 2000). 

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Data Sources 

Cancer incidence data for this indicator were obtained by querying the National Cancer Institute’s (NCI’s) 

Surveillance, Epidemiology, and End Results (SEER) Program database through the Cancer Query 

Systems (CANQUES) web-based interface (NCI, 2006), available at 

http://www.seer.cancer.gov/canques/incidence.html. 

References 

ACS (American Cancer Society). 2003. Cancer facts and figures, 2003. Accessed October 19, 2005. 

<http://www.cancer.org/downloads/STT/CAFF2003PWSecured.pdf> 

Hankey, B.F., E.J. Feuer, L.X. Clegg, et al. 1999. Cancer surveillance series: interpreting trends in 

prostate cancer-part I: evidence of the effects of screening in recent prostate cancer incidence, mortality, 

and survival rates. J. Natl. Cancer Inst. 91:1017-1024. 

<http://www.jncicancerspectrum.oxfordjournals.org/cgi/reprint/jnci%3b91/12/1017.pdf> 

Edwards, K.E., M.L. Brown, P.A. Wingo, et al. 2005. Annual report to the nation on the status of cancer, 

1975-2002, featuring population-based trends in cancer treatment. J. Natl. Cancer Inst. 97(19):1407-1427. 

<http://jncicancerspectrum.oxfordjournals.org/cgi/reprint/jnci;97/19/1407.pdf> 

NCHS (National Center for Health Statistics). 2006. Deaths: final data 2003. National Vital Statistics 

Reports 54(13). April 19. <http://www.cdc.gov/nchs/data/nvsr/nvsr54/nvsr54_13.pdf> 

NCI (National Cancer Institute). 2006. Surveillance, Epidemiology, and End Results (SEER) Program 

CANQUES database. SEER registry public use, Nov 2005, Sub (1973-2003). National Cancer Institute, 

DCCPS, Surveillance Research Program. Released April 2006, based on November 2005 submission. 

Accessed September 2006. <http://www.seer.cancer.gov/canques/incidence.html> 

NCI (National Cancer Institute). n.d. Dictionary of cancer terms. Accessed October 7, 2004. 

<http://cancer.gov/dictionary/> 

NTP (National Toxicology Program). 2004. Report on carcinogens. Eleventh ed. U.S. Department of 

Health and Human Services, Public Health Service. Accessed February 2, 2005. 

<http://ntp.niehs.nih.gov/ntp/roc/toc11.html> 

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INDICATOR: Childhood Cancer Incidence 

The term “cancer” is used to characterize diseases in which abnormal cells divide without control. A 

cancerous cell loses its ability to regulate its own growth, control cell division, and communicate with 

other cells. The cellular changes caused by cancer cells are complex and occur over a period of time. This 

may be accelerated in children. The classification 

of cancers in children differs from the 

classification used for adult cancers. The 

International Classification of Childhood Cancer 

(ICCC) classifies childhood cancer based on 

tumor morphology rather than, as for adults, the 

site of the tumor. If left unchecked, cancer cells 

can invade nearby tissues and can spread through 

the bloodstream and lymphatic system to other 

parts of the body (NCI, 2004). 

The causes of childhood cancers are largely 

unknown. Only a small percentage of cases can 

be explained by a few conditions such as specific 

chromosomal/genetic abnormalities (e.g., Down 

syndrome) and ionizing radiation exposure (NCI, 

2002). Environmental exposures have long been 

suspected of increasing the risk of certain 

childhood cancers. Researchers continue to 

examine environmental influences on childhood 

cancer. 

This indicator presents incidence rates for 

childhood cancers using data collected through 

the National Cancer Institute’s Surveillance, 

Epidemiology, and End Results (SEER) Program. 

The SEER Program collects and publishes cancer 

incidence and survival data from 14 populationbased cancer registries and three supplemental 

registries covering approximately 26 percent of 

the U.S. population. 

What the Data Show 

In general, overall childhood (ages 0-19 years) 

cancer incidence for the U.S. has increased 

slightly between 1973 and 2003 (Exhibit 5-12), 

increasing over time from an age-adjusted 

incidence rate of 13.8 per 100,000 in 1973 to a 

high of 17.2 per 100,000 in 2002. A slightly 

lower rate (15.4 per 100,000) was reported in 

2003. Males generally had higher rates than 

females, although for some years the reverse was 

true. Incidence among black females and males 

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age 0-19 years was lower compared to white females and males. In 2003, black females and males age 0­

19 years had overall incidence rates of 11.8 and 10.3 per 100,000, respectively, compared to white 

females and males with rates of 14.7 and 18.2 per 100,000 (Exhibit 5-12). 

Exhibit 5-13 presents the age-adjusted incidence rates for the top five cancers among children 0-19 years 

of age between 1973 and 2003. In general, there are no clearly identifiable trends among any of the top 

five cancers over the reported time period. Leukemia continues to be the most frequently diagnosed 

cancer in children age 0-19 years. 

Indicator Limitations 

• Incidence data generated from SEER are updated annually. There may be changes in the 

numerator (e.g., revised counts of newly identified cases) or denominator (i.e., revised 

population counts) numbers that result in small changes in the overall incidence rates for the 

same year depending on when a query is run within the SEER database. For example, the 

SEER database queried in 2005 generating incidence rates for the year 2000 may provide 

different incidence rates than the database queried in 2004 for the same year (i.e., 2000). 

Data Sources 

Cancer incidence data for this indicator were obtained by querying the National Cancer Institute’s (NCI’s) 

Surveillance, Epidemiology, and End Results (SEER) Program database through the Cancer Query 

Systems (CANQUES) web-based interface (NCI, 2006), available at 

http://www.seer.cancer.gov/canques/incidence.html. 

References 

NCI (National Cancer Institute). 2006. Surveillance, Epidemiology, and End Results (SEER) Program 

CANQUES database. SEER registry public use, Nov 2005, Sub (1973-2003). National Cancer Institute, 

DCCPS, Surveillance Research Program. Released April 2006, based on November 2005 submission. 

Accessed 2006. <http://www.seer.cancer.gov/canques/incidence.html> 

NCI (National Cancer Institute). 2004. Dictionary of cancer terms. Accessed October 7, 2004. 

<http://cancer.gov/dictionary/> 

NCI (National Cancer Institute). 2002. Cancer facts: National Cancer Institute research on childhood 

cancers. Accessed February 2, 2005. <http://cis.nci.nih.gov/fact/pdfdraft/6_sites/fs6_40.pdf> 

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INDICATOR: Cardiovascular Disease Prevalence and Mortality 

The broad category of cardiovascular disease (CVD) includes any disease involving the heart and blood 

vessels. Coronary heart disease, cerebrovascular disease (commonly known as stroke), and hypertension 

are the major cardiovascular diseases (American Heart Association, 2003). In addition to being a major 

risk factor for heart disease and stroke, hypertension is a commonly diagnosed disease that can also lead 

to kidney damage and other health problems. Obesity, physical inactivity, and sodium intake are all 

important risk factors for hypertension (NIH, 2004). Since 1900, cardiovascular disease has been the 

leading cause of death in the United States every year except 1918 (American Heart Association, 2003) 

(General Mortality indicator, p. 5-13). The U.S. age-adjusted mortality rate for CVD reached a peak in 

1950 (CDC, 1999). Between 1950 and 1999, the age-adjusted mortality rate for CVD declined 60 percent. 

The major risk factors for CVD include tobacco use, high blood pressure, high blood cholesterol, 

diabetes, physical inactivity, and poor nutrition (CDC, 2004). 

Environmental factors may also play a role in CVD morbidity and mortality independent of other risk 

factors. However, susceptible populations such as the elderly and other high-risk populations may be 

most impacted. For example, chronic exposure to ambient airborne particulate matter has been shown in 

studies to be associated with increased hospitalizations and mortality among older individuals, largely due 

to cardiopulmonary and cardiovascular disease (U.S. EPA, 2004). Environmental tobacco smoke (ETS) 

may also contribute to CVD. Although the smoke to which a nonsmoker is exposed is less concentrated 

than that inhaled by smokers, research has demonstrated increased cardiovascular-related health risks 

associated with ETS (State of California, 2005). 

This indicator presents U.S. adult (age 18 and older) prevalence rates for heart disease (all types), 

coronary heart disease, stroke, and hypertension; and mortality rates for CVD as a whole as well as 

coronary heart disease (including myocardial infarction), stroke, and hypertension. CVD prevalence data 

were compiled between 1997 and 2004 from the National Center for Health Statistics (NCHS) National 

Health Interview Survey (NHIS). NHIS is the principal 

source of information on the health of the civilian noninstitutionalized population of the United States and 

since 1960 has been one of the major data collection 

programs of NCHS. CVD prevalence is based on the 

number of adults who reported that they had ever been 

told by a doctor or other health practitioner that they 

had a specified cardiovascular disease. Mortality data 

(all ages) were compiled between 1979 and 2002 using 

the National Vital Statistics System (NVSS), 

maintained by NCHS. The NVSS registers virtually all 

deaths and births nationwide with data coverage from 

1933 to 2003 and from all 50 States and the District of 

Columbia. 

What the Data Show 

CVD Prevalence 

Among adults 18 years and older, the prevalence of 

heart disease and stroke between 1997 and 2004 has 

remained essentially the same (Exhibit 5-14). In 

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contrast, the prevalence of hypertension has shown a slow increase from 191.6 cases per 1,000 in 1999 to 

220.7 cases per 1,000 in 2004. 

Gender, race, and age differences in CVD prevalence exist. The prevalence of coronary heart disease 

among males is consistently higher than females (76.6 cases per 1,000 compared with 50.9 cases per 

1,000 for women in 2004). In contrast, hypertension is more prevalent among women (228.0 cases per 

1,000 for women compared with 212.8 for men in 2004). Among the racial groups reported, American 

Indian and Alaska Natives typically had the highest prevalence of coronary heart disease between 1999 

and 2003. In 2004, however, whites had the highest prevalence of coronary heart disease (67.5 cases per 

1,000) followed by American Indian and Alaska Natives (58.6 cases per 1,000), blacks or African 

Americans (44.0 cases per 1,000), and Asians (32.2 cases per 1,000). In 2004, Asians also consistently 

had the lowest prevalence of stroke (16.7 cases per 1,000) and hypertension (132.2 cases per 1,000) 

among the racial groups reported. In addition, the Hispanic or Latino population had a consistently lower 

prevalence of the major CVD-related diseases compared with the non-Hispanic or Latino population from 

1999-2004, the period for which these data are available. For example, in 2004, prevalence in Hispanics 

or Latinos was lower than non-Hispanics or Latinos for coronary heart disease (38.9 versus 66.8 cases per 

1,000, respectively), hypertension (139.3 versus 232.3 cases per 1,000, respectively), and stroke (17.2 

versus 26.9 cases per 1,000, respectively).(Data not shown.) 

CVD Mortality 

In 1998, the national age-adjusted CVD mortality rate 

(all types) was 352.0 per 100,000 compared to a rate 

of 541.0 per 100,000 in 1980 (Exhibit 5-15). This 

decline appears to continue after 1999, with the rate 

dropping from 349.3 per 100,000 in 1999 to 317.4 per 

100,000 in 2002. Both coronary heart disease and 

stroke mortality rates have been declining in the 

United States. The age-adjusted coronary heart disease 

mortality rate ranged from 345.2 per 100,000 in 1980 

to 197.1 per 100,000 in 1998. For stroke mortality the 

age-adjusted rate ranged from 97.1 per 100,000 in 

1979 to 59.3 per 100,000 in 1998. The age-adjusted 

mortality rates for myocardial infarction ranged from 

157.9 in 1979 to 76 per 100,000 in 1998. The ageadjusted mortality rate (2000 U.S. Standard 

Population) for coronary heart disease, stroke, and 

myocardial infarction in 2002 was 170.9, 56.2, and 

62.1 per 100,000, respectively, compared to 194.6, 

61.6, and 73.2 per 100,000, respectively, in 1999. 

Death rates from hypertension remained essentially the 

same between 1999 and 2002. 

Both coronary heart disease and stroke mortality have been declining over time in the 10 EPA Regions 

(Exhibits 5-16 and 5-17). In 1979, coronary heart disease and stroke age-adjusted mortality rates (2000 

U.S. Standard Population) ranged from 285.6 (Region 10) to 401.9 (Region 2) per 100,000 and 80.3 

(Region 2) to 111.4 (Region 4) per 100,000, respectively. In 1998, coronary heart disease and stroke 

mortality rates ranged 145.6 (Region 8) to 233.2 (Region 2) per 100,000 and 43.2 (Region 2) to 68.5 per 

(Region 10) 100,000, respectively. The observed decreases in coronary heart disease and stroke mortality 

also appear to continue in the 1999-2002 period. 

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Differences exist in CVD mortality rates among gender, racial and age groups. For example, in 2002, 

those age 65 and older had the highest CVD (all types), coronary heart disease, and stroke mortality 

(2,119.4, 1,135.9, and 393.2 per 100,000, respectively) compared to younger age groups. For the same 

year, the age-adjusted CVD, coronary heart disease, and stroke mortality rates for those 45-64 years of 

age were 185.2, 108.5, and 23.8 per 100,000, respectively. Notable differences in CVD (all types) and, 

specifically, coronary heart disease mortality rates exist between males and females, but not for stroke 

mortality. Coronary heart disease mortality among males in 2002 was 220.4 per 100,000 compared to 

133.6 per 100,000 for women. In 2002, black or African American males had the highest CVD mortality 

rate at 487.5 per 100,000 compared to white males (370.7 per 100,000), black or African American 

females (363.8 per 100,000) and white females (262.8 per 100,000). (Data not shown.) 

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Indicator Limitations 

• Prevalence data reported in the NHIS are based on self-reported responses to specific 

questions pertaining to CVD-related illnesses, and are subject to the biases associated with 

self-reported data. Self-reported data may underestimate the disease prevalence being 

measured if, for whatever reason, the respondent is not fully aware of his/her condition. 

• All prevalence data are based on crude rates and are not age-adjusted, as CDC did not report 

age-adjusted data prior to 2002 in the data sources used for this indicator. Therefore, the 

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reported disease prevalence rates across time or within different race and gender subgroups 

may not reflect differences in the age distribution of the populations being compared. 

• For one or more years for which data are presented, coronary heart disease and stroke 

prevalence rates presented for Native American and Alaskan Natives have a relative standard 

error of greater than 30 percent. In addition, stroke prevalence rates for one or more years for 

which data are presented for Asians have a relative standard error of greater than 30 percent. 

As such, these rates should be used with caution as they do not meet the standard of 

reliability or precision. 

• CVD mortality rates are based on underlying cause-of-death as entered on a death certificate 

by a physician. Some individuals may have had competing causes of death. “When more than 

one cause or condition is entered by the physician, the underlying cause is determined by the 

sequence of conditions on the certificate, provisions of the ICD [International Classification 

of Diseases], and associated selection rules and modifications” (CDC, n.d.). Consequently, 

some misclassification of reported mortality might occur in individuals with competing 

causes of death, as well as the possible underreporting of CVD as the cause of death. 

• CVD mortality rates reported previously for specified years may differ because new ageadjusted rates reflect the 2000 standard census population whereas earlier age-adjusted rates 

are based on different (e.g., 1990) standard population projections. 

• For some of the reported years, if the user selects a CDC WONDER query for the United 

States with data grouped by state, or selects a WONDER query for a specific state, CDC 

WONDER reports state population figures that do not add up to the national population 

reported by CDC WONDER. This is because the two different sets of populations come from 

different U.S. Census population estimates. (For all other years, these two sets of population 

data are the same.) 

• The International Classification of Diseases 9th Revision (ICD-9) codes were used to specify 

underlying cause of death for years 1979-1998. Beginning in 1999, cause of death is specified 

with the International Classification of Diseases 10th Revision (ICD-10) codes. The two 

revisions differ substantially, and to prevent confusion about the significance of any specific 

disease code, data queries are separate. 

Data Sources 

CVD prevalence data were obtained from annual reports published by CDC’s National Center for Health 

Statistics (NCHS, 1999-2006), which summarize health statistics compiled from the center’s National 

Health Interview Survey (http://www.cdc.gov/nchs/products/pubs/pubd/series/sr10/ser10.htm). CVD 

mortality statistics were obtained from CDC’s “compressed mortality” database, accessed through CDC 

WONDER (CDC, 2006) (http://wonder.cdc.gov/mortSQL.html). EPA Regional mortality statistics were 

generated by combining and age-adjusting state-by-state totals for each EPA Region using data from 

CDC WONDER. 

References 

American Heart Association. 2003. Heart disease and stroke statistics—2004 update. Dallas, TX. 

CDC (Centers for Disease Control and Prevention). 2006. CDC Wide-ranging OnLine Data for 

Epidemiologic Research (WONDER). Compressed mortality file, underlying cause of death. 1999-2003 

(with ICD 10 codes) and 1979-1998 (with ICD 9 codes). Accessed 2006. 

<http://wonder.cdc.gov/mortSQL.html> 

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CDC (Centers for Disease Control and Prevention). 2004. The burden of chronic diseases and their risk 

factors—national and state perspectives. Accessed February 2, 2005. 

<http://www.cdc.gov/nccdphp/burdenbook2004/pdf/burden_book2004.pdf> 

CDC (Centers for Disease Control and Prevention). 1999. Decline in deaths from heart disease and stroke, 

United States, 1990-1999. Washington, DC. 

CDC (Centers for Disease Control and Prevention). n.d. CDC WONDER: Help page for compressed 

mortality file. <http://wonder.cdc.gov/wonder/help/mort.html> 

U.S. EPA. 2004. Air quality criteria for particulate matter. Volumes I (EPA/600/P-99/002aF) and II 

(EPA/600/P-99/002bF). National Center for Environmental Assessment–RTP Office, Office of Research 

and Development. 

NCHS (National Center for Health Statistics). 2006. Summary health statistics for U.S. adults: National 

Health Interview Survey, 2004. Vital Health Stat 10(228). 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_228.pdf> 

NCHS (National Center for Health Statistics). 2005. Summary health statistics for U.S. adults: National 

Health Interview Survey, 2003. Vital Health Stat 10(225). 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_225.pdf> 

NCHS (National Center for Health Statistics). 2004. Summary health statistics for U.S. adults: National 

Health Interview Survey, 2002. Vital Health Stat 10(222). 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_222.pdf> 

NCHS (National Center for Health Statistics). 2003. Summary health statistics for U.S. adults: National 

Health Interview Survey, 2001. Vital Health Stat 10(218). 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_218.pdf> 

NCHS (National Center for Health Statistics). 2002. Summary health statistics for U.S. adults: National 

Health Interview Survey, 2000. Vital Health Stat 10(215). 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_215.pdf> 

NCHS (National Center for Health Statistics). 2001. Summary health statistics for U.S. adults: National 

Health Interview Survey, 1999. Vital Health Stat 10(212). 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_212.pdf> 

NCHS (National Center for Health Statistics). 2000. Summary health statistics for U.S. adults: National 

Health Interview Survey, 1998. Vital Health Stat 10(209). 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_209.pdf> 

NCHS (National Center for Health Statistics). 1999. Summary health statistics for U.S. adults: National 

Health Interview Survey, 1997. Vital Health Stat 10(205). 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_205.pdf> 

NIH (National Institute of Health). 2004. NIH news: the increasing number of adults with high blood 

pressure. Accessed September 11, 2005. <http://www.nhlbi.nih.gov/new/press/04-08-23.htm> 

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State of California. 2005. Proposed identification of environmental tobacco smoke as a toxic air 

contaminant. Part B: health effects assessment for environmental tobacco smoke. As approved by the 

Scientific Review Panel on June 24, 2005. California Environmental Protection Agency, Office of 

Environmental Health Hazard Assessment. <http://www.arb.ca.gov/regact/ets2006/ets2006.htm> 

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Chronic obstructive pulmonary disease (COPD), sometimes referred to as chronic lung disease, is a 

disease that damages lung tissue or restricts airflow through the bronchioles and bronchi (NHLBI, 2003). 

Chronic bronchitis and emphysema are the most frequently occurring COPDs. Smoking is the most 

common cause of COPD, including cigarette, pipe, and cigars (NHLBI, 2003). Other factors involved in 

the development and progression of COPD include, asthma, heavy exposure to air pollutants in the 

ambient air and workplace environment, genetic factors, and respiratory infections (CDC, 2005; 

American Lung Association, 2004). 

Environmental tobacco smoke (ETS) may also increase the risk of developing COPD. The effect of 

chronic ETS exposure alone on pulmonary function in otherwise healthy adults is likely to be small. 

However, in combination with other exposures (e.g., prior smoking history, exposure to occupational 

irritants or ambient air pollutants), ETS exposure could contribute to chronic respiratory impairment. 

Children are especially sensitive to the respiratory effects of ETS exposure (State of California, 2005). 

This indicator presents U.S. adult (age 18 and older) prevalence rates for chronic bronchitis and 

emphysema and mortality rates for COPD as a whole and for chronic bronchitis and emphysema. COPD 

prevalence data were compiled from 1997 to 2004 from the National Center for Health Statistic’s (NCHS) 

National Health Interview Survey (NHIS). NHIS is the principal source of information on the health of 

the civilian non-institutionalized population of the United States and since 1960 has been one of the major 

data collection programs of NCHS. COPD prevalence is based on the number of adults who reported that 

they had ever been told by a doctor or other health practitioner that they had a specified chronic bronchitis 

or emphysema. Mortality data (all ages) were compiled between 1979 and 2002 using the National Vital 

Statistics System (NVSS), maintained by NCHS. The NVSS registers virtually all deaths and births 

nationwide with data coverage from 1933 to 2003 and from all 50 States and the District of Columbia. 

What the Data Show

COPD Prevalence 

Exhibit 5-18 presents the prevalence of chronic bronchitis (Panel A) and emphysema (Panel B) from 1999 

to 2004. The reported total prevalence of chronic bronchitis in U.S. adults over the age of 18 years ranged 

from a low of 40 (2003) to a high of 55 (2001) cases per 1,000. The reported total prevalence of 

INDICATOR: Chronic Obstructive Pulmonary Disease Prevalence and Mortality 
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emphysema in U.S. adults during the same time period ranged from 14 (1999) to 17 (1997) cases per 

1,000. A small increase in prevalence of chronic bronchitis can be seen from 1999 to 2001, with an 

overall decline from 2002 to 2004. The reported total prevalence of emphysema in U.S. adults during the 

same time period ranged from 14 (1999) to 17 (2004) cases per 1,000. No notable change in the 

prevalence for emphysema was evident during this time period. Exhibit 5-18 also displays chronic 

bronchitis and emphysema prevalence by race. Chronic bronchitis prevalence was higher among white 

(designated as “white only”) adults compared to black (“black or African American only”) adults during 

1999 (46 versus 36 cases per 1,000, respectively) and 2000 (49 versus 40 cases per 1,000, respectively). 

The same racial difference in prevalence exists for emphysema, but the difference remains consistent 

throughout the entire time period. 

In addition, the Hispanic or Latino population had a consistently lower prevalence of chronic bronchitis 

and emphysema diseases compared with the non-Hispanic or Latino population from 1999-2004, the 

period for which these data are available. For example, in 2004, prevalence in Hispanics or Latinos was 

lower than non-Hispanics or Latinos for chronic bronchitis (44 compared to 25 cases per 1,000, 

respectively) and emphysema (18 compared to 6 cases per 1,000, respectively). (Data not shown.) 

Gender differences are also seen. In 2004, females had about twice the reported prevalence of chronic 

bronchitis than males (56 versus 27 cases per 1,000 respectively), a consistently observed difference 

between 1997 and 2004. Unlike with chronic bronchitis, the prevalence rates for emphysema have been 

consistently higher in males than in females. (Data not shown). 

COPD Mortality 

In 2003, COPD continues to be the fourth leading cause 

of mortality accounting for 126,382 deaths (General 

Mortality indicator, p.5-13). The age-adjusted mortality 

rate for COPD as a whole has increased over time, with 

rates ranging from 25.5 per 100,000 in 1979 to 41.8 per 

100,000 in 1998. From 1999-2002,rates held steadier, 

ranging from 45.4 per 100,000 in 1999 to 43.5 per 

100,000 in 2002. Mortality rates for emphysema (1.9 

and 1.1 per 100,000 1979 and 1998, respectively and 

0.4 and 0.3 per 100,000 for 1999 and 2003, 

respectively) and chronic bronchitis (6.9 and 6.5 per 

100,000 1979 and 1998, respectively and 6.5 and 5.1 

per 100,000 1999 and 2003, respectively) have not 

changed substantially during this same time period 

(data not shown). 

Exhibit 5-19 presents the overall COPD mortality rates 

in the U.S. and the 10 EPA Regions for the time 

periods 1979-1998 and 1999-2002. The age-adjusted 

COPD mortality rates have been increasing in each of 

the 10 Regions from 1979 to 1998. The rates ranged 

from 22.2 (Region 2) to 31.2 (Region 8) per 100,000 in 

1979 and 33.5 (Region 2) to 47.9 (Region 8) per 

100,000 in 1998. 

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COPD age-adjusted mortality rates have slowly been declining for males over time with rates of 58.7, 

55.8, 54.0, and 53.5 per 100,000 in 1999, 2000, 2001, and 2002, respectively. For females, the rates are 

lower than males and have been stable over the above four years (37.7, 37.4, 37.6, and 37.4 per 100,000 

in 1999, 2000, 2001, and 2002, respectively). The COPD age-adjusted mortality rate is higher among 

whites (45.4 per 100,000 in 2002) compared to blacks or African Americans (31.2 per 100,000 in 2002). 

COPD mortality rate increases with age with the 2002 rate of 0.4, 1.2, 21.9, and 300.6 per 100,000 for 

those age 0-14 years, 15-44 years, 45-64 years and 65 years and older, respectively. 

Indicator Limitations 

• Prevalence data presented in the NHIS are based on self-reported responses to specific 

questions pertaining to COPD-related illnesses, and are subject to the biases associated with 

self-reported data. Self-reported data may underestimate the disease prevalence being 

measured if, for whatever reason, the respondent is not fully aware of his/her condition. 

• All prevalence data are based on crude rates and are not age-adjusted, as CDC did not report 

age-adjusted data prior to 2002 in the data sources used for this indicator. Therefore, the 

reported disease prevalence rates across time or within different race and gender subgroups 

may not reflect differences in the age distribution of the populations being compared. 

• COPD mortality rates are based on underlying cause-of-death as entered on a death certificate 

by a physician. Some individuals may have had competing causes of death. “When more than 

one cause or condition is entered by the physician, the underlying cause is determined by the 

sequence of conditions on the certificate, provisions of the ICD [International Classification 

of Diseases], and associated selection rules and modifications” (CDC, n.d.). Consequently, 

some misclassification of reported mortality might occur in individuals with competing 

causes of death, as well as the possible underreporting of COPD as the cause of death. 

• For some of the reported years, if the user selects a CDC WONDER query for the United 

States with data grouped by state, or selects a WONDER query for a specific state, CDC 

WONDER reports state population figures that do not add up to the national population 

reported by CDC WONDER. This is because the two different sets of populations come from 

different U.S. Census population estimates. (For all other years, these two sets of population 

data are the same.) 

• The International Classification of Diseases 9th Revision (ICD-9) codes were used to specify 

underlying cause of death for years 1979-1998. Beginning in 1999, cause of death is specified 

with the International Classification of Diseases 10th Revision (ICD-10) codes. The two 

revisions differ substantially, and to prevent confusion about the significance of any specific 

disease code, data queries are separate. 

Data Sources 

COPD prevalence data were obtained from annual reports published by CDC’s National Center for Health 

Statistics (NCHS, 1997-2006), which summarize health statistics compiled from the center’s National 

Health Interview Survey (http://www.cdc.gov/nchs/products/pubs/pubd/series/sr10/ser10.htm). Mortality 

statistics were obtained from CDC’s “compressed mortality” database, accessed through CDC WONDER 

(CDC, 2006) (http://wonder.cdc.gov/mortSQL.html). EPA Regional mortality statistics were generated by 

combining and age-adjusting state-by-state totals for each EPA Region using data from CDC WONDER. 

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References 

American Lung Association. 2004. Chronic obstructive pulmonary disease (COPD) fact sheet. Accessed 

February 7, 2005. <http://www.lungusa.org/site/pp.asp?c=dvLUK9O0E&b=35020> 

CDC (Centers for Disease Control and Prevention). 2006. CDC Wide-ranging OnLine Data for 

Epidemiologic Research (WONDER). Compressed mortality file, underlying cause of death. 1999-2003 

(with ICD 10 codes) and 1979-1998 (with ICD 9 codes). Accessed 2006. 

<http://wonder.cdc.gov/mortSQL.html> 

CDC (Centers for Disease Control and Prevention). 2005. Facts about chronic obstructive pulmonary 

disease (COPD). Accessed February 7, 2005. <http://www.cdc.gov/nceh/airpollution/copd/copdfaq.htm> 

CDC (Centers for Disease Control and Prevention). n.d. CDC WONDER: Help page for compressed 

mortality file. <http://wonder.cdc.gov/wonder/help/mort.html> 

NCHS (National Center for Health Statistics). 2006. Summary health statistics for U.S. adults: National 

Health Interview Survey, 2004. Vital Health Stat 10(228). 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_228.pdf> 

NCHS (National Center for Health Statistics). 2005. Summary health statistics for U.S. adults: National 

Health Interview Survey, 2003. Vital Health Stat 10(225). 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_225.pdf> 

NCHS (National Center for Health Statistics). 2004. Summary health statistics for U.S. adults: National 

Health Interview Survey, 2002. Vital Health Stat 10(222). 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_222.pdf> 

NCHS (National Center for Health Statistics). 2003. Summary health statistics for U.S. adults: National 

Health Interview Survey, 2001. Vital Health Stat 10(218). 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_218.pdf> 

NCHS (National Center for Health Statistics). 2002. Summary health statistics for U.S. adults: National 

Health Interview Survey, 2000. Vital Health Stat 10(215). 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_215.pdf> 

NCHS (National Center for Health Statistics). 2001. Summary health statistics for U.S. adults: National 

Health Interview Survey, 1999. Vital Health Stat 10(212). 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_212.pdf> 

NCHS (National Center for Health Statistics). 2000. Summary health statistics for U.S. adults: National 

Health Interview Survey, 1998. Vital Health Stat 10(209). 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_209.pdf> 

NCHS (National Center for Health Statistics). 1999. Summary health statistics for U.S. adults: National 

Health Interview Survey, 1997. Vital Health Stat 10(205). 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_205.pdf> 

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NHLBI (National Heart, Lung, and Blood Institute). 2003. Chronic obstructive pulmonary disease fact 

sheet. NIH publication No. 03-5229. Bethesda, MD: U.S. Department of Health and Human Services. 

Accessed October 29, 2004. <http://www.nhlbi.nih.gov/health/public/lung/other/copd_fact.pdf> 

State of California. 2005. Proposed identification of environmental tobacco smoke as a toxic air 

contaminant. Part B: health effects assessment for environmental tobacco smoke. As approved by the 

Scientific Review Panel on June 24, 2005. California Environmental Protection Agency., Office of 

Environmental Health Hazard Assessment. <http://www.arb.ca.gov/regact/ets2006/ets2006.htm> 

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1 INDICATOR: Asthma Prevalence 

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Asthma is a chronic respiratory disease characterized by inflammation of the airways and lungs. During 

an asthma attack, the airways that carry air to the lungs are constricted, and as a result, less air is able to 

flow in and out of the lungs (NHLBI, 2004). Asthma attacks can cause a multitude of symptoms ranging 

in severity from mild to life-threatening. These symptoms include wheezing, breathlessness, chest 

tightness, and coughing (NHLBI, 2004). Currently, there is no cure for asthma; however, people who 

have asthma can still lead quality, productive lives if they control their asthma. Taking medication and 

avoiding contact with environmental “triggers” can control asthma. 

A family history of asthma contributes to susceptibility, but mostly, it is unknown what causes the 

development of asthma. Environmental exposures such as environmental tobacco smoke, dust mites, 

cockroach allergen, outdoor air pollution, pets, and mold are considered important triggers of an asthma 

attack (CDC, 2003, 2004). 

Statistics for lifetime diagnosis prevalence, current asthma prevalence, and asthma attack prevalence are 

based on national estimates from the National Health Interview Survey (NHIS). NHIS is the principal 

source of information on the health of the civilian non-institutionalized population of the United States 

and since 1960 has been one of the major data collection programs of NCHS. For this indicator, lifetime 

asthma diagnosis is defined as the number of adults/children who reported that they had ever been told by 

a doctor or other health practitioner that they had asthma. To determine current asthma prevalence, 

adults/children who had been told that they had asthma were asked whether they still have asthma. 

Asthma attack prevalence is based on the number of adults/children who reported an asthma episode or 

attack in the past 12 months. 

What the Data Show

From 2002 to 2004,approximately 7 percent of the U.S. population reported that they currently have 

asthma (NCHS, 2006a). Reported asthma rates are highest in the child and adolescent population. 

Adult Asthma

In adults, asthma prevalence rates (i.e., lifetime diagnosis) generally increased from 1997 to 2001 (Exhibit 

5-20, panel B). The prevalence rates range from a low of 85 cases per 1,000 in 1999 to a high of 109 

cases per 1,000 in 2001. Asthma was consistently higher among adult females than males, with a range of 

98 (1999) and 123 (2001) cases per 1,000 in females and 71 (1999) and 94 (2001) cases per 1,000 in 

males. The asthma prevalence rate also consistently decreases in older populations. In 2004, the asthma 

prevalence rate was 99 (ages 18-44 years), 100 (ages 45-64), 103 (ages 65-74 years), and 73 (ages 75+ 

years) cases per 1,000 (data not shown). 

Exhibit 5-21 compares asthma rates across racial and ethnic groups for the 2002-2004 time period. As 

shown in Panel A, the lifetime asthma diagnosis in adults was highest among American Indian/Alaska 

Natives (142 cases per 1,000), followed by black or African Americans (112 cases per 1,000), whites (100 

cases per 1,000), and lowest among Asians (72 cases per 1,000). This same general pattern is seen for 

current asthma and asthma attack prevalence. Panel B shows that Hispanics or Latinos had lower rates 

across all three asthma prevalence categories compared to non-Hispanic whites and non-Hispanic blacks. 

For lifetime asthma diagnosis, 76 cases per 1,000 were reported in Hispanics or Latinos, 105 cases per 

1,000 in non-Hispanic whites, and 111 cases per 1,000 in non-Hispanic blacks. 
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Childhood Asthma 

In 2004, approximately nine million children within 

the United States (age 0-17 years) were reported as 

ever having a diagnosis of asthma and nearly 4 million 

reported experiencing an asthma episode or attack 

during the previous 12 months. As shown in Exhibit 5­

22, asthma prevalence rates increased approximately 4 

percent per year between 1980 and 1996. Rates in 

subsequent years (1997-2004), reported in three 

categories, show no sharp upward or downward 

change. Lifetime asthma diagnosis rates range from a 

low of 108 cases per 1,000 in 1999 to a high of 127 

cases per 1,000 in 2001. Since tracking began in 2001, 

current asthma prevalence has ranged from 

approximately 83.4 cases per 1,000 (2002) to 87 cases 

per 1,000 (2001). Asthma attack prevalence rates show 

a slight increase from 52.7 per 1,000 in 1999 to 57.7 

cases per 1,000 in 2002; however, a slight decrease 

(54.6 and 54.4 cases per 1,000) was observed for 2003 

and 2004. Male children consistently had higher rates 

of asthma prevalence than female children (Exhibit 5­

20, panel A). 

The overall pattern of asthma prevalence across races 

in children during 2002-2004 is similar to that seen in 

adults (Exhibit 5-21). One notable exception is that 

asthma prevalence in black or African American 

children was higher than asthma prevalence in 

American Indian/Alaska Native children, the reverse of what was observed in the adult population. For 

example, reported lifetime asthma diagnosis was highest among black or African American children (173 

cases per 1,000), followed by American Indian/Alaska Natives (153 cases per 1,000), whites (112 cases 

per 1,000), and lowest among Asians (78 cases per 1,000). Hispanic children had a lower asthma 

prevalence rates for all three categories compared to non-Hispanic white and non-Hispanic black children. 

Indicator Limitations 

• The National Health Interview Survey (NHIS) questionnaire underwent major changes in 

1997, and the data presented focus on surveys conducted from 1997 to the most currently 

available release (2004). The redesigned NHIS is different in content, format, and mode of 

data collection from earlier versions of the survey. Due to changes in methodology, 

comparisons between 1997–2004 NHIS estimates and pre-1997 NHIS data may not be valid. 

• Prevalence data reported in the NHIS are based on self-reported responses to specific 

questions pertaining to airway-related illnesses, and are subject to the biases associated with 

self-reported data. Self-reported data may underestimate the disease prevalence being 

measured if, for whatever reason, the respondent is not fully aware of his/her condition. 

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Asthma prevalence data were obtained from annual reports published by CDC’s National Center for 

Health Statistics (NCHS, 1999; 2000; 2001; 2002a,b; 2003a,b,c,d; 2004a,b; 2005a,b; 2006a,b,c), which 

summarize health statistics compiled from the center’s National Health Interview Survey (NHIS) 

(http://www.cdc.gov/nchs/products/pubs/pubd/series/sr10/ser10.htm). Race and ethnicity data were 

obtained from CDC’s online “Health Data for All Ages” (NCHS, 2006a) 

(http://www.cdc.gov/nchs/health_data_for_all_ages.htm). The data used by CDC to create the asthma 

tables in Health Data for All Ages originate from the NHIS. The pre-1997 data also originate from NHIS, 

as compiled by NCHS in Akinbami and Schoendorf (2002). 

References 

Akinbami and Schoendorf. 2002. Trends in childhood asthma: prevalence, health care utilization, and 

mortality. Pediatrics. 110:2 (Pt 1):315-22 

CDC (Centers for Disease Control and Prevention). 2003. Basic facts about asthma. Accessed February 3, 

2005. <http://www.cdc.gov/asthma/faqs.htm> 

CDC (Center for Disease Control and Prevention). 2004. Asthma’s impact on children and adolescents. 

Accessed November 22, 2004. <http://www.cdc.gov/asthma/children.htm> 

NCHS (National Center for Health Statistics). 2006a. Health data for all ages. Accessed 2006. 

<http://www.cdc.gov/nchs/health_data_for_all_ages.htm> 

NCHS (National Center for Health Statistics). 2006b. Summary health statistics for U.S. adults: National 

Health Interview Survey, 2004. Vital Health Stat 10(228). See Table 3 and Table 4. 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_228.pdf> 

NCHS (National Center for Health Statistics). 2006c. Summary health statistics for U.S. children: 

National Health Interview Survey, 2004. Vital Health Stat 10(227). See Table 1 and Appendix III. 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_227.pdf> 

NCHS (National Center for Health Statistics). 2005a. Summary health statistics for U.S. adults: National 

Health Interview Survey, 2003. Vital Health Stat 10(225). See Table 3 and Table 4. 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_225.pdf> 

NCHS (National Center for Health Statistics). 2005b. Summary health statistics for U.S. children: 

National Health Interview Survey, 2003. Vital Health Stat 10(223). See Table 1 and Appendix III. 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_223.pdf> 

NCHS (National Center for Health Statistics). 2004a. Summary health statistics for U.S. adults: National 

Health Interview Survey, 2002. Vital Health Stat 10(222). See Table 3 and Table 4. 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_222.pdf> 

NCHS (National Center for Health Statistics). 2004b. Summary health statistics for U.S. children: 

National Health Interview Survey, 2002. Vital Health Stat 10(221). See Table 1 and Appendix III. 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_221.pdf> 

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NCHS (National Center for Health Statistics). 2003a. Summary health statistics for U.S. adults: National 

Health Interview Survey, 2001. Vital Health Stat 10(218). See Table 3 and Table 4. 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_218.pdf> 

NCHS (National Center for Health Statistics). 2003b. Summary health statistics for U.S. children: 

National Health Interview Survey, 2001. Vital Health Stat 10(216). See Table 1 and Appendix III. 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_216.pdf> 

NCHS (National Center for Health Statistics). 2003c. Summary health statistics for U.S. children: 

National Health Interview Survey, 2000. Vital Health Stat 10(213). See Table 1 and Appendix III. 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_213.pdf> 

NCHS (National Center for Health Statistics). 2003d. Summary health statistics for U.S. children: 

National Health Interview Survey, 1999. Vital Health Stat 10(210). See Table 1 and Appendix III. 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_210.pdf> 

NCHS (National Center for Health Statistics). 2002a. Summary health statistics for U.S. adults: National 

Health Interview Survey, 2000. Vital Health Stat 10(215). See Table 3 and Table 4. 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_215.pdf> 

NCHS (National Center for Health Statistics). 2002b. Summary health statistics for U.S. children: 

National Health Interview Survey, 1998. Vital Health Stat 10(208). See Table 1 and Appendix III. 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_208.pdf> 

NCHS (National Center for Health Statistics). 2002c. Summary health statistics for U.S. children: 

National Health Interview Survey, 1997. Vital Health Stat 10(203). See Table 1 and Appendix III. 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_203.pdf> 

NCHS (National Center for Health Statistics). 2001. Summary health statistics for U.S. adults: National 

Health Interview Survey, 1999. Vital Health Stat 10(212). See Table 3 and Table 4. 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_212.pdf> 

NCHS (National Center for Health Statistics). 2000. Summary health statistics for U.S. adults: National 

Health Interview Survey, 1998. Vital Health Stat 10(209). See Table 3 and Table 4. 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_209.pdf> 

NCHS (National Center for Health Statistics). 1999. Summary health statistics for U.S. adults: National 

Health Interview Survey, 1997. Vital Health Stat 10(205). See Table 3 and Table 4. 

<http://www.cdc.gov/nchs/data/series/sr_10/sr10_205.pdf> 

NHLBI (National Heart, Lung, and Blood Institute). 2004. Diseases and conditions index. Accessed 

November 12, 2004. <http://www.nhlbi.nih.gov/health/dci/Diseases/Asthma/Asthma_WhatIs.html> 

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INDICATOR: Infectious Diseases Associated with Environmental Exposures or 

Conditions

Infectious diseases are human illnesses caused by viruses, bacteria, parasites, fungi and other microbes. 

They may be spread by direct contact with an infected person or animal, by ingesting contaminated food 

or water, by insects like mosquitos or ticks (disease vectors), or by contact with contaminated 

surroundings like animal droppings or contaminated air. Demographic and environmental factors such as 

population growth, increased urbanization, and alteration of habitats of disease-carrying insects and 

animals (e.g., irrigation, deforestation) may promote the spread of infectious diseases (CDC, 1998a). The 

three broad infectious disease categories included here are those whose appearance and spread may be 

influenced to some extent by environmental conditions and change. They include gastrointestinal (GI) 

disease, arthropod-borne disease, and legionellosis. 

Gastrointestinal (GI) Diseases 

Eight notifiable GI diseases caused by microorganisms are discussed below including: cholera, 

cryptosporidiosis, Escherichia coli (E. Coli) O157:H7, giardiasis, Hepatitis A, salmonellosis, shigellosis, 

and typhoid fever. The major environmental source of gastrointestinal illness is water or food that is 

contaminated with pathogenic microorganisms. The primary means of transmission for these eight 

diseases is through ingestion of contaminated food/water or through contact and accidental ingestion of 

fecal matter (CDC, 2005a). 

Arthropod-borne Diseases 

Three arthropod-borne diseases are included: Lyme disease (transmission of Borrelia burgdorferi by 

ticks), Rocky Mountain spotted fever (transmission of Rickettsia rickettsii by ticks), and West Nile virus 

(transmitted by mosquitoes). Certain ticks and mosquitoes (arthropods) can carry bacteria and viruses that 

cause disease in humans. The arthropods acquire the bacteria or viruses when they bite an infected 

mammal or bird. Some studies indicate that spread of vector-borne disease may be influenced by land use 

and/or other environmental change (CDC, 2004). In recent years, both Lyme disease and West Nile virus 

have spread across the United States (CDC, 1993, 2000, 2004). Surveillance for Lyme disease was 

initiated by the Centers for Disease Control (CDC) in 1982 (CDC, 1993). 

Legionellosis

Legionellosis or Legionnaires’ disease is a serious and sometimes fatal form of pneumonia. It is caused 

by legionella bacteria, which are found naturally in the environment and thrive in warm water and warm 

damp places. They are commonly found in lakes, rivers, creeks, hot springs and other bodies of water. 

This bacterium has been associated with outbreaks in the U.S. linked to poorly maintained artificial water 

systems (e.g., air conditioning and industrial cooling systems) and air ventilation systems. Infection 

results from inhalation of contaminated water sprays or mists (CDC, 2003a). 

This indicator reflects occurrence of the aforementioned notifiable diseases as reported by health 

departments to the National Notifiable Diseases Surveillance System. A notifiable disease is one for 

which regular, frequent, and timely information regarding individual cases is considered necessary for the 

prevention and control of the disease (CDC, 2005b). Data are collected by all 50 states, five territories, 

New York City, and the District of Columbia, based on a list of recommended Nationally Notifiable 

Infectious Diseases, and compiled nationally. The temporal coverage of the data varies by disease. 
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What the Data Show 

Gastrointestinal Diseases 

Exhibits 5-23 and 5-24 present the number of reported cases for each of the eight notifiable GI diseases 

from 1995-2004. In comparison to the other GI diseases, the number of newly identified cholera cases 

reported each year is low. From 1995 to 2004, just 73 laboratory-confirmed cases of cholera were 

reported to CDC with only five cases being reported in 2004, the most current reporting year. Of these 73 

total cases, 48 (66 percent) were acquired outside the United States. The number of newly identified cases 

of typhoid fever was relatively stable from 1995 to 2004 ranging between a low of 321cases in 2002 and a 

high of 396 cases in 1996. In 2004, 322 cases of typhoid fever were reported. Hepatitis A has continued to 

decline, with 31,582 cases reported in 1995 compared to 5,683 cases in 2004. No notable changes in the 

number of cases were revealed for cryptosporidiosis, E. Coli O157:H7, giardiasis (only 3 years of 

reporting data available), salmonellosis, and shigellosis, but under-reporting has probably occurred 

because of milder cases not being diagnosed or reported. 

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Arthopod-borne Diseases 

Exhibit 5-25 presents the number of reported cases for three arthropod-borne diseases. Lyme disease is 

the most commonly reported arthropod-borne disease in the United States with 19,804 cases reported in 

2003, a continued decrease from the record number reported in 2002 (23,763 cases). CDC began 

surveillance of Rocky Mountain spotted fever in 1970. The number of new cases of Rocky Mountain 

spotted fever reported from 1995 to 2004 has fluctuated considerably, ranging between a low of 365 cases 

in 1998 and a high of 1,713 cases in 2004. Reported cases increased slightly in 2004 (1,713 cases) 

compared to 2003 (1,091 cases). Cases of West Nile virus were first documented in the United States in 

1999. A total of 80 cases were reported in 1999 (62 cases) and 2000 (18 cases) (data not shown). West 

Nile virus became nationally reportable in 2002, and the number of reported cases rose from 2,840 in 

2002 to 2,866 in 2003. However, in 2004, the number of reported cases decreased to 1,142. 

Legionellosis 

Exhibit 5-26 presents the number of reported 

cases of legionellosis within the U.S. 

population from 1995 to 2004. Through this 

period, the number of new cases of 

legionellosis was relatively stable, ranging 

from a low of 1,108 cases in 1999 to 1,355 

cases in 1998. However, in 2003, the number 

of new cases reported increased to 2,232, 

decreasing in 2004 to 2,093. 

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Indicator Limitations 

• State health departments report cases of notifiable diseases to CDC and policies for reporting 

can vary by disease or reporting jurisdiction. 

• Disease reporting likely underestimates the actual number of cases for a given time period 

because reporting nationally notifiable diseases to CDC is voluntary. Additionally, the 

completeness of reporting likely varies by disease. The degree of completeness of data 

reporting is influenced by many factors such as the diagnostic facilities available, the control 

measures in effect, public awareness of a specific disease, and the interests, resources, and 

priorities of state and local officials responsible for disease control and public health 

surveillance (CDC, 2006). 

• Factors such as changes in case definitions for public health surveillance, introduction of new 

diagnostic tests, or discovery of new disease entities can cause changes in disease reporting 

that are independent of the true incidence of disease (CDC, 2004). 

• For West Nile Virus, only confirmed “neuroinvasive” cases are reported, the most severe 

form of the condition. West Nile virus may also include West Nile fever, which refers to 

typically less severe cases with no evidence of neuroinvasion. West Nile fever is not currently 

on the list of nationally notifiable diseases, and therefore it is optional whether or not state 

health departments report these cases to CDC (CDC, 2005c). 

Data Sources 

The data for this indicator were obtained from CDC annual reports that summarize data on nationally 

notifiable infectious diseases reported to CDC by state health agencies across the country (CDC, 1996, 

1997, 1998b, 1999, 2001, 2002, 2003b, 2004, 2005b, 2006). Data are collected and compiled from reports 

sent by state health departments to the National Notifiable Diseases Surveillance System (NNDSS), 

which is operated by CDC. NNDSS is neither a single surveillance system nor a method of reporting. 

Certain NNDSS data are reported to CDC through separate surveillance information systems and through 

different reporting mechanisms; however, these data are aggregated and compiled for publication 

purposes (CDC, 2006). 

References 

CDC (Centers for Disease Control and Prevention). 2006. Summary of notifiable diseases—United 

States, 2004. MMWR 53(53). <http://www.cdc.gov/mmwr/PDF/wk/mm5353.pdf> See Table 1. 

CDC (Centers for Disease Control and Prevention). 2005a. Foodborne illness—frequently asked 

questions. Accessed April 11, 2005. 

<http://www.cdc.gov/ncidod/dbmd/diseaseinfo/foodborneinfections_g.htm#howdiagnosed> 

CDC (Centers for Disease Control and Prevention). 2005b. Summary of notifiable diseases—United 

States, 2003. MMWR 52(54). <http://www.cdc.gov/mmwr/PDF/wk/mm5254.pdf> See Table 1. 

CDC (Centers for Disease Control and Prevention). 2005c. West Nile virus statistics, surveillance, and 

control: 2005 West Nile virus activity in the United States. Accessed October 16, 2005. 

<http://www.cdc.gov/ncidod/dvbid/westnile/surv&controlCaseCount05_detailed.htm> 

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CDC (Centers for Disease Control and Prevention). 2004. Summary of notifiable diseases—United 

States, 2002. MMWR 51(53). <http://www.cdc.gov/mmwr/PDF/wk/mm5153.pdf> See Table 1. 

CDC (Centers for Disease Control and Prevention). 2003a. Legionnaires’ disease fact sheet. Accessed 

October 20, 2005. <http://www.air-care.com.sg/legionella-factsheet.html> 

CDC (Centers for Disease Control and Prevention). 2003b. Summary of notifiable diseases—United 

States, 2001. MMWR 50(53). <http://www.cdc.gov/mmwr/PDF/wk/mm5053.pdf> See Table 1. 

CDC (Centers for Disease Control and Prevention). 2002. Summary of notifiable diseases—United 

States, 2000. MMWR 49(53). <http://www.cdc.gov/mmwr/PDF/wk/mm4953.pdf> See Table 1. 

CDC (Centers for Disease Control and Prevention). 2001. Summary of notifiable diseases—United 

States, 1999. MMWR 48(53). <http://www.cdc.gov/mmwr/PDF/wk/mm4853.pdf> See Table 1. 

CDC (Centers for Disease Control and Prevention). 2000. Update: West Nile virus activity—eastern 

United States, 2000. MMWR 49(46):1044-1047. 

<http://www.cdc.gov/mmwr/preview/mmwrhtml/mm4946a2.htm> 

CDC (Centers for Disease Control and Prevention). 1999. Summary of notifiable diseases—United 

States, 1998. MMWR 47(53). <http://www.cdc.gov/mmwr/PDF/wk/mm4753.pdf> See Table 1. 

CDC (Centers for Disease Control and Prevention). 1998a. Preventing emerging infectious diseases. A 

strategy for the 21st century. <http://www.cdc.gov/ncidod/emergplan/plan98.pdf> 

CDC (Centers for Disease Control and Prevention). 1998b. Summary of notifiable diseases—United 

States, 1997. MMWR 46(54). <http://www.cdc.gov/mmwr/PDF/wk/mm4654.pdf> See Table 1. 

CDC (Centers for Disease Control and Prevention). 1997. Summary of notifiable diseases—United 

States, 1996. MMWR 45(53). <http://www.cdc.gov/mmwr/PDF/wk/mm4553.pdf> See Table 1. 

CDC (Centers for Disease Control and Prevention). 1996. Summary of notifiable diseases—United 

States, 1995. MMWR 44(53). <http://www.cdc.gov/mmwr/PDF/wk/mm4453.pdf> See Table 1. 

CDC (Centers for Disease Control and Prevention). 1993. Lyme disease—United States, 1991-1992. 

MMWR 42(18):345-348. <http://www.cdc.gov/mmwr/preview/mmwrhtml/00020506.htm> 

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INDICATOR: Birth Defects Rates and Mortality 

Congenital anomalies, or birth defects, are structural defects that are present in the fetus at birth. 

Although birth defects are the leading cause of infant mortality (deaths occurring to those <1 year of age) 

in the United States, the cause is unknown for approximately 70 percent of all cases (Infant Mortality 

indicator, p. 5-19) (CDC, 2005). Many different factors are associated with the development of birth 

defects such as genetic and/or chromosomal aberrations, exposure to viruses or bacteria, uncontrolled 

diabetes, cigarette smoke, use of drugs and alcohol during pregnancy, and prenatal exposure to chemicals 

in the workplace or pollutants in the environment. All of these factors can change normal infant growth or 

development resulting in different types of birth defects (NICHD, 2005). 

This indicator presents birth defects rates at birth and mortality among infants in the United States as 

recorded in the National Vital Statistics System (NVSS), which registers virtually all births and deaths 

nationwide. Data collection began in 1933 and is available through 2003 (rates at birth) and 2002 

(mortality). Birth defects data are collected on death certificates from all 50 States and the District of 

Columbia and recorded on birth certificates for 49 States and the District of Columbia. Reported race and 

ethnicity data are based on the race and ethnicity of the mother. 

What the Data Show

Exhibit 5-27 presents the rate of live births with identified specific congenital anomalies (i.e., birth 

defects) between 1999 and 2003. The most frequently occurring types of birth defects were various 

musculoskeletal/integumental anomalies, circulatory/respiratory system anomalies, and heart 

malformations. In 2003, heart malformations occurred at a rate of 128.9 per 100,000 live births, which 

was highest among the specific anomalies listed (i.e., categories that do not include “other”). The overall 

rate of birth defects (i.e., all birth defects combined) between 1999 and 2003 has been relatively stable 

through the period, with the exception of a noticeable decline in 2003. Blacks have a consistently higher 

rate of birth defects than whites during this time period, with a rate of 127.3 (blacks) compared with 101.6 

(whites) birth defects per 100,000 live births in 2003 (data not shown). 

Birth defects continue to be the leading cause of infant mortality, accounting for 5,621 (20.1 percent) of 

the 28,025 infant deaths in 2003 (Exhibit 5-7, Infant Mortality indicator, p. 5-19). Between 1979 and 

1998 a decline in the national birth defects mortality rate has been observed ranging from 255.4 per 

100,000 live births in 1979 to 157.6 per 100,000 in 1998. From 1999 to 2003 the birth defects mortality 

rates were 144.2 (1999), 150.9 (2000), 136.7 (2001), 139.4 (2002), and 140.4 (2003) per 100,000. 

Birth defect mortality was consistently higher among black compared to white infants. In 2003, for 

example, mortality attributed to birth defects among black male and female infants was 170.7 and 143.8 

per 100,000 infants, respectively, and among white male and female infants was 143.2 and 131.8 per 

100,000 infants, respectively. (Data not shown.) 
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Indicator Limitations 

• Because some birth defects are not recognized immediately, they are often underreported on 

both birth and death certificates (Friis and Sellers, 1999). Many anomalies are hard to detect 

at birth, which limits early ascertainment and complete reporting. The most serious and/or 

apparent anomalies are more likely to be identified and reported prior to hospital discharge 

(Honein et al., 2001). 

• The lack of uniform reporting on birth certificates introduces additional uncertainty. For 

example, race information may be missing or incomplete. Also, beginning in 2003, two states 

began using a revised “standard certificate of live birth;” therefore, a subset of anomaly data 

was excluded because of the lack of comparability with other data sets (NCHS, 2005). 

• The congenital anomalies reported on birth certificates are rare events. Since a small change 

in the number of anomalies reported can result in a relatively large change in rates, caution 

should also be used in comparing yearly rates for a specific anomaly. 

• The birth defect anomaly groupings that include “other” (e.g., other musculoskeletal 

anomalies) include a large number of non-specific birth defects and should be considered 

separately from the specific birth defects listed. 

• Birth defects mortality rates are based on underlying cause-of-death as entered on a death 

certificate by a physician. Incorrect coding and low rates of autopsies that confirm the cause 

of death may occur. Additionally, some individuals may have had competing causes of death. 

“When more than one cause or condition is entered by the physician, the underlying cause is 

determined by the sequence of conditions on the certificate, provisions of the ICD 

[International Classification of Diseases], and associated selection rules and modifications” 

(CDC, n.d.). Consequently, some misclassification of reported mortality might occur in 

individuals with competing causes of death, as well as underreporting of some birth defects as 

the cause of death. 

• The International Classification of Diseases 9th Revision (ICD-9) codes were used to specify 

underlying cause of death for years 1979-1998. Beginning in 1999, cause of death is specified 

with the International Classification of Diseases 10th Revision (ICD-10) codes. The two 

revisions differ substantially, and to prevent confusion about the significance of any specific 

disease code, data queries are separate. The relatively large difference between birth defect 

mortality rates reported from 1979 through 1998 and those reported beginning in 1999 may 

be due to some changes in the criteria used to report birth defect mortality during the switch 

from ICD-9 to ICD-10. 

Data Sources 

The birth defects rate data used for this indicator are from National Vital Statistics Reports published by 

CDC’s National Center for Health Statistics (NCHS, 2001; 2002a,b; 2003; 2005). The birth defects 

mortality data were obtained from a published report by CDC’s National Center for Health Statistics 

(NCHS, 2006) and from CDC’s compressed mortality files (underlying cause of death), accessed via 

CDC WONDER (CDC, 2006), at http://wonder.cdc.gov. 

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References 

CDC (Centers for Disease Control and Prevention). 2006. CDC Wide-ranging OnLine Data for 

Epidemiologic Research (WONDER). Compressed mortality file, underlying cause of death. 1999-2003 

(with ICD 10 codes) and 1979-1998 (with ICD 9 codes). Accessed 2006. 

<http://wonder.cdc.gov/mortSQL.html> 

CDC (Centers for Disease Control and Prevention). 2005. Birth defects. Accessed February 7, 2005. 

<http://www.cdc.gov/node.do/id/0900f3ec8000dffe> 

CDC (Centers for Disease Control and Prevention). n.d. CDC WONDER: Help page for compressed 

mortality file. <http://wonder.cdc.gov/wonder/help/mort.html> 

Friis, R.H., and T.A. Sellers. 1999. Epidemiology for public health practice. Second ed. Gaithersburg, 

MD: Aspen Publishers, Inc. 

Honein, M.A., L.J. Paulozzi, and M.L. Watkins. 2001. Maternal smoking and birth defects: validity of 

birth data for effect estimation. Public Health Reports 116:327-335. 

NCHS (National Center for Health Statistics). 2006. Deaths: final data for 2003. National Vital Statistics 

Reports 54(13). April 19. <http://www.cdc.gov/nchs/data/nvsr/nvsr54/nvsr54_13.pdf> 

NCHS (National Center for Health Statistics). 2005. Births: final data for 2003. National Vital Statistics 

Reports 54(2). <http://www.cdc.gov/nchs/data/nvsr/nvsr54/nvsr54_02.pdf> See Table 49. 

NCHS (National Center for Health Statistics). 2003. Births: final data for 2002. National Vital Statistics 

Reports 52(10). <http://www.cdc.gov/nchs/data/nvsr/nvsr52/nvsr52_10.pdf> See Table 49. 

NCHS (National Center for Health Statistics). 2002a. Births: final data for 2001. National Vital Statistics 

Reports 51(2). <http://www.cdc.gov/nchs/data/nvsr/nvsr51/nvsr51_02.pdf> See Table 49. 

NCHS (National Center for Health Statistics). 2002b. Births: final Data for 2000. National Vital Statistics 

Reports 50(5). <http://www.cdc.gov/nchs/data/nvsr/nvsr50/nvsr50_05.pdf> See Table 49. 

NCHS (National Center for Health Statistics). 2001. Births: final data for 1999. National Vital Statistics 

Reports 49(1). <http://www.cdc.gov/nchs/data/nvsr/nvsr49/nvsr49_01.pdf> See Table 49. 

NICHD (National Institute of Child Health and Human Development). 2005. Birth defects and human 

development. Accessed February 3, 2005. 

<http://www.nichd.nih.gov/about/womenhealth/birth_defects.cfm> 

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1 INDICATOR: Low Birthweight 

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“Low birthweight” (LBW) is typically defined as any infant weighing <2,500 grams at birth. Weight is a 

critical health measure because LBW children are more prone to death and disability than their 

counterparts.

Environmental exposures have been implicated as a risk factor for LBW (e.g., maternal smoking, 

maternal exposure to lead, diethylstilbestrol, occupational exposures) (Sram et al., 2005; Kiely et al., 

1994). However, the etiology of term-LBW (born 37+ weeks gestation) infants and preterm-LBW (born 

<37 weeks gestation) infants differs. For term-LBW infants, underlying causes include factors such as 

maternal smoking, weight at conception, and gestational weight gain, whereas for preterm-LBW infants, 

the etiology largely remains unexplained (CDC, 1994). 

This indicator presents the percentage of LBW infants born in the U.S. based on natality data reported to 

the National Vital Statistics System (NVSS). The NVSS registers virtually all deaths and births 

nationwide with data coverage from 1933 to 2003 and from all 50 States and the District of Columbia. 

The data presented are based on singleton births only. This was done to eliminate the effect of multiple 

births. The data are presented across three maternal age groups (< 20, 20-39, and 40 and over). 

Additionally, the data are stratified and reported for preterm (less than 37 weeks) and full-term (37 weeks 

and over) births because of the strong association between birthweight and gestational age. 

What the Data Show

As expected, the percent of total LBW deliveries among preterm births are much higher than the percent 

of total LBW deliveries among full term births across each of the three maternal age categories (Exhibits 

5-28 and 5-29). 

In general, small differences in the percent of LBW babies among maternal age categories are evident for 

both pre- and full-term births. For example, in 2002, the frequency of LBW babies among full-term births 

for mothers less than 20 years old (3.9 percent) is about 1 percent higher than mothers who are 40 years 

and older (3.0 percent) and about 1.5 percent higher than mothers who are in the 20-39 age group (2.4 

percent) (Exhibit 5-29). 

Among the full-term births, black women had consistently higher frequencies of LBW babies compared 

to any of the other racial groups reported from 1995 and 2002. This racial pattern is evident in 2002 for 

all three maternal age groups and the difference is most apparent in the 40 and older age group (6.2 

percent for blacks and 2.5 percent for whites) (Exhibit 5-29). 

The percentage of LBW babies among the other two racial groups reported in 2002, Native Americans 

and Asians/Pacific Islanders, was 2.4 percent and 3.5 percent, respectively, for the 40 and older age 

group. For Native Americans, there was little variation in frequency of LBW among the three different 

age groups reported (< 20 years, > 20-39 years, and 40 and older) during 2002, whereas Asian/Pacific 

Islanders fluctuations across age groups were somewhat greater. Hispanic women and non-Hispanic 

women had very similar frequencies of LBW babies. For example, in 2002, the percent of LBW babies 

for Hispanic women was 2.3 percent compared to 2.6 percent for non-Hispanic women. (Data not shown.) 
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Indicator Limitations 

• Complete reporting of natality indicators such as LBW may vary due to differences in the 

reporting requirements established by each state. It is possible that in some states the number 

of LBW babies may be under reported. 

Data Source 

The data used for this indicator were obtained from CDC’s National Center for Health Statistics, Division 

of Vital Statistics, natality public-use data (1995-2002) available via CDC WONDER (CDC, 2006), at 

http://wonder.cdc.gov. 

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References 

CDC (Centers for Disease Control and Prevention). 2006. CDC Wide-ranging OnLine Data for 

Epidemiologic Research (WONDER). Natality data query. Accessed 2006. 

<http://wonder.cdc.gov/natality.html> 

CDC (Centers for Disease Control and Prevention). 1994. Increasing incidence of low birthweight—

United States, 1981-1991. MMWR 43:335-339. Accessed February 2, 2005. 

<http://www.cdc.gov/mmwr/preview/mmwrhtml/00030918.htm> 

Kiely, J.S., K.M. Brett, S. Yu, and D.L. Rowley. 1994. Low birthweight and intrauterine growth 

retardation. In: Wilcox, L.S., and J.S. Marks, eds. From data to action: CDC’s public health surveillance 

for women, infants, and children. CDC’s maternal and child health monograph 1994. Atlanta, GA: 

Centers for Disease Control and Prevention. 

Sram R.J., B Binkova, J. Dejmek, and M. Bobak. 2005. Ambient air pollution and pregnancy outcomes: a 

review of the literature. Environ. Health Perspect. 113(4): 375-382 

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INDICATOR: Preterm Delivery 

Preterm delivery is defined as delivery prior to 37 weeks of gestation (a typical pregnancy lasts 40 

weeks). The shorter the gestational age of an infant, the more likely (s)he is to suffer adverse effects. 

Preterm birth along with low birthweight is the second leading cause of infant death (Infant Mortality 

indicator, p. 5-19) (NCHS, 2004, 2005), and is associated with nearly half of all neurological birth defects 

(Goldenberg and Rouse, 1998; NCHS, 2005). 

The determinants of preterm births are not fully known and the causes are often multi-factorial. Maternal 

high risk conditions (e.g., infertility problems, vaginal spotting, inadequate maternal weight gain), 

maternal previous history, socioeconomic status, smoking, alcohol consumption before third trimester, 

and multiple gestation pregnancy are known risk factors for preterm delivery. Environmental 

contaminants (e.g., lead, environmental tobacco smoke, air pollution) continue to be studied to better 

understand the likely associations with preterm delivery. 

This indicator presents the proportion of U.S. infants 

born prior to 37 weeks of gestation, based on natality 

data reported to the National Vital Statistics System 

(NVSS). The NVSS registers virtually all deaths and 

births nationwide with data coverage from 1933 to 

2003 and from all 50 States and the District of 

Columbia. The data presented here on preterm 

delivery were based on singleton births only. This 

was done to eliminate the effect of multiple births. 

The data are presented across three maternal age 

groups (< 20 years, 20-39 years, and 40 years and 

over). 

What the Data Show 

The proportion of infants defined as preterm has risen 

14 percent since 1990 (NCHS, 2003). A small overall 

increase in preterm births has been observed from 

1995 (9.8 percent) to 2002 (10.4 percent). The largest 

percent increase between 1995 and 2000 has occurred 

among mothers in the 40 and over age group, with the 

percent of preterm births ranging from 12.0 (1995) to 

13.1 percent (2002). The next largest percent increase 

was observed in the 20-39 year old maternal group, 

ranging from 9.2 percent (1996) to 10.0 percent 

(2002), with little change over time among those less 

than 20 years of age (Exhibit 5-30, panel A). 

In 1995, the percent of preterm births was almost 

twice as high among black mothers compared to 

white mothers (16.4 versus 8.5 percent) (Exhibit 5-30, 

panel B). Between 1995-2002, preterm delivery 

among black mothers decreased slightly from 16.4 
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percent in 1995 to 15.9 percent in 2002. During the same time, preterm delivery among white mothers 

increased slightly, rising from 8.5 percent in 1995 to 9.5 percent in 2002, resulting in a slight narrowing 

of the difference in the preterm birth rate between black and white mothers. Preterm delivery for Hispanic 

mothers ranged from 10.1 (1995) to 10.6 percent (2002) compared to 9.7 (1996) and 10.4 (2002) percent 

for non-Hispanic mothers between 1995 and 2002. (Data not shown.) 

Indicator Limitations 

• “The primary measure used to determine the gestational age of the newborn is the interval 

between the first day of the mother’s last normal menstrual period (LMP) and the date of 

birth.” This measurement is subject to error, including imperfect maternal recall or 

misidentification of the LMP because of postconception bleeding, delayed ovulation, or 

intervening early miscarriage These data are edited for LMP-based gestational ages, which 

are clearly inconsistent with the infant’s plurality and birthweight, but reporting problems for 

this item persist and may occur more frequently among some subpopulations and among 

births with shorter gestations (NCHS, 2003). 

• Preterm delivery data were extracted from the CDC WONDER database. Slight differences in 

percentages were obtained compared to reports by NCHS (2003). The source of these 

differences in unknown. 

Data Source 

The data used for this indicator were obtained from CDC’s National Center for Health Statistics, Division 

of Vital Statistics, natality public-use data (1995-2002) available via CDC WONDER (CDC, 2006), at 

http://wonder.cdc.gov. 

References 

CDC (Centers for Disease Control and Prevention). 2006. CDC Wide-ranging OnLine Data for 

Epidemiologic Research (WONDER). Natality data query. Accessed 2006. 

<http://wonder.cdc.gov/natality.html> 

Goldenberg, R.L., and D.J. Rouse. 1998. Prevention of premature birth. New Engl. J. Med. 339:313-320. 

NCHS (National Center for Health Statistics). 2005. Births: final data for 2003. National Vital Statistics 

Reports 54(2). Accessed December 20, 2005. 

<http://www.cdc.gov/nchs/data/nvsr/nvsr54/nvsr54_02.pdf> 

NCHS (National Center for Health Statistics). 2004. Infant mortality statistics from the 2002 period 

linked birth/infant death data set. National Vital Statistics Reports 53(10). 

NCHS (National Center for Health Statistics). 2003. Births: final data for 2002. National Vital Statistics 

Reports 52(10). Accessed November 21, 2005. 

<http://www.cdc.gov/nchs/data/nvsr/nvsr52/nvsr52_10.pdf> 

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5.3.3 Discussion 

What These Indicators Say About Trends in Diseases and Conditions for 

Which Environmental Contaminants May Be a Risk Factor 

The indicators selected to answer this question represent diseases and conditions that affect multiple 

systems of the human body and are associated with a number of causal factors, some of which include 

contaminants in the air, water, and land. Some indicators represent chronic conditions (e.g., various 

cancers, heart and lung disease), some are primarily acute in nature (e.g., infectious diseases), and others 

represent conditions of the developing fetus and neonate. Understandably, no striking trends are evident 

across the broad categories of diseases represented by the indicators. However, some changes in disease 

rates or occurrence were observed for individual indicators. These relate largely to disease patterns 

observed over time and to differences observed across age groups, gender, and racial and ethnic groups. 

Generally, the occurrence of many chronic diseases in adults is increasing with the aging of the 

population (Cancer indicator, p. 5-31; Cardiovascular Disease indicator, p. 5-37; Chronic Obstructive 

Pulmonary Disease indicator, p. 5-43). However, while overall cancer incidence rates showed a steady 

increase from the mid-1970s to the mid-1990s, rates have held relatively steady between 1997 and 2003. 

With the exception of prostate cancer in males and breast cancer in females, site-specific cancer rates also 

have remained fairly constant. Similarly, prevalence rates for CVD and COPD have shown no striking 

changes between 1997 and 2003. Prevalence rates for adult asthma have increased slightly between 1997 

and 2001, with slight declines from 2002 to 2004 (Asthma indicator, p. 5-48). 

No distinct upward or downward patterns were revealed between 1995 and 2004 for most of the acute 

infectious gastrointestinal diseases presented in this report. One exception is the decrease in Hepatitis A 

cases, which have been attributed to childhood vaccination for this disease.36 Generally increased reported 

occurrence of arthropod-borne diseases and legionellosis bear watching (Infectious Diseases indicator, p. 

5-53). 

Review of diseases in children and birth outcomes revealed the following overall trends. Childhood 

cancer incidence has increased slightly since 1975, with boys having a higher incidence rate than girls. 

Leukemia and brain and other nervous system cancers remain the leading cancer sites in children 

(Childhood Cancer indicator, p. 5-35). As with adults, prevalence rates for childhood asthma have not 

changed much between 1997 and 2004, though a 4 percent increase was reported between 1980 and the 

mid-1990s (Asthma indicator, p. 5-48). A wide range of birth defects continues to be reported each year, 

but with no great shifts in rates observed for specific types of defects from 1999 to 2003. Heart anomalies 

and physical defects remain the most prevalent types of birth defects based on birth certificate data (Birth 

Defects indicator, p. 5-58). Among full-term singleton births, the percentage of low birthweight infants 

has not varied greatly from 1995 and 2002. Age of mother showed the greatest influence, with the 

greatest number of low birthweight infants born to younger mothers (less than 20 years old) (Low 

Birthweight indicator, p. 5-62). The highest rate of preterm births is also seen in these younger mothers, 

though nearly comparable and rising pre-term birth rates are seen among mothers over the age of 40 

(Preterm Delivery indicator, p. 5-65). 

36 Centers for Disease Control and Prevention. 2005. Summary of notifiable diseases—United States, 2003. MMWR 

52(54):5-14. <http://www.cdc.gov/mmwr/summary.html> 

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Some differences were observed across racial and ethnic groups. Observations are reported for the most 

recently available annual data set. Overall, cancer incidence is higher among black males than for any 

other racial group. Less disparity was observed between cancer incidence in white and black women. 

With childhood cancers, higher rates have been consistently reported in whites than in blacks (Cancer 

indicator, p. 5-31, Childhood Cancer indicator, p. 5-35). For cardiovascular disease (p. 5-37), prevalence 

rates are highest in American Indian/Alaska Natives, followed by whites, blacks or African Americans, 

and Asians. Asthma rates were generally reported highest among blacks or African Americans in children 

and American Indian/Alaska Natives in adults, followed by, whites, and Asians (Asthma indicator, p. 5­

48). 

The percentage of preterm and low birthweight infants is consistently higher among blacks than in whites 

(1.5 to nearly 3 times higher). This observation is seen across all maternal age groups (Preterm Delivery 

indicator, p. 5-65; Low Birthweight indicator, p. 5-62). When available, reported disease rates were 

generally lower (Asthma indicator, p. 5-48; Cardiovascular Disease indicator, p. 5-37) or comparable 

(Preterm Delivery indicator, p. 5-65; Low Birthweight indicator, p. 5-62) in non-Hispanic and Hispanic 

populations. 

Limitations, Gaps, and Challenges 

In answering this question, EPA reviewed general trends in morbidity and mortality of several diseases 

that may be related, at least in part, to environmental contaminant exposures. The indicators presented in 

this section provide an overall picture of specific disease rates or occurrence across the nation, including 

among some population subgroups. ROE indicator data sets, however, do not enable extensive analysis of 

disease trends within or across geographic regions, nor do they allow fully consistent reporting of trends 

across racial and ethnic groups. In addition, other diseases or conditions of potential interest exist, but for 

which no national scale data are currently available, or for which the strength of associations with 

environmental contaminants are still being evaluated. Specific limitations, data gaps, and challenges 

related to answering the question on trends in disease are highlighted below. 

Geographic patterns. Mortality data sets enable some analysis at the EPA regional level, but underlying 

data for most ROE indicators selected to answer this question do not enable meaningful analysis of 

geographic trends across the nation. The regional analyses presented in this report for CVD and COPD 

mortality reveal no discernable patterns. 

Other diseases and conditions for which environmental contaminants may be risk factors. Additional data 

are needed to prompt or enable EPA to track other diseases and conditions with potential environmental 

risk factors (direct or indirect), particularly those for which unexplained increases are being noted. 

Examples of diseases or conditions with suggestive or growing evidence that environmental contaminants 

are a risk factor follow. The extent to which national-level indicators meeting ROE criteria are available 

to track these diseases and conditions varies. 

Behavioral and neurodevelopmental disorders in children continue to receive attention. These include 

disabilities of the functioning brain that affect a child’s behavior, motor skills, memory, or ability to learn. 

Examples include attention-deficit/hyperactivity disorder (ADHD), dyslexia and other learning 

disabilities, cerebral palsy, mental retardation, and autism. Considerable evidence exists documenting that 

lead and methylmercury are associated with mental retardation and impairment of mental function and 

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attention.37 While the role of other environmental contaminants in contributing to some of these disorders 

is not fully known or understood (e.g., ADHD), the weight of evidence suggesting relationships between 

behavioral and neurodevelopmental effects from exposure to PCBs, environmental tobacco smoke, and 

other contaminants continues to grow.38,39 NHIS tracks ADHD and mental retardation, though the 

accurate reporting of these types of disorders is complicated by the difficulties in diagnoses and possible 

underreporting (e.g., institutionalized children are excluded from the NHIS survey population). 

As the U.S. population continues to age, more individuals are afflicted with neurodegenerative disorders 

such as Parkinson’s disease and Alzheimer’s disease. For example, Alzheimer’s disease is the eighth 

leading cause of death in the nation (General Mortality indicator, p. 5-13). Such diseases are characterized 

by the progressive loss of neural cells, which lead to central nervous system dysfunction (e.g., memory 

loss, cognitive deficits, personality changes, motor control abnormalities). The etiology of these disorders 

is multifactorial, but in many cases the etiology is unknown. Ongoing research is exploring the role, if 

any, of environmental contaminant exposure (e.g., heavy metals, pesticides). Thus far, findings are largely 

inconclusive due to conflicting results.40 

Diabetes was reported as the sixth leading cause of death in the United States in 2002 (General Mortality 

indicator, p. 5-13). Two types of diabetes exist. Diabetes mellitus (type 2), the most common form of 

diabetes, is characterized by the body’s resistance to insulin action and a relative deficiency of insulin. 

Known risk factors for diabetes mellitus include factors such as age, obesity, family history, physical 

inactivity, and dietary glycemic load. Type 1 diabetes results from decreased insulin production by the 

pancreas as part of an autoimmune response. Onset typically occurs before adulthood and believed to be 

triggered by genetic predisposition and possible environmental factors. Diabetes itself is a risk factor for 

the development of many other acute and chronic conditions. Epidemiological research has been 

conducted to evaluate possible associations between environmental contaminant exposure and diabetes; 

however, findings are inconclusive. Occupational and environmental exposures to contaminants such as 

arsenic, PCBs, dioxins, and nitrates have been examined.41,42 Other endocrine and metabolic disorders, 

such as thyroid disorders continue to be studied. Research suggests that various environmental 

37 Mendola P., S.G. Selevan, S. Gutter, and D. Rice. 2002. Environmental factors associated with a spectrum of 

neurodevelopmental deficits. Ment. Retard. Dev. Disabil. Res. Rev. 8(3):188-197. 

38 Schantz, S.L., J.J. Widholm, and D.C. Rice. 2003. Effects of PCB exposure on neuropsychological function in 

children. Review. Environ. Health Perspect. 111(3):357-376. 

39 State of California. 2005. Proposed identification of environmental tobacco smoke as a toxic air contaminant. Part 

B: health effects assessment for environmental tobacco smoke. As approved by the Scientific Review Panel on June 

24, 2005. California Environmental Protection Agency, Office of Environmental Health Hazard Assessment. 

<http://www.arb.ca.gov/regact/ets2006/ets2006.htm> 

40 Brown, R.C., A.H. Lockwood, and B.R. Sonawane. 2005. Neurodegenerative disorders: an overview of 

environmental risk factors. Environ. Health Perspect. 113(9):1250-1256. 

41 Longnecker, M.P., and J.L. Daniels. 2001. Environmental contaminants as etiologic factors for diabetes. Environ. 

Health Perspect. 109(Suppl 6):871-876. 

42 Remillard, R.B., and N.J. Bunce. 2002. Linking dioxins to diabetes: epidemiology and biologic plausibility. 

Review. Environ. Health Perspect. 110(9):853-858. 

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contaminants are capable of disrupting endocrine function in many species, including humans (e.g., 

phthalates, POPs). 

Reproductive function is another condition of interest to EPA. Scientists are studying whether 

environmental contaminants may cause alterations in reproductive function and contribute to conditions 

such as ovarian failure, decreased sperm counts, infertility, sub-fecundity, and possibly early onset of 

puberty. For example, components of cigarette smoke and other environmental contaminants have been 

studied in association with possible effects on female reproductive function.43 Other contaminants under 

study include pesticides, dioxins, various metals, and solvents. 

Renal disease is of interest because of the vital function of the kidneys in maintaining human health and 

the range of complex factors that lead to kidney dysfunction and disease. The kidneys can be seriously 

affected by a number of primary diseases such as hypertension and diabetes. Nephritis and nephritic 

syndrome were reported as the ninth leading cause of death in 2002 (General Mortality indicator, p. 5-13). 

EPA is interested because the kidney is known to be the target of some environmental contaminants. For 

example, as evidenced through occupational exposure, poisoning, and other experimental studies, 

exposure to heavy metals such as lead, cadmium, and mercury has been shown to be nephrotoxic.44,45 The 

U.S. Renal Data System is a national data system that collects, analyzes, and distributes morbidity and 

mortality information about end-stage renal disease (ESRD) in the United States. 

Infectious diseases represent a continuing threat in the United States and worldwide. CDC continues to 

monitor infectious diseases and implement preventive strategies for infectious diseases whose incidence 

has increased within the past two decades or threatens to increase in the near future.46 Infectious diseases 

of EPA interest may shift over time, making tracking of these diseases more of a challenge. An area of 

research interest for arthropod-borne diseases, and a potential issue for zoonotic diseases, is whether their 

incidence may change with changes in environmental condition such as land use, local weather 

conditions, or other environmental disturbances. 

Other data collection systems. To better answer the question, expanded national-level health data 

collection systems are needed, as well as integration of systems that collect health data. For example, the 

birth certificate data currently used to track birth defects on a national level have limitations (see Birth 

Defects indicator, p. 5-58). The CDC recognizes the need for continuing efforts to improve birth defects 

surveillance and recently released improved national prevalence estimates for major birth defects looking 

at data reported through the National Birth Defects Prevention Network.47 Also, as noted above, systems 

43 Mlynarcikova, A., M. Fickova, and S. Scsukova. 2005. Ovarian intrafollicular processes as a target for cigarette 

smoke components and selected environmental reproductive disruptors. Review. Endocr Regul. 39(1):21-32. 

44 Klaassen, C.D., ed. 2001. Casarett and Doull’s toxicology: the basic science of poisons. Sixth ed. New York, NY: 

McGraw-Hill. 

45 Jarup, L. 2003. Hazards of heavy metal contamination. Review. Br. Med. Bull. 68:167-182. 

46 Centers for Disease Control and Prevention. 1998. Preventing emerging diseases. A strategy for the 21st century. 

Atlanta, GA: U.S. Department of Health and Human Services. 

47 Centers for Disease Control and Prevention. 2006. Improved national prevalence estimates for 18 selected major 

birth defects—United States, 1999-2001. MMWR 54(51&52):1301-1305. 

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do not exist at the state or national level to track many of the diseases or conditions that may be related to 

environmental hazards. Existing environmental hazard, exposure, and disease tracking systems are not 

linked together. 

Some efforts are underway to begin tracking exposure and health outcomes together. For example, CDC’s 

“environmental public health tracking network” involves the collection and integration of data from 

environmental hazard monitoring and from human exposure and health outcome surveillance; CDC’s goal 

is to build a national tracking network (http://www.cdc.gov/nceh/tracking/). In addition, CDC has 

initiated the “environmental public health indicator project,” which identifies indicators of environmental 

hazards and health effects that state health departments can use to develop comprehensive environmental 

public health programs (http://www.cdc.gov/nceh/indicators/default.htm). Such programs will help bridge 

some existing gaps in knowledge between disease trends and environmental condition. These efforts also 

will enhance data collection efforts at the community level (state and local) and help ensure better 

temporal and spatial congruence between environmental, surveillance, and biomonitoring programs. 

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5.4 WHAT ARE THE TRENDS IN HUMAN EXPOSURE TO ENVIRONMENTAL

CONTAMINANTS, INCLUDING ACROSS POPULATION SUBGROUPS AND 

GEOGRAPHIC REGIONS? 

5.4.1 Introduction 

Understanding the extent to which human populations are being exposed to environmental contaminants 

helps identify those contaminants of potential public health concern and populations who may be 

disproportionately exposed to contaminants, such as children, women of childbearing age, certain race or 

ethnic groups, or other potentially susceptible subgroups. Tracking the levels of environmental 

contaminants in a population also enables an assessment of how exposures to those contaminants are 

changing in that population. 

Referring back to the Environmental Public Health Paradigm presented in Section 5.1.1, measurements of 

human exposure to environmental contaminants can be made in the ambient environment (air, water, 

land), at the point of human contact, or after contact and contaminant entry into the human body has 

occurred. The sidebar on the next page further distinguishes the different types of exposure measures. In 

answering this question, the focus is on human biomonitoring, which involves the measurement of human 

tissues or excreta for direct or indirect evidence of exposure to chemical, biological, or radiological 

substances. The ambient pollutant measurements presented in the media chapters are not considered here, 

nor can they be directly linked with biomonitoring data presented to answer this question. 

Historically, human exposure has been defined as the amount of a chemical, physical, or biological 

contaminant at the outer boundary of the body available for exchange or intake via inhalation, ingestion, 

or skin or eye contact.48 As such, human exposure to environmental contaminants has been estimated 

primarily through measurements of contaminant concentrations in air, water, or soil, combined with 

estimates of the frequency and duration of human contact with the contaminated media. These resulting 

exposure estimates have provided a valuable foundation for many of the regulatory and non-regulatory 

actions that have been taken to limit exposure to ambient contaminants. However, developments in data 

collection techniques and analytical methods have improved the capability to characterize human 

exposure via biomonitoring, which provide measurements of contaminants within the human body. 

For a few environmental contaminants, particularly lead and some other metals, biomonitoring has been 

used for exposure characterization for a number of years. More recently, techniques for biomonitoring 

have been expanded to include many additional environmental contaminants. These measurements 

provide a tool that complements ambient measurements in characterizing human exposure to 

environmental contaminants, However, concentrations of environmental contaminants reported at a 

national level in blood, urine, or any other type of tissue cannot be used to extrapolate directly to a 

particular source. 

The use of biological markers (or biomarkers) builds on the more traditional exposure assessment 

approach, providing more information on the extent to which a contaminant enters, remains, and acts in 

the body. Biomarker information attempts to determine the extent to which a contaminant is present in the 

48 Aldrich, T., J. Griffith, C. Cooke. 1993. Environmental epidemiology and risk assessment. New York, NY: Van 

Norstrand Reinhold. 

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Measuring Human Exposure 

Various approaches can be used to measure or estimate the levels of human exposures. No approach 

is best suited to all environmental contaminants, and each approach has strengths and weaknesses. 

Available biomonitoring data are used to answer the question on trends in human exposure to 

environmental contaminants. 

Ambient pollutant measurements. Historically, human exposures have been estimated using 

environmental measurements of ambient pollutant concentrations. One limitation of ambient 

measurements is that the presence of a contaminant in the environment may not be fully informative 

regarding the extent to which individuals are exposed. In some cases, emissions data are used to 

model or estimate ambient concentrations. 

Models of exposure. This approach combines knowledge of environmental contaminant 

concentrations with information on people’s activities and locations (e.g., time spent working, exercising 

outdoors, sleeping, shopping) to account for the contact with pollutants. This approach requires 

knowledge of pollutant levels where people live, work, and play, as well as knowledge of their day-today activities. Since model output is not a direct measure of environmental conditions or exposure, it is 

not considered to be a true indicator of exposure. 

Personal monitoring data. With personal monitoring, the monitoring device is worn by individuals as 

they engage in their normal day-to-day activities. This approach is most commonly used in workplace 

environments. Personal monitoring data provide valuable insights into the source of contaminants to 

which people are actually being exposed. However, a challenge with personal monitoring (as with 

biomonitoring) is ensuring that sufficient sampling is conducted to be representative of the population 

being studied. No national-scale level personal monitoring data are available. 

Biomonitoring data. Several environmental contaminants, notably heavy metals and some pesticides 

and other persistent organic pollutants, can accumulate in the body. These pollutants or their 

metabolites can be measured in human tissues or fluids such as blood or urine. These residues reflect 

the amount of contaminant that gets into or is present in the body, but by themselves do not provide 

information on how the person came into contact with the contaminant. 

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body after entering through portals of entry such as the eyes, skin, stomach, intestines, or lungs. Given the 

complex set of factors that govern contaminants that are absorbed and distributed in the body, a direct 

measurement of the levels of a contaminant or related “marker” in the body offers more information about 

exposure than measured ambient levels alone. 

In general, a biomarker reports the level of a substance or a marker (i.e., the product of an interaction 

between an agent and some target molecule or cell) present in samples collected from the body or 

produced by the body. Biomarkers of exposure measure concentrations of a contaminant, its 

metabolite(s), or reaction product(s) in the body fluids or tissue, most commonly blood or urine. 

Measurements can also be taken from a variety of other body compartments, such as feces, breast milk, 

hair, nails, exhaled air, and tissues obtained through biopsy or autopsy. The exposure measure used to 

answer this question focuses on biomarkers of exposure. Biomarkers of exposure do not predict whether 

biological alterations and potential health effect will result. Whether a particular exposure ultimately 

results in an adverse health outcome depends on a host of factors, as is described in Section 5.1 of this 

chapter. 

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5.4.2 Indicators 

The answer to the question on trends in human exposure relies on national-scale biomonitoring data 

collected as part of CDC’s National Health and Nutrition Examination Survey (NHANES), primarily data 

collected from 1999-2002. As part of the survey, blood and urine samples are routinely collected to 

measure certain contaminants (or their metabolites) of public health concern. NHANES is conducted 

annually, but the data are combined and reported for a two-year time period to provide more stable 

population estimates and to obtain adequate sample sizes for many subgroup analyses. The chemicals in 

CDC’s current suite of biomarkers are based largely on scientific data that suggest exposure in the U.S. 

population, the seriousness of known or suspected health effects associated with some levels of exposure, 

the availability and adequacy of analytical methods, along with logistical and cost considerations.49 

Seven individual or groups of contaminants from NHANES are considered, including metals, persistent 

organic pollutants (POPs), pesticides, and phthalates (Table 5.3.1). The data presented represent data from 

NHANES in its entirety or a subset of the original data, with emphasis on those compounds for which 

CDC was able to calculate geometric means.50 The levels of detection (LOD) presented in the tables that 

follow vary from chemical to chemical. The LOD is the level at which the measurement has a 95 percent 

probability of being greater than zero. Percentile estimates that are less than the LOD for the chemical 

analysis are reported as “<LOD.” In cases where the proportion of results below the LOD was greater 

than 40 percent, geometric means were not calculated and the results were reported as “NC,” or not 

calculated. 

Blood measurements for chemicals that may concentrate in lipid (e.g., dioxins, furans, PCBs, 

organochlorine pesticides) are presented per gram of total lipid as well as per whole weight of blood. 

Because these compounds are lipophilic, they concentrate in the body’s lipid stores, including the lipid in 

blood. Blood levels reported per gram of total lipid represent the amount of these chemicals that are 

stored in body fat. (Blood levels per whole weight of blood are included to facilitate comparison with 

studies investigating exposure to these chemicals that report results in these units). For chemicals 

measured in urine, levels are reported as volume in urine and per gram of creatinine. Expressing the result 

per gram of creatinine helps adjust for the effects of urinary dilution. For example, if one person 

consumed more fluids than another person, that individual’s urine output is likely higher and more dilute 

than that of the other person.51 

49 Centers for Disease Control and Prevention. 2005. Third national report on human exposure to environmental 

chemicals. NCEH publication no. 05-0570. <http://www.cdc.gov/exposurereport/3rd/> 

50 Geometric means are calculated by taking the log of each concentration, then calculating the mean of those log 

values, and finally, taking the antilog of that mean. A geometric mean provides a better estimate of central tendency 

and is influenced less by high values than is the arithmetic mean. This type of distribution is common when 

measuring environmental chemicals in blood or urine (CDC 2005). 

51 Centers for Disease Control and Prevention. 2005. Third national report on human exposure to environmental 

chemicals. NCEH publication no. 05-0570. <http://www.cdc.gov/exposurereport/3rd/> 

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Table 5.4.1. ROE Indicators of Trends in Biomarkers of Exposure to Common Environmental 

Contaminants 

NATIONAL INDICATORS LOCATION 

Blood Lead Level 5.4.2 – p. 5-76 

Blood Mercury Level 5.4.2 – p. 5-79 

Blood Cadmium Level 5.4.2 – p. 5-82 

Blood Persistent Organic Pollutants Level 5.4.2 – p. 5-85 

Blood Cotinine Level 2.4.2 – p. 2-114 

Urinary Pesticide Level 5.4.2 – p. 5-94 

Urinary Phthalate Level 5.4.2 – p. 5-100 

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1 INDICATOR: Blood Lead Level

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Lead is a naturally occurring metal found in small amounts in rock and soil. Lead has been used 

industrially in the production of gasoline, ceramic products, paints, metal alloys, batteries, and solder. 

While lead arising from the combustion of leaded gasoline was a major source of exposure in past 

decades, today lead based paint and lead-contaminated dust from paint are the primary sources of lead 

exposure in the home. Lead levels can be measured in blood or urine. 

Lead is a neurotoxic metal that affects areas of the brain that regulate behavior and nerve cell 

developments (NRC, 1993). Its adverse effects range from subtle responses to overt toxicity, depending 

on how much lead is taken into the body and the age and health status of the person (CDC, 1991). Lead is 

one of the few pollutants for which biomonitoring and health effect data are sufficient to clearly evaluate 

environmental management efforts to reduce lead in the environment. 

Infants, children, and fetuses are more vulnerable to the effects of lead because the blood-brain barrier is 

not fully developed (Nadakavukaren, 2000). Thus, a smaller amount of lead will have a greater effect in 

children than in adults. In addition, ingested lead is more readily absorbed into a child’s bloodstream, 

while adults absorb only 10 percent. Because of lead’s adverse effects on cognitive development, CDC 

has defined an elevated blood lead level as equal to or greater than 10 micrograms/deciliter (μg/dL) for 

children under 6 years of age (CDC, 2005). 

This indicator is based on data collected by the National Health and Nutrition Examination Survey 

(NHANES). NHANES is a series of surveys conducted by CDC’s National Center for Health Statistics 

(NCHS) that is designed to collect data on the health and nutritional status of the civilian, noninstitutionalized U.S. population using a complex, stratified, multistage, probability-cluster design. CDC 

began monitoring blood lead in 1976 as part of NHANES II, which covered the period 1976 through 

1980. Blood lead was also monitored in NHANES III, which covered the period between 1988 and 1994. 

CDC’s National Center for Environmental Health (NCEH) conducted the laboratory analyses for the 

biomonitoring samples. Beginning in 1999, NHANES became a continuous and annual national survey 

visiting 15 U.S. locations per year and surveying and reporting for approximately 5,000 people annually. 

What the Data Show

The overall geometric mean blood lead levels among all participants age 1 year and older from NHANES 

1999-2000 and 2001-2002 were 1.7 micrograms per deciliter (μg/dL) and 1.5 μg/dL, respectively (Exhibit 

5-31). Adults age 20 years and older had a geometric mean lead level of 1.6 μg/dL during the 2001-2002 

NHANES. For this same period males and females had a geometric mean lead level of 1.8 μg/dL and 1.2 

μg/dL, respectively. For non-Hispanic blacks, Mexican Americans, and non-Hispanic whites during 

2001-2002 the geometric mean lead levels were 1.7, 1.5, and 1.4 μg/dL, respectively. The geometric 

mean blood levels among every age, race, and ethnic group, as well as for both males and females, 

declined in the most recent 2001-2002 survey. Of all age groups, children age 1-5 years had the highest 

geometric mean lead level at 1.7 μg/dL. However, this age group also showed the largest decline between 

1999-2000 and 2001-2002 (2.2 μg/dL versus 1.7 μg/dL, respectively). Children age 6-11 and 12-19 years 

had reported geometric mean lead levels of 1.3 and 0.9 μg/dL, respectively for the 2001-2002 survey. 

Blood lead levels have declined steadily since NHANES surveillance of blood lead levels across the U.S. 

began in 1976. NHANES II (1976-1980) reported a geometric mean blood lead level of 14.9 μg/dL 

among children age 1-5 years, the highest at risk population for lead exposure and effects and just over 88 
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percent of this high-risk population had blood lead levels greater than or equal to 10 μg/dL (CDC, 2004a). 

Data collected from 1991-1994 as part of NHANES III (phase 2) showed that the geometric mean blood 

lead level for children age 1-5 years was 2.7 μg/dL with 4.4 percent of children age 1-5 years having 

blood lead levels greater than or equal to 10 μg/dL (CDC, 2005). Children age 1-5 whose blood was 

sampled between 1999-2002 had a geometric mean blood lead level of 1.9 μg/dL, with 1.6 percent of the 

children having blood lead levels greater than or equal to 10 μg/dL (CDC, 2005). 

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Indicator Limitations 

• Because the data from NHANES 1999-2000 and 2001-2002 represent only two survey 

periods, changes in estimates between the two time periods do not necessarily reflect a trend. 

Earlier data sets are available (e.g., NHANES III), but the data are not directly comparable to 

NHANES 1999-2002. When CDC releases additional survey results (e.g., 2003-2004) it will 

become possible to more fully evaluate trends (CDC, 2002, 2004b). 

• The measurement of lead or any other environmental chemical in a person’s blood or urine 

does not by itself mean that the chemical has caused or will cause harmful effects in that 

person. 

Data Source 

Data used for this indicator were extracted from two CDC reports that present results of the ongoing 

National Health and Nutrition Examination Survey (CDC, 2004a and 2005). The underlying laboratory 

data supporting CDC’s reports are available online in SAS® transport file format at 

http://www.cdc.gov/nchs/about/major/nhanes/datalink.htm. 

References 

CDC (Centers for Disease Control and Prevention). 2005. Third national report on human exposure to 

environmental chemicals. NCEH publication no. 05-0570. Accessed September 9, 2005. 

<http://www.cdc.gov/exposurereport/report.htm> 

CDC (Centers for Disease Control and Prevention). 2004a. Children’s blood lead levels in the United 

States. Accessed October 11, 2005. <http://www.cdc.gov/nceh/lead/research/kidsBLL.htm> 

CDC (Centers for Disease Control and Prevention). 2004b. NHANES analytic guidelines. June 2004 

version. Accessed October 21, 2005. 

<http://www.cdc.gov/nchs/data/nhanes/nhanes_general_guidelines_june_04.pdf> 

CDC (Centers for Disease Control and Prevention). 2002. NHANES 1999-2000 addendum to the 

NHANES III analytic guidelines. Updated August 30, 2002. Accessed October 11, 2005. 

<http://www.cdc.gov/nchs/data/nhanes/guidelines1.pdf> 

CDC (Centers for Disease Control and Prevention). 1991. Preventing lead poisoning in young children. 

Accessed November 21, 2004. <http://aepo-xdvwww.epo.cdc.gov/wonder/prevguid/p0000029/p0000029.asp> 

Nadakavukaren, A. 2000. Our global environment: a health perspective. Fifth ed. Prospect Heights, IL: 

Waveland Press, Inc. 

NRC (National Research Council). 1993. Measuring lead exposure in infants, children, and other 

sensitive populations. Washington, DC: National Academies Press. 

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INDICATOR: Blood Mercury Level 

Mercury is a naturally occurring metal. However, through many industrial processes (e.g., chemical 

manufacturing operations, coal combustion), mercury is widespread and persistent in the environment. It 

is found in elemental form and in various organic compounds and complexes. Methylmercury (an organic 

form) can accumulate in the food chain in aquatic systems and lead to high concentrations in predatory 

fish. Consumption of contaminated fish is the major source of human exposure to methylmercury in the 

United States (NRC, 2000). 

The human health effects of mercury are diverse and depend on the forms of mercury encountered and the 

severity and length of exposure. Fetuses and children may be more susceptible to mercury than adults, 

with concern for the occurrence of developmental and neurological health effects (NRC, 2000). Prenatal 

exposures interfere with the growth and migration of neurons and have the potential to cause irreversible 

damage to the developing central nervous system. 

This indicator quantifies the blood mercury levels (includes organic and inorganic) among U.S. women 

age 16-49 years and children age 1-5 years, using data from the 1999-2002 National Health and Nutrition 

Examination Survey (NHANES). NHANES does not report blood mercury data for adult males. 

NHANES is a series of surveys conducted by CDC’s National Center for Health Statistics (NCHS) that is 

designed to collect data on the health and nutritional status of the civilian, non-institutionalized U.S. 

population using a complex, stratified, multistage, probability-cluster design. CDC’s National Center for 

Environmental Health (NCEH) conducted the laboratory analyses for the biomonitoring samples. 

Beginning in 1999, NHANES became a continuous and annual national survey. Data for 1999-2000 and 

2001-2002 are presented here as a baseline with the intent of reporting trends across time as more data 

become available in the future. 

What the Data Show

Exhibit 5-32 presents the geometric mean and four percentiles of blood mercury for selected populations 

sampled during NHANES 1999-2000 and 2001-2002. For women age 16-49 years there was a small 

decline in geometric mean blood mercury levels from 1999-2000 and 2001-2002 (1.0 and 0.8 micrograms 

per deciliter [μg/L] respectively). Decreases occurred for each of the four percentiles, but were most 

pronounced at the 90th and especially 95th percentiles. 5.7 percent of women tested between 1999 and 

2002 had mercury levels measured between 5.8 and 58 μg/L. For children age 1-5 years the geometric 

mean remained the same at 0.3 μg/L. 

When the geometric means are stratified across three racial/ethnic groups, black, non-Hispanic women 

age 16-49 had the highest levels during both the 1999-2000 and 2001-2002 surveys (1.4 and 1.1 μg/L 

respectively), followed by white, non-Hispanics (0.9 and 0.8 μg/L respectively), and Mexican Americans 

(0.8 and 0.7 μg/L respectively). Among children age 1-5 years, black, non-Hispanics have the highest 

geometric mean between 1999 and 2002 (0.50 μg/L), followed by Mexican Americans (0.35 μg/L) and 

white, non-Hispanics (0.29 μg/L) (CDC, 2004a). 
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Indicator Limitations 

• Because the data from NHANES 1999-2000 and 2001-2002 represent only two survey 

periods, changes in estimates between the two time periods do not necessarily reflect a trend. 

When CDC releases additional survey results (e.g., 2003-2004) it will become possible to 

more fully evaluate trends (CDC, 2002, 2004b). 

• The measurement of mercury or any other environmental chemical in a person’s blood or 

urine does not by itself mean that the chemical has caused or will cause harmful effects in 

that person. 

• Generally recognized guidelines for blood levels of mercury have not been established. 

Data Sources 

Data used for this indicator were extracted from two CDC reports that present results of the ongoing 

National Health and Nutrition Examination Survey (CDC, 2004a and 2005). The underlying laboratory 

data supporting CDC’s reports are available online in SAS® transport file format at 

http://www.cdc.gov/nchs/about/major/nhanes/datalink.htm. 

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References 

CDC (Centers for Disease Control and Prevention). 2005. Third national report on human exposure to 

environmental chemicals. NCEH publication no. 05-0570. Accessed September 9, 2005. 

<http://www.cdc.gov/exposurereport/report.htm> 

CDC (Centers for Disease Control and Prevention). 2004a. Blood mercury levels in young children and 

childbearing-aged women—United States, 1999-2002. MMWR 53:1018-1020. Accessed December 2, 

2004. <http://www.cdc.gov/mmwr/PDF/wk/mm5343.pdf> 

CDC (Centers for Disease Control and Prevention). 2004b. NHANES analytic guidelines. June 2004 

version. Accessed October 21, 2005. 

<http://www.cdc.gov/nchs/data/nhanes/nhanes_general_guidelines_june_04.pdf> 

CDC (Centers for Disease Control and Prevention). 2002. NHANES 1999-2000 addendum to the 

NHANES III analytic guidelines. Updated August 30, 2002. Accessed October 11, 2005. 

<http://www.cdc.gov/nchs/data/nhanes/guidelines1.pdf> 

NRC (National Research Council). 2000. Toxicological effects of methylmercury. Washington, DC: 

National Academies Press. 

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INDICATOR: Blood Cadmium Level

Cadmium is a metal that is usually found in nature combined with oxygen, chlorine, or sulfur. Cadmium 

enters the environment from the weathering of rocks and minerals that contain cadmium. Exposure to 

cadmium can occur in occupations such as mining or electroplating, where cadmium is produced or used. 

Cadmium exposure can also occur from exposure to cigarette smoke (CDC, 2005). 

Cadmium and its compounds are toxic to humans and animals. Once absorbed into the human body, 

cadmium can accumulate in the kidneys and remain in the body for decades. Chronic exposure to 

cadmium may result in serious kidney damage. Osteomalacia, a bone disorder similar to rickets, is also 

associated with long-term ingestion of cadmium. Acute airborne exposure, as occurs from welding on 

cadmium-alloy metals, can result in swelling (edema) and scarring (fibrosis) of the lungs (CDC, 2005). 

This indicator reflects blood cadmium concentrations in μg/L for the United States population, age 1 year 

and older, as measured in the 1999-2002 National Health and Nutrition Examination Survey (NHANES). 

NHANES is a series of surveys conducted by the Centers for Disease Control and Prevention’s (CDC) 

National Center for Health Statistics (NCHS) that is designed to collect data on the health and nutritional 

status of the civilian, non-institutionalized U.S. population using a complex, stratified, multistage, 

probability-cluster design. CDC’s National Center for Environmental Health (NCEH) conducted the 

laboratory analyses for the biomonitoring samples. Beginning in 1999, NHANES became a continuous 

and annual national survey; biomonitoring for certain environmental chemicals also was implemented. 

Data for 1999-2000 and 2001-2002 are presented here as a baseline with the intent of reporting trends 

across time as more data become available in the future. 

What the Data Show

Exhibit 5-33 presents the geometric means and selected percentiles for blood cadmium among 

participants age 1 year and older from NHANES 1999-2000 and 2001-2002. During the 2001-2002 

survey the overall geometric mean blood cadmium level was not calculated because of the high number of 

samples that were below the method’s limit of detection. However, the blood cadmium levels at the four 

different percentiles (50th, 75th, 90th, and 95th) are very similar across the two survey periods, with 

levels ranging between 0.3 and 1.4 μg/L. The blood cadmium measurements were similar among males 

and females as well as among the racial or ethnic groups sampled across both time periods. 

During the 1999-2000 survey the overall geometric mean among participants age 20 years or older was 

slightly higher (0.5 μg/L) than the geometric mean among the 12–19 year age group (0.3 μg/L). 

Compared to the other age groups, those older than 20 years had higher cadmium levels for each of the 

four selected percentiles during both survey periods. During the 1999-2000 survey, approximately onehalf of all participants under the age of 12 had non-detectable blood cadmium concentrations. This 

proportion increased to about 90 percent during the 2001-2002 survey. 
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Indicator Limitations 

• Because the data from NHANES 1999-2000 and 2001-2002 represent only two survey 

periods, changes in estimates between the two time periods do not necessarily reflect a trend. 

When CDC releases additional survey results (e.g., 2003-2004) it will become possible to 

more fully evaluate trends (CDC, 2002, 2004b). 

• The measurement of cadmium or any other environmental chemical in a person’s blood or 

urine does not by itself mean that the chemical has caused or will cause harmful effects in 

that person. 

• Generally recognized guidelines for blood levels of cadmium have not been established. 

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Data Sources 

Data used for this indicator were extracted from the CDC report that presents results of the ongoing 

National Health and Nutrition Examination Survey (CDC, 2005). The underlying laboratory data 

supporting CDC’s report are available online in SAS® transport file format at 

http://www.cdc.gov/nchs/about/major/nhanes/datalink.htm. 

References 

CDC (Centers for Disease Control and Prevention). 2005. Third national report on human exposure to 

environmental chemicals. NCEH publication no. 05-0570. 

<http://www.cdc.gov/exposurereport/report.htm> 

CDC (Centers for Disease Control and Prevention). 2004. NHANES analytic guidelines. June 2004 

version. Accessed October 21, 2005. 

<http://www.cdc.gov/nchs/data/nhanes/nhanes_general_guidelines_june_04.pdf> 

CDC (Centers for Disease Control and Prevention). 2002. NHANES 1999-2000 addendum to the 

NHANES III analytic guidelines. Updated August 30, 2002. Accessed October 11, 2005. 

<http://www.cdc.gov/nchs/data/nhanes/guidelines1.pdf> 

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INDICATOR: Blood Persistent Organic Pollutants Level

Persistent organic pollutants (POPs) are manmade organic chemicals that remain in the environment for 

years or decades. Some POPs are toxic; others are not. Toxic POPs are of special concern because they 

often remain toxic for decades or longer. The more persistent a toxic chemical is, the greater the 

probability for human exposure over time. Because they circulate globally long after being released into 

the environment, POPs are often detected in locations far from the original source (U.S. EPA, 2004a). 

One of the major sources of POPs exposure among the general population is food. Food contamination 

begins with contaminated soil and/or plants but is of greatest concern to humans as the POPs move up the 

food chain into animals. Because POPs typically accumulate in fatty tissue and are slow to be 

metabolized, they bioconcentrate (i.e., increase in concentration) with each trophic level. Therefore, foods 

such as dairy products, eggs, animal fats, and some types of fish are more likely to contain greater 

concentrations of POPs than fruits, vegetables, and grains. POPs have been linked to adverse health 

effects such as cancer, nervous system damage, reproductive disorders, and disruption of the immune 

system in both humans and animals (U.S. EPA, 2004a). 

This indicator presents data from CDC’s National Health and Nutrition Examination Survey (NHANES) 

1999-2000 and 2001-2002. NHANES is a series of surveys conducted by CDC’s National Center for 

Health Statistics (NCHS) that is designed to collect data on the health and nutritional status of the 

civilian, non-institutionalized U.S. population using a complex, stratified, multistage, probability-cluster 

design. CDC’s National Center for Environmental Health (NCEH) conducted the laboratory analyses for 

the biomonitoring samples. Beginning in 1999, NHANES became a continuous and annual national 

survey; biomonitoring for certain environmental chemicals also was implemented. These data are 

presented here as a baseline with the intent of reporting trends over larger time periods in the future. 

Blood levels of POPs or their metabolites were measured in NHANES participants age 12 years or older. 

This indicator includes the following three broad classes of POPs: 

• Organochlorine pesticides 

• Polychlorinated dibenzo-p-dioxins (dioxins) and polychlorinated dibenzo-p-furans (furans) 

• Polychlorinated biphenyls (PCBs) 

Organochlorine pesticides were first introduced in the 1940s. Because of their environmental 

persistence, EPA banned most uses of these chemicals during the 1970s and 1980s. However, many other 

countries still produce and/or use organochlorines. These fat-soluble chemicals are most commonly 

absorbed through fatty foods. These pesticides are associated with effects to the central nervous system at 

acute exposure levels and potential carcinogenic effects with long-term exposure (Reigart and Roberts, 

1999). This indicator includes eight organochlorine pesticides that were measured in NHANES 1999­

2000 and 2001-2002; data for three of these pesticides (aldrin, dieldrin, and endrin) first became available 

with the release of results from NHANES 2001-2002 (CDC, 2005). 

• Aldrin and dieldrin. These two pesticides were widely used from the 1950s until 1970 when 

EPA prohibited most agricultural uses. However, they continued to be used to control 

termites until that use was prohibited in 1987. Aldrin rapidly converts to dieldrin in the 

environment or after being ingested or absorbed into the body. Dieldrin is more persistent and 

often accumulates in fatty tissues (CDC, 2005). 
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• Chlordane and heptachlor. EPA banned these pesticides in 1988. Within the body, 

chlordane is metabolized to oxychlordane and trans-nonachlor, and heptachlor is metabolized 

to heptachlor epoxide (CDC, 2003). Chlordane was commonly used against termites and on 

some agricultural crops and heptachlor was used primarily against soil insects and termites 

(Ritter et al., n.d.). 

• DDT. Dichlorodiphenyltrichlorethane, or DDT, was banned in the United States in 1973 but 

is still produced in other countries, where it is used primarily to control mosquitoes. In the 

body or the environment, DDT breaks down to DDE (dichlorodiphenyldichloroethane), a 

more persistent chemical. DDT or DDE in the human body may reflect either a relatively 

recent exposure or cumulative past exposures (CDC, 2005). 

• Endrin. Endrin is a stereoisomer (i.e., a molecule that is a mirror image of another molecule 

with the same molecular formula) of dieldrin. Endrin production was discontinued in 1986 

primarily because of its persistence in the environment. Unlike many other organochlorine 

pesticides, endrin does not readily accumulate in body tissues and is metabolized and 

eliminated from the body relatively quickly (CDC, 2005). 

• Hexachlorobenzene (HCB) was commonly used as a pesticide until 1965. HCB was also 

used in the past as a fungicide to protect wheat seeds, and for a variety of industrial purposes, 

including rubber, aluminum, dye production and wood preservation (U.S. EPA, 2004b). EPA 

canceled registered use in 1984; however, HCB is still formed as a by-product during 

manufacturing of other chemicals and pesticides (U.S. EPA, 2004b). 

• Mirex has not been produced or used in the United States since 1978. It was used primarily 

in the southern United States to control fire ants. The primary source of exposure is dietary, 

most often through consumption of fish (U.S. EPA, 2004c). 

Dioxins and furans are similar classes of chlorinated aromatic chemicals, usually generated as pollutants 

or by-products. In the environment, dioxins and furans occur as a mixture of about 20 compounds (termed 

“congeners”). Half-lives of these congeners range from roughly 3 to 19 years (CDC, 2005). Human 

exposure occurs primarily through food; other sources of exposure include industrial accidents, burning of 

PCBs contaminated with dioxins and furans, burning of many plastics such as PVC, and spraying or 

unintended releases of contaminated herbicides such as Agent Orange. The detection of dioxins and 

furans in human blood can reflect either recent or past exposures (CDC, 2005). 

Human health effects associated with dioxins and furans are wide-ranging. The effects of individual 

congeners are difficult to determine since most people are exposed to mixtures of several congeners. 

However, overall health effects include liver disorders, fetal injury, porphyria (a condition resulting in 

abnormal metabolic function), elevated lipid levels, chloracne, hormonal changes, neurologic damage, 

and immunogenic changes. The dioxin congener TCDD (2,3,7,8-tetrachlorodibenzo-p-dioxin) is the most 

toxic form of dioxin and it is classified as a known human carcinogen (IARC, 1997). The half-life of 

TCDD is estimated to be around 7 years (CDC, 2005). 

Polychlorinated biphenyls (PCBs) are chlorinated aromatic hydrocarbons used in a variety of industries 

as electrical insulating and heat exchange fluids. PCBs are composed of mixtures of up to 209 different 

chlorinated congeners. United States production of PCBs peaked in the early 1970s; PCBs were banned in 

1979. Sources of exposure for the general population include releases from waste sites and fires involving 

transformers, ingestion of foods contaminated by PCBs, and migration from packaging materials. PCBs 

typically accumulate in fatty tissues (ATSDR, 2000). 

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The detection of PCBs in human blood can reflect either recent or past exposures. PCBs with higher 

degrees of chlorination persist in the human body from several months to years after exposure. Coplanar 

and mono-ortho substituted PCBs exhibit health effects similar to dioxins. The human health effects of 

PCBs include changes in liver function, elevated lipids, and gastrointestinal cancers (CDC, 2005). 

What the Data Show 

Organochlorine pesticides. Exhibit 5-34 presents the lipid-adjusted and whole weight geometric means 

and four percentile values for selected organochlorine pesticide metabolites measured in blood. The 

overall geometric mean for p,p’-DDE (metabolite for DDT) during the1999-2000 survey was 260 

nanograms per gram (ng/g), compared to 295 ng/g in 2001-2002. During the most recent survey (2001­

2002), the geometric mean for trans-nonachlor (metabolite for chlordane) was 17 ng/g, compared with 

18.3 ng/g in 1999-2000. Aldrin, dieldrin, endrin, heptachlor epoxide (metabolite for heptachlor), HCB, 

and mirex were not measured with sufficient frequency above the limit of detection to calculate a 

geometric mean. 

Geometric mean blood concentrations of p, p’-DDE were compared among demographic groups after 

adjustment for the covariates of race/ethnicity, age, and gender. For samples collected between 1999 and 

2002, the 12-19 year age group had less than half the blood DDE level compared to the 20 years or older 

age group (CDC, 2005). The adjusted geometric mean level in Mexican Americans was 652 ng/g during 

the most recent survey, more than two and one-half times higher than levels in non-Hispanic whites and 

two times higher than levels in non-Hispanic blacks. It is unknown whether differences in geometric 

mean blood DDE concentrations between different age groups or racial/ethnic groups represent 

differences in exposure, body size relationships, or metabolism (CDC, 2005) (data not shown). 

Dioxins and furans. In the U.S., quantifiable emissions of dioxin-like compounds from all known 

sources have decreased by an estimated 89 percent between 1987 and 2000 (U.S. EPA, 2006). Values 

reported in NHANES 1999-2000 and 2001-2002 support that estimated decline (CDC, 2005). For 

example, among the entire NHANES 1999-2000 sample population, TCDD (generally considered the 

most toxic dioxin) was detected less than one percent of the time (CDC, 2003). During 2001-2002, only a 

small number of the dioxin and furan congeners analyzed were detected frequently enough for geometric 

means to be calculated (Exhibit 5-35). TCDD continued to be among the list of congeners analyzed in 

NHANES 2001-2002, though only the 95th percentiles for women and non-Hispanic blacks could be 

characterized (6.4 and 7.4 picograms/gram [pg/g] TCDD lipid-adjusted, respectively) (data not shown). 

From NHANES 1999-2000, none of the six dioxin or nine furan congeners measured in the blood were 

detected with sufficient frequency to calculate a geometric mean. 

In general, the more highly chlorinated dioxin and furan congeners were the main contributors to the 

human body burden. The higher concentrations of these congeners in human samples are a result of their 

greater persistence in the environment, bioaccumulation in the food chain, resistance to metabolic 

degradation, and greater solubility in body fat (CDC, 2005). 

PCBs. During the NHANES 1999-2000 subsample period, none of the 3 coplanar and 25 other PCB 

congeners were measured in blood with sufficient frequency above the limit of detection to calculate a 

geometric mean. The frequency of detection of the eight mono-ortho substituted PCBs ranged from 2 to 

47 percent (CDC, 2003). Coplanar PCB congeners 169 and 126, which exhibit dioxin-like toxicity, had a 

detection rate above 5 percent (CDC, 2003). In the 2001-2002 survey, a total of 12 dioxin-like PCB 

compounds, three coplanar PCBs and nine mono-ortho-substituted PCBs, were measured in blood. In 

addition, a total of 25 non dioxin-like PCBs were also included in the 2001-2002 NHANES analysis. 

However, only two coplanar PCBs and three non-dioxin-like PCB compounds were detected with 

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sufficient frequency to calculate a geometric mean (Exhibit 5-35). Although some PCB congeners were 

detected with greater frequency during the 2001-2002 survey compared to 1999-2000, this may, in part, 

be attributed to improved limits of detection in NHANES 2001-2002 (CDC 2005). After adjusting for a 

number of covariates (e.g., age, gender, blood cotinine, and lipid level), there were some differences 

observed in the concentrations of different PCB congeners between different demographic subgroups. 

However, it is unknown whether these differences represent differences in exposure, pharmacokinetics, or 

the relationship of dose per body weight (CDC, 2005). 

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Indicator Limitations 

• Because the data from NHANES 1999-2000 and 2001-2002 represent only two survey 

periods, changes in estimates between the two time periods do not necessarily reflect a trend. 

When CDC releases additional survey results (e.g., 2003-2004) it will become possible to 

more fully evaluate trends (CDC, 2002, 2004b). 

• The measurement of an environmental chemical in a person’s blood or urine does not by

itself mean that the chemical has caused or will cause harmful effects in that person. 

• Generally recognized reference levels for organochlorine pesticides and dioxin, furan, and 

PCB congeners in blood have not yet been established.

Data Sources 

Data used for this indicator were extracted from the CDC report that presents results of the ongoing 

National Health and Nutrition Examination Survey (CDC, 2005). The underlying laboratory data 

supporting CDC’s report are available online in SAS® transport file format at 

http://www.cdc.gov/nchs/about/major/nhanes/datalink.htm. 

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References 

ATSDR (Agency for Toxic Substances and Disease Registry). 2000. Toxicological profile for 

polychlorinated biphenyls (PCBs). Atlanta, GA: U.S. Department of Health and Human Services, Public 

Health Service. 

CDC (Centers for Disease Control and Prevention). 2005. Third national report on human exposure to 

environmental chemicals. NCEH publication no. 05-0570. Accessed September 9, 2005. 

<http://www.cdc.gov/exposurereport/report.htm>

CDC (Centers for Disease Control and Prevention). 2004. NHANES analytic guidelines. June 2004 

version. Accessed October 21, 2005. 

<http://www.cdc.gov/nchs/data/nhanes/nhanes_general_guidelines_june_04.pdf> 

CDC (Centers for Disease Control and Prevention). 2003. Second national report on human exposure to 

environmental chemicals. NCEH publication 02-0716. Accessed November 21, 2004. 

CDC (Centers for Disease Control and Prevention). 2002. NHANES 1999-2000 addendum to the 

NHANES III analytic guidelines. Updated August 30, 2002. Accessed October 11, 2005. 

<http://www.cdc.gov/nchs/data/nhanes/guidelines1.pdf> 

IARC (International Agency for Research on Cancer). 1997. Polychlorinated dibenzo-para-dioxins and 

polychlorinated dibenzofurans. IARC Monographs on the Evaluation of Carcinogenic Risks to Humans 

vol. 69. Lyon, France. 

Reigart, J.R., and J.R. Roberts. 1999. Recognition and management of pesticide poisonings. Prepared for 

U.S. EPA. Accessed April 11, 2005. 

<http://www.epa.gov/pesticides/safety/healthcare/handbook/contents.htm> 

Ritter, L., K.R. Solomon, J. Forget, M. Stemeroff, and C. O’Leary. n.d. Persistent organic pollutants. The 

International Programme on Chemical Safety (IPCS) within the framework of the Inter-Organization 

Programme for the Sound Management of Chemicals (IOMC). 

<http://www.chem.unep.ch/pops/ritter/en/ritteren.pdf> 

U.S. EPA. 2006. Inventory of sources of environmental releases of dioxin-like compounds in the United 

States: the year 2000 update. EPA/600/P-03/002a. Washington, DC. [link will be provided at future date] 

U.S. EPA. 2004a. Pesticides: regulating pesticides—persistent organic pollutants (POPs). Updated 

August 2004. Accessed December 7, 2004. <http://www.epa.gov/oppfead1/international/pops.htm> 

U.S. EPA. 2004b. Hexachlorobenzene. Updated December 2004. Accessed December 7, 2004. 

<http://www.epa.gov/pbt/pubs/hexa.htm> 

U.S. EPA. 2004c. Mirex. Updated December 2004. Accessed December 7, 2004. 

<http://www.epa.gov/pbt/pubs/mirex.htm> 

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1 INDICATOR: Urinary Pesticide Level

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Pesticides are chemicals or biological agents that kill plant or animal pests and may include herbicides, 

insecticides, fungicides, and rodenticides. More than one billion pounds of pesticides are used in the 

United States each year to control weeds, insects, and other organisms that threaten or undermine human 

activities (Aspelin, 2003). Some of these compounds can be harmful to humans if ingested, inhaled, or 

otherwise contacted in sufficient quantities. The primary routes of exposure for the general population are 

ingestion of a treated food source and contact with applications in or near residential sites. Herbicide 

exposure may also result from contaminated water. Those who manufacture, formulate, and/or apply 

these chemicals may also be occupationally exposed. 

This indicator reports the results of human biomonitoring for three classes of non-persistent insecticides 

and three classes of herbicides, which can be measured through metabolites that result from the chemical 

breakdown of the pesticide within the body. Measurement of non-persistent pesticide metabolites in urine 

typically reflects recent exposure (i.e., in the last few days) due to the short time these metabolites remain 

within the body (CDC, 2005). 

The three classes of insecticides covered by this indicator are carbamates, organophosphates (OPs), and 

pyrethroids. Carbamate insecticides have a wide variety of uses, which include applications on 

agricultural crops, residential lawns and gardens, and golf courses. Carbamate insecticides do not persist 

long in the environment, so they have a low potential for bioaccumulation. Organophosphates are used to 

control a broad spectrum of insects and account for about half of all insecticides used in the United States. 

Although organophosphates are still used for insect control on many food crops, most residential uses are 

being phased out in the United States. Pyrethroids are synthetic analogues of pyrethrins, which are natural 

chemicals found in chrysanthemum flowers. All three groups are neurotoxicants that act by 

overstimulating the nervous system of exposed organisms. Symptoms of exposure to pesticides in these 

classes may include muscle weakness or paralysis, difficulty breathing, difficulty concentrating, impaired 

coordination, and memory loss (CDC, 2005) 

The three herbicide classes discussed here are licensed for both commercial and restricted use. Restricted 

use products can only be applied by certified applicators or under the supervision of such an applicator 

(U.S. EPA, 2003). The herbicide groups are: chlorphenoxy acids, triazines, and chloroacetamides. 

Symptoms of acute high dose exposure to these herbicides may include skin and mucosal irritation as 

well as burning sensations in the nasopharynx and chest if inhaled (Reigart and Roberts, 1999). 

This indicator presents pesticide urinary metabolite data collected as part of CDC’s National Health and 

Nutrition Examination Survey (NHANES). NHANES is a series of surveys conducted by CDC’s National 

Center for Health Statistics (NCHS) that is designed to collect data on the health and nutritional status of 

the civilian, non-institutionalized U.S. population using a complex, stratified, multistage, probabilitycluster design. CDC’s National Center for Environmental Health (NCEH) conducted the laboratory 

analyses for the biomonitoring samples. Beginning in 1999, NHANES became a continuous and annual 

national survey; biomonitoring for certain environmental chemicals also was implemented. Data for 

1999-2000 and 2001-2002 are presented here as a baseline with the intent of reporting trends over larger 

time periods in the future. Carbamates, organophosphates, and herbicides were measured as part of 

NHANES 1999-2000; urinary levels of pyrethroids were added during the NHANES 2001-2002 survey. 

This indicator presents data for a subsample of survey participants age 6 to 59 years. NHANES also 

measured levels of a class of persistent pesticides, the organochlorine pesticides, which are not discussed 

here but can be found under the Indicator “Blood Persistent Organic Pollutants Level.” 
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What the Data Show 

Carbamates. Exhibit 5-36 presents the geometric means and four percentile values for unadjusted and 

creatinine-adjusted urinary concentrations of the carbamate pesticide metabolites. Of the three metabolites 

presented, only 1-naphthol was detected with sufficient frequency to calculate a measurable geometric 

mean, which was 1.70 μg/L and 1.52 migrograms per gram (μg/g) (creatinine-adjusted). 

Organophosphates. NHANES 1999-2000 and 2001-2002 measured urinary concentrations of dialkyl 

phosphates, which are the primary metabolites of many organophosphate compounds. Exhibit 5-37 

presents the geometric means and four percentile values for urinary concentrations and creatinineadjusted urinary concentrations of these metabolites. Only three of the six urinary dialkyl phosphates 

presented (dimethylthiophosphate, diethylphosphate, and diethylthiophosphate) were measured with 

sufficient frequency above the limit of detection to calculate a geometric mean. The geometric means for 

those metabolites were 1.82 μg/L (1.64 μg/g creatinine), 1.03 μg/L (0.92 μg/g creatinine), and 0.46 μg/L 

(0.45 μg/L creatinine), respectively. 

Pyrethroids. Pyrethroid (parent and metabolite) compounds were not included in the NHANES 1999­

2000 list of analytes measured in urine. During the 2001-2002 NHANES, however, five pyrethroid 

urinary metabolites were measured in urine samples from a subgroup of participants. Only one of these 

metabolites, 3-phenoxybenzoic acid was measured with sufficient frequency above the limit of detection 

to calculate a geometric mean. The geometric mean concentration of this metabolite measured in urine 

was 0.32 μg/L (Exhibit 5-38). 

Herbicides. During the 1999-2000 survey, none of the direct metabolites of the three primary classes of 

herbicide were detected in urine with sufficient frequency above the limit of detection to calculate a 

geometric mean; therefore, data are not displayed. The metabolites 2,4,5-trichlorophenoxyacetic acid and 

atrazine mercapturate were detected in only 1.2 percent and 3.3 percent, respectively, of the subsample 

(CDC, 2003). The minor metabolite 2,4-dichlorophenol had a geometric mean of 1.1 μg/L measured in 

urine; however, this metabolite can also be a result of metabolism of several other chemicals or a 

byproduct in the manufacture of chemicals. The findings from the 2001-2002 survey were generally 

consistent with earlier findings showing these metabolites to be frequently near or below the limits of 

detection. Unlike the 1999-2000 results, 2,4-dichlorophenol samples collected during 2001-2002 were not 

detected with sufficient frequency above the detection limit to calculate a geometric mean. However, the 

reported concentration of this metabolite at the 75th, 90th, and 95thpercentile were higher during the 2001­

2002 survey than during the 1999-2000 survey (CDC, 2005). 

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Indicator Limitations 

• Because the data from NHANES 1999-2000 and 2001-2002 represent only two survey 

periods, changes in estimates between the two time periods do not necessarily reflect a trend. 

When CDC releases additional survey results (e.g., 2003-2004) it will become possible to 

more fully evaluate trends (CDC, 2002, 2004b). 

• Urine creatinine concentrations were used to adjust the urinary concentrations of pesticides 

and metabolites of pesticides and phthalates in subsets of adults participating in NHANES. 

Traditionally, this approach has been used in population groups without much diversity. 

However, the inclusion of multiple demographic groups (e.g., children) in NHANES may 

increase the variability in the urinary creatinine levels when comparing across these different 

study populations (Barr et al., 2004). 

• The measurement of an environmental chemical in a person’s blood or urine does not by 

itself mean that the chemical has caused or will cause harmful effects in that person. 

• Generally recognized reference levels for carbamate, organophosphate, herbicide, and 

pyrethroid metabolites in urine have not yet been established. 

• Some metabolites may result from sources other than pesticide exposure. For example, 1­

naphthol in the urine may reflect multiple sources of exposure, and is therefore not just an 

indicator of carbamate pesticide exposure. 

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Data Sources 

Data used for this indicator were extracted from two CDC publications that present results of the ongoing 

National Health and Nutrition Examination Survey (CDC, 2003 and 2005). The underlying laboratory 

data supporting CDC’s report are available online in SAS® transport file format at 

http://www.cdc.gov/nchs/about/major/nhanes/datalink.htm. 

References 

Aspelin, A.L. 2003. Pesticide usage in the United States: trends during the 20th century. Raleigh, NC: 

Center for Integrated Pest Management, North Carolina State University. 

<http://www.pestmanagement.info/pesticide_history/index.pdf> 

Barr, D.B., L.C. Wilder, S.P. Caudill, A.J. Gonzalez, L.L. Needham, and J.L. Pirkle. 2004. Urinary 

creatinine concentrations in the U.S. population: implications for urinary biological monitoring 

measurements. Environ. Health Persp. 113:192-200. Accessed September 14, 2005. 

<http://ehp.niehs.nih.gov/members/2004/7337/7337.html> 

CDC (Centers for Disease Control and Prevention). 2005. Third national report on human exposure to 

environmental chemicals. NCEH publication no. 05-0570. Accessed September 29, 2005. 

<http://www.cdc.gov/exposurereport/report.htm> 

CDC (Centers for Disease Control and Prevention). 2004. NHANES analytic guidelines. June 2004 

version. Accessed October 21, 2005. 

<http://www.cdc.gov/nchs/data/nhanes/nhanes_general_guidelines_june_04.pdf> 

CDC (Centers for Disease Control and Prevention). 2003. Second national report on human exposure to 

environmental chemicals. NCEH publication 02-0716. Accessed November 21, 2004. 

CDC (Centers for Disease Control and Prevention). 2002. NHANES 1999-2000 addendum to the 

NHANES III analytic guidelines. Updated August 30, 2002. Accessed October 11, 2005. 

<http://www.cdc.gov/nchs/data/nhanes/guidelines1.pdf> 

Reigart, J.R., and J.R. Roberts. 1999. Recognition and management of pesticide poisonings. Prepared for 

U.S. Environmental Protection Agency. Accessed April 11, 2005. 

<http://www.epa.gov/pesticides/safety/healthcare/handbook/contents.htm> 

U.S. EPA. 2003. Restricted use products (RUP) report. Accessed March 10, 2005. 

<http://www.epa.gov/opprd001/rup/> 

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INDICATOR: Urinary Phthalate Level 

Phthalates are industrial chemicals added to many consumer products such as food packaging, plastics 

(plastic bags, garden hoses, recreational toys, medical tubing, plastic clothes, etc.), adhesives, detergents, 

personal-care products (such as soap, shampoo, nail polish, et.), and many others. Exposure can occur 

through food that has been in contact with phthalate containing packaging as well as direct contact with 

products that contain phthalates. 

Acute high dose exposure to di (2-ethylhexyl) phthalate may be associated with mild gastrointestinal 

disturbances, nausea and vertigo (U.S. EPA, 2005). Chronic exposure has been associated with damage to 

the liver and testes, cancer, and birth defects in animal studies. However, the extent to which these effects 

occur in humans has not yet been fully investigated (CDC, 2005). A recent review of six phthalate 

compounds conducted by the Center for the Evaluation of Risks to Human Reproduction summarizes the 

increasing body of data showing reproductive and developmental toxicity from low-level exposures to 

certain phthalate compounds as well as highlighting the critical data gaps that exist (Kavlock et al., 

2002a–g). 

This indicator is based on data collected by the National Health and Nutrition Examination Survey 

(NHANES). NHANES is a series of surveys conducted by CDC’s National Center for Health Statistics 

(NCHS) that is designed to collect data on the health and nutritional status of the civilian, noninstitutionalized U.S. population using a complex, stratified, multistage, probability-cluster design. 

CDC’s National Center for Environmental Health (NCEH) conducted the laboratory analyses for the 

biomonitoring samples. Beginning in 1999, NHANES became a continuous and annual national survey; 

biomonitoring for certain environmental chemicals also was implemented. Metabolites of phthalates are 

measured in urine as a biomarker of phthalate exposure in the population. Data for 1999-2000 and 2001­

2002 are presented here as a baseline with the intent of reporting trends across time as more data become 

available in the future.

What the Data Show

Exhibit 5-39 presents the geometric means and four percentiles for urinary concentrations and creatinineadjusted urinary concentrations of 12 selected metabolites of phthalates among a subsample of 

participants age 6 years and older from the most current NHANES (2001-2002). Seven of the 12 

phthalates were also previously measured in the 1999-2000 survey and are also presented in the table. 

Mono-ethyl phthalate (metabolite for diethyl phthalate, an industrial solvent used in many products 

including those containing fragrances) was the phthalate detected in the highest concentration during both 

surveys (1999-2000 and 2001-2002), with a creatinine-adjusted geometric mean concentration of 163 and 

167 μg/g of creatinine, respectively. 

In addition, other phthalate compounds such as mono-n-butyl phthalate (the metabolite for dibutyl 

phthalate, an industrial solvent used in cosmetics, printing inks, insecticides), mono-benzyl phthalate 

(metabolite for benzylbutyl phthalate, an industrial solvent used in adhesives, vinyl flooring, and car care 

products), and mono-2-ethylhexyl phthalate (metabolite for di-2-ethylhexyl phthalate, used to produce 

flexible plastics) were detected in urine samples. Mono-cyclohexyl phthalate, mono-n-octyl phthalate, and 

mono-isononyl phthalate were not measured with sufficient frequency above the limit of detection to 

calculate a geometric mean for those samples collected between 1999 and 2002. 

During the 1999-2000 and 2001-2002 surveys, the geometric mean levels for mono-ethyl phthalate, 

mono-n-butyl phthalate, mono-benzyl phthalate, and mon-2-ethylhexyl phthalate among specified 
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demographic subgroups were compared after adjustment for the covariates of race/ethnicity, age, gender, 

and urinary creatinine. For those age 6-11 years compared to the older age groups (12-19 years and 20+ 

years), urinary mono-ethyl phthalate levels were found to be lower, but urinary mono-butyl, monobenzyl, and mono-2-ethylhexyl phthalates were higher (CDC, 2005). Females tended to have a higher 

level than males for mono-ethyl, mono-butyl, and mono-benzyl phthalates. Non-Hispanic blacks had 

higher levels of mono-ethyl phthalate than non-Hispanic whites or Mexican Americans. (Data not 

shown.) 

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Indicator Limitations 

• Because the data from NHANES 1999-2000 and 2001-2002 represent only two survey 

periods, changes in estimates between the two time periods do not necessarily reflect a trend. 

When CDC releases additional survey results (e.g., 2003-2004) it will become possible to 

more fully evaluate trends (CDC, 2002, 2004b). 

• Urine creatinine concentrations were used to adjust the urinary concentrations of phthalates 

and metabolites of phthalates in subsets of adults participating in NHANES. Traditionally, 

this approach has been used in population groups without much diversity. However, the 

inclusion of multiple demographic groups (e.g., children) in NHANES may increase the 

variability in the urinary creatinine levels when comparing across these different study 

populations (Barr et al., 2004). 

• Differences in the excretion of various phthalates may be due to differences in either 

exposure or toxicokinetics. The low detection rates for some of the long alkyl chain 

phthalates metabolites may be due to significantly less metabolism to the monoester 

metabolite. 

• It is unknown whether differences between ages, genders, or races/ethnicities represent 

differences in exposure, body-size relationships, or metabolism. 

• The measurement of an environmental chemical in a person’s blood or urine does not by 

itself mean that the chemical has caused or will cause harmful effects in that person. 

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• Generally recognized reference levels for phthalate metabolites in urine have not been 

established. 

Data Sources 

Data used for this indicator were extracted from the CDC report that presents results of the ongoing 

National Health and Nutrition Examination Survey (CDC, 2005). The underlying laboratory data 

supporting CDC’s report are available online in SAS® transport file format at 

http://www.cdc.gov/nchs/about/major/nhanes/datalink.htm. 

References 

Barr, D.B., L.C. Wilder, S.P. Caudill, A.J. Gonzalez, L.L. Needham, and J.L. Pirkle. 2004. Urinary 

creatinine concentrations in the U.S. population: implications for urinary biological monitoring 

measurements. Environ. Health Persp. 113:192-200. Accessed September 14, 2005. 

<http://ehp.niehs.nih.gov/members/2004/7337/7337.html> 

CDC (Centers for Disease Control and Prevention). 2005. Third national report on human exposure to 

environmental chemicals. NCEH publication no. 05-0570. Accessed September 29, 2005. 

<http://www.cdc.gov/exposurereport/report.htm> 

CDC (Centers for Disease Control and Prevention). 2004. NHANES analytic guidelines. June 2004 

version. Accessed October 21, 2005. 

<http://www.cdc.gov/nchs/data/nhanes/nhanes_general_guidelines_june_04.pdf> 

CDC (Centers for Disease Control and Prevention). 2002. NHANES 1999-2000 addendum to the 

NHANES III analytic guidelines. Updated August 30, 2002. Accessed October 11, 2005. 

<http://www.cdc.gov/nchs/data/nhanes/guidelines1.pdf> 

U.S. EPA. 2005. Consumer factsheet on: di(2-ethylhexyl)phthalate. Accessed March 21, 2005. 

<http://www.epa.gov/safewater/dwh/c-soc/phthalat.html> 

Kavlock, R., et al. 2002a. NTP Center for the evaluation of risks to human reproduction: phthalates expert 

panel report on the reproductive and developmental toxicity of di-n-octyl phthalate. Reprod. Toxicol. 

16(5):721-734. 

Kavlock, R., et al. 2002b. NTP Center for the evaluation of risks to human reproduction: phthalates expert 

panel report on the reproductive and developmental toxicity of di-n-hexyl phthalate. Reprod. Toxicol. 

16(5):709-719. 

Kavlock, R., et al. 2002c. NTP Center for the evaluation of risks to human reproduction: phthalates expert 

panel report on the reproductive and developmental toxicity of di-isononyl phthalate. Reprod. Toxicol. 

16(5):679-708. 

Kavlock, R., et al. 2002d. NTP Center for the evaluation of risks to human reproduction: phthalates expert 

panel report on the reproductive and developmental toxicity of di-isodecyl phthalate. Reprod. Toxicol. 

16(5):655-678. 

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Kavlock, R., et al. 2002e. NTP Center for the evaluation of risks to human reproduction: phthalates expert 

panel report on the reproductive and developmental toxicity of di(2-ethylhexyl)phthalate. Reprod. 

Toxicol. 16(5):529-653. 

Kavlock, R., et al. 2002f. NTP Center for the evaluation of risks to human reproduction: phthalates expert 

panel report on the reproductive and developmental toxicity of di-n-butyl phthalate. Reprod. Toxicol. 

16(5):489-527. 

Kavlock, R., et al. 2002g. NTP Center for the evaluation of risks to human reproduction: phthalates expert 

panel report on the reproductive and developmental toxicity of butyl benzyl phthalate. Reprod. Toxicol. 

16(5):453-487. 

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5.4.3 Discussion 

What These Indicators Say About Trends in Exposure to Environmental 

Contaminants 

The biomonitoring indicators presented in this section provide an overall representation of the levels of 

selected contaminants, or metabolites of contaminants, in human blood and urine across the U.S. 

population. Measurable levels of many of these contaminants appear in at least some subset of the 

populations tested. Together, these indicators help us understand the extent to which exposure to 

individual substances has or has not occurred on a national scale. 

Lead, mercury, cadmium, POP metabolites, and cotinine were reported at varying levels in sampled blood 

and the metabolites of pesticides and phthalates in the urine of a subset of those tested. Based on the 

available data, some notable changes in blood levels were reported over time, primarily for the metals. 

Compared to historic data collected by CDC, blood lead levels have been steadily declining since the 

1980s. The same general observation is true for blood cotinine (see Section 2.4). 

Most blood mercury levels in children and women tested were reported below 5.8 μg/L—levels believed 

not to be associated with harmful health effects. However, nearly 6 percent of women tested showed 

blood mercury between 5.8 and 58 μg/L. The latter level is considered a general lower bound for 

neurological effects in developing fetuses and children of exposed mothers.52 

Current NHANES datasets provide some information about variability of biomarkers across age, gender, 

race, or ethnicity. Such analysis is only possible, however, for those chemicals frequently measured above 

the level of detection. For example, blood lead levels are highest among children; cadmium levels are 

reported highest in the most recent survey in those 20 years and older. Blood mercury levels are reported 

for children age 1-5 years and women of child-bearing age only, with the highest levels reported in the 

latter group. In most cases where disparities are observed, it is unknown whether the differences observed 

represent differences in exposure, pharmacokinetics (absorption, distribution, metabolism, and excretion), 

or the relationship of dose per body weight.53 

Limitations, Gaps, and Challenges 

Available national level data provide information on the general magnitude of exposures that are 

occurring for this subset of contaminants. Further, they serve as a firm foundation or baseline for future 

analysis. However, available indicator data answer only a part of the question. At this point in time, most 

of the biomonitoring indicators alone do not 1) enable an extensive assessment of temporal trends, 2) 

identify and explain possible differences among some subpopulations, 3) provide information on the 

geographic distribution of the population of concern, or any particular “hot spots” that may exist, 4) 

reveal exposure conditions, 5) provide information for all contaminants of potential interest, 6) consider 

exposure to multiple contaminants, or 7) provide perspective as to whether measured levels are elevated 

52 Centers for Disease Control and Prevention. 2005. Third national report on human exposure to environmental 

chemicals. NCEH publication no. 05-0570.<http://www.cdc.gov/exposurereport/3rd/> 

53 Centers for Disease Control and Prevention. 2005. Third national report on human exposure to environmental 

chemicals. NCEH publication no. 05-0570. <http://www.cdc.gov/exposurereport/3rd/> 

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or likely to cause harmful effects. These represent the most notable limitations, challenges, and data gaps 

of EPA interest in answering the question of trends in exposure to environmental contaminants. 

Temporal Trends. The relatively short time frame of the indicator dataset limits the analysis of temporal 

trends, but these indicators can serve as a baseline for future analysis. Most of the indicators presented to 

answer this question reflect data from only one or two NHANES sampling periods (1999-2000 and 2001­

2002). Only as additional NHANES reports are released every two years, will meaningful temporal trend 

analysis be possible. However, CDC has been monitoring blood lead and cotinine since approximately 

1976; for these contaminants, more meaningful temporal trend analysis is possible. 

Subgroup Analysis. The adequacy of data for subgroup evaluations varies by indicator. The NHANES 

datasets presented in this chapter contain a sufficiently large sample size to provide reliable age, gender, 

race, and ethnicity subgroup analyses. In some cases, however, the numbers of observations were 

insufficient to meet statistical reliability or confidentiality requirements for reporting estimates for all race 

or ethnicity categories.54 The benefits of such analyses have been demonstrated in earlier NHANES 

subgroup comparisons of blood lead levels (e.g., children age 1-5 years, children living in urban or lowincome areas), which have allowed resources to be targeted to higher risk or susceptible populations. 

However, not all ages are represented for all biomarkers in NHANES. Further, in cases where a small 

percentage of samples had detectable concentrations of the measured contaminant, subgroup comparisons 

are not possible or less meaningful. 

Geographic Trends. The data currently available do not allow for reliable regional subgroup analyses, 

because the number of geographic regions sampled each year is relatively small. Although the NHANES 

sampling scheme is designed to obtain a cross-section of data from various regions across the United 

States, the dataset is not sufficiently representative to allow inferences about regional levels of the 

selected biomonitoring indicators. 

Exposure Conditions. Biomonitoring data alone do not provide information on when or how exposure to a 

particular contaminant occurred. Many different exposure scenarios (e.g., acute high exposure versus 

long-term low-level exposures) can lead to the same concentration measured in the body. The measure 

does not necessarily identify the source(s) of that contaminant or how a person was exposed (e.g., 

exposure via drinking water versus food versus inhalation; environmental versus non-environmental 

source). Biomarkers of exposure integrate exposures across multiple exposure routes. Additional 

information on ambient conditions would be needed to determine what exposures contribute to 

concentrations in people’s bodies. For example, lead in children’s blood may come from exposure to 

airborne sources, contaminated water or food, or contaminated soil or dust. In addition, some biomarkers 

are not specific to a particular contaminant, making interpretation of the data and its significance 

uncertain. Lastly, some environmental contaminants are also produced in trace amounts by normal 

metabolic processes (e.g., formaldehyde and acetone), so their presence cannot always be attributed to 

external exposure.55,56 

54 National Center for Health Statistics. 2005. Health, United States, 2005, with chartbook on trends in the health of 

Americans. DHHS publication no. 2005-1232. Hyattsville, MD 

55 Watson, W.P., and A. Mutti. 2004. Role of biomarkers in monitoring exposures to chemicals: present position, 

future prospects. Biomarkers 9(3):211-242. 

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Other Environmental Contaminants. There are still many contaminants for which no biomonitoring 

indicators exist, and others that are simply not feasible to analyze using current technology or data 

collection methods. For example, although it is possible to measure the amount of radiation that a person 

is exposed to using a dosimeter, biomarkers are not yet feasible for national estimates of exposure to 

radon. Similar issues of feasibility exist with other contaminants, including most criteria air pollutants 

(e.g., ozone, nitrogen dioxide, carbon monoxide, and particulate matter), biological agents (e.g., molds, 

certain infectious agents such as bacteria or viruses, or dust mites), byproducts from the disinfection of 

drinking water (e.g., chlorine or chlorine-containing compounds), and several contaminants commonly 

found in air and drinking water at Superfund sites (e.g., trichloroethylene and tetrachloroethylene, among 

others). In many cases, biomonitoring for these contaminants is either cost-prohibitive or not yet 

technologically feasible. However, biomonitoring methods are constantly evolving. For example, CDC 

has added a number of environmental contaminants to its biomonitoring efforts, which will be included in 

future reports. These include arsenic, polybrominated compounds, perfluorinated compounds (e.g., 

perfluorooctane sulfonate [PFOS] and perfluorooctanoic acid [PFOA]), among others.57 

In addition, there is continued concern that certain chemicals, referred to as endocrine disruptors, may 

contribute to adverse health effects in humans and may impact the health of future generations. 

Information about the magnitude and pattern of human exposure to endocrine disruptors is being collected 

for only a small subset of chemicals that comprise this group (e.g., PCBs, DDT and its metabolites); 

wider testing will be challenging because there are still many compounds that have not yet been classified 

as endocrine disruptors, but may someday be identified as such. Moreover, understanding the specific 

window of vulnerability during different stages of development will be critical in evaluating the potential 

harmful effects of these chemicals. 

Multiple contaminants. Current biomonitoring indicators do not consider the effects of exposures to 

multiple contaminants. Specifically, biomarker measurements that are collected in NHANES do not 

provide any perspective regarding how different classes of contaminants interact with one another once 

they enter the body and to what extent these chemicals are additive, antagonistic, or synergistic. 

Clinical Reference or Comparison Levels. For most available biomonitoring indicators, no general 

scientific consensus exists as to how to interpret measured levels of contaminants in blood and urine. For 

example, are measured levels associated with some clinical effect or elevated above some “safe” or 

“background” level? Tracking trends in exposure over time, combined with trends in ambient 

measurements and health outcome measurements, is a key part of establishing such reference values. 

Establishing background or reference ranges (distributions) will help in identifying people with unusually 

high exposure or the percentage of the populations with contaminant exposures above established levels 

of concern. 

56 Bates, M.N., J.W. Hamilton, J.S. LaKind, P. Langenberg, M. O’Malley, and W. Snodgrass. 2005. Workgroup 

report: biomonitoring study design, interpretation, and communication—lessons learned and path forward. Environ. 

Health Perspect. 113(11):1615-1621. 

57 Department of Health and Human Services. 2003. Candidate chemicals for possible inclusion in future releases of 

the national report on human exposure to environmental chemicals. Federal Register 68(189):56296-98. September 

30. 

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