DRAFT EPHI Impact Report – March 2018

Disclaimer

The research described in this document has been funded wholly by the U.S. Environmental Protection Agency (EPA) under the Science To Achieve Results (STAR) grants program. The information provided does not necessarily reflect the views of the Agency, and no official endorsement should be inferred. Mention of trade names or commercial products does not constitute endorsement or recommendation by EPA for use. The information presented in this report is intended to provide the reader with insights about the progress and scientific achievements of STAR research grants. The report lists the grantees whose research is discussed and indicates where more detailed peer-reviewed scientific information can be found. This report is not intended to be used directly for environmental assessments or decision making. Readers with these interests should instead consult the peer-reviewed publications produced by the STAR grants and conduct necessary data quality evaluations as required for their assessments. EPA has received permission to use the images within this document.

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Contents

Contents ...... 3 EPHI Research Highlights ...... 5 Background...... 6 EPHI Grant Discoveries ...... 9 Decision-Support Indicators ...... 9 Measuring Respiratory Health Impacts of Particulate Matter Reductions ...... 9 Using Proximity to Toxic Emissions as a Measure of Environmental Health and Economic Impacts ...... 10 Longitudinal Indicators of Policy Impact on Pollution, Exposure, and Health Risk ...... 12 Considering Spatial Relations between People, Emissions, and Exposures to Improve Decision-Making ...... 12 Tribal Environmental Public Health Indicators ...... 13 Air Quality-Related Indicators ...... 17 Indicators Evaluating Potential Links Between Air Pollutant Exposure and Health Effects ...... 17 Components of Fine Particulate Matter and Cardiovascular and Respiratory Disease Indicators ...... 17 Fine Particulate Matter Exposure and Cardiovascular Disease Indicators ...... 18 Course Particulate Matter and Cardiovascular and Respiratory Disease Indicators ...... 18 Traffic-Related Air Pollution Exposure and Asthma Indicators ...... 19 School Environment and Children's Health and School Performance Indicators ...... 20 Chlorinated Solvents Exposure and Birth Defects Indicators ...... 21 Indicators of Health Outcomes Related to Air Pollution ...... 21 Asthma and other Respiratory Effects Indicators...... 21 Cardiovascular Effects Indicators ...... 22 Immunological Effects Indicators ...... 23 Indicators of Exposure to Air Pollutants ...... 24 Mobility-based Air Pollution Exposure Indicators ...... 24 Integrated Mobile Source Indicators (IMSI) ...... 24 Traffic Exposure Indicators ...... 25 Drinking and Surface Water ...... 26 Arsenic Drinking Water Exposure and Heart Disease Indicators ...... 26 Mercury Exposure Indicator that Considers Selenium ...... 27 Indicators of Exposure to Perfluorooctanoic Acid ...... 28 Waterborne Pathogen Indicators for Recreational Waters ...... 29 Multipathway Pollutant Exposure Indicators ...... 30 Arsenic Exposure Indicators ...... 31 Organochlorine Exposure and Type 2 Diabetes Indicators ...... 32 Other Stressor Exposure and Health Outcome Indicators ...... 33 Pollen Exposure and Allergic Disease Indicators ...... 34

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Heat-related Excess Mortality Indicators ...... 35 For More Information ...... 36 Appendix A. EPHI Grants ...... 37 Appendix B. Publications Attributed to EPHI Grants ...... 40 Cited References ...... 46

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EPHI Research Highlights The U.S. Environmental Protection Agency (EPA) initiated its Environmental Public Health Indicators (EPHI) research program in 2006. Since then, EPA competitively funded 20 extramural Science-to-Achieve Results (STAR) grants. These grants researched and developed EPHI that help identify predictive linkages between environmental hazards, human exposures, and disease outcomes. To date, total funding for the program was $9.5M. All the EPHI grants are now complete. This report summarizes findings, accomplishments, and impacts of EPA’s EPHI research program. EPHI indicators have directly supported health interventions, informed policy and decision-making, and improved the understanding of the links between environmental exposures and health effects. The results have helped public health professionals identify susceptible individuals and communities in the greatest need of interventions. They have assisted decision-makers in identifying opportunities for protective actions and in understanding the economic impacts of environmental stressors in their communities. Specific EPHI research program accomplishments and impact highlights—outcomes—include the following: . Conducted human health studies linking particulate matter and cardiovascular health effects which were among the evidence considered by EPA in its 2009 Integrated Science Assessment for Particulate Matter that informs the National Ambient Air Quality Standards. . Contributed to Minnesota’s Clean Air Dialogue Work Group decision to reduce emissions in Minnesota. . Identified association between peak tree pollen and allergy health effects that was cited in a New York City Department of Health and Mental Hygiene health advisory regarding risk of asthma exacerbation due to pollen. . Characterized over time community exposures to and sources of perfluorooctanoic acid in the Mid-Ohio River Valley and the findings were among the evidence that led to improvement in municipal drinking water treatment methods. . Tested novel indicators of exposure to waterborne pathogens and confirmed the predictive accuracy of a rapid water quality indicator developed by EPA, which has been adopted by Chicago Park District to improve their beach monitoring. . Developed a significantly improved measure of mercury exposure from seafood that more accurately accounts for selenium interactions, providing information helpful to guide pregnant and breastfeeding women’s seafood choices. . Identified and analyzed indicators of heat-related illness linked to heat-related death, which informed the National Weather Service’s revision of its heat advisory threshold for New York City. . Completed ground breaking studies of effect of hazardous waste cleanups on infant health and analysis of community economic impacts of toxics-emitting plants. . Developed visual methods to identify the greatest potential improvements among air pollution emission sources considering efficiency, equality, and justice. . Developed, refined, applied, and shared Indigenous Health Indicators that better capture American Indian cultural health values to inform tribal environmental decision-making. . Discovered new information about the exposure-response relationship between particulate matter and asthma emergency department visits and hospital admissions. . Identified temporal trends in school children’s asthma hospital admissions and associations between teacher health and school characteristics, which demonstrate the importance of healthy school environments. . Analyzed geographic data sets in combination with birth outcome data for the largest study population ever to identify risk factors for birth defects. . Confirmed feasibility of new indicators of asthma, other respiratory effects, and immunological effects. . Capitalized on cell phone GPS technology in combination with GIS data to develop new measures of traffic exposure. . Identified associations between heart disease and low-level arsenic exposure via drinking water. . Identified dietary sources of arsenic as a primary exposure pathway. . Developed biomarkers of exposure to phased-out pesticides in agricultural part of Mississippi. 5 DRAFT EPHI Impact Report – March 2018

Background Environmental Public Health Indicators What is an indicator? An indicator provides an easily interpretable The Environmental Public Health Indicators (EPHI) research measure of the state of the environment or health of supported through the U.S. Environmental Protection Agency’s a population. (EPA) Science to Achieve Results (STAR) grant program has supported the development of new and improved indicators of Environmental public health indicators (EPHIs) linkages among environmental hazards, human exposures, and provide information about a population’s health public health disease outcomes. EPHIs can be used for assessing status with respect to environmental factors. They the actual impacts of environmental risk management decisions, can be used to assess health or a factor associated long-term tracking and surveillance of environmental public with health in a specified population through direct 1 health, or informing health or environment-related decisions. or indirect measures. There are two types of EPHIs: These indicators provide ways to measure and track the state of . Exposure indicators, which measure or estimate the environment or better monitor community health at a local, the direct contact of humans with chemicals in regional, or national scale. their environment. These can be tied to projected health outcomes using toxicity EPA’s mission is to protect human health and the environment. information or epidemiological data that relate Early Agency efforts focused on improving the ability to assess exposure to health outcomes. exposure, toxicity, and risk. More recently, efforts have expanded . Outcome indicators, which measure actual to include identifying predictive or consequential linkages environmental or health-related results such as between pollutants and health outcomes where health outcomes cleaner air or water or reduced incidence of are changes in human health that result from exposure to disease known or believed to be caused by chemicals and/or other stressors present in the environment. exposure to environmental pollutants. Health outcome indicators measure the occurrence in a Since 2012, EPA pivoted toward the development population of diseases or conditions that are known or believed to and application of sustainability indicators. This type be caused by exposure to environmental pollutants. Health of indicator is defined as a measurable aspect of outcome indicators can be derived at a community, regional, or environmental, economic, or social systems that is national level based on the data used in their development. useful for monitoring changes in system Health outcome indicators can be used to: characteristics relevant to the continuation of 2 . describe the health status of a population and discover human and environmental well-being. EPHIs are important temporal and spatial behaviors of diseases; sustainability indicators. . identify causal factors for specific diseases or trends that explain disease prevalence or exposure occurrence; . predict disease occurrence from the distribution of exposure for a specific population; or . evaluate the health impact of environmental policy decisions or interventions.

The Significance of EPHI Research A growing number of emerging contaminants are suspected of contributing to adverse health outcomes, but many exposure-outcome relationships remain uncertain. Although chronic diseases are leading causes of disease and death in the U.S., the contribution of environmental factors to chronic health effects is not well understood. In addition, environmental health managers and policy-makers often are asked whether changes in environmental policies produce demonstrable improvements in public health outcomes. The research conducted by EPA’s EPHI grantees can help answer these important questions. Use of EPHIs and associated data can lead to better-informed public and science-based environmental health policies and decisions. EPHI research results provide communities and decision-makers: . A better understanding of the associations between pollutants and their impact on environmental quality, human exposure, and the cumulative effects on health and disease. . An improved understanding of variability of pollution impact over time, geographic location, and population type and size, and environmental health disparities. . Public health surveillance, tracking, and early-warning information. . Opportunities to understand or demonstrate actual impacts, progress, or effectiveness of environmental health decisions or programs on human health or environmental goals.

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. Evidence to inform formulation of strategies and development of future environmental health management programs or goals. Information provided by EPHI research helps communities navigate efforts to achieve sustainability and measure progress. The EPHI grant program is part of a larger EPA environmental indicators effort that aims to improve the assessment of the “state of the environment” that results from local, state, and federal risk management decisions intended to improve environmental quality and human health. The challenge for this effort, and for other environmental and public health indicator initiatives, is to link national-level indicators of pollutants to actual human exposures and health outcomes. EPHI Grant Basics, Publication Outcomes, and Career Impacts In total, EPA awarded $9.5 million through 20 EPHI grants to academic and nonprofit institutions. The locations of these awards are shown geographically in Exhibit 1 and listed in Appendix A. EPA’s STAR program awarded these research grants through a competitive solicitation process, which included both an independent external peer review for scientific merit and an internal review for relevance to EPA’s research priorities. Ten grants, awarded from two solicitations in 2007 & 2008, focused on outcome-based environmental health indicators that could reliably signal trends in source to exposure, exposure to outcome, and ultimately source to exposure to outcome relationships. These indicators will be helpful in evaluating the public health impacts of changes in environmental conditions, management approaches, or policies. Ten grants, awarded from a 2011 solicitation, focused on developing indicators for long-term tracking and surveillance of environmental public health, making better informed decisions, and assessing the actual impacts of environmental risk management decisions. Environmental public health tracking--the ongoing collection, integration, analysis, and dissemination of data--can be done at the local, state, or national level. Scientific publications resulting from these 20 STAR EPHI grants are presented in Appendix B. To date, there are 115 journal publications and 4 book chapters, with the most recent publication in January 2018. Using cost per publication as a metric to evaluate the productivity of this set of 20 grants (which included analysis of large data sets, numerous scientifically innovative approaches, and human subjects research), the cost per publication was less than $80,000. Of the EPHI publications, 100 are indexed in the Web of Science Core Collection and: • span 32 different research categories; • include contributions from 208 different authors; • have been cited over 2,600 times (not including self-citations) in over 2,100 articles with nearly 100 in the first three months of 2018; • represent collaborations with eight state or local government agencies, four tribal governments or organizations, six different branches of the federal government and authors representing eight different countries; • include two “Highly Cited Papers,” meaning each received enough citations to place it among the top 1% in their academic fields of Environment/Ecology (cited 230 times) and Social Sciences (cited 154 times); and • include seven papers cited over 100 times and 32 papers cited over 20 times. Twelve of the 20 EPHI principal investigators responded to a recent inquiry concerning the educational support provided by these EPHI grants. More than 24 early career researchers were involved in the research efforts, including 10 PhD students, seven Mater’s students and three post-doctoral researchers. Relevance of EPHI Research to EPA’s Strategic Plan In February 2018, EPA published the FY2018-2022 EPA Strategic Plan3. Although this research was initiated and completed before publication of this strategic plan, the body of research contributed through these research grants to the scientific community supports Goal 1 of the Strategic Plan “Core Mission: Deliver real results to provide Americans with clean air, land, and water, and ensure chemical safety.” This Strategic Goal indicates EPA will use the best available science and research to address current and future environmental hazards, develop new approaches, and improve the foundation for decision making. This goal highlights EPA’s desire to collaborate with other federal agencies, states, sovereign tribal nations, local governments, communities, and other partners and stakeholders to address existing pollution and prevent future problems and pay particular attention to vulnerable populations. The suite of research supported by the STAR grant EPHI program is composed of collaborative and innovative research efforts that illuminate environmental threats to public health and vulnerable communities and support EPA’s core mission.

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Exhibit 1 Exhibit . Map Map . d epicting epicting l ocations of EPHI g rant recipients.

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EPHI Grant Discoveries

Decision-Support Indicators There is a desire to expand the amount and quality of evidence-based and data-driven information to inform environmental decision-making. All EPHIs have the potential to support, directly or indirectly, decisions by communities and governments at multiple levels. Highlighted here are five EPHI research efforts that delivered results particularly beneficial to evaluations of policy or other actions, and informed planning and prioritization decisions. The first three sections present studies conducted over time-spans when reductions, or increases followed by reductions, of pollutants took place. The studies look at different measures of exposure, health outcomes, or economic impacts over the same time periods to evaluate the accuracy of proposed indicators to demonstrate actual impacts, progress, or effectiveness of policy decisions on human health or environmental goals. The fourth section presents a tool for policy makers to use in evaluating sometimes conflicting considerations when considering reductions to environmental exposures. The final section presents novel research on the development of indicators for tribal communities reflective of a broader definition of health and wellbeing embraced by many tribal communities. Measuring Respiratory Health Impacts of Particulate Matter Reductions EPHI researchers at the Minnesota Department of Health, Minnesota Pollution Control Agency, and Olmsted Medical Center, led by Dr. Jean Johnson, developed and evaluated indicators to measure impacts of air pollution reductions on exposures to fine particulate matter and respiratory health outcomes.

Results The study areas for these EPHI efforts were the Minneapolis-St. Paul metropolitan area and Olmstead County, Minnesota.4 The health outcomes studied included total respiratory, chronic lower respiratory disease, and asthma hospitalizations gleaned from existing hospital data sets. The researchers used health outcomes and local air pollution data for a 2-year baseline period (2003- 2005) and--following reductions in air pollution resulting from implementation of several national, state, and local regulations--additional data collected through 2009. Mean Average concentrations of particulate matter smaller than 2.5 microns in size were lower in later periods compared to the baseline period. The researchers found hospitalizations for air-pollution related issues to be a significant indicator of particulate matter levels in the Minneapolis-St. Paul metropolitan area using data from 2003-2009, the longest time-frame evaluated. However, there was not consistency in the results across the health outcomes and different time periods evaluated in the study. In the study using only data for Olmstead County, with its lower population and one continuous PM2.5 monitor, they found more asthma occurrences in areas with more car traffic and, coincidentally, with higher poverty rates.

What is Particulate Matter (PM)? Exhibit 2. Size comparisons for particles of particulate matter (PM) air pollution.5 PM is used to refer to a mixture of solid particles and liquid droplets found in the air. It is made up of very fine dust, soot, smoke, and droplets that are formed from chemical reactions and produced when fuels such as coal, wood, or oil are burned. PM air pollutants are so small that they can be inhaled and cause health problems by getting deep in a person’s lungs and enter his or her bloodstreams. PM10 refers to particles with diameters generally 10 micrometers and smaller. Finer particles, known as PM2.5, are particles with diameters generally 2.5 micrometers and smaller. Exhibit 2 provides size comparisons to visualize the different sizes of particulate matter (PM) air pollution.5

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Impact Dr. Johnson presented results from this EPHI grant to state legislators several times during testimony on the health impacts of air pollution. The results also provided critical support to Minnesota’s Clean Air Dialogue, a facilitated stakeholder process in which leaders from the business, government and nonprofit sectors identify potential emission reduction strategies that are efficient, effective and beneficial for Minnesotans and Minnesota industries. In April 2013, Minnesota’s Clean Air Dialogue Work Group members announced their recommendations to reduce emissions and keep Minnesota’s air clean, describing these EPHI grant findings in their final report. According to Dr. Johnson, the trends show measurable positive impacts of PM reduction policies in the Twin Cities and will be used to further support clean air initiatives.

“This EPHI STAR research has provided a critical foundation of evidence, using indicators for tracking the success of air pollution reduction strategies and for protecting public health. Building on the work over several years and working with community and business partners, the investigators continue to support new initiatives reducing particulate matter emissions and keeping Minnesota’s air clean.” – Jean Johnson, PhD, Minnesota Department of Health

In another study, EPHI researchers at Johns Hopkins University and Harvard University, led by Dr. Francesca Dominici, developed new methods to evaluate the effectiveness of air quality regulations in reducing levels of air pollution by estimating the public health benefits of air pollution regulations, referred to as “accountability” research. They conducted novel epidemiological studies linking data from independent data sets.

Results The EPHI research team assessed whether the risk of exposure to particulate matter (PM10) changed when several air quality regulatory programs were implemented.6 They identified weak evidence of a trend of decline in the short-term effect of PM10 on mortality from 1987 through 2000. Geographic differences in the trend also were noted. In addition, they found larger effects for fine particulate matter. Day-to-day variations in all-cause and cardiopulmonary mortality were associated with concentrations of fine particulate matter (PM2.5).

Impact Although the study does not provide direct evidence of health benefits, its approach offers a quantitative way to assess whether the association between day-to-day changes in pollution levels and health effects weakens over time. This research is an important component of responsible governmental policy intervention and environmental health tracking research.

Using Proximity to Toxic Emissions as a Measure of Environmental Health and Economic Impacts Communities have many questions while considering actions to protect health or improve their economies. One way to address these uncertainties is to compile and analyze new sets of “big data,” which unite and enable analysis of diverse measures of health, location, exposure, and economics. An EPHI grant to Princeton University, led by Dr. Janet Currie, investigated how a large and comprehensive data set—geocoded Vital Statistics Natality data collected from birth certificates—could be used to improve understanding of the impact of environmental hazards. The records cover millions of births over long periods and feature information about mothers’ birth outcomes, background, and residence location (coded for security). These sets can be linked with other informative data sets for far-reaching analyses. Results EPHI researchers used the database of Vital Statistics Natality records for five large states—Florida, Michigan, New Jersey, Pennsylvania, and Texas and for New York City from 1989 to 2011. They geocoded residential location and linked births to the same mother over time to calculate distances between maternal homes and environmental hazards. They also incorporated economic data and performed economic impact analyses.

In one study, EPHI investigators sought to improve understanding of the environmental health impacts from EPA’s Superfund program cleanups.7 Starting in 1980, the Superfund program has helped protect human health and the environment by managing the cleanup of the nation’s worst hazardous waste sites. 8 The researchers compared birth outcomes before and after a site cleanup for mothers who live near and farther from some of the more hazardous 10 DRAFT EPHI Impact Report – March 2018

Superfund sites. They found a 20 to 25% increase in anomalies at birth for infants born to mothers living within one mile of the Superfund sites compared to infants born to mothers living further away from the sites. In other words, the results suggest that Superfund cleanups reduced the incidence of anomalies detected at birth by approximately 20–25%. In another study, Dr. Currie’s team focused on environmental health outcomes and housing value impacts associated with proximity to industrial plants that emit toxic pollutants as reported to EPA’s Toxic Release Inventory.9 They linked information on the location and activities of the 1,600 plants with information on nearby birth outcomes and housing transactions. They found that housing prices within 0.5 miles of a toxics-emitting plant decreased by about 11% after the plant opened, relative to the price before the plant was built (see Exhibit 3). For an average plant opening, this decline indicates an aggregate loss in housing values of approximately $4.25 million. They also found that the incidence of low birthweight increased by roughly 3% within 1 mile of operating toxics-emitting plants (see Exhibit 4). They identified comparable magnitudes between 0 and 0.5 miles and 0.5 and 1 miles. In both analyses, no impacts on housing prices or infant birthweight were found beyond 1 mile.

Exhibit 3. Event study plots of the effect of toxics-emitting plant openings and closings on local housing values. The plotted coefficients show the time path of housing values 0–1 miles from a plant, relative to 1–2 miles from a plant, conditional on plant- by-distance and plant-by-year fixed effects. The dashed lines represent 95% confidence intervals. The findings suggest that plant openings (Panel A) led to housing price declines in the year of the plant opening. The results for plant closings (Panel B) are less striking, but on average prices rose slightly after the year of a closing.8

Exhibit 4. Effect of toxics-emitting plant openings and closings on the incidence of low birthweight. Shown are coefficients for event-time that plot the time path of low birthweight “near” (i.e., less than 1 mile) relative to “far” (1 to 2 miles) before and after a plant opening or closing. The dashed lines represent 95% confidence intervals.8

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Impact This research demonstrated the feasibility of using existing data in novel ways to assess environmental hazards. The approach was made possible through access to confidential Vital Statistics Natality data and the large samples provide statistical power to detect health effects from relatively low levels of pollution. The information is responsive to critical environmental and economic questions posed by communities and decision-makers. The grant generated ground-breaking studies. One was the first to examine the effect of hazardous waste cleanups on infant health rather than focusing on proximity to a site.6 Another was the first large-scale empirical analysis of the external costs of toxics-emitting plants.8 The research on health outcomes led Dr. Currie and her fellow researchers to conclude there is strong evidence that early-life exposure to pollution can have long-term consequences later in life and the benefits of pollution control may be particularly high for children—a more vulnerable segment of the population.10 Longitudinal Indicators of Policy Impact on Pollution, Exposure, and Health Risk Developing improved measures of the effectiveness of environmental policies is increasingly important for decision- making. An EPHI project at Johns Hopkins University, led by Dr. Thomas Burke, collaborated with the New Jersey Departments of Environment and Health to address this need. The project applied risk assessment as an indicator to represent potential impacts on public health and used it to evaluate the impact of environmental policies on population exposures and health risks for New Jersey. Results The EPHI investigators applied risk assessment methods to translate environmental monitoring and surveillance data into metrics of health risk. They then used risk assessment to evaluate health risks from polychlorinated biphenyls (PCBs) in fish and trichloroethylene (TCE) in drinking water prior to and after implementation of environmental policies to regulate the contaminants.11 Their analyses showed a quantifiable drop in cancer risk from PCB levels pre-ban to post- ban; however, due to the environmental persistence of PCBs, the non-cancer risks remained elevated for some scenarios ten years’ post-ban. For TCE, their analyses showed progress toward reduced TCE in drinking water. Their analyses indicate reductions in environmental pollutants, exposures, and population risks because of implementation of state and national environmental policies. Impact This EPHI grant work contributed to the growing body of knowledge on longitudinal indicators of environmental progress. The longitudinal approach they used to track pollutants and exposures provides a valuable tool for evaluating and improving the effectiveness of environmental policies. Although direct impacts of the research are difficult to measure, the EPHI investigators continue to apply the methods to other community and national environmental issues.

“This research developed approaches to combine historical pollutant measures with risk analysis to assess the impact of environmental policies. The work highlights the critical role of state-level environmental monitoring programs in tracking environmental progress and evaluating the effectiveness of national policies.” –Thomas Burke, PhD, Johns Hopkins University Considering Spatial Relations between People, Emissions, and Exposures to Improve Decision-Making Decision makers need methods to evaluate and prioritize activities to improve air quality. California’s South Coast Air Basin surrounds the city of Los Angeles. This area provides an important case study because of its large population (16 million), generally poor air quality, and extensive ambient air monitoring network. EPHI investigators at the University of Minnesota, led by Dr. Julian Marshall, used data from Southern California to model how reductions in diesel-generated fine particulate matter from specific sources could change various measures of environmental equality and justice. Results The EPHI researchers quantified how reductions in emission of fine diesel particles from specific sources—on- and off-road vehicles, ships, trains, and stationary sources--would change various measures of environmental equality and justice. The four environmental measures they assessed were: impact, efficiency, equality, and justice as defined in Exhibit 5.12 On- and off-road source categories were the largest sources of fine diesel particulate matter. Hispanic and

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non-white householders with incomes in the bottom 25th percentile showed a 44% higher mean population average intake compared to their white non-Hispanic households with incomes in the top 25th percentile. This disparity in average intakes for the two different categories of households was true for every source category of fine diesel particles. Exhibit 5. Air pollution metrics considered in Southern California diesel-generated fine particulate matter scenario.12 Metric Description Impact Total intake, total amount inhaled by the population per day Efficiency Intake fraction: the fraction of emissions from a given source category inhaled by the population Equality Atkinson index, a metric that quantifies income inequality used to reflect the goal of having equal exposure among all people; 0 represents perfect equality; 1 represents maximum inequality Justice Relative percent difference between average exposure for high-income whites with income in the upper 25% percentile vs. low-income nonwhites with income in the lowest 25% percentile

Impact This EPHI research offers decision-makers a way to consider multiple metrics when comparing different emission reduction options. The method can be expanded to evaluate more specific options that target specific sources, such as ships or trains. They are also useful in showing the effect of changes in location-specific emissions, such as for trains or ships. The findings revealed the significance of train and on-road emissions for fine diesel particulate matter pollution in the southern coastal region of California. The researchers estimated reductions in train emissions would produce the greatest improvements in terms of efficiency, equality, and justice. They found that reductions in on-road emissions would produce improvements in impact, equality, and justice. Emission reductions from ships, however, could exacerbate existing population inequalities. On- and off-road mobile sources together contributed most of the total emissions. This multi-scenario approach helps communities quantify and prioritize actions to address air pollution challenges. Tribal Environmental Public Health Indicators Indigenous communities, including American Indian and Native Alaskan communities have concerns about the health of their people like many other communities. Tribes have been requesting the use of tribal-specific definitions of health in health risk assessments, but approaches were lacking. One challenge is that conventional health assessments focus on a narrow concept of health that concentrates on disease and physiological measures. Tribal communities tend to have broader definitions of health and wellbeing. No measures were established that reflect the multilevel (e.g., familial, tribal) and complex connections between people, nature, and the spirit world that many Indigenous people in the U.S. consider essential to health and wellbeing. An EPHI grant to the Swinomish Tribal Community, led by Dr. Jamie Donatuto, built on previous work to create and test EPHI specific to Native American tribal communities in the Puget Sound/Salish Sea region of the Pacific Northwest. See Exhibit 6 for information about the Swinomish Tribe. Results The Swinomish partnered with the Lower Elwha Klallam Tribe, the Port Gamble S’Klallam Tribe, the Suquamish Tribe, and the Stillaguamish Tribe on this EPHI grant project that expanded a preliminary set of indicators developed under a previous STAR project (Bioaccumulative Toxics in Native American Shellfish, R829467).13 The EPHI researchers used a community-based approach with multiple research methods—individual interviews, group workshops, ranking with descriptive scales, weighting techniques—to identify more specific and contextual Indigenous health risks and impacts.14 They developed and tested a set of six Indigenous Health Indicators, each with specific attributes and measures (see Exhibits 7 and 8). In subsequent work, the investigators tested the efficacy of the indicators in two Indigenous communities to identify coastal climate adaptation priorities for Coast Salish communities. The results informed gaps in the Swinomish Climate Change Adaption Action Plan (2010), which supports coastal zone planning and decision-making on the Reservation.15

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Exhibit 6. Swinomish is a U.S. federally recognized American Indian Tribe. The Tribe occupies the Swinomish Indian Reservation on the southern portion of Fidalgo Island in Washington State. The Swinomish are fishing, hunting, and gathering people and 90% of the reservation is bordered by water.13

Clockwise from left • Coast Salish canoe families patiently waiting to request to come ashore at the Paddle to Swinomish of 2011. Photo by Caroline Edwards. • First Salmon Ceremony and Blessing of the Fleet. The Swinomish Canoe Family sings a blessing song for the salmon and for the safety of fisherman. Photo by Caroline Edwards. • The Salmon Dancer Canoe Family paddles along the shorelines of Swinomish. Photo by Ann Smock.

Exhibit 7. Six Indigenous Health Indicators reflect health considerations essential to the Swinomish Tribe way of life.14

Community Connection Work—Community members have a job or role they and other community members respect, and they work together (mutual appreciation, respect, cooperation). Sharing—Community members engage in active sharing networks, which are integral to a healthy community, ensuring that everyone in the community receives traditional foods and other natural resources such as plant medicines, especially Elders. Relations—Community members support, trust, and depend on each other. Natural Resources Security Quality—The natural resources, including the elements (e.g., water), are abundant and healthy. Access—All resource use areas (i.e., Usual and Accustomed areas in WA) are open to harvest/use (not closed or privatized) by community members. Safety—The natural resources themselves are healthy, not affected by pollution, climate change, etc. Cultural Use Respect/Stewardship—Community members are conferring respect of/to the natural resources and connections between humans, environment and spirit world; ensuring cultural resources are properly maintained. Sense of Place—Community members are engaging in traditional resource-based activities, which is a continued reminder/connection to ancestors and homeland. Practice—Community assemblies able to follow appropriate customs (e.g., can obtain specific natural resources if needed such as cedar, certain foods) and to honor proper rituals, prayers, and thoughtful intentions. Community members feel they are able to satisfy spiritual/cultural needs, for example, consume foods and medicines to satisfy Spirit’s “hunger.” Education The Teachings—The community maintains the knowledge, values, and beliefs important to them. Elders—The knowledge keepers are valued and respected and able to pass on the knowledge. Youth—The community’s future is able to receive, respect, and practice the Teachings. Self-Determination Healing/restoration—The availability of and access to healing opportunities (e.g., traditional medicines, language programs) for community members, and the community’s freedom to define and enact their own, chosen environmental, health, and habitat restoration programs. Development—The ability for a community to determine and enact their own, chosen community enrichment activities in their homelands without detriment from externally imposed loss of resources. Trust—The community trusts and supports its government. 14 DRAFT EPHI Impact Report – March 2018

Resilience Self-Esteem—The beliefs and evaluations community members hold about themselves are positive, providing an internal guiding mechanism to steer and nurture people through challenges, and improving control over outcomes. Identity—Community members are able to strongly connect with who they are as a community (Tribe or Nation) in positive ways. Sustainability—The community is to adapt (e.g., people hunt with guns and use motorboats today but that does not discount the significance of harvesting) and move within homelands voluntarily in response to changes (the “7 generations thinking”).

Exhibit 8. Six Indigenous Health Indicators reflect health considerations essential to the Swinomish Tribe way of life.1615 (Graphic developed by Emma Fox, Swinomish Communications Department)

Impact The Indigenous Health Indicators have been shown to be a technically effective tool for recognizing and equitably incorporating Indigenous considerations and prioritizations of health into environmental public health assessments. They have been used in numerous ways in multiple communities because the measures for each indicator can be tailored to fit an individual community’s health beliefs and priorities. The article describing these indicators has been viewed more than 1200 times according to the journal (the same IP address is counted only once) by viewers on every continent of the world but Antarctica .14 In addition, this work stimulated additional research collaborations between the Swinomish Tribe and the National Libraries of Medicine, the National Science Foundation, and the North Pacific Landscape Conservation Cooperative, among other government organizations.

An additional STAR grant was also competitively awarded to the Swinomish to use the Indigenous Health Indicators as the primary assessment tool to determine community health impacts from changes in habitats of culturally important foods such as salmon due to sea level rise and increased storm surge. This information is being incorporated into the Swinomish Climate Change Action Plan. The information is also used for year 1 and 5-year planning and decision-making about the Tribe’s shorelines and first foods. The indicators are also integral to the first Swinomish Community Public Health Assessment.

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The Indigenous Health Indicators are the basis for the 13 Moons environmental health curriculum, one of the first environmental health curricula developed in Indian Country. A website provides information (see Exhibit 9). The curriculum will be formally published in 2018 and is already taught in the local public school, at Northwest Indian College and within the community. Swinomish staff worked with other tribal communities to tailor the Indigenous Health Indicators for their community health priorities and needs. For example, the Tsleil-Waututh First Nation (British Columbia, Canada) amended the Indigenous Health Indicators for use in an oil spill impact assessment project. The Squaxin Island Tribe (Washington State) used them to assess community health impacts from ocean acidification. The Lumbee Tribe (North Carolina) used the Indigenous Health Indicator process to develop their own Public Health Department. Within the broader scientific community, this work supported the development of a framework of human wellbeing for ecosystem-based management.17

Additional potential uses of the Indigenous Health Indicators include improvement of:

. human health risk assessments, . health impact assessments, . natural resource damage assessments, . measuring baseline community environmental health and setting goals, . ecosystem services evaluations, and . social-ecological systems research. Exhibit 9. EPHI researchers established a website (http://www.swinomish-nsn.gov/ihi/) and held numerous discussions about the need for and significance of establishing a set of environmental public health indicators specific to Indigenous communities.

“The Indigenous Health Indicators provide an innovative tool for indigenous communities to more equitably evaluate community health based on their own health definitions, needs, and priorities such that planning and decision-making by those communities and others is based on more accurate data.” – Jamie Donatuto, PhD, Swinomish Tribal Community

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Air Quality-Related Indicators Our nation’s air quality has improved since the 1990s, but public health challenges remain. Air pollution exposures are associated with increased emergency department visits and hospital stays for breathing and heart problems, asthma, and increases in illnesses such as pneumonia and bronchitis.18 Air pollution can affect everyone, including citizens in both urban and rural communities. Presented here are 12 significant contributions to improving air pollution indicators from EPHI grants. These EPHI researchers investigated the links between air pollution exposure and adverse (and costly) health outcomes, such as cardiovascular events and hospitalizations. EPHI research also reduced uncertainties for specific aspects of the air pollution source-to-receptor pathway. At the source end, the researchers characterized sources that emit pollutants and measured air pollution levels, which helped communities understand where pollution originates and how often people are exposed to unhealthy levels of air pollution. At the receptor or people end, they identified cellular-level indicators of exposure to and effects from air pollutants, also known as biomarkers. This research improved understanding of the mechanisms of how air pollutant exposure contributes to disease. Indicators Evaluating Potential Links Between Air Pollutant Exposure and Health Effects Components of Fine Particulate Matter and Cardiovascular and Respiratory Disease Indicators Researchers at Johns Hopkins University and Harvard University, led by Dr. Francesca Dominici, identified compelling links between components of fine particulate matter, PM2.5, and indicators of cardiovascular or respiratory disease. Results EPHI researchers examined a large human population and used real-world concentrations of particulate matter components. For 119 U.S. urban communities and 12 million Medicare enrollees (i.e., 65 and over), the researchers estimated associations between daily concentrations of PM2.5 components and the risk of hospital 19 admissions. They evaluated major PM2.5 chemical components: sulfate, nitrate, silicon, elemental carbon, organic carbon matter, and sodium and ammonium ions, as well as weather. Among these constituents of PM2.5, they found ambient levels of elemental carbon and organic carbon matter to be associated with the largest risks of emergency hospitalizations. Elemental carbon and organic carbon matter are primarily generated from vehicles, diesel engines, and burning wood. Multipollutant models also showed evidence that the risk of Findings (Johns Hopkins University and cardiovascular admission associated with a same-day elemental carbon Harvard University) concentration was larger than risks associated with any other PM2.5 component. Identified two PM2.5 components— elemental carbon and organic carbon This grant also investigated the regional and seasonal variations of matter—as being associated with highest short-term effects of fine particulate matter on cardiovascular and 20 risks of emergency hospitalizations. respiratory hospitalizations among older adults in 202 U.S. counties. They found higher respiratory disease admissions in the winter while Found evidence for association of organic cardiovascular admissions varied little by season. Regionally, the U.S. carbon matter with respiratory-related Northeast showed the strongest evidence of an interaction between hospital admissions. PM2.5 and hospitalizations for both respiratory and cardiovascular Demonstrated regional and temporal diseases. Fine particulate matter components with higher patterns in the association between PM2.5 concentrations in the seasons and regions that showed the largest and cardiovascular and respiratory short-term effects of PM2.5 on hospitalization are associated with hospitalizations. several sources. These components corresponded to several combustion sources and to metals and sea salt. Impact The research provided a significantly more complete picture of the health effects of particulate matter chemical components. EPA cited results of this EPHI grant in its 2009 Integrated Science Assessment for Particulate 17 DRAFT EPHI Impact Report – March 2018

Matter.21 This document is EPA’s evaluation of the scientific literature on the potential human health and welfare effects associated with ambient exposures to particulate matter. Development of this document is part of the Agency’s periodic review of the national ambient air quality standards (NAAQS) for particulate matter. EPA indicated that these grant results suggest that the observed associations between PM2.5 and cardiovascular disease hospitalizations might be due primarily to particles from oil combustion and traffic. As of March 2018, the two journal articles describing these grant results are Highly Cited Papers, meaning each of them received enough citations to place them in the top 1% of their academic fields, with Web of Science indicating the paper by Peng et. al., was cited 229 times in papers representing 25 countries and the paper by Bell et. al. was cited 154 times in articles representing 20 countries.19,20 The results also helped focus future research and better design studies for evaluating the mechanisms of injury from particulate matter components. The statistical tools the researchers developed provided a reproducible methodology applicable in future characterizations of the health effects of complex mixtures. Fine Particulate Matter Exposure and Cardiovascular Disease Indicators An EPHI grant to the New York University School of Medicine and New York City Department of Health and Mental Hygiene, led by Dr. Kazuhiko Ito, evaluated using readily available health data for tracking impacts of fine particulate matter on the cardiovascular health of people in New York City.22 Results By examining chief complaint data from emergency departments, the researchers identified an association between ambient fine particles and cardiovascular morbidity.23 In New York City, chief complaint data is available to the Department of Health and Findings (New York University School of Mental Hygiene typically within 24 hours, making possible recognition Medicine and New York City Department of of sudden changes in cardiovascular illness related to ambient air Health and Mental Hygiene) pollution and other environmental events. Found that syndromic surveillance data—data In a related analysis, the researchers examined seasonal variations in that are available as soon as 1 day after associations between PM2.5 constituent pollutants and cardiovascular occurrence, e.g., asthma and cardiovascular hospitalizations and mortality. Particulate components related to coal emergency department visits: combustion were associated with cardiovascular hospitalizations in the . Are highly correlated with physician- winter and cardiovascular mortality in the summer, while local diagnosed emergency department visits combustion sources, such as traffic and residual oil burning, were and hospitalizations data information that associated with cardiovascular outcomes throughout the year.24 suffers from long (e.g., 2-year) lag times; Impact The research supported the ability to model, in near real- . Are correlated with air pollution and time, acute cardiovascular outcome indicators of environmental weather variables; exposures in a large metropolitan area. The New York City Department . Are effective tools to measure health of Health and Mental Hygiene used the results of this study in their impacts of air pollution; . Help detect unusual events; and health impact assessment for cleaner heating fuels and reduced motor 25,26 . Provide near real-time means to predict vehicle emissions. This work was influential in informing and and reduce health risks in response to accelerating implementation of New York City’s heating fuel developing air pollution and regulations to phase out the use of all heavy heating oil by 2030. The meteorological exposures. Ito et al. study was cited 104 times according to Web of Science (March 2018) with citations representing research in 18 countries. This research was also cited in the EPA’s proposed rule presenting the review of the Primary National Ambient Air Quality Standards for Oxides of Nitrogen in July 2017.27 Course Particulate Matter and Cardiovascular and Respiratory Disease Indicators Johns Hopkins University and Harvard University EPHI grant researchers filled gaps in evidence regarding the health risks of exposures to coarse particulate matter, that is, particles with diameters greater than 2.5 µm and up to 10 µm. Primary emission sources of course particulate matter include mechanical grinding, road dirt, windblown dust, and agricultural activities. Results EPHI researchers examined associations between particulate matter levels and daily counts of cardiac or respiratory emergency hospital admission

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data for 108 U.S. counties.28 The western U.S. showed levels of course particulate matter twice the levels detected in the eastern U.S.. The eastern U.S., however, had higher levels of fine particulate matter (approximately 3 µg/m3) compared to western states. After adjusting for exposures to fine particulate matter, the researchers found no statistically significant associations between coarse particulates and hospital admissions for cardiovascular and respiratory diseases. Impact The research helped fill a significant knowledge gap regarding the health impacts of course particulate matter. This EPHI study was one of only three studies of course particulate matter EPA cited in its 2009 Integrated Science Assessment for Particulate Matter.29 EPA also noted that this EPHI study was one of three “large, comprehensive, and informative studies based on Medicare hospitalization data.” In addition, other researchers have cited this EPHI study article 177 times, with citations representing research in 24 countries, according to Web of Science (March 2018). 28 Traffic-Related Air Pollution Exposure and Asthma Indicators In one of the EPHI grants that looked specifically at children’s health, a grant to the Michigan Department of Community Health (now known as the Michigan Department of Health and Human Services), University of Michigan — Ann Arbor, and Michigan State University, led by Dr. Robert Wahl, focused on acute childhood asthma events and daily air pollutant levels. Whereas previous research focused primarily on linear relationships between levels of air pollutants and asthma response, this grant evaluated whether asthma emergency department visits and hospital admissions indicated threshold exposure exist for different air pollutants. The grant also evaluated whether there was a relationship between asthma and traffic-related pollution. Asthma is a chronic, multifactorial disease The analysis considered asthma emergency department visits characterized by: Results and hospital admissions for Detroit, Michigan children (2 to 18 years of . Airway obstruction, age) enrolled in Medicaid. They looked at a variety of air pollutants and . Airway hyperresponsiveness, found concentrations of sulfur dioxide and PM2.5 were associated with . Airway inflammation, and asthma emergency department visits and hospitalizations, and evidence . Airway remodeling. indicated that proximity to major roadways was associated with asthma There has been a dramatic increase in the events.30,31 The long-term trend of daily asthma events demonstrated a prevalence of asthma worldwide in seasonal pattern (Exhibit 10). The highest frequency occurred during industrialized countries. the fall, and the lowest during the summer. The findings demonstrated the existence of a threshold effect in the range from 11 to 13 mg/m3 for PM2.5. The researchers also performed spatial analyses of asthma cases to evaluate associations with traffic exposures and found moderately strong evidence of elevated risk of asthma close to major roads. Exhibit 10. Trend of daily counts of asthma events for pediatric Medicaid population (children 2-18 years of age) in Detroit, Michigan, 2004 to 2006. Daily observations are shown as points with a trend shown as an overlaying fitted curve. The events include emergency department visits without hospitalization, direct admission for hospitalization, and hospitalizations admitted through the emergency department.30

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Impact This research was important because risk assessments that assume linearity between air pollution levels and an asthma response might underestimate the true risk. A threshold or nonlinear concentration-response relationship has significant impact on risk assessment and risk management decisions. A response threshold would also have implications for asthma education and management, and air pollution monitoring and warning systems. School Environment and Children’s Health and School Performance Indicators In another EPHI grant that focused on impacts to children, an EPHI grant to the New York State Department of Health, led by Dr. Shao Lin, developed new and improved on existing indicators related to the school environment. Many school-aged children, teachers, and administrative and custodial staff spend substantial time in school buildings. Like other structures, school buildings can be plagued by mold, vermin, allergens, vehicle exhaust intrusion, and problems with heating, ventilation, or air conditioning. According to a 2012–2013 Department of Education survey, 25% of public schools rated the indoor air quality of permanent and portable buildings as unsatisfactory or poor.32 They evaluated links between the school environment and children’s health and performance as well as the impacts of environmental policy intervention.

Results Highlighted here are some of the results of the EPHI researchers’ diverse research on indicators related to the school environment. . The proportion of U.S. children reported currently to have asthma increased from 8.7% in 2001 to 9.4% in 2010, but then decreased to 8.4% in 2015.33 The researchers assessed whether asthmatic children were more likely to be sensitized, exposed, or both to indoor allergens including pet dander, cockroach, dust mite, and mouse allergens, compared to non-asthmatic children.34 The study observed significantly positive associations between children’s asthma and sensitization to dust mite, cat, and dog allergens. Children sensitized to cockroach allergens were more likely to live in homes with higher levels of cockroach allergen. Compared to children without asthma, asthmatic children were more likely to be sensitized and had significantly higher indoor exposure to cat allergens compared to those who were only sensitized or only exposed to cat allergens. They also identified trends in asthma hospital admissions among age groups and noticed school-aged children show some patterns around returning to school after breaks. . A school’s indoor air quality is an important factor for the health of its occupants. The EPHI researchers examined indoor air quality management strategies between public elementary schools and their school districts in New York State.35 They found that nearly half (47%) of the school district respondents said they had a district-wide indoor air quality program. Regarding specific strategies, the respondents most frequently reported ventilating newly painted areas (92%). The least commonly reported strategy was having a classroom animal policy (29%). Many school districts lacked some important indoor air quality management strategies. . The importance of teacher health cannot be overlooked. Teachers are a critical point of delivery for education and their wellbeing contributes to their day-to-day success. EPHI researchers surveyed New York State school teachers to assess building-related health symptoms and classroom characteristics.36 Approximately 500 teachers responded to the survey. Their most commonly reported symptoms included sinus problems (16.8%), headache (15.0%), allergies/congestion (14.8%), and throat irritation (14.6%). Experiencing one or more of these symptoms was associated most strongly with reports of dust, dust reservoirs, paint odors, mold, and moldy odors.

Impact The school environmental health indicators developed through this EPHI grant can be used for public health surveillance tools and to develop interventions to improve health of students, teachers, and staff. For example, the health symptoms reported among New York teachers while at work appear to be associated with characteristics related to poor classroom indoor air quality. Efforts to improve school indoor air quality might improve teacher performance and reduce sickness and absenteeism. The researchers informed key stakeholders of their results, including the New York State Department of Health Environmental Public Health Tracking and State Education Department. The EPHI grant experience helped the researchers achieve two new federal grant awards related to school environmental health.

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“The school environmental health indicators we developed in this study could be used by other scientists and policy makers for research and diseases surveillance.” – Dr. Shao Lin, New York State Department of Health Chlorinated Solvents Exposure and Birth Defects Indicators In the U.S., approximately 1 in 33 infants is born with a defect. Birth defects are among the leading causes of infant mortality. The risk factors associated with approximately two-thirds of birth defects are still unknown and could include environmental exposures. For some types of birth defects, maternal exposure to air pollution has been hypothesized as a factor. EPHI researchers at Texas State University, Texas A & M Health Science Center, Texas Department of State Health Services, and University of North Carolina at Charlotte, led by Dr. F Benjamin Zhan, tackled a difficult challenge in this area—to develop methods to analyze a considerable amount of geographically referenced data and identify risk factors most likely to be associated with birth defects. Results EPHI researchers investigated associations between birth defects and mothers’ proximity to industrial releases of chlorinated solvents.37 These solvents are widely used in industrial processes, including metal degreasing, dry cleaning, and production of pharmaceuticals, pesticides, and adhesives. The birth defects they evaluated included neural tube, oral cleft, limb deficiency, and congenital heart defects for a large study population—the largest at the time of publication. The study results indicated that mothers’ residential proximity to several chlorinated solvent air emissions are associated with neural tube, oral cleft, and congenital heart defects, especially among children of older mothers. The researchers also validated a model—the Emission Weighted Proximity Model (EWPM)—that is a simpler and less expensive way to estimate air pollution exposure intensities.38 They compared EWPM to National-Scale Air Toxics Assessment estimations with ground air quality monitoring data collected by the Texas Commission on Environmental Quality. These results indicated that the EWPM is a valid alternative approach for cases where epidemiological analysis requires environmental data and health outcome data for a large geographic area and over multiple years. Impact The weighting of emissions from multiple point sources using distance was a significant advancement. Most studies in the past have used emissions from the nearest point source or some other basic approach.

“The methods can be widely used in environmental health research. The exposure dataset may be useful for researchers to analyze in the future. The visual analytics approach developed by this project is a novel approach to examination of the association between health outcome and multiple exposures, one that holds considerable promise.” – F. Benjamin Zhan, PhD, Texas State University Indicators of Health Outcomes Related to Air Pollution Asthma and other Respiratory Effects Indicators EPHI investigators at the New York University School of Medicine and New York City Department of Health and Mental Hygiene, led by Dr. Kazuhiko Ito, aimed to improve the accuracy of near real-time surveillance of asthma exacerbations. They sought to determine whether emergency department (ED) visits for asthma based on subjects’ chief complaints data, which is available the day after an ED visit, was correlated with physician-diagnosed asthma ED visits and asthma hospitalizations (data not available as quickly). Results EPHI investigators evaluated New York City data and found that data from symptom observations (e.g., asthma- and cardiovascular-related ED visits) were correlated with physician-diagnosed asthma ED visits and asthma hospitalizations.39 They also found asthma ER visit and hospitalizations were correlated with weather and air pollution variables. Their results showed that within-city asthma morbidity was temporally associated with daily variation in air pollution measures—all three air pollutants they evaluated (PM2.5, nitrogen dioxide, and ozone) were positively and significantly associated with asthma ED visit counts. Asthma was also spatially associated with socioeconomic factors (e.g., poverty) and environmental factors (e.g., residential proximity to traffic). 21 DRAFT EPHI Impact Report – March 2018

Impact This research demonstrated that data on asthma ED visits (available a day after a visit) is a good indicator of physician- diagnosed asthma ED visits and reasonable indicator of physician- diagnosed asthma hospitalizations. This indicator validation and associated analysis supports the identification of at-risk populations for asthma. An EPHI grant to the University of California at Los Angeles and at Berkeley, led by Dr. Ying-Ying Meng, explored the feasibility of combining existing environmental monitoring data and California Health Interview Survey (CHIS) data to develop health outcome indicators of breathing problems. They considered people who have Findings (New York University School of been diagnosed with asthma and those who have not. Medicine, New York City of Health and Mental Hygiene, University of California – Los Angeles, Results EPHI researchers developed long-term criteria air and University of California – Berkeley) pollutant exposure indicators using measurement data for ozone, nitrogen dioxide, and course and fine particulate matter from Confirmed feasibility of new health outcome California Air Resource Board (CARB) air monitors for CHIS 2003 and indicators: 2005 respondents.40 They identified positive associations between • asthma-related emergency exposures to criteria air pollutants and health effects for people with department (ED) visits, asthma. Health outcome indicators such as asthma-related ED visits, • absences from school/work, absences from school/work, medication use, and frequent asthma • medication use, symptoms may serve as a new set of health indicators for ozone, • frequent asthma symptoms, and particulate matter, and nitrogen dioxide exposures. The researchers • asthma-like symptoms among those also observed associations between exposure estimates for criteria without asthma diagnosis. air pollutants and asthma-like health outcomes among those without asthma. diagnoses, including wheeze symptoms, having two or more wheeze attacks, and seeking medical help for breathing problems. They used geostatistical modeling to develop exposure indicators. For the CHIS 2003 respondents, they observed positive associations between asthma health outcomes and these new exposure indicators for nitrogen oxide, nitrogen dioxide, and nitrogen oxides.

Impact New health outcome indicators for criteria pollutant exposures were identified for people with and without asthma diagnosis. Geostatistical modeling-based exposure indicators show promise for improving the accuracy of pollutant assessment compared to indicators based on air monitoring data alone. This conclusion is particularly relevant for traffic emissions exposures. The research grant also identified community-level health impacts in California and differences in health outcomes across racial/ethnic groups that add to the scientific evidence supporting policy decisions at the local, state, and national levels. Cardiovascular Effects Indicators Reducing the burden of heart disease and stroke has been challenged by many factors. Among them are gaps in understanding of environmental factors that predispose individuals to plaque rupture and factors associated with cardiovascular disease. An EPHI research collaboration project between the Lovelace Biomedical and Environmental Research Institute and the University of New Mexico, led by Dr. Matthew Campen, characterized the progression of atherosclerosis associated with exposure to ambient environmental air pollutants to identify more robust indicators of exposure.

Results The EPHI researchers used animal models and human studies to identify markers of air pollution-induced toxicity to the cardiovascular system. They investigated mechanisms of the effects from exposures to important air pollutants, alone and in combination. Highlights of their findings include the following. . Rats exposed episodically via inhalation for 16 weeks to ozone or diesel exhaust particulates exhibited induced aortic and cardiac molecular alterations.41

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. Studies in mice generated findings that identify a specific cellular receptor—oxidized low-density lipoprotein receptor—as a possible mediator of air pollution-induced progression of cardiovascular disease.42 . Evaluations of plasma collected from healthy human volunteers before and after exposure to diesel exhaust and nitrogen dioxide suggest that exposure to diesel or nitrogen dioxide can cause upregulation of proinflammatory factors in the circulatory system.43

Impact This research contributed significantly to improving the understanding of the mechanism underlying the well- documented relationship between air pollution and cardiovascular mortality. The journal articles describing the findings were cited between 35 and 58 times by other articles representing thirteen countries. The assays developed because of the grant offer new approaches to assessing the cardiovascular risk associated with air pollution exposure. Dr. Campen indicated this research directly supported current and more advanced scientific thinking regarding inflammatory biomarkers. The new thinking is to develop a holistic screen of serum or plasma using a cell culture exposure approach. They concluded that assessing the net functional balance of inflammation in serum is superior to a single or even several inflammatory biomarkers. The researchers recently applied the approach for a tribal community living near abandoned uranium mine sites in the Southwest, the results of which are being considered in prioritizations of mine site remediation.44

“The outcome of this research was the development of a novel clinically‐ and epidemiologically‐viable tool for assessing the overall circulating inflammatory potential of humans. This tool is being used currently to study individuals with disease (heart, kidney, lung), as well as toxicological impacts of environmental exposures in communities.” – Matthew Campen, PhD, University of New Mexico

Immunological Effects Indicators EPHI researchers at Stanford University, led by Dr. Kari Nadeau, studied T regulatory cells as an immunological indicator of ambient air pollution exposure and asthma in children. T cells suppress immune responses that can lessen effects of asthma.

Results The research demonstrated ambient air pollution impairs T cells, which leads to more severe asthma via an immune system mechanism in asthmatic children. Impaired T regulatory cell function is associated with ambient air pollution, including polycyclic aromatic hydrocarbons, particulate matter, and ozone.45,46 This association is more pronounced in individuals with atopic diseases, such as asthma or allergic rhinitis.46

Impact T regulatory cells are readily detected in blood samples and can be monitored in both children and adults, making them a potentially valuable indicator for long-term monitoring. Because T regulatory cells Findings (Stanford University) are associated with other diseases, including cancer and autoimmunity, Multiplex immunophenotyping is a they also could serve as a useful indicator for additional health outcomes. potential approach to identify specific Validation of the findings in a larger cohort of subjects across different immune cell types and their response to development timelines could support development of immunotherapies environmental exposures. to treat air pollution-associated asthma. The 2010 publication of these results has been cited 138 times in the Web of Science Core Collection Identified on a cellular level, the impact of with citations from 20 countries. air pollution on the immune functioning of asthmatic children is detrimental. “This grant has supported research showing on a cellular Immune indicators help link environmental level the detrimental impact of air pollution on the exposures to disease outcomes, including immune functioning of asthmatic children.” respiratory disorders, allergy, and asthma. – Kari Nadeau, MD, PhD, Stanford University

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Indicators of Exposure to Air Pollutants Mobility-based Air Pollution Exposure Indicators EPHI researchers at the University of Minnesota, led by Dr. Julian Marshall, tackled a source of uncertainty that has challenged ambient air pollution epidemiological studies of large populations. Accurately characterizing exposure to outdoor pollution is difficult because people tend to move around, which affects their concentrations, or levels, of pollution exposures. Personal monitoring, although more accurate, is expensive. Error can be introduced if epidemiological studies do not account for mobility—for example at work, school, or shopping--but no one had studied this question before. Results The EPHI research team compiled data for two study areas (Vancouver and Southern California) and analyzed residence- and mobility-based estimates of individual exposure to ambient nitrogen dioxide.47 They calculated the bias for scenarios when mobility was not considered. They found that ignoring daily mobility contributes to negative bias in effect estimates. In addition, increasing spatial variation of pollution estimates led to stronger negative bias. The negative bias strengthened with increased time and distance spent away from the residence. Impact This EPHI research was the first to investigate the effect of relying on residence-only-based estimates of outdoor air pollution levels instead of mobility-based measures for large epidemiological studies. Such studies will benefit from incorporating mobility information in exposure estimates. The study publication was cited 67 times in publications from 13 countries as of March 2018, according to Web of Science. Integrated Mobile Source Indicators (IMSI) Gasoline and diesel traffic emissions in urban areas can be significant contributors to fine particulate matter, nitrogen oxides (NOx), and carbon monoxide (CO) emissions. Humans are exposed to mixtures of these and other pollutants, rather than one pollutant at a time. Georgia Institute of Technology and Emory University researchers, led by Dr. Armistead Russell, applied a multipollutant approach to indicator development to see if the refined indicators are more likely to explain associations with health outcomes.48 Results The researchers used air quality monitoring data collected in Atlanta from 1999 to 2004. They developed two sets of IMSIs.49 One set—emission based—was based on analysis of pollutant emissions and Findings (Georgia Institute of Technology) observed concentrations. The other—health outcome based—used a IMSI agreed well with observed trends of sensitivity analysis, two-pollutant mixtures, and health outcome data. traffic. Using routinely collected monitoring data, the researchers developed: Emission-based IMSI have stronger . An improved indicator for biomass burning by estimating the associations with emergency department fraction of potassium associated with biomass burning based on a linear visits for cardiovascular diseases, possibly regression with iron; this measure had a significantly better correlation due to their better spatial with an organic tracer of biomass burning compared to total potassium, representativeness. which is also found in soil dust and sea salt;50 A multipollutant framework is more . A method to better estimate secondary aerosol fraction of informative to understanding health risk particulate matter;51 and from mobiles source emissions than using . single pollutant indicators. Specific source indicators for the impacts of mobile sources that allowed characterization of diesel and gasoline vehicle impacts, separately.

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The health outcome data they evaluated was cardiovascular disease ED visits. They assessed short-term effects of these pollutant pairs by looking at the daily measure of the indicator to see if it predicts that same day’s cardiovascular disease count. The emission-based IMSI for gasoline and diesel vehicles showed statistically significant associations as a predictor of cardiovascular disease-related ED visits in the model.

Impact IMSI can be used in epidemiological analyses and in assessing the impact of mobile sources on emissions, air quality, and health outcomes. These indicators are useful for cost-benefit analysis of air pollution reduction. The IMSI indicators enable greater differentiation of particulate matter sources using routine monitoring data. Compared with individual environmental indicators, IMSI are better indicators of regional impacts of mobile sources. This multipollutant framework is a useful tool for cost-benefit analyses of air pollution reduction policies. Traffic Exposure Indicators Traffic is a source of a wide variety of air pollutants, including gases, metals, diesel particles, and other particles of diverse size and chemical composition. Traffic also produces noise, heat, and water vapor. Studies have identified associations between exposure to traffic and health effects, including asthma, low birth weight, respiratory disease, cardiovascular disease, and developmental deficits.52 The EPHI grant to the Minnesota Department of Health, Minnesota Pollution Control Agency, and Olmsted Medical Center, led by Dr. Jean Johnson, researched novel methods including using geographic information system (GIS) and telecommunications global positioning system (GPS) technologies to quantify exposure to traffic. Results To develop a new indicator of exposure to traffic density, EPHI researchers used GIS data to calculate traffic density for the state of Minnesota and combined these data with cell phone telecommunications GPS data that records activities and travel patterns to develop a spatially resolved surface or representation of traffic density.53 Exhibit 11 shows a street map of central Minneapolis-St. Paul depicting a 54-minute bicycle ride path, color coded according to traffic density. Exhibit 11. A bicycle ride path in central Minneapolis-St. Paul, Minnesota, color coded by traffic density exposure, with green indicating lower traffic density and red indicating higher traffic density; inset graph shows the density values over time.53

.

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Impact The method integrates the deleterious effects of traffic rather than focusing on one specific pollutant at a time and allows integration of exposure over the course of an individual’s travel or along a travelled route. This approach better characterizes exposure to air pollution and can be useful in future studies correlating exposure to air pollution with observed health effects. Impact The traffic density calculation the EPHI researchers developed compared well with other measures of traffic exposure. This exposure indicator combines effects of multiple stressors associated with traffic, which is advantageous to single-pollutant assessments. The measures of traffic exposure over time generated can be used as an indicator to evaluate health outcomes, for example, as a predictive variable in epidemiological studies. The methodology has potential applicability for other environmental exposure assessment efforts.

Drinking and Surface Water On average across all ages, people drink 0.9 liters of water daily.54 Water is essential to life, but it can also be a potential exposure pathway for contaminants and microbial pathogens. Described here are three research projects by EPHI grantees that developed indicators related to drinking water or recreating in surface waters. Arsenic Drinking Water Exposure and Heart Disease Indicators Each year, 25 of every 100 deaths in the U.S. are attributable to heart disease—approximately 610,000 people.55 Over half (approximately 370,000 people) are due to coronary heart disease, the most common type of heart disease. The risk factors for heart disease, which include high blood pressure (hypertension), high cholesterol (hyperlipidemia), and smoking, are well-established and extremely common; around 47% of the American population has at least one of the three primary risk factors.55 The risk of heart disease is doubled for individuals with hyperlipidemia.56 In addition to health concerns, economic costs are associated with heart disease and its risk factors; hypertension alone costs the U.S. approximately $46 billion per year in healthcare services, medications, and missed days of work.57 Given these extensive health and economic considerations, identifying and understanding the environmental elements contributing to heart disease and risk factors of heart disease are important. Through research funded by an EPHI grant led by Dr. Sid O’Bryant, researchers at Texas Tech University provided the first demonstration that coronary heart disease is associated with increased exposure to low-level groundwater arsenic.58

Results After gathering health data from approximately 500 people, EPHI researchers used GIS methods to predict arsenic groundwater concentrations near the homes of the study subjects, which then were validated with traditional sampling methods.56 Groundwater arsenic concentrations ranged from 2.2 to 15.3 µg/L; as the current EPA standard for arsenic is 10 µg/L, these concentrations are considered low level.59 They found that a history of coronary heart disease was associated with increased GIS-estimated levels of groundwater arsenic. Hypertension, a heart disease risk factor, also was associated with higher exposure to groundwater arsenic at the estimated low levels.

Impact These findings lend support to the proposition that increases in heart disease mortality are the result of increased risks of coronary heart disease and its risk factors (i.e., hypertension) associated with higher low-level arsenic exposure. The research contributions have important implications for national strategies to decrease the incidence of heart disease.

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Mercury Exposure Indicator that Considers Selenium Selenium is an essential trace element. Selenium-dependent enzymes— selenoenzymes—are important for brain, endocrine system, and eye health. Mercury inhibits brain selenoenzyme activity. Developing children are potentially at risk if their mothers eat foods that contain more mercury than selenium, for example shark and whale meat. But eating other kinds of ocean fish during pregnancy is associated with a 4- to 6-point increase in child intelligence quotient and improved maternal health. An EPHI grant to the University of North Dakota, led by Dr. Nicholas V. Ralston, developed an indicator that more accurately considers the interactions between selenium and mercury to improve risk assessment and management of mercury.

Results EPHI investigators enhanced the reliability of a national-level indicator called selenium health benefit value (HBVSe) that considers both methyl mercury exposure and dietary selenium intake focusing on pregnant women’s consumption.60 This indicator is a conservative index that predicts effects of maternal methyl mercury exposures from seafood consumption. They compiled mercury and selenium concentrations and calculated HBVSe results for more than 13,000 ocean and freshwater fish and shellfish. Exhibit 12 shows results for selected seafood. They found that most freshwater and ocean fish contain more selenium than mercury. Consuming these types of fish is anticipated to be beneficial instead of harmful.

Exhibit 12. Comparison of seafood HBVSe values. Consumption of seafood with positive HBVSe would negate risks associated with methyl mercury exposures. Although intermittent methyl mercury exposures are unlikely to compromise maternal or fetal selenium status, consistent consumption of negative HBVSe seafood could have risks, especially among mothers with poor selenium intakes. The HBVSe provides information that confirms FDA and EPA advice for pregnant and breast-feeding women regarding seafood ingestion.60

Negative HBVSe = Harmful Positive HBVSe = Beneficial

HBVSe

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“We are now able to solve mercury related problems in fresh water bodies using natural, safe, and inexpensive approaches that better protect human and wildlife that eat fish from these lakes and rivers.” – Nicholas Ralston, PhD, University of North Dakota

Impact The HBVSe indicator provides a more reliable and objective index for assessing relative effects of exposures to methyl mercury. The indicator can help improve epidemiological and toxicological studies of methyl mercury by considering selenium, ingestion of which counteracts adverse effects of maternal methyl mercury exposures on selenium availability in fetal brains, thus contributing to improved health outcomes. The HBVSe indicator provides a reliable, easily understood, and consistent index for identifying healthy seafood choices. Application of the new indicator might enable many fresh water bodies in the U.S. to no longer be under restriction regarding mercury content of the fish caught there. The indicator also enhances how we respond to mercury risks where they do exist and helps to assess actual impacts of environmental risk management resolutions. The information is also important for freshwater fish from regions with selenium-poor soils. The indicator can be used for long-term tracking and surveillance of environmental public health, which will promote better-informed decisions and recommendations on fish consumption. The results of this and other of their work presented in two of their publications58,61, have been cited over 60 times by researchers in publications from 29 countries.

In addition, this research provided essential information captured in “Fish Issue Fact Sheets” (available at http://net- effects.und.edu/factsheets.aspx) developed to inform the public and clinicians and scientists about the benefits of eating fish and the importance of considering selenium as well as mercury content when evaluating exposures. Information from this project has also been shared with the United Nations’ Food and Agriculture Organization, at international meetings in Sweden, and with European food safety agencies in Brussels and Paris and groups in Spain. The HBVSe is rapidly becoming a risk assessment criterion for agencies around the world. Indicators of Exposure to Perfluorooctanoic Acid Perfluorooctanoic acid (PFOA) is an industrial chemical used to produce other perfluoroalkyl substances used in coatings that are stick- and stain-resistant, water-resistant coatings, food wrapping, firefighting foams, metal plating, semiconductors, photographics, and photolithographics. PFOA has been used widely in the past several decades and is very environmentally persistent. Because of this, PFOA and other perfluorinated chemicals, known as per- and polyfluoroalkyl substances (PFAS) are quite prevalent around the world and are detectable in living organisms, including humans. Concern over effects from PFOA exposures led to it being included on the most recent Contaminant Candidate List, CCL-4, under the Safe Drinking Water Act and finalized on November 17, 2016. This is a list of contaminants that are currently not subject to any national primary drinking water regulations, but are known or anticipated to occur in public water systems.62 There is evidence that exposure to PFAS can lead to adverse human health effects. The most consistent findings from human epidemiology studies are increased cholesterol levels (i.e., is hypercholesteremic) among exposed populations63. Abnormal levels of cholesterol in the blood are associated with the risk of heart disease. An EPHI grant to the University of Cincinnati and Harvard School of Public Health, led by Dr. Susan Pinney, investigated biological and exposure PFOA indicators in the mid-Ohio River Valley. This area is of concern due to historical industrial discharges of PFOA into the Ohio River, which contaminated water systems downstream. Results EPHI researchers measured perfluorinated chemical levels in preserved serum from three existing cohorts, one of which featured samples collected for 18 years (1991 to 2008).64 Human exposure to PFOA has occurred throughout the Mid-Ohio River Valley as indicated by serum concentrations above U.S. population levels in samples collected as early as 1991. The earliest serum samples (1991 to 2003) had the highest PFOA concentrations after adjusting for other factors.

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Serum PFOA levels were significantly associated with water source, sampling year, age at sampling, tap water consumption, pregnancy, gravidity, and breastfeeding.

Impact This study is the first to characterize serum concentrations of PFOA in samples obtained as early as 1991 with the benefit of study participant water supply source information. The results suggest that where serum PFOA was elevated in the mid-Ohio River Valley community, drinking water was a primary source of exposure. The EPHI research in combination with other research funding sources ultimately led to a revised water treatment practice in the Greater Cincinnati area. Evidence was accumulating that higher exposures to perfluorinated chemicals were occurring in the area. The researchers informed local water departments of the serum concentrations they had measured because of the EPHI grant. In response, by 2012 the Greater Cincinnati Water Works implemented granular activated carbon filtration at both their plants to meet new federal regulations and prepare for future regulations. They also considered the biomarker information in determining the appropriate frequency for reactivating their granular activated carbon filters.

“PFOA exposure to humans was widespread throughout the Mid-Ohio River Valley as indicated by serum concentrations above U.S. population levels in samples obtained as early as 1991. Drinking water from the Ohio River and Ohio River Aquifer, primarily contaminated by releases 209-666 kilometers upstream, is likely the primary exposure source.” – Susan Pinney, PhD, University of Cincinnati Waterborne Pathogen Indicators for Recreational Waters An estimated 87.2 million people visited U.S. beaches in 2003.65 A goal of the Clean Water Act is to ensure the nation’s waters are suitable for recreational activities. These activities include full contact activities such as swimming and snorkeling, and incidental contact activities such as boating, kayaking, and fishing. Recreation on our nation’s beaches is sometimes threatened by an overabundance of microbial pathogens that can lead to illness among beachgoers. The effects of beach closures can be particularly intense for some communities where the beach is an important source of tourism income for the local economy. An EPHI grant to University of Illinois at Chicago, MycoMetrics, and USGS Biological Resources Division, led by Dr. Samuel Dorevitch, identified microbial measures of water quality that could be used in beach monitoring to improve public health protection. Results The research team generated several important findings related to water quality indicators. . They evaluated microbial measures of water quality—including viruses (coliphages) and the protozoan pathogens Giardia and Cryptosporidium species—as predictors of gastrointestinal illness occurrence among recreators who had incidental contact with the water.66 They developed a novel estimate of exposure—the estimated dose of indicators and pathogens—that accounted for both volume of water ingested and density of microbes in water. The study determined that measures of water quality, for example, pathogen densities, were not useful as predictors of the occurrence of acute gastrointestinal illness. Compared to other secondary incidental activities, fishing appears to be associated with a higher risk of illness, possibly due to the additional microbes on bait and fish. They also observed an association between decreased incidence of illness and frequent use of a water recreation location and recreating without exposing the face to the water. . Prior epidemiological studies of water quality indicators and health have not considered severity of illness. To address this question, EPHI researchers evaluated measures as predictors of gastrointestinal illness severity among swimmers using data from the National Epidemiological and Environmental Assessment of Recreational Water (NEEAR) study and the Chicago Health Environmental Exposure and Recreation Study (CHEERS).67

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. They determined that a rapid water quality indicator method developed by EPA (enterococci DNA measured by quantitative polymerase chain reaction [qPCR]) predicted gastrointestinal illness severity better than conventional methods they evaluated.68 . The EPHI researchers also estimated costs of gastrointestinal illness attributable to water recreation (see Exhibit 13).69 They relied on data from the NEEAR and CHEERS studies.

“This grant research has led to significant improvements in water quality monitoring in the Chicago area. The public now receives information about hazardous levels of bacteria within a few hours, rather than the following day.” – Samuel Dorevitch, PhD, University of Illinois at Chicago Exhibit 13. Estimates of costs of gastrointestinal illness attributable to water recreation (2007 U.S. dollars).67 $1,676 for every 1,000-people engaged in swimming or wading at freshwater and marine beaches in six states (NEEAR study data). $1,220 for every 1,000-people engaged in incidental contact recreation including canoeing, kayaking, fishing, rowing, or paddling in the Chicago area (CHEERS study data).

Impact This EPHI project has several impressive impacts. The researchers completed the first epidemiological study of water recreation to evaluate measures of protozoan parasites as predictors of illness. They identified a superior water quality detection method that adds value as an environmental public health indicator for beach managers. The findings help focus efforts to reduce risk and associated costs, for example, education efforts about the hazards of swallowing water and promoting hand washing to decrease exposure in those who fish could decrease risk of gastrointestinal illness following incidental contact with recreational waters. The cost of illness information can be used to understand the benefits of beach monitoring programs, costs of improving stormwater and wastewater infrastructure, and other interventions to reduce the burden of illness associated with recreation in surface waters. The research led to implementation of an improved beach monitoring program for Chicago beaches. For many years the Chicago Park District used a culture method for E. coli testing. That method required at least 18 hours. The EPHI research focused on the evaluation of rapid methods, including the DNA-based qPCR method, which can generate results within hours. The Chicago Park District manages beaches that experience approximately 20 million visits per summer. They recognized that the qPCR method can generate results more quickly than the culture method. During the summers of 2015 and 2016, EPHI researchers started qPCR monitoring at the Chicago beaches. The program enables rapid notification of the public, both online and at beaches, about hazardous conditions (i.e., high levels of indicator bacteria). The information goes into a public data portal (https://data.cityofchicago.org/Parks-Recreation/Beach-Lab-Data/2ivx- z93u/about ) and is referred to as “DNA testing.” Multipathway Pollutant Exposure Indicators Contaminants that persist in the environment are a cause for concern due to the potential for exposure via multiple pathways—for example ingestion of drinking water and ingestion of food. Summarized here are two EPHI research examples that examined exposures that could arise from more than one exposure pathway.

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Arsenic Exposure Indicators Arsenic exposure continues to be a U.S. public health concern due to exposures through nonregulated sources. Inorganic arsenic is classified as a Group 1 human carcinogen and contamination of drinking water has been linked to cancers. Monitoring of arsenic in food has focused typically on total arsenic because arsenic in food is thought to be usually organic and not toxic. Knowledge of arsenic species in foods, however, is incomplete. Approximately one-quarter of commonly consumed foods in the U.S. contains measurable arsenic according to the U.S. Food and Drug Administration Total Diet Study. EPHI researchers, led by Dr. Jefferey Burgess, at the University of Arizona developed indicators evaluating the contribution of dietary sources of arsenic dose and methylation.

Results EPHI researchers analyzed data from four population studies—the National Human Exposure Assessment Survey (NHEXAS), Arizona, the Arizona Border Study (an extension of NHEXAS-Arizona), the Binational Arsenic Exposures Survey (BAsES), and the 2003–04 National Health and Nutrition Examination Survey (NHANES).70,71 Their models addressed person-specific data for intake of food, use of multiple sources of water for drinking and cooking, and concentrations of arsenic in urine, cooking and drinking water, and food samples (total and speciated arsenic where possible). They found that dietary total and inorganic arsenic intake, both measured and modeled, was a significant predictor of urinary total arsenic and was independent of household tap water arsenic concentrations either above or below the EPA maximum contaminant level (MCL) at that time of 10 ppb (see Exhibit 14).

Exhibit 14. Proportion of aggregate inorganic arsenic intake among non-seafood eaters attributable to food and water used for drinking and cooking, stratified by household tap water arsenic concentrations ≤10 ppb versus >10 ppb, in two study populations, NHEXAS-AZ and BAsES.71

Impact The research results from this EPHI grant demonstrated that food is the primary source of exposure to inorganic and total arsenic in most U.S. populations. These results might have influenced federal action levels for arsenic in rice, rice products, apple juice, and other foods. Arsenic measured directly from food was found to be a better predictor of urinary arsenic levels than modeled dietary arsenic estimates. Identifying the contributions of food, drinking water, and cooking water to arsenic exposure provides important information needed to assess arsenic risks and establish protective policies. 31 DRAFT EPHI Impact Report – March 2018

According to Web of Science, these two publications have been referenced a combined total of 36 times by citations representing 16 countries (retrieved March 2018).

“This research also showed an independent relationship between dietary inorganic arsenic and a biomarker linked to adverse health (MMP-9) in populations with low levels of arsenic in drinking water (below 3 ppb). This is a novel finding that emphasizes the importance of further research on potential adverse effects of arsenic exposure from food.” – Jefferey L. Burgess, PhD, University of Arizona Organochlorine Exposure and Type 2 Diabetes Indicators The Mississippi Delta is a highly rural area with a history of intense agriculture. It suffers from high poverty and shortages of health professionals. An EPHI grant to Mississippi State University, led by Dr. Janice Chambers, researched an association between exposure to organochlorine (OC) insecticides and type 2 diabetes. The Mississippi Delta region was selected because of the historical use of high levels of OC insecticides and the prevalence of Type 2 diabetes among the population in that region.

Results The EHPI researchers worked to develop and use a new indicator to study linkage between soil residues of organochlorine insecticides, levels of their stable metabolites/degradants in people, and the occurrence of type 2 diabetes. Organochlorine pesticides were heavily used for agriculture in the 1950s and 1960s. Residues of DDE—a stable metabolite of DDT—are found in the U.S. and worldwide. The project focused on the levels of DDE, the persistent metabolite of the heavily used insecticide DDT. The researchers sampled soils and blood levels of DDE in two areas of Mississippi, the Mississippi Delta and a nonagricultural area that would have had a much lower use of DDT and has a lower prevalence of type 2 diabetes (the non-Delta). 72

What is diabetes?

Diabetes is a chronic disease that affects how the body turns food into energy.73 Most food is broken down into sugar (also called glucose) and released into the bloodstream. The pancreas makes a hormone called insulin, which lets blood sugar into cells to use as energy. People with diabetes either do not make enough insulin or cannot use insulin as effectively. When enough insulin is not available or cells stop responding to insulin, the concentration of sugar in the blood stream can be too high. Too much blood sugar over time can cause serious health problems, such as heart disease, vision loss, and kidney disease.

Type 1 diabetes is caused by an autoimmune reaction (the body attacks itself by mistake) that stops the body from making insulin. About 5% of the people who have diabetes have type 1.

With Type 2 diabetes, the body does not use insulin well and cannot keep blood sugar at normal levels. Most people with diabetes—9 in 10—have type 2 diabetes. It develops over many years and is usually diagnosed in adults, although increasingly in children, teens, and young adults.

The prevalence of type 2 diabetes increased in Mississippi from 9.5% to 12.3% from 2004 to 2008.

The U.S. prevalence of type 2 diabetes is 7.7%; in Mississippi it is 13.1%.

The researchers collected and analyzed soil samples. They found 10-times higher DDE levels in the Delta soil samples compared to the non-Delta soils (see Exhibit 15). They analyzed blood samples and found about 1.5-fold higher blood levels of DDE in the Delta study sample than in the non-Delta study sample. They found statistical associations between higher levels of DDE and type 2 diabetes in the non-Delta study sample but not, however, in the Delta study sample, counter to expectations. They also discovered that African Americans had higher blood DDE levels than Caucasians, 32 DRAFT EPHI Impact Report – March 2018

which could be informative for future research identifying risk factors involved in the multiple health disparities observed in African Americans.

Exhibit 15. Patterns of DDE concentrations in Mississippi.72

Impact The Mississippi Delta population is unique from the standpoint of environmental sampling. The measurements will add appreciably to the global literature that currently suggests that organochlorine compound levels are biomarkers of type 2 diabetes risk. The data indicate the potential value of DDE as a biomarker of type 2 diabetes risk for people who were exposed to low or moderate levels of DDT/DDE and could have utility in identifying those individuals who should be targeted for extra lifestyle adjustments for maintaining health. DDE does not appear appropriate, however, as a biomarker in highly exposed populations. The project has been delayed to comply with important Institutional Review Board requirements, and manuscripts for submission to peer-reviewed journals are in preparation.

“This research has identified the organochlorine compound DDE (the bioaccumulative metabolite of the insecticide DDT) as a potential biomarker of risk (environmental public health indicator) for type 2 diabetes in people who were exposed to only low or moderate levels of DDT/DDE and may have utility in identifying those individuals who should be targeted for extra lifestyle adjustments for maintaining health. However, DDE cannot serve as a biomarker in highly exposed populations.” – Janice Chambers, PhD, Mississippi State University Other Stressor Exposure and Health Outcome Indicators Two non-chemical environmental stressor indicators tremendously important to community health were investigated by EPHI program grants—pollen and heat. The research identified indicators linking these stressors with health effects, which led to improved guidance to prevent disease and death. 33 DRAFT EPHI Impact Report – March 2018

Pollen Exposure and Allergic Disease Indicators EPHI researchers at Mount Sinai School of Medicine collaborated with EPHI investigators led by Dr. Kazuhiko at the New York School of Medicine to investigate the association between pollen levels and population health behaviors.

Results EPHI researchers focused on assessing the association between peaks in daily tree pollen concentrations and over-the-counter allergy medication sales over a six-year period in New York City.74 The study used a new minor illness surveillance approach incorporating a more direct indicator of allergic disease that could capture the burden of illness more accurately. The allergy medication sales align with tree pollen peaks (Exhibit 16).

Impact By following maple, oak, and birch tree pollen peaks, health departments can anticipate allergic responses and improve public health advisories. Used in combination with meteorological forecast models, the indicator will facilitate the creation of more specific pollen season charts and inform future projections of pollen-related morbidity. In 2013, the New York City Department of Health and Mental Hygiene issued a health advisory to medical providers citing this EPHI research. The City continues to provide health advisories that alert providers of the increased risk of pollen’s exacerbation of asthma in sensitive patients. Exhibit 16. Time-series plot of daily allergy medication sales; superimposed lines are dates of tree pollen peaks color coded by tree type.74

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Heat-related Excess Mortality Indicators Approximately 618 people in the U.S. are killed by extreme heat every year.75 Older adults, the very young, and people with chronic medical condition are at highest risk. However, even young and healthy people can be affected if they participate in strenuous physical activities during hot weather or fail to adequately hydrate. Deaths from heat are not available for timely surveillance during heat waves. The EPHI grant to the New York School of Medicine and New York City Department of Health and Mental Hygiene, led by Dr. Kazuhiko Ito, developed improved indicators of heat-related illness.

Results EPHI researchers investigated associations among daily weather conditions, heat-related ambulance calls and ED visits, and excess natural-cause mortality in New York City.76 They analyzed data for May to September between 1999 and 2008. They observed that an 11% increase in natural-cause mortality was associated with an increase from the 50th percentile to 99th percentile of same-day and one-day later heat-related emergency medical system calls and ED visits, respectively. The study confirmed that tracking heat-related illness during heat waves using these syndromic-surveillance indicators predict associated excess natural-cause mortality better than weather variables alone.

Impact The study results contributed to the revision (i.e., lowering) of the National Weather Service heat advisory threshold temperature for New York City. The guidance instructs that a Heat Advisory is issued when the heat index is forecast to reach 95 to 99 degrees F for at least two consecutive days or 100 to 104 degrees F for any length of time.77

“The output from this project became useful for New York City Department of Health’s policies for air pollution, weather, and pollen.” – Kazuhiko Ito, PhD, New York School of Medicine

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For More Information

A searchable database of EPA STAR grant information, including publications and annual and final reports for the EPHI grants is available at https://cfpub.epa.gov/ncer_abstracts/index.cfm/fuseaction/search.welcome. These EPHI grants are associated with the following EPA STAR grant requests for applications (RFAs): • Development of Environmental Health Outcome Indicators (2006) • Development of Environmental Health Outcome Indicators (2007) • Exploring Linkages Between Health Outcomes and Environmental Hazards, Exposures, and Interventions for Public Health Tracking and Risk Management (2009) These EPHI grants were supported through EPA’s Sustainable and Healthy Communities Research Program- a customer-oriented, interdisciplinary research program that engages in direct communication with both internal Agency partners and external stakeholders at the state and local (community) level to match scientific and technical expertise with place-based environmental and related public health challenges. The program’s focus is to provide the solutions, tools, and other decision-support resources needed to meet Agency and partner statutory obligations, accelerate the pace of contaminated site clean ups, and advance the understanding of the links between environmental quality, public health, and human well-being. The largest and most diverse national research program within EPA’s Office of Research and Development, the program includes research in three broad categories: (1) technical and scientific support to clean up and remediate contaminated sites; (2) understanding the flow of materials in order to reduce the generation of waste and/or develop beneficial uses of waste; and (3) the development of solutions to revitalize communities impacted by contaminated sites and those effected by natural disasters. The heart of the program is the recognition that innovative, interdisciplinary environmental and public health research can be done in ways that deliver solutions to the most pressing needs of our customers and partners while simultaneously helping states and local communities align a healthy environment with sustained economic growth, public health, and human well-being. For more information, visit https://www.epa.gov/aboutepa/about-sustainable-and-healthy-communities-research- program. EPA has researched and developed a wide array of environmental and public health indicators. Examples include: • Report on Environment https://cfpub.epa.gov/roe/ • America’s Children and the Environment https://www.epa.gov/ace • Climate Change Indicators https://www.epa.gov/climate-indicators

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Appendix A. EPHI Grants The original abstract, annual reports, and final reports for these grants can be found by searching on the EPA’s Grantee Research Project Results website at: https://cfpub.epa.gov/ncer_abstracts/index.cfm/fuseaction/search.welcome

EPA GRANT TITLE PRINCIPAL INSTITUTIONS GRANT INVESTIGATORS & CO- AMOUNT GRANT INVESTIGATORS NUMBER R833622 Statistical Models for Estimating Francesca Dominici Harvard T.H. Chan $500,000 the Health Impact of Air Quality Roger D. Peng School of Public Regulations Marta Rava Health, The Johns Jonathan M. Samet Hopkins University Ronald H. White Scott L. Zeger R833623 Near Real Time Modeling of Kazuhiko Ito New York University $494,552 Weather, Air Pollution, and Health Robert Mathes School of Medicine, Outcome Indicators in New York Thomas Matte New York City City Kristina Metzger Department of Arthur Nadas Health and Mental George D. Thurston Hygiene R833624 Impact of Emission Reductions on Julian D. Marshall University of $459,556 Exposures and Exposure Gurumurthy Minnesota School of Distributions: Application of a Ramachandran Public Health Geographic Exposure Model R833626 Development and Assessment of Armistead G. Russell Georgia Institute of $499,512 Environmental Indicators: Lyndsey Darrow Technology, Emory Application to Mobile Source Mitchel Klein University Impacts on Emissions, Air Quality James Mulholland and Health Outcomes Jorge Pachon Jeremy Sarnat Stefanie Ebelt Sarnat Paige Tolbert R833627 Measuring the Impact of Jean Johnson Minnesota $488,650 Particulate Matter Reductions by Greg Pratt Department of

Environmental Health Outcome Barbara Yawn Health, Minnesota Indicators Pollution Control

Agency, Olmsted Medical Center

R833628 The Detroit Asthma Morbidity, Air Robert L Wahl Michigan $499,777 Quality and Traffic (DAMAT) Study Stuart A. Batterman Department of Lorraine Cameron Community Health, Michael Depa Michigan State Kevin Dombkowski University, School of Erika Garcia Public Health and Mary Lee Hultin College of Anna Michalak Engineering, Bhramar Mukherjee University of Elizabeth Wasilevich Michigan Julie Wirth

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EPA GRANT TITLE PRINCIPAL INSTITUTIONS GRANT INVESTIGATORS & CO- AMOUNT GRANT INVESTIGATORS NUMBER R833629 Development of Exposure and Ying-Ying Meng University of $500,000 Health Outcome Indicators for Michael Jerrfett California - Los Those with Asthma or Other Beate R. Ritz Angeles, University Respiratory Problems Michelle Wilhelm of California - Berkeley

R833990 Novel Markers of Air Pollution- Matthew J. Campen Lovelace Biomedical $500,000 induced Vascular Toxicity Amie K. Lund & Environmental Research Institute, University of New Mexico

R833991 Longitudinal Indicators of Policy Thomas A. Burke The Johns Hopkins $499,961 Impact on Pollution, Exposure and Mary A. Fox University Health Risk

R833992 Modeling Dietary Contributions to Jefferey L. Burgess Mel and Enid $499,999 Arsenic Dose and Methylation: Robin B. Harris Zuckerman College Elucidating Predictive Linkages Paul Hsu of Public Health, M. Elena Martinez University of Mary Kay O'Rourke Arizona

R834786 Novel Immunological Approaches Kari Nadeau Stanford University $250,000 to Link Ambient Air Pollution Exposure to Health Outcomes

R834787 Assess the Linkage Between Shao Lin The State University $500,000 School-Related Environment, Syni-An Hwang of New York at Children's School Albany, New York Performance/Health, and State Department of Environmental Policies Through Health Environmental Public Health Tracking

R834788 PFOA Concentration in Serum Susan M. Pinney University of $499,980 Collected 1991-2008 and Related Frank M. Biro Cincinnati Health Effects Robert Bornschein Robert L. Herrick Paul Succop R834789 Rapidly Measured Indicators of Samuel Dorevitch University of Illinois $499,831 Waterborne Pathogens Rebecca N Bushon at Chicago, Salvatore Cali MycoMetrics, USGS King-Teh Lin Biological Resources Li Liu Division Peter Scheff

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EPA GRANT TITLE PRINCIPAL INSTITUTIONS GRANT INVESTIGATORS & CO- AMOUNT GRANT INVESTIGATORS NUMBER R834790 Air Pollution-Exposure-Health F. Benjamin Zhan Texas State $499,987 Effect Indicators: Mining Massive Jean D. Brender University, Texas A Geographically-Referenced Peter H. Langlois & M Health Science Environmental Health Data to Jing Yang Center, Texas Identify Risk Factors for Birth Department of State Defects Health Services, University of North Carolina at Charlotte R834791 Tribal Environmental Public Health Jamie Donatuto Swinomish Indian $235,517 Indicators Larry Campbell Tribal Community

R834792 Fish Selenium Health Benefit Nicholas V.C. Ralston University of North $490,089 Values in Mercury Risk Laura Raymond Dakota Management

R834793 Using Vital Statistics Natality Data Janet Currie Princeton University $492,103 to Assess the Impact of Environmental Policy: The Examples of Superfund, the Toxic Release Inventory, and E-ZPass

R834794 Development and Validation of Sid E. O'Bryant Texas Tech $482,900 the Cumulative Environmental Gordon Gong University Health Exposure Index for Arsenic: A Leigh Johnson Sciences Center, Novel Environmental Public Health Kevin R. Mulligan University of North Indicator Yan Zhang Texas - Health Science Center at Ft Worth, Texas Tech University

R834795 New Environmental Public Health Janice E. Chambers Mississippi State $500,000 Indicator Linking Organochlorine John Allen Crow University - Main Compounds and Type 2 Diabetes Matthew K. Ross Campus Robert W. Wills

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Appendix B. Publications Attributed to EPHI Grants Aggarwal, S., Jain, R., & Marshall, J. D. (2012). Correction to real-time prediction of size-resolved ultrafine PM on freeways. ENVIRONMENTAL SCIENCE & TECHNOLOGY, 46(13), 7431-7432. doi:10.1021/es301825v Aggarwal, S., Jain, R., & Marshall, J. D. (2012). Real-time prediction of size-resolved ultrafine PM on freeways. ENVIRONMENTAL SCIENCE & TECHNOLOGY, 46(4), 2234-2241. doi:10.1021/es203290p Barr, C. D., Diez, D. M., Wang, Y., Dominici, F., & Samet, J. M. (2012). Comprehensive Smoking Bans and Acute Myocardial Infarction Among Medicare Enrollees in 387 US Counties: 1999–2008. AMERICAN JOURNAL OF EPIDEMIOLOGY, 176(7), 642-648. doi:10.1093/aje/kws267 Barr, C. D., & Dominici, F. (2010). Cap and trade legislation for greenhouse gas emissions: public health benefits from air pollution mitigation. JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 303(1), 69-70. doi:doi: 10.1001/jama.2009.1955 Batterman, S. A., Zhang, K., & Kononowech, R. (2010). Prediction and analysis of near-road concentrations using a reduced-form emission/dispersion model. Environmental Health, 9, 29. doi:doi: 10.1186/1476-069X-9-29. Bell, M. L., Ebisu, K., Peng, R. D., Walker, J., Samet, J. M., Zeger, S. L., & Dominici, F. (2008). Seasonal and regional short- term effects of fine particles on hospital admissions in 202 US counties, 1999-2005. AMERICAN JOURNAL OF EPIDEMIOLOGY, 168(11), 1301-1310. doi:doi: 10.1093/aje/kwn252 Bobb, J. F., Dominici, F., & Peng, R. D. (2011). A Bayesian Model Averaging Approach for Estimating the Relative Risk of Mortality Associated with Heat Waves in 105 U.S. Cities. Biometrics, 67(4), 1605-1616. doi:10.1111/j.1541- 0420.2011.01583.x Brender, J. D., Shinde, M. U., Zhan, F. B., Gong, X., & Langlois, P. H. (2014). Maternal residential proximity to chlorinated solvent emissions and birth defects in offspring: a case-control study. Environmental Health, 13, 96. doi:doi: 10.1186/1476-069X-13-96 Breslow, S. J., Sojka, B., Barnea, R., Basurto, X., Carothers, C., Charnley, S., . . . Levin, P. S. (2016). Conceptualizing and operationalizing human wellbeing for ecosystem assessment and management. Environmental Science & Policy, 66, 250-259. doi: 10.1016/j.envsci.2016.06.023 Campen, M., Lund, A., & Rosenfeld, M. (2012). Mechanisms linking traffic-related air pollution and atherosclerosis. CURRENT OPINION IN PULMONARY MEDICINE, 18(2), 155-160. doi:10.1097/MCP.0b013e32834f210a Chang, H. H., Peng, R. D., & Dominici, F. (2011). Estimating the acute health effects of coarse particulate matter accounting for exposure measurement error. BIOSTATISTICS. doi:10.1093/biostatistics/kxr002 Channell, M., Paffett, M., Devlin, R., Madden, M., & Campen, M. (2012). Circulating factors induce coronary endothelial cell activation following exposure to inhaled diesel exhaust and nitrogen dioxide in humans: evidence from a novel translational in vitro model. Toxicological Sciences, 127(1), 179-186. doi:10.1093/toxsci/kfs084 Currie, J. (2011). Inequality at birth: some causes and consequences. AMERICAN ECONOMIC REVIEW, 101(3), 1-22. doi:DOI: 10.1257/aer.101.3.1 Currie, J. (2013). Pollution and infant health. Child Development Perspectives, 7(4), 237-242. doi:10.1111/cdep.12047 Currie, J., Davis, L., Greenstone, M., & Walker, R. (2015). Environmental health risks and housing values: evidence from 1,600 toxic plant openings and closings. AMERICAN ECONOMIC REVIEW, 105(2), 678-709. doi:10.1257/aer.20121656 Currie, J., Graff, Z., JS, Meckel, K., Neidell, M., & Schlenker, W. (2013). Something in the water: contaminated drinking water and infant health. Canadian Journal of Economics, 46(3), 791-810. doi:10.1111/caje.12039 Currie, J., Greenstone, M., & Moretti, E. (2011). Superfund cleanups and infant health. AMERICAN ECONOMIC REVIEW, 101(3), 435-441. doi:10.1257/aer.101.3.435 Currie, J., Ray, S., & Neidell, M. (2011). Quasi-experimental studies suggest that lowering air pollution levels benefits infants' and children's health. Health Affairs, 30(12), 2391-2399. doi:10.1377/hlthaff.2011.0212 Currie, J., & Schwandt, H. (2015). The 9/11 dust cloud and pregnancy outcomes: a reconsideration. The Journal of Human Resources, 51(4), 805-831. doi:10.3368/jhr.51.4.0714-6533R Currie, J., Zivin, J., Mullen, J., & Neidell, M. (2014). What do we know about short- and long-term effects of early-life exposure to pollution? ANNUAL REVIEW OF RESOURCE ECONOMICS, 6(1), 217-247. doi:10.1146/annurev- resource-100913-012610 Darrow, L. A., Klein, M., Sarnat, J. A., Mulholland, J. A., Strickland, M. J., Sarnat, S. E., . . . Tolbert, P. E. (2011). The use of alternative pollutant metrics in time-series studies of ambient air pollution and respiratory emergency department visits. J Expos Sci Environ Epidemiol, 21(1), 10-19. doi:10.1038/jes.2009.49

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DeFlorio-Barker, S., Wade, T. J., Jones, R. M., Friedman, L. S., Wing, C., & Dorevitch, S. (2016). Estimated Costs of Sporadic Gastrointestinal Illness Associated with Surface Water Recreation: A Combined Analysis of Data from NEEAR and CHEERS Studies. Environ Health Perspect, in press. doi:10.1289/EHP130 DeFlorio-Barker, S., Wade, T. J., Turyk, M., & Dorevitch, S. (2016). Water recreation and illness severity. Journal of Water and Health, 14(5), 713-726. doi:10.2166/wh.2016.002 Dominici, F., Peng, R., Zeger, S., White, R., & Samet, J. (2007). Particulate air pollution and mortality in the United States: did the risks change from 1987 to 2000? AMERICAN JOURNAL OF EPIDEMIOLOGY, 166(8), 880-888. doi:10.1093/aje/kwm222 Donatuto, J., Campbell, L., & Gregory, R. (2016). Developing Responsive Indicators of Indigenous Community Health. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 13(9), 899. doi:10.3390/ijerph13090899 Donatuto, J., Grossman, E., Konovsky, J., Grossman, S., & Campbell, L. (2014). Indigenous community health and climate change: integrating biophysical and social science indicators. COASTAL MANAGEMENT, 42(4), 355-372. doi:10.1080/08920753.2014.923140 Dorevitch, S., DeFlorio-Barker, S., Jones, R. M., & Liu, L. (2015). Water quality as a predictor of gastrointestinal illness following incidental contact water recreation. Water Research, 83, 94-103. doi: 10.1016/j.watres.2015.06.028 Edwards, M., Hall, J., Gong, G., & O’Bryant, S. E. (2014). Arsenic exposure, AS3MT polymorphism, and neuropsychological functioning among rural dwelling adults and elders: a cross-sectional study. Environmental Health, 13(1), 15. doi:doi: 10.1186/1476-069X-13-15 Edwards, M., Johnson, L., Mauer, C., Barber, R., Hall, J., & O’Bryant, S. (2014). Regional specific groundwater arsenic levels and neuropsychological functioning: a cross-sectional study. International Journal of Environmental Health Research, 24(6), 546-557. doi:10.1080/09603123.2014.883591 Eftim, S. E., Samet, J. M., Janes, H., McDermott, A., & Dominici, F. (2008). Fine particulate matter and mortality: a comparison of the six cities and American Cancer Society cohorts with a medicare cohort. Epidemiology, 19(2), 209-216. doi:10.1097/EDE.0b013e3181632c09 Falkowski, J., Atchison, T., DeButte-Smith, M., Weiner, M. F., & O'Bryant, S. (2014). Executive Functioning and the Metabolic Syndrome: A Project FRONTIER Study. Archives of Clinical Neuropsychology, 29(1), 47-53. doi:10.1093/arclin/act078 Flanders, W. D., Klein, M., Darrow, L. A., Strickland, M. J., Sarnat, S. E., Sarnat, J. A., . . . Tolbert, P. E. (2011). A Method for Detection of Residual Confounding in Time-series and Other Observational Studies. Epidemiology, 22(1), 59-67. doi:10.1097/EDE.0b013e3181fdcabe Flanders, W. D., Klein, M., Darrow, L. A., Strickland, M. J., Sarnat, S. E., Sarnat, J. A., . . . Tolbert, P. E. (2011). A Method to Detect Residual Confounding in Spatial and Other Observational Studies. Epidemiology, 22(6), 823-826. doi:10.1097/EDE.0b013e3182305dac Fox, M. A., Sheehan, M. C., & Burke, T. A. (2015). A risk assessment approach for policy evaluation: New Jersey case studies. HUMAN AND ECOLOGICAL RISK ASSESSMENT, 21(8), 2258-2272. doi:DOI:10.1080/10807039.2015.1046982 Gilman, C. L., Soon, R., Sauvage, L., Ralston, N. V. C., & Berry, M. J. (2015). Umbilical cord blood and placental mercury, selenium and selenoprotein expression in relation to maternal fish consumption. Journal of Trace Elements in Medicine and Biology, 30, 17-24. doi:http://dx.doi.org/10.1016/j.jtemb.2015.01.006 Gong, G., Hargrave, K., Hobson, V., Spallholz, J., Boylan, M., Lefforge, D., & O'Bryant, S. (2011). Low-level groundwater arsenic exposure impacts cognition: a Project FRONTIER study. JOURNAL OF ENVIRONMENTAL HEALTH, 74(2), 16-23. Gong, G., Mattevada, S., & O’Bryant, S. E. (2014). Comparison of the accuracy of kriging and IDW interpolations in estimating groundwater arsenic concentrations in Texas. ENVIRONMENTAL RESEARCH, 130, 59-69. doi:http://dx.doi.org/10.1016/j.envres.2013.12.005 Gong, G., & O'Bryant, S. (2012). Low level arsenic exposure, AS3MT gene polymorphism and cardiovascular diseases in rural Texas counties. ENVIRONMENTAL RESEARCH, 113, 52-57. doi:10.1016/j.envres.2012.01.003 Gong, X., Zhan, F. B., Brender, J. D., Langlois, P. H., & Lin, Y. (2016). Validity of the Emission Weighted Proximity Model in estimating air pollution exposure intensities in large geographic areas. Science of The Total Environment, 563– 564, 478-485. doi:10.1016/j.scitotenv.2016.04.088 Greven, S., Dominici, F., & Zeger, S. (2011). An Approach to the Estimation of Chronic Air Pollution Effects Using Spatio- Temporal Information. Journal of the American Statistical Association, 106(494), 396-406. doi:10.1198/jasa.2011.ap09392

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Hall, J., Edwards, M., Barber, R., Johnson, L., Gong, G., & O'Bryant, S. E. (2012). Higher groundwater selenium exposure is associated with better memory: a Project FRONTIER study. NEUROSCIENCE & MEDICINE, 3(1), 18-25. doi:doi: 10.4236/nm.2012.31004 Herrick, R. L., Buckholz, J., Biro, F. M., Calafat, A. M., Ye, X. Y., Xie, C. C., & Pinney, S. M. (2017). Polyfluoroalkyl substance exposure in the Mid-Ohio River Valley, 1991-2012. Environmental Pollution, 228, 50-60. doi:10.1016/j.envpol.2017.04.092 Hew, K. M., Walker, A. I., Kohli, A., Garcia, M., Syed, A., McDonald-Hyman, C., . . . Nadeau, K. C. (2015). Childhood exposure to ambient polycyclic aromatic hydrocarbons is linked to epigenetic modifications and impaired systemic immunity in T cells. Clinical & Experimental Allergy, 45(1), 238-248. doi:10.1111/cea.12377 Hew, K. M., Walker, A. I., Kohli, A., Garcia, M., Syed, A., McDonald-Hyman, C., . . . Nadeau, K. C. (2015). Childhood exposure to ambient polycyclic aromatic hydrocarbons is linked to epigenetic modifications and impaired systemic immunity in T cells. Clinical and Experimental Allergy, 45(1), 238-248. doi:10.1111/cea.12377 Ito, K., Mathes, R., Ross, Z., Nadas, A., Thurston, G., & Matte, T. (2011). Fine particulate matter constituents associated with cardiovascular hospitalizations and mortality in New York City. ENVIRONMENTAL HEALTH PERSPECTIVES, 119(4), 467-473. doi:10.1289/ehp.1002667 Janes, H., Dominici, F., & Zeger, S. (2007). Partitioning evidence of association between air pollution and mortality. Epidemiology, 18(4), 427-428. doi:10.1097/EDE.0b013e318068647b Janes, H., Dominici, F., & Zeger, S. (2010). On quantifying the magnitude of confounding. BIOSTATISTICS, 11(3), 572-582. doi:10.1093/biostatistics/kxq007 Janes, H., Dominici, F., & Zeger, S. L. (2007). Trends in air pollution and mortality: an approach to the assessment of unmeasured confounding. Epidemiology, 18(4), 416-423. doi:10.1097/EDE.0b013e31806462e9 Johnson, L. A., Cushing, B., Rohlfing, G., Edwards, M., Davenloo, H., D'Agostino, D., . . . O'Bryant, S. E. (2014). The Hachinski Ischemic Scale and cognition: the influence of ethnicity. Age and Ageing, 43(3), 364-369. doi:10.1093/ageing/aft189 Johnson, L. A., Gamboa, A., Vintimilla, R., Edwards, M., Hall, J., Weiser, B., . . . O'Bryant, S. E. (2016). A Depressive Endophenotype for Predicting Cognitive Decline among Mexican American Adults and Elders. Journal of Alzheimer's Disease, 54(1), 201-206. doi:10.3233/JAD-150743 Johnson, L. A., Hall, J. R., & O’Bryant, S. E. (2013). A Depressive Endophenotype of Mild Cognitive Impairment and Alzheimer’s Disease. PLOS ONE, 8(7), e68848. doi:10.1371/journal.pone.0068848 Johnson, L. A., Phillips, J. A., Mauer, C., Edwards, M., Balldin, V. H., Hall, J. R., . . . O'Bryant, S. E. (2013). The impact of GPX1 on the association of groundwater selenium and depression: a Project FRONTIER study. BMC PSYCHIATRY, 13, 7. doi:doi: 10.1186/1471-244X-13-7 Kielb, C., Lin, S., Muscatiello, N., Hord, W., Rogers-Harrington, J., & Healy, J. (2015). Building-related health symptoms and classroom indoor air quality: a survey of school teachers in New York State. INDOOR AIR, 25(4), 371-380. doi:10.1111/ina.12154 Kodavanti, U. P., Thomas, R., Ledbetter, A. D., Schladweiler, M. C., Shannahan, J. H., Wallenborn, J. G., . . . Parinandi, N. L. (2011). Vascular and cardiac Impairments in rats inhaling ozone and diesel exhaust particles. ENVIRONMENTAL HEALTH PERSPECTIVES, 119(3), 312-318. doi:doi: 10.1289/ehp.1002386 Kohli, A., Garcia, M. A., Miller, R. L., Maher, C., Humblet, O., Hammond, S. K., & Nadeau, K. (2012). Secondhand smoke in combination with ambient air pollution exposure is associated with increased CpG methylation and decreased expression of IFN-γ in T effector cells and Foxp3 in T regulatory cells in children. Clinical Epigenetics, 4(1), 17. doi:doi: 10.1186/1868-7083-4-17 Kurzius-Spencer, M., Burgess, J. L., Harris, R. B., Hartz, V., Roberge, J., Huang, S., . . . O'Rourke, M. K. (2014). Contribution of diet to aggregate arsenic exposures[mdash]An analysis across populations. J Expos Sci Environ Epidemiol, 24(2), 156-162. doi:10.1038/jes.2013.37 Kurzius-Spencer, M., Harris, R. B., Hartz, V., Roberge, J., Hsu, C.-H., O'Rourke, M. K., & Burgess, J. L. (2016). Relation of dietary inorganic arsenic to serum matrix metalloproteinase-9 (MMP-9) at different threshold concentrations of tap water arsenic. J Expos Sci Environ Epidemiol, 26(5), 445-451. doi:10.1038/jes.2014.92 Kurzius-Spencer, M., O'Rourke, M. K., Hsu, C.-H., Hartz, V., Harris, R. B., & Burgess, J. L. (2013). Measured versus modeled dietary arsenic and relation to urinary arsenic excretion and total exposure. J Expos Sci Environ Epidemiol, 23(4), 442-449. doi:10.1038/jes.2012.120 Lee, D., Balachandran, S., Pachon, J., Shankaran, R., Lee, S., Mulholland, J., & Russell, A. (2009). Ensemble-trained PM2.5 source apportionment approach for health studies. ENVIRONMENTAL SCIENCE & TECHNOLOGY, 43(18), 7023- 7031. doi:10.1021/es9004703

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Li, S., Batterman, S., Wasilevich, E., Elasaad, H., Wahl, R., & Mukherjee, B. (2011). Asthma exacerbation and proximity of residence to major roads: a population-based matched case-control study among the pediatric Medicaid population in Detroit, Michigan. Environmental Health, 10, 34. doi:doi: 10.1186/1476-069X-10-34 Li, S., Batterman, S., Wasilevich, E., Wahl, R., Wirth, J., Su, F.-C., & Mukherjee, B. (2011). Association of daily asthma emergency department visits and hospital admissions with ambient air pollutants among the pediatric Medicaid population in Detroit: time-series and time-stratified case-crossover analyses with threshold effects. ENVIRONMENTAL RESEARCH, 111(8), 1137-1147. doi:doi: 10.1016/j.envres.2011.06.002 Li, S., Mukherjee, B., & Batterman, S. (2012). Point source modeling of matched case-control data with multiple disease subtypes. Statistics in Medicine, 30(28), 3617-3637. doi:doi: 10.1002/sim.5388 Li, S., Mukherjee, B., Batterman, S., & Ghosh, M. (2013). Bayesian Analysis of Time-Series Data under Case-Crossover Designs: Posterior Equivalence and Inference. Biometrics, 69(4), 925-936. doi:10.1111/biom.12102 Lin, S., Jones, R., Munsie, J. P., Nayak, S., Fitzgerald, E. F., & Hwang, S. (2012). Childhood asthma and indoor allergen exposure and sensitization in Buffalo, New York. INTERNATIONAL JOURNAL OF HYGIENE AND ENVIRONMENTAL HEALTH, 215(3), 297-305. doi:doi: 10.1016/j.ijheh.2011.08.017 Lin, S., Jones, R., Pantea, C., Ozkaynak, H., Rao, S. T., Hwang, S. A., & Garcia, V. C. (2013). Impact of NOx emissions reduction policy on hospitalizations for respiratory disease in New York State. JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY, 23(1), 73-80. doi:doi: 10.1038/jes.2012.69 Lin, S., Kielb, C. L., Reddy, A. L., Chapman, B. R., & Hwang, S. A. (2012). Comparison of indoor air quality management strategies between the school and district levels in New York State. JOURNAL OF SCHOOL HEALTH, 82(3), 139- 146. doi:doi: 10.1111/j.1746-1561.2011.00677.x Lindgren, P., Johnson, J., Williams, A., Yawn, B., & Pratt, G. C. (2016). Asthma exacerbations and traffic: examining relationships using link-based traffic metrics and a comprehensive patient database. Environ Health, 15(1), 102. doi:10.1186/s12940-016-0184-2 Liu, J., Zhang, L., Winterroth, L. C., Garcia, M., Weiman, S., Wong, J. W., . . . Nadeau, K. C. (2013). Epigenetically mediated pathogenic effects of phenanthrene on regulatory T cells. Journal of Toxicology, 2013(2013), 967029. doi:doi: 10.1155/2013/967029 Lund, A. K., Melanie Doyle-Eisele, Ying-Hsuan Lin, Maiko Arashiro, Jason D. Surratt, Tom Holmes, Katherine A. Schilling, John H. Seinfeld, Annette C. Rohr, Eladio M. Knipping, Jacob D. McDonald (2013). The effects of α-pinene versus toluene-derived secondary organic aerosol exposure on the expression of markers associated with vascular disease. Inhalation Toxicology, 25(6), 309-324. doi:10.3109/08958378.2013.782080 Lund, A. K., Doyle-Eisele, M., Lin, Y.-H., Arashiro, M., Surratt, J. D., Holmes, T., . . . McDonald, J. D. (2013). The effects of α- pinene versus toluene-derived secondary organic aerosol exposure on the expression of markers associated with vascular disease. Inhalation Toxicology, 25(6), 309-324. doi:10.3109/08958378.2013.782080 Lund, A. K., Lucero, J., Harman, M., Madden, M. C., McDonald, J. D., Seagrave, J. C., & Campen, M. J. (2011). The oxidized low-density lipoprotein receptor mediates vascular effects of inhaled vehicle emissions. American Journal of Respiratory and Critical Care Medicine, 184(1), 82-91. doi:doi: 10.1164/rccm.201012-1967OC Maier, M. L., Balachandran, S., Sarnat, S. E., Turner, J. R., Mulholland, J. A., & Russell, A. G. (2013). Application of an Ensemble-Trained Source Apportionment Approach at a Site Impacted by Multiple Point Sources. ENVIRONMENTAL SCIENCE & TECHNOLOGY, 47(8), 3743-3751. doi:doi: 10.1021/es304255u Marshall, J. D. (2008). Environmental inequality: air pollution exposures in California's South Coast Air Basin. ATMOSPHERIC ENVIRONMENT, 42(21), 5499–5503. doi:10.1016/j.atmosenv.2008.02.005 Marshall, J. D., Swor, K. R., & Nguyen, N. P. (2014). Prioritizing environmental justice and equality: diesel emissions in southern California. ENVIRONMENTAL SCIENCE & TECHNOLOGY, 48(7), 4063-4068. doi:10.1021/es405167f Mathes, R. W., Ito, K., & Matte, T. (2011). Assessing syndromic surveillance of cardiovascular outcomes from emergency department chief complaint data in New York City. PLOS ONE, 6(2), e14677. doi:doi: 10.1371/journal.pone.0014677 McOliver, C. A., Camper, A. K., Doyle, J. T., Eggers, M. J., Ford, T. E., Lila, M. A., . . . Donatuto, J. (2015). Community-based research as a mechanism to reduce environmental health disparities in American Indian and Alaska Native communities. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 12(4), 4076- 4100. doi:doi: 10.3390/ijerph120404076 Menon, C. V., Jahn, D. R., Mauer, C. B., & O'Bryant, S. E. (2013). Executive Functioning as a Mediator of the Relationship Between Premorbid Verbal Intelligence and Health Risk Behaviors in a Rural-Dwelling Cohort: A Project FRONTIER Study. Archives of Clinical Neuropsychology, 28(2), 169-179. doi:10.1093/arclin/acs102 Metzger, K. B., Ito, K., & Matte, T. D. (2010). Summer heat and mortality in New York City: how hot is too hot? ENVIRONMENTAL HEALTH PERSPECTIVES, 118(1), 80-86. doi:10.1289/ehp.0900906

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Muscatiello, N., McCarthy, A., Kielb, C., Hsu, W.-H., Hwang, S.-A., & Lin, S. (2015). Classroom conditions and CO2 concentrations and teacher health symptom reporting in 10 New York State schools. INDOOR AIR, 25(2), 157- 167. doi:doi: 10.1111/ina.12136 Nadeau, K., McDonald-Hyman, C., Noth, E. M., Pratt, B., Hammond, S. K., Balmes, J., & Tager, I. (2010). Ambient air pollution impairs regulatory T-cell function in asthma. Journal of Allergy and Clinical Immunology, 126(4), 845- 852.e810. doi:doi: 10.1016/j.jaci.2010.08.008. Nguyen, N. P. a. J. D. M. (2018). Impact, efficiency, inequality, and injustice of urban air pollution: variability by emission location. Environmental Research Letters, 13, 024002. doi:10.1088/1748-9326/aa9cb5 O'Bryant, S. E., Edwards, M., Menon, C. V., Gong, G., & Barber, R. C. (2011). Long-term low-level arsenic exposure is associated with poorer neuropsychological functioning: a Project FRONTIER study. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, SPECIAL ISSUE: ADVANCES IN ENVIRONMENTAL NEUROTOXICOLOGY, 8(3), 861-874. doi:doi: 10.3390/ijerph8030861 O'Bryant, S. E., Johnson, L., Balldin, V., Edwards, M., Barber, R., Williams, B., . . . Hall, J. (2013). Characterization of Mexican Americans with mild cognitive impairment and Alzheimer's disease. J Alzheimers Dis, 33(2), 373-379. doi:10.3233/jad-2012-121420 O'Bryant, S. E., Johnson, L., Reisch, J., Edwards, M., Hall, J., Barber, R., . . . Singh, M. (2013). Risk factors for mild cognitive impairment among Mexican Americans. Alzheimer's & Dementia, 9(6), 622-631.e621. doi:http://dx.doi.org/10.1016/j.jalz.2012.12.007 Pachon, J. E., Balachandran, S., Hu, Y., Mulholland, J. A., Darrow, L. A., Sarnat, J. A., . . . Russell, A. G. (2012). Development of outcome-based, multipollutant mobile source indicators. Journal of the Air and Waste Management Association, 62(4), 431-442. doi:DOI: 10.1080/10473289.2012.656218 Pachon, J. E., Balachandran, S., Hu, Y., Weber, R. J., Mulholland, J. A., & Russell, A. G. (2010). Comparison of SOC estimates and uncertainties from aerosol chemical composition and gas phase data in Atlanta. ATMOSPHERIC ENVIRONMENT, 44(32), 3907-3914. doi:10.1016/j.atmosenv.2010.07.017 Pachon, J. E., Weber, R. J., Zhang, X. L., Mulholland, J. A., & Russell, A. G. (2013). Revising the use of potassium (K) in the source apportionment of PM2.5. Atmospheric Pollution Research, 4(1), 14-21. doi:10.5094/Apr.2013.002 Peng, R. D., Bell, M. L., Geyh, A. S., McDermott, A., Zeger, S. L., Samet, J. M., & Dominici, F. (2009). Emergency admissions for cardiovascular and respiratory diseases and the chemical composition of fine particle air pollution. ENVIRONMENTAL HEALTH PERSPECTIVES, 117(6), 957-963. doi:doi: 10.1289/ehp.0800185 Peng, R. D., Bobb, J. F., Tebaldi, C., McDaniel, L., Bell, M. L., & Dominici, F. (2011). Toward a Quantitative Estimate of Future Heat Wave Mortality under Global Climate Change. ENVIRONMENTAL HEALTH PERSPECTIVES, 119(5), 701-706. doi:10.1289/ehp.1002430 Peng, R. D., Chang, H. H., Bell, M. L., McDermott, A., Zeger, S. L., Samet, J. M., & Dominici, F. (2008). Coarse particulate matter air pollution and hospital admissions for cardiovascular and respiratory diseases among Medicare patients. JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 299(18), 2172-2179. doi:10.1001/jama.299.18.2172 Peng, R. D., Dominici, F., & Welty, L. J. (2009). A Bayesian hierarchical distributed lag model for estimating the time course of risk of hospitalization associated with particulate matter air pollution. JOURNAL OF THE ROYAL STATISTICAL SOCIETY, SERIES C, 58(1), 3-24. doi:10.1111/j.1467-9876.2008.00640.x Pratt, G. C., Parson, K., Shinoda, N., Lindgren, P., Dunlap, S., Yawn, B., . . . Johnson, J. (2014). Quantifying traffic exposure. 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