Studies show associations between air pollution exposure and coronavirus 2019 (COVID19) hospitalizations, but have not substantially explored regional differences. In this study, we estimate associations between shorter-term exposure to fine particulate matter (PM2.5) and hospitalization among individuals with SARS-CoV-2 infection. This study utilized data from 72,385 patients (78,504 hospitalizations) with a hospital-confirmed SARS-CoV-2 infection between January 1, 2020 and December 31, 2020. Daily PM2.5 concentrations from ground-based monitors were averaged to generate 2, 5, and 21-day average exposures prior to hospitalization. We used a time-stratified case-crossover approach to estimate associations between PM2.5 and COVID19-related hospitalizations in 57 Core Based Statistical Areas (CBSAs) across the United States (US). We subsequently conducted nationwide and region-specific random effects meta-analysis. In the random effects meta-analysis, a 1 µg/m3 increase in 2, 5, and 21-day average PM2.5 are associated with a 0.61

BACKGROUND:Brownfields consist of abandoned and disused sites, spanning many former purposes. Brownfields represent a heterogenous yet ubiquitous exposure for many Americans, which may contain hazardous wastes and represent urban blight. Neonates and pregnant individuals are often sensitive to subtle environmental exposures. We evaluate if residential exposure to lead (Pb) brownfields is associated with birth defects. METHODS:Using North Carolina birth records from 2003 to 2015, we sampled 169,499 births within 10 km of a Pb brownfield with 3255 cardiovascular, central nervous, or external defects identified. Exposure was classified by binary specification of residing within 3 km of a Pb brownfield. We utilized multivariable logistic regression models adjusted for demographic covariates available from birth records and 2010 Census to estimate odds ratios (OR) and 95% confidence intervals (CI). Effect measure modification was assessed by inclusion of interaction terms and stratification for the potential modifiers of race/ethnicity and diabetes status. RESULTS:We observed positive associations between cardiovascular birth defects and residential proximity to Pb brownfields, OR (95%CI): 1.15 (1.04, 1.26), with suggestive positive associations for central nervous 1.16 (0.91, 1.47) and external defects 1.19 (0.88, 1.59). We did observe evidence of effect measure modification via likelihood ratio tests (LRT) for race/ethnicity for central nervous and external defect groups (LRT p values 0.08 and 0.02). We did observe modification by diabetes status for the cardiovascular group (LRT p value 0.08). CONCLUSIONS:Our results from this analysis indicate that residential proximity to Pb brownfields is associated with cardiovascular birth defects with suggestive associations for central nervous and external defects. In-depth analyses of individual defects and other contaminants or brownfield site functions may reveal additional novel associations.

Background: Global urbanization is leading to increased exposure to traffic-related air pollution (TRAP), which is associated with adverse health events. While individuals with cardiovascular disease (CVD) are known to have elevated susceptibility to air pollution exposure, no studies have evaluated how mortality risks associated with TRAP exposure differ based on the presence of CVD. Methods: We used three electronic health record-based cohorts to examine associations between proximity to major roadways and all-cause mortality. The three cohorts were a random sample of the hospital population, individuals with a prior myocardial infarction, and individuals with diagnosed heart failure (HF). We used Cox proportional hazards models to evaluate associations while adjusting for age, race, sex, and census block group socioeconomic status. Results: Residing <250 m from a major roadway was associated with a hazard ratio (HR) of 1.13 (95% confidence interval = 1.05, 1.23) for individuals with HF, an HR of 1.07 (95% confidence interval = 0.96, 1.20) for those with a prior myocardial infarction, and an HR of 1.03 (95% confidence interval = 0.89, 1.20) for a random sample of hospital patients. This pattern persisted across several sensitivity analyses including alternative definitions of proximity to major roadways and matching the cohorts on demographics. Conclusion: These results highlight the differences in air quality-related health risks based on underlying CVD. Individuals with HF consistently had the highest environmental health risks. These results may better inform risks related to TRAP exposure in populations with differing underlying CVD.

Background Chronic kidney disease (CKD) affects more than 38 million people in the United States, predominantly those over 65 years of age. While CKD etiology is complex, recent research suggests associations with environmental exposures. Methods Our primary objective is to examine creatinine-based estimated glomerular filtration rate (eGFRcr) and diagnosis of CKD and potential associations with fine particulate matter (PM2.5), ozone (O-3), and nitrogen dioxide (NO2) using a random sample of North Carolina electronic healthcare records (EHRs) from 2004 to 2016. We estimated eGFRcr using the serum creatinine-based 2021 CKD-EPI equation. PM2.5 and NO2 data come from a hybrid model using 1 km(2) grids and O-3 data from 12 km(2) CMAQ grids. Exposure concentrations were 1-year averages. We used linear mixed models to estimate eGFRcr per IQR increase of pollutants. We used multiple logistic regression to estimate associations between pollutants and first appearance of CKD. We adjusted for patient sex, race, age, comorbidities, temporality, and 2010 census block group variables. Results We found 44,872 serum creatinine measurements among 7,722 patients. An IQR increase in PM2.5 was associated with a 1.63 mL/min/1.73m(2) (95% CI: -1.96, -1.31) reduction in eGFRcr, with O3 and NO2 showing positive associations. There were 1,015 patients identified with CKD through e-phenotyping and ICD codes. None of the environmental exposures were positively associated with a first-time measure of eGFRcr < 60 mL/min/1.73m2. NO2 was inversely associated with a first-time diagnosis of CKD with aOR of 0.77 (95% CI: 0.66, 0.90). Conclusions One-year average PM2.5 was associated with reduced eGFRcr, while O-3 and NO(2 )were inversely associated. Neither PM(2.5 )or O-3 were associated with a first-time identification of CKD, NO2 was inversely associated. We recommend future research examining the relationship between air pollution and impaired renal function.

BACKGROUND:Ambient fine particulate matter (PM2.5) contributes to global morbidity and mortality. One way to understand the health effects of PM2.5 is by examining its impact on performed hospital procedures, particularly among those with existing chronic disease. However, such studies are rare. Here, we investigated the associations between annual average PM2.5 and hospital procedures among individuals with heart failure.METHODS:Using electronic health records from the University of North Carolina Healthcare System, we created a retrospective cohort of 15,979 heart failure patients who had at least one of 53 common (frequency > 10%) procedures. We used daily modeled PM2.5 at 1x1 km resolution to estimate the annual average PM2.5 at the time of heart failure diagnosis. We used quasi-Poisson models to estimate associations between PM2.5 and the number of performed hospital procedures over the follow-up period (12/31/2016 or date of death) while adjusting for age at heart failure diagnosis, race, sex, year of visit, and socioeconomic status.RESULTS:A 1 μg/m3 increase in annual average PM2.5 was associated with increased glycosylated hemoglobin tests (10.8%; 95% confidence interval = 6.56%, 15.1%), prothrombin time tests (15.8%; 95% confidence interval = 9.07%, 22.9%), and stress tests (6.84%; 95% confidence interval = 3.65%, 10.1%). Results were stable under multiple sensitivity analyses.CONCLUSIONS:These results suggest that long-term PM2.5 exposure is associated with an increased need for diagnostic testing on heart failure patients. Overall, these associations give a unique lens into patient morbidity and potential drivers of healthcare costs linked to PM2.5 exposure.

BACKGROUND:Air pollution exposure is a significant risk factor for morbidity and mortality, especially for those with pre-existing chronic disease. Previous studies highlighted the risks that long-term particulate matter exposure has for readmissions. However, few studies have evaluated source and component specific associations particularly among vulnerable patient populations. OBJECTIVES:Use electronic health records from 5556 heart failure (HF) patients diagnosed between July 5, 2004 and December 31, 2010 that were part of the EPA CARES resource in conjunction with modeled source-specific fine particulate matter (PM2.5) to estimate the association between exposure to source and component apportioned PM2.5 at the time of HF diagnosis and 30-day readmissions. METHODS:We used zero-inflated mixed effects Poisson models with a random intercept for zip code to model associations while adjusting for age at diagnosis, year of diagnosis, race, sex, smoking status, and neighborhood socioeconomic status. We undertook several sensitivity analyses to explore the impact of geocoding precision and other factors on associations and expressed associations per interquartile range increase in exposures. RESULTS:We observed associations between 30-day readmissions and an interquartile range increase in gasoline- (16.9% increase; 95% confidence interval = 4.8%, 30.4%) and diesel-derived PM2.5 (9.9% increase; 95% confidence interval = 1.7%, 18.7%), and the secondary organic carbon component of PM2.5 (SOC; 20.4% increase; 95% confidence interval = 8.3%, 33.9%). Associations were stable in sensitivity analyses, and most consistently observed among Black study participants, those in lower income areas, and those diagnosed with HF at an earlier age. Concentration-response curves indicated a linear association for diesel and SOC. While there was some non-linearity in the gasoline concentration-response curve, only the linear component was associated with 30-day readmissions. DISCUSSION:There appear to be source specific associations between PM2.5 and 30-day readmissions particularly for traffic-related sources, potentially indicating unique toxicity of some sources for readmission risks that should be further explored.

Accumulating evidence underscores the large role played by the environment in the health of communities and individuals. We review the currently known contribution of environmental exposures and pollutants on kidney disease and its associated morbidity. We review air pollutants, such as particulate matter; water pollutants, such as trace elements, per- and polyfluoroalkyl substances, and pesticides; and extreme weather events and natural disasters. We also discuss gaps in the evidence that presently relies heavily on observational studies and animal models, and propose using recently developed analytic methods to help bridge the gaps. With the expected increase in the intensity and frequency of many environmental exposures in the decades to come, an improved understanding of their potential effect on kidney disease is crucial to mitigate potential morbidity and mortality.

OBJECTIVE:Short-term ambient fine particulate matter (PM2.5) is associated with adverse cardiovascular events including myocardial infarction (MI). However, few studies have examined associations between PM2.5 and subclinical cardiomyocyte damage outside of overt cardiovascular events. Here we evaluate the impact of daily PM2.5 on cardiac troponin I, a cardiomyocyte specific biomarker of cellular damage.METHODS:We conducted a retrospective cohort study of 2924 patients identified using electronic health records from the University of North Carolina Healthcare System who had a recorded MI between 2004 and 2016. Troponin I measurements were available from 2014 to 2016, and were required to be at least 1 week away from a clinically diagnosed MI. Daily ambient PM2.5 concentrations were estimated at 1 km resolution and assigned to patient residence. Associations between log-transformed troponin I and daily PM2.5 were evaluated using distributed lag linear mixed effects models adjusted for patient demographics, socioeconomic status and meteorology.RESULTS:A 10 µg/m3 elevation in PM2.5 3 days before troponin I measurement was associated with 0.06 ng/mL higher troponin I (95% CI=0.004 to 0.12). In stratified models, this association was strongest in patients that were men, white and living in less urban areas. Similar associations were observed when using 2-day rolling averages and were consistently strongest when using the average exposure over the 5 days prior to troponin I measurement.CONCLUSIONS:Daily elevations in PM2.5 were associated with damage to cardiomyocytes, outside of the occurrence of an MI. Poor air quality may cause persistent damage to the cardiovascular system leading to increased risk of cardiovascular disease and adverse cardiovascular events.

BACKGROUND:Neighborhood-level socioeconomic status (SES) is associated with health outcomes, including cardiovascular disease and diabetes, but these associations are rarely studied across large, diverse populations. METHODS:We used Ward's Hierarchical clustering to define eight neighborhood clusters across North Carolina using 11 census-based indicators of SES, race, housing, and urbanicity and assigned 6992 cardiac catheterization patients at Duke University Hospital from 2001 to 2010 to clusters. We examined associations between clusters and coronary artery disease index > 23 (CAD), history of myocardial infarction, hypertension, and diabetes using logistic regression adjusted for age, race, sex, body mass index, region of North Carolina, distance to Duke University Hospital, and smoking status. RESULTS:Four clusters were urban, three rural, and one suburban higher-middle-SES (referent). We observed greater odds of myocardial infarction in all six clusters with lower or middle-SES. Odds of CAD were elevated in the rural cluster that was low-SES and plurality Black (OR 1.16, 95% CI 0.94-1.43) and in the rural cluster that was majority American Indian (OR 1.31, 95% CI 0.91-1.90). Odds of diabetes and hypertension were elevated in two urban and one rural low- and lower-middle SES clusters with large Black populations. CONCLUSIONS:We observed higher prevalence of cardiovascular disease and diabetes in neighborhoods that were predominantly rural, low-SES, and non-White, highlighting the importance of public health and healthcare system outreach into these communities to promote cardiometabolic health and prevent and manage hypertension, diabetes and coronary artery disease.

BACKGROUND:Brownfields are a multitude of abandoned and disused sites, spanning many former purposes. Brownfields represent a heterogenous yet ubiquitous exposure for many Americans, which may contain hazardous wastes and represent urban blight. Neonates and pregnant individuals are often sensitive to subtle environmental exposures. We evaluate whether residential brownfield exposure is associated with birth defects. METHODS:Using North Carolina birth records from 2003 to 2015, we sampled 753,195 births with 39,495 defects identified. We examined defect groups and 30 distinct phenotypes. Number of brownfields within 2,000 m of the residential address at birth was summed. We utilized mixed effects multivariable logistic regression models adjusted for demographic and environmental covariates available from birth records, 2010 Census, and EPA's Environmental Quality Index to estimate odds ratios (OR) and 95% confidence intervals (CI). RESULTS:We observed positive associations between cardiovascular and external defect groups (OR [95% CI]: 1.07 [1.02-1.13] and 1.17 [1.01-1.35], respectively) and any brownfield exposure. We also observed positive associations with atrial septal and ventricular septal defects (1.08 [1.01-1.16] and 1.15 [1.03-1.28], respectively), congenital cataracts (1.38 [0.98-1.96]), and an inverse association with gastroschisis (0.74 [0.58-0.94]). Effect estimates for several additional defects were positive, though we observed null associations for most group and individual defects. Additional analyses indicated an exposure-response relationship for several defects across levels of brownfield exposure. CONCLUSIONS:Our results indicate that residential proximity to brownfields is associated with birth defects, especially cardiovascular and external defects. In-depth analyses of individual defects and specific contaminants or brownfield sites may reveal additional novel associations.

BACKGROUND AND AIM: Fine particulate air pollution (PM2.5) exposure is associated with increased risk of hospital readmissions. This study aims to determine if this association differs according to the attributable source of the PM2.5. METHODS: We used zero-inflated poisson mixed-effects models to associate source-apportioned PM2.5 with the number of 30-day readmissions after HF diagnosis. The study cohort included patients diagnosed with HF who had a hospital visit at a University of North Carolina Healthcare System facility between July 5, 2004, and December 31, 2010. The exposure was the annual average source-apportioned PM2.5 at the date of HF diagnosis. Patient zip code was included as a random effect and models were adjusted for year of diagnosis, sex, race, age, smoking status and 2010 census block group measures of urbanicity, percent receiving public assistance, median income, and median house value. PM2.5 was apportioned into the sources using a Chemical Mass Balance Gas Constrained-Iteration model. Results are presented as the percent change in number of expected readmissions per interquartile range increase in source-apportioned PM2.5 and the associated 95% confidence interval (CI). RESULTS: We observed associations with 30-day readmissions for gasoline (16.89%; 95% CI = 4.82-30.36), diesel (9.87%; 95% CI = 1.72-18.69), and secondary organic carbon (SOC; 20.44%; 95% CI = 8.29-33.95) PM2.5. Associations were greater for study participants in a census block group with an income below the median value. Associations were also greater for Black HF patients compared to white HF patients. CONCLUSIONS: Associations between 30-day readmissions and PM2.5 appear greatest for traffic and SOC-related sources which may be due to a combination of differential toxicity as well as the distribution of these sources amongst HF patients. This abstract does not necessarily represent the views or policies of the US Environmental Protection Agency. KEYWORDS: Heart failure, hospital utilization, particulate matter, air pollution

Background and aims: Chronic kidney disease (CKD) affects more than 38 million people in the United States, predominantly those over 65 years of age. While CKD etiology is complex, recent research suggests associations with certain environmental exposures. Additional studies are needed to understand the strength of associations. We examine estimated glomerular filtration rate (eGFR) using a random sample of North Carolina electronic healthcare records (EHRs) and potential relationships with PM₂.₅ and O₃. Methods: Patient data came from a random sample of 7,065 EHRs within the EPA CARES resource, with recorded serum creatinine concentrations. Patients were seen at a University of North Carolina Healthcare System affiliated hospital or clinic from 2004-2017. We estimated eGFR using CKD-EPI equations. PM₂.₅ data comes from a hybrid model using 1x1 km grids and O₃ data from CMAQ 12x12 km grids. Exposures were annual average PM₂.₅ and O₃ based on the creatinine lab test date. We used multiple linear regression to estimate eGFR per IQR increase of PM₂.₅ & O₃. We adjusted for patient sex, race, age, comorbidities, and 2010 census block group measures of sociodemographic and economic factors. Results: Patients averaged 55.3 (SD: 16.2) years of age, with 58.3% female. There were 1,001 patients (14.2%) diagnosed with CKD, identified by ICD-9 & 10 codes. Mean concentrations for the study period of PM₂.₅ and O₃ were 9.92 (IQR: 1.61) µg/m³ and 40.20 (IQR: 2.53) ppb respectively. eGFR decreased 8.45 mL/min/1.73m² (95% CI: 7.92, 8.98) per IQR increase of PM₂.₅ and a more modest decrease of 0.66 mL/min/1.73m² (95% CI: -.08, 1.40) per IQR of O₃. Conclusions: Annual average PM₂.₅, and to a lesser extent O₃, were associated with lower (poorer) eGFR. Future work will examine the relationship between air pollution and onset of CKD and impaired renal function. This abstract does not reflect EPA policy.

Background and Aim: Health impacts of heat exposure are increasingly important due to climate change. Anxiety and depression are common and understudied mental health conditions, possibly associated with heat exposure. We examined associations between short-term (5-day) apparent temperature and health visits for anxiety and/or depression in North Carolina. Methods: We linked electronic health records from a random sample of adults seen at University of North Carolina Healthcare System hospitals 2004-2018 in the EPA CARES resource with climate data from PRISM Climate Group. We examined 5-day mean apparent temperature (incorporating temperature and humidity) at the ZIP code level for patients diagnosed with anxiety and/or depression compared to first recorded visit for those with any other diagnosis. We used log binomial regression models adjusted for personal (age, sex, race, health insurance status), environmental (season, annual PM2.5 concentration, climate division) and neighborhood (median household income, percent Bachelor's degree or more, percent urban) covariates. Results: We included 17,145 patients, 2219 of whom were diagnosed with anxiety and/or depression. Those with anxiety and/or depression were, on average, younger (46.4 vs 48.0 years), more likely to be female (69.7% vs 59.7%), and White (74.7% vs 62.4%), compared to those with other diagnoses. Mean five-day apparent temperature was 17.6 degrees C (SD 10.4). The prevalence of having a diagnosis of anxiety and/or depression was 1% higher per degree increase in five-day mean apparent temperature (PR 1.01, 95% CI 1.00, 1.02) compared to other diagnoses. Results were similar when limiting to anxiety, depression, and geographic region. Conclusions: We did not observe substantial associations between apparent temperature and anxiety or depression relative to other outcomes. Future studies should expand this work to larger areas with more temperature variability and consider mental health trends independent of other outcomes. This abstract does not reflect EPA policy. Keywords: climate, heat, mental health

Background Short-term changes in ambient fine particulate matter (PM2.5) increase the risk for unplanned hospital readmissions. However, this association has not been fully evaluated for high-risk patients or examined to determine if the readmission risk differs based on time since discharge. Here we investigate the relation between ambient PM2.5 and 30-day readmission risk in heart failure (HF) patients using daily time windows and examine how this risk varies with respect to time following discharge. Methods We performed a retrospective cohort study of 17,674 patients with a recorded HF diagnosis between 2004 and 2016. The cohort was identified using the EPA CARES electronic health record resource. The association between ambient daily PM2.5 (mu g/m(3)) concentration and 30-day readmissions was evaluated using time-dependent Cox proportional hazard models. PM2.5 associated readmission risk was examined throughout the 30-day readmission period and for early readmissions (1-3 days post-discharge). Models for 30-day readmissions included a parametric continuous function to estimate the daily PM2.5 associated readmission hazard. Fine-resolution ambient PM2.5 data were assigned to patient residential address and hazard ratios are expressed per 10 mu g/m(3) of PM2.5. Secondary analyses examined potential effect modification based on the time after a HF diagnosis, urbanicity, medication prescription, comorbidities, and type of HF. Results The hazard of a PM2.5 realated readmission within 3 days of discharge was 1.33 (95% CI 1.18-1.51). This PM2.5 readmission hazard was slightly elevated in patients residing in non-urban areas (1.43, 95%CI 1.22-1.67) and for HF patients without a beta-blocker prescription prior to the readmission (1.35; 95% CI 1.19-1.53). Conclusion Our findings add to the evidence indicating substantial air quality-related health risks in individuals with underlying cardiovascular disease. Hospital readmissions are key metrics for patients and providers alike. As a potentially modifiable risk factor, air pollution-related interventions may be enacted that might assist in reducing costly and burdensome unplanned readmissions.

Objectives: Develop a tool for applying various COVID-19 re-opening guidelines to the more than 120 U.S. Environmental Protection Agency (EPA) facilities.Methods: A geographic information system boundary was created for each EPA facility encompassing the county where the EPA facility is located and the counties where employees commuted from. This commuting area is used for display in the Dashboard and to summarize population and COVID-19 health data for analysis.Results: Scientists in EPA’s Office of Research and Development developed the EPA Facility Status Dashboard, an easy-to-use web application that displays data and statistical analyses on COVID-19 cases, testing, hospitalizations, and vaccination rates.Conclusion: The Dashboard was designed to provide readily accessible information for EPA management and staff to view and understand the COVID-19 risk surrounding each facility. It has been modified several times based on user feedback, availability of new data sources, and updated guidance. The views expressed in this article are those of the authors and do not necessarily represent the views or the policies of the U.S. Environmental Protection Agency.

Background: Per and polyfluoroalkyl substances (PFAS) are associated with health outcomes ranging from cancer to high cholesterol. However, there has been little examination of how PFAS exposure might impact the development of multiple chronic diseases, known as multimorbidity. Here, we associated the presence of one or more PFAS in water systems serving the zip code of residence with chronic disease and multimorbidity. Methods: We used data from the unregulated contaminant monitoring rule 3 to estimate exposure to PFAS for a random sample of 10,168 patients from the University of North Carolina Healthcare System. The presence of 16 chronic diseases was determined via. their electronic health records. We used a logistic regression model in a cross-sectional study design to associate the presence of one or more PFAS with multimorbidity. Models were adjusted for age, race, sex, smoking status, socioeconomic status, and 20 county-level confounders. Results: There were four PFAS found in water systems that served at least one zip code represented in our patient data: PFOA, PFHpA, PFOS, and PFHxS. Exposure to any PFAS was associated with a odds ratio of 1.25 for multimorbidity (95% confidence interval = 1.09, 1.45). Among the chronic diseases with at least 300 cases, we observed associations with dyslipidemia, hypertension, ischemic heart disease, and osteoporosis. Conclusion: Exposure to PFAS is associated with a range of chronic diseases as well as multimorbidity. Accounting for the joint impacts of PFAS on multiple chronic conditions may give an increasingly clear picture of the public health impacts of PFAS.

Background and Aim: Dementia continues to pose a serious health concern for aging populations around the world and may be affected by fine particulate (PM2.5) air pollution. As our planet warms and climates shift, environmental factors may contribute to chronic health outcomes, including dementia. We aim to determine if any association between prior year average temperature and diagnosis of dementia is discernable using available medical records data. Methods: Using a random sample of University of North Carolina (UNC) electronic health records, we identified 318 individuals with any diagnosis of dementia. We utilized a 4:1 matched case-control design to link each case with hospital-based controls by birth year, sex, race, Census 2010 income and education tertiles, and climate zone. Climate data was derived from PRISM Climate Group data. Prior year average air temperature (min=12.26°C max=18.50°C), relative humidity (min=58.18% max=75.74%), and apparent temperature (min=11.86°C max=19.86°C) were calculated based on patient zip code. We also examined associations with prior year PM2.5 (min=5.50 µg/m3 max=15.56 µg/m3) estimated using an ensemble machine learning model and first diagnosis of dementia or first non-dementia diagnosis for controls. We conducted multivariable logistic regression models to estimate odds ratios (OR) and 95% confidence intervals (CI) adjusted for our matching variables and urbanicity. Results: We observed significant positive associations between diagnosis of dementia and increased PM2.5 (OR 1.18; 95%CI 1.09-1.28) per 1 µg/m3, and for relative humidity (OR 1.06; 95%CI 1.01-1.11) per 1%. Air and apparent temperature showed similar patterns (OR 1.16; 95% CI 0.99-1.35 and OR 1.17; 95%CI 1.02-1.34) per 1°C. Conclusion: Our findings indicate that there are associations between both PM2.5 and year prior heat exposures and dementia. These findings suggest that further investigation into the role of heat and dementia is warranted. This abstract does not reflect EPA policy. Keywords: dementia, heat, climate change, air pollution

BACKGROUND AND AIM: Fine particulate matter (PM2.5) pollution exposure is increasingly recognized as a risk factor for cardiovascular disease (CVD), a leading cause of death among American Indians (AIs). PM2.5 estimates for AIs, however, remain largely unknown due to sparse monitoring. We describe ambient PM2.5 concentrations and regional/temporal trends in the Strong Heart Study (SHS) communities (Arizona [AZ], Oklahoma [OK], and North and South Dakota [ND and SD]) from 2001–2003 and 2006–2009. METHODS: We used SHS phase IV (2001-2003, n=2,769) and phase V (2006-2009, n=2,478) data. We used an ensemble-based model of daily mean PM2.5 concentrations at a 1km2 resolution and estimated participants' mean 30-day ambient exposure at the ZIP code-level. We performed descriptive analyses to depict how population-based concentrations of PM2.5 vary over the three SHS regions and two phases. RESULTS:There were significant differences in 30-day PM2.5 exposure between study sites. The overall median 30-day PM2.5 exposure in the different study sites were as follows: 9.2 μg/m3 (IQR: 2.1) in AZ, 9.1 μg/m3 (IQR: 2.4) in OK, and 5.5 μg/m3 (IQR: 2.8) in ND and SD. We did not detect a seasonal effect on PM2.5 exposure in AZ; however, PM2.5 in the wintertime was slightly higher in OK and substantially higher in ND and SD. These trends hold over both visit periods and all study sites. Annual median PM2.5 remained stable between phases IV and V for the OK and ND and SD regions; in AZ, PM2.5 first declined in phase V relative to phase IV but began to increase in 2008-2009. CONCLUSIONS:Understanding regional and temporal trends in ambient PM2.5 concentrations, which vary across tribal populations, may help to understand environmental exposures and CVD in AIs. This abstract does not reflect EPA policy. KEYWORDS: air pollution, American Indian, cardiovascular disease