Data on county socioeconomic status for 2,132 US counties and each county’s average annual cardiovascular mortality rate (CMR) and total PM2.5 concentration for 21 years (1990-2010). County CMR, PM2.5, and socioeconomic data were obtained from the U.S. National Center for Health Statistics, U.S. Environmental Protection Agency’s Community Multiscale Air Quality modeling system, and the U.S. Census, respectively. A socioeconomic index was created using seven county-level measures from the 1990 US census using factor analysis. Quintiles of this index were used to generate categories of county socioeconomic status. This dataset is associated with the following publication: Wyatt, L., G. Peterson, T. Wade, L. Neas, and A. Rappold. The contribution of improved air quality to reduced cardiovascular mortality: Declines in socioeconomic differences over time. ENVIRONMENT INTERNATIONAL. Elsevier B.V., Amsterdam, NETHERLANDS, 136: 105430, (2020).

County-level annual cardiovascular mortality rates and annual average PM2.5 concentrations, 2132 U.S. counties, 1990-2010. Included national emissions by sectors and county-level confounders (annual COPD mortality rates, percent non-white population, and median income). This dataset is associated with the following publication: Peterson, G., C. Hogrefe, L. Neas, A. Corrigan, R. Mathur, and A. Rappold. Impacts of Reductions in Emissions from Major Source Sectors on Fine Particulate Matter-Related Cardiovascular Mortality. ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA, 128(1): 17005, (2020).

County-level annual cardiovascular mortality rates and annual average PM2.5 concentrations, 2132 U.S. counties, 1990-2010. Included national emissions by sectors and county-level confounders (annual COPD mortality rates, percent non-white population, and median income). This dataset is associated with the following publication: Peterson, G., C. Hogrefe, L. Neas, A. Corrigan, R. Mathur, and A. Rappold. Impacts of Reductions in Emissions from Major Source Sectors on Fine Particulate Matter-Related Cardiovascular Mortality. ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA, 128(1): 17005, (2020).

This dataset documents rates and trends in local hypertension-related cardiovascular disease (CVD) death rates. Specifically, this report presents county (or county equivalent) estimates of hypertension-related CVD death rates in 2000-2019 and trends during two intervals (2000-2010, 2010-2019) by age group (ages 35–64 years, ages 65 years and older), race/ethnicity (non-Hispanic American Indian/Alaska Native, non-Hispanic Asian/Pacific Islander, non-Hispanic Black, Hispanic, non-Hispanic White), and sex (female, male). The rates and trends were estimated using a Bayesian spatiotemporal model and a smoothed over space, time, and demographic group. Rates are age-standardized in 10-year age groups using the 2010 US population. Data source: National Vital Statistics System.

Background: Adverse cardiovascular events have been linked with PM2.5 exposure obtained primarily from air quality monitors, which rarely co-locate with participant residences. Modeled PM2.5 predictions at finer resolution may more accurately predict residential exposure; however few studies have compared results across different exposure assessment methods. Methods: We utilized a cohort of 5679 patients who had undergone a cardiac catheterization between 2002–2009 and resided in NC. Exposure to PM2.5 for the year prior to catheterization was estimated using data from air quality monitors (AQS), Community Multiscale Air Quality (CMAQ) fused models at the census tract and 12 km spatial resolutions, and satellite-based models at 10 km and 1 km resolutions. Case status was either a coronary artery disease (CAD) index>23 or a recent myocardial infarction (MI). Logistic regression was used to model odds of having CAD or an MI with each 1-unit (μg/m3) increase in PM2.5, adjusting for sex, race, smoking status, socioeconomic status, and urban/rural status. Results: We found that the elevated odds for CAD>23 and MI were nearly equivalent for all exposure assessment methods. One difference was that data from AQS and the census tract CMAQ showed a rural/urban difference in relative risk, which was not apparent with the satellite or 12 km-CMAQ models. Conclusions: Long-term air pollution exposure was associated with coronary artery disease for both modeled and monitored data. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Clinical data are located in: C:\Users\rdevlin\OneDrive - Environmental Protection Agency (EPA)\Excel Files\Cathgen Satellite data are located in : C:\Users\rdevlin\OneDrive - Environmental Protection Agency (EPA)\Excel Files\New Ikm Satellite Data C:\Users\rdevlin\OneDrive - Environmental Protection Agency (EPA)\Excel Files\Satellite Data CMAQ data are located in C:\Users\rdevlin\OneDrive - Environmental Protection Agency (EPA)\Excel Files\CMAQ Data. Format: There are two types of datasets used in this study: clinical data taken from patient records at the Duke Medical Center; and air pollution data (PM2.5) taken from a federal reference monitor located in Raleigh, CMAQ data obtained from collaborators at Georgia Tech and NERL/ORD, and satellite data obtained from collaborators at Harvard. Metadata are in the form of Excel spreadsheets that contain columns of data that specify clinical and exposure information for each individual participating in the study. This dataset is associated with the following publication: McGuinn, L., C. Ward-Caviness, A. Schneider, Q. Di, A. Chudnovsky, J. Schwartz, P. Koutrakis, A. Russell, V. Garcia, W. Krause, E. Hauser, L. Neas, W. Cascio, D. Diaz-Sanchez, and R. Devlin. Fine Particulate Matter and Cardiovascular Disease: Comparison of Assessment Methods for Long-term Exposure. ENVIRONMENTAL RESEARCH. Academic Press Incorporated, Orlando, FL, USA, 159: 16-23, (2017).

Background: Adverse cardiovascular events have been linked with PM2.5 exposure obtained primarily from air quality monitors, which rarely co-locate with participant residences. Modeled PM2.5 predictions at finer resolution may more accurately predict residential exposure; however few studies have compared results across different exposure assessment methods. Methods: We utilized a cohort of 5679 patients who had undergone a cardiac catheterization between 2002–2009 and resided in NC. Exposure to PM2.5 for the year prior to catheterization was estimated using data from air quality monitors (AQS), Community Multiscale Air Quality (CMAQ) fused models at the census tract and 12 km spatial resolutions, and satellite-based models at 10 km and 1 km resolutions. Case status was either a coronary artery disease (CAD) index>23 or a recent myocardial infarction (MI). Logistic regression was used to model odds of having CAD or an MI with each 1-unit (μg/m3) increase in PM2.5, adjusting for sex, race, smoking status, socioeconomic status, and urban/rural status. Results: We found that the elevated odds for CAD>23 and MI were nearly equivalent for all exposure assessment methods. One difference was that data from AQS and the census tract CMAQ showed a rural/urban difference in relative risk, which was not apparent with the satellite or 12 km-CMAQ models. Conclusions: Long-term air pollution exposure was associated with coronary artery disease for both modeled and monitored data. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Clinical data are located in: C:\Users\rdevlin\OneDrive - Environmental Protection Agency (EPA)\Excel Files\Cathgen Satellite data are located in : C:\Users\rdevlin\OneDrive - Environmental Protection Agency (EPA)\Excel Files\New Ikm Satellite Data C:\Users\rdevlin\OneDrive - Environmental Protection Agency (EPA)\Excel Files\Satellite Data CMAQ data are located in C:\Users\rdevlin\OneDrive - Environmental Protection Agency (EPA)\Excel Files\CMAQ Data. Format: There are two types of datasets used in this study: clinical data taken from patient records at the Duke Medical Center; and air pollution data (PM2.5) taken from a federal reference monitor located in Raleigh, CMAQ data obtained from collaborators at Georgia Tech and NERL/ORD, and satellite data obtained from collaborators at Harvard. Metadata are in the form of Excel spreadsheets that contain columns of data that specify clinical and exposure information for each individual participating in the study. This dataset is associated with the following publication: McGuinn, L., C. Ward-Caviness, A. Schneider, Q. Di, A. Chudnovsky, J. Schwartz, P. Koutrakis, A. Russell, V. Garcia, W. Krause, E. Hauser, L. Neas, W. Cascio, D. Diaz-Sanchez, and R. Devlin. Fine Particulate Matter and Cardiovascular Disease: Comparison of Assessment Methods for Long-term Exposure. ENVIRONMENTAL RESEARCH. Academic Press Incorporated, Orlando, FL, USA, 159: 16-23, (2017).

2013 to 2015, 3-year average. Rates are age-standardized. County rates are spatially smoothed. The data can be viewed by gender and race/ethnicity. Data source: National Vital Statistics System. Additional data, maps, and methodology can be viewed on the Interactive Atlas of Heart Disease and Stroke http://www.cdc.gov/dhdsp/maps/atlas

2017 to 2019, 3-year average. Rates are age-standardized. County rates are spatially smoothed. The data can be viewed by sex and race/ethnicity. Data source: National Vital Statistics System. Additional data, maps, and methodology can be viewed on the Interactive Atlas of Heart Disease and Stroke https://www.cdc.gov/heart-disease-stroke-atlas/about/index.html

The U.S. Environmental Protection Agency provides information on the particulate matter concentration for Allegheny County that have a diameter greater or equal to 2.5 mm. The data is based on a combination of 2012 model and monitor data reported by the U.S. Environmental Protection Agency’s Office of Air and Radiation. The data represents the mean PM 2.5 measurement in micrograms per cubic meter for each census tract in Allegheny County. This data was obtained from the U.S. Department of Environmental Protection’s Environmental Justice Screen tool.