You are here:
Fine Particulate Matter and Cardiovascular Disease: Comparison of Assessment Methods for Long-term Exposure
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, 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.
Epidemiology studies have associated PM concentrations with adverse cardiovascular outcomes. These studies usually use PM values obtained from community based monitors, which has significant limitations due to the number and location of monitors. These studies typically assume that everyone residing with a certain radius of a monitor (e.g. 30 miles) was exposed to the same PM concentration. This assumption is particularly problematic when studying rural populations where almost no monitors are located. New modeling approaches are using remote sensing data from satellite or have developed emissions based models (e.g. CMAQ) that can estimate PM values at much fine resolutions as small as 1 x 1 km grids. This paper compares associations between PM and adverse cardiovascular outcomes using 5 different exposure assessment methods: monitors, two satellite models (10km and 1 km grids), and two CMAQ models (13 km grids and census tracts). All of the models produce similar associations for urban populations, but the satellite and 13km grid CMAQ model also find positive associations in rural populations, while the monitor data and data from the census tract resolution CMAQ model do not. These data suggest that models that have fine scale resolution may be more useful for studies of rural populations.
Record Details:Record Type: DOCUMENT (JOURNAL/PEER REVIEWED JOURNAL)
Organization:U.S. ENVIRONMENTAL PROTECTION AGENCY
OFFICE OF RESEARCH AND DEVELOPMENT
NATIONAL HEALTH AND ENVIRONMENTAL EFFECTS RESEARCH LABORATORY
ASSOCIATE DIRECTOR FOR HEALTH