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Activity Number: 309 - Statistical Advances in Source Apportionment of Air Pollutants and Source-Specific Health Effects Evaluation
Type: Topic-Contributed
Date/Time: Wednesday, August 11, 2021 : 3:30 PM to 5:20 PM
Sponsor: Korean International Statistical Society
Abstract #317561
Title: Assessing Multi-Pollutant, Source-Specific Exposures and Differential Health Effects
Author(s): Eun Sug Park* and Elaine Symanski
Companies: Texas A&M Transportation Institute and Baylor College of Medicine
Keywords: Air pollution; Health effects; Source apportionment; Spatial misalignment

Most previous studies examining health effects of source-specific air pollution have used monitor-specific source contributions estimated under the implicit assumption that pollution levels are homogeneous within a defined range of a monitor or within a city or county, which is often violated. Such methods are subject to non-ignorable exposure measurement error resulting from spatial misalignment between estimated source-specific exposures and health outcomes, leading to biased health effects estimates. This bias can be substantial particularly when assessing differential health effects across racial or ethnic groups whose residence locations are spatially clustered (e.g., within certain census tract or zip code areas). In this study, we assess source-specific exposures using multipollutant spatial data in Harris County, TX, and apply a spatially enhanced source apportionment method that accounts for spatial correlation and enables prediction of source-specific exposures at unmonitored locations. This allows us to more accurately estimate health effects of source-specific exposures among different racial/ethnic groups by reducing spatial misalignment errors.

Authors who are presenting talks have a * after their name.

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