Fine particulate (PM2.5) air pollution has been consistently linked to survival, but reported effect estimates are geographically heterogeneous. Exposure to different types of particle mixtures may explain some of this variation.
We used k-means cluster analyses to identify cities with similar pollution profiles, (ie, PM2.5 composition) across the United States. We examined the impact of PM2.5 on survival, and its variation across clusters of cities with similar PM2.5 composition, among Medicare enrollees in 81 US cities (2000–2010). We used time-varying annual PM2.5 averages, measured at ambient central monitoring sites, as the exposure of interest. We ran by-city Cox models, adjusting for individual data on previous cardiopulmonary-related hospitalizations and stratifying by follow-up time, age, gender, and race. This eliminates confounding by factors varying across cities and long-term trends, focusing on year-to-year variations of air pollution around its city-specific mean and trend. We then pooled the city-specific effects using a random effects meta-regression. In this second stage, we also assessed effect modification by cluster membership and estimated cluster-specific PM2.5 effects.
We followed more than 19 million subjects and observed more than 6 million deaths. We found a harmful impact of annual PM2.5 concentrations on survival (hazard ratio = 1.11 [95% confidence interval = 1.01, 1.23] per 10 μg/m3). This effect was modified by particulate composition, with higher effects observed in clusters containing high concentrations of nickel, vanadium, and sulfate. For instance, our highest effect estimate was observed in cities with harbors in the Northwest, characterized by high nickel, vanadium, and elemental carbon concentrations (1.9 [1.1, 3.3]). We observed null or negative associations in clusters with high oceanic and crustal particles.
To the best of our knowledge, this is the first study to examine the association between PM2.5 composition and survival. Our findings indicate that long-term exposure to fuel oil combustion and power plant emissions have the highest impact on survival.
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From the Departments of aEnvironmental Health, bBiostatistics, Harvard School of Public Health, Boston, MA; and cDepartment of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA.
Submitted 29 May 2014; accepted 22 January 2015.
This publication was developed under a STAR Research Assistance Agreement No. RD-834900 and was also made possible by USEPA STAR Fellowship Assistance Agreement no. FP-9172890-01, Grant RD 83479801, and R834894 awarded by the US Environmental Protection Agency. Its contents are solely the responsibility of the grantee and do not necessarily represent the official views of the USEPA. Furthermore, USEPA does not endorse the purchase of any commercial products or services mentioned in the publication. This publication was also made possible by training grant NIH T32 ES007069 and by NIEHS ES0002.
Disclosure: The authors report no conflicts of interest.
Supplemental digital content is available through direct URL citations in the HTML and PDF versions of this article (www.epidem.com). This content is not peer-reviewed or copy-edited; it is the sole responsibility of the author.
Correspondence: Marianthi-Anna Kioumourtzoglou, 401 Park Drive, Landmark Building, 3rd Floor East, PO Box 15697, Boston, MA 02215. E-mail: firstname.lastname@example.org.