BACKGROUND: 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. METHODS: 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. RESULTS: 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/m). 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. CONCLUSIONS: 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.
BACKGROUND: 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. METHODS: 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. RESULTS: 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/m). 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. CONCLUSIONS: 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.
Authors: Philip K Hopke; Kazuhiko Ito; Therese Mar; William F Christensen; Delbert J Eatough; Ronald C Henry; Eugene Kim; Francine Laden; Ramona Lall; Timothy V Larson; Hao Liu; Lucas Neas; Joseph Pinto; Matthias Stölzel; Helen Suh; Pentti Paatero; George D Thurston Journal: J Expo Sci Environ Epidemiol Date: 2006-05 Impact factor: 5.563
Authors: Claudio Pelucchi; Eva Negri; Silvano Gallus; Paolo Boffetta; Irene Tramacere; Carlo La Vecchia Journal: BMC Public Health Date: 2009-12-08 Impact factor: 3.295
Authors: Wenjie Shan; Yanming Lu; Yinshi Guo; Yaqin Li; Lingyun Xu; Lanfang Cao Journal: Environ Sci Pollut Res Int Date: 2016-06-28 Impact factor: 4.223
Authors: Cheng Peng; Akin Cayir; Marco Sanchez-Guerra; Qian Di; Ander Wilson; Jia Zhong; Anna Kosheleva; Letizia Trevisi; Elena Colicino; Kasey Brennan; Alexandra E Dereix; Lingzhen Dai; Brent A Coull; Pantel Vokonas; Joel Schwartz; Andrea A Baccarelli Journal: Epidemiology Date: 2017-11 Impact factor: 4.822
Authors: Joshua P Keller; Mathias Drton; Timothy Larson; Joel D Kaufman; Dale P Sandler; Adam A Szpiro Journal: Ann Appl Stat Date: 2017-04-08 Impact factor: 2.083