Background: Fine particulate (PM 2.5 ) 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, PM 2.5 composition) across the United States. We examined the impact of PM 2.5 on survival, and its variation across clusters of cities with similar PM 2.5 composition, among Medicare enrollees in 81 US cities (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010). We used timevarying annual PM 2.5 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 PM 2.5 effects. Results: We followed more than 19 million subjects and observed more than 6 million deaths. We found a harmful impact of annual PM 2.5 concentrations on survival (hazard ratio = 1.11 [95%
Some of the researchers also used k-means clustering REF to cluster cities which exhibited similar pollution characteristics.
PM2.5 and survival among older adults: effect modification by particulate composition.
Epidemiology
Epidemiology
Medicine