Evaluation of associations between estimates of particulate matter exposure and new onset type 2 diabetes in the REGARDS cohort

Abstract

Background: Studies of PM2.5 and type 2 diabetes employ differing methods for exposure assignment, which could explain inconsistencies in this growing literature. We hypothesized associations between PM2.5 and new onset type 2 diabetes would differ by PM2.5 exposure data source, duration, and community type. Methods: We identified participants of the US-based REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort who were free of diabetes at baseline (2003–2007); were geocoded at their residence; and had follow-up diabetes information. We assigned PM2.5 exposure estimates to participants for periods of 1 year prior to baseline using three data sources, and 2 years prior to baseline for two of these data sources. We evaluated adjusted odds of new onset diabetes per 5 µg/m3 increases in PM2.5 using generalized estimating equations with a binomial distribution and logit link, stratified by community type. Results: Among 11,208 participants, 1,409 (12.6%) had diabetes at follow-up. We observed no associations between PM2.5 and diabetes in higher and lower density urban communities, but within suburban/small town and rural communities, increases of 5 µg/m3 PM2.5 for 2 years (Downscaler model) were associated with diabetes (OR [95% CI] = 1.65 [1.09, 2.51], 1.56 [1.03, 2.36], respectively). Associations were consistent in direction and magnitude for all three PM2.5 sources evaluated. Significance: 1- and 2-year durations of PM2.5 exposure estimates were associated with higher odds of incident diabetes in suburban/small town and rural communities, regardless of exposure data source. Associations within urban communities might be obfuscated by place-based confounding.