PM2.5 and Mortality in 207 US Cities: Modification by Temperature and City Characteristics

Abstract

Background: The reported estimated effects between long-term PM2.5 exposures and mortality vary spatially. We assessed whether community-level variables, including socioeconomic status indicators and temperature, modify this association.

Methods: We used data from >35 million Medicare enrollees from 207 US cities (2000-2010). For each city, we calculated annual PM2.5 averages, measured at ambient central monitoring sites. We used a variation of a causal modeling approach and fitted city-specific Cox models, which we then pooled using a random effects meta-regression. In this second stage, we assessed whether temperature and city-level variables, including smoking and obesity rates, poverty, education and greenness, modify the long-term PM2.5-mortality association.

Results: We found an association between long-term PM2.5 and survival (hazard ratio = 1.2; 95% confidence interval [CI]: 1.1, 1.3 per 10 μg/m increase in the annual PM2.5 average concentrations). We observed elevated estimates in the Southeastern, South and Northwestern US (hazard ratio = 1.9; 95% CI: 1.7, 2.2, and 1.4; 95% CI: 1.2, 1.7, and 1.4; 95% CI: 1.1, 1.9, respectively). We observed a higher association between long-term PM2.5 exposure and mortality in warmer cities. Furthermore, we observed increasing estimates with increasing obesity rates, %residents and families in poverty, %black residents and %population without a high school degree, and lower effects with increasing median household income and %white residents.

Conclusions: To the best of our knowledge, this is the first study to assess modification by temperature and community-level characteristics on the long-term PM2.5-survival association. Our findings suggest that living in cities with high temperatures and low socio economic status (SES) is associated with higher effect estimates.

Figure 1

By-region PM_2.5–mortality effect estimates, presented as HRs (95%CI) per 10 µg/m³ of PM_2.5.

Figure 2

The impact of annual average temperature on the PM_2.5–mortality association. The color of the points is a function of the precision of each city-specific HR, with darker color for higher precision.

Figure 3

Effect modification by selected variables on the PM_2.5–mortality association, presented as HRs (95%CI) per 10 µg/m³ at the 25^th and 75^th percentiles of each variable. The variables presented here significantly modify the long-term PM_2.5-mortality association. The results for all variables examined are presented in eTable 3.