title: 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.
authors.affiliation: From the Departments of aEnvironmental Health, bEpidemiology, & cBiostatistics, Harvard T.H. Chan School of Public Health, Boston, MA.
authors.forename: Marianthi-Anna
authors.initials: MA
authors.lastname: Kioumourtzoglou
authors.forename: Joel
authors.initials: J
authors.lastname: Schwartz
authors.forename: Peter
authors.initials: P
authors.lastname: James
authors.forename: Francesca
authors.initials: F
authors.lastname: Dominici
authors.forename: Antonella
authors.initials: A
authors.lastname: Zanobetti
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D002947:Cities / Q000453:epidemiology* / Q000706:statistics & numerical data; D004522:Educational Status; D005006:Ethnicity / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D007182:Income / Q000706:statistics & numerical data; D008297:Male; D006278:Medicare; D009026:Mortality; D009765:Obesity / Q000453:epidemiology*; D052638:Particulate Matter; D011203:Poverty / Q000706:statistics & numerical data*; D016016:Proportional Hazards Models; D012923:Social Class; D013696:Temperature; D014481:United States / Q000453:epidemiology
chemical_list: D052638:Particulate Matter