title: Long-term Exposure to PM2.5 and Mortality Among Older Adults in the Southeastern US.
abstract: Little is known about what factors modify the effect of long-term exposure to PM2.5 on mortality, in part because in most previous studies certain groups such as rural residents and individuals with lower socioeconomic status (SES) are under-represented.
  
  
  
  We studied 13.1 million Medicare beneficiaries (age ≥65) residing in seven southeastern US states during 2000-2013 with 95 million person-years of follow-up. We predicted annual average of PM2.5 in each zip code tabulation area (ZCTA) using a hybrid spatiotemporal model. We fit Cox proportional hazards models to estimate the association between long-term PM2.5 and mortality. We tested effect modification by individual-level covariates (race, sex, eligibility for both Medicare and Medicaid, and medical history), neighborhood-level covariates (urbanicity, percentage below poverty level, lower education, median income, and median home value), mean summer temperature, and mass fraction of 11 PM2.5 components.
  
  
  
  The hazard ratio (HR) for death was 1.021 (95% confidence interval: 1.019, 1.022) per 1 μg m increase in annual PM2.5. The HR decreased with age. It was higher among males, non-whites, dual-eligible individuals, and beneficiaries with previous hospital admissions. It was higher in neighborhoods with lower SES or higher urbanicity. The HR increased with mean summer temperature. The risk associated with PM2.5 increased with relative concentration of elemental carbon, vanadium, copper, calcium, and iron and decreased with nitrate, organic carbon, and sulfate.
  
  
  
  Associations between long-term PM2.5 exposure and death were modified by individual-level, neighborhood-level variables, temperature, and chemical compositions.
authors.affiliation: From the aDepartment of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA; and bJohn A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA.
authors.forename: Yan
authors.initials: Y
authors.lastname: Wang
authors.forename: Liuhua
authors.initials: L
authors.lastname: Shi
authors.forename: Mihye
authors.initials: M
authors.lastname: Lee
authors.forename: Pengfei
authors.initials: P
authors.lastname: Liu
authors.forename: Qian
authors.initials: Q
authors.lastname: Di
authors.forename: Antonella
authors.initials: A
authors.lastname: Zanobetti
authors.forename: Joel D
authors.initials: JD
authors.lastname: Schwartz
mesh_terms: D001741:Black or African American / Q000706:statistics & numerical data; D000368:Aged; D000369:Aged, 80 and over; D000397:Air Pollution / Q000706:statistics & numerical data*; D004781:Environmental Exposure / Q000706:statistics & numerical data*; D005006:Ethnicity / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D008297:Male; D008484:Medicaid; D006278:Medicare; D009026:Mortality; D052638:Particulate Matter; D016016:Proportional Hazards Models; D012111:Residence Characteristics / Q000706:statistics & numerical data; D015144:Southeastern United States; D013696:Temperature; D014481:United States; D044465:White People / Q000706:statistics & numerical data
chemical_list: D052638:Particulate Matter