Long-term Exposure to PM2.5 and Mortality Among Older Adults in the Southeastern US

Abstract

Background 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. Methods 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. Results The hazard ratio (HR) for death was 1.021 (95% confidence interval: 1.019–1.022) per one μg m-3 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. Conclusions Associations between long-term PM2.5 exposure and death were modified by individual-level, neighborhood-level variables, temperature, and chemical compositions.

Doubly Robust Additive Hazards Models to Estimate Effects of a Continuous Exposure on Survival

“…By comparison, we found a hazard ratio of 1.021 (1.019, 1.022) using Cox proportional hazard model adjusting for the same set of covariates. 17 We further found that an increase in the percentage of truncation from 1% to 5% resulted in a decrease in the effect estimate for PM 2.5 (eFigure 9; http://links.lww.com/EDE/B260). …”

“…By comparison, some effect modification using hazard difference (e.g., hospital admissions, dual eligibility) showed the same direction as hazard ratios, whereas some (e.g., age) does not. 17 In addition, we found that black people with dual eligibility had a hazard difference of 1.60 × 10 −3 (1.21, 1.99) × 10 −3 . Black people age 75–84 years old had a hazard difference of 2.28 × 10 −3 (1.80, 2.75) × 10 −3 , suggesting an increase in susceptibility among these populations.…”

“…25 The confounders include individual-, ZCTA-, and county-level covariates (age, race, sex, socioeconomic status, medical history, and area-level health variables), which were assumed constant within a follow-up year but could vary between follow-up years. A detailed description of the covariates is published elsewhere 17 and is also given in eAppendix 7; http://links.lww.com/EDE/B260.…”

“…The hazard differences are compared with the estimated hazard ratios for the same set of subgroups reported in a previous publication. 17 …”

Air Pollution and Mortality in the Medicare Population

“…4,[7][8][9] Studies with large cohorts have investigated the relationship between long-term exposures to PM 2.5 and ozone and mortality 4,[9][10][11][12][13] ; others have estimated the health effects of fine particles at low concentrations (e.g., below 12 μg per cubic meter for PM 2.5 ). [14][15][16][17][18] However, most of these studies have included populations whose socioeconomic status is higher than the national average and who reside in well-monitored urban areas. Consequently, these studies provide limited information on the health effects of long-term exposure to low levels of air pollution in smaller cities and rural areas or among minorities or persons with low socioeconomic status.…”