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Air pollution and mortality in a large, representative U.S. cohort: multiple-pollutant analyses, and spatial and temporal decompositions

BACKGROUND: Cohort studies have documented associations between fine particulate matter air pollution (PM(2.5)) and mortality risk. However, there remains uncertainty regarding the contribution of co-pollutants and the stability of pollution-mortality associations in models that include multiple air...

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Detalles Bibliográficos
Autores principales: Lefler, Jacob S., Higbee, Joshua D., Burnett, Richard T., Ezzati, Majid, Coleman, Nathan C., Mann, Dalton D., Marshall, Julian D., Bechle, Matthew, Wang, Yuzhou, Robinson, Allen L., Arden Pope, C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6873509/
https://www.ncbi.nlm.nih.gov/pubmed/31752939
http://dx.doi.org/10.1186/s12940-019-0544-9
Descripción
Sumario:BACKGROUND: Cohort studies have documented associations between fine particulate matter air pollution (PM(2.5)) and mortality risk. However, there remains uncertainty regarding the contribution of co-pollutants and the stability of pollution-mortality associations in models that include multiple air pollutants. Furthermore, it is unclear whether the PM(2.5)-mortality relationship varies spatially, when exposures are decomposed according to scale of spatial variability, or temporally, when effect estimates are allowed to change between years. METHODS: A cohort of 635,539 individuals was compiled using public National Health Interview Survey (NHIS) data from 1987 to 2014 and linked with mortality follow-up through 2015. Modelled air pollution exposure estimates for PM(2.5), other criteria air pollutants, and spatial decompositions (< 1 km, 1–10 km, 10–100 km, > 100 km) of PM(2.5) were assigned at the census-tract level. The NHIS samples were also divided into yearly cohorts for temporally-decomposed analyses. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) in regression models that included up to six criteria pollutants; four spatial decompositions of PM(2.5); and two- and five-year lagged mean PM(2.5) exposures in the temporally-decomposed cohorts. Meta-analytic fixed-effect estimates were calculated using results from temporally-decomposed analyses and compared with time-independent results using 17- and 28-year exposure windows. RESULTS: In multiple-pollutant analyses, PM(2.5) demonstrated the most robust pollutant-mortality association. Coarse fraction particulate matter (PM(2.5–10)) and sulfur dioxide (SO(2)) were also associated with excess mortality risk. The PM(2.5)-mortality association was observed across all four spatial scales of PM(2.5), with higher but less precisely estimated HRs observed for local (< 1 km) and neighborhood (1–10 km) variations. In temporally-decomposed analyses, the PM(2.5)-mortality HRs were stable across yearly cohorts. The meta-analytic HR using two-year lagged PM(2.5) equaled 1.10 (95% CI 1.07, 1.13) per 10 μg/m(3). Comparable results were observed in time-independent analyses using a 17-year (HR 1.13, CI 1.09, 1.16) or 28-year (HR 1.09, CI 1.07, 1.12) exposure window. CONCLUSIONS: Long-term exposures to PM(2.5), PM(2.5–10), and SO(2) were associated with increased risk of all-cause and cardiopulmonary mortality. Each spatial decomposition of PM(2.5) was associated with mortality risk, and PM(2.5)-mortality associations were consistent over time.