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Associations between Long-Term Exposure to Chemical Constituents of Fine Particulate Matter (PM(2.5)) and Mortality in Medicare Enrollees in the Eastern United States

BACKGROUND: Several epidemiological studies have reported that long-term exposure to fine particulate matter (PM(2.5)) is associated with higher mortality. Evidence regarding contributions of PM(2.5) constituents is inconclusive. OBJECTIVES: We assembled a data set of 12.5 million Medicare enrollees...

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Detalles Bibliográficos
Autores principales: Chung, Yeonseung, Dominici, Francesca, Wang, Yun, Coull, Brent A., Bell, Michelle L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: NLM-Export 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4421760/
https://www.ncbi.nlm.nih.gov/pubmed/25565179
http://dx.doi.org/10.1289/ehp.1307549
Descripción
Sumario:BACKGROUND: Several epidemiological studies have reported that long-term exposure to fine particulate matter (PM(2.5)) is associated with higher mortality. Evidence regarding contributions of PM(2.5) constituents is inconclusive. OBJECTIVES: We assembled a data set of 12.5 million Medicare enrollees (≥ 65 years of age) to determine which PM(2.5) constituents are a) associated with mortality controlling for previous-year PM(2.5) total mass (main effect); and b) elevated in locations exhibiting stronger associations between previous-year PM(2.5) and mortality (effect modification). METHODS: For 518 PM(2.5) monitoring locations (eastern United States, 2000–2006), we calculated monthly mortality rates, monthly long-term (previous 1-year average) PM(2.5), and 7-year averages (2000–2006) of major PM(2.5) constituents [elemental carbon (EC), organic carbon matter (OCM), sulfate (SO(4)(2–)), silicon (Si), nitrate (NO(3)(–)), and sodium (Na)] and community-level variables. We applied a Bayesian hierarchical model to estimate location-specific mortality rates associated with previous-year PM(2.5) (model level 1) and identify constituents that contributed to the spatial variability of mortality, and constituents that modified associations between previous-year PM(2.5) and mortality (model level 2), controlling for community-level confounders. RESULTS: One–standard deviation (SD) increases in 7-year average EC, Si, and NO(3)(–) concentrations were associated with 1.3% [95% posterior interval (PI): 0.3, 2.2], 1.4% (95% PI: 0.6, 2.4), and 1.2% (95% PI: 0.4, 2.1) increases in monthly mortality, controlling for previous-year PM(2.5). Associations between previous-year PM(2.5) and mortality were stronger in combination with 1-SD increases in SO(4)(2–) and Na. CONCLUSIONS: Long-term exposures to PM(2.5) and several constituents were associated with mortality in the elderly population of the eastern United States. Moreover, some constituents increased the association between long-term exposure to PM(2.5) and mortality. These results provide new evidence that chemical composition can partly explain the differential toxicity of PM(2.5). CITATION: Chung Y, Dominici F, Wang Y, Coull BA, Bell ML. 2015. Associations between long-term exposure to chemical constituents of fine particulate matter (PM(2.5)) and mortality in Medicare enrollees in the eastern United States. Environ Health Perspect 123:467–474; http://dx.doi.org/10.1289/ehp.1307549