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Distributed Lag Analyses of Daily Hospital Admissions and Source-Apportioned Fine Particle Air Pollution
BACKGROUND: Past time-series studies of the health effects of fine particulate matter [aerodynamic diameter ≤ 2.5 μm (PM(2.5))] have used chemically nonspecific PM(2.5) mass. However, PM(2.5) is known to vary in chemical composition with source, and health impacts may vary accordingly. OBJECTIVE: We...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
National Institute of Environmental Health Sciences
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3080925/ https://www.ncbi.nlm.nih.gov/pubmed/21172759 http://dx.doi.org/10.1289/ehp.1002638 |
Sumario: | BACKGROUND: Past time-series studies of the health effects of fine particulate matter [aerodynamic diameter ≤ 2.5 μm (PM(2.5))] have used chemically nonspecific PM(2.5) mass. However, PM(2.5) is known to vary in chemical composition with source, and health impacts may vary accordingly. OBJECTIVE: We tested the association between source-specific daily PM(2.5) mass and hospital admissions in a time-series investigation that considered both single-lag and distributed-lag models. METHODS: Daily PM(2.5) speciation measurements collected in midtown Manhattan were analyzed via positive matrix factorization source apportionment. Daily and distributed-lag generalized linear models of Medicare respiratory and cardiovascular hospital admissions during 2001–2002 considered PM(2.5) mass and PM(2.5) from five sources: transported sulfate, residual oil, traffic, steel metal works, and soil. RESULTS: Source-related PM(2.5) (specifically steel and traffic) was significantly associated with hospital admissions but not with total PM(2.5) mass. Steel metal works–related PM(2.5) was associated with respiratory admissions for multiple-lag days, especially during the cleanup efforts at the World Trade Center. Traffic-related PM(2.5) was consistently associated with same-day cardiovascular admissions across disease-specific subcategories. PM(2.5) constituents associated with each source (e.g., elemental carbon with traffic) were likewise associated with admissions in a consistent manner. Mean effects of distributed-lag models were significantly greater than were maximum single-day effect models for both steel- and traffic-related PM(2.5). CONCLUSIONS: Past analyses that have considered only PM(2.5) mass or only maximum single-day lag effects have likely underestimated PM(2.5) health effects by not considering source-specific and distributed-lag effects. Differing lag structures and disease specificity observed for steel-related versus traffic-related PM(2.5) raise the possibility of distinct mechanistic pathways of health effects for particles of differing chemical composition. |
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