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A framework for estimating the US mortality burden of fine particulate matter exposure attributable to indoor and outdoor microenvironments
Exposure to fine particulate matter (PM(2.5)) is associated with increased mortality. Although epidemiology studies typically use outdoor PM(2.5) concentrations as surrogates for exposure, the majority of PM(2.5) exposure in the US occurs in microenvironments other than outdoors. We develop a framew...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group US
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7039807/ https://www.ncbi.nlm.nih.gov/pubmed/30518794 http://dx.doi.org/10.1038/s41370-018-0103-4 |
Sumario: | Exposure to fine particulate matter (PM(2.5)) is associated with increased mortality. Although epidemiology studies typically use outdoor PM(2.5) concentrations as surrogates for exposure, the majority of PM(2.5) exposure in the US occurs in microenvironments other than outdoors. We develop a framework for estimating the total US mortality burden attributable to exposure to PM(2.5) of both indoor and outdoor origin in the primary non-smoking microenvironments in which people spend most of their time. The framework utilizes an exposure-response function combined with adjusted mortality effect estimates that account for underlying exposures to PM(2.5) of outdoor origin that likely occurred in the original epidemiology populations from which effect estimates are derived. We demonstrate the framework using several different scenarios to estimate the potential magnitude and bounds of the US mortality burden attributable to total PM(2.5) exposure across all non-smoking environments under a variety of assumptions. Our best estimates of the US mortality burden associated with total PM(2.5) exposure in the year 2012 range from ~230,000 to ~300,000 deaths. Indoor exposure to PM(2.5) of outdoor origin is typically the largest total exposure, accounting for ~40–60% of total mortality, followed by residential exposure to indoor PM(2.5) sources, which also drives the majority of variability in each scenario. |
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