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A New Method to Jointly Estimate the Mortality Risk of Long-Term Exposure to Fine Particulate Matter and its Components

Most studies on the association between exposure to fine particulate matter (PM(2.5)) and mortality have considered only total concentration of PM(2.5) or individual components of PM(2.5), and not the combined effects of concentration and particulate composition. We sought to develop a method to est...

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Autores principales: Crouse, Dan L., Philip, Sajeev, van Donkelaar, Aaron, Martin, Randall V., Jessiman, Barry, Peters, Paul A., Weichenthal, Scott, Brook, Jeffrey R., Hubbell, Bryan, Burnett, Richard T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4702114/
https://www.ncbi.nlm.nih.gov/pubmed/26732864
http://dx.doi.org/10.1038/srep18916
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author Crouse, Dan L.
Philip, Sajeev
van Donkelaar, Aaron
Martin, Randall V.
Jessiman, Barry
Peters, Paul A.
Weichenthal, Scott
Brook, Jeffrey R.
Hubbell, Bryan
Burnett, Richard T.
author_facet Crouse, Dan L.
Philip, Sajeev
van Donkelaar, Aaron
Martin, Randall V.
Jessiman, Barry
Peters, Paul A.
Weichenthal, Scott
Brook, Jeffrey R.
Hubbell, Bryan
Burnett, Richard T.
author_sort Crouse, Dan L.
collection PubMed
description Most studies on the association between exposure to fine particulate matter (PM(2.5)) and mortality have considered only total concentration of PM(2.5) or individual components of PM(2.5), and not the combined effects of concentration and particulate composition. We sought to develop a method to estimate the risk of death from long-term exposure to PM(2.5) and the distribution of its components, namely: sulphate, nitrate, ammonium, organic mass, black carbon, and mineral dust. We decomposed PM(2.5) exposure into the sum of total concentration and the proportion of each component. We estimated the risk of death due to exposure using a cohort of ~2.4 million Canadians who were followed for vital status over 16 years. Modelling the concentration of PM(2.5) with the distribution of the proportions of components together was a superior predictor for mortality than either total PM(2.5) concentration alone, or all component concentrations modelled together. Our new approach has the advantage of characterizing the toxicity of the atmosphere in its entirety. This is required to fully understand the health benefits associated with strategies to improve air quality that may result in complex changes not only in PM(2.5) concentration, but also in the distribution of particle components.
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spelling pubmed-47021142016-01-14 A New Method to Jointly Estimate the Mortality Risk of Long-Term Exposure to Fine Particulate Matter and its Components Crouse, Dan L. Philip, Sajeev van Donkelaar, Aaron Martin, Randall V. Jessiman, Barry Peters, Paul A. Weichenthal, Scott Brook, Jeffrey R. Hubbell, Bryan Burnett, Richard T. Sci Rep Article Most studies on the association between exposure to fine particulate matter (PM(2.5)) and mortality have considered only total concentration of PM(2.5) or individual components of PM(2.5), and not the combined effects of concentration and particulate composition. We sought to develop a method to estimate the risk of death from long-term exposure to PM(2.5) and the distribution of its components, namely: sulphate, nitrate, ammonium, organic mass, black carbon, and mineral dust. We decomposed PM(2.5) exposure into the sum of total concentration and the proportion of each component. We estimated the risk of death due to exposure using a cohort of ~2.4 million Canadians who were followed for vital status over 16 years. Modelling the concentration of PM(2.5) with the distribution of the proportions of components together was a superior predictor for mortality than either total PM(2.5) concentration alone, or all component concentrations modelled together. Our new approach has the advantage of characterizing the toxicity of the atmosphere in its entirety. This is required to fully understand the health benefits associated with strategies to improve air quality that may result in complex changes not only in PM(2.5) concentration, but also in the distribution of particle components. Nature Publishing Group 2016-01-06 /pmc/articles/PMC4702114/ /pubmed/26732864 http://dx.doi.org/10.1038/srep18916 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Crouse, Dan L.
Philip, Sajeev
van Donkelaar, Aaron
Martin, Randall V.
Jessiman, Barry
Peters, Paul A.
Weichenthal, Scott
Brook, Jeffrey R.
Hubbell, Bryan
Burnett, Richard T.
A New Method to Jointly Estimate the Mortality Risk of Long-Term Exposure to Fine Particulate Matter and its Components
title A New Method to Jointly Estimate the Mortality Risk of Long-Term Exposure to Fine Particulate Matter and its Components
title_full A New Method to Jointly Estimate the Mortality Risk of Long-Term Exposure to Fine Particulate Matter and its Components
title_fullStr A New Method to Jointly Estimate the Mortality Risk of Long-Term Exposure to Fine Particulate Matter and its Components
title_full_unstemmed A New Method to Jointly Estimate the Mortality Risk of Long-Term Exposure to Fine Particulate Matter and its Components
title_short A New Method to Jointly Estimate the Mortality Risk of Long-Term Exposure to Fine Particulate Matter and its Components
title_sort new method to jointly estimate the mortality risk of long-term exposure to fine particulate matter and its components
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4702114/
https://www.ncbi.nlm.nih.gov/pubmed/26732864
http://dx.doi.org/10.1038/srep18916
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