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The Shape of the Concentration–Response Association between Fine Particulate Matter Pollution and Human Mortality in Beijing, China, and Its Implications for Health Impact Assessment

BACKGROUND: Studies found approximately linear short-term associations between particulate matter (PM) and mortality in Western communities. However, in China, where the urban PM levels are typically considerably higher than in Western communities, some studies suggest nonlinearity in this associati...

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Autores principales: Yan, Meilin, Wilson, Ander, Bell, Michelle L., Peng, Roger D., Sun, Qinghua, Pu, Weiwei, Yin, Xiaomei, Li, Tiantian, Anderson, G. Brooke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Environmental Health Perspectives 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6792375/
https://www.ncbi.nlm.nih.gov/pubmed/31170008
http://dx.doi.org/10.1289/EHP4464
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author Yan, Meilin
Wilson, Ander
Bell, Michelle L.
Peng, Roger D.
Sun, Qinghua
Pu, Weiwei
Yin, Xiaomei
Li, Tiantian
Anderson, G. Brooke
author_facet Yan, Meilin
Wilson, Ander
Bell, Michelle L.
Peng, Roger D.
Sun, Qinghua
Pu, Weiwei
Yin, Xiaomei
Li, Tiantian
Anderson, G. Brooke
author_sort Yan, Meilin
collection PubMed
description BACKGROUND: Studies found approximately linear short-term associations between particulate matter (PM) and mortality in Western communities. However, in China, where the urban PM levels are typically considerably higher than in Western communities, some studies suggest nonlinearity in this association. Health impact assessments (HIA) of PM in China have generally not incorporated nonlinearity in the concentration–response (C-R) association, which could result in large discrepancies in estimates of excess deaths if the true association is nonlinear. OBJECTIVES: We investigated nonlinearity in the C-R associations between with PM with aerodynamic diameter [Formula: see text] ([Formula: see text]) and mortality in Beijing, China, and the sensitivity of HIA to linearity assumptions. METHODS: We modeled the C-R association between [Formula: see text] and cause-specific mortality in Beijing, China (2009–2012), using generalized linear models (GLM). [Formula: see text] was included through either linear, piecewise-linear, or spline functions to investigate evidence of nonlinearity. To determine the sensitivity of HIA to linearity assumptions, we estimated [Formula: see text]-attributable deaths using both linear- and nonlinear-based C-R associations between [Formula: see text] and mortality. RESULTS: We found some evidence that, for nonaccidental and circulatory mortality, the shape of the C-R association was relatively flat at lower concentrations of [Formula: see text] , but then had a positive slope at higher concentrations, indicating nonlinearity. Conversely, the shape for respiratory mortality was positive and linear at lower concentrations of [Formula: see text] , but then leveled off at the higher concentrations. Estimates of excess deaths attributable to short-term [Formula: see text] exposure were, in some cases, very sensitive to the linearity assumption in the association, but in other cases robust to this assumption. CONCLUSIONS: Our results demonstrate some evidence of nonlinearity in [Formula: see text] –mortality associations and that an assumption of linearity in this association can influence HIAs, highlighting the importance of understanding potential nonlinearity in the [Formula: see text] –mortality association at the high concentrations of [Formula: see text] in developing megacities like Beijing. https://doi.org/10.1289/EHP4464
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spelling pubmed-67923752019-11-06 The Shape of the Concentration–Response Association between Fine Particulate Matter Pollution and Human Mortality in Beijing, China, and Its Implications for Health Impact Assessment Yan, Meilin Wilson, Ander Bell, Michelle L. Peng, Roger D. Sun, Qinghua Pu, Weiwei Yin, Xiaomei Li, Tiantian Anderson, G. Brooke Environ Health Perspect Research BACKGROUND: Studies found approximately linear short-term associations between particulate matter (PM) and mortality in Western communities. However, in China, where the urban PM levels are typically considerably higher than in Western communities, some studies suggest nonlinearity in this association. Health impact assessments (HIA) of PM in China have generally not incorporated nonlinearity in the concentration–response (C-R) association, which could result in large discrepancies in estimates of excess deaths if the true association is nonlinear. OBJECTIVES: We investigated nonlinearity in the C-R associations between with PM with aerodynamic diameter [Formula: see text] ([Formula: see text]) and mortality in Beijing, China, and the sensitivity of HIA to linearity assumptions. METHODS: We modeled the C-R association between [Formula: see text] and cause-specific mortality in Beijing, China (2009–2012), using generalized linear models (GLM). [Formula: see text] was included through either linear, piecewise-linear, or spline functions to investigate evidence of nonlinearity. To determine the sensitivity of HIA to linearity assumptions, we estimated [Formula: see text]-attributable deaths using both linear- and nonlinear-based C-R associations between [Formula: see text] and mortality. RESULTS: We found some evidence that, for nonaccidental and circulatory mortality, the shape of the C-R association was relatively flat at lower concentrations of [Formula: see text] , but then had a positive slope at higher concentrations, indicating nonlinearity. Conversely, the shape for respiratory mortality was positive and linear at lower concentrations of [Formula: see text] , but then leveled off at the higher concentrations. Estimates of excess deaths attributable to short-term [Formula: see text] exposure were, in some cases, very sensitive to the linearity assumption in the association, but in other cases robust to this assumption. CONCLUSIONS: Our results demonstrate some evidence of nonlinearity in [Formula: see text] –mortality associations and that an assumption of linearity in this association can influence HIAs, highlighting the importance of understanding potential nonlinearity in the [Formula: see text] –mortality association at the high concentrations of [Formula: see text] in developing megacities like Beijing. https://doi.org/10.1289/EHP4464 Environmental Health Perspectives 2019-06-06 /pmc/articles/PMC6792375/ /pubmed/31170008 http://dx.doi.org/10.1289/EHP4464 Text en EHP is an open-access journal published with support from the National Institute of Environmental Health Sciences, National Institutes of Health. All content is public domain unless otherwise noted.
spellingShingle Research
Yan, Meilin
Wilson, Ander
Bell, Michelle L.
Peng, Roger D.
Sun, Qinghua
Pu, Weiwei
Yin, Xiaomei
Li, Tiantian
Anderson, G. Brooke
The Shape of the Concentration–Response Association between Fine Particulate Matter Pollution and Human Mortality in Beijing, China, and Its Implications for Health Impact Assessment
title The Shape of the Concentration–Response Association between Fine Particulate Matter Pollution and Human Mortality in Beijing, China, and Its Implications for Health Impact Assessment
title_full The Shape of the Concentration–Response Association between Fine Particulate Matter Pollution and Human Mortality in Beijing, China, and Its Implications for Health Impact Assessment
title_fullStr The Shape of the Concentration–Response Association between Fine Particulate Matter Pollution and Human Mortality in Beijing, China, and Its Implications for Health Impact Assessment
title_full_unstemmed The Shape of the Concentration–Response Association between Fine Particulate Matter Pollution and Human Mortality in Beijing, China, and Its Implications for Health Impact Assessment
title_short The Shape of the Concentration–Response Association between Fine Particulate Matter Pollution and Human Mortality in Beijing, China, and Its Implications for Health Impact Assessment
title_sort shape of the concentration–response association between fine particulate matter pollution and human mortality in beijing, china, and its implications for health impact assessment
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6792375/
https://www.ncbi.nlm.nih.gov/pubmed/31170008
http://dx.doi.org/10.1289/EHP4464
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