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Assessing short-term impact of PM(10) on mortality using a semiparametric generalized propensity score approach
BACKGROUND: The shape of the exposure-response curve describing the effects of air pollution on population health has crucial regulatory implications, and it is important in assessing causal impacts of hypothetical policies of air pollution reduction. METHODS: After having reformulated the problem o...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7193397/ https://www.ncbi.nlm.nih.gov/pubmed/32357874 http://dx.doi.org/10.1186/s12940-020-00599-6 |
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author | Forastiere, Laura Carugno, Michele Baccini, Michela |
author_facet | Forastiere, Laura Carugno, Michele Baccini, Michela |
author_sort | Forastiere, Laura |
collection | PubMed |
description | BACKGROUND: The shape of the exposure-response curve describing the effects of air pollution on population health has crucial regulatory implications, and it is important in assessing causal impacts of hypothetical policies of air pollution reduction. METHODS: After having reformulated the problem of assessing the short-term impact of air pollution on health within the potential outcome approach to causal inference, we developed a method based on the generalized propensity score (GPS) to estimate the average dose-response function (aDRF) and quantify attributable deaths under different counterfactual scenarios of air pollution reduction. We applied the proposed approach to assess the impact of airborne particles with a diameter less than or equal to 10 μm (PM(10)) on deaths from natural, cardiovascular and respiratory causes in the city of Milan, Italy (2003-2006). RESULTS: As opposed to what is commonly assumed, the estimated aDRFs were not linear, being steeper for low-moderate values of exposure. In the case of natural mortality, the curve became flatter for higher levels; this behavior was less pronounced for cause-specific mortality. The effect was larger in days characterized by higher temperature. According to the curves, we estimated that a hypothetical intervention able to set the daily exposure levels exceeding 40 μg/m(3) to exactly 40 would have avoided 1157 deaths (90%CI: 689, 1645) in the whole study period, 312 of which for respiratory causes and 771 for cardiovascular causes. These impacts were higher than those obtained previously from regression-based methods. CONCLUSION: This novel method based on the GPS allowed estimating the average dose-response function and calculating attributable deaths, without requiring strong assumptions about the shape of the relationship. Its potential as a tool for investigating effect modification by temperature and its use in other environmental epidemiology contexts deserve further investigation. |
format | Online Article Text |
id | pubmed-7193397 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-71933972020-05-06 Assessing short-term impact of PM(10) on mortality using a semiparametric generalized propensity score approach Forastiere, Laura Carugno, Michele Baccini, Michela Environ Health Methodology BACKGROUND: The shape of the exposure-response curve describing the effects of air pollution on population health has crucial regulatory implications, and it is important in assessing causal impacts of hypothetical policies of air pollution reduction. METHODS: After having reformulated the problem of assessing the short-term impact of air pollution on health within the potential outcome approach to causal inference, we developed a method based on the generalized propensity score (GPS) to estimate the average dose-response function (aDRF) and quantify attributable deaths under different counterfactual scenarios of air pollution reduction. We applied the proposed approach to assess the impact of airborne particles with a diameter less than or equal to 10 μm (PM(10)) on deaths from natural, cardiovascular and respiratory causes in the city of Milan, Italy (2003-2006). RESULTS: As opposed to what is commonly assumed, the estimated aDRFs were not linear, being steeper for low-moderate values of exposure. In the case of natural mortality, the curve became flatter for higher levels; this behavior was less pronounced for cause-specific mortality. The effect was larger in days characterized by higher temperature. According to the curves, we estimated that a hypothetical intervention able to set the daily exposure levels exceeding 40 μg/m(3) to exactly 40 would have avoided 1157 deaths (90%CI: 689, 1645) in the whole study period, 312 of which for respiratory causes and 771 for cardiovascular causes. These impacts were higher than those obtained previously from regression-based methods. CONCLUSION: This novel method based on the GPS allowed estimating the average dose-response function and calculating attributable deaths, without requiring strong assumptions about the shape of the relationship. Its potential as a tool for investigating effect modification by temperature and its use in other environmental epidemiology contexts deserve further investigation. BioMed Central 2020-05-01 /pmc/articles/PMC7193397/ /pubmed/32357874 http://dx.doi.org/10.1186/s12940-020-00599-6 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visithttp://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Methodology Forastiere, Laura Carugno, Michele Baccini, Michela Assessing short-term impact of PM(10) on mortality using a semiparametric generalized propensity score approach |
title | Assessing short-term impact of PM(10) on mortality using a semiparametric generalized propensity score approach |
title_full | Assessing short-term impact of PM(10) on mortality using a semiparametric generalized propensity score approach |
title_fullStr | Assessing short-term impact of PM(10) on mortality using a semiparametric generalized propensity score approach |
title_full_unstemmed | Assessing short-term impact of PM(10) on mortality using a semiparametric generalized propensity score approach |
title_short | Assessing short-term impact of PM(10) on mortality using a semiparametric generalized propensity score approach |
title_sort | assessing short-term impact of pm(10) on mortality using a semiparametric generalized propensity score approach |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7193397/ https://www.ncbi.nlm.nih.gov/pubmed/32357874 http://dx.doi.org/10.1186/s12940-020-00599-6 |
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