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Acute effect of daily fine particulate matter pollution on cerebrovascular mortality in Shanghai, China: a population-based time series study
Numerous studies have investigated the impacts of ambient fine particulate matter (PM(2.5)) on human health. In this study, we examined the association of daily PM(2.5) concentrations with the number of deaths for the cerebrovascular disease on the same day, using the generalized additive model (GAM...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6717171/ https://www.ncbi.nlm.nih.gov/pubmed/31264151 http://dx.doi.org/10.1007/s11356-019-05689-8 |
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author | Leepe, Khadija Akter Li, Mei Fang, Xin Hiyoshi, Ayako Cao, Yang |
author_facet | Leepe, Khadija Akter Li, Mei Fang, Xin Hiyoshi, Ayako Cao, Yang |
author_sort | Leepe, Khadija Akter |
collection | PubMed |
description | Numerous studies have investigated the impacts of ambient fine particulate matter (PM(2.5)) on human health. In this study, we examined the association of daily PM(2.5) concentrations with the number of deaths for the cerebrovascular disease on the same day, using the generalized additive model (GAM) controlling for temporal trend and meteorological variables. We used the data between 2012 and 2014 from Shanghai, China, where the adverse health effects of PM(2.5) have been of particular concern. Three different approaches (principal component analysis, shrinkage smoothers, and the least absolute shrinkage and selection operator regularization) were used in GAM to handle multicollinear meteorological variables. Our results indicate that the average daily concentration of PM(2.5) in Shanghai was high, 55 μg/m(3), with an average daily death for cerebrovascular disease (CVD) of 62. There was 1.7% raised cerebrovascular disease deaths per 10 μg/m(3) increase in PM(2.5) concentration in the unadjusted model. However, PM(2.5) concentration was no longer associated with CVD deaths after controlling for meteorological variables. The results were consistent in the three modelling techniques that we used. As a large number of people are exposed to air pollution, further investigation with longer time period including individual-level information is needed to examine the association. |
format | Online Article Text |
id | pubmed-6717171 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-67171712019-09-13 Acute effect of daily fine particulate matter pollution on cerebrovascular mortality in Shanghai, China: a population-based time series study Leepe, Khadija Akter Li, Mei Fang, Xin Hiyoshi, Ayako Cao, Yang Environ Sci Pollut Res Int Research Article Numerous studies have investigated the impacts of ambient fine particulate matter (PM(2.5)) on human health. In this study, we examined the association of daily PM(2.5) concentrations with the number of deaths for the cerebrovascular disease on the same day, using the generalized additive model (GAM) controlling for temporal trend and meteorological variables. We used the data between 2012 and 2014 from Shanghai, China, where the adverse health effects of PM(2.5) have been of particular concern. Three different approaches (principal component analysis, shrinkage smoothers, and the least absolute shrinkage and selection operator regularization) were used in GAM to handle multicollinear meteorological variables. Our results indicate that the average daily concentration of PM(2.5) in Shanghai was high, 55 μg/m(3), with an average daily death for cerebrovascular disease (CVD) of 62. There was 1.7% raised cerebrovascular disease deaths per 10 μg/m(3) increase in PM(2.5) concentration in the unadjusted model. However, PM(2.5) concentration was no longer associated with CVD deaths after controlling for meteorological variables. The results were consistent in the three modelling techniques that we used. As a large number of people are exposed to air pollution, further investigation with longer time period including individual-level information is needed to examine the association. Springer Berlin Heidelberg 2019-07-01 2019 /pmc/articles/PMC6717171/ /pubmed/31264151 http://dx.doi.org/10.1007/s11356-019-05689-8 Text en © The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Research Article Leepe, Khadija Akter Li, Mei Fang, Xin Hiyoshi, Ayako Cao, Yang Acute effect of daily fine particulate matter pollution on cerebrovascular mortality in Shanghai, China: a population-based time series study |
title | Acute effect of daily fine particulate matter pollution on cerebrovascular mortality in Shanghai, China: a population-based time series study |
title_full | Acute effect of daily fine particulate matter pollution on cerebrovascular mortality in Shanghai, China: a population-based time series study |
title_fullStr | Acute effect of daily fine particulate matter pollution on cerebrovascular mortality in Shanghai, China: a population-based time series study |
title_full_unstemmed | Acute effect of daily fine particulate matter pollution on cerebrovascular mortality in Shanghai, China: a population-based time series study |
title_short | Acute effect of daily fine particulate matter pollution on cerebrovascular mortality in Shanghai, China: a population-based time series study |
title_sort | acute effect of daily fine particulate matter pollution on cerebrovascular mortality in shanghai, china: a population-based time series study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6717171/ https://www.ncbi.nlm.nih.gov/pubmed/31264151 http://dx.doi.org/10.1007/s11356-019-05689-8 |
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