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Mathematical modeling in the health risk assessment of air pollution-related disease burden in China: A review
This review paper covers an overview of air pollution-related disease burden in China and a literature review on the previous studies which have recently adopted a mathematical modeling approach to demonstrate the relative risk (RR) of air pollution-related disease burden. The associations between a...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9727382/ https://www.ncbi.nlm.nih.gov/pubmed/36504933 http://dx.doi.org/10.3389/fpubh.2022.1060153 |
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author | Chung, Chee Yap Yang, Jie Yang, Xiaogang He, Jun |
author_facet | Chung, Chee Yap Yang, Jie Yang, Xiaogang He, Jun |
author_sort | Chung, Chee Yap |
collection | PubMed |
description | This review paper covers an overview of air pollution-related disease burden in China and a literature review on the previous studies which have recently adopted a mathematical modeling approach to demonstrate the relative risk (RR) of air pollution-related disease burden. The associations between air pollution and disease burden have been explored in the previous studies. Therefore, it is necessary to quantify the impact of long-term exposure to ambient air pollution by using a suitable mathematical model. The most common way of estimating the health risk attributable to air pollution exposure in a population is by employing a concentration-response function, which is often based on the estimation of a RR model. As most of the regions in China are experiencing rapid urbanization and industrialization, the resulting high ambient air pollution is influencing more residents, which also increases the disease burden in the population. The existing RR models, including the integrated exposure-response (IER) model and the global exposure mortality model (GEMM), are critically reviewed to provide an understanding of the current status of mathematical modeling in the air pollution-related health risk assessment. The performances of different RR models in the mortality estimation of disease are also studied and compared in this paper. Furthermore, the limitations of the existing RR models are pointed out and discussed. Consequently, there is a need to develop a more suitable RR model to accurately estimate the disease burden attributable to air pollution in China, which contributes to one of the key steps in the health risk assessment. By using an updated RR model in the health risk assessment, the estimated mortality risk due to the impacts of environment such as air pollution and seasonal temperature variation could provide a more realistic and reliable information regarding the mortality data of the region, which would help the regional and national policymakers for intensifying their efforts on the improvement of air quality and the management of air pollution-related disease burden. |
format | Online Article Text |
id | pubmed-9727382 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97273822022-12-08 Mathematical modeling in the health risk assessment of air pollution-related disease burden in China: A review Chung, Chee Yap Yang, Jie Yang, Xiaogang He, Jun Front Public Health Public Health This review paper covers an overview of air pollution-related disease burden in China and a literature review on the previous studies which have recently adopted a mathematical modeling approach to demonstrate the relative risk (RR) of air pollution-related disease burden. The associations between air pollution and disease burden have been explored in the previous studies. Therefore, it is necessary to quantify the impact of long-term exposure to ambient air pollution by using a suitable mathematical model. The most common way of estimating the health risk attributable to air pollution exposure in a population is by employing a concentration-response function, which is often based on the estimation of a RR model. As most of the regions in China are experiencing rapid urbanization and industrialization, the resulting high ambient air pollution is influencing more residents, which also increases the disease burden in the population. The existing RR models, including the integrated exposure-response (IER) model and the global exposure mortality model (GEMM), are critically reviewed to provide an understanding of the current status of mathematical modeling in the air pollution-related health risk assessment. The performances of different RR models in the mortality estimation of disease are also studied and compared in this paper. Furthermore, the limitations of the existing RR models are pointed out and discussed. Consequently, there is a need to develop a more suitable RR model to accurately estimate the disease burden attributable to air pollution in China, which contributes to one of the key steps in the health risk assessment. By using an updated RR model in the health risk assessment, the estimated mortality risk due to the impacts of environment such as air pollution and seasonal temperature variation could provide a more realistic and reliable information regarding the mortality data of the region, which would help the regional and national policymakers for intensifying their efforts on the improvement of air quality and the management of air pollution-related disease burden. Frontiers Media S.A. 2022-11-23 /pmc/articles/PMC9727382/ /pubmed/36504933 http://dx.doi.org/10.3389/fpubh.2022.1060153 Text en Copyright © 2022 Chung, Yang, Yang and He. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Public Health Chung, Chee Yap Yang, Jie Yang, Xiaogang He, Jun Mathematical modeling in the health risk assessment of air pollution-related disease burden in China: A review |
title | Mathematical modeling in the health risk assessment of air pollution-related disease burden in China: A review |
title_full | Mathematical modeling in the health risk assessment of air pollution-related disease burden in China: A review |
title_fullStr | Mathematical modeling in the health risk assessment of air pollution-related disease burden in China: A review |
title_full_unstemmed | Mathematical modeling in the health risk assessment of air pollution-related disease burden in China: A review |
title_short | Mathematical modeling in the health risk assessment of air pollution-related disease burden in China: A review |
title_sort | mathematical modeling in the health risk assessment of air pollution-related disease burden in china: a review |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9727382/ https://www.ncbi.nlm.nih.gov/pubmed/36504933 http://dx.doi.org/10.3389/fpubh.2022.1060153 |
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