دورية أكاديمية
أعرض في EDS

Mathematical modeling in the health risk assessment of air pollution-related disease burden in China: A review.

التفاصيل البيبلوغرافية
العنوان: Mathematical modeling in the health risk assessment of air pollution-related disease burden in China: A review.
المؤلفون: Chung CY; Department of Chemical and Environmental Engineering, University of Nottingham Ningbo China, Ningbo, Zhejiang Province, China., Yang J; Department of Mathematics, University of Hull, Hull, United Kingdom., Yang X; Department of Mechanical, Materials and Manufacturing Engineering, University of Nottingham Ningbo China, Ningbo, Zhejiang Province, China., He J; Department of Chemical and Environmental Engineering, University of Nottingham Ningbo China, Ningbo, Zhejiang Province, China.
المصدر: Frontiers in public health [Front Public Health] 2022 Nov 23; Vol. 10, pp. 1060153. Date of Electronic Publication: 2022 Nov 23 (Print Publication: 2022).
نوع المنشور: Journal Article; Review; Research Support, Non-U.S. Gov't
اللغة: English
بيانات الدورية: Publisher: Frontiers Editorial Office Country of Publication: Switzerland NLM ID: 101616579 Publication Model: eCollection Cited Medium: Internet ISSN: 2296-2565 (Electronic) Linking ISSN: 22962565 NLM ISO Abbreviation: Front Public Health Subsets: MEDLINE
أسماء مطبوعة: Original Publication: Lausanne : Frontiers Editorial Office
مواضيع طبية MeSH: Air Pollution*/adverse effects, Risk Assessment ; Cost of Illness ; Climate ; Models, Theoretical
مستخلص: 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.
Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
(Copyright © 2022 Chung, Yang, Yang and He.)
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فهرسة مساهمة: Keywords: COPD; air pollution; health risk assessment; lung cancer; mathematical model; relative risk; temperature
تواريخ الأحداث: Date Created: 20221212 Date Completed: 20221216 Latest Revision: 20230130
رمز التحديث: 20231215
مُعرف محوري في PubMed: PMC9727382
DOI: 10.3389/fpubh.2022.1060153
PMID: 36504933
قاعدة البيانات: MEDLINE
الوصف
تدمد:2296-2565
DOI:10.3389/fpubh.2022.1060153