Department of Chemical and Environmental Engineering, University of Nottingham Ningbo China, Ningbo, Zhejiang Province, China.
Department of Mathematics, University of Hull, Hull, United Kingdom.
Front Public Health. 2022 Nov 23;10:1060153. doi: 10.3389/fpubh.2022.1060153. eCollection 2022.
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.
这篇综述文章概述了中国与空气污染相关的疾病负担,并对之前采用数学建模方法来展示与空气污染相关的疾病负担的相对风险 (RR) 的研究进行了文献回顾。之前的研究已经探讨了空气污染与疾病负担之间的关系。因此,有必要使用合适的数学模型来量化长期暴露于环境空气污染的影响。估计人群中因空气污染暴露而导致的健康风险最常见的方法是采用浓度-反应函数,该函数通常基于 RR 模型的估计。由于中国大多数地区正在经历快速的城市化和工业化,由此导致的高环境空气污染正在影响更多的居民,这也增加了人群中的疾病负担。对现有的 RR 模型,包括综合暴露-反应 (IER) 模型和全球暴露死亡率模型 (GEMM),进行了批判性审查,以了解当前数学建模在空气污染相关健康风险评估中的现状。本文还研究并比较了不同 RR 模型在疾病死亡率估计中的性能。此外,还指出并讨论了现有 RR 模型的局限性。因此,需要开发更合适的 RR 模型来准确估计中国因空气污染导致的疾病负担,这是健康风险评估的关键步骤之一。通过在健康风险评估中使用更新的 RR 模型,可以更准确地估计环境(如空气污染和季节性温度变化)对死亡率的影响,为该地区的死亡率数据提供更现实和可靠的信息,这将有助于地区和国家决策者加强改善空气质量和管理与空气污染相关的疾病负担的力度。