Empirical dynamic modeling of the association between ambient PM2.5 and under-five mortality across 2851 counties in Mainland China, 1999–2012

Alnwisi, Sameh M M; Chai, Chengwei; Acharya, Bipin Kumar; Qian, Aaron; Zhang, Shiyu; Zhang, Zilong; Vaughn, Michael G.; Xian, Hong; Wang, Qinzhou; Lin, Hualiang

doi:10.1016/j.ecoenv.2022.113513

Cited by 3 publications

(2 citation statements)

References 67 publications

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“…Census-based data at various spatial levels is popularly used in pollution-related epidemiology or ecological studies (1,11). It can represent the health status at the population level.…”

Section: Mortality Datamentioning

confidence: 99%

“…This study illustrated that climate sustainability, at certain level, could mitigate the adverse health influence of air pollution, and provided a new perspective on health risk mitigation from pollution reduction and climate adaptation. disease, lung cancer, chronic obstructive pulmonary disease (COPD), lower-respiratory infections (e.g., pneumonia), stroke, type 2 diabetes, and, more recently, adverse birth outcomes (1)(2)(3)(4)(5)(6)(7). PM 2.5 , carrying harmful chemicals, can penetrate deeply into the human lung system and blood circulation to cause cardiovascular and respiratory diseases, resulting in an estimated 42 million deaths (∼7.6% of the total mortality) and 1031 million disability-adjusted life-years lost (8).…”

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confidence: 99%

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County level study of the interaction effect of PM2.5 and climate sustainability on mortality in China

Guo

Yang²,

Li³

et al. 2023

Front. Public Health

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IntroductionPM2.5 and climate change are two major public health concerns, with majority of the research on their interaction focused on the synergistic effect, particularly for extreme events such as hot or cold temperatures. The climate sustainability index (CLS) was introduced to comprehensively explore the impact of climate change and the interactive effect on human health with air pollution.MethodsIn this study, a county-level panel data in China was collected and used. The generalized additive model (GAM) and geographically and temporally weighted regression (GTWR) was used to explore the interactive and spatial effect on mortality between CLS and PM2.5.Results and discussionsIndividually, when CLS is higher than 150 or lower than 50, the mortality is higher. Moreover, when PM2.5 is more than 35 μg/m3, the influence on mortality is significantly increased as PM2.5 concentration rises; when PM2.5 is above 70 μg/m3, the trend is sharp. A nonlinear antagonistic effect between CLS and PM2.5 was found in this study, proving that the combined adverse health effects of climate change and air pollution, especially when CLS was lower (below 100) and PM2.5 was higher (above 35 μg/m3), the antagonistic effect was much stronger. From a spatial perspective, the impact of CLS and PM2.5 on mortality varies in different geographical regions. A negative and positive influence of CLS and PM2.5 was found in east China, especially in the northeastern and northern regions, -which were heavily polluted. This study illustrated that climate sustainability, at certain level, could mitigate the adverse health influence of air pollution, and provided a new perspective on health risk mitigation from pollution reduction and climate adaptation.

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“…Census-based data at various spatial levels is popularly used in pollution-related epidemiology or ecological studies (1,11). It can represent the health status at the population level.…”

Section: Mortality Datamentioning

confidence: 99%