Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Socioeconomic disparity in the association between long-term exposure to PM2.5 and mortality in 2640 Chinese counties
Background: Although the association between long-term exposure to PM2.5 and mortality has been evaluated intensively, little is known about the socioeconomic disparity in the association. Methods: We collected data on annual all-cause mortality, PM2.5 concentration, socioeconomic and demographic characteristics of 2640 counties from the two most recent Chinese censuses in 2000 and 2010. We applied the difference-in-differences (DID) method to estimate PM2.5-mortality association for counties at different quartiles of literacy rate, college rate, urbanization rate and GDP per capita, respectively. Results: Overall, every 10 µg/m3 increase in annual average PM2.5 was associated with 3.8% (95% confidence interval [CI]: 3.0–5.0) increase of all-cause mortality. The stratified analysis suggested higher health impact of exposure in counties with lower socioeconomic status. For counties of the lowest quartile (Q1) of literacy rate, college rate, urbanization rate and GDP per capita, the effect estimates were 6.0% (95% CI: 4.2–7.7), 4.4% (95% CI: 2.8–6.0), 3.5% (95% CI: 2.0–5.1) and 4.9% (95% CI: 2.7–7.1), respectively. There was strong evidence for elevated risk in mortality associated with PM2.5 of all socioeconomic factors in the lowest quartile (Q1) compared with the highest quartile counties (Q4) (p-value for difference < 0.05). Conclusions: There was socioeconomic disparity in the PM2.5-mortality association in China. Dwellers living in less developed counties are more vulnerable to long-term exposure to ambient PM2.5 than those living in developed counties.
Socioeconomic disparity in the association between long-term exposure to PM2.5 and mortality in 2640 Chinese counties
Background: Although the association between long-term exposure to PM2.5 and mortality has been evaluated intensively, little is known about the socioeconomic disparity in the association. Methods: We collected data on annual all-cause mortality, PM2.5 concentration, socioeconomic and demographic characteristics of 2640 counties from the two most recent Chinese censuses in 2000 and 2010. We applied the difference-in-differences (DID) method to estimate PM2.5-mortality association for counties at different quartiles of literacy rate, college rate, urbanization rate and GDP per capita, respectively. Results: Overall, every 10 µg/m3 increase in annual average PM2.5 was associated with 3.8% (95% confidence interval [CI]: 3.0–5.0) increase of all-cause mortality. The stratified analysis suggested higher health impact of exposure in counties with lower socioeconomic status. For counties of the lowest quartile (Q1) of literacy rate, college rate, urbanization rate and GDP per capita, the effect estimates were 6.0% (95% CI: 4.2–7.7), 4.4% (95% CI: 2.8–6.0), 3.5% (95% CI: 2.0–5.1) and 4.9% (95% CI: 2.7–7.1), respectively. There was strong evidence for elevated risk in mortality associated with PM2.5 of all socioeconomic factors in the lowest quartile (Q1) compared with the highest quartile counties (Q4) (p-value for difference < 0.05). Conclusions: There was socioeconomic disparity in the PM2.5-mortality association in China. Dwellers living in less developed counties are more vulnerable to long-term exposure to ambient PM2.5 than those living in developed counties.
Socioeconomic disparity in the association between long-term exposure to PM2.5 and mortality in 2640 Chinese counties
Chunlei Han (Autor:in) / Rongbin Xu (Autor:in) / Caroline X. Gao (Autor:in) / Wenhua Yu (Autor:in) / Yajuan Zhang (Autor:in) / Kun Han (Autor:in) / Pei Yu (Autor:in) / Yuming Guo (Autor:in) / Shanshan Li (Autor:in)
2021
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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