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 ch...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2021-01-01
|
| Series: | Environment International |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0160412020321966 |
| _version_ | 1818601556322287616 |
|---|---|
| author | Chunlei Han Rongbin Xu Caroline X. Gao Wenhua Yu Yajuan Zhang Kun Han Pei Yu Yuming Guo Shanshan Li |
| author_facet | Chunlei Han Rongbin Xu Caroline X. Gao Wenhua Yu Yajuan Zhang Kun Han Pei Yu Yuming Guo Shanshan Li |
| author_sort | Chunlei Han |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-16T12:53:16Z |
| format | Article |
| id | doaj.art-13149289ebfb4a658665612432b9e844 |
| institution | Directory Open Access Journal |
| issn | 0160-4120 |
| language | English |
| last_indexed | 2024-12-16T12:53:16Z |
| publishDate | 2021-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Environment International |
| spelling | doaj.art-13149289ebfb4a658665612432b9e8442022-12-21T22:31:05ZengElsevierEnvironment International0160-41202021-01-01146106241Socioeconomic disparity in the association between long-term exposure to PM2.5 and mortality in 2640 Chinese countiesChunlei Han0Rongbin Xu1Caroline X. Gao2Wenhua Yu3Yajuan Zhang4Kun Han5Pei Yu6Yuming Guo7Shanshan Li8School of Public Health and Management, Binzhou Medical University, Yantai, Shandong, China; Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, AustraliaDepartment of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, AustraliaDepartment of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia; Centre for Youth Mental Health (Orygen), University of Melbourne, Melbourne, AustraliaDepartment of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, AustraliaSchool of Public Health and Management, Ningxia Medical University, Yinchuan, Ningxia Hui Autonomous Region, ChinaSchool of Economy, Shandong University, Jinan, Shandong, ChinaDepartment of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, AustraliaSchool of Public Health and Management, Binzhou Medical University, Yantai, Shandong, China; Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia; Corresponding authors.Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia; Corresponding authors.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.http://www.sciencedirect.com/science/article/pii/S0160412020321966PM2.5-mortality associationSocioeconomic statusDifference-in-differences |
| spellingShingle | Chunlei Han Rongbin Xu Caroline X. Gao Wenhua Yu Yajuan Zhang Kun Han Pei Yu Yuming Guo Shanshan Li Socioeconomic disparity in the association between long-term exposure to PM2.5 and mortality in 2640 Chinese counties Environment International PM2.5-mortality association Socioeconomic status Difference-in-differences |
| title | Socioeconomic disparity in the association between long-term exposure to PM2.5 and mortality in 2640 Chinese counties |
| title_full | Socioeconomic disparity in the association between long-term exposure to PM2.5 and mortality in 2640 Chinese counties |
| title_fullStr | Socioeconomic disparity in the association between long-term exposure to PM2.5 and mortality in 2640 Chinese counties |
| title_full_unstemmed | Socioeconomic disparity in the association between long-term exposure to PM2.5 and mortality in 2640 Chinese counties |
| title_short | Socioeconomic disparity in the association between long-term exposure to PM2.5 and mortality in 2640 Chinese counties |
| title_sort | socioeconomic disparity in the association between long term exposure to pm2 5 and mortality in 2640 chinese counties |
| topic | PM2.5-mortality association Socioeconomic status Difference-in-differences |
| url | http://www.sciencedirect.com/science/article/pii/S0160412020321966 |
| work_keys_str_mv | AT chunleihan socioeconomicdisparityintheassociationbetweenlongtermexposuretopm25andmortalityin2640chinesecounties AT rongbinxu socioeconomicdisparityintheassociationbetweenlongtermexposuretopm25andmortalityin2640chinesecounties AT carolinexgao socioeconomicdisparityintheassociationbetweenlongtermexposuretopm25andmortalityin2640chinesecounties AT wenhuayu socioeconomicdisparityintheassociationbetweenlongtermexposuretopm25andmortalityin2640chinesecounties AT yajuanzhang socioeconomicdisparityintheassociationbetweenlongtermexposuretopm25andmortalityin2640chinesecounties AT kunhan socioeconomicdisparityintheassociationbetweenlongtermexposuretopm25andmortalityin2640chinesecounties AT peiyu socioeconomicdisparityintheassociationbetweenlongtermexposuretopm25andmortalityin2640chinesecounties AT yumingguo socioeconomicdisparityintheassociationbetweenlongtermexposuretopm25andmortalityin2640chinesecounties AT shanshanli socioeconomicdisparityintheassociationbetweenlongtermexposuretopm25andmortalityin2640chinesecounties |