Estimating causal links of long-term exposure to particulate matters with all-cause mortality in South China
Background: The association between long-term particulate matter (PM) exposure and all-cause mortality has been well-documented. However, evidence is still limited from high-exposed cohorts, especially for PM1 which is smaller while more toxic than other commonly investigated particles. We aimed to...
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| Format: | Article |
| Language: | English |
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Elsevier
2023-01-01
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| Series: | Environment International |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0160412022006535 |
| _version_ | 1828059331364388864 |
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| author | Ying Wang Jing Wei Yuqin Zhang Tong Guo Shirui Chen Wenjing Wu Shimin Chen Ziqiang Li Yanji Qu Jianpeng Xiao Xinlei Deng Yu Liu Zhicheng Du Wangjian Zhang Yuantao Hao |
| author_facet | Ying Wang Jing Wei Yuqin Zhang Tong Guo Shirui Chen Wenjing Wu Shimin Chen Ziqiang Li Yanji Qu Jianpeng Xiao Xinlei Deng Yu Liu Zhicheng Du Wangjian Zhang Yuantao Hao |
| author_sort | Ying Wang |
| collection | DOAJ |
| description | Background: The association between long-term particulate matter (PM) exposure and all-cause mortality has been well-documented. However, evidence is still limited from high-exposed cohorts, especially for PM1 which is smaller while more toxic than other commonly investigated particles. We aimed to examine the potential casual links of long-term PMs exposure with all-cause mortality in high-exposed areas. Methods: A total of 580,757 participants in southern China were enrolled during 2009–2015 and followed up to 2020. The annual average concentration of PM1, PM2.5, and PM10 at 1 km2 spatial resolution was assessed for each residential address through validated spatiotemporal models. We used marginal structural Cox models to estimate the PM-mortality associations which were further stratified by sociodemographic, lifestyle factors and general exposure levels. Results: 37,578 deaths were totally identified during averagely 8.0 years of follow-up. Increased exposure to all 3 PM size fractions were significantly associated with increased risk of all-cause mortality, with hazard ratios (HRs) of 1.042 (95 % confidence interval (CI): 1.037–1.046), 1.031 (95 % CI: 1.028–1.033), and 1.029 (95 % CI: 1.027–1.031) per 1 μg/m3 increase in PM1, PM2.5, and PM10 concentrations, respectively. We observed greater effect estimates among the elderly (age ≥ 65 years), unmarried participants, and those with low education attainment. Additionally, the effect of PM1, PM2.5, and PM10 tend to be higher in the low-exposure group than in the general population. Conclusions: We provided comprehensive evidence for the potential causal links between long-term PM exposure and all-cause mortality, and suggested stronger links for PM1 compared to large particles and among certain vulnerable subgroups. |
| first_indexed | 2024-04-10T21:41:18Z |
| format | Article |
| id | doaj.art-52c77e65fb2a4b78b1365d4995ab8aab |
| institution | Directory Open Access Journal |
| issn | 0160-4120 |
| language | English |
| last_indexed | 2024-04-10T21:41:18Z |
| publishDate | 2023-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Environment International |
| spelling | doaj.art-52c77e65fb2a4b78b1365d4995ab8aab2023-01-19T04:16:29ZengElsevierEnvironment International0160-41202023-01-01171107726Estimating causal links of long-term exposure to particulate matters with all-cause mortality in South ChinaYing Wang0Jing Wei1Yuqin Zhang2Tong Guo3Shirui Chen4Wenjing Wu5Shimin Chen6Ziqiang Li7Yanji Qu8Jianpeng Xiao9Xinlei Deng10Yu Liu11Zhicheng Du12Wangjian Zhang13Yuantao Hao14Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, ChinaDepartment of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, USADepartment of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, ChinaDepartment of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, ChinaDepartment of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, ChinaDepartment of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, ChinaDepartment of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, ChinaDepartment of Preventive Medicine, School of Basic Medicine and Public Health, Jinan University, Guangzhou, ChinaGuangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangzhou, ChinaGuangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, ChinaEpidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USADepartment of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, ChinaDepartment of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China; Corresponding authors.Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China; Corresponding authors.Peking University Center for Public Health and Epidemic Preparedness & Response, Peking, Beijing, China; Corresponding authors.Background: The association between long-term particulate matter (PM) exposure and all-cause mortality has been well-documented. However, evidence is still limited from high-exposed cohorts, especially for PM1 which is smaller while more toxic than other commonly investigated particles. We aimed to examine the potential casual links of long-term PMs exposure with all-cause mortality in high-exposed areas. Methods: A total of 580,757 participants in southern China were enrolled during 2009–2015 and followed up to 2020. The annual average concentration of PM1, PM2.5, and PM10 at 1 km2 spatial resolution was assessed for each residential address through validated spatiotemporal models. We used marginal structural Cox models to estimate the PM-mortality associations which were further stratified by sociodemographic, lifestyle factors and general exposure levels. Results: 37,578 deaths were totally identified during averagely 8.0 years of follow-up. Increased exposure to all 3 PM size fractions were significantly associated with increased risk of all-cause mortality, with hazard ratios (HRs) of 1.042 (95 % confidence interval (CI): 1.037–1.046), 1.031 (95 % CI: 1.028–1.033), and 1.029 (95 % CI: 1.027–1.031) per 1 μg/m3 increase in PM1, PM2.5, and PM10 concentrations, respectively. We observed greater effect estimates among the elderly (age ≥ 65 years), unmarried participants, and those with low education attainment. Additionally, the effect of PM1, PM2.5, and PM10 tend to be higher in the low-exposure group than in the general population. Conclusions: We provided comprehensive evidence for the potential causal links between long-term PM exposure and all-cause mortality, and suggested stronger links for PM1 compared to large particles and among certain vulnerable subgroups.http://www.sciencedirect.com/science/article/pii/S0160412022006535Particulate matterAll-cause mortalityLong-term effectCausal inference model |
| spellingShingle | Ying Wang Jing Wei Yuqin Zhang Tong Guo Shirui Chen Wenjing Wu Shimin Chen Ziqiang Li Yanji Qu Jianpeng Xiao Xinlei Deng Yu Liu Zhicheng Du Wangjian Zhang Yuantao Hao Estimating causal links of long-term exposure to particulate matters with all-cause mortality in South China Environment International Particulate matter All-cause mortality Long-term effect Causal inference model |
| title | Estimating causal links of long-term exposure to particulate matters with all-cause mortality in South China |
| title_full | Estimating causal links of long-term exposure to particulate matters with all-cause mortality in South China |
| title_fullStr | Estimating causal links of long-term exposure to particulate matters with all-cause mortality in South China |
| title_full_unstemmed | Estimating causal links of long-term exposure to particulate matters with all-cause mortality in South China |
| title_short | Estimating causal links of long-term exposure to particulate matters with all-cause mortality in South China |
| title_sort | estimating causal links of long term exposure to particulate matters with all cause mortality in south china |
| topic | Particulate matter All-cause mortality Long-term effect Causal inference model |
| url | http://www.sciencedirect.com/science/article/pii/S0160412022006535 |
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