Geographical Variation of COPD Mortality and Related Risk Factors in Jiading District, Shanghai
Background: Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in China. Although numerous studies have been conducted to determine the risk factors for COPD mortality such as ambient air pollution, the results are not fully consistent.Methods: This study included mort...
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| Format: | Article |
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Frontiers Media S.A.
2021-02-01
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| Series: | Frontiers in Public Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2021.627312/full |
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| author | Qian Peng Na Zhang Na Zhang Na Zhang Hongjie Yu Yueqin Shao Ying Ji Yaqing Jin Peisong Zhong Yiying Zhang Honglin Jiang Honglin Jiang Honglin Jiang Chunlin Li Chunlin Li Chunlin Li Ying Shi Ying Shi Ying Shi Yingyan Zheng Yingyan Zheng Yingyan Zheng Ying Xiong Ying Xiong Ying Xiong Zhengzhong Wang Zhengzhong Wang Zhengzhong Wang Feng Jiang Feng Jiang Feng Jiang Yue Chen Qingwu Jiang Qingwu Jiang Qingwu Jiang Yibiao Zhou Yibiao Zhou Yibiao Zhou |
| author_facet | Qian Peng Na Zhang Na Zhang Na Zhang Hongjie Yu Yueqin Shao Ying Ji Yaqing Jin Peisong Zhong Yiying Zhang Honglin Jiang Honglin Jiang Honglin Jiang Chunlin Li Chunlin Li Chunlin Li Ying Shi Ying Shi Ying Shi Yingyan Zheng Yingyan Zheng Yingyan Zheng Ying Xiong Ying Xiong Ying Xiong Zhengzhong Wang Zhengzhong Wang Zhengzhong Wang Feng Jiang Feng Jiang Feng Jiang Yue Chen Qingwu Jiang Qingwu Jiang Qingwu Jiang Yibiao Zhou Yibiao Zhou Yibiao Zhou |
| author_sort | Qian Peng |
| collection | DOAJ |
| description | Background: Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in China. Although numerous studies have been conducted to determine the risk factors for COPD mortality such as ambient air pollution, the results are not fully consistent.Methods: This study included mortality analysis and a case-control design by using the data extracted from the Mortality Registration System in Jiading District, Shanghai. Traditional logistic regression, geographically weighted logistic regression (GWLR), and spatial scan statistical analysis were performed to explore the geographic variation of COPD mortality and the possible influencing factors.Results: Traditional logistic regression showed that extreme lower temperature in the month prior to death, shorter distance to highway, lower GDP level were associated with increased COPD mortality. GWRL model further demonstrated obvious geographical discrepancies for the above associations. We additionally identified a significant cluster of low COPD mortality (OR = 0.36, P = 0.002) in the southwest region of Jiading District with a radius of 3.55 km by using the Bernoulli model. The geographical variation in age-standardized mortality rate for COPD in Jiading District was explained to a certain degree by these factors.Conclusion: The risk of COPD mortality in Jiading District showed obvious geographical variation, which were partially explained by the geographical variations in effects of the extreme low temperature in the month prior to death, residential proximity to highway, and GDP level. |
| first_indexed | 2024-12-16T09:59:37Z |
| format | Article |
| id | doaj.art-e5192b9f5f9d4078b6a28634b59b34c4 |
| institution | Directory Open Access Journal |
| issn | 2296-2565 |
| language | English |
| last_indexed | 2024-12-16T09:59:37Z |
| publishDate | 2021-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Public Health |
| spelling | doaj.art-e5192b9f5f9d4078b6a28634b59b34c42022-12-21T22:35:49ZengFrontiers Media S.A.Frontiers in Public Health2296-25652021-02-01910.3389/fpubh.2021.627312627312Geographical Variation of COPD Mortality and Related Risk Factors in Jiading District, ShanghaiQian Peng0Na Zhang1Na Zhang2Na Zhang3Hongjie Yu4Yueqin Shao5Ying Ji6Yaqing Jin7Peisong Zhong8Yiying Zhang9Honglin Jiang10Honglin Jiang11Honglin Jiang12Chunlin Li13Chunlin Li14Chunlin Li15Ying Shi16Ying Shi17Ying Shi18Yingyan Zheng19Yingyan Zheng20Yingyan Zheng21Ying Xiong22Ying Xiong23Ying Xiong24Zhengzhong Wang25Zhengzhong Wang26Zhengzhong Wang27Feng Jiang28Feng Jiang29Feng Jiang30Yue Chen31Qingwu Jiang32Qingwu Jiang33Qingwu Jiang34Yibiao Zhou35Yibiao Zhou36Yibiao Zhou37Jiading District Center for Disease Control and Prevention, Shanghai, ChinaFudan University School of Public Health, Shanghai, ChinaKey Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, ChinaFudan University Center for Tropical Disease Research, Shanghai, ChinaJiading District Center for Disease Control and Prevention, Shanghai, ChinaJiading District Center for Disease Control and Prevention, Shanghai, ChinaJiading District Center for Disease Control and Prevention, Shanghai, ChinaJiading District Center for Disease Control and Prevention, Shanghai, ChinaJiading District Center for Disease Control and Prevention, Shanghai, ChinaJiading District Center for Disease Control and Prevention, Shanghai, ChinaFudan University School of Public Health, Shanghai, ChinaKey Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, ChinaFudan University Center for Tropical Disease Research, Shanghai, ChinaFudan University School of Public Health, Shanghai, ChinaKey Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, ChinaFudan University Center for Tropical Disease Research, Shanghai, ChinaFudan University School of Public Health, Shanghai, ChinaKey Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, ChinaFudan University Center for Tropical Disease Research, Shanghai, ChinaFudan University School of Public Health, Shanghai, ChinaKey Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, ChinaFudan University Center for Tropical Disease Research, Shanghai, ChinaFudan University School of Public Health, Shanghai, ChinaKey Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, ChinaFudan University Center for Tropical Disease Research, Shanghai, ChinaFudan University School of Public Health, Shanghai, ChinaKey Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, ChinaFudan University Center for Tropical Disease Research, Shanghai, ChinaFudan University School of Public Health, Shanghai, ChinaKey Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, ChinaFudan University Center for Tropical Disease Research, Shanghai, ChinaFaculty of Medicine, School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, CanadaFudan University School of Public Health, Shanghai, ChinaKey Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, ChinaFudan University Center for Tropical Disease Research, Shanghai, ChinaFudan University School of Public Health, Shanghai, ChinaKey Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, ChinaFudan University Center for Tropical Disease Research, Shanghai, ChinaBackground: Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in China. Although numerous studies have been conducted to determine the risk factors for COPD mortality such as ambient air pollution, the results are not fully consistent.Methods: This study included mortality analysis and a case-control design by using the data extracted from the Mortality Registration System in Jiading District, Shanghai. Traditional logistic regression, geographically weighted logistic regression (GWLR), and spatial scan statistical analysis were performed to explore the geographic variation of COPD mortality and the possible influencing factors.Results: Traditional logistic regression showed that extreme lower temperature in the month prior to death, shorter distance to highway, lower GDP level were associated with increased COPD mortality. GWRL model further demonstrated obvious geographical discrepancies for the above associations. We additionally identified a significant cluster of low COPD mortality (OR = 0.36, P = 0.002) in the southwest region of Jiading District with a radius of 3.55 km by using the Bernoulli model. The geographical variation in age-standardized mortality rate for COPD in Jiading District was explained to a certain degree by these factors.Conclusion: The risk of COPD mortality in Jiading District showed obvious geographical variation, which were partially explained by the geographical variations in effects of the extreme low temperature in the month prior to death, residential proximity to highway, and GDP level.https://www.frontiersin.org/articles/10.3389/fpubh.2021.627312/fullCOPDtraffic-related pollutanttemperatureGWLRmortality |
| spellingShingle | Qian Peng Na Zhang Na Zhang Na Zhang Hongjie Yu Yueqin Shao Ying Ji Yaqing Jin Peisong Zhong Yiying Zhang Honglin Jiang Honglin Jiang Honglin Jiang Chunlin Li Chunlin Li Chunlin Li Ying Shi Ying Shi Ying Shi Yingyan Zheng Yingyan Zheng Yingyan Zheng Ying Xiong Ying Xiong Ying Xiong Zhengzhong Wang Zhengzhong Wang Zhengzhong Wang Feng Jiang Feng Jiang Feng Jiang Yue Chen Qingwu Jiang Qingwu Jiang Qingwu Jiang Yibiao Zhou Yibiao Zhou Yibiao Zhou Geographical Variation of COPD Mortality and Related Risk Factors in Jiading District, Shanghai Frontiers in Public Health COPD traffic-related pollutant temperature GWLR mortality |
| title | Geographical Variation of COPD Mortality and Related Risk Factors in Jiading District, Shanghai |
| title_full | Geographical Variation of COPD Mortality and Related Risk Factors in Jiading District, Shanghai |
| title_fullStr | Geographical Variation of COPD Mortality and Related Risk Factors in Jiading District, Shanghai |
| title_full_unstemmed | Geographical Variation of COPD Mortality and Related Risk Factors in Jiading District, Shanghai |
| title_short | Geographical Variation of COPD Mortality and Related Risk Factors in Jiading District, Shanghai |
| title_sort | geographical variation of copd mortality and related risk factors in jiading district shanghai |
| topic | COPD traffic-related pollutant temperature GWLR mortality |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2021.627312/full |
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