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Pan Q, Zha S, Li J, Guan H, Xia J, Yu J, Cui C, Liu Y, Xu J, Liu J, Chen G, Jiang M, Zhang J, Ding X, Zhao X. Identification of the susceptible subpopulations for wide pulse pressure under long-term exposure to ambient particulate matters. Sci Total Environ 2022; 834:155311. [PMID: 35439510 DOI: 10.1016/j.scitotenv.2022.155311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Revised: 04/11/2022] [Accepted: 04/12/2022] [Indexed: 06/14/2023]
Abstract
Wide pulse pressure (WPP) is a preclinical indicator for arterial stiffness and cardiovascular diseases. Long-term exposure to ambient particulate matters (PMs) would increase the risk of WPP. Although reducing pollutants emissions and avoiding outdoor activity during a polluted period are effective ways to blunt the adverse effects. Identifying and protecting the susceptible subpopulation is another crucial way to reduce the disease burdens. Therefore, we aimed to identify the susceptible subpopulations of WPP under long-term exposure to PMs. The WPP was defined as pulse pressure over 60 mmHg. Three-year averages of PMs were estimated using random forest approaches. Associations between WPP and PMs exposure were estimated using generalized propensity score weighted logistic regressions. Demographic, socioeconomic characteristics, health-related behaviors, and hematological biomarkers were collected to detect the modification effects on the WPP-PMs associations. Susceptible subpopulations were defined as those with significantly higher risks of WPP under PMs exposures. The PMs-WPP associations were significant with ORs (95%CI) of 1.126 (1.094, 1.159) for PM1, 1.174 (1.140, 1.210) for PM2.5, and 1.111 (1.088, 1.135) for PM10. There were 17 subpopulations more sensitive to WPP under long-term exposure to PMs. The susceptibility was higher in subpopulations with high BMI (Q3-Q4 quartiles), high-intensive physical activity (Q3 or Q4 quartile), insufficient or excessive fruit intake (Q1 or Q5 quartile), insufficient or too long sleep length (<7 or >8 h). Subpopulations with elevated inflammation markers (WBC, LYM, BAS, EOS: Q3-Q4 quartiles) and glucose metabolism indicators (HbA1c, GLU: Q3-Q4 quartiles) were more susceptible. Besides, elder, urban living, low socioeconomic level, and excessive red meat and sodium salt intake were also related to higher susceptibility. Our findings on the susceptibility characteristics would help to develop more targeted disease prevention and therapy strategies. Health resources can be allocated more effectively by putting more consideration to subpopulations with higher susceptibility.
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Affiliation(s)
- Qing Pan
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Shun Zha
- Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Jingzhong Li
- Tibet Center for Disease Control and Prevention, Tibet, China
| | - Han Guan
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China
| | - Jingjie Xia
- Chengdu Center for Disease Control and Prevention, Chengdu, China
| | - Jianhong Yu
- Pidu District Center for Disease Control and Prevention, Chengdu, China
| | | | - Yuanyuan Liu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jiayue Xu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jin Liu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Gongbo Chen
- Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangdong, China
| | - Min Jiang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Juying Zhang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
| | - Xianbin Ding
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China
| | - Xing Zhao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
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