Yuqin Zhang , Jing Wei , Shirui Chen , Tarik Benmarhnia , Kai Zhang , Xiaowen Wang , Xinlei Deng , Haogao Gu , Ziqiang Lin , Yanji Qu , Jianpeng Xiao , Jie Jiang , Zhicheng Du , Wangjian Zhang , Yuantao Hao
{"title":"Individual and mixed associations between fine particulate matter components and hospital admissions for hypertension: Insights from a large-scale South Chinese cohort study","authors":"Yuqin Zhang , Jing Wei , Shirui Chen , Tarik Benmarhnia , Kai Zhang , Xiaowen Wang , Xinlei Deng , Haogao Gu , Ziqiang Lin , Yanji Qu , Jianpeng Xiao , Jie Jiang , Zhicheng Du , Wangjian Zhang , Yuantao Hao","doi":"10.1016/j.scs.2025.106293","DOIUrl":null,"url":null,"abstract":"<div><div>Fine particulate matter (PM<sub>2.5</sub>) pollution threatens urban sustainability. Few cohort studies have assessed hypertension risks linked to lagged and cumulative exposure to PM<sub>2.5</sub> components. Using data from a cohort study of 36,271 individuals in South China (2015–2020), we examined the individual associations between time-varying PM<sub>2.5</sub> and six components (NO<sub>3</sub><sup>−</sup>, SO<sub>4</sub><sup>2−</sup>, BC, CL<sup>−</sup>, NH<sub>4</sub><sup>+</sup>, and OM) with hypertension hospitalization through Cox proportional hazards regression. Mixed associations of simultaneous exposure to these components were analyzed at lag 0, lag 1, lag 2, lag 0–1, and lag 0–2 years using quantile-based g-computation models. Individual-effect analysis revealed strong associations, with each quantile increase in CL<sup>−</sup>, NH<sub>4</sub><sup>+</sup>, SO<sub>4</sub><sup>2−</sup>, and NO<sub>3</sub><sup>−</sup> linked to 17 %–32 % higher hypertension risks across different time windows. Co-exposure to PM<sub>2.5</sub> components at different lag times increased hospital admissions for overall hypertension, with hazard ratios (95 % confidence intervals) of 1.151 (1.136–1.166), 1.221 (1.205–1.238), 1.257 (1.241–1.273), 1.087 (1.073–1.101), and 1.197 (1.182–1.212). Secondary water-soluble ions (NO<sub>3</sub><sup>−</sup>, SO<sub>4</sub><sup>2−</sup>, NH<sub>4</sub><sup>+</sup>, CL<sup>−</sup>) were major contributors. Increased susceptibility was observed among those under 45, men, individuals with lower education, unhealthy weight, or limited green space exposure. These findings highlight the lagged and cumulative impacts of simultaneous exposure to PM<sub>2.5</sub> component on hypertension.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"124 ","pages":"Article 106293"},"PeriodicalIF":10.5000,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Cities and Society","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2210670725001702","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
Individual and mixed associations between fine particulate matter components and hospital admissions for hypertension: Insights from a large-scale South Chinese cohort study
Fine particulate matter (PM2.5) pollution threatens urban sustainability. Few cohort studies have assessed hypertension risks linked to lagged and cumulative exposure to PM2.5 components. Using data from a cohort study of 36,271 individuals in South China (2015–2020), we examined the individual associations between time-varying PM2.5 and six components (NO3−, SO42−, BC, CL−, NH4+, and OM) with hypertension hospitalization through Cox proportional hazards regression. Mixed associations of simultaneous exposure to these components were analyzed at lag 0, lag 1, lag 2, lag 0–1, and lag 0–2 years using quantile-based g-computation models. Individual-effect analysis revealed strong associations, with each quantile increase in CL−, NH4+, SO42−, and NO3− linked to 17 %–32 % higher hypertension risks across different time windows. Co-exposure to PM2.5 components at different lag times increased hospital admissions for overall hypertension, with hazard ratios (95 % confidence intervals) of 1.151 (1.136–1.166), 1.221 (1.205–1.238), 1.257 (1.241–1.273), 1.087 (1.073–1.101), and 1.197 (1.182–1.212). Secondary water-soluble ions (NO3−, SO42−, NH4+, CL−) were major contributors. Increased susceptibility was observed among those under 45, men, individuals with lower education, unhealthy weight, or limited green space exposure. These findings highlight the lagged and cumulative impacts of simultaneous exposure to PM2.5 component on hypertension.
期刊介绍:
Sustainable Cities and Society (SCS) is an international journal that focuses on fundamental and applied research to promote environmentally sustainable and socially resilient cities. The journal welcomes cross-cutting, multi-disciplinary research in various areas, including:
1. Smart cities and resilient environments;
2. Alternative/clean energy sources, energy distribution, distributed energy generation, and energy demand reduction/management;
3. Monitoring and improving air quality in built environment and cities (e.g., healthy built environment and air quality management);
4. Energy efficient, low/zero carbon, and green buildings/communities;
5. Climate change mitigation and adaptation in urban environments;
6. Green infrastructure and BMPs;
7. Environmental Footprint accounting and management;
8. Urban agriculture and forestry;
9. ICT, smart grid and intelligent infrastructure;
10. Urban design/planning, regulations, legislation, certification, economics, and policy;
11. Social aspects, impacts and resiliency of cities;
12. Behavior monitoring, analysis and change within urban communities;
13. Health monitoring and improvement;
14. Nexus issues related to sustainable cities and societies;
15. Smart city governance;
16. Decision Support Systems for trade-off and uncertainty analysis for improved management of cities and society;
17. Big data, machine learning, and artificial intelligence applications and case studies;
18. Critical infrastructure protection, including security, privacy, forensics, and reliability issues of cyber-physical systems.
19. Water footprint reduction and urban water distribution, harvesting, treatment, reuse and management;
20. Waste reduction and recycling;
21. Wastewater collection, treatment and recycling;
22. Smart, clean and healthy transportation systems and infrastructure;