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Zhang W, Kong M, Jiang Y, Gan Q, Wei J, Zhang Q, Wang J, Shen J, Wu S. Ambient air pollutants exposure during gestation and incidence risk of hypertensive disorders of pregnancy or preeclampsia in China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 359:124722. [PMID: 39147229 DOI: 10.1016/j.envpol.2024.124722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Revised: 06/27/2024] [Accepted: 08/11/2024] [Indexed: 08/17/2024]
Abstract
The relationships between the exposure to ambient air pollutants during gestation and the incidence of hypertensive disorders in pregnancy (HDPs) or preeclampsia are contradictory. This prospective cohort study enrolled the participants between January 2020 and December 2021 from the Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology. The exposure to ambient air pollutants and daily temperatures were obtained from the ChinaHighAirPollutants dataset and the Big Earth Data Platform for Three Poles, respectively. Logistic regression models were used as single- and two-pollutant models. Restricted cubic splines were applied to each ambient air pollutant exposure to further evaluate the exposure-response relationships. Quantile G-computation approaches were employed to evaluate the cumulative impact of mixed ambient air pollutants on the incidence risk HDPs and preeclampsia. Among 19,325 participants (median age: 30.2 years), 1669 (8.64%) were diagnosed with HDPs and 180 (0.94%) with preeclampsia. While mostly null risk estimates were observed, exposure to PM1, PM2.5, PM10, and NO2 correlated with a decreased incidence risk for HDPs and preeclampsia during most gestational periods. Additionally, our multi-pollutant model presented that an increase by one quartile in the cumulative effect of ambient air pollutants was associated with a significantly decreased incidence risk for HDPs in the trimester before gestation and in the third trimester during gestation, as well as for preeclampsia in the third trimester during gestation. These findings warrant further investigation into the mechanisms underlying these associations.
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Affiliation(s)
- Wenkai Zhang
- Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Minghao Kong
- Tongji University School of Medicine, Shanghai, China
| | - Yuan Jiang
- Tongji University School of Medicine, Shanghai, China
| | - Quan Gan
- Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, USA
| | - Qing Zhang
- Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiayi Wang
- School of Atmospheric Sciences, Nanjing University, Nanjing, China
| | - Jun Shen
- Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Shijie Wu
- Tongji University School of Medicine, Shanghai, China.
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Chen S, Liu D, Huang L, Guo C, Gao X, Xu Z, Yang Z, Chen Y, Li M, Yang J. Global associations between long-term exposure to PM 2.5 constituents and health: A systematic review and meta-analysis of cohort studies. JOURNAL OF HAZARDOUS MATERIALS 2024; 474:134715. [PMID: 38838524 DOI: 10.1016/j.jhazmat.2024.134715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 05/10/2024] [Accepted: 05/22/2024] [Indexed: 06/07/2024]
Abstract
Existing studies on the most impactful component remain controversial, hindering the optimization of future air quality standards that concerns particle composition. We aimed to summarize the health risk associated with PM2.5 components and identify those components with the greatest health risk. We performed a meta-analysis to quantify the combined health effects of PM2.5 components, and used the meta-smoothing to produce the pooled concentration-response (C-R) curves. Out of 8954 initial articles, 80 cohort studies met the inclusion criteria, including a total of 198.08 million population. The pooled C-R curves demonstrated approximately J-shaped association between total mortality and exposure to BC, and NO3-, but U-shaped and inverted U-shaped relationship withSO42- and OC, respectively. In addition, this study found that exposure to various elements, including BC,SO42-NO3-, NH4+, Zn, Ni, and Si, were significantly associated with an increased risk of total mortality, with Ni presenting the largest estimate. And exposure to NO3-, Zn, and Si was positively associated with an increased risk of respiratory mortality, while exposure to BC, SO42-, and NO3- showed a positive association with risk of cardiovascular mortality. For health outcome of morbidity, BC was notably associated with a higher incidence of asthma, type 2 diabetes and stroke. Subgroup analysis revealed a higher susceptibility to PM2.5 components in Asia compared to Europe and North America, and females showed a higher vulnerability. Given the significant health effects of PM2.5 components, governments are advised to introduce them in regional monitoring and air quality control guidelines. ENVIRONMENTAL IMPLICATION: PM2.5 is a complex mixture of chemical components from various sources, and each component has unique physicochemical properties and uncertain toxicity, posing significant threat to public health. This study systematically reviewed cohort studies on the association between long-term exposure to 13 PM2.5 components and the risk of morbidity and mortality. And we applied the meta-smoothing approach to establish the pooled concentration-response associations between PM2.5 components and mortality globally. Our findings will provide strong support for PM2.5 components monitoring and the improvement of air quality-related regulations. This will aid in helping to enhance health intervention strategies and mitigating public exposure to detrimental particulate matter.
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Affiliation(s)
- Sujuan Chen
- The Key Laboratory of Advanced Interdisciplinary Studies, The First Affiliated Hospital of Guangzhou Medical University, China; School of Public Health, Guangzhou Medical University, Guangzhou 511436, China
| | - Di Liu
- School of Public Health, Guangzhou Medical University, Guangzhou 511436, China
| | - Lin Huang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China
| | - Cui Guo
- Department of Urban Planning and Design, Faculty of Architecture, the University of Hong Kong, Hong Kong SAR
| | - Xiaoke Gao
- School of Public Health, Guangzhou Medical University, Guangzhou 511436, China
| | - Zhiwei Xu
- School of Medicine and Dentistry, Griffith University, Gold Coast, Queensland, Australia
| | - Zhou Yang
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Yu Chen
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Mengmeng Li
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Jun Yang
- The Key Laboratory of Advanced Interdisciplinary Studies, The First Affiliated Hospital of Guangzhou Medical University, China; School of Public Health, Guangzhou Medical University, Guangzhou 511436, China.
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Guo Y, Ji S, Rong S, Hong W, Ding J, Yan W, Qin G, Li G, Sang N. Screening Organic Components and Toxicogenic Structures from Regional Fine Particulate Matters Responsible for Myocardial Fibrosis in Male Mice. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:11268-11279. [PMID: 38875123 DOI: 10.1021/acs.est.4c00735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2024]
Abstract
Numerous studies indicate that fine particulate matters (PM2.5) and its organic components are urgent risk factors for cardiovascular diseases (CVDs). Combining toxicological experiments, effect-directed analyses, and nontarget identification, this study aims to explore whether PM2.5 exposure in coal-combustion areas induces myocardial fibrosis and how to identify the effective organic components and their toxic structures to support regional risk control. First, we constructed an animal model of real-world PM2.5 exposure during the heating season and found that the exposure impaired cardiac systolic function and caused myocardial fibrosis, with chemokine Ccl2-mediated inflammatory response being the key cause of collagen deposition. Then, using the molecular event as target coupled with two-stage chromatographic isolation and mass spectrometry analyses, we identified a total of 171 suspect organic compounds in the PM2.5 samples. Finally, using hierarchical characteristic fragment analysis, we predicted that 40 of them belonged to active compounds with 6 alert structures, including neopentane, butyldimethylamine, 4-ethylphenol, hexanal, decane, and dimethylaniline. These findings provide evidence for risk management and prevention of CVDs in polluted areas.
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Affiliation(s)
- Yuqiong Guo
- College of Environment and Resource, Research Center of Environment and Health, Shanxi University, Taiyuan, Shanxi 030006, PR China
| | - Shaoyang Ji
- College of Environment and Resource, Research Center of Environment and Health, Shanxi University, Taiyuan, Shanxi 030006, PR China
| | - Shuling Rong
- Department of Cardiology, Shanxi Provincial Key Laboratory of Cardiovascular Disease Diagnosis, Treatment and Clinical Pharmacology, The Second Hospital of Shanxi Medical University, Taiyuan, Shanxi 030001, PR China
| | - Wenjun Hong
- Institute of Environmental and Health Sciences, China Jiliang University, Hangzhou, Zhejiang 310018, PR China
| | - Jinjian Ding
- Institute of Environmental and Health Sciences, China Jiliang University, Hangzhou, Zhejiang 310018, PR China
| | - Wei Yan
- Xuzhou Engineering Research Center of Medical Genetics and Transformation, Key Laboratory of Genetic Foundation and Clinical Application, Department of Genetics, Xuzhou Medical University, Xuzhou, Jiangsu 221004, PR China
| | - Guohua Qin
- College of Environment and Resource, Research Center of Environment and Health, Shanxi University, Taiyuan, Shanxi 030006, PR China
| | - Guangke Li
- College of Environment and Resource, Research Center of Environment and Health, Shanxi University, Taiyuan, Shanxi 030006, PR China
| | - Nan Sang
- College of Environment and Resource, Research Center of Environment and Health, Shanxi University, Taiyuan, Shanxi 030006, PR China
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Zhou H, Liang X, Zhang X, Wu J, Jiang Y, Guo B, Wang J, Meng Q, Ding X, Baima Y, Li J, Wei J, Zhang J, Zhao X. Associations of Long-Term Exposure to Fine Particulate Constituents With Cardiovascular Diseases and Underlying Metabolic Mediations: A Prospective Population-Based Cohort in Southwest China. J Am Heart Assoc 2024; 13:e033455. [PMID: 38761074 PMCID: PMC11179805 DOI: 10.1161/jaha.123.033455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 04/01/2024] [Indexed: 05/20/2024]
Abstract
BACKGROUND The health effects of particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5) might differ depending on compositional variations. Little is known about the joint effect of PM2.5 constituents on metabolic syndrome and cardiovascular disease (CVD). This study aims to evaluate the combined associations of PM2.5 components with CVD, identify the most detrimental constituent, and further quantify the mediation effect of metabolic syndrome. METHODS AND RESULTS A total of 14 427 adults were included in a cohort study in Sichuan, China, and were followed to obtain the diagnosis of CVD until 2021. Metabolic syndrome was defined by the simultaneous occurrence of multiple metabolic disorders measured at baseline. The concentrations of PM2.5 chemical constituents within a 1-km2 grid were derived based on satellite- and ground-based detection methods. Cox proportional hazard models showed that black carbon, organic matter (OM), nitrate, ammonium, chloride, and sulfate were positively associated with CVD risks, with hazard ratios (HRs) ranging from 1.24 to 2.11 (all P<0.05). Quantile g-computation showed positive associations with 4 types of CVD risks (HRs ranging from 1.48 to 2.25, all P<0.05). OM and chloride had maximum weights for CVD risks. Causal mediation analysis showed that the positive association of OM with total CVD was mediated by metabolic syndrome, with a mediation proportion of 1.3% (all P<0.05). CONCLUSIONS Long-term exposure to PM2.5 chemical constituents is positively associated with CVD risks. OM and chloride appear to play the most responsible role in the positive associations between PM2.5 and CVD. OM is probably associated with CVD through metabolic-related pathways.
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Affiliation(s)
- Hanwen Zhou
- West China School of Public Health and West China Fourth Hospital Sichuan University Chengdu Sichuan China
| | - Xian Liang
- Chengdu Center for Disease Control and Prevention Chengdu Sichuan China
| | - Xueli Zhang
- Health Information Center of Sichuan Province Chengdu Sichuan China
| | - Jialong Wu
- West China School of Public Health and West China Fourth Hospital Sichuan University Chengdu Sichuan China
| | - Ye Jiang
- West China School of Public Health and West China Fourth Hospital Sichuan University Chengdu Sichuan China
| | - Bing Guo
- West China School of Public Health and West China Fourth Hospital Sichuan University Chengdu Sichuan China
| | - Junhua Wang
- School of Public Health, The key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education Guizhou Medical University Guiyang China
| | - Qiong Meng
- Department of Epidemiology and Health Statistics, School of Public Health Kunming Medical University Kunming Yunnan China
| | - Xianbin Ding
- Chongqing Municipal Center for Disease Control and Prevention Chongqing China
| | | | - Jingzhong Li
- Tibet Center for Disease Control and Prevention Lhasa Tibet China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center University of Maryland College Park MD USA
| | - Juying Zhang
- West China School of Public Health and West China Fourth Hospital Sichuan University Chengdu Sichuan China
| | - Xing Zhao
- West China School of Public Health and West China Fourth Hospital Sichuan University Chengdu Sichuan China
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Feng C, Yang B, Wang Z, Zhang J, Fu Y, Yu B, Dong S, Ma H, Liu H, Zeng H, Reinhardt JD, Yang S. Relationship of long-term exposure to air pollutant mixture with metabolic-associated fatty liver disease and subtypes: A retrospective cohort study of the employed population of Southwest China. ENVIRONMENT INTERNATIONAL 2024; 188:108734. [PMID: 38744043 DOI: 10.1016/j.envint.2024.108734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 05/06/2024] [Accepted: 05/08/2024] [Indexed: 05/16/2024]
Abstract
BACKGROUND While evidence suggests that PM2.5 is associated with overall prevalence of Metabolic (dysfunction)-Associated Fatty Liver Disease (MAFLD), effects of comprehensive air pollutant mixture on MAFLD and its subtypes remain unclear. OBJECTIVE To investigate individual and joint effects of long-term exposure to comprehensive air pollutant mixture on MAFLD and its subtypes. METHODS Data of 27,699 participants of the Chinese Cohort of Working Adults were analyzed. MAFLD and subtypes, including overweight/obesity, lean, and diabetes MAFLD, were diagnosed according to clinical guidelines. Concentrations of NO3-, SO42-, NH4+, organic matter (OM), black carbon (BC), PM2.5, SO2, NO2, O3 and CO were estimated as a weighted average over participants' residential and work addresses for the three years preceding outcome assessment. Logistic regression and weighted quantile sum regression were used to estimate individual and joint effects of air pollutant mixture on presence of MAFLD. RESULTS Overall prevalence of MAFLD was 26.6 % with overweight/obesity, lean, and diabetes MAFLD accounting for 92.0 %, 6.4 %, and 1.6 %, respectively. Exposure to SO42-, NO3-, NH4+, BC, PM2.5, NO2, O3and CO was significantly associated with overall MAFLD, overweight/obesity MAFLD, or lean MAFLD in single pollutant models. Joint effects of air pollutant mixture were observed for overall MAFLD (OR = 1.10 [95 % CI: 1.03, 1.17]), overweight/obesity (1.09 [1.02, 1.15]), and lean MAFLD (1.63 [1.28, 2.07]). Contributions of individual air pollutants to joint effects were dominated by CO in overall and overweight/obesity MAFLD (Weights were 42.31 % and 45.87 %, respectively), while SO42- (36.34 %), SO2 (21.00 %) and BC (12.38 %) were more important in lean MAFLD. Being male, aged above 45 years and smoking increased joint effects of air pollutant mixture on overall MAFLD. CONCLUSIONS Air pollutant mixture was associated with MAFLD, particularly the lean MAFLD subtype. CO played a pivotal role in both overall and overweight/obesity MAFLD, whereas SO42- were associated with lean MAFLD.
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Affiliation(s)
- Chuanteng Feng
- Institute for Disaster Management and Reconstruction, Sichuan University, Chengdu 610200, China; West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - Bo Yang
- Department of Health Management Center, Clinical Medical College & Affiliated Hospital, Chengdu University, Chengdu 610106, China
| | - Zihang Wang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - Jiayi Zhang
- Department of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Yao Fu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - Bin Yu
- Institute for Disaster Management and Reconstruction, Sichuan University, Chengdu 610200, China; West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - Shu Dong
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - Hua Ma
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - Hongyun Liu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - Honglian Zeng
- Department of Health Management Center, Clinical Medical College & Affiliated Hospital, Chengdu University, Chengdu 610106, China
| | - Jan D Reinhardt
- Institute for Disaster Management and Reconstruction, Sichuan University, Chengdu 610200, China; Department of Rehabilitation Medicine, Jiangsu Province Hospital/Nanjing Medical University First Affiliated Hospital, Nanjing 210009, China; Department of Health Sciences and Medicine, University of Lucerne, Lucerne 6002, Switzerland.
| | - Shujuan Yang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China; Department of Health Management Center, Clinical Medical College & Affiliated Hospital, Chengdu University, Chengdu 610106, China; International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan 430079, China.
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Zhou H, Liang X, Tan K, Guo Y, Zhao X, Chen G, Guo B, Li S, Feng S, Pan Q, Li T, Pan J, Ma B, Gao Y, Guan H, Zhang X, Baima Y, Xie L, Zhang J. Mediation of metabolic syndrome in the association between long-term exposure to particulate matter and incident cardiovascular disease: Evidence from a population-based cohort in Chengdu. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 269:115827. [PMID: 38100852 DOI: 10.1016/j.ecoenv.2023.115827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 12/09/2023] [Accepted: 12/11/2023] [Indexed: 12/17/2023]
Abstract
BACKGROUND Particulate matter (PM) exposure has been linked with cardiovascular disease (CVD) and metabolic syndrome (MetS), the latter characterized by concurrent multiple metabolic disorders. As a result, the mechanisms assumption from PM to CVD through MetS have emerged, thus requiring further epidemiological evidence. This cohort study aimed to assess whether MetS mediates the associations of PM with CVD risk. METHODS This study included 14,195 participants from the Chengdu cohort of the China Multi-Ethnic Cohort (CMEC) study in 2018. The primary outcome of incident CVD diagnoses was identified using matched hospital records from the Health Information Center of Sichuan Province. Residence-specific levels of PM with aerodynamic diameters of ≤ 1 µm (PM1), ≤ 2.5 µm (PM2.5), and ≤ 10 µm (PM10) were estimated by spatiotemporal models. Causal mediation analyses were applied to evaluate the indirect effect of MetS. RESULTS Increased exposure levels to PM were significantly associated with MetS and CVD. Mediation analyses indicated that the associations between PM exposure and CVD were mediated by MetS, with the proportion of multiple mediations being 19.3%, 12.1%, and 13.5% for PM1, PM2.5, and PM10, respectively. Further moderated mediation analyses suggested that male, overweight individuals, alcohol drinkers, and those suffering from indoor air pollution may experience more significant adverse effects from PM exposure on CVD via MetS than others. CONCLUSIONS Our findings suggest that MetS partially mediates the association between long-term exposure to PM and CVD. These mediation effects appear to be amplified by demographic characteristics and unhealthy lifestyles.
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Affiliation(s)
- Hanwen Zhou
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Xian Liang
- Chengdu Center for Disease Control and Prevention, Chengdu, Sichuan 610041, China
| | - Kun Tan
- Health information center of Sichuan Province, Chengdu, Sichuan 610041, China
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne VIC 3004, Australia
| | - Xing Zhao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Gongbo Chen
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne VIC 3004, Australia
| | - Bing Guo
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Shanshan Li
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne VIC 3004, Australia
| | - Shiyu Feng
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Qing Pan
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Tian Li
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Jingping Pan
- Health information center of Sichuan Province, Chengdu, Sichuan 610041, China
| | - Bangjing Ma
- Qingbaijiang District Center for Disease Control and Prevention of Chengdu, Chengdu, Sichuan 610399, China
| | - Yang Gao
- Chongqing Center for Disease Control and Prevention, Chongqing 400042, China
| | - Han Guan
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, Guizhou 550025, China
| | - Xuehui Zhang
- School of Public Health, Kunming Medical University, Kunming, Yunnan 650500, China
| | - Yangji Baima
- School of Medicine, Tibet University, Tibet 850000, China
| | - Linshen Xie
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
| | - Juying Zhang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
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Bai Y, Liu M. Multi-scale spatiotemporal trends and corresponding disparities of PM 2.5 exposure in China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 340:122857. [PMID: 37925009 DOI: 10.1016/j.envpol.2023.122857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 10/13/2023] [Accepted: 11/01/2023] [Indexed: 11/06/2023]
Abstract
Despite the effectiveness of targeted measures to mitigate air pollution, China-a developing country with high PM2.5 concentration and dense population, faces a high risk of PM2.5-related mortality. However, existing studies on long-term PM2.5 exposure in China have not reached a consensus as to which year it peaked during the "initially pollution, then mitigation" process. Furthermore, analyses in these studies were rarely undertaken from multi-spatial scales. In this study, a piecewise linear regression model was employed to detect the turning point of population-weighted exposure (PWE) to PM2.5 for the period 2000-2020. Multi-scale spatiotemporal patterns of PM2.5 exposure were evaluated during upward and downward periods at the province, city and county levels, and their corresponding disparities were estimated using the Gini index. The results showed that 2013 was the breakpoint year for PM2.5 PWE across China from 2000 to 2020. Cities and counties where PM2.5 PWE displayed increasing trends during the mitigation stage (2013-2020) basically became the heaviest PM2.5 exposure regions in 2020. High PM2.5 exposure was observed in Beijing-Tianjin-Hebei, Central China, and the Tarim Basin in Xinjiang, whereas lower PM2.5 exposure regions were mainly concentrated in Hainan Province, the Hengduan Mountains, and northern Xinjiang. These cross-provincial patterns might have been overlooked when conducting macro-scale analyses. Province-level PM2.5 exposure inequality was less than the city- and county-levels estimations, and regional inequalities were high in eastern and western China. In this study, multi-scale PM2.5 exposure trends and their disparities over a prolonged period were investigated, and the findings provide a reference for pollution mitigation and regional inequality reduction.
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Affiliation(s)
- Yu Bai
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Menghang Liu
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, China.
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8
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Shi H, Zhou Q, Zhang H, Sun S, Zhao J, Wang Y, Huang J, Jin Y, Zheng Z, Wu R, Zhang Z. The Combined Effects of Hourly Multi-Pollutant on the Risk of Ambulance Emergency Calls: A Seven-Year Time Series Study. TOXICS 2023; 11:895. [PMID: 37999547 PMCID: PMC10675017 DOI: 10.3390/toxics11110895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 10/28/2023] [Accepted: 10/29/2023] [Indexed: 11/25/2023]
Abstract
BACKGROUND Ambulance emergency calls (AECs) are seen as a more suitable metric for syndromic surveillance due to their heightened sensitivity in reflecting the health impacts of air pollutants. Limited evidence has emphasized the combined effect of hourly air pollutants on AECs. This study aims to investigate the combined effects of multipollutants (i.e., PM2.5, PM10, Ozone, NO2, and SO2) on all-cause and cause-specific AECs by using the quantile g-computation method. METHODS We used ambulance emergency dispatch data, air pollutant data, and meteorological data from between 1 January 2013 and 31 December 2019 in Shenzhen, China, to estimate the associations of hourly multipollutants with AECs. We followed a two-stage analytic protocol, including the distributed lag nonlinear model, to examine the predominant lag for each air pollutant, as well as the quantile g-computation model to determine the associations of air pollutant mixtures with all-cause and cause-specific AECs. RESULTS A total of 3,022,164 patients were identified during the study period in Shenzhen. We found that each interquartile range increment in the concentrations of PM2.5, PM10, Ozone, NO2, and SO2 in 0-8 h, 0-8 h, 0-48 h, 0-28 h, and 0-24 h was associated with the highest risk of AECs. Each interquartile range increase in the mixture of air pollutants was significantly associated with a 1.67% (95% CI, 0.12-3.12%) increase in the risk of all-cause AECs, a 1.81% (95% CI, 0.25-3.39%) increase in the risk of vascular AECs, a 1.77% (95% CI, 0.44-3.11%) increase in reproductive AECs, and a 2.12% (95% CI, 0.56-3.71%) increase in AECs due to injuries. CONCLUSIONS We found combined effects of pollutant mixtures associated with an increased risk of AECs across various causes. These findings highlight the importance of targeted policies and interventions to reduce air pollution, particularly for PM, Ozone, and NO2 emissions.
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Affiliation(s)
- Hanxu Shi
- Department of Global Health, School of Public Health, Peking University, Beijing 100191, China; (H.S.); (Y.J.); (Z.Z.)
| | - Qiang Zhou
- Shenzhen Center for Prehospital Care, Shenzhen 518025, China; (Q.Z.); (H.Z.)
| | - Hongjuan Zhang
- Shenzhen Center for Prehospital Care, Shenzhen 518025, China; (Q.Z.); (H.Z.)
| | - Shengzhi Sun
- School of Public Health, Capital Medical University, Beijing 100054, China;
| | - Junfeng Zhao
- School of Computer Science, Peking University, Beijing 100871, China;
| | - Yasha Wang
- National Engineering Research Center of Software Engineering, Peking University, Beijing 100871, China;
| | - Jie Huang
- School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen 518055, China;
| | - Yinzi Jin
- Department of Global Health, School of Public Health, Peking University, Beijing 100191, China; (H.S.); (Y.J.); (Z.Z.)
- Institute for Global Health and Development, Peking University, Beijing 100871, China
| | - Zhijie Zheng
- Department of Global Health, School of Public Health, Peking University, Beijing 100191, China; (H.S.); (Y.J.); (Z.Z.)
| | - Rengyu Wu
- Shenzhen Center for Prehospital Care, Shenzhen 518025, China; (Q.Z.); (H.Z.)
| | - Zhenyu Zhang
- Department of Global Health, School of Public Health, Peking University, Beijing 100191, China; (H.S.); (Y.J.); (Z.Z.)
- Institute for Global Health and Development, Peking University, Beijing 100871, China
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