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Gabet S, Puy L. Current trend in air pollution exposure and stroke. Curr Opin Neurol 2024:00019052-990000000-00205. [PMID: 39508397 DOI: 10.1097/wco.0000000000001331] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2024]
Abstract
PURPOSE OF REVIEW Stroke is the second leading cause of death worldwide, and exposure to particulate air pollution is now recognized as one of the major modifiable risk factors. However, air pollution can vary in terms of physicochemical composition and exposition specificities. Therefore, its relationships with stroke outcomes remain under intense investigation. RECENT FINDINGS This review highlights, alongside particles, that short-term and long-term exposure to nitrogen dioxide (NO2) and ozone is likely to be also linked to stroke-related morbidity and mortality. Moreover, air pollution may increase the risk of transitioning from a healthy status to incident stroke and morbimortality after stroke. Additionally, relationships may vary depending on the air pollution mixture (e.g., particle-related components, pollutant interactions), pollutant sources (e.g., traffic-related or not), stroke etiology (ischemic or hemorrhagic), or exposed individual's characteristics (e.g., age, sex, genetic predisposition, weight status). Nonlinear dose-response functions and short-term effect lags have been reported, but these features need further refinement. SUMMARY The relationship between stroke and air pollution is now well established. Nonetheless, future research should further consider the physicochemical properties of air pollutants, multiple exposures, and individual vulnerabilities. Moreover, advanced statistical methods should be more commonly used to better describe the relationship shapes.
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Affiliation(s)
- Stephan Gabet
- University Lille, CHU Lille, Institut Pasteur de Lille, ULR 4483-IMPacts de l'Environnement Chimique sur la Santé (IMPECS)
| | - Laurent Puy
- University Lille, Inserm, CHU Lille, U1172 - LilNCog - Lille Neuroscience & Cognition, Lille, France
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Chen Z, Zhu M, Ni W, Wu B, Liu T, Lin B, Lai L, Jing Y, Jiang L, Ouyang Z, Hu J, Zheng H, Peng W, Yu X, Fan J. Association of PM 2.5 exposure in early pregnancy and maternal liver function: A retrospective cohort study in Shenzhen, China. ENVIRONMENTAL RESEARCH 2024; 263:119934. [PMID: 39276834 DOI: 10.1016/j.envres.2024.119934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2024] [Revised: 09/02/2024] [Accepted: 09/03/2024] [Indexed: 09/17/2024]
Abstract
OBJECTIVE Studies have shown that fine particulate matter (PM2.5) has adverse effects on the liver function, but epidemiological evidence is limited, especially regarding pregnant women. This study aims to investigate the association between PM2.5 exposure in early pregnancy and maternal liver function during pregnancy. METHODS This retrospective cohort study included 13,342 pregnant participants. PM2.5 and Ozone (O3) exposure level, mean temperature, and relative humidity for each participant were assessed according to their residential address. The levels of serum aspartate aminotransferase (AST), alanine aminotransferase (ALT), and total bilirubin (TBIL) were measured during the second and third trimesters. Data on PM2.5 and O3 exposure level were sourced from Tracking Air Pollution in China (TAP), while the mean temperature and relative humidity were obtained from the ERA5 dataset. The Generalized Additive Model (GAM) was used to analyze the associations between PM2.5 exposure and maternal liver function during pregnancy, adjusting for potential confounding factors. RESULTS According to the results, each 10 μg/m3 increase in PM2.5 was associated with an increase of 3.57% (95% CI: 0.29%, 6.96%) in ALT and 4.25% (95% CI: 2.33%, 6.21%) in TBIL during the second trimester and 4.51% (95% CI: 2.59%, 6.47%) in TBIL during the third trimester, respectively. After adjusting for O3, these associations remained significant, and the effect of PM2.5 on ALT during the second trimester was further strengthened. No significant association observed between PM2.5 and AST. CONCLUSIONS PM2.5 exposure in early pregnancy is associated with increasement of maternal ALT and TBIL, suggesting that PM2.5 exposure may have an adverse effect on maternal liver function. Although this finding indicates an association between PM2.5 exposure and maternal liver function, more research is needed to confirm our findings and explore the underlying biological mechanisms.
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Affiliation(s)
- Zhijian Chen
- Department of Preventive Healthcare, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China; Faculty of Medicine, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, China
| | - Minting Zhu
- School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Weigui Ni
- Department of Preventive Healthcare, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China
| | - Bo Wu
- Department of Preventive Healthcare, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China
| | - Tao Liu
- China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China; Key Laboratory of Viral Pathogenesis & Infection Prevention and Control, Jinan University, Ministry of Education, Guangzhou 510632, China
| | - Bingyi Lin
- Department of Preventive Healthcare, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China
| | - Lijuan Lai
- Department of Preventive Healthcare, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China
| | - Yi Jing
- Department of Preventive Healthcare, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China
| | - Long Jiang
- Department of Preventive Healthcare, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China
| | - Zhongai Ouyang
- Department of Preventive Healthcare, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China; School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Jianxiong Hu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Haoqu Zheng
- Faculty of Medicine, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, China
| | - Wan Peng
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Xi Yu
- Faculty of Medicine, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, China.
| | - Jingjie Fan
- Department of Preventive Healthcare, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China.
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Liu Z, Meng H, Wang X, Lu W, Ma X, Geng Y, Su X, Pan D, Liang P. Interaction between ambient CO and temperature or relative humidity on the risk of stroke hospitalization. Sci Rep 2024; 14:16740. [PMID: 39033193 PMCID: PMC11271280 DOI: 10.1038/s41598-024-67568-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Accepted: 07/12/2024] [Indexed: 07/23/2024] Open
Abstract
Although the independent effects of ambient CO, temperature or humidity on stroke have been confirmed, it is still unclear where there is an interaction between these factors and who is sensitive populations for these. The stroke hospitalization and ambient CO, temperature, humidity data were collected in 22 Counties and districts of Ningxia, China in 2014-2019. The lagged effect of ambient CO, temperature or humidity were analyze by the generalized additive model; the interaction were evaluated by the bivariate response surface model and stratified analysis with relative excessive risk (RERI). High temperature and CO levels had synergistic effects on hemorrhagic stroke (RERI = 0.05, 95% CI 0.033-0.086) and ischemic stroke (RERI = 0.035, 95% CI 0.006-0.08). Low relative humidity and CO were synergistic in hemorrhagic stroke (RERI = 0.192, 95% CI 0.184-0.205) and only in ischemic stroke in the elderly group (RERI = 0.056, 95% CI 0.025-0.085). High relative humidity and CO exhibited antagonistic effects on the risk of ischemic stroke hospitalization in both male and female groups (RERI = - 0.088, 95% CI - 0.151to - 0.031; RERI = - 0.144, 95% CI - 0.216 to - 0.197). Exposure to CO increases the risk of hospitalization related to hemorrhagic and ischemic strokes. CO and temperature or humidity interact with risk of stroke hospitalization with sex and age differences.
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Affiliation(s)
- Zhuo Liu
- School of Public Health and Management, Ningxia Medical University, Yinchuan, 750001, China
- Ningxia Key Laboratory of Environmental Factors and Chronic Disease Control, Yinchuan, 750000, China
| | - Hua Meng
- School of Public Health and Management, Ningxia Medical University, Yinchuan, 750001, China
- Ningxia Key Laboratory of Environmental Factors and Chronic Disease Control, Yinchuan, 750000, China
| | - Xingtian Wang
- General hospital of Ningxia Medical University, No. 804, Shengli Street, Xingqing District, Yinchuan, 750001, Ningxia, China
| | - Wenwen Lu
- Shenzhen Futian District Chronic Disease Prevention and Treatment Hospital, 18 Xinzhou 8Th Street, Futian District, Shenzhen, 518048, China
| | - Xiaojuan Ma
- School of Public Health and Management, Ningxia Medical University, Yinchuan, 750001, China
- Ningxia Key Laboratory of Environmental Factors and Chronic Disease Control, Yinchuan, 750000, China
| | - Yuhui Geng
- School of Public Health and Management, Ningxia Medical University, Yinchuan, 750001, China
- Ningxia Key Laboratory of Environmental Factors and Chronic Disease Control, Yinchuan, 750000, China
| | - Xinya Su
- School of Public Health and Management, Ningxia Medical University, Yinchuan, 750001, China
- Ningxia Key Laboratory of Environmental Factors and Chronic Disease Control, Yinchuan, 750000, China
| | - Dongfeng Pan
- Department of Emergency Medicine, People's Hospital of Ningxia Hui Autonomous Region, Yinchuan, 750000, China
| | - Peifeng Liang
- Public Health Center, People's Hospital of Ningxia Hui Autonomous Region, Ningxia Medical University, 301 Zhengyuan North Street, Yinchuan, 750000, Ningxia, China.
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Lin Z, Wang M, Ma J, Liu Y, Lawrence WR, Chen S, Zhang W, Hu J, He G, Liu T, Zhang M, Ma W. The joint effects of mixture exposure to multiple meteorological factors on step count: A panel study in China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 346:123469. [PMID: 38395131 DOI: 10.1016/j.envpol.2024.123469] [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: 11/04/2023] [Revised: 01/21/2024] [Accepted: 01/29/2024] [Indexed: 02/25/2024]
Abstract
The public health burden of increasing extreme weather events has been well documented. However, the influence of meteorological factors on physical activity remains limited. Existing mixture effect methods cannot handle cumulative lag effects. Therefore, we developed quantile g-computation Distributed lag non-linear model (QG-DLNM) by embedding a DLNM into quantile g-computation to allow for the concurrent consideration of both cumulated lag effects and mixture effects. We gathered repeated measurement data from Henan Province in China to investigate both the individual impact of meteorological factor on step counts using a DLNM, and the joint effect using the QG-DLNM. We projected future step counts linked to changes in temperature and relative humidity driven by climate change under three scenarios from the sixth phase of the Coupled Model Intercomparison Project. Our findings indicate there are inversed U-shaped associations for temperature, wind speed, and mixture exposure with step counts, peaking at 11.6 °C in temperature, 2.7 m/s in wind speed, and 30th percentile in mixture exposure. However, there are negative associations between relative humidity and rainfall with step counts. Additionally, relative humidity possesses the highest weights in the joint effect (49% contribution). Compared to 2022s, future step counts are projected to decrease due to temperature changes, while increase due to relative humidity changes. However, when considering both future temperature and humidity changes driven by climate change, the projections indicate a decrease in step counts. Our findings may suggest Chinese physical activity will be negatively influenced by global warming.
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Affiliation(s)
- Ziqiang Lin
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, 511443, China
| | - Mengmeng Wang
- Department of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Medical School, 1066 Xueyuan Boulevard, Nanshan District, Shenzhen, Guangdong, 518055, China
| | - Junrong Ma
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, 511443, China
| | - Yingyin Liu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, 511443, China
| | - Wayne R Lawrence
- Department of Epidemiology and Biostatistics, School of Public Health, University at Albany, State University of New York, 1 University Place, Rensselaer, NY, 12144, USA
| | - Shirui Chen
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Wangjian Zhang
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Jianxiong Hu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, 511443, China
| | - Guanhao He
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, 511443, China
| | - Tao Liu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, 511443, China
| | - Ming Zhang
- Department of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Medical School, 1066 Xueyuan Boulevard, Nanshan District, Shenzhen, Guangdong, 518055, China
| | - Wenjun Ma
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, 511443, China.
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Zhu Q, Yu M, Bai G, Zhou C, Meng R, Huang B, Gong W, Zhang H, Hu R, Hou Z, Xiao Y, Jin D, Qin M, Hu J, Xiao J, He G, Lin L, Liang X, Guo Y, Liu T, Ma W. The joint associations of ambient air pollutants and weather factors with mortality: Evidence from a national time-stratified case-crossover study in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 907:168129. [PMID: 39491184 DOI: 10.1016/j.scitotenv.2023.168129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2023] [Revised: 09/29/2023] [Accepted: 10/24/2023] [Indexed: 11/05/2024]
Abstract
BACKGROUND People in daily life are usually exposed to multiple environmental factors, but few studies have evaluated the joint health impacts of ambient air pollutants and weather factors. OBJECTIVES To investigate the joint associations of short-term exposures to ambient air pollutants and weather factors with mortality and estimate the mortality burden attributable to these multiple environmental exposures in China. METHODS We collected individual death information from six provinces (Guangdong, Yunnan, Hunan, Zhejiang, Tibet and Jilin) in China during 2013 to 2018, and applied a time-stratified case-crossover study design to estimate the joint associations of air pollutants [PM2.5 (particulate matter with an aerodynamic diameter ≤2.5 μm), O3 (ozone), NO2 (nitrogen dioxide), SO2 (sulfur dioxide), and CO (carbon monoxide)] and weather factors (temperature and relative humidity) with mortality. Air pollutant concentrations on the case day and control days were assessed using a random forest model, and the corresponding temperature and relative humidity data were assessed using a thin plate smoothing model. Excess risks (ER) of exposure to air pollutants and weather factors were estimated using Cox proportional regression models and the attributable fraction (AF) was calculated. RESULTS A total of 6,685,146 deaths were enrolled in this study. The overall AF of total mortality attributed to air pollutants (lag03 days) and weather factors (lag021 days) was 16.65 % (95%CI: 16.43 %, 16.87 %), in which the joint AFs attributable to air pollutants and weather factors were 5.31 % (95%CI: 5.08 %, 5.53 %) and 11.34 % (95%CI: 11.12 %, 11.56 %) respectively, and temperature contributed 56 % in the joint effects. Stratified analyses showed greater AFs in females (21.32 %) than in males (14.61 %), and in the elderly (>100 years, 42.34 %) than in young people (21-30 years, 7.67 %). The AFs of mortality from cardiovascular diseases, respiratory diseases, and pneumonia attributed to the joint exposures were 22.72 %, 24.82 % and 33.03 %, respectively. DISCUSSION This study provides the joint associations of short-term exposures to both air pollutants and weather factors with mortality risk in China, which has important implications in comprehensively assessing the health impacts of environmental exposures, and taking actions to protect human health.
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Affiliation(s)
- Qijiong Zhu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China; Disease Control and Prevention Institute of Jinan University, Jinan University, Guangzhou 510632, China
| | - Min Yu
- Zhejiang Center for Disease Control and Prevention, Hangzhou, Zhejiang 310051, China
| | - Guoxia Bai
- Institute of Non-communicable Diseases Prevention and Control, Tibet Center for Disease Control and Prevention, Lhasa 850000, China
| | - Chunliang Zhou
- Department of Environment and Health, Hunan Provincial Center for Disease Control and Prevention, Changsha 450001, China
| | - Ruilin Meng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Biao Huang
- Health Hazard Factors Control Department, Jilin Provincial Center for Disease Control and Prevention, Changchun 130062, China
| | - Weiwei Gong
- Zhejiang Center for Disease Control and Prevention, Hangzhou, Zhejiang 310051, China
| | - Haoming Zhang
- Yunnan Center for Disease Control and Prevention, Kunming 650022, China
| | - Ruying Hu
- Zhejiang Center for Disease Control and Prevention, Hangzhou, Zhejiang 310051, China
| | - Zhulin Hou
- Health Hazard Factors Control Department, Jilin Provincial Center for Disease Control and Prevention, Changchun 130062, China
| | - Yize Xiao
- Yunnan Center for Disease Control and Prevention, Kunming 650022, China
| | - Donghui Jin
- Department of Environment and Health, Hunan Provincial Center for Disease Control and Prevention, Changsha 450001, China
| | - Mingfang Qin
- Yunnan Center for Disease Control and Prevention, Kunming 650022, China
| | - Jianxiong Hu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Jianpeng Xiao
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Guanhao He
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China; Disease Control and Prevention Institute of Jinan University, Jinan University, Guangzhou 510632, China
| | - Lifeng Lin
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Xiaofeng Liang
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China; Disease Control and Prevention Institute of Jinan University, Jinan University, Guangzhou 510632, China
| | - Yanfang Guo
- Bao'an District Hospital for Chronic Diseases Prevention and Cure, Shenzhen 518101, China.
| | - Tao Liu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China; Disease Control and Prevention Institute of Jinan University, Jinan University, Guangzhou 510632, China.
| | - Wenjun Ma
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China; Disease Control and Prevention Institute of Jinan University, Jinan University, Guangzhou 510632, China
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Liu C, Yu Y, Liu C, Tang L, Zhao K, Zhang P, He F, Wang M, Shi C, Lu Z, Zhang B, Wei J, Xue F, Guo X, Jia X. Effect of neighbourhood greenness on the association between air pollution and risk of stroke first onset: A case-crossover study in shandong province, China. Int J Hyg Environ Health 2023; 254:114262. [PMID: 37776760 DOI: 10.1016/j.ijheh.2023.114262] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 09/11/2023] [Accepted: 09/19/2023] [Indexed: 10/02/2023]
Abstract
BACKGROUND Higher neighbourhood greenness is associated with beneficial health outcomes, and short-term exposure to air pollution is associated with an elevated risk of stroke onset. However, little is known about their interactions. METHODS Daily data on stroke first onset were collected from 20 counties in Shangdong Province, China, from 2013 to 2019. The enhanced vegetation index (EVI) and concentrations of fine particulate matter (PM2.5), nitrogen dioxide (NO2), ozone (O3), carbon monoxide (CO), and sulfur dioxide (SO2) were calculated for each individual at the village or community level based on their home address to measure their neighbourhood exposure to greenness and air pollution. EVI was categorised as low or high, and a time-stratified case-crossover design was used to estimate the percent excess risk (ER%) of stroke associated with short-term exposure to air pollution. We further stratified greenness on the basis of EVI values into quartiles and introduced interaction terms between air pollutant concentrations and the median EVI values of the quartiles to assess the effect of greenness on the associations between short-term exposure and stroke. RESULTS Individuals living in the high-greenness areas had weaker associations between total stroke risk and exposure to NO2 (low greenness: ER% = 1.765% [95% CI 1.205%-2.328%]; high greenness: ER% = 0.368% [95% CI -0.252% to 0.991%]; P = 0.001), O3 (low greenness: 0.476% [95% CI 0.246%-0.706%]; high greenness: ER% = 0.085% [95% CI -0.156% to 0.327%]; P = 0.011), and SO2 (low greenness: 0.632% [95% CI 0.138%-1.129%]; high greenness: ER% = -0.177% [95% CI -0.782% to 0.431%]; P = 0.035). CONCLUSION Residence in areas with higher greenness was related to weaker associations between air pollution and stroke risk, suggesting that effectively planning green spaces can improve public health.
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Affiliation(s)
- Chao Liu
- Department of Epidemiology and Statistics, Bengbu Medical College, China
| | - Ying Yu
- Department of Physiology, School of Basic Medicine, Bengbu Medical College, China
| | - Chengrong Liu
- Department of Epidemiology and Statistics, Bengbu Medical College, China
| | - Lulu Tang
- Department of Epidemiology and Statistics, Bengbu Medical College, China
| | - Ke Zhao
- Department of Epidemiology and Statistics, Bengbu Medical College, China
| | - Peiyao Zhang
- Department of Epidemiology and Statistics, Bengbu Medical College, China
| | - Fenfen He
- Department of Epidemiology and Statistics, Bengbu Medical College, China
| | - Meng Wang
- Wuxi School of Medicine, Jiangnan University, Wuxi, China
| | - Chunxiang Shi
- Meteorological Data Laboratory, National Meteorological Information Center, Beijing, China
| | - Zilong Lu
- Shandong Center for Disease Control and Prevention, Jinan, China
| | - Bingyin Zhang
- Shandong Center for Disease Control and Prevention, Jinan, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA.
| | - Fuzhong Xue
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Healthcare Big Data Research Institute, Jinan, China.
| | - Xiaolei Guo
- Shandong Center for Disease Control and Prevention, Jinan, China.
| | - Xianjie Jia
- Department of Epidemiology and Statistics, Bengbu Medical College, China.
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7
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Xu J, Shi Y, Chen G, Guo Y, Tang W, Wu C, Liang S, Huang Z, He G, Dong X, Cao G, Yang P, Lin Z, Zhu S, Wu F, Liu T, Ma W. Joint Effects of Long-Term Exposure to Ambient Fine Particulate Matter and Ozone on Asthmatic Symptoms: Prospective Cohort Study. JMIR Public Health Surveill 2023; 9:e47403. [PMID: 37535415 PMCID: PMC10436124 DOI: 10.2196/47403] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Revised: 05/08/2023] [Accepted: 06/21/2023] [Indexed: 08/04/2023] Open
Abstract
BACKGROUND The associations of long-term exposure to air pollutants in the presence of asthmatic symptoms remain inconclusive and the joint effects of air pollutants as a mixture are unclear. OBJECTIVE We aimed to investigate the individual and joint associations of long-term exposure to ambient fine particulate matter (PM2.5) and daily 8-hour maximum ozone concentrations (MDA8 O3) in the presence of asthmatic symptoms in Chinese adults. METHODS Data were derived from the World Health Organization Study on Global Ageing and Adult Health (WHO SAGE) cohort study among adults aged 50 years or older, which was implemented in 1 municipality and 7 provinces across China during 2007-2018. Annual average MDA8 O3 and PM2.5 at individual residential addresses were estimated by an iterative random forest model and a satellite-based spatiotemporal model, respectively. Participants who were diagnosed with asthma by a doctor or taking asthma-related therapies or experiencing related conditions within the past 12 months were recorded as having asthmatic symptoms. The individual associations of PM2.5 and MDA8 O3 with asthmatic symptoms were estimated by a Cox proportional hazards regression model, and the joint association was estimated by a quantile g-computation model. A series of subgroup analyses was applied to examine the potential modifications of some characteristics. We also calculated the population-attributable fraction (PAF) of asthmatic symptoms attributed to PM2.5 and MDA8 O3. RESULTS A total of 8490 adults older than 50 years were included, and the average follow-up duration was 6.9 years. During the follow-up periods, 586 (6.9%) participants reported asthmatic symptoms. Individual effect analyses showed that the risk of asthmatic symptoms was positively associated with MDA8 O3 (hazard ratio [HR] 1.12, 95% CI 1.01-1.24, for per quantile) and PM2.5 (HR 1.18, 95% CI 1.05-1.31, for per quantile). Joint effect analyses showed that per equal quantile increment of MDA8 O3 and PM2.5 was associated with an 18% (HR 1.18, 95% CI 1.05-1.33) increase in the risk of asthmatic symptoms, and PM2.5 contributed more (68%) in the joint effects. The individual PAFs of asthmatic symptoms attributable to PM2.5 and MDA8 O3 were 2.86% (95% CI 0.17%-5.50%) and 4.83% (95% CI 1.42%-7.25%), respectively, while the joint PAF of asthmatic symptoms attributable to exposure mixture was 4.32% (95% CI 1.10%-7.46%). The joint associations were greater in participants with obesity, in urban areas, with lower family income, and who used unclean household cooking fuel. CONCLUSIONS Long-term exposure to PM2.5 and MDA8 O3 may individually and jointly increase the risk of asthmatic symptoms, and the joint effects were smaller than the sum of individual effects. These findings informed the importance of joint associations of long-term exposure to air pollutants with asthma.
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Affiliation(s)
- Jiahong Xu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Yan Shi
- Shanghai Municipal Centre for Disease Control and Prevention, Shanghai, China
| | - Gongbo Chen
- School of Public Health and Preventive Medicine, Monash University, Victoria, Australia
| | - Yanfei Guo
- Shanghai Municipal Centre for Disease Control and Prevention, Shanghai, China
| | - Weiling Tang
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Cuiling Wu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Shuru Liang
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Zhongguo Huang
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Guanhao He
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Xiaomei Dong
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Ganxiang Cao
- School of Public Health, Guangdong Pharmaceutical University, Guangzhou, China
| | - Pan Yang
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Ziqiang Lin
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Sui Zhu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Fan Wu
- Shanghai Medical College, Fudan University, Shanghai, China
| | - Tao Liu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Wenjun Ma
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
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