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Chen S, Zhang Y, Wei J, Hao C, Wu W, Li Z, Guo T, Lin Z, Zhang W, Hao Y. Risk of stroke admission after long-term exposure to PM 1: Evidence from a large cohort in South China. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 283:116720. [PMID: 39053181 DOI: 10.1016/j.ecoenv.2024.116720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Revised: 07/04/2024] [Accepted: 07/09/2024] [Indexed: 07/27/2024]
Abstract
BACKGROUND Limited attention has been paid to the health effects of long-term PM1 exposure on stroke admission. Current investigations exploring the long-term PM exposure effect are largely based on observational studies, and PM generally is not allocated randomly to participants. Using traditional regression models might confuse messaging and hinder policy recommendations for pollution control and disease prevention policies. METHODS We conducted a cohort study among 36,271 adults from one of the largest cities in China in 2015 and followed up through 2020. Hazard ratios of stroke admissions following long-term PM1 exposure were estimated via a causal inference approach, marginal structural time-varying Cox proportional hazard model, accounting for multiple confounders. Additionally, several sensitivity analyses and impact modification analyses were carried out. RESULTS AND DISCUSSION Associations with 1 μg/m3 increase in long-term PM1 were identified for total (HR, 1.079; 95 %CI, 1.012-1.151) and ischemic stroke admissions (HR, 1.092; 95 %CI, 1.018-1.171). The harmful associations varied with exposure duration, initially increasing and then decreasing. The 2-3 years cumulative exposure was associated with a 3.3-5.4 % raised risk for total stroke. For every 1 μg/m³ increase in long-term PM1 exposure, females exhibited a higher risk of both total and ischemic stroke (13 % and 16 %) than men (4 % and 5 %). Low-exposure individuals (whose annual PM1 concentrations were under the third quartile among the annual concentrations for all the participants) exhibited greater sensitivity to PM1 effects (total stroke: 1.079 vs. 1.107; ischemic stroke: 1.092 vs. 1.116). The results underline the importance of safeguarding low-exposed people in highly polluted areas and suggest that long-term PM1 exposure may increase stroke admission risk, warranting attention to vulnerable groups.
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Affiliation(s)
- Shirui Chen
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Yuqin Zhang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA
| | - Chun Hao
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Wenjing Wu
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Zhiqiang Li
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Tong Guo
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Ziqiang Lin
- Department of Preventive Medicine, School of Basic Medicine and Public Health, Jinan University, Guangzhou, China.
| | - Wangjian Zhang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China.
| | - Yuantao Hao
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, China.
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Mahakalkar AU, Gianquintieri L, Amici L, Brovelli MA, Caiani EG. Geospatial analysis of short-term exposure to air pollution and risk of cardiovascular diseases and mortality-A systematic review. CHEMOSPHERE 2024; 353:141495. [PMID: 38373448 DOI: 10.1016/j.chemosphere.2024.141495] [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: 12/28/2023] [Revised: 02/15/2024] [Accepted: 02/16/2024] [Indexed: 02/21/2024]
Abstract
The cardiovascular risk associated with short-term ambient air pollution exposure is well-documented. However, recent advancements in geospatial techniques have provided new insights into this risk. This systematic review focuses on short-term exposure studies that applied advanced geospatial pollution modelling to estimate cardiovascular disease (CVD) risk and accounted for additional unconventional neighbourhood-level confounders to analyse their modifier effect on the risk. Four databases were investigated to select publications between 2018 and 2023 that met the inclusion criteria of studying the effect of particulate matter (PM2.5 and PM10), SO2, NOx, CO, and O3 on CVD mortality or morbidity, utilizing pollution modelling techniques, and considering spatial and temporal confounders. Out of 3277 publications, 285 were identified for full-text review, of which 34 satisfied the inclusion criteria for qualitative analysis, and 12 of them were chosen for additional quantitative analysis. Quality assessment revealed that 28 out of 34 included articles scored 4 or above, indicating high quality. In 30 studies, advanced pollution modelling techniques were used, while in 4 only simpler methods were applied. The most pertinent confounders identified were socio-demographic variables (e.g., socio-economic status, population percentage by race or ethnicity) and neighbourhood-level built environment variables (e.g., urban/rural area, percentage of green space, proximity to healthcare), which exhibited varying modifier effects depending on the context. In the quantitative analysis, only PM 2.5 showed a significant positive association to all-cause CVD-related hospitalisation. Other pollutants did not show any significant effect, likely due to the high inter-study heterogeneity and a limited number of cases. The application of advanced geospatial measurement and modelling of air pollution exposure, as well as its risk, is increasing. This review underscores the importance of accounting for unconventional neighbourhood-level confounders to enhance the understanding of the CVD risk associated with short-term pollution exposure.
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Affiliation(s)
- Amruta Umakant Mahakalkar
- Politecnico di Milano, Electronics, Information and Bioengineering Dpt., Milan, Italy; University School for Advanced Studies IUSS, Pavia, Italy
| | - Lorenzo Gianquintieri
- Politecnico di Milano, Electronics, Information and Bioengineering Dpt., Milan, Italy.
| | - Lorenzo Amici
- Politecnico di Milano, Civil and Environmental Engineering Dpt., Milan, Italy
| | | | - Enrico Gianluca Caiani
- Politecnico di Milano, Electronics, Information and Bioengineering Dpt., Milan, Italy; IRCCS Istituto Auxologico Italiano, Milan, Italy
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Sun Z, Chen L, Liu Z, Feng L, Cui Y, Zhang X, Wu Y, Zhang J. Modifying effects of green space on the relationships between air pollution and ischemic cerebrovascular event recurrence in Tianjin, China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2024:1-11. [PMID: 38357761 DOI: 10.1080/09603123.2024.2314636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 02/01/2024] [Indexed: 02/16/2024]
Abstract
This study aimed to explore how air pollution and green space influence ICE recurrence and whether they might interact with each other. A case-cross design was used in this study, which was carried out in Tianjin, China. A total of 8306 patients with recurrent ICE were collected from 2019 to 2020. The maximum effects of PM2.5, PM10, SO2, NO2, CO were 1.012 (95%CI: 1.004, 1.019), 1.010 (95%CI: 1.004, 1.016), 1.035 (95%CI: 0.982, 1.091), 1.067 (95%CI: 1.043, 1.091) and 1.012 (95%CI: 1.004, 1.021) , respectively, and the risk was higher in males and in the 50-60 age group. In the stratification of greening, it was found that air pollution except O3 had the highest risk of ICE recurrence for those with lower green space. Our study found that air pollution (except O3) can increase the risk of ICE recurrence, and this risk can be reduced by increasing green space.
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Affiliation(s)
- Zhiying Sun
- Environmental Health and School Health, Tianjin Centers for Disease Control and Prevention, Tianjin, China
| | - Lu Chen
- Environmental Health and School Health, Tianjin Centers for Disease Control and Prevention, Tianjin, China
| | - Zhonghui Liu
- Environmental Health and School Health, Tianjin Centers for Disease Control and Prevention, Tianjin, China
| | - Lihong Feng
- Environmental Health and School Health, Tianjin Centers for Disease Control and Prevention, Tianjin, China
| | - Yushan Cui
- Environmental Health and School Health, Tianjin Centers for Disease Control and Prevention, Tianjin, China
| | - Xianwei Zhang
- Environmental Health and School Health, Tianjin Centers for Disease Control and Prevention, Tianjin, China
| | - Yan Wu
- Environmental Health and School Health, Tianjin Centers for Disease Control and Prevention, Tianjin, China
| | - Jingwei Zhang
- Environmental Health and School Health, Tianjin Centers for Disease Control and Prevention, Tianjin, China
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Zhang S, Chen L, Qian ZM, Li D, Cai M, Wang C, Zhang Z, Vaughn MG, Keith AE, Li H, Lin H. Associations between air pollution and the risk of first admission and multiple readmissions for cardiovascular diseases. Heart 2024; 110:337-345. [PMID: 37673655 DOI: 10.1136/heartjnl-2023-322682] [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: 03/29/2023] [Accepted: 08/19/2023] [Indexed: 09/08/2023] Open
Abstract
OBJECTIVES We aimed to investigate the associations between air pollutants and the risk of admission and multiple readmission events for cardiovascular disease (CVD). METHODS A total of 285 009 participants free of CVD at baseline from the UK Biobank were included in this analysis. Four major cardiovascular admission events were identified during the follow-up: chronic ischaemic heart disease (CIHD), cerebrovascular disease, atrial fibrillation and heart failure. We used Prentice, Williams and Peterson-Total Time model to examine the association between ambient air pollution and first admission, as well as multiple readmissions for these CVDs. RESULTS During a median follow-up of 12 years, 17 176 (6.03%) participants were hospitalised with CVDs, and 6203 (36.11%) patients with CVD had subsequent readmission events for CVDs. We observed significant associations between air pollution and both first admission and readmission for CVDs, with generally stronger associations on readmission for cardiovascular events. For example, the adjusted HRs for the first admission and subsequent readmission for cerebrovascular disease were 1.130 (95% CI 1.070 to 1.194) and 1.270 (95% CI 1.137 to 1.418) for each IQR increase of particulate matter with a diameter ≤2.5 µm. The corresponding HRs for CIHD were 1.060 (95% CI 1.008 to 1.114) and 1.120 (95% CI 1.070 to 1.171). Sex stratified analyses showed that the associations were generally more pronounced among females than males. CONCLUSION This study provides evidence that ambient air pollutants might play an important role in both first admission and readmission for cardiovascular events. In addition, patients with pre-existing CVDs may be more vulnerable to air pollution compared with healthy population.
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Affiliation(s)
- Shiyu Zhang
- Department of Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Lan Chen
- Department of Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Zhengmin Min Qian
- Department of Epidemiology and Biostatistics, Saint Louis University College for Public Health and Social Justice, Saint Louis, Missouri, USA
| | - Dan Li
- Department of Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Miao Cai
- Department of Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China
| | - Zilong Zhang
- Department of Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Michael G Vaughn
- School of Social Work, College for Public Health and Social Justice, Saint Louis University, Saint Louis, Missouri, USA
| | - Amy E Keith
- Department of Epidemiology and Biostatistics, Saint Louis University College for Public Health and Social Justice, Saint Louis, Missouri, USA
| | - Haitao Li
- Department of Social Medicine and Health Service Management, Health Science Center, Shenzhen University, Shenzhen, Guangdong, China
| | - Hualiang Lin
- Department of Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou, Guangdong, China
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Lai Z, Zhang J, Ran S, Zheng D, Feng J, Wu G, Cai M, Lin H. Ambient fine particulate matter chemical composition associated with in-hospital case fatality, hospital expenses, and length of hospital stay among patients with heart failure in China. J Glob Health 2024; 14:04032. [PMID: 38299774 PMCID: PMC10832573 DOI: 10.7189/jogh.14.04032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2024] Open
Abstract
*Joint senior authorship. BACKGROUND Previous studies have observed the adverse effects of ambient fine particulate matter pollution (PM2.5) on heart failure (HF). However, evidence regarding the impacts of specific PM2.5 components remains scarce. METHODS We included 58 129 patients hospitalised for HF between 2013 and 2017 in 11 cities of Shanxi, China from inpatient discharge database. We evaluated exposure to PM2.5 and its components ((sulphate (SO42-), nitrate (NO3-), ammonium (NH4+), organic matter (OM) and black carbon (BC)), along with meteorological factors using bilinear interpolation at each patients' residential address. We used multivariable logistic and linear regression models to assess the associations of these components with in-hospital case fatality, hospital expenses, and length of hospital stay. RESULTS Increase equivalents to the interquartile range (IQR) in OM (odds ratio (OR) = 1.13; 95% confidence interval (CI) = 1.02, 1.26) and BC (OR = 1.14; 95% CI = 1.02, 1.26) were linked to in-hospital case fatality. Per IQR increments in PM2.5, SO42-, NO3-, OM, and BC were associated with cost increases of 420.62 (95% CI = 285.75, 555.49), 221.83 (95% CI = 96.95, 346.71), 214.93 (95% CI = 68.66, 361.21), 300.06 (95% CI = 176.96, 423.16), and 303.09 (95% CI = 180.76, 425.42) CNY. Increases of 1 IQR in PM2.5, SO42-, OM, and BC were associated with increases in length of hospital stay of 0.10 (95% CI = 0.02, 0.19), 0.09 (95% CI = 0.02, 0.17), 0.10 (95% CI = 0.03, 0.17), and 0.16 (95% CI = 0.08, 0.23) days. CONCLUSIONS Our findings suggest that ambient SO42-, OM, and BC might be significant risk factors for HF, emphasising the importance of formulating customised guidelines for the chemical constituents of PM and controlling the emissions of the most dangerous components.
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Kong D, Tao Y, Xiao H, Xiong H, Wei W, Cai M. Predicting preterm birth using auto-ML frameworks: a large observational study using electronic inpatient discharge data. Front Pediatr 2024; 12:1330420. [PMID: 38362001 PMCID: PMC10867966 DOI: 10.3389/fped.2024.1330420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Accepted: 01/16/2024] [Indexed: 02/17/2024] Open
Abstract
Background To develop and compare different AutoML frameworks and machine learning models to predict premature birth. Methods The study used a large electronic medical record database to include 715,962 participants who had the principal diagnosis code of childbirth. Three Automatic Machine Learning (AutoML) were used to construct machine learning models including tree-based models, ensembled models, and deep neural networks on the training sample (N = 536,971). The area under the curve (AUC) and training times were used to assess the performance of the prediction models, and feature importance was computed via permutation-shuffling. Results The H2O AutoML framework had the highest median AUC of 0.846, followed by AutoGluon (median AUC: 0.840) and Auto-sklearn (median AUC: 0.820), and the median training time was the lowest for H2O AutoML (0.14 min), followed by AutoGluon (0.16 min) and Auto-sklearn (4.33 min). Among different types of machine learning models, the Gradient Boosting Machines (GBM) or Extreme Gradient Boosting (XGBoost), stacked ensemble, and random forrest models had better predictive performance, with median AUC scores being 0.846, 0.846, and 0.842, respectively. Important features related to preterm birth included premature rupture of membrane (PROM), incompetent cervix, occupation, and preeclampsia. Conclusions Our study highlights the potential of machine learning models in predicting the risk of preterm birth using readily available electronic medical record data, which have significant implications for improving prenatal care and outcomes.
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Affiliation(s)
- Deming Kong
- Wuhan Children’s Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Ye Tao
- Wuhan Children’s Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Haiyan Xiao
- Wuhan Children’s Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Huini Xiong
- Wuhan Children’s Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Weizhong Wei
- Wuhan Children’s Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Miao Cai
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China
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Lin X, Cai M, Tan K, Liu E, Wang X, Song C, Wei J, Lin H, Pan J. Ambient particulate matter and in-hospital case fatality of acute myocardial infarction: A multi-province cross-sectional study in China. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 268:115731. [PMID: 38007949 DOI: 10.1016/j.ecoenv.2023.115731] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 11/18/2023] [Accepted: 11/21/2023] [Indexed: 11/28/2023]
Abstract
The acute myocardial infarction (AMI) outcomes have been extensively linked with ambient particulate matter (PM). However, whether a smaller particle has greater impact and the consequent attributable burden associated with PM of different sizes remain unclear. We conducted a multi-province cross-sectional study among AMI patients using the inpatient discharge datasets from four Chinese provinces (Shanxi, Sichuan, Guangxi, and Guangdong) from 2014 to 2019. Ambient PM exposure for each patient was assessed using the ChinaHighAirPollutants dataset. We employed the mixed-effects logistic regression models to evaluate the association of PM of different sizes (PM1, PM2.5, PM10) on in-hospital case fatality. The potential reducible fractions in in-hospital case fatality were estimated through counterfactual analyses. Of 177,749 participants, 125,501 (70.6 %) were male and the in-hospital case fatality rate was 4.9%. For short-term (7-day average) exposure, the odds ratios (ORs) for PM1, PM2.5, and PM10 (per 10 µg/m3) were 1.052 (95 % confidence interval [CI], 1.032-1.071), 1.026 (95 % CI, 1.014-1.037), and 1.016 (95% CI, 1.008-1.024), respectively. The estimated ORs for long-term exposure (annual average) were 1.303 (95 % CI, 1.252-1.356) for PM1, 1.209 (95 % CI, 1.178-1.241) for PM2.5, 1.157 (95 % CI, 1.134-1.181) for PM10. Short-term exposure to PM1 showed the highest potential reducible fraction (8.5 %, 95 % CI, 5.0-11.7 %), followed by PM2.5 and PM10, while the greatest potential reducible fraction of long-term exposure was observed in PM10 (30.9 %, 95 % CI, 27.2-34.4%), followed by PM2.5 and PM1. In summary, PM with smaller size had a more pronounced impact on in-hospital AMI case fatality, with PM1 exhibiting greater effects than PM2.5 and PM10. Substantial health benefits for AMI patients could be achieved by mitigating ambient PM exposure.
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Affiliation(s)
- Xiaojun Lin
- HEOA Group, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, Ren Min Nan Road, Chengdu, Sichuan 610041, China; Institute for Healthy Cities and West China Research Center for Rural Health Development, Sichuan University, No. 16, Section 3, Ren Min Nan Road, Chengdu, Sichuan 610041, China; West China-PUMC C.C. Chen Institute of Health, Sichuan University, No. 16, Section 3, Ren Min Nan Road, Chengdu, Sichuan 610041, China
| | - Miao Cai
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, No. 74, Zhongshan 2nd road, Yuexiu District, Guangzhou, Guangdong 510080, China
| | - Kun Tan
- Health Information Center of Sichuan Province, No. 39, Wangjiaguai Street, Chengdu, Sichuan 610041, China
| | - Echu Liu
- Department of Health Management and Policy, College for Public Health and Social Justice, Saint Louis University, St. Louis, MO 63103, USA
| | - Xiuli Wang
- HEOA Group, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, Ren Min Nan Road, Chengdu, Sichuan 610041, China; Institute for Healthy Cities and West China Research Center for Rural Health Development, Sichuan University, No. 16, Section 3, Ren Min Nan Road, Chengdu, Sichuan 610041, China; West China-PUMC C.C. Chen Institute of Health, Sichuan University, No. 16, Section 3, Ren Min Nan Road, Chengdu, Sichuan 610041, China
| | - Chao Song
- HEOA Group, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, Ren Min Nan Road, Chengdu, Sichuan 610041, China; Institute for Healthy Cities and West China Research Center for Rural Health Development, Sichuan University, No. 16, Section 3, Ren Min Nan Road, Chengdu, Sichuan 610041, China; West China-PUMC C.C. Chen Institute of Health, Sichuan University, No. 16, Section 3, Ren Min Nan Road, Chengdu, Sichuan 610041, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20740, USA.
| | - Hualiang Lin
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, No. 74, Zhongshan 2nd road, Yuexiu District, Guangzhou, Guangdong 510080, China.
| | - Jay Pan
- HEOA Group, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 16, Section 3, Ren Min Nan Road, Chengdu, Sichuan 610041, China; West China-PUMC C.C. Chen Institute of Health, Sichuan University, No. 16, Section 3, Ren Min Nan Road, Chengdu, Sichuan 610041, China; China Center for South Asian Studies, Sichuan University, No.24 South Section I, Yihuan Road, Chengdu, Sichuan 610065, China.
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Wang H, Matusik M, Wunderlich R, Hanson SE, Babich K, Samad L, Qian AM, McMillin SE, Ye X, Zhang S, Liu Y, Chen X, Li Z, Lin H, Zhu H, Wang X. Short-Term Ambient Air Pollution and Urticaria in Guangzhou, China: Estimating the Association and Population Attributable Fraction. TOXICS 2023; 11:949. [PMID: 38133350 PMCID: PMC10747676 DOI: 10.3390/toxics11120949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 11/03/2023] [Accepted: 11/09/2023] [Indexed: 12/23/2023]
Abstract
Limited evidence is available regarding the association between acute exposure to ambient air pollutants and the risk of urticaria, even though the skin is an organ with direct contact with the external environment. This study utilized generalized additive models to investigate the association between particulate matter with an aerodynamic diameter smaller than 10 μm (PM10) and 2.5 μm (PM2.5), nitrogen dioxide (NO2) and sulfur dioxide (SO2), and daily outpatient visits for urticaria in Guangzhou, China from 2013 to 2017. We also estimated the attributable fraction of urticaria outpatient visits due to air pollution. A total of 216,648 outpatient visits due to urticaria occurred during the study period. All air pollutants were significantly associated with an increased excess risk of urticaria. Each 10 μg/m3 increase in PM2.5, PM10, NO2, and SO2 was associated with an increase of 1.23% (95% CI: 0.42%, 2.06%), 0.88% (95% CI: 0.28%, 1.49%), 3.09% (95% CI: 2.16%, 4.03%), and 2.82% (95% CI: 0.93%, 4.74%) in hospital visits for urticaria at lag05, respectively. It was estimated that 3.77% (95% CI: 1.26%, 6.38%), 1.91% (95% CI: 0.60%, 3.26%), 6.36% (95% CI: 4.38%, 8.41%), and 0.08% (95% CI: 0.03%, 0.14%) of urticaria outpatient visits were attributable to PM2.5, PM10, NO2, and SO2 using the World Health Organization's air quality guideline as the reference. Relatively stronger associations were observed during the cold season. This study indicates that short-term air pollution may play a significant role in outpatient visits for urticaria, and that such relationships could be modified by season.
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Affiliation(s)
- Huanli Wang
- Department of Dermatology, Guangzhou Institute of Dermatology, Guangzhou 510095, China
- Institute of Dermatology, Guangzhou Medical University, Guangzhou 510095, China
| | - Morgan Matusik
- University of New Mexico Hospital, Albuquerque, NM 87106, USA
| | | | - Sarah E. Hanson
- Bureau of Communicable Disease Control and Prevention, Missouri Department of Health and Senior Services, Jefferson City, MO 63103, USA
| | - Kelly Babich
- Connecticut Department of Public Health, Office of Public Health Preparedness and Response, Hartford, CT 06134, USA
| | - Lilianne Samad
- Department of Epidemiology and Biostatistics, College for Public Health and Social Justice, Saint Louis University, Saint Louis, MO 63104, USA
| | - Aaron M. Qian
- Department of Psychology, College of Arts and Sciences, Saint Louis University, Saint Louis, MO 63108, USA
| | | | - Xingdong Ye
- Department of Dermatology, Guangzhou Institute of Dermatology, Guangzhou 510095, China
- Institute of Dermatology, Guangzhou Medical University, Guangzhou 510095, China
| | - Sanquan Zhang
- Department of Dermatology, Guangzhou Institute of Dermatology, Guangzhou 510095, China
- Institute of Dermatology, Guangzhou Medical University, Guangzhou 510095, China
| | - Yumei Liu
- Department of Dermatology, Guangzhou Institute of Dermatology, Guangzhou 510095, China
- Institute of Dermatology, Guangzhou Medical University, Guangzhou 510095, China
| | - Xiaoyin Chen
- Department of Dermatology, Guangzhou Institute of Dermatology, Guangzhou 510095, China
- Institute of Dermatology, Guangzhou Medical University, Guangzhou 510095, China
| | - Zhenjie Li
- Department of Dermatology, Guangzhou Institute of Dermatology, Guangzhou 510095, China
- Institute of Dermatology, Guangzhou Medical University, Guangzhou 510095, China
| | - Hualiang Lin
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Huilan Zhu
- Department of Dermatology, Guangzhou Institute of Dermatology, Guangzhou 510095, China
- Institute of Dermatology, Guangzhou Medical University, Guangzhou 510095, China
| | - Xiaojie Wang
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
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Xu X, Zhang W, Shi X, Su Z, Cheng W, Wei Y, Ma H, Li T, Wang Z. China's air quality improvement strategy may already be having a positive effect: evidence based on health risk assessment. Front Public Health 2023; 11:1250572. [PMID: 37927881 PMCID: PMC10624126 DOI: 10.3389/fpubh.2023.1250572] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 09/15/2023] [Indexed: 11/07/2023] Open
Abstract
Aiming to investigate the health risk impact of PM2.5 pollution on a heavily populated province of China. The exposure response function was used to assess the health risk of PM2.5 pollution. Results shows that the total number of premature deaths and diseases related to PM2.5 pollution in Shandong might reach 159.8 thousand people based on the new WHO (2021) standards. The health effects of PM2.5 pollution were more severe in men than in women. Five of the 16 cities in Shandong had higher health risks caused by PM2.5 pollution, including LinYi, HeZe, JiNing, JiNan, and WeiFang. PM2.5 pollution resulted in nearly 7.4 billions dollars in healthy economic cost, which accounted for 0.57% of GDP in Shandong in 2021. HeZe, LiaoCheng, ZaoZhuang, and LinYi were the cities where the health economic loss was more than 1% of the local GDP, accounted for 1.30, 1.26, 1.08, and 1.04%. Although the more rigorous assessment criteria, the baseline concentration was lowered by 30 μg/m3 compared to our previous study, there was no significant increase in health risks and economic losses. China's air quality improvement strategy may already be having a positive effect.
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Affiliation(s)
- Xianmang Xu
- Heze Branch, Biological Engineering Technology Innovation Center of Shandong Province, Qilu University of Technology (Shandong Academy of Sciences), Heze, China
- Shandong Analysis and Test Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai, China
| | - Wen Zhang
- Department of Clinical Medicine, Heze Medical College, Heze, China
| | - Xiaofeng Shi
- Department of Clinical Medicine, Heze Medical College, Heze, China
| | - Zhi Su
- Heze Ecological Environment Monitoring Center of Shandong Province, Heze, China
| | - Wei Cheng
- Heze Branch, Biological Engineering Technology Innovation Center of Shandong Province, Qilu University of Technology (Shandong Academy of Sciences), Heze, China
| | - Yinuo Wei
- Heze Branch, Biological Engineering Technology Innovation Center of Shandong Province, Qilu University of Technology (Shandong Academy of Sciences), Heze, China
| | - He Ma
- Heze Branch, Biological Engineering Technology Innovation Center of Shandong Province, Qilu University of Technology (Shandong Academy of Sciences), Heze, China
| | - Tinglong Li
- Heze Branch, Biological Engineering Technology Innovation Center of Shandong Province, Qilu University of Technology (Shandong Academy of Sciences), Heze, China
| | - Zhenhua Wang
- Shandong Analysis and Test Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China
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10
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Zhang J, Chen G, Xia H, Wang X, Wang C, Cai M, Gao Y, Lip GYH, Lin H. Associations of Life's Essential 8 and fine particulate matter pollution with the incidence of atrial fibrillation. JOURNAL OF HAZARDOUS MATERIALS 2023; 459:132114. [PMID: 37494795 DOI: 10.1016/j.jhazmat.2023.132114] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2023] [Revised: 07/07/2023] [Accepted: 07/20/2023] [Indexed: 07/28/2023]
Abstract
Both unhealthy lifestyle factors and ambient air pollution have been closely linked with the risk of atrial fibrillation (AF). We retrieved 250,898 participants without AF at baseline from UK Biobank. LE8 was determined by 8 metrics, and was characterized as low, moderate and high cardiovascular health (CVH). Exposure to PM2.5 was estimated at the geocoded residential address of each participant. During a median follow-up of 12.46 years, we identified 14,743 (5.9%) incident AF cases. Participants with moderate and high CVH showed a decreased risk of incident AF compared to those with low CVH. Of the LE8 metrics, ideal body mass index (BMI) and blood pressure (BP) were associated with a decrease of 11.57% and 11.46% AF cases. High PM2.5 exposure was associated with an 8% increased risk of AF as compared to low PM2.5 exposure. Compared with those who had low CVH and high PM2.5 exposure, participants with a high CVH and low PM2.5 exposure had the lower AF incidence. Our study found higher CVH is protective, while higher PM2.5 might be one risk factor of AF. Adherence to the LE8 guidelines may help reduce the incidence of AF, especially in those with lower PM2.5 exposure.
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Affiliation(s)
- Junguo Zhang
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Ge Chen
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Hui Xia
- Center for Health Care, Longhua District, Shenzhen, China
| | - Xiaojie Wang
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - ChongJian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Miao Cai
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Yanhui Gao
- Department of Medical Statistics, School of Basic Medicine and Public Health, Jinan University, Guangzhou, China; Department of Epidemiology and Health Statistics, School of Public Health, Guangdong Pharmaceutical University, Guangzhou, China
| | - Gregory Y H Lip
- Liverpool Centre for Cardiovascular Science at University of Liverpool, Liverpool John Moores University and Liverpool Heart & Chest Hospital, Liverpool, United Kingdom; Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
| | - Hualiang Lin
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
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11
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Rios FJ, Montezano AC, Camargo LL, Touyz RM. Impact of Environmental Factors on Hypertension and Associated Cardiovascular Disease. Can J Cardiol 2023; 39:1229-1243. [PMID: 37422258 DOI: 10.1016/j.cjca.2023.07.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 06/24/2023] [Accepted: 07/02/2023] [Indexed: 07/10/2023] Open
Abstract
Hypertension is the primary cause of cardiovascular diseases and is responsible for nearly 9 million deaths worldwide annually. Increasing evidence indicates that in addition to pathophysiologic processes, numerous environmental factors, such as geographic location, lifestyle choices, socioeconomic status, and cultural practices, influence the risk, progression, and severity of hypertension, even in the absence of genetic risk factors. In this review, we discuss the impact of some environmental determinants on hypertension. We focus on clinical data from large population studies and discuss some potential molecular and cellular mechanisms. We highlight how these environmental determinants are interconnected, as small changes in one factor might affect others, and further affect cardiovascular health. In addition, we discuss the crucial impact of socioeconomic factors and how these determinants influence diverse communities with economic disparities. Finally, we address opportunities and challenges for new research to address gaps in knowledge on understanding molecular mechanisms whereby environmental factors influence development of hypertension and associated cardiovascular disease.
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Affiliation(s)
- Francisco J Rios
- Research Institute of the McGill University Health Centre, Montréal, Québec, Canada.
| | - Augusto C Montezano
- Research Institute of the McGill University Health Centre, Montréal, Québec, Canada
| | - Livia L Camargo
- Research Institute of the McGill University Health Centre, Montréal, Québec, Canada
| | - Rhian M Touyz
- Research Institute of the McGill University Health Centre, Montréal, Québec, Canada.
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12
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Li X, Abdullah LC, Sobri S, Syazarudin Md Said M, Aslina Hussain S, Poh Aun T, Hu J. Long-term spatiotemporal evolution and coordinated control of air pollutants in a typical mega-mountain city of Cheng-Yu region under the "dual carbon" goal. JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION (1995) 2023; 73:649-678. [PMID: 37449903 DOI: 10.1080/10962247.2023.2232744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 05/31/2023] [Accepted: 06/20/2023] [Indexed: 07/18/2023]
Abstract
Clarifying the spatiotemporal distribution and impact mechanism of pollution is the prerequisite for megacities to formulate relevant air pollution prevention and control measures and achieve carbon neutrality goals. Chongqing is one of the dual-core key megacities in Cheng-Yu region and as a typical mountain-city in China, environmental problems are complex and sensitive. This research aims to investigate the exceeding standard levels and spatio-temporal evolution of criteria pollutants between 2014 and 2020. The results indicated that PM10, PM2.5, CO and SO2 were decreased significantly by 45.91%, 52.86%, 38.89% and 66.67%, respectively. Conversely, the concentration of pollutant O3 present a fluctuating growth and found a "seesaw" phenomenon between it and PM. Furthermore, PM and O3 are highest in winter and summer, respectively. SO2, NO2, CO, and PM showed a "U-shaped", and O3 showed an inverted "U-shaped" seasonal variation. PM and O3 concentrations are still far behind the WHO, 2021AQGs standards. Significant spatial heterogeneity was observed in air pollution distribution. These results are of great significance for Chongqing to achieve "double control and double reduction" of PM2.5 and O3 pollution, and formulate a regional carbon peaking roadmap under climate coordination. Besides, it can provide an important platform for exploring air pollution in typical terrain around the world and provide references for related epidemiological research.Implications: Chongqing is one of the dual-core key megacities in Cheng-Yu region and as a typical mountain city, environmental problems are complex and sensitive. Under the background of the "14th Five-Year Plan", the construction of the "Cheng-Yu Dual-City Economic Circle" and the "Dual-Carbon" goal, this article comprehensively discussed the annual and seasonal excess levels and spatiotemporal evolution of pollutants under the multiple policy and the newest international standards (WHO,2021AQG) backgrounds from 2014 to 2020 in Chongqing. Furthermore, suggestions and measures related to the collaborative management of pollutants were discussed. Finally, limitations and recommendations were also put forward.Clarifying the spatiotemporal distribution and impact mechanism of pollution is the prerequisite for cities to formulate relevant air pollution control measures and achieve carbon neutrality goals. This study is of great significance for Chongqing to achieve "double control and double reduction" of PM2.5 and O3 pollution, study and formulate a regional carbon peaking roadmap under climate coordination and an action plan for sustained improvement of air quality.In addition, this research can advanced our understanding of air pollution in complex terrain. Furthermore, it also promote the construction of the China national strategic Cheng-Yu economic circle and build a beautiful west. Moreover, it provides scientific insights for local policymakers to guide smart urban planning, industrial layout, energy structure, and transportation planning to improve air quality throughout the Cheng-Yu region. Finally, this is also conducive to future scientific research in other regions of China, and even megacities with complex terrain in the world.
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Affiliation(s)
- Xiaoju Li
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, Serdang, Malaysia
- Department of Resource and Environment, Xichang University, Xichang City, Sichuan Province, China
| | - Luqman Chuah Abdullah
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, Serdang, Malaysia
| | - Shafreeza Sobri
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, Serdang, Malaysia
| | - Mohamad Syazarudin Md Said
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, Serdang, Malaysia
| | - Siti Aslina Hussain
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, Serdang, Malaysia
| | - Tan Poh Aun
- SOx NOx Asia Sdn Bhd, Subang Jaya, Selangor, Malaysia
| | - Jinzhao Hu
- Department of Resource and Environment, Xichang University, Xichang City, Sichuan Province, China
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13
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Tian W, Zhu G, Xiao W, Gao B, Lu W, Wang Y. Stroke burden and attributable risk factors in China, 1990-2019. Front Neurol 2023; 14:1193056. [PMID: 37292127 PMCID: PMC10245554 DOI: 10.3389/fneur.2023.1193056] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 05/03/2023] [Indexed: 06/10/2023] Open
Abstract
Background and purpose Understanding the temporal trends of stroke burden and its attributable risk factors are essential for targeted prevention strategies. We aimed to describe the temporal trends and attributable risk factors of stroke in China. Methods Data on the stroke burden [incidence, prevalence, mortality, and disability-adjusted life years (DALYs)] and the population-attributable fraction for stroke risk factors from 1990 to 2019 were obtained from the Global Burden of Disease Study 2019 (GBD 2019). We analyzed trends in the burden of stroke and its attributable risk factors from 1990 to 2019, and the characteristics of stroke-attributable risk factors by sex, age group, and stroke subtype. Results From 1990 to 2019, the age-standardized incidence, mortality, and DALY rates for total stroke decreased by 9.3% (3.3, 15.5), 39.8% (28.6, 50.7), and 41.6% (30.7, 50.9) respectively. The corresponding indicators all decreased for intracerebral hemorrhage and subarachnoid hemorrhage. The age-standardized incidence rate of ischemic stroke increased by 39.5% (33.5 to 46.2) for male patients and by 31.4% (24.7 to 37.7) for female patients, and the age-standardized mortality and DALY rates remained almost unchanged. The three leading stroke risk factors were high systolic blood pressure, ambient particulate matter pollution, and smoking. High systolic blood pressure has remained the leading risk factor since 1990. The attributable risk of ambient particulate matter pollution shows a clear upward trend. Smoking and alcohol consumption were important risk factors for men. Conclusion This study reinforced the findings of an increased stroke burden in China. Precise stroke prevention strategies are needed to reduce the disease burden of stroke.
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Affiliation(s)
- Wenxin Tian
- School of Public Health, Department of Epidemiology and Health Statistics, Tianjin Medical University, Heping District, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Heping District, Tianjin, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin Medical University, Heping District, Tianjin, China
| | - Guanghan Zhu
- School of Public Health, Department of Epidemiology and Health Statistics, Tianjin Medical University, Heping District, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Heping District, Tianjin, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin Medical University, Heping District, Tianjin, China
| | - Wenbo Xiao
- School of Public Health, Department of Epidemiology and Health Statistics, Tianjin Medical University, Heping District, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Heping District, Tianjin, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin Medical University, Heping District, Tianjin, China
| | - Bei Gao
- School of Public Health, Department of Epidemiology and Health Statistics, Tianjin Medical University, Heping District, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Heping District, Tianjin, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin Medical University, Heping District, Tianjin, China
| | - Wenli Lu
- School of Public Health, Department of Epidemiology and Health Statistics, Tianjin Medical University, Heping District, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Heping District, Tianjin, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin Medical University, Heping District, Tianjin, China
| | - Yuan Wang
- School of Public Health, Department of Epidemiology and Health Statistics, Tianjin Medical University, Heping District, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin Medical University, Heping District, Tianjin, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin Medical University, Heping District, Tianjin, China
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14
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Li M, Edgell RC, Wei J, Li H, Qian ZM, Feng J, Tian F, Wang X, Xin Q, Cai M, Lin H. Air pollution and stroke hospitalization in the Beibu Gulf Region of China: A case-crossover analysis. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 255:114814. [PMID: 36965278 PMCID: PMC10107400 DOI: 10.1016/j.ecoenv.2023.114814] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 03/15/2023] [Accepted: 03/17/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND The relationship between air pollution and stroke has been extensively studied, however, the evidence regarding the association between air pollution and hospitalization due to stroke and its subtypes in coastal areas of China is limited. OBJECTIVE To estimate the associations between air pollution and hospitalizations of stroke and its subtypes in the Beibu Gulf Region of China. METHODS We conducted a time-stratified case-crossover study in 15 cities in Beibu Gulf Region in China from 2013 to 2016. Exposures to PM1, PM2.5, PM10, SO2, NO2, O3, and CO on the case and control days were assessed at residential addresses using bilinear interpolation. Conditional logistic regressions were constructed to estimate city-specific associations adjusting for meteorological factors and public holidays. Meta-analysis was further conducted to pool all city-level estimates. RESULTS There were 271,394 case days and 922,305 control days. The odds ratios (ORs) for stroke hospitalizations associated with each interquartile range (IQR) increase in 2-day averages of SO2 (IQR: 10.8 µg/m3), NO2 (IQR: 11.2 µg/m3), and PM10 (IQR: 37 µg/m3) were 1.047 (95 % CI [confidence interval]: 1.015-1.080), 1.040 (95 % CI: 1.027-1.053), and 1.018 (95 % CI: 1.004-1.033), respectively. The associations with hospitalizations of ischemic stroke were significant for all seven pollutants, while the association with hemorrhagic stroke was significant only for CO. The associations of SO2, NO2, and O3 with stroke hospitalization were significantly stronger in the cool season. CONCLUSIONS Short-term increase in SO2, NO2, and PM10 might be important triggers of stroke hospitalization. All seven air pollutants were associated with ischemic stroke hospitalization, while only CO was associated with hemorrhagic stroke hospitalization. These results should be considered in public health policy.
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Affiliation(s)
- Meijun Li
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Randall C Edgell
- Department of Neurology, School of Medicine, Saint Louis University, 1008 South Spring, Saint Louis, MO 63110, USA
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park 20740, USA
| | - Haopeng Li
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Zhengmin Min Qian
- Department of Epidemiology and Biostatistics, College for Public Health & Social Justice, Saint Louis University, 3545 Lafayette Avenue, Saint Louis, MO 63104, USA
| | - Jin Feng
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Fei Tian
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Xiaojie Wang
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Qinghua Xin
- Shandong Academy of Occupational Health and Occupational Medicine, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan 271016, China.
| | - Miao Cai
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
| | - Hualiang Lin
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
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15
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Cai M, Wei J, Zhang S, Liu W, Wang L, Qian Z, Lin H, Liu E, McMillin SE, Cao Y, Yin P. Short-term air pollution exposure associated with death from kidney diseases: a nationwide time-stratified case-crossover study in China from 2015 to 2019. BMC Med 2023; 21:32. [PMID: 36694165 PMCID: PMC9875429 DOI: 10.1186/s12916-023-02734-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Accepted: 01/11/2023] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND Long-term exposure to air pollution has been associated with the onset and progression of kidney diseases, but the association between short-term exposure to air pollution and mortality of kidney diseases has not yet been reported. METHODS A nationally representative sample of 101,919 deaths from kidney diseases was collected from the Chinese Center for Disease Control and Prevention from 2015 to 2019. A time-stratified case-crossover study was applied to determine the associations. Satellite-based estimates of air pollution were assigned to each case and control day using a bilinear interpolation approach and geo-coded residential addresses. Conditional logistic regression models were constructed to estimate the associations adjusting for nonlinear splines of temperature and relative humidity. RESULTS Each 10 µg/m3 increment in lag 0-1 mean concentrations of air pollutants was associated with a percent increase in death from kidney disease: 1.33% (95% confidence interval [CI]: 0.57% to 2.1%) for PM1, 0.49% (95% CI: 0.10% to 0.88%) for PM2.5, 0.32% (95% CI: 0.08% to 0.57%) for PM10, 1.26% (95% CI: 0.29% to 2.24%) for NO2, and 2.9% (95% CI: 1.68% to 4.15%) for SO2. CONCLUSIONS: Our study suggests that short-term exposure to ambient PM1, PM2.5, PM10, NO2, and SO2 might be important environmental risk factors for death due to kidney diseases in China.
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Affiliation(s)
- Miao Cai
- Department of Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, Guangdong, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, 20740, USA
| | - Shiyu Zhang
- Department of Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, Guangdong, China
| | - Wei Liu
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100050, China
| | - Lijun Wang
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100050, China
| | - Zhengmin Qian
- Department of Epidemiology and Biostatistics, College for Public Health and Social Justice, Saint Louis University, St. Louis, 63103, USA
| | - Hualiang Lin
- Department of Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, Guangdong, China
| | - Echu Liu
- Department of Health Management and Policy, College for Public Health and Social Justice, Saint Louis University, St. Louis, MO, 63103, USA
| | - Stephen Edward McMillin
- School of Social Work, College for Public Health and Social Justice, Saint Louis University, St. Louis, MO, 63103, USA
| | - Yu Cao
- Information Center, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
| | - Peng Yin
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100050, China.
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16
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Guo L, Liu Y, Xue T, Liang L, Nima Y, Yang Y, Li Q, Zhang Q. Association between sedentary time and metabolic syndrome: A cross-sectional study among Chinese Garze Tibetans. Front Public Health 2022; 10:1009764. [PMID: 36466463 PMCID: PMC9713937 DOI: 10.3389/fpubh.2022.1009764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 10/31/2022] [Indexed: 11/18/2022] Open
Abstract
Background Chinese Tibetans have long hours of sitting without much physical activity given their religious behavior, raising potential harmful health hazards. However, the relationship between sedentary time and metabolic syndrome (MetS) has not been investigated in Chinese Tibetans. Methods From Jan 2021 to Jun 2022, residents in Garze Tibetan Autonomous Prefecture in Southwest China's Sichuan province were recruited using a multi-stage, stratified, random-cluster sampling strategy. MetS were ascertained using definition proposed by the International Diabetes Federation. Associations between sedentary time and the prevalence of MetS in the total sample and by age and sex were estimated using logistic regression models. Results Among 971 Chinese Tibetan participants (mean age 41.1 years and 73.8% female), 319 (32.9%) were diagnosed as having MetS. We found positive associations of sedentary time over 11 h per day with the prevalence of MetS in crude (OR: 1.23; 95% CI: 1.12-1.36, p < 0.001), age and sex adjusted (OR: 1.18; 95% CI: 1.08-1.29, p < 0.001), and fully adjusted (OR: 1.17; 95% CI: 1.08-1.29, p < 0.001) models, compared to those who had <8 h of sedentary time per day. Sensitivity analyses suggest consistent positive association between sedentary time and each metric of MetS. Conclusions Sedentary time longer than 11 h per day is significantly associated with increased risk of MetS, suggesting that polices to advocate health education may alleviate the health burden of MetS among Tibetans in China.
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Affiliation(s)
- Lei Guo
- Guangdong Second Provincial General Hospital, Guangzhou, China,*Correspondence: Lei Guo
| | - Yixuan Liu
- Guangdong Second Provincial General Hospital, Guangzhou, China,Yixuan Liu
| | - Tingting Xue
- Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Liang Liang
- Garze Tibetan Autonomous Prefecture People's Hospital, Kangding, China
| | - Yongcuo Nima
- Garze Tibetan Autonomous Prefecture People's Hospital, Kangding, China
| | - Yang Yang
- Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Qun Li
- Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Qiushi Zhang
- Guangdong Second Provincial General Hospital, Guangzhou, China,Qiushi Zhang
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