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Chen G, Guo Y, Yue X, Xu R, Yu W, Ye T, Tong S, Gasparrini A, Bell ML, Armstrong B, Schwartz J, Jaakkola JJK, Lavigne E, Saldiva PHN, Kan H, Royé D, Urban A, Vicedo-Cabrera AM, Tobias A, Forsberg B, Sera F, Lei Y, Abramson MJ, Li S. All-cause, cardiovascular, and respiratory mortality and wildfire-related ozone: a multicountry two-stage time series analysis. Lancet Planet Health 2024; 8:e452-e462. [PMID: 38969473 DOI: 10.1016/s2542-5196(24)00117-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Revised: 05/12/2024] [Accepted: 05/13/2024] [Indexed: 07/07/2024]
Abstract
BACKGROUND Wildfire activity is an important source of tropospheric ozone (O3) pollution. However, no study to date has systematically examined the associations of wildfire-related O3 exposure with mortality globally. METHODS We did a multicountry two-stage time series analysis. From the Multi-City Multi-Country (MCC) Collaborative Research Network, data on daily all-cause, cardiovascular, and respiratory deaths were obtained from 749 locations in 43 countries or areas, representing overlapping periods from Jan 1, 2000, to Dec 31, 2016. We estimated the daily concentration of wildfire-related O3 in study locations using a chemical transport model, and then calibrated and downscaled O3 estimates to a resolution of 0·25° × 0·25° (approximately 28 km2 at the equator). Using a random-effects meta-analysis, we examined the associations of short-term wildfire-related O3 exposure (lag period of 0-2 days) with daily mortality, first at the location level and then pooled at the country, regional, and global levels. Annual excess mortality fraction in each location attributable to wildfire-related O3 was calculated with pooled effect estimates and used to obtain excess mortality fractions at country, regional, and global levels. FINDINGS Between 2000 and 2016, the highest maximum daily wildfire-related O3 concentrations (≥30 μg/m3) were observed in locations in South America, central America, and southeastern Asia, and the country of South Africa. Across all locations, an increase of 1 μg/m3 in the mean daily concentration of wildfire-related O3 during lag 0-2 days was associated with increases of 0·55% (95% CI 0·29 to 0·80) in daily all-cause mortality, 0·44% (-0·10 to 0·99) in daily cardiovascular mortality, and 0·82% (0·18 to 1·47) in daily respiratory mortality. The associations of daily mortality rates with wildfire-related O3 exposure showed substantial geographical heterogeneity at the country and regional levels. Across all locations, estimated annual excess mortality fractions of 0·58% (95% CI 0·31 to 0·85; 31 606 deaths [95% CI 17 038 to 46 027]) for all-cause mortality, 0·41% (-0·10 to 0·91; 5249 [-1244 to 11 620]) for cardiovascular mortality, and 0·86% (0·18 to 1·51; 4657 [999 to 8206]) for respiratory mortality were attributable to short-term exposure to wildfire-related O3. INTERPRETATION In this study, we observed an increase in all-cause and respiratory mortality associated with short-term wildfire-related O3 exposure. Effective risk and smoke management strategies should be implemented to protect the public from the impacts of wildfires. FUNDING Australian Research Council and the Australian National Health and Medical Research Council.
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Affiliation(s)
- Gongbo Chen
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Yuming Guo
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
| | - Xu Yue
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, China
| | - Rongbin Xu
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Wenhua Yu
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Tingting Ye
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Shilu Tong
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; School of Public Health and Social Work, Queensland University of Technology, Brisbane, QLD, Australia
| | - Antonio Gasparrini
- Department of Public Health Environments and Society, London School of Hygiene & Tropical Medicine, London, UK
| | - Michelle L Bell
- School of the Environment, Yale University, New Haven, CT, USA; School of Health Policy and Management, College of Health Sciences, Korea University, Seoul, South Korea
| | - Ben Armstrong
- Department of Public Health Environments and Society, London School of Hygiene & Tropical Medicine, London, UK
| | - Joel Schwartz
- Department of Environmental Health, Harvard T H Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Jouni J K Jaakkola
- Center for Environmental and Respiratory Health Research, University of Oulu, Oulu, Finland; Medical Research Center Oulu, OuluUniversity Hospital and University of Oulu, Oulu, Finland; Finnish Meteorological Institute, Helsinki, Finland
| | - Eric Lavigne
- School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada; Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, Canada
| | | | - Haidong Kan
- Department of Environmental Health, School of Public Health, Fudan University, Shanghai, China
| | - Dominic Royé
- Department of Geography, University of Santiago de Compostela, Santiago de Compostela, Spain; CIBER Epidemiology and Public Health, Madrid, Spain
| | - Aleš Urban
- Institute of Atmospheric Physics, Academy of Sciences of the Czech Republic, Prague, Czech Republic; Faculty of Environmental Sciences, Czech University of Life Sciences, Prague, Czech Republic
| | - Ana Maria Vicedo-Cabrera
- Institute of Social and Preventive Medicine and Oeschger Center for Climate Change Research, University of Bern, Bern, Switzerland
| | - Aurelio Tobias
- Institute of Environmental Assessment and Water Research, Spanish Council for Scientific Research, Barcelona, Spain; School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan
| | - Bertil Forsberg
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Francesco Sera
- Department of Statistics, Computer Science and Applications "G Parenti", University of Florence, Florence, Italy
| | - Yadong Lei
- State Key Laboratory of Severe Weather and Key Laboratory of Atmospheric Chemistry of China Meteorological Administration, Chinese Academy of Meteorological Sciences, Beijing, China
| | - Michael J Abramson
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Shanshan Li
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
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Zheng XY, Guo SJ, Hu JX, Meng RL, Xu YJ, Lv YH, Wang Y, Xiao N, Li C, Xu XJ, Zhao DJ, Zhou HY, He JH, Tan XM, Wei J, Lin LF, Guan WJ. Long-term associations of PM 1 versus PM 2.5 and PM 10 with asthma and asthma-related respiratory symptoms in the middle-aged and elderly population. ERJ Open Res 2024; 10:00972-2023. [PMID: 38957167 PMCID: PMC11215765 DOI: 10.1183/23120541.00972-2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 02/25/2024] [Indexed: 07/04/2024] Open
Abstract
Background Few studies have compared the associations between long-term exposures to particulate matters (aerodynamic diameter ≤1, ≤2.5 and ≤10 µm: PM1, PM2.5 and PM10, respectively) and asthma and asthma-related respiratory symptoms. The objective of the present study was to compare the strength of the aforementioned associations in middle-aged and elderly adults. Methods We calculated the mean 722-day personal exposure estimates of PM1, PM2.5 and PM10 at 1 km×1 km spatial resolution between 2013 and 2019 at individual levels from China High Air Pollutants (CHAP) datasets. Using logistic regression models, we presented the associations as odds ratios and 95% confidence intervals, for each interquartile range (IQR) increase in PM1/PM2.5/PM10 concentration. Asthma denoted a self-reported history of physician-diagnosed asthma or wheezing in the preceding 12 months. Results We included 7371 participants in COPD surveillance from Guangdong, China. Each IQR increase in PM1, PM2.5 and PM10 was associated with a greater odds (OR (95% CI)) of asthma (PM1: 1.22 (1.02-1.45); PM2.5: 1.24 (1.04-1.48); PM10: 1.30 (1.07-1.57)), wheeze (PM1: 1.27 (1.11-1.44); PM2.5: 1.30 (1.14-1.48); PM10: 1.34 (1.17-1.55)), persistent cough (PM1: 1.33 (1.06-1.66); PM2.5: 1.36 (1.09-1.71); PM10: 1.31 (1.02-1.68)) and dyspnoea (PM1: 2.10 (1.84-2.41); PM2.5: 2.17 (1.90-2.48); PM10: 2.29 (1.96-2.66)). Sensitivity analysis results were robust after excluding individuals with a family history of allergy. Associations of PM1, PM2.5 and PM10 with asthma and asthma-related respiratory symptoms were slightly stronger in males. Conclusion Long-term exposure to PM is associated with increased risks of asthma and asthma-related respiratory symptoms.
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Affiliation(s)
- Xue-yan Zheng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
- Xue-yan Zheng, Shu-jun Guo and Jian-xiong Hu contributed equally to this article as joint first authors
| | - Shu-jun Guo
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Department of Respiratory and Critical Care Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Xue-yan Zheng, Shu-jun Guo and Jian-xiong Hu contributed equally to this article as joint first authors
| | - Jian-xiong Hu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
- Xue-yan Zheng, Shu-jun Guo and Jian-xiong Hu contributed equally to this article as joint first authors
| | - Rui-lin Meng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Yan-jun Xu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Yun-hong Lv
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Ye Wang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Ni Xiao
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Chuan Li
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Xiao-jun Xu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - De-jian Zhao
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Hong-ye Zhou
- Department of Epidemiology and Biostatistics, School of Public Health, Guangdong Pharmaceutical University, Guangzhou, China
| | - Jia-hui He
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Department of Respiratory and Critical Care Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Xiao-min Tan
- Department of Epidemiology and Biostatistics, School of Public Health, Guangdong Pharmaceutical University, Guangzhou, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA
| | - Li-feng Lin
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
- School of Public Health, Southern Medical University, Guangzhou, China
- Li-feng Lin and Wei-jie Guan contributed equally to this article as lead authors and supervised the work
| | - Wei-jie Guan
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Department of Respiratory and Critical Care Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Thoracic Surgery, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Guangzhou National Laboratory, Guangzhou, China
- Li-feng Lin and Wei-jie Guan contributed equally to this article as lead authors and supervised the work
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Liang W, Li R, Chen G, Ma H, Han A, Hu Q, Xie N, Wei J, Shen H, Wang X, Xiang H. Long-term exposure to ambient particulate matter is associated with prognosis in people living with HIV/AIDS: Evidence from a longitudinal study. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 928:172453. [PMID: 38641108 DOI: 10.1016/j.scitotenv.2024.172453] [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: 12/04/2023] [Revised: 02/24/2024] [Accepted: 04/11/2024] [Indexed: 04/21/2024]
Abstract
BACKGROUND Evidence on the association between particulate matter (PM) exposure and prognosis in people living with HIV/AIDS (PWHA) is scarce. We aim to investigate the associations of long-term exposure to PM with AIDS-related deaths and complications. METHODS We collected follow-up information on 7444 PWHAs from 2000 to 2021 from the HIV/AIDS Comprehensive Response Information Management System of the Wuhan Center for Disease Control and Prevention. The AIDS-related deaths and complications were assessed by physicians every 3 to 6 months, and the monthly average PM concentrations for each PWHA were extracted from the China High Air Pollutants dataset. We employed time-varying Cox regression models to evaluate the associations of the average cumulative PM exposure concentrations with AIDS-related deaths and complications, as well as the mediating effects of AIDS-related complications in PM-induced AIDS-related deaths. RESULTS For each 1 μg/m3 increase in PM1, PM2.5, and PM10, the adjusted hazard ratios (HRs) for AIDS-related deaths were 1.021 (1.009, 1.033), 1.012 (1.005, 1.020), and 1.010 (1.005, 1.015), respectively; and the HRs for AIDS-related complications were 1.049 (1.034, 1.064), 1.029 (1.020, 1.038), and 1.031 (1.024, 1.037), respectively. AIDS-related complications mediated 18.38 % and 18.68 % of the association of exposure to PM1 and PM2.5 with AIDS-related deaths, respectively. The association of PM exposure with AIDS-related deaths was more significant in older PWHA. Meanwhile, the association between PM exposure and AIDS-related complications was stronger in PWHA with a BMI ≥ 24 kg/m2. CONCLUSION Long-term exposure to PM is positively associated with AIDS-related deaths and complications, and AIDS-related complications have mediating effects in PM-induced AIDS-related deaths. Our evidence emphasizes that enhanced protection against PM exposure for PWHAs is an additional mitigation strategy to reduce AIDS-related deaths and complications.
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Affiliation(s)
- Wei Liang
- Department of Global Health, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan 430071, China
| | - Ruihan Li
- Department of Global Health, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan 430071, China
| | - Gongbo Chen
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Hongfei Ma
- Wuhan Center for Disease Control and Prevention, 288# Machang Road, Wuhan 430024, China
| | - Aojing Han
- Department of Global Health, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan 430071, China
| | - Qilin Hu
- Department of Global Health, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan 430071, China
| | - Nianhua Xie
- Wuhan Center for Disease Control and Prevention, 288# Machang Road, Wuhan 430024, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20742, United States
| | - Huanfeng Shen
- School of Resource and Environmental Science, Wuhan University, 115# Donghu Road, Wuhan 430071, China
| | - Xia Wang
- Wuhan Center for Disease Control and Prevention, 288# Machang Road, Wuhan 430024, China.
| | - Hao Xiang
- Department of Global Health, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan 430071, China; Global Health Institute, School of Public Health, Wuhan University, 115# Donghu Road, Wuhan 430071, China.
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Xu J, Chen Y, Lu F, Chen L, Dong Z. The Association between Short-Term Exposure to PM 1 and Daily Hospital Admission and Related Expenditures in Beijing. TOXICS 2024; 12:393. [PMID: 38922073 PMCID: PMC11209456 DOI: 10.3390/toxics12060393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Revised: 05/16/2024] [Accepted: 05/18/2024] [Indexed: 06/27/2024]
Abstract
Ambient particulate matter (PM) pollution is a leading environmental health threat worldwide. PM with an aerodynamic diameter ≤ 1.0 μm, also known as PM1, has been implicated in the morbidity and mortality of several cardiorespiratory and cerebrovascular diseases. However, previous studies have mostly focused on analyzing fine PM (PM2.5) associated with disease metrics, such as emergency department visits and mortality, rather than ultrafine PM, including PM1. This study aimed to evaluate the association between short-term PM1 exposure and hospital admissions (HAs) for all-cause diseases, chronic obstructive pulmonary disease (COPD), and respiratory infections (RIs), as well as the associated expenditures, using Beijing as a case study. Here, based on air pollution and hospital admission data in Beijing from 2015 to 2017, we performed a time-series analysis and meta-analysis. It was found that a 10 μg/m3 increase in the PM1 concentration significantly increased all-cause disease HAs by 0.07% (95% Confidence Interval (CI): [0, 0.14%]) in Beijing between 2015 and 2017, while the COPD and RI-related HAs were not significantly associated with short-term PM1 exposure. Meanwhile, we estimated the attributable number of HAs and hospital expenditures related to all-cause diseases. This study revealed that an average of 6644 (95% CI: [351, 12,917]) cases of HAs were attributable to ambient PM1, which was estimated to be associated with a 106 million CNY increase in hospital expenditure annually (95% CI: [5.6, 207]), accounting for 0.32% (95% CI: [0.02, 0.62%]) of the annual total expenses. The findings reported here highlight the underlying impact of ambient PM pollution on health risks and economic burden to society and indicate the need for further policy actions on public health.
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Affiliation(s)
- Jingwen Xu
- School of Cancer and Pharmaceutical Sciences, Faculty of Life Sciences and Medicine, King’s College London, London SE1 1UL, UK
| | - Yan Chen
- Ganzhou People’s Hospital, Ganzhou 341000, China
| | - Feng Lu
- Beijing Municipal Health Big Data and Policy Research Center, Beijing 100034, China
| | - Lili Chen
- School of Public Health, Southeast University, Nanjing 210009, China
| | - Zhaomin Dong
- School of Materials Science and Engineering, Beihang University, Beijing 100191, China
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Zhang Y, Chen S, Wei J, Jiang J, Lin X, Wang Y, Hao C, Wu W, Yuan Z, Sun J, Wang H, Du Z, Zhang W, Hao Y. Long-term PM 1 exposure and hypertension hospitalization: A causal inference study on a large community-based cohort in South China. Sci Bull (Beijing) 2024; 69:1313-1322. [PMID: 38556396 DOI: 10.1016/j.scib.2024.03.028] [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: 09/28/2023] [Revised: 12/11/2023] [Accepted: 01/26/2024] [Indexed: 04/02/2024]
Abstract
Limited evidence exists on the effect of submicronic particulate matter (PM1) on hypertension hospitalization. Evidence based on causal inference and large cohorts is even more scarce. In 2015, 36,271 participants were enrolled in South China and followed up through 2020. Each participant was assigned single-year, lag0-1, and lag0-2 moving average concentration of PM1 and fine inhalable particulate matter (PM2.5) simulated based on satellite data at a 1-km resolution. We used an inverse probability weighting approach to balance confounders and utilized a marginal structural Cox model to evaluate the underlying causal links between PM1 exposure and hypertension hospitalization, with PM2.5-hypertension association for comparison. Several sensitivity studies and the analyses of effect modification were also conducted. We found that a higher hospitalization risk from both overall (HR: 1.13, 95% CI: 1.05-1.22) and essential hypertension (HR: 1.15, 95% CI: 1.06-1.25) was linked to each 1 µg/m3 increase in the yearly average PM1 concentration. At lag0-1 and lag0-2, we observed a 17%-21% higher risk of hypertension associated with PM1. The effect of PM1 was 6%-11% higher compared with PM2.5. Linear concentration-exposure associations between PM1 exposure and hypertension were identified, without safety thresholds. Women and participants that engaged in physical exercise exhibited higher susceptibility, with 4%-22% greater risk than their counterparts. This large cohort study identified a detrimental relationship between chronic PM1 exposure and hypertension hospitalization, which was more pronounced compared with PM2.5 and among certain groups.
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Affiliation(s)
- 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 510080, China
| | - 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 510080, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park 20742, USA
| | - Jie Jiang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Xiao Lin
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou 510080, China
| | - Ying Wang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou 510080, China
| | - 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 510080, 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 510080, China
| | - Zhupei Yuan
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou 510080, China
| | - Jie Sun
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou 510080, China
| | - Han Wang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou 510080, China
| | - Zhicheng Du
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou 510080, 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 510080, China.
| | - Yuantao Hao
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Peking University Center for Public Health and Epidemic Preparedness & Response, Peking University, Beijing 100191, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China.
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Shi T, Peng Y, Ma X, Han G, Zhang H, Pei Z, Li S, Mao H, Zhang X, Gong W. China's "coal-to-gas" policy had large impact on PM 1.0 distribution during 2016-2019. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 359:121071. [PMID: 38718608 DOI: 10.1016/j.jenvman.2024.121071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2024] [Revised: 03/24/2024] [Accepted: 04/30/2024] [Indexed: 05/22/2024]
Abstract
Particulate matter with an aerodynamic diameter of less than 1 μm (PM1.0) can be extremely hazardous to human health, so it is imperative to accurately estimate the spatial and temporal distribution of PM1.0 and analyze the impact of related policies on it. In this study, a stacking generalization model was trained based on aerosol optical depth (AOD) data from satellite observations, combined with related data affecting aerosol concentration such as meteorological data and geographic data. Using this model, the PM1.0 concentration distribution in China during 2016-2019 was estimated, and verified by comparison with ground-based stations. The coefficient of determination (R2) of the model is 0.94, and the root-mean-square error (RMSE) is 8.49 μg/m3, mean absolute error (MAE) is 4.10 μg/m3, proving that the model has a very high performance. Based on the model, this study analyzed the PM1.0 concentration changes during the heating period (November and December) in the regions where the "coal-to-gas" policy was implemented in China, and found that the proposed "coal-to-gas" policy did reduce the PM1.0 concentration in the implemented regions. However, the lack of natural gas due to the unreasonable deployment of the policy in the early stage caused the increase of PM1.0 concentration. This study can provide a reference for the next step of urban air pollution policy development.
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Affiliation(s)
- Tianqi Shi
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91198 Gif-sur-Yvette, France; Electronic Information School, Wuhan University, Luoyu Road No.129, Wuhan, 430079, China; State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Luoyu Road No.129, Wuhan, 430079, China
| | - Yanran Peng
- Electronic Information School, Wuhan University, Luoyu Road No.129, Wuhan, 430079, China
| | - Xin Ma
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Luoyu Road No.129, Wuhan, 430079, China.
| | - Ge Han
- School of Remote Sensing and Information Engineering, Wuhan University, Luoyu Road No.129, Wuhan, 430079, China
| | - Haowei Zhang
- Electronic Information School, Wuhan University, Luoyu Road No.129, Wuhan, 430079, China
| | - Zhipeng Pei
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Luoyu Road No.129, Wuhan, 430079, China
| | - Siwei Li
- School of Remote Sensing and Information Engineering, Wuhan University, Luoyu Road No.129, Wuhan, 430079, China
| | - Huiqin Mao
- Ministry of Ecology and Environment Center for Satellite Application on Ecology and Environment, Beijing, China
| | - Xingying Zhang
- Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites (LRCVES/CMA), National Satellite Meteorological Center, China Meteorological Administration (NSMC/CMA), Beijing, 100081, China
| | - Wei Gong
- Electronic Information School, Wuhan University, Luoyu Road No.129, Wuhan, 430079, China; State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Luoyu Road No.129, Wuhan, 430079, China
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Li Y, Zhu L, Wei J, Wu C, Zhao Z, Norbäck D, Zhang X, Lu C, Yu W, Wang T, Zheng X, Zhang L, Zhang Y. Intrauterine and early postnatal exposures to submicron particulate matter and childhood allergic rhinitis: A multicity cross-sectional study in China. ENVIRONMENTAL RESEARCH 2024; 247:118165. [PMID: 38215923 DOI: 10.1016/j.envres.2024.118165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 12/11/2023] [Accepted: 01/08/2024] [Indexed: 01/14/2024]
Abstract
BACKGROUND Airborne particulate matter pollution has been linked to occurrence of childhood allergic rhinitis (AR). However, the relationships between exposure to particulate matter with an aerodynamic diameter ≤1 μm (PM1) during early life (in utero and first year of life) and the onset of childhood AR remain largely unknown. This study aims to investigate potential associations of in utero and first-year exposures to size-segregated PMs, including PM1, PM1-2.5, PM2.5, PM2.5-10, and PM10, with childhood AR. METHODS We investigated 29286 preschool children aged 3-6 years in 7 Chinese major cities during 2019-2020 as the Phase II of the China Children, Families, Health Study. Machine learning-based space-time models were utilized to estimate early-life residential exposure to PM1, PM2.5, and PM10 at 1 × 1-km resolutions. The concentrations of PM1-2.5 and PM2.5-10 were calculated by subtracting PM1 from PM2.5 and PM2.5 from PM10, respectively. Multiple mixed-effects logistic models were used to assess the odds ratios (ORs) and 95% confidence intervals (CIs) of childhood AR associated with per 10-μg/m3 increase in exposure to particulate air pollution during in utero period and the first year of life. RESULTS Among the 29286 children surveyed (mean ± standard deviation, 4.9 ± 0.9 years), 3652 (12.5%) were reported to be diagnosed with AR. Average PM1 concentrations during in utero period and the first year since birth were 36.3 ± 8.6 μg/m3 and 33.1 ± 6.9 μg/m3, respectively. Exposure to PM1 and PM2.5 during pregnancy and the first year of life was associated with an increased risk of AR in children, and the OR estimates were higher for each 10-μg/m3 increase in PM1 than for PM2.5 (e.g., 1.132 [95% CI: 1.022-1.254] vs. 1.079 [95% CI: 1.014-1.149] in pregnancy; 1.151 [95% CI: 1.014-1.306] vs. 1.095 [95% CI: 1.008-1.189] in the first year of life). No associations were observed between AR and both pre- and post-natal exposure to PM1-2.5, indicating that PM1 rather than PM1-2.5 contributed to the association between PM2.5 and childhood AR. In trimester-stratified analysis, childhood AR was only found to be associated with exposure to PM1 (OR = 1.077, 95% CI: 1.027-1.128), PM2.5 (OR = 1.048, 95% CI: 1.018-1.078), and PM10 (OR = 1.032, 95% CI: 1.007-1.058) during the third trimester of pregnancy. Subgroup analysis suggested stronger PM-AR associations among younger (<5 years old) and winter-born children. CONCLUSIONS Prenatal and postnatal exposures to ambient PM1 and PM2.5 were associated with an increased risk of childhood AR, and PM2.5-related hazards could be predominantly attributed to PM1. These findings highlighted public health significance of formulating air quality guideline for ambient PM1 in mitigating children's AR burden caused by particulate air pollution.
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Affiliation(s)
- Yachen Li
- Institute of Social Development and Health Management, Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Public Health, Wuhan University of Science and Technology, Wuhan 430065, China
| | - Lifeng Zhu
- Institute of Social Development and Health Management, Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Public Health, Wuhan University of Science and Technology, Wuhan 430065, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20740, USA
| | - Chuansha Wu
- Department of Environmental Hygiene and Occupational Medicine, School of Public Health, Wuhan University of Science and Technology, Wuhan 430065, China
| | - Zhuohui Zhao
- Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200030, China
| | - Dan Norbäck
- Department of Medical Sciences, Uppsala University, Uppsala SE 75185, Sweden
| | - Xin Zhang
- Research Centre for Environmental Science and Engineering, Shanxi University, Taiyuan 030006, China
| | - Chan Lu
- Department of Occupational and Environmental Health, School of Public Health, Xiangya Medical College, Central South University, Changsha 410078, China
| | - Wei Yu
- Joint International Research Laboratory of Green Buildings and Built Environments (Ministry of Education), Chongqing University, Chongqing 400045, China
| | - Tingting Wang
- School of Nursing and Health Management, Shanghai University of Medicine and Health Sciences, Shanghai 201318, China
| | - Xiaohong Zheng
- School of Energy and Environment, Southeast University, Nanjing 210096, China
| | - Ling Zhang
- Department of Environmental Hygiene and Occupational Medicine, School of Public Health, Wuhan University of Science and Technology, Wuhan 430065, China.
| | - Yunquan Zhang
- Institute of Social Development and Health Management, Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Public Health, Wuhan University of Science and Technology, Wuhan 430065, China.
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8
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Chen R, Yang C, Guo Y, Chen G, Li S, Li P, Wang J, Meng R, Wang HY, Peng S, Sun X, Wang F, Kong G, Zhang L. Association between ambient PM 1 and the prevalence of chronic kidney disease in China: A nationwide study. JOURNAL OF HAZARDOUS MATERIALS 2024; 468:133827. [PMID: 38377899 DOI: 10.1016/j.jhazmat.2024.133827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Revised: 02/08/2024] [Accepted: 02/16/2024] [Indexed: 02/22/2024]
Abstract
Particulate of diameter ≤ 1 µm (PM1) presents a novel risk factor of adverse health effects. Nevertheless, the association of PM1 with the risk of chronic kidney disease (CKD) in the general population is not well understood, particularly in regions with high PM1 levels like China. Based on a nationwide representative survey involving 47,204 adults and multi-source ambient air pollution inversion data, the present study evaluated the association of PM1 with CKD prevalence in China. The two-year average PM1, particulate of diameter ≤ 2.5 µm (PM2.5), and PM1-2.5 values were accessed using a satellite-based random forest approach. CKD was defined as estimated glomerular filtration rate < 60 ml/min/1.73 m2 or albuminuria. The results suggested that a 10 μg/m3 rise in PM1 was related to a higher CKD risk (odds ratio [OR], 1.13; 95% confidence interval [CI] 1.08-1.18) and albuminuria (OR, 1.11; 95% CI, 1.05-1.17). The association between PM1 and CKD was more evident among urban populations, older adults, and those without comorbidities such as diabetes or hypertension. Every 1% increase in the PM1/PM2.5 ratio was related to the prevalence of CKD (OR, 1.03; 95% CI, 1.03-1.04), but no significant relationship was found for PM1-2.5. In conclusion, the present study demonstrated long-term exposure to PM1 was associated with an increased risk of CKD in the general population and PM1 might play a leading role in the observed relationship of PM2.5 with the risk of CKD. These findings provide crucial evidence for developing air pollution control strategies to reduce the burden of CKD.
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Affiliation(s)
- Rui Chen
- Renal Division, Department of Medicine, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China; Research Units of Diagnosis and Treatment of Immune-mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China
| | - Chao Yang
- Renal Division, Department of Medicine, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China; Research Units of Diagnosis and Treatment of Immune-mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China; Advanced Institute of Information Technology, Peking University, Hangzhou, China
| | - Yuming Guo
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Gongbo Chen
- Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Shanshan Li
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Pengfei Li
- Advanced Institute of Information Technology, Peking University, Hangzhou, China
| | - Jinwei Wang
- Renal Division, Department of Medicine, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China; Research Units of Diagnosis and Treatment of Immune-mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China
| | - Ruogu Meng
- National Institute of Health Data Science at Peking University, Beijing 100191, China
| | - Huai-Yu Wang
- National Institute of Health Data Science at Peking University, Beijing 100191, China
| | - Suyuan Peng
- National Institute of Health Data Science at Peking University, Beijing 100191, China
| | - Xiaoyu Sun
- Advanced Institute of Information Technology, Peking University, Hangzhou, China; National Institute of Health Data Science at Peking University, Beijing 100191, China
| | - Fulin Wang
- National Institute of Health Data Science at Peking University, Beijing 100191, China; Institute of Medical Technology, Peking University Health Science Center, Beijing 100191, China
| | - Guilan Kong
- Advanced Institute of Information Technology, Peking University, Hangzhou, China; National Institute of Health Data Science at Peking University, Beijing 100191, China
| | - Luxia Zhang
- Renal Division, Department of Medicine, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China; Research Units of Diagnosis and Treatment of Immune-mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China; Advanced Institute of Information Technology, Peking University, Hangzhou, China; National Institute of Health Data Science at Peking University, Beijing 100191, China.
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9
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Christodoulou A, Bezantakos S, Bourtsoukidis E, Stavroulas I, Pikridas M, Oikonomou K, Iakovides M, Hassan SK, Boraiy M, El-Nazer M, Wheida A, Abdelwahab M, Sarda-Estève R, Rigler M, Biskos G, Afif C, Borbon A, Vrekoussis M, Mihalopoulos N, Sauvage S, Sciare J. Submicron aerosol pollution in Greater Cairo (Egypt): A new type of urban haze? ENVIRONMENT INTERNATIONAL 2024; 186:108610. [PMID: 38626495 DOI: 10.1016/j.envint.2024.108610] [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: 02/24/2024] [Accepted: 03/26/2024] [Indexed: 04/18/2024]
Abstract
Greater Cairo, the largest megacity of the Middle East North Africa (MENA) region, is currently suffering from major aerosol pollution, posing a significant threat to public health. However, the main sources of pollution remain insufficiently characterized due to limited atmospheric observations. To bridge this knowledge gap, we conducted a continuous 2-month field study during the winter of 2019-2020 at an urban background site, documenting for the first time the chemical and physical properties of submicron (PM1) aerosols. Crustal material from both desert dust and road traffic dust resuspension contributed as much as 24 % of the total PM1 mass (rising to 66 % during desert dust events), a figure not commonly observed in urban environments. Our observations showed significant decreases in black carbon concentrations and ammonium sulfate compared to data from 15 years ago, indicating an important reduction in both local and regional emissions as a result of effective mitigation measures. The diurnal variability of carbonaceous aerosols was attributed to emissions emanating from local traffic at rush hours and nighttime open biomass burning. Surprisingly, semi-volatile ammonium chloride (NH4Cl) originating from local open biomass and waste burning was found to be the main chemical species in PM1 over Cairo. Its nighttime formation contributed to aerosol water uptake during morning hours, thereby playing a major role in the build-up of urban haze. While our results confirm the persistence of a significant dust reservoir over Cairo, they also unveil an additional source of highly hygroscopic (semi-volatile) inorganic salts, leading to a unique type of urban haze. This haze, with dominant contributors present in both submicron (primarily as NH4Cl) and supermicron (largely as dust) modes, underscores the potential implications of heterogeneous chemical transformation of air pollutants in urban environments.
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Affiliation(s)
- Aliki Christodoulou
- Climate and Atmosphere Research Center (CARE-C), the Cyprus Institute, Nicosia, 2121, Cyprus; IMT Nord Europe, Institut Mines-Télécom, Univ. Lille, Centre for Energy and Environment, 59000 Lille, France.
| | - Spyros Bezantakos
- Climate and Atmosphere Research Center (CARE-C), the Cyprus Institute, Nicosia, 2121, Cyprus
| | | | - Iasonas Stavroulas
- Climate and Atmosphere Research Center (CARE-C), the Cyprus Institute, Nicosia, 2121, Cyprus; Institute for Environmental Research and Sustainable Development, National Observatory of Athens, Athens, Greece
| | - Michael Pikridas
- Climate and Atmosphere Research Center (CARE-C), the Cyprus Institute, Nicosia, 2121, Cyprus
| | - Konstantina Oikonomou
- Climate and Atmosphere Research Center (CARE-C), the Cyprus Institute, Nicosia, 2121, Cyprus
| | - Minas Iakovides
- Climate and Atmosphere Research Center (CARE-C), the Cyprus Institute, Nicosia, 2121, Cyprus
| | - Salwa K Hassan
- Air Pollution Research Department, Environment and Climate Change Research Institute, National, Research Centre, El Behooth Str., Giza 12622 Dokki, Egypt
| | - Mohamed Boraiy
- Physics and Mathematical Engineering Department, Faculty of Engineering, Port Said University, Port Said, Egypt
| | - Mostafa El-Nazer
- Theoretical Physics Department, Physics Institute, National Research Centre, El Behooth Str., Giza 12622 Dokki, Egypt
| | - Ali Wheida
- Theoretical Physics Department, Physics Institute, National Research Centre, El Behooth Str., Giza 12622 Dokki, Egypt
| | - Magdy Abdelwahab
- Astronomy and Meteorology Department, Faculty of Science, Cairo University, Cairo, Egypt
| | - Roland Sarda-Estève
- Laboratoire Des Sciences Du Climat Et de l'Environnement (LSCE), CNRS-CEA-UVSQ, Gif-sur-Yvette, France
| | - Martin Rigler
- Research and Development Department, Aerosol D.o.o., Ljubjana, Slovenia
| | - Giorgos Biskos
- Climate and Atmosphere Research Center (CARE-C), the Cyprus Institute, Nicosia, 2121, Cyprus
| | - Charbel Afif
- Climate and Atmosphere Research Center (CARE-C), the Cyprus Institute, Nicosia, 2121, Cyprus; Emissions, Measurements, and Modeling of the Atmosphere (EMMA) Laboratory, CAR, Faculty of Science, Saint Joseph University, Beirut, Lebanon
| | - Agnes Borbon
- Laboratoire de Météorologie Physique, UMR6016, Université Clermont Auvergne, OPGC, CNRS, 63000 Clermont-Ferrand, France
| | - Mihalis Vrekoussis
- Climate and Atmosphere Research Center (CARE-C), the Cyprus Institute, Nicosia, 2121, Cyprus; University of Bremen, Institute of Environmental Physics and Remote Sensing (IUP), Germany; Center of Marine Environmental Sciences (MARUM), University of Bremen, Germany
| | - Nikos Mihalopoulos
- Climate and Atmosphere Research Center (CARE-C), the Cyprus Institute, Nicosia, 2121, Cyprus; Institute for Environmental Research and Sustainable Development, National Observatory of Athens, Athens, Greece
| | - Stéphane Sauvage
- IMT Nord Europe, Institut Mines-Télécom, Univ. Lille, Centre for Energy and Environment, 59000 Lille, France
| | - Jean Sciare
- Climate and Atmosphere Research Center (CARE-C), the Cyprus Institute, Nicosia, 2121, Cyprus
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10
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Li Y, Yu B, Yin L, Li X, Nima Q. Long-term exposure to particulate matter is associated with elevated blood pressure: Evidence from the Chinese plateau area. J Glob Health 2024; 14:04039. [PMID: 38483442 PMCID: PMC10939114 DOI: 10.7189/jogh.14.04039] [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: 03/17/2024] Open
Abstract
Background Ambient air pollution could increase the risk of hypertension; however, evidence regarding the relationship between long-term exposure to particulate matter and elevated blood pressure in plateau areas with lower pollution levels is limited. Methods We assessed the associations of long-term exposure to particulate matter (PM, PM1, PM2.5, and PM10) with hypertension, diastolic blood pressure (DBP), systolic blood pressure (SBP) and pulse pressure (PP) in 4.235 Tibet adults, based on the baseline of the China multi-ethnic cohort study (CMEC) in Lhasa city, Tibet from 2018-19. We used logistic regression and linear regression models to evaluate the associations of ambient PM with hypertension and blood pressure, respectively. Results Long-term exposure to PM1, PM2.5, and PM10 is positively associated with hypertension, DBP, and SBP, while negatively associated with PP. Among these air pollutants, PM10 had the strongest effect on hypertension, DBP, and SBP, while PM2.5 had the strongest effect on PP. The results showed for hypertension odds ratio (OR) = 1.99; 95% confidence interval (CI) = 1.58, 2.51 per interquartile range (IQR) μg/m3 increase in PM1, OR = 1.93; 95% CI = 1.55, 2.40 per IQR μg/m3 increase in PM2.5, and OR = 2.12; 95% CI = 1.67, 2.68 per IQR μg/m3 increase in PM10. Conclusions Long-term exposure to ambient air pollution was associated with an increased risk of hypertension, elevated SBP and DBP levels, and decreased PP levels. To reduce the risk of hypertension and PP reduction, attention should be paid to air quality interventions in plateau areas with low pollution levels.
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Affiliation(s)
- Yajie Li
- Tibet Centre for Disease Control and Prevention, Lhasa, Tibet Autonomous Region, China
| | - Bin Yu
- Institute for Disaster Management and Reconstruction, Sichuan University – Hong Kong Polytechnic University, Chengdu, China
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Li Yin
- Meteorological Medical Research Center, Panzhihua Central Hospital, Panzhihua, China
- Clinical Medical Research Center, Panzhihua Central Hospital, Panzhihua, China
- Dali University, Dali, China
| | - Xianzhi Li
- Meteorological Medical Research Center, Panzhihua Central Hospital, Panzhihua, China
- Clinical Medical Research Center, Panzhihua Central Hospital, Panzhihua, China
- Dali University, Dali, China
| | - Qucuo Nima
- Tibet Centre for Disease Control and Prevention, Lhasa, Tibet Autonomous Region, China
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11
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Li D, Wu S, Tang L, Chen S, Cui F, Ma Y, Liu R, Wang J, Tian Y. Long-term exposure to reduced specific-size ambient particulate matter and progression of arterial stiffness among Chinese adults. JOURNAL OF HAZARDOUS MATERIALS 2024; 466:133482. [PMID: 38246055 DOI: 10.1016/j.jhazmat.2024.133482] [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: 11/05/2023] [Revised: 12/22/2023] [Accepted: 01/08/2024] [Indexed: 01/23/2024]
Abstract
To assess the associations of ambient specific-size PM with brachial-ankle pulse wave velocity (baPWV) and the progression of arterial stiffness. Participants were included from the Kailuan study, the cross-sectional study involved 36,486 participants, while the longitudinal study enrolled 16,871 participants. PM exposures was assessed through satellite-based random forest approaches at a 1 km resolution. Initial observations indicated a link between baseline baPWV and heightened levels of PM1, PM2.5, and PM10 exposure, and greater effects were observed for PM1 (β: 22.52, 95% CI: 18.14-26.89), followed by PM2.5 (β: 9.76, 95% CI: 7.52-12.00), and PM10 (β: 8.88, 95% CI: 7.32-10.45). Furthermore, the growth rate of baPWV was higher in participants exposed to high levels of PM1 exposure (β: 2.77, 95% CI: 1.19-4.35), succeeded by PM2.5 and PM10. Throughout a median follow-up period of 4.04 years, arterial stiffness was diagnosed in 1709 subjects. Long-term exposure to PM was linked with an increased risk of incident arterial stiffness, estimated HR for fixed 10 µg/m3 increments in annual average PM1 was 2.20 (95% CI: 2.01-2.42), PM2.5 was 1.48 (95% CI: 1.41-1.55), and PM10 1.32 (95% CI: 1.27-1.36). PM had a greater impact on men and older individuals (P for interaction <0.001). Long-term exposures to ambient PM1, PM2.5, and PM10 were positively associated with baPWV and an increased risk of arterial stiffness. Higher estimated effects were observed for PM1 than PM2.5 and PM10.
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Affiliation(s)
- Dankang Li
- Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan 430030, China
| | - Shouling Wu
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, No.57 Xinhua East Road, Tangshan City 063001, China
| | - Linxi Tang
- Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan 430030, China
| | - Shuohua Chen
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, No.57 Xinhua East Road, Tangshan City 063001, China
| | - Feipeng Cui
- Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan 430030, China
| | - Yudiyang Ma
- Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan 430030, China
| | - Run Liu
- Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan 430030, China
| | - Jianing Wang
- Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan 430030, China
| | - Yaohua Tian
- Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan 430030, China.
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12
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Guo T, Cheng X, Wei J, Chen S, Zhang Y, Lin S, Deng X, Qu Y, Lin Z, Chen S, Li Z, Sun J, Chen X, Chen Z, Sun X, Chen D, Ruan X, Tuohetasen S, Li X, Zhang M, Sun Y, Zhu S, Deng X, Hao Y, Jing Q, Zhang W. Unveiling causal connections: Long-term particulate matter exposure and type 2 diabetes mellitus mortality in Southern China. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 274:116212. [PMID: 38489900 DOI: 10.1016/j.ecoenv.2024.116212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 03/09/2024] [Accepted: 03/11/2024] [Indexed: 03/17/2024]
Abstract
Evidence of the potential causal links between long-term exposure to particulate matters (PM, i.e., PM1, PM2.5, and PM1-2.5) and T2DM mortality based on large cohorts is limited. In contrast, the existing evidence usually suffers from inherent bias with the traditional association assessment. A prospective cohort of 580,757 participants in the southern region of China were recruited during 2009 and 2015 and followed up through December 2020. PM exposure at each residential address was estimated by linking to the well-established high-resolution simulation dataset. Hazard ratios (HRs) were calculated using time-varying marginal structural Cox models, an established causal inference approach, after adjusting for potential confounders. During follow-up, a total of 717 subjects died from T2DM. For every 1 μg/m3 increase in PM2.5, the adjusted HRs and 95% confidence interval (CI) for T2DM mortality was 1.036 (1.019-1.053). Similarly, for every 1 μg/m3 increase in PM1 and PM1-2.5, the adjusted HRs and 95% CIs were 1.032 (1.003-1.062) and 1.085 (1.054-1.116), respectively. Additionally, we observed a generally more pronounced impact among individuals with lower levels of education or lower residential greenness which as measured by the Normalized Difference Vegetation Index (NDVI). We identified substantial interactions between NDVI and PM1 (P-interaction = 0.003), NDVI and PM2.5 (P-interaction = 0.019), as well as education levels and PM1 (P-interaction = 0.049). The study emphasizes the need to consider environmental and socio-economic factors in strategies to reduce T2DM mortality. We found that PM1, PM2.5, and PM1-2.5 heighten the peril of T2DM mortality, with education and green space exposure roles in modifying it.
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Affiliation(s)
- Tong Guo
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Xi Cheng
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, Maryland 20740, USA
| | - Shirui Chen
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Yuqin Zhang
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Shao Lin
- Department of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, NY, USA
| | - Xinlei Deng
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Yanji Qu
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangdong, China
| | - Ziqiang Lin
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, Guangdong, China
| | - Shimin Chen
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Zhiqiang Li
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Jie Sun
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Xudan Chen
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Zhibing Chen
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Xurui Sun
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Dan Chen
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Xingling Ruan
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Shaniduhaxi Tuohetasen
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Xinyue Li
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Man Zhang
- Department of nosocomial infection management, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China
| | - Yongqing Sun
- Department of Ultrasound, Beijing Obstetrics and Gynecology Hospital, Capital Medical University. Beijing Maternal and Child Health Care Hospital, Beijing 100026, China
| | - Shuming Zhu
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Xueqing Deng
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Yuantao Hao
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking, China.
| | - Qinlong Jing
- Guangzhou Municipal Health Commission, Guangzhou, China.
| | - Wangjian Zhang
- Department of Medical Statistics, School of Public Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong 510080, China.
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Ren W, Yang H, Liu W, Zhang S, Yang Y, Yang L, Liu W, Zhang H, He K, Li X, Ge J. Exposure to mixtures of PM 2.5 components and term premature rupture of membranes: a case-crossover study in Shijiazhuang, China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2024:1-13. [PMID: 38269576 DOI: 10.1080/09603123.2024.2308017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 01/16/2024] [Indexed: 01/26/2024]
Abstract
This study aims to explore the acute effects of short-term exposure to PM2.5 components and their mixture on PROM. Counts of hospital admissions due to PROM were collected at the Fourth Hospital of Shijiazhuang. The associations between the PROM and PM2.5 components was examined using a time-stratified case-crossover approach. The overall effects of components on TPROM were examined using the BKMR. During the study period 30,709 cases of PROMwere identified. The relative risks and the 95% CI of TPROM were 1.013 (1.002, 1.028) and 1.015 (1.003, 1.028) associated with per interquartile range increase in nitrate and ammonium ion on the current day and they were 1.007 (1.001, 1.013) and 1.003 (1.000, 1.005) on the previous day. The results from the BKMR models showed a higher risk of TPROM was associated with exposure to mixtures, in which, nitrate and organic matter were the main contributors to the overall effect.
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Affiliation(s)
- Weiyan Ren
- Hebei Key Laboratory of Environment and Human Health, School of Public Health, Hebei Medical University, Shijiazhuang, China
| | - Huangmin Yang
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Wencong Liu
- Department of Ultrasonics, The First Affiliated Hospital of Hebei Medical University, Shijiazhuang, China
| | - Shaochong Zhang
- Department of Medical Records, Shijiazhuang Fourth Hospital, shijiazhuang, China
| | - Yanjing Yang
- Department of Medical Records, Shijiazhuang Fourth Hospital, shijiazhuang, China
| | - Lei Yang
- Hebei Key Laboratory of Environment and Human Health, School of Public Health, Hebei Medical University, Shijiazhuang, China
| | - Wenxuan Liu
- Hebei Key Laboratory of Environment and Human Health, School of Public Health, Hebei Medical University, Shijiazhuang, China
| | - Haijuan Zhang
- Department of Medical Records, Shijiazhuang Fourth Hospital, shijiazhuang, China
| | - Ke He
- Department of Medical Records, Shijiazhuang Fourth Hospital, shijiazhuang, China
| | - Xia Li
- Department of Medical Records, Shijiazhuang Fourth Hospital, shijiazhuang, China
| | - Jun Ge
- Department of Medical Records, Shijiazhuang Fourth Hospital, shijiazhuang, China
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Yu LJ, Li XL, Wang YH, Zhang HY, Ruan SM, Jiang BG, Xu Q, Sun YS, Wang LP, Liu W, Yang Y, Fang LQ. Short-Term Exposure to Ambient Air Pollution and Influenza: A Multicity Study in China. ENVIRONMENTAL HEALTH PERSPECTIVES 2023; 131:127010. [PMID: 38078423 PMCID: PMC10711743 DOI: 10.1289/ehp12146] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 10/02/2023] [Accepted: 10/27/2023] [Indexed: 12/18/2023]
Abstract
BACKGROUND Air pollution is a major risk factor for planetary health and has long been suspected of predisposing humans to respiratory diseases induced by pathogens like influenza viruses. However, epidemiological evidence remains elusive due to lack of longitudinal data from large cohorts. OBJECTIVE Our aim is to quantify the short-term association of influenza incidence with exposure to ambient air pollutants in Chinese cities. METHODS Based on air pollutant data and influenza surveillance data from 82 cities in China over a period of 5 years, we applied a two-stage time series analysis to assess the association of daily incidence of reported influenza cases with six common air pollutants [particulate matter with aerodynamic diameter ≤ 2.5 μ m (PM 2.5 ), particulate matter with aerodynamic diameter ≤ 10 μ m (PM 10 ), NO 2 , SO 2 , CO, and O 3 ], while adjusting for potential confounders including temperature, relative humidity, seasonality, and holiday effects. We built a distributed lag Poisson model for one or multiple pollutants in each individual city in the first stage and conducted a meta-analysis to pool city-specific estimates in the second stage. RESULTS A total of 3,735,934 influenza cases were reported in 82 cities from 2015 to 2019, accounting for 72.71% of the overall case number reported in the mainland of China. The time series models for each pollutant alone showed that the daily incidence of reported influenza cases was positively associated with almost all air pollutants except for ozone. The most prominent short-term associations were found for SO 2 and NO 2 with cumulative risk ratios of 1.094 [95% confidence interval (CI): 1.054, 1.136] and 1.093 (95% CI: 1.067, 1.119), respectively, for each 10 μ g / m 3 increase in the concentration at each of the lags of 1-7 d. Only NO 2 showed a significant association with the daily incidence of influenza cases in the multipollutant model that adjusts all six air pollutants together. The impact of air pollutants on influenza was generally found to be greater in children, in subtropical cities, and during cold months. DISCUSSION Increased exposure to ambient air pollutants, particularly NO 2 , is associated with a higher risk of influenza-associated illness. Policies on reducing air pollution levels may help alleviate the disease burden due to influenza infection. https://doi.org/10.1289/EHP12146.
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Affiliation(s)
- Lin-Jie Yu
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - Xin-Lou Li
- Department of Medical Research, Key Laboratory of Environmental Sense Organ Stress and Health of the Ministry of Environmental Protection, PLA Strategic Support Force Medical Center, Beijing, P. R. China
| | - Yan-He Wang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - Hai-Yang Zhang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - Shi-Man Ruan
- Jinan Center for Disease Control and Prevention, Jinan, P. R. China
| | - Bao-Gui Jiang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - Qiang Xu
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - Yan-Song Sun
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - Li-Ping Wang
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, P. R. China
| | - Wei Liu
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - Yang Yang
- Department of Statistics, Franklin College of Arts and Science, University of Georgia, Athens, Georgia, USA
| | - Li-Qun Fang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
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Chen S, Zhang Y, Wang Y, Lawrence WR, Rhee J, Guo T, Chen S, Du Z, Wu W, Li Z, Wei J, Hao Y, Zhang W. Long-term particulate matter exposure and the risk of neurological hospitalization: Evidence from causal inference of a large longitudinal cohort in South China. CHEMOSPHERE 2023; 345:140397. [PMID: 37838030 PMCID: PMC10841469 DOI: 10.1016/j.chemosphere.2023.140397] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 09/12/2023] [Accepted: 10/08/2023] [Indexed: 10/16/2023]
Abstract
With limited evidence on the neurological impact of particulate matter (PM) exposure in China, particularly for PM1 which is smaller but more toxic, we conducted a large Chinese cohort study using causal inference approaches to comprehensively clarify such impact. A total of 36,271 participants in southern China were recruited in 2015 and followed up through 2020. We obtained the neurological hospitalizations records by linking the cohort data to the electronic reports from 418 medical institutions across the study area. By using high-resolution PM concentrations from satellite-based spatiotemporal models and the cohort data, we performed marginal structural Cox models under causal assumptions to assess the potential causal links between time-varying PM exposure and neurological hospitalizations. Our findings indicated that increasing PM1, PM2.5, and PM10 concentrations by 1 μg/m³ were associated with higher overall neurological hospitalization risks, with hazard ratios (HRs) of 1.10 (95% confidence interval (CI) 1.04-1.16), 1.09 (95% CI 1.04-1.14), and 1.03 (95% CI 1.00-1.06), respectively. PM1 appeared to have a stronger effect on neurological hospitalization, with a 1% and 7% higher impact compared to PM2.5 and PM10, respectively. Additionally, each 1-μg/m3 increase in the annual PM1 concentration was associated with an elevated risk of hospitalizations for ischemic stroke (HR: 1.15; 95% CI, 1.06-1.26), which tended to be larger than the estimates for PM2.5 (HR: 1.13, 95% CI, 1.04-1.23) and PM10 (HR: 1.05, 95% CI, 1.00-1.09). Furthermore, never-married or female individuals tended be at a greater risk compared with their counterparts. Our study provides important insights into the health impact of particles, particularly smaller particles, on neurological hospitalization risk and highlights the need for clean-air policies that specifically target these particles.
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Affiliation(s)
- Shimin Chen
- Department of Medical Statistics, School of Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Yuqin Zhang
- Department of Medical Statistics, School of Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Ying Wang
- Department of Medical Statistics, School of Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Wayne R Lawrence
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, United States
| | - Jongeun Rhee
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, United States
| | - Tong Guo
- Department of Medical Statistics, School of Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Shirui Chen
- Department of Medical Statistics, School of Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Zhicheng Du
- Department of Medical Statistics, School of Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Wenjing Wu
- Department of Medical Statistics, School of Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Zhiqiang Li
- Department of Medical Statistics, School of Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, United States.
| | - 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.
| | - Wangjian Zhang
- Department of Medical Statistics, School of Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, Guangdong, China.
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Baheti B, Chen G, Ding Z, Wu R, Zhang C, Zhou L, Liu X, Song X, Wang C. Residential greenness alleviated the adverse associations of long-term exposure to ambient PM 1 with cardiac conduction abnormalities in rural adults. ENVIRONMENTAL RESEARCH 2023; 237:116862. [PMID: 37574100 DOI: 10.1016/j.envres.2023.116862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 07/27/2023] [Accepted: 08/08/2023] [Indexed: 08/15/2023]
Abstract
BACKGROUND Ambient air pollution was linked to elevated risks of adverse cardiovascular events, and alterations in electrophysiological properties of the heart might be potential pathways. However, there is still lacking research exploring the associations between PM1 exposure and cardiac conduction parameters. Additionally, the interactive effects of PM1 and residential greenness on cardiac conduction parameters in resource-limited areas remain unknown. METHODS A total of 27483 individuals were enrolled from the Henan Rural Cohort study. Cardiac conduction parameters were tested by 12-lead electrocardiograms. Concentrations of PM1 were evaluated by satellite-based spatiotemporal models. Levels of residential greenness were assessed using Enhanced Vegetation Index (EVI) and Normalized difference vegetation index (NDVI). Logistic regression models and restricted cubic splines were fitted to explore the associations of PM1 and residential greenness exposure with cardiac conduction abnormalities risk, and the interaction plot method was performed to visualize their interaction effects. RESULTS The 3-year median concentration of PM1 was 56.47 (2.55) μg/m3, the adjusted odds rate (ORs) and 95% confidence intervals (CIs) for abnormal HR, PR, QRS, and QTc interval risk in response to 1 μg/m3 increase in PM1 were 1.064 (1.044, 1.085), 1.037 (1.002, 1.074), 1.061 (1.044, 1.077) and 1.046 (1.028, 1.065), respectively. Participants exposure to higher levels of PM1 had increased risks of abnormal HR (OR = 1.221, 95%CI: 1.144, 1.303), PR (OR = 1.061, 95%CI: 0.940, 1.196), QRS (OR = 1.225, 95%CI: 1.161, 1.294) and QTc interval (OR = 1.193, 95%CI: 1.121, 1.271) compared with lower levels of PM1. Negative interactive effects of exposure to PM1 and residential greenness on abnormal HR, QRS, and QTc intervals were observed (Pfor interaction < 0.05). CONCLUSION Long-term PM1 exposure was associated with elevated cardiac conduction abnormalities risks, and this adverse association might be mitigated by residential greenness to some extent. These findings emphasize that controlling PM1 pollution and increasing greenness levels might be effective strategies to reduce cardiovascular disease burdens in resource-limited areas.
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Affiliation(s)
- Bota Baheti
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Gongbo Chen
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Zhongao Ding
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Ruiyu Wu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Caiyun Zhang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Lue Zhou
- NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, Zhengzhou, Henan, PR China
| | - Xiaotian Liu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Xiaoqin Song
- Physical Examination Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, PR China.
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China; NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, Zhengzhou, Henan, PR China.
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Tian Y, Duan M, Cui X, Zhao Q, Tian S, Lin Y, Wang W. Advancing application of satellite remote sensing technologies for linking atmospheric and built environment to health. Front Public Health 2023; 11:1270033. [PMID: 38045962 PMCID: PMC10690611 DOI: 10.3389/fpubh.2023.1270033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 09/01/2023] [Indexed: 12/05/2023] Open
Abstract
Background The intricate interplay between human well-being and the surrounding environment underscores contemporary discourse. Within this paradigm, comprehensive environmental monitoring holds the key to unraveling the intricate connections linking population health to environmental exposures. The advent of satellite remote sensing monitoring (SRSM) has revolutionized traditional monitoring constraints, particularly limited spatial coverage and resolution. This innovation finds profound utility in quantifying land covers and air pollution data, casting new light on epidemiological and geographical investigations. This dynamic application reveals the intricate web connecting public health, environmental pollution, and the built environment. Objective This comprehensive review navigates the evolving trajectory of SRSM technology, casting light on its role in addressing environmental and geographic health issues. The discussion hones in on how SRSM has recently magnified our understanding of the relationship between air pollutant exposure and population health. Additionally, this discourse delves into public health challenges stemming from shifts in urban morphology. Methods Utilizing the strategic keywords "SRSM," "air pollutant health risk," and "built environment," an exhaustive search unfolded across prestigious databases including the China National Knowledge Network (CNKI), PubMed and Web of Science. The Citespace tool further unveiled interconnections among resultant articles and research trends. Results Synthesizing insights from a myriad of articles spanning 1988 to 2023, our findings unveil how SRMS bridges gaps in ground-based monitoring through continuous spatial observations, empowering global air quality surveillance. High-resolution SRSM advances data precision, capturing multiple built environment impact factors. Its application to epidemiological health exposure holds promise as a pioneering tool for contemporary health research. Conclusion This review underscores SRSM's pivotal role in enriching geographic health studies, particularly in atmospheric pollution domains. The study illuminates how SRSM overcomes spatial resolution and data loss hurdles, enriching environmental monitoring tools and datasets. The path forward envisions the integration of cutting-edge remote sensing technologies, novel explorations of urban-public health associations, and an enriched assessment of built environment characteristics on public well-being.
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Affiliation(s)
- Yuxuan Tian
- Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming, Yunnan, China
| | - Mengshan Duan
- Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming, Yunnan, China
| | - Xiangfen Cui
- Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming, Yunnan, China
| | - Qun Zhao
- Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming, Yunnan, China
| | - Senlin Tian
- Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming, Yunnan, China
| | - Yichao Lin
- Guizhou Research Institute of Coal Mine Design Co., Ltd., Guiyang, China
| | - Weicen Wang
- China Academy of Urban Planning Design, Beijing, China
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Tao J, Zhang Y, Li Z, Yang M, Huang C, Hossain MZ, Xu Y, Wei X, Su H, Cheng J, Zhang W. Daytime and nighttime high temperatures differentially increased the risk of cardiovascular disease: A nationwide hospital-based study in China. ENVIRONMENTAL RESEARCH 2023; 236:116740. [PMID: 37495061 DOI: 10.1016/j.envres.2023.116740] [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: 04/19/2023] [Revised: 07/01/2023] [Accepted: 07/24/2023] [Indexed: 07/28/2023]
Abstract
Short-term exposure to ambient high temperature (heat) could increase the risk of cardiovascular disease (CVD). However, available evidence on the burden of daytime and nighttime heat on CVD is limited and vulnerable populations remain unknown so far. We aimed to examine and differentiate the impact of daytime and nighttime heat on CVD in China. Data on daily outpatient visits for CVD were collected from 15 Chinese cities spanning multiple geographical regions, climates, and socio-economic conditions. The population-weighted temperature was used to calculate excess heat exposure in warm seasons (June-September) from 2011 to 2015. Hot day excess (HDE) and hot night excess (HNE), the sum of temperature above the heat threshold during daytime and nighttime respectively, were used to represent daytime and nighttime excess heat. A distributed lag non-linear model was employed to estimate the city-level association between HDE/HNE and daily CVD cases. The city-level association was then pooled by multivariate meta-analysis. We further estimated the disease burden of CVD attributable to HDE and HNE by geographical regions, gender, and age. A total of 729,409 cases of CVD were included in this study. Both HDE and HNE were associated with an increased risk of CVD, with greater effects from nighttime heat (relative risk (RR): 1.38; 95% confidence interval (CI): 1.18-1.61) than daytime heat (RR: 1.10; 95% CI: 1.05-1.15). The proportion of CVD cases attributable to HNE was 15.7%, which was almost three times as high as HDE (4.6%, p for difference <0.05). Males, people living in northern cities, and those aged less than 45 years were more vulnerable to HNE. Our findings for the first time revealed an intra-day difference in the heat effect on CVD, with a greater impact from nighttime heat exposure, which should be considered to protect vulnerable populations on hot days.
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Affiliation(s)
- Junwen Tao
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, China
| | - Yongming Zhang
- Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, National Clinical Research Center for Respiratory Diseases, Beijing, China
| | - Zhiwei Li
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, China
| | - Min Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, China
| | - Cunrui Huang
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Mohammad Zahid Hossain
- International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh
| | - Yuanyong Xu
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Xianyu Wei
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China; Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Hong Su
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, China
| | - Jian Cheng
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, China.
| | - Wenyi Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China; Chinese PLA Center for Disease Control and Prevention, Beijing, China.
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Nieckarz Z, Pawlak K, Zoladz JA. Health risks for children exercising in an air-polluted environment can be reduced by monitoring air quality with low-cost particle sensors. Sci Rep 2023; 13:18261. [PMID: 37880283 PMCID: PMC10600107 DOI: 10.1038/s41598-023-45426-3] [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: 08/12/2023] [Accepted: 10/19/2023] [Indexed: 10/27/2023] Open
Abstract
A child's body is highly sensitive to air quality, especially regarding the concentration of particulate matter (PM). Nevertheless, due to the high cost of precision instruments, measurements of PM concentrations are rarely carried out in school areas where children spend most of their daily time. This paper presents the results of PM measurements made by a validated, low-cost university air pollution measurement system operating in a rural area near schools. An assessment of children's exposure to PM during school hours (8 a.m.-6 p.m.) at different times of the year was carried out. We show that PM10 concentrations in the air, particularly in winter, often exceeded the alert values of 50 µg m-3, posing a health risk to children, especially when children exercise outside the school building. We also calculated the rate and total PM10 deposition in the respiratory tract during various physical activities performed in clean and polluted air. Monitoring actual PM10 concentrations as presented in this paper, using a low cost sensors, offer school authorities and teachers an opportunity to reduce health risks for children. This can be achieved by adjusting the duration and exercise intensity of children's outdoor physical activities according to the measured air quality.
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Affiliation(s)
- Zenon Nieckarz
- Marian Smoluchowski Institute of Physics, Jagiellonian University, ul. Łojasiewicza 11, 30-348, Kraków, Poland.
| | - Krzysztof Pawlak
- Department of Zoology and Animal Welfare, Faculty of Animal Science, Agricultural University of Cracow, Kraków, Poland
| | - Jerzy A Zoladz
- Chair of Exercise Physiology and Muscle Bioenergetics, Faculty of Health Sciences, Jagiellonian University Medical College, ul. Skawińska 8, 31-066, Kraków, Poland
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Li X, Li Y, Yu B, Nima Q, Meng H, Shen M, Zhou Z, Liu S, Tian Y, Xing X, Yin L. Urban-rural differences in the association between long-term exposure to ambient particulate matter (PM) and malnutrition status among children under five years old: A cross-sectional study in China. J Glob Health 2023; 13:04112. [PMID: 37736866 PMCID: PMC10515095 DOI: 10.7189/jogh.13.04112] [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: 09/23/2023] Open
Abstract
Background The evidence regarding the relationship between postnatal exposure of air pollution and child malnutrition indicators, as well as the corresponding urban-rural disparities, is limited, especially in low-pollution area of low- and middle-income countries (LMICs). Therefore, our aim was to contrast the effect estimates of varying ambient particulate matter (PM) on malnutrition indicators between urban and rural areas in Tibet, China. Methods Six malnutrition indicators were evaluated in this study, namely, Z-scores of height for age (HFA), Z-scores of weight for age (WFA), Z-scores of weight for height (WFH), stunting, underweight, and wasting. Exposure to particles with an aerodynamic diameter ≤2.5 micron (μm) (PM2.5), particles with an aerodynamic diameter ≤10 μm (PM10) and particles with an aerodynamic diameter between 2.5 and 10 μm (PMc) was estimated using satellite-based random forest models. Linear regression and logistic regression models were used to assess the associations between PM and the above malnutrition indicators. Furthermore, the effect estimates of different PM were contrasted between urban and rural areas. Results A total of 2511 children under five years old were included in this study. We found long-term exposure to PM2.5, PMc, and PM10 was associated with an increased risk of stunting and a decreased risk of underweight. Of these air pollutants, PMc had the strongest association for Z-scores of HFA and stunting, while PM2.5 had the strongest association for underweight. The results showed that the odds ratio (OR) for stunting were 1.36 (95% confidence interval (CI) = 1.06 to 1.75) per interquartile range (IQR) microgrammes per cubic metre (μg/m3) increase in PM2.5, 1.80 (95% CI = 1.30 to 2.50) per IQR μg/m3 increase in PMc and 1.55 (95% CI = 1.17 to 2.05) per IQR μg/m3 increase in PM10. The concentrations of PM were higher in urban areas, and the effects of PM on malnutrition indicators among urban children were higher than those of rural children. Conclusions Our results suggested that PM exposure might be an important trigger of child malnutrition. Further prospective researches are needed to provide important scientific literature for understanding child malnutrition risk concerning postnatal exposure of air pollutants and formulating synthetically social and environmental policies for malnutrition prevention.
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Affiliation(s)
- Xianzhi Li
- Meteorological Medical Research Center, Panzhihua Central Hospital, Panzhihua, Sichuan Province, China
- Clinical Medical Research Center, Panzhihua Central Hospital, Panzhihua, Sichuan Province, China
- Dali University, Dali, Yunnan Province, China
| | - Yajie Li
- Tibet Center for Disease Control and Prevention, Lhasa, Tibet Autonomous Region, China
| | - Bin Yu
- Institute for Disaster Management and Reconstruction, Sichuan University - Hong Kong Polytechnic University, Chengdu, Sichuan Province, China
| | - Qucuo Nima
- Tibet Center for Disease Control and Prevention, Lhasa, Tibet Autonomous Region, China
| | - Haorong Meng
- Yunnan Center for Disease Control and Prevention, Kunming, Yunnan Province, China
| | - Meiying Shen
- Nursing department, Panzhihua Central Hospital, Panzhihua, Sichuan Province, China
| | - Zonglei Zhou
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, China
| | - Shunjin Liu
- Meteorological Medical Research Center, Panzhihua Central Hospital, Panzhihua, Sichuan Province, China
- Clinical Medical Research Center, Panzhihua Central Hospital, Panzhihua, Sichuan Province, China
- Dali University, Dali, Yunnan Province, China
| | - Yunyun Tian
- Clinical Medical Research Center, Panzhihua Central Hospital, Panzhihua, Sichuan Province, China
- Dali University, Dali, Yunnan Province, China
| | - Xiangyi Xing
- Meteorological Medical Research Center, Panzhihua Central Hospital, Panzhihua, Sichuan Province, China
- Dali University, Dali, Yunnan Province, China
- Department of Pharmacy, Panzhihua Central Hospital, Panzhihua, Sichuan Province, China
| | - Li Yin
- Meteorological Medical Research Center, Panzhihua Central Hospital, Panzhihua, Sichuan Province, China
- Clinical Medical Research Center, Panzhihua Central Hospital, Panzhihua, Sichuan Province, China
- Dali University, Dali, Yunnan Province, China
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21
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Tian Y, Wu J, Wu Y, Wang M, Wang S, Yang R, Wang X, Wang J, Yu H, Li D, Wu T, Wei J, Hu Y. Short-term exposure to reduced specific-size ambient particulate matter increase the risk of cause-specific cardiovascular disease: A national-wide evidence from hospital admissions. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 263:115327. [PMID: 37611473 DOI: 10.1016/j.ecoenv.2023.115327] [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: 04/23/2023] [Revised: 07/21/2023] [Accepted: 08/02/2023] [Indexed: 08/25/2023]
Abstract
Evidence for the health effects of ambient PM1 (particulate matter with an aerodynamic diameter ≤ 1 µm) pollution is limited, and it remains unclear whether a smaller particulate matter has a greater impact on human health. We conducted a time-series study in 184 major cities by extracting daily hospital data on admissions for ischemic heart disease, heart failure, heart rhythm disturbances, and stroke between 2014 and 2017 from a medical insurance claims database of 0.28 billion beneficiaries. City-specific associations were estimated with over-dispersed generalized additive models. A random-effects meta-analysis was used to estimate regional and national average associations. We conducted stratified and meta-regression analyses to explore potential effect modifiers of the association. We recorded 8.83 million cardiovascular admissions during the study period. At the national-average level, a 10-μg/m3 increase in same-day PM1, PM2.5(particulate matter with an aerodynamic diameter ≤ 2.5 µm) and PM10(particulate matter with an aerodynamic diameter ≤ 10 µm) concentrations corresponded to a 1.14% (95% confidence interval 0.88-1.41%), 0.55% (0.40-0.70%), and 0.45% (0.36-0.55%) increase in cardiovascular admissions, respectively. PM1 exposure was also positively associated with all cardiovascular disease subtypes, including ischemic heart disease (1.28% change; 0.99-1.56%), heart failure (1.30% change; 0.70-1.91%), heart rhythm disturbances (1.11% change; 0.65-1.58%), and ischemic stroke (1.29% change; 0.88-1.71%). The associations between PM1 and cardiovascular admissions were stronger in cities with lower PM1 levels, higher air temperatures and relative humidity, as well as in subgroups with elder age (all P < 0.05). This study provides robust evidence of short-term associations between PM1 concentrations and increased hospital admissions for all major cardiovascular diseases in China. Our findings suggest a greater short-term impact on cardiovascular risk from PM1 in comparison to PM2.5 and PM10.
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Affiliation(s)
- Yaohua Tian
- Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, 430030 Wuhan, China; Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No.38 Xueyuan Road, 100191 Beijing, China
| | - Junhui Wu
- School of Nursing, Peking University, No. 38 Xueyuan Road, Beijing 100191, China
| | - Yiqun Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No.38 Xueyuan Road, 100191 Beijing, China
| | - Mengying Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No.38 Xueyuan Road, 100191 Beijing, China
| | - Siyue Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No.38 Xueyuan Road, 100191 Beijing, China
| | - Ruotong Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No.38 Xueyuan Road, 100191 Beijing, China
| | - Xiaowen Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No.38 Xueyuan Road, 100191 Beijing, China
| | - Jiating Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No.38 Xueyuan Road, 100191 Beijing, China
| | - Huan Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No.38 Xueyuan Road, 100191 Beijing, China
| | - Dankang Li
- Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, 430030 Wuhan, China
| | - Tao Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No.38 Xueyuan Road, 100191 Beijing, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA.
| | - Yonghua Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No.38 Xueyuan Road, 100191 Beijing, China; Medical Informatics Center, Peking University, No.38 Xueyuan Road, 100191 Beijing, China.
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22
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Cao Y, Zang T, Qiu T, Xu Z, Chen X, Fan X, Zhang Q, Huang Y, Liu J, Wu N, Shen N, Bai J, Li G, Huang J, Liu Y. Does PM 1 exposure during pregnancy impact the gut microbiota of mothers and neonates? ENVIRONMENTAL RESEARCH 2023; 231:116304. [PMID: 37268213 DOI: 10.1016/j.envres.2023.116304] [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: 12/26/2022] [Revised: 05/12/2023] [Accepted: 05/31/2023] [Indexed: 06/04/2023]
Abstract
BACKGROUND Ambient air pollutant exposure can change the composition of gut microbiota at 6-months of age, but there is no epidemiological evidence on the impacts of exposure to particulate matter with an aerodynamic diameter ≤1 μm (PM1) during pregnancy on gut microbiota in mothers and neonates. We aimed to determine if gestational PM1 exposure is associated with the gut microbiota of mothers and neonates. METHODS Leveraging a mother-infant cohort from the central region of China, we estimated the exposure concentrations of PM1 during pregnancy based on residential address records. The gut microbiota of mothers and neonates was analyzed using 16 S rRNA V3-V4 gene sequences. Functional pathway analyses of 16 S rRNA V3-V4 bacterial communities were conducted using Tax4fun. The impact of PM1 exposure on α-diversity, composition, and function of gut microbiota in mothers and neonates was evaluated using multiple linear regression, controlling for nitrogen dioxide (NO2) and ozone (O3). Permutation multivariate analysis of variance (PERMANOVA) was used to analyze the interpretation degree of PM1 on the sample differences at the OTU level using the Bray-Curtis distance algorithm. RESULTS Gestational PM1 exposure was positively associated with the α-diversity of gut microbiota in neonates and explained 14.8% (adj. P = 0.026) of the differences in community composition among neonatal samples. In contrast, gestational PM1 exposure had no impact on the α- and β-diversity of gut microbiota in mothers. Gestational PM1 exposure was positively associated with phylum Actinobacteria of gut microbiota in mothers, and genera Clostridium_sensu_stricto_1, Streptococcus, Faecalibacterium of gut microbiota in neonates. At Kyoto Encyclopedia of Genes and Genomes pathway level 3, the functional analysis results showed that gestational PM1 exposure significantly down-regulated Nitrogen metabolism in mothers, as well as Two-component system and Pyruvate metabolism in neonates. While Purine metabolism, Aminoacyl-tRNA biosynthesis, Pyrimidine metabolism, and Ribosome in neonates were significantly up-regulated. CONCLUSIONS Our study provides the first evidence that exposure to PM1 has a significant impact on the gut microbiota of mothers and neonates, especially on the diversity, composition, and function of neonatal meconium microbiota, which may have important significance for maternal health management in the future.
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Affiliation(s)
- Yanan Cao
- School of Public Health, Wuhan University, Wuhan, 430071, China
| | - Tianzi Zang
- Center for Women's and Children's Health, Wuhan University School of Nursing, Wuhan University, Wuhan, 430071, China
| | - Tianlai Qiu
- Center for Women's and Children's Health, Wuhan University School of Nursing, Wuhan University, Wuhan, 430071, China
| | - Zhihu Xu
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing, 100191, China
| | - Xiangxu Chen
- Center for Women's and Children's Health, Wuhan University School of Nursing, Wuhan University, Wuhan, 430071, China
| | - Xiaoxiao Fan
- Center for Women's and Children's Health, Wuhan University School of Nursing, Wuhan University, Wuhan, 430071, China
| | - Qianping Zhang
- Center for Women's and Children's Health, Wuhan University School of Nursing, Wuhan University, Wuhan, 430071, China
| | - Yingjuan Huang
- Center for Women's and Children's Health, Wuhan University School of Nursing, Wuhan University, Wuhan, 430071, China
| | - Jun Liu
- Center for Women's and Children's Health, Wuhan University School of Nursing, Wuhan University, Wuhan, 430071, China
| | - Ni Wu
- Center for Women's and Children's Health, Wuhan University School of Nursing, Wuhan University, Wuhan, 430071, China
| | - Natalie Shen
- Emory University Rollins School of Public Health, 1520 Clifton Road, Atlanta, GA, 30322, USA
| | - Jinbing Bai
- Emory University Nell Hodgson Woodruff School of Nursing, 1520 Clifton Road, Atlanta, GA, 30322, USA
| | - Guoxing Li
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing, 100191, China
| | - Jing Huang
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing, 100191, China.
| | - Yanqun Liu
- Center for Women's and Children's Health, Wuhan University School of Nursing, Wuhan University, Wuhan, 430071, China.
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23
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Cheng J, Zheng H, Wei J, Huang C, Ho HC, Sun S, Phung D, Kim H, Wang X, Bai Z, Hossain MZ, Tong S, Su H, Xu Z. Short-term residential exposure to air pollution and risk of acute myocardial infarction deaths at home in China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:76881-76890. [PMID: 37247141 PMCID: PMC10300167 DOI: 10.1007/s11356-023-27813-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 05/17/2023] [Indexed: 05/30/2023]
Abstract
Air pollution remains a major threat to cardiovascular health and most acute myocardial infarction (AMI) deaths occur at home. However, currently established knowledge on the deleterious effect of air pollution on AMI has been limited to routinely monitored air pollutants and overlooked the place of death. In this study, we examined the association between short-term residential exposure to China's routinely monitored and unmonitored air pollutants and the risk of AMI deaths at home. A time-stratified case-crossover analysis was undertaken to associate short-term residential exposure to air pollution with 0.1 million AMI deaths at home in Jiangsu Province (China) during 2016-2019. Individual-level residential exposure to five unmonitored and monitored air pollutants including PM1 (particulate matter with an aerodynamic diameter ≤ 1 μm) and PM2.5 (particulate matter with an aerodynamic diameter ≤ 2.5 μm), SO2 (sulfur dioxide), NO2 (nitrogen dioxide), and O3 (ozone) was estimated from satellite remote sensing and machine learning technique. We found that exposure to five air pollutants, even below the recently released stricter air quality standards of the World Health Organization (WHO), was all associated with increased odds of AMI deaths at home. The odds of AMI deaths increased by 20% (95% confidence interval: 8 to 33%), 22% (12 to 33%), 14% (2 to 27%), 13% (3 to 25%), and 7% (3 to 12%) for an interquartile range increase in PM1, PM2.5, SO2, NO2, and O3, respectively. A greater magnitude of association between NO2 or O3 and AMI deaths was observed in females and in the warm season. The greatest association between PM1 and AMI deaths was found in individuals aged ≤ 64 years. This study for the first time suggests that residential exposure to routinely monitored and unmonitored air pollutants, even below the newest WHO air quality standards, is still associated with higher odds of AMI deaths at home. Future studies are warranted to understand the biological mechanisms behind the triggering of AMI deaths by air pollution exposure, to develop intervention strategies to reduce AMI deaths triggered by air pollution exposure, and to evaluate the cost-effectiveness, accessibility, and sustainability of these intervention strategies.
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Affiliation(s)
- Jian Cheng
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China
- Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, China
| | - Hao Zheng
- Department of Environmental Health, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA
| | - Cunrui Huang
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Hung Chak Ho
- Department of Public and International Affairs, City University of Hong Kong , Hong Kong, China
| | - Shengzhi Sun
- School of Public Health, Capital Medical University, Beijing, China
| | - Dung Phung
- School of Public Health, Faculty of Medicine, University of Queensland, Brisbane, Australia
| | - Ho Kim
- Department of Public Health Science, Graduate School of Public Health, Seoul National University, Seoul, Republic of Korea
- Institute of Health and Environment and Graduate School of Public Health, Seoul National University, Seoul, Republic of Korea
| | - Xiling Wang
- School of Public Health, Fudan University, Shanghai, China
- Shanghai Key Laboratory of Meteorology and Health, Shanghai Meteorological Service, Shanghai, China
| | - Zhongliang Bai
- School of Health Services Management, Anhui Medical University, Hefei, China
| | - Mohammad Zahid Hossain
- International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh
| | - Shilu Tong
- Department of Clinical Epidemiology and Biostatistics, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
- School of Public Health, Institute of Environment and Population Health, Anhui Medical University, Hefei, China
- Center for Global Health, Nanjing Medical University, Nanjing, China
- School of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia
| | - Hong Su
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China
- Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, China
| | - Zhiwei Xu
- School of Medicine and Dentistry, Griffith University, Gold Coast, Queensland, 4222, Australia.
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24
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Zhang M, Yang BY, Zhang Y, Sun Y, Liu R, Zhang Y, Su S, Zhang E, Zhao X, Chen G, Wu Q, Hu L, Zhang Y, Wang L, Luo Y, Liu X, Li J, Wu S, Mi X, Zhang W, Dong G, Yin C, Yue W. Association of ambient PM 1 exposure with maternal blood pressure and hypertensive disorders of pregnancy in China. iScience 2023; 26:106863. [PMID: 37255659 PMCID: PMC10225929 DOI: 10.1016/j.isci.2023.106863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 03/30/2023] [Accepted: 05/08/2023] [Indexed: 06/01/2023] Open
Abstract
Evidence concerning PM1 exposure, maternal blood pressure (BP), and hypertensive disorders of pregnancy (HDP) is sparse. We evaluated the associations using 105,063 participants from a nationwide cohort. PM1 concentrations were evaluated using generalized additive model. BP was measured according to the American Heart Association recommendations. Generalized linear mixed models were used to assess the PM1-BP/HDP associations. Each 10 μg/m3 higher first-trimester PM1 was significantly associated with 1.696 mmHg and 1.056 mmHg higher first-trimester SBP and DBP, and with 11.4% higher odds for HDP, respectively. The above associations were stronger among older participants (> 35 years) or those educated longer than 17 years or those with higher household annual income (> 400,000 CNY). To conclude, first-trimester PM1 were positively associated with BP/HDP, which may be modified by maternal age, education level, and household annual income. Further research is warranted to provide more information for both health management of HDP and environmental policies enactment.
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Affiliation(s)
- Man Zhang
- Central Laboratory, Beijing Obstetrics and Gynecology Hospital, Capital Medical University. Beijing Maternal and Child Health Care Hospital, Beijing 100026, China
| | - Bo-Yi Yang
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Yuqin Zhang
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Yongqing Sun
- Prenatal Diagnosis Center, Beijing Obstetrics and Gynecology Hospital, Capital Medical University. Beijing Maternal and Child Health Care Hospital, Beijing 100026, China
| | - Ruixia Liu
- Central Laboratory, Beijing Obstetrics and Gynecology Hospital, Capital Medical University. Beijing Maternal and Child Health Care Hospital, Beijing 100026, China
| | - Yue Zhang
- Central Laboratory, Beijing Obstetrics and Gynecology Hospital, Capital Medical University. Beijing Maternal and Child Health Care Hospital, Beijing 100026, China
| | - Shaofei Su
- Central Laboratory, Beijing Obstetrics and Gynecology Hospital, Capital Medical University. Beijing Maternal and Child Health Care Hospital, Beijing 100026, China
| | - Enjie Zhang
- Central Laboratory, Beijing Obstetrics and Gynecology Hospital, Capital Medical University. Beijing Maternal and Child Health Care Hospital, Beijing 100026, China
| | - Xiaoting Zhao
- Central Laboratory, Beijing Obstetrics and Gynecology Hospital, Capital Medical University. Beijing Maternal and Child Health Care Hospital, Beijing 100026, China
| | - Gongbo Chen
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Qizhen Wu
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Lixin Hu
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Yunting Zhang
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Lebing Wang
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Yana Luo
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Xiaoxuan Liu
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Jiaxin Li
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Sihan Wu
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Xin Mi
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Preventive Medicine, 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
| | - Guanghui Dong
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Chenghong Yin
- Prenatal Diagnosis Center, Beijing Obstetrics and Gynecology Hospital, Capital Medical University. Beijing Maternal and Child Health Care Hospital, Beijing 100026, China
| | - Wentao Yue
- Central Laboratory, Beijing Obstetrics and Gynecology Hospital, Capital Medical University. Beijing Maternal and Child Health Care Hospital, Beijing 100026, China
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Lyu J, Chen D, Zhang X, Yan J, Shen G, Yin S. Coagulation effect of atmospheric submicron particles on plant leaves: Key functional characteristics and a comparison with dry deposition. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 868:161582. [PMID: 36640873 DOI: 10.1016/j.scitotenv.2023.161582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 12/23/2022] [Accepted: 01/09/2023] [Indexed: 06/17/2023]
Abstract
Submicron particles have become a new focus in research on air pollution control. The abilities of urban tree species to retain particles can be used to alleviate urban haze pollution. However, research has focused mostly on plants and environmental conditions rather than on particle itself. Particle migration and transformation at the leaf-air interface are the key to dust retention. Submicron particles coagulate when they are retained by leaves. In this study, NaCl was used to simulate submicron particles. The average sizes of the particles on the leaves of 10 greening tree species in Shanghai in different seasons were measured using the sweep-resuspension method to characterize the coagulation effect. Thereafter, the effects of leaf characteristics were investigated and analyzed in relation to dry deposition velocity. The results indicated that the particles on the leaves of Ginkgo biloba, Osmanthus fragrans, Sabina chinensis (L.) Ant. "Kaizuca," Cinnamomum camphora, and Metasequoia glyptostroboides were large. The seasonal variability of the sizes of the particles on the leaves of different tree species varied. The average particle size was positively correlated with wax content and negatively correlated with single leaf area; however, the other factors correlated with particle size varied by season. For example, in April, the average particle size was positively correlated with tensile strength, wind resistance, adaxial epidermal roughness, and water potential, whereas the effects of stomatal conductance were more complex. Non-significant correlation was identified between coagulation and dry deposition although both were positively correlated with roughness and wax content. This study explored the effects of leaf characteristics on coagulation. The results may serve as a theoretical foundation for explaining the microscopic process underlying dust retention in plants and may provide a clearer scientific basis for the prevention and control of submicron particle pollution and the selection of urban greening tree species.
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Affiliation(s)
- Junyao Lyu
- School of Agriculture and Biology, Shanghai Jiao Tong University, 800 Dongchuan Rd., Shanghai 200240, China; Shanghai Yangtze River Delta Eco-Environmental Change and Management Observation and Research Station, Ministry of Science and Technology, Ministry of Education, 800 Dongchuan Rd., Shanghai 200240, China; Shanghai Urban Forest Ecosystem Research Station, National Forestry and Grassland Administration, 800 Dongchuan Rd., Shanghai 200240, China
| | - Dele Chen
- School of Agriculture and Biology, Shanghai Jiao Tong University, 800 Dongchuan Rd., Shanghai 200240, China; Shanghai Yangtze River Delta Eco-Environmental Change and Management Observation and Research Station, Ministry of Science and Technology, Ministry of Education, 800 Dongchuan Rd., Shanghai 200240, China; Shanghai Urban Forest Ecosystem Research Station, National Forestry and Grassland Administration, 800 Dongchuan Rd., Shanghai 200240, China
| | - Xuyi Zhang
- School of Agriculture and Biology, Shanghai Jiao Tong University, 800 Dongchuan Rd., Shanghai 200240, China; Shanghai Yangtze River Delta Eco-Environmental Change and Management Observation and Research Station, Ministry of Science and Technology, Ministry of Education, 800 Dongchuan Rd., Shanghai 200240, China; Shanghai Urban Forest Ecosystem Research Station, National Forestry and Grassland Administration, 800 Dongchuan Rd., Shanghai 200240, China
| | - Jingli Yan
- School of Agriculture and Biology, Shanghai Jiao Tong University, 800 Dongchuan Rd., Shanghai 200240, China; Shanghai Yangtze River Delta Eco-Environmental Change and Management Observation and Research Station, Ministry of Science and Technology, Ministry of Education, 800 Dongchuan Rd., Shanghai 200240, China; Shanghai Urban Forest Ecosystem Research Station, National Forestry and Grassland Administration, 800 Dongchuan Rd., Shanghai 200240, China
| | - Guangrong Shen
- School of Agriculture and Biology, Shanghai Jiao Tong University, 800 Dongchuan Rd., Shanghai 200240, China; Shanghai Yangtze River Delta Eco-Environmental Change and Management Observation and Research Station, Ministry of Science and Technology, Ministry of Education, 800 Dongchuan Rd., Shanghai 200240, China; Shanghai Urban Forest Ecosystem Research Station, National Forestry and Grassland Administration, 800 Dongchuan Rd., Shanghai 200240, China
| | - Shan Yin
- School of Agriculture and Biology, Shanghai Jiao Tong University, 800 Dongchuan Rd., Shanghai 200240, China; Shanghai Yangtze River Delta Eco-Environmental Change and Management Observation and Research Station, Ministry of Science and Technology, Ministry of Education, 800 Dongchuan Rd., Shanghai 200240, China; Shanghai Urban Forest Ecosystem Research Station, National Forestry and Grassland Administration, 800 Dongchuan Rd., Shanghai 200240, China; Key Laboratory for Urban Agriculture, Ministry of Agriculture and Rural Affairs, 800 Dongchuan Rd., Shanghai 200240, China.
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26
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Guo J, Chai G, Song X, Hui X, Li Z, Feng X, Yang K. Long-term exposure to particulate matter on cardiovascular and respiratory diseases in low- and middle-income countries: A systematic review and meta-analysis. Front Public Health 2023; 11:1134341. [PMID: 37056647 PMCID: PMC10089304 DOI: 10.3389/fpubh.2023.1134341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Accepted: 02/28/2023] [Indexed: 03/30/2023] Open
Abstract
BackgroundLong-term exposure to particulate matter (PM) has essential and profound effects on human health, but most current studies focus on high-income countries. Evidence of the correlations between PM and health effects in low- and middle-income countries (LMICs), especially the risk factor PM1 (particles < 1 μm in size), remains unclear.ObjectiveTo explore the effects of long-term exposure to particulate matter on the morbidity and mortality of cardiovascular and respiratory diseases in LMICs.MethodsA systematic search was conducted in the PubMed, Web of Science, and Embase databases from inception to May 1, 2022. Cohort studies and case-control studies that examine the effects of PM1, PM2.5, and PM10 on the morbidity and mortality of cardiovascular and respiratory diseases in LMICs were included. Two reviewers independently selected the studies, extracted the data, and assessed the risk of bias. Outcomes were analyzed via a random effects model and are reported as the relative risk (RR) with 95% CI.ResultsOf the 1,978 studies that were identified, 38 met all the eligibility criteria. The studies indicated that long-term exposure to PM2.5, PM10, and PM1 was associated with cardiovascular and respiratory diseases: (1) Long-term exposure to PM2.5 was associated with an increased risk of cardiovascular morbidity (RR per 1.11 μg/m3, 95% CI: 1.05, 1.17) and mortality (RR per 1.10 μg/m3, 95% CI: 1.06, 1.14) and was significantly associated with respiratory mortality (RR 1.31, 95% CI: 1.25, 1.38) and morbidity (RR 1.08, 95% CI: 1.02, 1.04); (2) An increased risk of respiratory mortality was observed in the elderly (65+ years) (RR 1.21, 95% CI: 1.00, 1.47) with long-term exposure to PM2.5; (3) Long-term exposure to PM10 was associated with cardiovascular morbidity (RR 1.07, 95% CI 1.01, 1.13), respiratory morbidity (RR 1.43, 95% CI: 1.21, 1.69) and respiratory mortality (RR 1.28, 95% CI 1.10, 1.49); (4) A significant association between long-term exposure to PM1 and cardiovascular disease was also observed.ConclusionsLong-term exposure to PM2.5, PM10 and PM1 was all related to cardiovascular and respiratory disease events. PM2.5 had a greater effect than PM10, especially on respiratory diseases, and the risk of respiratory mortality was significantly higher for LMICs than high-income countries. More studies are needed to confirm the effect of PM1 on cardiovascular and respiratory diseases.
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Affiliation(s)
- Juanmei Guo
- School of Management, Lanzhou University, Lanzhou, China
| | - Guorong Chai
- School of Management, Lanzhou University, Lanzhou, China
- *Correspondence: Guorong Chai
| | - Xuping Song
- Evidence-based Social Sciences Research Center, School of Public Health, Lanzhou University, Lanzhou, China
- Key Laboratory of Evidence-Based Medicine and Knowledge Translation of Gansu Province, Lanzhou, China
- Xuping Song
| | - Xu Hui
- Evidence-based Social Sciences Research Center, School of Public Health, Lanzhou University, Lanzhou, China
- Key Laboratory of Evidence-Based Medicine and Knowledge Translation of Gansu Province, Lanzhou, China
| | - Zhihong Li
- Evidence-based Social Sciences Research Center, School of Public Health, Lanzhou University, Lanzhou, China
- Key Laboratory of Evidence-Based Medicine and Knowledge Translation of Gansu Province, Lanzhou, China
| | - Xiaowen Feng
- Evidence-based Social Sciences Research Center, School of Public Health, Lanzhou University, Lanzhou, China
| | - Kehu Yang
- Evidence-based Social Sciences Research Center, School of Public Health, Lanzhou University, Lanzhou, China
- Key Laboratory of Evidence-Based Medicine and Knowledge Translation of Gansu Province, Lanzhou, China
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Li Y, Zhu L, Wang Y, Tang Z, Huang Y, Wang Y, Zhang J, Zhang Y. Emergency Department Visits in Children Associated with Exposure to Ambient PM 1 within Several Hours. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:4910. [PMID: 36981834 PMCID: PMC10049417 DOI: 10.3390/ijerph20064910] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 03/02/2023] [Accepted: 03/08/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Emerging evidence has integrated short-term exposure to PM1 with children's morbidity and mortality. Nevertheless, most available studies have been conducted on a daily scale, ignoring the exposure variations over the span of a day. OBJECTIVE The main intention of this study was to examine the association between pediatric emergency department visits (PEDVs) and intra-day exposures to PM1 and PM2.5. We also aimed to investigate whether a high PM1/PM2.5 ratio elevated the risk of PEDVs independent from PM2.5 exposure within several hours. METHODS We collected hourly data on aerial PM1 and PM2.5 concentrations, all-cause PEDVs, and meteorological factors from two megacities (i.e., Guangzhou and Shenzhen) in southern China during 2015-2016. Time-stratified case-crossover design and conditional logistic regression analysis were used to assess the associations of PEDVs with exposures to PM1 and PM2.5 at different lag hours. The contribution of PM1 to PM2.5-associated risk was quantified by introducing PM1/PM2.5 ratio as an additional exposure indicator in the analysis adjusting for PM2.5. Subgroup analyses were performed stratified by sex, age, and season. RESULTS During this study period, 97,508 and 101,639 children were included from Guangzhou and Shenzhen, respectively. PM1 and PM2.5 exposures within several hours were both remarkably related to an increased risk of PEDVs. Risks for PEDVs increased by 3.9% (95% confidence interval [CI]: 2.7-5.0%) in Guangzhou and 3.2% (95% CI: 1.9-4.4%) in Shenzhen for each interquartile range (Guangzhou: 21.4 μg/m3, Shenzhen: 15.9 μg/m3) increase in PM1 at lag 0-3 h, respectively. A high PM1/PM2.5 ratio was substantially correlated with increased PEDVs, with an excess risk of 2.6% (95% CI: 1.2-4.0%) at lag 73-96 h in Guangzhou and 1.2% (95% CI: 0.4-2.0%) at lag 0-3 h in Shenzhen. Stratified analysis showed a clear seasonal pattern in PM-PEDVs relationships, with notably stronger risks in cold months (October to March of the following year) than in warm months (April to September). CONCLUSIONS Exposures to ambient PM1 and PM2.5 within several hours were related to increased PEDVs. A high PM1/PM2.5 ratio may contribute an additional risk independent from the short-term impacts of PM2.5. These findings highlighted the significance of reducing PM1 in minimizing health risks due to PM2.5 exposure in children.
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Nie C, Li Z, Yang T, Zhong J, Liu Q, Mi F, Yu J, Pan Y, Kan H, Hong F. Associations of long-term exposure to particulate matter with gallstone risks in Chinese adults: A large cross-sectional study. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 252:114644. [PMID: 36791505 DOI: 10.1016/j.ecoenv.2023.114644] [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: 12/02/2022] [Revised: 02/10/2023] [Accepted: 02/11/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Epidemiological evidence regarding the relation of exposure to ambient particulate matter (PM) with gallstone disease (GSD) risk remains lacking. We tested the hypothesis that long-term exposure to PM is related to the development of GSD and that dyslipidemia can mediate the effect of PM-associated GSD formation. METHODS We extracted related information on the basis of the baseline survey of the China Multi-Ethnic Cohort Study. The exposure levels of PM (PM1, PM2.5, and PM10) were assessed by validated spatiotemporal models. The relation of exposure to ambient PM with GSD risks was analyzed by non-conditional logistic regression models. Additionally, mediation analysis was conducted to assess whether dyslipidemia was related to the relation of PM exposure with GSD risks. RESULTS A total of 72,893 participants were included. Increased ambient PM exposure was positively associated with a higher GSD risk, with ORs (and 95% CI) of 1.17 (1.06, 1.28), 1.10 (1.05, 1.15), and 1.07 (1.04, 1.10) for every 10 μg/m3 increment in PM1, PM2.5, and PM10, separately. The association was more remarkable in males, drinkers, and central obesity participants. Dyslipidemia significantly mediated the association between PM and GSD, with mediating proportions of 5.37%, 9.13%, and 7.66% in PM1, PM2.5, and PM10, respectively. CONCLUSION Exposure to PM may relate to the increased risk of GSD in Chinese adults, especially among males, drinkers, and central obesity participants. Dyslipidemia may partially mediate the effect of PM-associated GSD development. Our results might provide epidemiological evidence for the progression of GSD related to PM and give new insights into GSD prevention and screening priorities.
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Affiliation(s)
- Chan Nie
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guizhou, Guiyang 550025, China
| | - Zhifeng Li
- Chongqing Center for Disease Control and Prevention, Chongqing 400042, China.
| | - Tingting Yang
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guizhou, Guiyang 550025, China
| | - Jianqin Zhong
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guizhou, Guiyang 550025, China
| | - Qiaolan Liu
- Sichuan University West China School of Public Health, Sichuan, Chengdu 610000, China
| | - Fei Mi
- School of Public Health, Kunming Medical University, Yunnan, Kunming 650000, China
| | - Jianhong Yu
- Pidu District Center for Disease Control and Prevention, Sichuan, Chengdu 611700, China
| | - Yongyue Pan
- School of Medicine, Tibet University, Lhasa, Tibet 850000, China
| | - Haidong Kan
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and Key Lab of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai 200032, China; Children's Hospital of Fudan University, National Center for Children's Health, Shanghai 200032, China.
| | - Feng Hong
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guizhou, Guiyang 550025, China.
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Zhang F, Tang H, Zhao D, Zhang X, Zhu S, Zhao G, Zhang X, Li T, Wei J, Li D, Zhu W. Short-term exposure to ambient particulate matter and mortality among HIV/AIDS patients: Case-crossover evidence from all counties of Hubei province, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 857:159410. [PMID: 36257445 DOI: 10.1016/j.scitotenv.2022.159410] [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: 07/10/2022] [Revised: 09/28/2022] [Accepted: 10/09/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) has been a worrisome public health problem in the world. However, evidence for associations between short-term exposure to particulate matter (PM) and mortality among HIV/AIDS patients is scarce. METHODS We collected daily death records in people with HIV/AIDS from all counties (N = 103) of Hubei province, China from 2018 to 2019. The county-level daily concentrations of PM1, PM2.5 and PM10 in the same period were extracted from ChinaHighAirPollutants dataset. A time-stratified case-crossover design with conditional logistic regression analysis was performed to assess the associations between PM and mortality. RESULTS Each 1 μg/m3 increased in PM1 corresponded with 0.89 % elevated in all-cause deaths (ACD) at lag 0-4 days. The largest effects of PM1, PM2.5 and PM10 on AIDS-related deaths (ARD) were detected at lag 0-4 days, and PM1 [percent changes in odds ratio: 2.51 % (95 % CIs: 0.82, 4.22)] appeared greater health hazards than PM2.5 [1.24 % (95 % CIs: 0.33, 2.15)] as well as PM10 [0.65 % (95 % CIs: 0.01, 1.30)]. In subgroup analyses, the significant associations of PM1/PM2.5 and ACD were only found in male and the cold season. We also observed the effects of PM1 and PM10 on ARD were significantly stronger (P for interaction <0.05) in males than females. In addition, we caught sight of HIV/AIDS patients aged over 60 years old were more susceptible to ARD caused by PM than younger population. CONCLUSIONS Our study suggested PM1 was positively linked with the risk of ACD and ARD. Male patients with HIV/AIDS were more significantly susceptible to PM1, PM2.5 and PM10. PM1/PM2.5 appeared stronger associations with ARD in HIV/AIDS patients aged over 60 years old and in the cold season.
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Affiliation(s)
- Faxue Zhang
- Department of Occupational and Environmental Health, School of Public Health, Wuhan University, Wuhan 430071, China
| | - Hen Tang
- Institute of Chronic Infectious Disease Prevention and Control, Hubei Provincial Center for Disease Control and Prevention, Wuhan 430079, China
| | - Dingyuan Zhao
- Institute of Chronic Infectious Disease Prevention and Control, Hubei Provincial Center for Disease Control and Prevention, Wuhan 430079, China
| | - Xupeng Zhang
- Department of Public Health, School of Public Health, Wuhan University, Wuhan 430071, China
| | - Shijie Zhu
- Department of Occupational and Environmental Health, School of Public Health, Wuhan University, Wuhan 430071, China
| | - Gaichan Zhao
- Department of Public Health, School of Public Health, Wuhan University, Wuhan 430071, China
| | - Xiaowei Zhang
- Department of Occupational and Environmental Health, School of Public Health, Wuhan University, Wuhan 430071, China
| | - Tianzhou Li
- Department of Occupational and Environmental Health, School of Public Health, Wuhan University, Wuhan 430071, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20740, USA.
| | - Dejia Li
- Department of Occupational and Environmental Health, School of Public Health, Wuhan University, Wuhan 430071, China.
| | - Wei Zhu
- Department of Occupational and Environmental Health, School of Public Health, Wuhan University, Wuhan 430071, China.
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Young LH, Hsu CS, Hsiao TC, Lin NH, Tsay SC, Lin TH, Lin WY, Jung CR. Sources, transport, and visibility impact of ambient submicrometer particle number size distributions in an urban area of central Taiwan. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 856:159070. [PMID: 36179847 DOI: 10.1016/j.scitotenv.2022.159070] [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: 07/11/2022] [Revised: 09/08/2022] [Accepted: 09/23/2022] [Indexed: 06/16/2023]
Abstract
This study applied positive matrix factorization (PMF) to identify the sources of size-resolved submicrometer (10-1000 nm) particles and quantify their contributions to impaired visibility based on the particle number size distributions (PNSDs), aerosol light extinction (bp), air pollutants (PM10, PM2.5, SO2, O3, and NO), and meteorological parameters (temperature, relative humidity, wind speed, wind direction, and ultraviolet index) measured hourly over an urban basin in central Taiwan between 2017 and 2021. The transport of source-specific PNSDs was evaluated with wind and back trajectory analyses. The PMF revealed six sources to the total particle number (TPN), surface (TPS), volume (TPV), and bp. Factor 1 (F1), the key contributor to TPN (35.0 %), represented nucleation (<25 nm) particles associated with fresh traffic emission and secondary new particle formation, which were transported from the west-southwest by stronger winds (>2.2 m s-1). F2 represented the large Aitken (50-100 nm) particles transported regionally via northerly winds, whereas F3 represented large accumulation (300-1000 nm) particles, which showed elevated concentrations under stagnant conditions (<1.1 m s-1). F4 represented small Aitken (25-50 nm) particles arising from the growth and transport of the nucleation particles (F1) via west-southwesterly winds. F5 represented large Aitken particles originating from combustion-related SO2 sources and carried by west-northwesterly winds. F6 represented small accumulation (100-300 nm) particles emitted both by local sources and by the remote SO2 sources found for F5. Overall, large accumulation particles (F3) played the greatest role in determining the TPV (66.4 %) and TPS (34.8 %), and their contribution to bp increased markedly from 17.3 % to 40.7 % as visibility decreased, indicating that TPV and TPS are better metrics than TPN for estimating bp. Furthermore, slow-moving air masses-and therefore stagnant conditions-facilitate the build-up of accumulation mode particles (F3 + F6), resulting in the poorest visibility.
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Affiliation(s)
- Li-Hao Young
- Department of Occupational Safety and Health, China Medical University, 100, Sec. 1, Jingmao Rd., Beitun Dist., Taichung 406040, Taiwan.
| | - Chih-Sheng Hsu
- Department of Occupational Safety and Health, China Medical University, 100, Sec. 1, Jingmao Rd., Beitun Dist., Taichung 406040, Taiwan
| | - Ta-Chih Hsiao
- Graduate Institute of Environmental Engineering, National Taiwan University, 1, Sec. 4, Roosevelt Rd., Taipei 10617, Taiwan
| | - Neng-Huei Lin
- Department of Atmospheric Sciences, National Central University, 300, Zhongda Rd., Zhongli Dist., Taoyuan 320317, Taiwan
| | - Si-Chee Tsay
- NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
| | - Tang-Huang Lin
- Center for Space and Remote Sensing Research, National Central University, 300, Zhongda Rd., Zhongli Dist., Taoyuan 320317, Taiwan
| | - Wen-Yinn Lin
- Institute of Environmental Engineering and Management, National Taipei University of Technology, 1, Sec. 3, Chung-Hsiao E. Rd., Taipei 106344, Taiwan
| | - Chau-Ren Jung
- Department of Public Health, China Medical University, 100, Sec. 1, Jingmao Rd., Beitun Dist., Taichung 406040, Taiwan
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Wang Y, Wei J, Zhang Y, Guo T, Chen S, Wu W, Chen S, Li Z, Qu Y, Xiao J, Deng X, Liu Y, Du Z, Zhang W, Hao Y. Estimating causal links of long-term exposure to particulate matters with all-cause mortality in South China. ENVIRONMENT INTERNATIONAL 2023; 171:107726. [PMID: 36638656 DOI: 10.1016/j.envint.2022.107726] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 12/03/2022] [Accepted: 12/29/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND The association between long-term particulate matter (PM) exposure and all-cause mortality has been well-documented. However, evidence is still limited from high-exposed cohorts, especially for PM1 which is smaller while more toxic than other commonly investigated particles. We aimed to examine the potential casual links of long-term PMs exposure with all-cause mortality in high-exposed areas. METHODS A total of 580,757 participants in southern China were enrolled during 2009-2015 and followed up to 2020. The annual average concentration of PM1, PM2.5, and PM10 at 1 km2 spatial resolution was assessed for each residential address through validated spatiotemporal models. We used marginal structural Cox models to estimate the PM-mortality associations which were further stratified by sociodemographic, lifestyle factors and general exposure levels. RESULTS 37,578 deaths were totally identified during averagely 8.0 years of follow-up. Increased exposure to all 3 PM size fractions were significantly associated with increased risk of all-cause mortality, with hazard ratios (HRs) of 1.042 (95 % confidence interval (CI): 1.037-1.046), 1.031 (95 % CI: 1.028-1.033), and 1.029 (95 % CI: 1.027-1.031) per 1 μg/m3 increase in PM1, PM2.5, and PM10 concentrations, respectively. We observed greater effect estimates among the elderly (age ≥ 65 years), unmarried participants, and those with low education attainment. Additionally, the effect of PM1, PM2.5, and PM10 tend to be higher in the low-exposure group than in the general population. CONCLUSIONS We provided comprehensive evidence for the potential causal links betweenlong-term PM exposureand all-cause mortality, and suggested stronger links for PM1compared to large particles and among certain vulnerable subgroups.
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Affiliation(s)
- Ying Wang
- 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, USA
| | - 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
| | - 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
| | - 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
| | - 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
| | - Shimin 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
| | - Ziqiang Li
- Department of Preventive Medicine, School of Basic Medicine and Public Health, Jinan University, Guangzhou, China
| | - Yanji Qu
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangzhou, China
| | - Jianpeng Xiao
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Xinlei Deng
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA
| | - Yu Liu
- 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
| | - Zhicheng Du
- 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.
| | - 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, Beijing, China.
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Fu N, Kim MK, Huang L, Liu J, Chen B, Sharples S. Experimental and numerical analysis of indoor air quality affected by outdoor air particulate levels (PM 1.0, PM 2.5 and PM 10), room infiltration rate, and occupants' behaviour. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 851:158026. [PMID: 35973538 DOI: 10.1016/j.scitotenv.2022.158026] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 08/10/2022] [Accepted: 08/10/2022] [Indexed: 06/15/2023]
Abstract
This study conducted an experimental analysis of how indoor air quality (IAQ) is influenced by the outdoor air pollutants levels, infiltration rate, and occupants' behaviours. The impacts of these factors on IAQ were analyzed using on-site measurements and numerical simulations. The results contribute to a better understanding of how to control the Indoor Particulate Level (IPL) for the specific conditions of the studied building. Results showed that occupant behaviour was the primary factor in determining the IPL, significantly changing the number of outdoor particles introduced to the building. Moreover, it was found that the IPL was exponentially correlated to the Outdoor Particulate Level (OPL). Based on numerical simulations, this study concluded that smaller particles do not always have more chance than larger particles of accessing the indoor environment through the building envelope. Meanwhile, a steady-state indoor particle concentration numerical model was established and verified using the 4-fold cross-validation method. Finally, simulation results identified that the room infiltration rate had a positive linear impact on IAQ if the OPL was under 30 μg/m3. This is because the increased air exchange rate can help to dilute indoor air pollutants when the outdoor air is relatively clean.
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Affiliation(s)
- Nuodi Fu
- Department of Architecture, Xi'an Jiaotong - Liverpool University, Suzhou 215123, China; School of Architecture, University of Liverpool, Liverpool L69 7ZX, United Kingdom
| | - Moon Keun Kim
- Department of Civil Engineering and Energy Technology, Oslo Metropolitan University, Oslo 0130, Norway.
| | - Long Huang
- School of Intelligent Manufacturing Ecosystem, Xi'an Jiaotong - Liverpool University, Suzhou 215123, China
| | - Jiying Liu
- School of Thermal Engineering, Shandong Jianzhu University, Jinan 250101, China
| | - Bing Chen
- Department of Urban Planning and Design, Xi'an Jiaotong - Liverpool University, Suzhou 215123, China
| | - Stephen Sharples
- School of Architecture, University of Liverpool, Liverpool L69 7ZX, United Kingdom
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Yu X, Wang Q, Wei J, Zeng Q, Xiao L, Ni H, Xu T, Wu H, Guo P, Zhang X. Impacts of traffic-related particulate matter pollution on semen quality: A retrospective cohort study relying on the random forest model in a megacity of South China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 851:158387. [PMID: 36049696 DOI: 10.1016/j.scitotenv.2022.158387] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 08/17/2022] [Accepted: 08/25/2022] [Indexed: 02/05/2023]
Abstract
BACKGROUND Emerging evidence shows the detrimental impacts of particulate matter (PM) on poor semen quality. High-resolution estimates of PM concentrations are conducive to evaluating accurate associations between traffic-related PM exposure and semen quality. METHODS In this study, we firstly developed a random forest model incorporating meteorological factors, land-use information, traffic-related variables, and other spatiotemporal predictors to estimate daily traffic-related PM concentrations, including PM2.5, PM10, and PM1. Then we enrolled 1310 semen donors corresponding to 4912 semen samples during the study period from January 1, 2019, and December 31, 2019 in Guangzhou city, China. Linear mixed models were employed to associate individual exposures to traffic-related PM during the entire (0-90 lag days) and key periods (0-37 and 34-77 lag days) with semen quality parameters, including sperm concentration, sperm count, progressive motility and total motility. RESULTS The results showed that decreased sperm concentration was associated with PM10 exposures (β: -0.21, 95 % CI: -0.35, -0.07), sperm count was inversely related to both PM2.5 (β: -0.19, 95 % CI: -0.35, -0.02) and PM10 (β: -0.19, 95 % CI: -0.33, -0.05) during the 0-90 days lag exposure window. Besides, PM2.5 and PM10 might diminish sperm concentration by mainly affecting the late phase of sperm development (0-37 lag days). Stratified analyses suggested that PBF and drinking seemed to modify the associations between PM exposure and sperm motility. We did not observe any significant associations of PM1 exposures with semen parameters. CONCLUSION Our results indicate that exposure to traffic-related PM2.5 and PM10 pollution throughout spermatogenesis may adversely affect semen quality, especially sperm concentration and count. The findings provided more evidence for the negative associations between traffic-related PM exposure and semen quality, highlighting the necessity to reduce ambient air pollution through environmental policy.
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Affiliation(s)
- Xiaolin Yu
- Department of Preventive Medicine, Shantou University Medical College, No. 22 Xinling Road, Shantou 515041, China
| | - Qiling Wang
- National Health Commission Key Laboratory of Male Reproduction and Genetics, Guangzhou, China; Department of Andrology, Guangdong Provincial Reproductive Science Institute (Guangdong Provincial Fertility Hospital), China
| | - Jing Wei
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China; Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA
| | - Qinghui Zeng
- Department of Preventive Medicine, Shantou University Medical College, No. 22 Xinling Road, Shantou 515041, China
| | - Lina Xiao
- Department of Preventive Medicine, Shantou University Medical College, No. 22 Xinling Road, Shantou 515041, China
| | - Haobo Ni
- Department of Preventive Medicine, Shantou University Medical College, No. 22 Xinling Road, Shantou 515041, China
| | - Ting Xu
- Department of Preventive Medicine, Shantou University Medical College, No. 22 Xinling Road, Shantou 515041, China
| | - Haisheng Wu
- Department of Preventive Medicine, Shantou University Medical College, No. 22 Xinling Road, Shantou 515041, China
| | - Pi Guo
- Department of Preventive Medicine, Shantou University Medical College, No. 22 Xinling Road, Shantou 515041, China
- Guangdong Provincial Key Laboratory of Infectious Diseases and Molecular Immunopathology, Shantou 515041, China
| | - Xinzong Zhang
- National Health Commission Key Laboratory of Male Reproduction and Genetics, Guangzhou, China
- Department of Andrology, Guangdong Provincial Reproductive Science Institute (Guangdong Provincial Fertility Hospital), China
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Han S, Zhang F, Yu H, Wei J, Xue L, Duan Z, Niu Z. Systemic inflammation accelerates the adverse effects of air pollution on metabolic syndrome: Findings from the China health and Retirement Longitudinal Study (CHARLS). ENVIRONMENTAL RESEARCH 2022; 215:114340. [PMID: 36108720 DOI: 10.1016/j.envres.2022.114340] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2022] [Revised: 09/08/2022] [Accepted: 09/10/2022] [Indexed: 06/15/2023]
Abstract
Long-term exposure to air pollution and systemic inflammation are associated with increased prevalence of metabolic syndrome (MetS); however, their joint effects in Chinese middle-aged and older adults is unknown. In this cross-sectional study, 11,838 residents aged 45 years and older from the China Health and Retirement Longitudinal Study (CHARLS) Wave 3 in 2015 were included. MetS was diagnosed using the Joint Interim Societies' definition. C-Reactive Protein (CRP) was assessed to reflect systemic inflammation. Individual exposure to air pollutants (particulate matter with a diameter ≤2.5 μm (PM2.5) or ≤ 10 μm (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and carbon monoxide (CO)) was evaluated using satellite-based spatiotemporal models according to participant residence at county-level. Generalized linear models (GLMs) were applied to examine the association between air pollution and MetS, and the modification effects of CRP between air pollution and MetS were estimated using interaction terms of CRP and air pollutants in the GLM models. The prevalence of MetS was 32.37%. The adjusted odd ratio (OR) of MetS was 1.192 (95% confidence interval (CI): 1.116, 1.272), 1.177 (95% CI: 1.103, 1.255), 1.158 (95% CI: 1.072, 1.252), 1.303 (95% CI: 1.211,1.403), 1.107 (95% CI: 1.046, 1.171) and 1.156 (95% CI:1.083, 1.234), per inter-quartile range increase in PM2.5 (24.04 μg/m3), PM10 (39.00 μg/m3), SO2 (19.05 μg/m3), NO2 (11.28 μg/m3), O3 (9.51 μg/m3) and CO (0.46 mg/m3), respectively. CRP was also associated with increased prevalence of MetS (OR = 1.049, 95% CI: 1.035, 1.064; per 1.90 mg/L increase in CRP). Interaction analysis suggested that high CRP levels enhanced the association between air pollution exposure and MetS. Long-term exposure to air pollution is associated with increased prevalence of MetS, which might be enhanced by systemic inflammation. Given the rapidly aging society and heavy burden of MetS, measures should be taken to improve air quality and reduce systemic inflammation.
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Affiliation(s)
- Shichao Han
- Department of Urology, Xijing Hospital, The Fourth Military Medical University, 127 West Changle Road, Xi'an, 710032, China
| | - Fen Zhang
- Departments of Hepatobiliary Surgery, Xijing Hospital, The Fourth Military Medical University, 127 West Changle Road, Xi'an, 710032, China
| | - Hongmei Yu
- Pukou District Center for Disease Control and Prevention, 120 Puyun Road, Nanjing, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, USA
| | - Lina Xue
- Department of Medical Affairs, Tangdu Hospital, The Fourth Military Medical University, 1 Xinsi Road, Xi'an, China
| | - Zhizhou Duan
- Preventive Health Service, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, 152 Aiguo Road, Nanchang, Jiangxi, China.
| | - Zhiping Niu
- Department of Urology, Xijing Hospital, The Fourth Military Medical University, 127 West Changle Road, Xi'an, 710032, China.
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Liu W, Wei J, Cai M, Qian Z, Long Z, Wang L, Vaughn MG, Aaron HE, Tong X, Li Y, Yin P, Lin H, Zhou M. Particulate matter pollution and asthma mortality in China: A nationwide time-stratified case-crossover study from 2015 to 2020. CHEMOSPHERE 2022; 308:136316. [PMID: 36084833 DOI: 10.1016/j.chemosphere.2022.136316] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 08/10/2022] [Accepted: 08/31/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND A national and comprehensive evaluation is lacking on the relationship between short-term exposure to submicron particulate matter (PM1) pollution and asthma mortality. METHODS Data was obtained from 29,553 asthma deaths from the China National Mortality Surveillance System from 2015 to 2020. We used a bilinear interpolation approach to estimate each participant's daily ambient particulate matter pollution and meteorological variables exposure based on their geocoded residential address and a 10 km × 10 km grid from China High Air Pollutants and the fifth generation of European ReAnalysis-Land reanalysis data set. The associations were estimated using a time-stratified case-crossover design and conditional logistic regressions. RESULTS Our results revealed significant associations between short-term exposure to various particulate matter and asthma mortality. The 5-day moving average of particulate matter exposure produced the most pronounced effect. Compared to fine particulate matter (PM2.5) and inhalable particulate matter (PM10), significantly stronger effects on asthma mortality related to PM1 pollution were noted. The ERs% for asthma mortality associated with each interquartile range (IQR) increase of exposures to PM1 (IQR: 19.2 μg/m3) was 5.59% (95% CI: 2.11-9.19), which is 14% and 22% higher than that for PM2.5 (IQR: 32.0 μg/m3, 4.82% (95% CI: 1.84-7.90)) and PM10 (IQR: 52.2 μg/m3, 4.37% (95% CI: 1.16-7.69)), respectively. The estimates remained consistent in various sensitivity analyses. CONCLUSIONS Our study provided national evidence that acute exposures to various ambient particulate matter pollution can increase mortality due to asthma in China, highlighting stronger associations with ambient PM1 than PM2.5 and PM10. China needs to adjust the current ambient air quality standards urgently and pay greater attention to the adverse health effects of PM1.
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Affiliation(s)
- Wei Liu
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, 20740, USA
| | - Miao Cai
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Zhengmin Qian
- Department of Epidemiology and Biostatistics, College for Public Health & Social Justice, Saint Louis University, Saint Louis, MO, USA
| | - Zheng Long
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Lijun Wang
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Michael G Vaughn
- School of Social Work, College for Public Health & Social Justice, Saint Louis University, Saint Louis, MO, USA
| | - Hannah E Aaron
- Department of Epidemiology and Biostatistics, College for Public Health & Social Justice, Saint Louis University, Saint Louis, MO, USA
| | - Xunliang Tong
- Department of Pulmonary and Critical Care Medicine, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Yanming Li
- Department of Pulmonary and Critical Care Medicine, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Peng Yin
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
| | - Hualiang Lin
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
| | - Maigeng Zhou
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
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Zong Z, Zhao M, Zhang M, Xu K, Zhang Y, Zhang X, Hu C. Association between PM 1 Exposure and Lung Function in Children and Adolescents: A Systematic Review and Meta-Analysis. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:15888. [PMID: 36497960 PMCID: PMC9740616 DOI: 10.3390/ijerph192315888] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 11/23/2022] [Accepted: 11/24/2022] [Indexed: 06/17/2023]
Abstract
The detrimental effects of PM2.5 and PM10 (particulate matter less than 2.5 or 10 μm) on human respiratory system, including lung function, have been widely assessed. However, the associations between PM1 (particulate matter of less than 1 μm) and lung function in children and adolescents are less explored, and current evidence is inconsistent. We conducted a meta-analysis of the literature on the association between PM1 and lung function in children and adolescents to fill this gap. With no date or language constraints, we used a combination of MeSH (Medical Subject Headings) terms and free text to search PubMed, EMBASE and Web of Science databases through, 1 October 2022 for "PM1 exposure" and "lung function". A total of 6420 relevant studies were identified through our initial search, and seven studies were included in our study. In this meta-analysis, the fixed effect and random effects statistical models were used to estimate the synthesized effects of the seven included studies. For every 10 μg/m3 increase in short-term PM1 exposure, forced vital capacity (FVC), forced expiratory volume in the first second (FEV1), peak expiratory flow (PEF) and maximal mid-expiratory flow (MMEF) decreased by 31.82 mL (95% CI: 20.18, 43.45), 32.28 mL (95% CI: 16.73, 48.91), 36.85 mL/s (95% CI: 15.33, 58.38) and 34.51 mL/s (95% CI: 19.61, 49.41), respectively. For each 10 μg/m3 increase in long-term PM1 exposure, FVC, FEV1, PEF and MMEF decreased by 102.34 mL (95% CI: 49.30, 155.38), 75.17 mL (95% CI: 39.61, 110.73), 119.01 mL/s (95% CI: 72.14, 165.88) and 44.94 mL/s (95% CI: 4.70, 85.18), respectively. Our study provides further scientific evidence for the harmful effects of PM1 exposure on lung function in children and adolescents, indicating that exposure to PM1 is detrimental to pulmonary health. To reduce the adverse health effects of air pollution on children and adolescents, effective preventive measures should be taken.
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Affiliation(s)
- Zhiqiang Zong
- Department of Clinical Medicine, The Second School of Clinical Medicine, Anhui Medical University, Hefei 230032, China
| | - Mengjie Zhao
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei 230032, China
| | - Mengyue Zhang
- Department of Clinical Medicine, The Second School of Clinical Medicine, Anhui Medical University, Hefei 230032, China
| | - Kexin Xu
- Department of Clinical Medicine, The Second School of Clinical Medicine, Anhui Medical University, Hefei 230032, China
| | - Yunquan Zhang
- School of Public Health, Wuhan University of Science and Technology, Wuhan 430065, China
| | - Xiujun Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei 230032, China
| | - Chengyang Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei 230032, China
- Department of Humanistic Medicine, School of Humanistic Medicine, Anhui Medical University, Hefei 230032, China
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Zhang Q, Meng X, Shi S, Kan L, Chen R, Kan H. Overview of particulate air pollution and human health in China: Evidence, challenges, and opportunities. Innovation (N Y) 2022; 3:100312. [PMID: 36160941 PMCID: PMC9490194 DOI: 10.1016/j.xinn.2022.100312] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 08/31/2022] [Indexed: 11/25/2022] Open
Abstract
Ambient particulate matter (PM) pollution in China continues to be a major public health challenge. With the release of the new WHO air quality guidelines in 2021, there is an urgent need for China to contemplate a revision of air quality standards (AQS). In the recent decade, there has been an increase in epidemiological studies on PM in China. A comprehensive evaluation of such epidemiological evidence among the Chinese population is central for revision of the AQS in China and in other developing countries with similar air pollution problems. We thus conducted a systematic review on the epidemiological literature of PM published in the recent decade. In summary, we identified the following: (1) short-term and long-term PM exposure increase mortality and morbidity risk without a discernible threshold, suggesting the necessity for continuous improvement in air quality; (2) the magnitude of long-term associations with mortality observed in China are comparable with those in developed countries, whereas the magnitude of short-term associations are appreciably smaller; (3) governmental clean air policies and personalized mitigation measures are potentially effective in protecting public and individual health, but need to be validated using mortality or morbidity outcomes; (4) particles of smaller size range and those originating from fossil fuel combustion appear to show larger relative health risks; and (5) molecular epidemiological studies provide evidence for the biological plausibility and mechanisms underlying the hazardous effects of PM. This updated review may serve as an epidemiological basis for China’s AQS revision and proposes several perspectives in designing future health studies. Acute effects of PM are smaller in China compared with developed countries Health effects caused by PM depend on particle composition, source, and size There are no thresholds for the health effects of PM Mechanistic studies support the biological plausibility of PM’s health effects
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Affiliation(s)
- Qingli Zhang
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai 200032, China
| | - Xia Meng
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai 200032, China
| | - Su Shi
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai 200032, China
| | - Lena Kan
- Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, MD 21205, USA
| | - Renjie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai 200032, China
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai 200032, China.,Children's Hospital of Fudan University, National Center for Children's Health, Shanghai 201102, China
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Wu C, Zhang Y, Wei J, Zhao Z, Norbäck D, Zhang X, Lu C, Yu W, Wang T, Zheng X, Zhang L. Associations of Early-Life Exposure to Submicron Particulate Matter With Childhood Asthma and Wheeze in China. JAMA Netw Open 2022; 5:e2236003. [PMID: 36219442 PMCID: PMC9554703 DOI: 10.1001/jamanetworkopen.2022.36003] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
IMPORTANCE Exposure to particulate matter (PM) has been associated with childhood asthma and wheeze. However, the specific associations between asthma and PM with an aerodynamic equivalent diameter of 1 μm or less (ie, PM1), which is a contributor to PM2.5 and potentially more toxic than PM2.5, remain unclear. OBJECTIVE To investigate the association of early-life (prenatal and first year) exposure to size-segregated PM, including PM1, PM1-2.5, PM2.5, PM2.5-10, and PM10, with childhood asthma and wheeze. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study was based on a questionnaire administered between June 2019 and June 2020 to caregivers of children aged 3 to 6 years in 7 Chinese cities (Wuhan, Changsha, Taiyuan, Nanjing, Shanghai, Chongqing, and Urumqi) as the second phase of the China, Children, Homes, Health study. EXPOSURES Exposure to PM1, PM1-2.5, PM2.5, PM2.5-10, and PM10 during the prenatal period and first year of life. MAIN OUTCOMES AND MEASURES The main outcomes were caregiver-reported childhood asthma and wheeze. A machine learning-based space-time model was applied to estimate early-life PM1, PM2.5, and PM10 exposure at 1 × 1-km resolution. Concentrations of PM1-2.5 and PM2.5-10 were calculated by subtracting PM1 from PM2.5 and PM2.5 from PM10, respectively. Multilevel (city and child) logistic regression models were applied to assess associations. RESULTS Of 29 418 children whose caregivers completed the survey (15 320 boys [52.1%]; mean [SD] age, 4.9 [0.9] years), 2524 (8.6%) ever had wheeze and 1161 (3.9%) were diagnosed with asthma. Among all children, 18 514 (62.9%) were breastfed for more than 6 months and 787 (2.7%) had parental history of atopy. A total of 22 250 children (75.6%) had a mother with an educational level of university or above. Of the 25 422 children for whom information about cigarette smoking exposure was collected, 576 (2.3%) had a mother who was a current or former smoker during pregnancy and 7525 (29.7%) had passive household cigarette smoke exposure in early life. Early-life PM1, PM2.5, and PM10 exposure were significantly associated with increased risk of childhood asthma, with higher estimates per 10-μg/m3 increase in PM1 (OR, 1.55; 95% CI, 1.27-1.89) than in PM2.5 (OR, 1.14; 95% CI, 1.03-1.26) and PM10 (OR, 1.11; 95% CI, 1.02-1.20). No association was observed between asthma and PM1-2.5 exposure, suggesting that PM1 rather than PM1-2.5 contributed to the association between PM2.5 and childhood asthma. There were significant associations between childhood wheeze and early-life PM1 exposure (OR, 1.23; 95% CI, 1.07-1.41) and PM2.5 exposure (OR, 1.08; 95% CI, 1.01-1.16) per 10-μg/m3 increase in PM1 and PM2.5, respectively. CONCLUSIONS AND RELEVANCE In this cross-sectional study, higher estimates were observed for the association between PM with smaller particles, such as PM1, vs PM with larger particles and childhood asthma. The results suggest that the association between PM2.5 and childhood asthma was mainly attributable to PM1.
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Affiliation(s)
- Chuansha Wu
- Department of Environmental Hygiene and Occupational Medicine, School of Public Health, Medical College, Wuhan University of Science and Technology, Wuhan, China
- Hubei Province Key Laboratory of Occupational Hazard Identification and Control, Wuhan University of Science and Technology, Wuhan, China
| | - Yunquan Zhang
- Hubei Province Key Laboratory of Occupational Hazard Identification and Control, Wuhan University of Science and Technology, Wuhan, China
- Department of Epidemiology and Biostatistics, School of Public Health, Medical College, Wuhan University of Science and Technology, Wuhan, China
| | - Jing Wei
- Department of Chemical and Biochemical Engineering, Iowa Technology Institute, The University of Iowa, Iowa City
| | - Zhuohui Zhao
- Department of Environmental Health, School of Public Health, Fudan University, Shanghai, China
| | - Dan Norbäck
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Xin Zhang
- Research Centre for Environmental Science and Engineering, Shanxi University, Taiyuan, China
| | - Chan Lu
- Department of Occupational and Environmental Health, School of Public Health, Xiangya Medical College, Central South University, Changsha, China
| | - Wei Yu
- Joint International Research Laboratory of Green Buildings and Built Environments, Ministry of Education, Chongqing University, Chongqing, China
| | - Tingting Wang
- School of Nursing and Health Management, Shanghai University of Medicine and Health Sciences, Shanghai, China
| | - Xiaohong Zheng
- School of Energy and Environment, Southeast University, Nanjing, China
| | - Ling Zhang
- Department of Environmental Hygiene and Occupational Medicine, School of Public Health, Medical College, Wuhan University of Science and Technology, Wuhan, China
- Hubei Province Key Laboratory of Occupational Hazard Identification and Control, Wuhan University of Science and Technology, Wuhan, China
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Cheng J, Tong S, Su H, Xu Z. Association between sub-daily exposure to ambient air pollution and risk of asthma exacerbations in Australian children. ENVIRONMENTAL RESEARCH 2022; 212:113556. [PMID: 35618005 DOI: 10.1016/j.envres.2022.113556] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Revised: 05/16/2022] [Accepted: 05/20/2022] [Indexed: 06/15/2023]
Abstract
Short-term exposure to ambient air pollution is associated with risk of asthma attacks. We investigated the association between ultra-short-term exposure to air pollution and risk of childhood asthma exacerbations. Hourly data on emergency department visits (EDVs) for asthma in children during 2013-2015 in Brisbane, Australia, were obtained. We undertook time-stratified case-crossover analyses to examine the hourly association between exposure to air pollutants (particles with diameter ≤10 μm (PM10), particles with diameter ≤2.5 μm (PM2.5), ozone (O3), and nitrogen dioxide (NO2)) and risk of EDVs for asthma after controlling for temperature, relative humidity, public holidays and circulating levels of influenza and respiratory syncytial virus. Risk of EDVs for asthma increased within a few hours after exposure to O3 (odds ratio [OR]: 1.170, 95% confidence interval (CI): 1.003-1.365) or NO2 (OR: 1.359, 95%CI: 1.049-1.760). The association between O3 exposure and risk of EDVs for asthma was stronger in boys (OR: 1.244, 95%CI: 1.025-1.511) than that in girls (OR: 1.055, 95%CI: 0.818-1.361). The association between NO2 exposure and risk of EDVs for asthma was stronger in school-age children [OR ranged from 1.376 (95%CI: 1.044-1.813) to 3.607 (95%CI: 1.552-8.385) across different lags] than that in preschool-age children, whereas the association between PM10 exposure and risk of EDVs for asthma was greater in preschool-age children [OR ranged from 1.873 (95%CI: 1.022-3.433) to 1.878 (95%CI: 1.028-3.431)] than that in school-age children. We observed an association of risk of EDVs for asthma with daytime air pollution exposure, but not with night-time air pollution exposure. This study suggests that risk of childhood asthma exacerbations increases within a few hours of air pollution exposure.
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Affiliation(s)
- Jian Cheng
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, China
| | - Shilu Tong
- Department of Clinical Epidemiology and Biostatistics, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, China; School of Public Health, Institute of Environment and Population Health, Anhui Medical University, Hefei, China; School of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia
| | - Hong Su
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, China.
| | - Zhiwei Xu
- School of Public Health, Faculty of Medicine, University of Queensland, 288 Herston Road, Herston, QLD, 4006, Australia.
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Song J, Ding Z, Zheng H, Xu Z, Cheng J, Pan R, Yi W, Wei J, Su H. Short-term PM 1 and PM 2.5 exposure and asthma mortality in Jiangsu Province, China: What's the role of neighborhood characteristics? ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2022; 241:113765. [PMID: 35753271 DOI: 10.1016/j.ecoenv.2022.113765] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 06/07/2022] [Accepted: 06/09/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Evidence suggests that particulate matter (PM) with smaller particle sizes (such as PM1, PM with an aerodynamic diameter≤1 µm) may have more toxic health effects. However, the short-term association between PM1 and asthma mortality remains largely unknown. OBJECTIVE This study aimed to examine the short-term effects of PM1 and PM2.5 on asthma mortality, as well as to investigate how neighborhood characteristics modified this association. METHODS Daily data on asthma mortality were collected from 13 cities in Jiangsu Province, China, between 2016 and 2017. A time-stratified case-crossover design was attempted to examine the short-term effects of PM1 and PM2.5 on asthma mortality. Individual exposure levels of PM1 and PM2.5 on case and control days were determined based on individual's residential addresses. Stratified analyses by neighborhood characteristics (including green space, tree canopy, blue space, population density, nighttime light and street connectivity) were conducted to identify vulnerable living environments. RESULTS Mean daily concentrations of PM1 and PM2.5 on case days were 33.8 μg/m3 and 54.3 μg/m3. Each 10 μg/m3 increase in three-day-averaged (lag02) PM1 and PM2.5 concentrations were associated with an increase of 6.66% (95%CI:1.18%,12.44%) and 2.39% (95%CI: 0.05%-4.78%) asthma mortality, respectively. Concentration-response curves showed a consistent increase in daily asthma mortality with increasing PM1 and PM2.5 concentrations. Subgroup analyses indicated that the effect of PM1 appeared to be evident in neighborhood characteristics with high green space, low urbanization level and poor street connectivity. CONCLUSION This study suggested an association between short-term PM1 and PM2.5 exposures and asthma mortality. Several neighborhood characteristics (such as green space and physical supportive environment) that could modify the effect of PM1 on asthma mortality should be further explored.
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Affiliation(s)
- Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui,Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Zhen Ding
- Department of Environmental Health, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Hao Zheng
- Department of Environmental Health, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Zhiwei Xu
- School of Public Health, University of Queensland, Queensland, Australia
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui,Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui,Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui,Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA.
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui,Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China.
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He M, Zhong Y, Chen Y, Zhong N, Lai K. Association of short-term exposure to air pollution with emergency visits for respiratory diseases in children. iScience 2022; 25:104879. [PMID: 36065191 PMCID: PMC9440288 DOI: 10.1016/j.isci.2022.104879] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 06/07/2022] [Accepted: 08/02/2022] [Indexed: 11/16/2022] Open
Abstract
Ambient air pollutants are health hazards to children. This study comprised 773,504 emergency department visits (EDVs) at 0–14 years of age with respiratory diseases in southern China. All air pollutants were positively associated with EDVs of total respiratory diseases, especially pneumonia. NO2, PM10, and PM2.5 had intraday effects and cumulative effects on asthma EDVs. The effect of SO2, PM10, and PM2.5 on pneumonia EDVs was stronger in girls than in boys. The effect of NO2 on acute upper respiratory tract infection EDVs was greater in children aged 0–5 years old; however, the effect of PM10 on acute upper respiratory tract infection EDVs was greater in the 6–14 years group. In a two-pollutant model, NO2 was associated with bronchitis and pneumonia, and PM10 was associated with acute upper respiratory tract infection. In this time-series study, NO2 and PM10 were risk indicators for respiratory diseases in children. Air pollution associates with children emergency visits for respiratory diseases NO2 and PM10 are risk indicators for respiratory diseases in children Young children are more sensitive to gaseous pollutants School-age children are more sensitive to PM10
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Liu T, Jiang Y, Hu J, Li Z, Guo Y, Li X, Xiao J, Yuan L, He G, Zeng W, Kan H, Rong Z, Chen G, Yang J, Wang Y, Ma W. Association of ambient PM 1 with hospital admission and recurrence of stroke in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 828:154131. [PMID: 35219663 DOI: 10.1016/j.scitotenv.2022.154131] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 02/10/2022] [Accepted: 02/21/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND Particulate matter (PM) pollution is a well-known risk factor of stroke. However, little is known about the association between PM1 (aerodynamic diameter ≤ 1.0 μm) and stroke. We estimated the associations of short-term exposure to PM1 with hospital admission and recurrence of stoke in China. METHODS Stroke data were derived from the Chinese Stroke Center Alliance (CASA) program conducted in 1458 hospitals in 292 Chinese cities from 2015 to 2019. Daily air pollution and meteorological data were collected in the cities where studied hospitals were located. Daily PM1 concentration was estimated by a generalized additive model (GAM) using PM2.5 and meteorological variables. A time-stratified case-crossover design was applied to estimate the associations of short-term exposure to PM1 with hospital admission of stroke. A GAM model was used to estimate the association between average PM1 exposure during hospitalization and the recurrence of stroke. RESULTS A total of 989,591 stroke cases were included in the study. Each 10 μg/m3 increase in PM1 (lag06-day) was associated with a 0.53% (95%CI, 0.39%, 0.67%) increment in hospital admission for stroke. The adverse effects of PM1 on ischemic stroke was stronger than on intracerebral hemorrhage. We found the associations were significant in Northeast (0.94%, 95%CI, 0.51%, 1.38%), North (0.47%, 95%CI, 0.20%, 0.75%), Central (0.57%, 95%CI, 0.30%, 0.85%), and East China (0.63%, 95%CI, 0.27%, 0.99%). Of all stroke cases, 62,988 (6.4%) had recurrent stoke attack during their hospitalization. Each 10 μg/m3 increase in PM1 was associated with a 1.64% (95%CI, 1.28%, 2.01%) increment in recurrence of stroke during hospitalization. CONCLUSIONS Short-term exposure to PM1 may increase the risk of incidence and recurrence of stroke in China, and the effects varied across different types of stroke and regions. Geographically targeted strategies and measures are needed to control air pollution for reducing the burden of stroke from PM1.
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Affiliation(s)
- Tao Liu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, 510632 Guangzhou, China; Disease Control and Prevention Institute of Jinan University, Jinan University, Guangzhou 510632, China
| | - Yong Jiang
- China National Clinical Research Center for Neurological Diseases, Beijing 100070, China
| | - Jianxiong Hu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Zixiao Li
- China National Clinical Research Center for Neurological Diseases, Beijing 100070, China; Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, 100070, China
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne 3800, Australia
| | - Xing Li
- 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
| | - Lixia Yuan
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Guanhao He
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Weilin Zeng
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200032, China; Children's Hospital of Fudan University, National Center for Children's Health, Shanghai 200032, China
| | - Zuhua Rong
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Gongbo Chen
- Guangdong Provincial Engineering Technology Research Center of Environmental and Health risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Jun Yang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China
| | - Yongjun Wang
- China National Clinical Research Center for Neurological Diseases, Beijing 100070, China; Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, 100070, China.
| | - Wenjun Ma
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, 510632 Guangzhou, China; Disease Control and Prevention Institute of Jinan University, Jinan University, Guangzhou 510632, China.
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Zhang R, Lai KY, Liu W, Liu Y, Lu J, Tian L, Webster C, Luo L, Sarkar C. Community-level ambient fine particulate matter and seasonal influenza among children in Guangzhou, China: A Bayesian spatiotemporal analysis. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 826:154135. [PMID: 35227720 DOI: 10.1016/j.scitotenv.2022.154135] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 02/21/2022] [Accepted: 02/21/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND Influenza is a major preventable infectious respiratory disease. However, there is little detailed long-term evidence of its associations with PM2.5 among children. We examined the community-level associations between exposure to ambient PM2.5 and incident influenza in Guangzhou, China. METHODS We used data from the city-wide influenza surveillance system collected by Guangzhou Centre for Disease Control and Prevention (GZCDC) over the period 2013 and 2019. Incident influenza was defined as daily new influenza (both clinically diagnosed and laboratory confirmed) cases as per standard diagnostic criteria. A 200-meter city-wide grid of daily ambient PM2.5 exposure was generated using a random forest model. We developed spatiotemporal Bayesian hierarchical models to examine the community-level associations between PM2.5 and the influenza adjusting for meteorological and socioeconomic variables and accounting for spatial autocorrelation. We also calculated community-wide influenza cases attributable to PM2.5 levels exceeding the China Grade 1 and World Health Organization (WHO) regulatory thresholds. RESULTS Our study comprised N = 191,846 children from Guangzhou aged ≤19 years and diagnosed with influenza between January 1, 2013 and December 31, 2019. Each 10 μg/m3 increment in community-level PM2.5 measured on the day of case confirmation (lag 0) and over a 6-day moving average (lag 0-5 days) was associated with higher risks of influenza (RR = 1.05, 95% CI: 1.05-1.06 for lag 0 and RR = 1.15, 95% CI: 1.14-1.16 for lag 05). We estimated that 8.10% (95%CI: 7.23%-8.57%) and 20.11% (95%CI: 17.64%-21.48%) influenza cases respectively were attributable to daily PM2.5 exposure exceeding the China Grade I (35 μg/m3) and the WHO limits (25 μg/m3). The risks associated with PM2.5 exposures were more pronounced among children of the age-group 10-14 compared to other age groups. CONCLUSIONS More targeted non-pharmaceutical interventions aimed at reducing PM2.5 exposures at home, school and during commutes among children may constitute additional influenza prevention and control polices.
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Affiliation(s)
- Rong Zhang
- Healthy High Density Cities Lab, HKUrbanLab, The University of Hong Kong, Knowles Building, Pokfulam Road, Pokfulam, Hong Kong, China
| | - Ka Yan Lai
- Healthy High Density Cities Lab, HKUrbanLab, The University of Hong Kong, Knowles Building, Pokfulam Road, Pokfulam, Hong Kong, China
| | - Wenhui Liu
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China
| | - Yanhui Liu
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China
| | - Jianyun Lu
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China
| | - Linwei Tian
- School of Public Health, The University of Hong Kong, Patrick Mason Building, Sassoon Road, Pokfulam, Hong Kong, China
| | - Chris Webster
- Healthy High Density Cities Lab, HKUrbanLab, The University of Hong Kong, Knowles Building, Pokfulam Road, Pokfulam, Hong Kong, China
| | - Lei Luo
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China.
| | - Chinmoy Sarkar
- Healthy High Density Cities Lab, HKUrbanLab, The University of Hong Kong, Knowles Building, Pokfulam Road, Pokfulam, Hong Kong, China.
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Zhou X, Li C, Gao Y, Zhou C, Huang L, Zhang X. Ambient air pollutants relate to hospital admissions for chronic obstructive pulmonary disease in Ganzhou, China. Rev Saude Publica 2022; 56:46. [PMID: 35703601 PMCID: PMC9165633 DOI: 10.11606/s1518-8787.2022056004324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Accepted: 12/27/2021] [Indexed: 11/13/2022] Open
Abstract
OBJECTIVE To evaluate the relationship between ambient air pollutants and chronic obstructive pulmonary disease in relatively low-polluted areas in China. METHODS Atmospheric pollutants levels and meteorological data were obtained from January 2016 to December 2020. The medical database including daily hospital admissions for chronic obstructive pulmonary disease (ICD10: J44) was derived from the First Affiliated Hospital of Gannan Medical University. The generalized additive model was used to analyze the percentage change with 95% confidence interval in daily hospital admissions for chronic obstructive pulmonary disease associated with a 10 µg/m3 increase in atmospheric pollutants levels. RESULTS In total, occurred 4,980 chronic obstructive pulmonary disease hospital admissions (not including emergency department visits) during 2016-2020. The mean concentrations of daily PM2.5, PM10, SO2, NO2, O3, and CO were 37.5 μg/m3, 60.1 μg/m3, 18.7 μg/m3, 23.5 μg/m3, 70.0 μg/m3, and 1.2 mg/m3 in Ganzhou. Each 10 µg/m3 increment of PM2.5, PM10, NO2, and O3 were significantly associated with 2.8% (95%CI: 1.0-4.7), 1.3% (95%CI: 0.3-2.4), 2.8% (95%CI: 0.4-5.4), and 1.5% (95%CI: 0.2-2.7) elevation in daily chronic obstructive pulmonary disease hospital admissions. The estimates of delayed effects of PM2.5, PM10, NO2, and O3 were observed at lag6, lag6, lag8, lag1, respectively. The health effects of particulate pollutants (PM2.5 and PM10) may be independent of other pollutants. The adverse effects of air pollutants were more evident in the warm season (May-Oct) than in the cold season (Nov-Apr). CONCLUSION Our study demonstrated that elevated concentrations of atmospheric pollutant (PM2.5, PM10, NO2, and O3), especially particulate pollutants, can be associated with increased daily count of hospital admissions for chronic obstructive pulmonary disease , which may promote further understanding of the potential hazards of relatively low levels of air pollution on chronic obstructive pulmonary disease and other respiratory disorders.
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Affiliation(s)
- Xingye Zhou
- Gannan Medical University. School of Public Health and Health Management. Ganzhou, China
| | - Chenwei Li
- Gannan Medical University. School of Public Health and Health Management. Ganzhou, China
| | - Yanfang Gao
- Gannan Medical University. School of Public Health and Health Management. Ganzhou, China
| | - Chuanfei Zhou
- Gannan Medical University. School of Public Health and Health Management. Ganzhou, China
| | - Lei Huang
- Gannan Medical University. School of Public Health and Health Management. Ganzhou, China
| | - Xiaokang Zhang
- Gannan Medical University. School of Public Health and Health Management. Ganzhou, China
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45
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Bian Y, Niu Z, Wang S, Pan Y, Zhang L, Chen C. Removal of Size-Dependent Submicron Particles Using Metal-Organic Framework-Based Nanofiber Air Filters. ACS APPLIED MATERIALS & INTERFACES 2022; 14:23570-23576. [PMID: 35579237 DOI: 10.1021/acsami.2c04970] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Particulate matter poses a serious threat to human health. In particular, exposure to submicron particles can result in more severe health effects as they can deposit more deeply into human tissues. Metal-organic framework (MOF)-based nanofiber filters are regarded as promising candidates for efficient particle control. In this study, ZIF-8@PAN nanofiber filters that were developed via an in situ growth strategy were selected for the filtration of submicron particles. The addition of ZIF-8 more effectively enhanced the filtration of particles with smaller sizes. For the most penetrating particle size of around 0.3 μm, the MOF-based nanofiber filter exhibited an 8.9% increase in filtration efficiency compared with that of the pure nanofiber filter. Meanwhile, for particles with large aerodynamic diameters (in the range of 0.7-1 μm, for example), the role of ZIF-8 was negligible. This work provides important insights into the filtration performance of MOF-based nanofiber filters in capturing submicron particles and may aid in designing nanofiber filters for efficient control of particles.
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Affiliation(s)
- Ye Bian
- School of Energy and Environment, Southeast University, Nanjing 210096, China
| | - Zhuolun Niu
- Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, N.T. 999077, Hong Kong SAR, China
| | - Shijie Wang
- Shanghai Institute of Ceramics, Chinese Academy of Sciences, 200050 Shanghai, China
| | - Yue Pan
- Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, N.T. 999077, Hong Kong SAR, China
| | - Li Zhang
- Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, N.T. 999077, Hong Kong SAR, China
| | - Chun Chen
- Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, N.T. 999077, Hong Kong SAR, China
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Mehmood T, Peng L. Polyethylene scaffold net and synthetic grass fragmentation: a source of microplastics in the atmosphere? JOURNAL OF HAZARDOUS MATERIALS 2022; 429:128391. [PMID: 35236024 DOI: 10.1016/j.jhazmat.2022.128391] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 01/19/2022] [Accepted: 01/27/2022] [Indexed: 05/12/2023]
Abstract
Microplastics (MPs) implications in the atmosphere are of current global concern. Currently, there is a growing interest regarding source appointment, fate, level of toxicity, and exposure intensity of ambient air MPs. Recent data suggest that polyethylene (PE) dominates ambient MPs in China's megacities. Albeit understanding of PE sources is limited and restricted to typical sources polluting terrestrial and marine environments. However, the air is a distinct environmental component and may have some separate pollution sources as well as the relative contribution of different sources could also contrast in different environments. Urbanization and fast construction activity resulting from increased economic growth in these places might be a potential source of ambient PE. Recently, the use of scaffold netting on construction sites and synthetic grass as land covering sheets has been on the rise. Generally, these PE items are often inferior and composed of recycled material, making them more prone to degradation. Also, because these items were continually exposed to open air, there is a considerable risk of fragmentation and atmospheric mixing. Therefore, unchecked and excessive usage of these materials can be risky. Here, PE's physical and chemical characteristics, transport and health risks in urban air are discussed here.
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Affiliation(s)
- Tariq Mehmood
- Key Laboratory of Agro-Forestry Environmental Processes and Ecological Regulation of Hainan Province, PR China; College of Ecology and Environment, Hainan University, Haikou, Hainan Province, PR China 570228
| | - Licheng Peng
- Key Laboratory of Agro-Forestry Environmental Processes and Ecological Regulation of Hainan Province, PR China; College of Ecology and Environment, Hainan University, Haikou, Hainan Province, PR China 570228.
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Rafiee A, Carvalho R, Lunardon D, Flores-Mir C, Major P, Quemerais B, Altabtbaei K. Particle Size, Mass Concentration, and Microbiota in Dental Aerosols. J Dent Res 2022; 101:785-792. [PMID: 35384778 PMCID: PMC9210116 DOI: 10.1177/00220345221087880] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Many dental procedures are considered aerosol-generating procedures that may put the dental operator and patients at risk for cross-infection due to contamination from nasal secretions and saliva. This aerosol, depending on the size of the particles, may stay suspended in the air for hours. The primary objective of the study was to characterize the size and concentrations of particles emitted from 7 different dental procedures, as well as estimate the contribution of the nasal and salivary fluids of the patient to the microbiota in the emitted bioaerosol. This cross-sectional study was conducted in an open-concept dental clinic with multiple operators at the same time. Particle size characterization and mass and particle concentrations were done by using 2 direct reading instruments: Dust-Trak DRX (Model 8534) and optical particle sizer (Model 3330). Active bioaerosol sampling was done before and during procedures. Bayesian modeling (SourceTracker2) of long-reads of the 16S ribosomal DNA was used to estimate the contribution of the patients’ nasal and salivary fluids to the bioaerosol. Aerosols in most dental procedures were sub-PM1 dominant. Orthodontic debonding and denture adjustment consistently demonstrated more particles in the PM1, PM2.5, PM4, and PM10 ranges. The microbiota in bioaerosol samples were significantly different from saliva and nasal samples in both membership and abundance (P < 0.05) but not different from preoperative ambient air samples. A median of 80.15% of operator exposure was attributable to sources other than the patients’ salivary or nasal fluids. Median operator’s exposure from patients’ fluids ranged from 1.45% to 2.75%. Corridor microbiota showed more patients’ nasal bioaerosols than oral bioaerosols. High-volume saliva ejector and saliva ejector were effective in reducing bioaerosol escape. Patient nasal and salivary fluids are minor contributors to the operator’s bioaerosol exposure, which has important implications for COVID-19. Control of bioaerosolization of nasal fluids warrants further investigation.
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Affiliation(s)
- A Rafiee
- Department of Medicine, University of Alberta, Edmonton, AB, Canada
| | - R Carvalho
- Department of Dentistry, University of Alberta, Edmonton, AB, Canada
| | - D Lunardon
- Department of Dentistry, University of Alberta, Edmonton, AB, Canada
| | - C Flores-Mir
- Department of Dentistry, University of Alberta, Edmonton, AB, Canada
| | - P Major
- Department of Dentistry, University of Alberta, Edmonton, AB, Canada
| | - B Quemerais
- Department of Medicine, University of Alberta, Edmonton, AB, Canada
| | - K Altabtbaei
- Department of Dentistry, University of Alberta, Edmonton, AB, Canada
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Kärkelä T, Tapper U, Kajolinna T. Comparison of 3R4F cigarette smoke and IQOS heated tobacco product aerosol emissions. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:27051-27069. [PMID: 34935111 PMCID: PMC8989957 DOI: 10.1007/s11356-021-18032-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Accepted: 12/06/2021] [Indexed: 06/05/2023]
Abstract
In this study, the smoke from a 3R4F research cigarette and the aerosol generated by the Heated Tobacco Product IQOS, also referred to as the Tobacco Heating System (THS) 2.2 in the literature, were compared. The objective was to characterize the gas and suspended particulate matter compositions in the mainstream smoke from a combusted 3R4F cigarette and in the aerosol generated by IQOS during use. The results indicated that the determined aerosol emissions from IQOS were notably lower than in the cigarette smoke under a Health Canada Intense puffing regimen. As an interesting detail in this study, the maximum nicotine concentrations within a puff were practically the same in both the 3R4F smoke and the IQOS aerosol, but the average concentration was lower for the IQOS aerosol. For both products, water constituted a significant proportion of the particulate matter, although it was substantially higher in the IQOS aerosol. Furthermore, combustion-related solid particles observed in the 3R4F smoke contained elements such as carbon, oxygen, potassium, calcium, and silicon. In contrast, IQOS aerosol particulate matter was composed of semi-volatile organic constituents with some minor traces of oxygen and silicon. The particulate matter found in the IQOS aerosol was volatile, which was especially noticeable when exposed to the electron beam of the scanning electron microscope (SEM) and Transmission Electron Microscope (TEM).
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Affiliation(s)
- Teemu Kärkelä
- Department of Nuclear Energy, VTT Technical Research Centre of Finland Ltd., Kivimiehentie 3, 02044 VTT, Espoo, Finland.
| | - Unto Tapper
- Department of Nuclear Energy, VTT Technical Research Centre of Finland Ltd., Kivimiehentie 3, 02044 VTT, Espoo, Finland
| | - Tuula Kajolinna
- Department of Mobility and Transport, VTT Technical Research Centre of Finland Ltd., Tietotie 4c, 02044 VTT, Espoo, Finland
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Using Real Time Measurements to Derive the Indoor and Outdoor Contributions of Submicron Particulate Species and Trace Gases. TOXICS 2022; 10:toxics10040161. [PMID: 35448422 PMCID: PMC9024529 DOI: 10.3390/toxics10040161] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 03/25/2022] [Accepted: 03/26/2022] [Indexed: 02/02/2023]
Abstract
The indoor environment is usually more polluted than outdoors due to emissions of gas and particle-phase pollutants from multiple sources, leading to their accumulation on top of the infiltration of outdoor pollution. While it is widely recognized that negative health effects arise from the exposure to outdoor air pollution, exposure to indoor pollutants also needs to be well assessed since we spend most of our time (~90%) breathing indoors. Indoor concentrations of pollutants are driven by physicochemical processes and chemical transformations taking place indoors, acting as sources and/or sinks. While these basic concepts are understood, assessing the contribution of each process is still challenging. In this study, we deployed online instrumentation in an unoccupied room to test a methodology for the apportionment of indoor and outdoor pollutant sources. This method was successfully applied to the apportionment of PM1 and VOCs, however, there are limitations for reactive gases such as O3. The results showed that this unoccupied indoor environment acts as a source of VOCs and contributes 87% on OVOCs and 6% on CxHy, while it acts as a sink for particles, likely due to losses through volatilization up to 60%.
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Zhang Y, He Q, Zhang Y, Xue X, Kan H, Wang X. Differential associations of particle size ranges and constituents with stroke emergency-room visits in Shanghai, China. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2022; 232:113237. [PMID: 35104777 DOI: 10.1016/j.ecoenv.2022.113237] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Revised: 01/19/2022] [Accepted: 01/21/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND AND PURPOSE Fine particulate matter (PM2.5) has been associated with increased risks of stroke, but it remains unclear which specific size ranges and chemical constituents dominate the effects of PM2.5 on stroke. We aimed to evaluate the associations of size-segregated particles and various constituents of PM2.5 with daily emergency-room visits for stroke. METHODS We conducted a time-series study to investigate the associations of 5 particle size ranges from 0.01 to 2.5 µm and 35 constituents of PM2.5 with the daily emergency-room visits for stroke in Shanghai, from 2014 to 2019. Over-dispersed generalized additive models were used to estimate the associations. The robustness of these associations was evaluated by additionally controlling for PM2.5 mass. RESULTS For size ranges from 0.01 to 0.3 µm, there were significant positive associations between particle number concentrations and daily emergency-room visits for stroke with the strongest associations occurring for the size range 0.05-0.1 µm. The size-dependent pattern was not changed by adjusting for PM2.5 and gaseous pollutants. The associations of daily emergency-room visits for stroke also varied considerably by various PM2.5 constituents. After controlling for the simultaneous exposure to PM2.5 and gaseous pollutants in two-pollutant models, we identified 11 out of 35 constituents that had robust associations, these being organic carbon, elemental carbon, chlorine, magnesium, ammonium, nitrate, sulfate, copper, manganese, lead and zinc. CONCLUSION Ultra-fine particles and some PM2.5 constituents (i.e., carbonaceous fractions, inorganic ions and some elements) may be mainly responsible for the excess risk of stroke induced by PM2.5.
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Affiliation(s)
- Yuhao Zhang
- Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai 200032, China; National Clinical Research Center for Interventional Medicine, Shanghai 200032, China; Shanghai Clinical Research Center for Interventional Medicine, Shanghai 200032, China.
| | - Qinglin He
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai 200032, China
| | - Yaping Zhang
- Department of Emergency, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Xiaowei Xue
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai 200032, China
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai 200032, China
| | - Xin Wang
- Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai 200032, China; National Clinical Research Center for Interventional Medicine, Shanghai 200032, China; Shanghai Clinical Research Center for Interventional Medicine, Shanghai 200032, China.
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