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Hu Y, Wang Y, Zhao Z, Zhao B. Reconsidering gas as clean energy: Switching to electricity for household cooking to reduce NO 2-attributed disease burden. ECO-ENVIRONMENT & HEALTH 2024; 3:174-182. [PMID: 38638171 PMCID: PMC11021829 DOI: 10.1016/j.eehl.2023.10.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Revised: 10/17/2023] [Accepted: 10/25/2023] [Indexed: 04/20/2024]
Abstract
Nitrogen dioxide (NO2) is a prevalent air pollutant in urban areas, originating from outdoor sources, household gas consumption, and secondhand smoke. The limited evaluation of the disease burden attributable to NO2, encompassing different health effects and contributions from various sources, impedes our understanding from a public health perspective. Based on modeled NO2 exposure concentrations, their exposure-response relationships with lung cancer, chronic obstructive pulmonary disease, and diabetes mellitus, and baseline disability-adjusted life years (DALYs), we estimated that 1,675 (655-2,624) thousand DALYs were attributable to NO2 in urban China in 2019 [138 (54-216) billion Chinese yuan (CNY) economic losses]. The transition from gas to electricity for household cooking was estimated to reduce the attributable economic losses by 35%. This reduction falls within the range of reductions achieved when outdoor air meets the World Health Organization interim target 3 and air quality guidelines for annual NO2, highlighting the significance of raising awareness of gas as a polluting household energy for cooking. These findings align with global sustainable development initiatives, providing a sustainable solution to promote public health while potentially mitigating climate change.
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Affiliation(s)
- Ying Hu
- Department of Building Science, School of Architecture, Tsinghua University, Beijing 100084, China
| | - Ye Wang
- Department of Building Science, School of Architecture, Tsinghua University, Beijing 100084, China
| | - Zhuohui Zhao
- School of Public Health, Fudan University, Shanghai 200433, China
- Key Laboratory of Public Health Safety of the Ministry of Education, NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai 200433, China
- Shanghai Typhoon Institute/CMA, Shanghai Key Laboratory of Meteorology and Health, IRDR International Center of Excellence on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, WMO/IGAC MAP-AQ Asian Office Shanghai, Fudan University, Shanghai 200433, China
| | - Bin Zhao
- Department of Building Science, School of Architecture, Tsinghua University, Beijing 100084, China
- Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
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2
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Lei Y, Yin Z, Lu X, Zhang Q, Gong J, Cai B, Cai C, Chai Q, Chen H, Chen R, Chen S, Chen W, Cheng J, Chi X, Dai H, Feng X, Geng G, Hu J, Hu S, Huang C, Li T, Li W, Li X, Liu J, Liu X, Liu Z, Ma J, Qin Y, Tong D, Wang X, Wang X, Wu R, Xiao Q, Xie Y, Xu X, Xue T, Yu H, Zhang D, Zhang N, Zhang S, Zhang S, Zhang X, Zhang X, Zhang Z, Zheng B, Zheng Y, Zhou J, Zhu T, Wang J, He K. The 2022 report of synergetic roadmap on carbon neutrality and clean air for China: Accelerating transition in key sectors. ENVIRONMENTAL SCIENCE AND ECOTECHNOLOGY 2024; 19:100335. [PMID: 37965046 PMCID: PMC10641488 DOI: 10.1016/j.ese.2023.100335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 10/19/2023] [Accepted: 10/19/2023] [Indexed: 11/16/2023]
Abstract
China is now confronting the intertwined challenges of air pollution and climate change. Given the high synergies between air pollution abatement and climate change mitigation, the Chinese government is actively promoting synergetic control of these two issues. The Synergetic Roadmap project was launched in 2021 to track and analyze the progress of synergetic control in China by developing and monitoring key indicators. The Synergetic Roadmap 2022 report is the first annual update, featuring 20 indicators across five aspects: synergetic governance system and practices, progress in structural transition, air pollution and associated weather-climate interactions, sources, sinks, and mitigation pathway of atmospheric composition, and health impacts and benefits of coordinated control. Compared to the comprehensive review presented in the 2021 report, the Synergetic Roadmap 2022 report places particular emphasis on progress in 2021 with highlights on actions in key sectors and the relevant milestones. These milestones include the proportion of non-fossil power generation capacity surpassing coal-fired capacity for the first time, a decline in the production of crude steel and cement after years of growth, and the surging penetration of electric vehicles. Additionally, in 2022, China issued the first national policy that synergizes abatements of pollution and carbon emissions, marking a new era for China's pollution-carbon co-control. These changes highlight China's efforts to reshape its energy, economic, and transportation structures to meet the demand for synergetic control and sustainable development. Consequently, the country has witnessed a slowdown in carbon emission growth, improved air quality, and increased health benefits in recent years.
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Affiliation(s)
- Yu Lei
- Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, Beijing, 100041, China
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing, 100041, China
| | - Zhicong Yin
- Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Xi Lu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
- Institute for Carbon Neutrality, Tsinghua University, Beijing, 100084, China
| | - Qiang Zhang
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Jicheng Gong
- State Key Joint Laboratory for Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering and Center for Environment and Health, Peking University, Beijing, 100871, China
| | - Bofeng Cai
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing, 100041, China
| | - Cilan Cai
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Qimin Chai
- National Center for Climate Change, Strategy and International Cooperation, Beijing, 100035, China
| | - Huopo Chen
- Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
| | - Renjie Chen
- School of Public Health, 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
| | - Shi Chen
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Wenhui Chen
- School of Economics and Management, Beijing University of Chemical Technology, Beijing, 100029, China
| | - Jing Cheng
- Department of Earth System Science, University of California, Irvine, CA, 92697, USA
| | - Xiyuan Chi
- National Meteorological Center, China Meteorological Administration, Beijing, 100081, China
| | - Hancheng Dai
- College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
| | - Xiangzhao Feng
- Policy Research Center for Environment and Economy, Ministry of Ecology and Environment of the People's Republic of China, Beijing, 100029, China
| | - Guannan Geng
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Jianlin Hu
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | - Shan Hu
- Building Energy Research Center, School of Architecture, Tsinghua University, Beijing, 100084, China
| | - Cunrui Huang
- Vanke School of Public Health, Tsinghua University, Beijing, 100084, China
| | - Tiantian Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China
| | - Wei Li
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Xiaomei Li
- National Center for Climate Change, Strategy and International Cooperation, Beijing, 100035, China
| | - Jun Liu
- Department of Environmental Engineering, School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, 100083, China
| | - Xin Liu
- Energy Foundation China, Beijing, 100004, China
| | - Zhu Liu
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Jinghui Ma
- Shanghai Typhoon Institute, Shanghai Meteorological Service, Shanghai, 200030, China
| | - Yue Qin
- College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
| | - Dan Tong
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Xuhui Wang
- College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China
| | - Xuying Wang
- Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, Beijing, 100041, China
| | - Rui Wu
- Transport Planning and Research Institute (TPRI) of the Ministry of Transport, Beijing, 100028, China
| | - Qingyang Xiao
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Yang Xie
- School of Economics and Management, Beihang University, Beijing, 100191, China
| | - Xiaolong Xu
- China Association of Building Energy Efficiency, Beijing, 100029, China
| | - Tao Xue
- Institute of Reproductive and Child Health/Ministry of Health Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100080, China
| | - Haipeng Yu
- Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China
| | - Da Zhang
- Institute of Energy, Environment, and Economy, Tsinghua University, Beijing, 100084, China
| | - Ning Zhang
- Department of Electrical Engineering, Tsinghua University, Beijing, 100084, China
| | - Shaohui Zhang
- School of Economics and Management, Beihang University, Beijing, 100191, China
| | - Shaojun Zhang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Xian Zhang
- The Administrative Centre for China's Agenda 21 (ACCA21), Ministry of Science and Technology (MOST), Beijing, 100038, China
| | - Xin Zhang
- National Center for Climate Change, Strategy and International Cooperation, Beijing, 100035, China
| | - Zengkai Zhang
- State Key Laboratory of Marine Environmental Science, College of the Environment and Ecology, Xiamen University, Xiamen, 361102, China
| | - Bo Zheng
- Institute of Environment and Ecology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China
| | - Yixuan Zheng
- Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, Beijing, 100041, China
| | - Jian Zhou
- Institute of Energy, Environment, and Economy, Tsinghua University, Beijing, 100084, China
| | - Tong Zhu
- State Key Joint Laboratory for Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering and Center for Environment and Health, Peking University, Beijing, 100871, China
| | - Jinnan Wang
- Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, Beijing, 100041, China
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing, 100041, China
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
- Institute for Carbon Neutrality, Tsinghua University, Beijing, 100084, China
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3
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Ma Y, Nobile F, Marb A, Dubrow R, Kinney PL, Peters A, Stafoggia M, Breitner S, Chen K. Air pollution changes due to COVID-19 lockdowns and attributable mortality changes in four countries. ENVIRONMENT INTERNATIONAL 2024; 187:108668. [PMID: 38640613 DOI: 10.1016/j.envint.2024.108668] [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: 11/29/2023] [Revised: 03/20/2024] [Accepted: 04/15/2024] [Indexed: 04/21/2024]
Abstract
COVID-19 lockdowns reduced nitrogen dioxide (NO2) and fine particulate matter (PM2.5) emissions in many countries. We aim to quantify the changes in these pollutants and to assess the attributable changes in mortality in Jiangsu, China; California, U.S.; Central-southern Italy; and Germany during COVID-19 lockdowns in early 2020. Accounting for meteorological impacts and air pollution time trends, we use a machine learning-based meteorological normalization technique and the difference-in-differences approach to quantify the changes in NO2 and PM2.5 concentrations due to lockdowns. Using region-specific estimates of the association between air pollution and mortality derived from a causal modeling approach using data from 2015 to 2019, we assess the changes in mortality attributable to the air pollution changes caused by the lockdowns in early 2020. During the lockdowns, NO2 reductions avoided 1.41 (95% empirical confidence interval [eCI]: 0.94, 1.88), 0.44 (95% eCI: 0.17, 0.71), and 4.66 (95% eCI: 2.03, 7.44) deaths per 100,000 people in Jiangsu, China; California, U.S.; and Central-southern Italy, respectively. Mortality benefits attributable to PM2.5 reductions were also significant, albeit of a smaller magnitude. For Germany, the mortality benefits attributable to NO2 changes were not significant (0.11; 95% eCI: -0.03, 0.25), and an increase in PM2.5 concentrations was associated with an increase in mortality of 0.35 (95% eCI: 0.22, 0.48) deaths per 100,000 people during the lockdown. COVID-19 lockdowns overall improved air quality and brought attributable health benefits, especially associated with NO2 improvements, with notable heterogeneity across regions. This study underscores the importance of accounting for local characteristics when policymakers adapt successful emission control strategies from other regions.
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Affiliation(s)
- Yiqun Ma
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA; Yale Center on Climate Change and Health, Yale School of Public Health, New Haven, CT, USA
| | - Federica Nobile
- Department of Epidemiology, Lazio Region Health Service / ASL Roma 1, Rome, Italy
| | - Anne Marb
- Chair of Epidemiology, IBE, Faculty of Medicine, LMU Munich, Munich, Germany; Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Robert Dubrow
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA; Yale Center on Climate Change and Health, Yale School of Public Health, New Haven, CT, USA
| | - Patrick L Kinney
- Department of Environmental Health, Boston University School of Public Health, Boston, MA, USA
| | - Annette Peters
- Chair of Epidemiology, IBE, Faculty of Medicine, LMU Munich, Munich, Germany; Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Massimo Stafoggia
- Department of Epidemiology, Lazio Region Health Service / ASL Roma 1, Rome, Italy
| | - Susanne Breitner
- Chair of Epidemiology, IBE, Faculty of Medicine, LMU Munich, Munich, Germany; Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Kai Chen
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA; Yale Center on Climate Change and Health, Yale School of Public Health, New Haven, CT, USA.
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Yang Z, Liu J, Yang J, Li L, Xiao T, Zhou M, Ou CQ. Haze weather and mortality in China from 2014 to 2020: Definitions, vulnerability, and effect modification by haze characteristics. JOURNAL OF HAZARDOUS MATERIALS 2024; 466:133561. [PMID: 38295725 DOI: 10.1016/j.jhazmat.2024.133561] [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: 11/11/2023] [Revised: 12/26/2023] [Accepted: 01/16/2024] [Indexed: 02/15/2024]
Abstract
Haze weather, characterized by low visibility due to severe air pollution, has aroused great public concern. However, haze definitions are inconclusive, and multicentre studies on the health impacts of haze are scarce. We collected data on the daily number of deaths and environmental factors in 190 Chinese cities from 2014 to 2020. The city-specific association was estimated using quasi-Poisson regression and then pooled using meta-analysis. We found a negative association between daily visibility and non-accidental deaths, and mortality risk sharply increased when visibility was < 10 km. Haze weather, defined as a daily average visibility of < 10 km without a limit for humidity, produced the best model fitness and greatest effect on mortality. A haze day was associated with an increase of 2.53% (95% confidence interval [CI]:1.96, 3.10), 2.84 (95% CI: 2.13, 3.56), and 2.99% (95% CI: 1.94, 4.04) in all non-accident, cardiovascular and respiratory mortality, respectively. Haze had the greatest effect on lung cancer mortality. The haze-associated risk of mortality increased with age. Severe haze (visibility <2 km) and damp haze (haze with relative humidity >90%) had greater health impacts. Our findings can help in the development of early warning systems and effective public health interventions for haze.
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Affiliation(s)
- Zhou Yang
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Jiangmei Liu
- National Center for Chronic and Noncommunicable Disease Control and Prevention (NCNCD), Chinese Center for Disease Control and Prevention (China CDC), Beijing 100050, China
| | - Jun Yang
- School of Public Health, Guangzhou Medical University, Guangzhou 511436, China
| | - Li Li
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Ting Xiao
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Maigeng Zhou
- National Center for Chronic and Noncommunicable Disease Control and Prevention (NCNCD), Chinese Center for Disease Control and Prevention (China CDC), Beijing 100050, China.
| | - Chun-Quan Ou
- State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China.
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Ma Y, Nobile F, Marb A, Dubrow R, Stafoggia M, Breitner S, Kinney PL, Chen K. Short-Term Exposure to Fine Particulate Matter and Nitrogen Dioxide and Mortality in 4 Countries. JAMA Netw Open 2024; 7:e2354607. [PMID: 38427355 PMCID: PMC10907920 DOI: 10.1001/jamanetworkopen.2023.54607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 11/22/2023] [Indexed: 03/02/2024] Open
Abstract
Importance The association between short-term exposure to air pollution and mortality has been widely documented worldwide; however, few studies have applied causal modeling approaches to account for unmeasured confounders that vary across time and space. Objective To estimate the association between short-term changes in fine particulate matter (PM2.5) and nitrogen dioxide (NO2) concentrations and changes in daily all-cause mortality rates using a causal modeling approach. Design, Setting, and Participants This cross-sectional study used air pollution and mortality data from Jiangsu, China; California; central-southern Italy; and Germany with interactive fixed-effects models to control for both measured and unmeasured spatiotemporal confounders. A total of 8 963 352 deaths in these 4 regions from January 1, 2015, to December 31, 2019, were included in the study. Data were analyzed from June 1, 2021, to October 30, 2023. Exposure Day-to-day changes in county- or municipality-level mean PM2.5 and NO2 concentrations. Main Outcomes and Measures Day-to-day changes in county- or municipality-level all-cause mortality rates. Results Among the 8 963 352 deaths in the 4 study regions, a 10-μg/m3 increase in daily PM2.5 concentration was associated with an increase in daily all-cause deaths per 100 000 people of 0.01 (95% CI, 0.001-0.01) in Jiangsu, 0.03 (95% CI, 0.004-0.05) in California, 0.10 (95% CI, 0.07-0.14) in central-southern Italy, and 0.04 (95% CI, 0.02- 0.05) in Germany. The corresponding increases in mortality rates for a 10-μg/m3 increase in NO2 concentration were 0.04 (95% CI, 0.03-0.05) in Jiangsu, 0.03 (95% CI, 0.01-0.04) in California, 0.10 (95% CI, 0.05-0.15) in central-southern Italy, and 0.05 (95% CI, 0.04-0.06) in Germany. Significant effect modifications by age were observed in all regions, by sex in Germany (eg, 0.05 [95% CI, 0.03-0.06] for females in the single-pollutant model of PM2.5), and by urbanicity in Jiangsu (0.07 [95% CI, 0.04-0.10] for rural counties in the 2-pollutant model of NO2). Conclusions and Relevance The findings of this cross-sectional study contribute to the growing body of evidence that increases in short-term exposures to PM2.5 and NO2 may be associated with increases in all-cause mortality rates. The interactive fixed-effects model, which controls for unmeasured spatial and temporal confounders, including unmeasured time-varying confounders in different spatial units, can be used to estimate associations between changes in short-term exposure to air pollution and changes in health outcomes.
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Affiliation(s)
- Yiqun Ma
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut
- Yale Center on Climate Change and Health, Yale School of Public Health, New Haven, Connecticut
| | - Federica Nobile
- Department of Epidemiology, Lazio Region Health Service ASL Roma 1, Rome, Italy
| | - Anne Marb
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, Ludwig-Maximilians-Universität München, Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München–German Research Center for Environmental Health, Neuherberg, Germany
| | - Robert Dubrow
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut
- Yale Center on Climate Change and Health, Yale School of Public Health, New Haven, Connecticut
| | - Massimo Stafoggia
- Department of Epidemiology, Lazio Region Health Service ASL Roma 1, Rome, Italy
| | - Susanne Breitner
- Chair of Epidemiology, Institute for Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, Ludwig-Maximilians-Universität München, Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München–German Research Center for Environmental Health, Neuherberg, Germany
| | - Patrick L. Kinney
- Department of Environmental Health, Boston University School of Public Health, Boston, Massachusetts
| | - Kai Chen
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut
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Zeng J, Lin G, Dong H, Li M, Ruan H, Yang J. Association Between Nitrogen Dioxide Pollution and Cause-Specific Mortality in China: Cross-Sectional Time Series Study. JMIR Public Health Surveill 2024; 10:e44648. [PMID: 38315528 PMCID: PMC10877496 DOI: 10.2196/44648] [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: 11/29/2022] [Revised: 09/18/2023] [Accepted: 01/07/2024] [Indexed: 02/07/2024] Open
Abstract
BACKGROUND Nitrogen dioxide (NO2) has been frequently linked to a range of diseases and associated with high rates of mortality and morbidity worldwide. However, there is limited evidence regarding the risk of NO2 on a spectrum of causes of mortality. Moreover, adjustment for potential confounders in NO2 analysis has been insufficient, and the spatial resolution of exposure assessment has been limited. OBJECTIVE This study aimed to quantitatively assess the relationship between short-term NO2 exposure and death from a range of causes by adjusting for potential confounders in Guangzhou, China, and determine the modifying effect of gender and age. METHODS A time series study was conducted on 413,703 deaths that occurred in Guangzhou during the period of 2010 to 2018. The causes of death were classified into 10 categories and 26 subcategories. We utilized a generalized additive model with quasi-Poisson regression analysis using a natural cubic splines function with lag structure of 0 to 4 days to estimate the potential lag effect of NO2 on cause-specific mortality. We estimated the percentage change in cause-specific mortality rates per 10 μg/m3 increase in NO2 levels. We stratified meteorological factors such as temperature, humidity, wind speed, and air pressure into high and low levels with the median as the critical value and analyzed the effects of NO2 on various death-causing diseases at those high and low levels. To further identify potentially vulnerable subpopulations, we analyzed groups stratified by gender and age. RESULTS A significant association existed between NO2 exposure and deaths from multiple causes. Each 10 μg/m3 increment in NO2 density at a lag of 0 to 4 days increased the risks of all-cause mortality by 1.73% (95% CI 1.36%-2.09%) and mortality due to nonaccidental causes, cardiovascular disease, respiratory disease, endocrine disease, and neoplasms by 1.75% (95% CI 1.38%-2.12%), 2.06% (95% CI 1.54%-2.59%), 2.32% (95% CI 1.51%-3.13%), 2.40% (95% CI 0.84%-3.98%), and 1.18% (95% CI 0.59%-1.78%), respectively. Among the 26 subcategories, mortality risk was associated with 16, including intentional self-harm, hypertensive disease, and ischemic stroke disease. Relatively higher effect estimates of NO2 on mortality existed for low levels of temperature, relative humidity, wind speed, and air pressure than with high levels, except a relatively higher effect estimate was present for endocrine disease at a high air pressure level. Most of the differences between subgroups were not statistically significant. The effect estimates for NO2 were similar by gender. There were significant differences between the age groups for mortality due to all causes, nonaccidental causes, and cardiovascular disease. CONCLUSIONS Short-term NO2 exposure may increase the risk of mortality due to a spectrum of causes, especially in potentially vulnerable populations. These findings may be important for predicting and modifying guidelines for NO2 exposure in China.
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Affiliation(s)
- Jie Zeng
- Department of Internet Medical Center, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Guozhen Lin
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
- Institute of Public Health, Guangzhou Medical University and Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Hang Dong
- Guangzhou Center for Disease Control and Prevention, Guangzhou, China
- Institute of Public Health, Guangzhou Medical University and Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Mengmeng Li
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Honglian Ruan
- School of Public Health, Guangzhou Medical University, Guangzhou, China
| | - Jun Yang
- School of Public Health, Guangzhou Medical University, Guangzhou, China
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Sun W, Han X, Cao M, Pan Z, Guo J, Huang D, Mi J, Liu Y, Guan T, Li P, Huang C, Wang M, Xue T. Middle-term nitrogen dioxide exposure and electrocardiogram abnormalities: A nationwide longitudinal study. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 266:115562. [PMID: 37866032 DOI: 10.1016/j.ecoenv.2023.115562] [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: 07/19/2023] [Revised: 10/03/2023] [Accepted: 10/07/2023] [Indexed: 10/24/2023]
Abstract
BACKGROUND Recently, professionals, such as those from the World Health Organization, have recommended a rigorous standard for nitrogen dioxide (NO2), a typical urban air pollutant affected by regular traffic emissions, based on its short-term and long-term cardiorespiratory effects. However, the association between middle-term NO2 exposure and cardiovascular disorders remains unknown. OBJECTIVES This study was conducted to examine the relationship between NO2 exposure and its middle-term cardiovascular risks indicated by electrocardiogram (ECG) abnormalities. METHOD We included 61,094 subjects (132,249 visits) with repeated ECG observations based on longitudinal data from the China National Stroke Screening Survey (CNSSS). The NO2 exposure concentration was derived from a predictive model, measured as the monthly average concentration in the 6 months of preceding the ECG measurement. We used the generalized estimation equation to assess the association between NO2 exposure and ECG abnormalities. RESULT For each 10 µg/m3 increase in monthly average NO2 concentration, the odds ratio of ECG abnormalities was 1.10 (95% confidence interval [CI] 1.09-1.12) after multiple adjustments. Stratified regression analyses of urban and rural residents showed associations between middle-term NO2 exposure and ECG abnormalities in urban (OR 1.09 [95% CI 1.08-1.11]) and rural residents (OR 1.14 [95% CI 1.10-1.19]). The association was robust within different subpopulations. Associations generally remained statistically significant (OR 1.03 [95% CI 1.02-1.05]) after extra adjustment for PM2.5. Exposure-response relationship analysis revealed a nearly linear relationship between NO2 exposure and the risk for ECG abnormalities. CONCLUSION Using the variation in ECG signals as a potentially reversible indicator for subclinical risk in cardiovascular systems, our study provides additional evidence on the increased risk posed by middle-term NO2 exposure. Our study showed that policies controlling for NO2 concentrations are beneficial to prevent cardiovascular diseases among Chinese adults.
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Affiliation(s)
- Wei Sun
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Xueyan Han
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Man Cao
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Zhaoyang Pan
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Jian Guo
- Department of Cardiology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China; Medical Research Center, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Dengmin Huang
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Jiarun Mi
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Yuanli Liu
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Tianjia Guan
- School of Health Policy and Management, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China.
| | - Pengfei Li
- Institute of Reproductive and Child Health/National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing 100191, China
| | - Conghong Huang
- College of Land Management, Nanjing Agricultural University, Nanjing 210095, China
| | - Meng Wang
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY 14214, United States
| | - Tao Xue
- Institute of Reproductive and Child Health/National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing 100191, China; Advanced Institute of Information Technology, Peking University, Hangzhou, Zhejiang, China; State Environmental Protection Key Laboratory of Atmospheric Exposure and Health Risk Management and Center for Environment and Health, Peking University, Beijing, China.
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8
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Liu M, Xiao S, Wang Y, Li L, Mi J, Wang S. Synergistic analysis of atmospheric pollutants NO 2 and PM 2.5 based on land use regression models: a case study of the Yangtze River Delta, China. ENVIRONMENTAL MONITORING AND ASSESSMENT 2023; 195:1048. [PMID: 37589897 DOI: 10.1007/s10661-023-11637-4] [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: 04/06/2023] [Accepted: 07/24/2023] [Indexed: 08/18/2023]
Abstract
Air pollution is considered one of the greatest threats to human health. This study combines a land use regression (LUR) model with satellite measurements and a distributed-lagged non-linear model (DLNM). It aims to predict high-resolution ground-level concentrations of nitrogen dioxide (NO2) and particulate matter 2.5 (PM2.5) in the Yangtze River Delta (YRD) and reveal the mechanisms of influence between NO2 and PM2.5 and precursors and meteorological factors. Results showed that the annual average NO2 and PM2.5 in the YRD urban agglomeration 2019 were 39.5 µg/m3 and 37.5 µg/m3, respectively. The seasonal variation of NO2 and PM2.5 showed winter > spring > autumn > summer. There is a compelling and complex relationship between NO2 and PM2.5. Predictors indicate that latitude (Y), surface pressure (P), ozone (O3), carbon monoxide (CO), aerosol optical depth (AOD), residential, and rangeland have positive impacts on NO2 and PM2.5. In contrast, temperature (T), precipitation (PRE), and industrial trees hurt NO2 and PM2.5. DLNM model results show that NO2 and PM2.5 had significant associations with the included precursors and meteorological elements, with lagged and non-linear effects observed. Satellite data could help significantly increase the accuracy of LUR models; the R2 of tenfold cross-validation was enhanced by 0.18-0.22. In 2019, PM2.5 will be the dominant pollutant in the YRD, and NO2 showed a high value in the central and eastern parts of the YRD. High concentrations of NO2 and PM2.5 are present in 86% of the YRD, meaning that residents will have difficulty avoiding exposure to these two high pollution levels.
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Affiliation(s)
- Minxia Liu
- College of Geography and Environmental Science, Northwest Normal University, Lanzhou, China.
| | - Shirui Xiao
- College of Geography and Environmental Science, Northwest Normal University, Lanzhou, China
| | - Yang Wang
- College of Geography and Environmental Science, Northwest Normal University, Lanzhou, China
| | - Le Li
- College of Geography and Environmental Science, Northwest Normal University, Lanzhou, China
| | - Jiale Mi
- College of Geography and Environmental Science, Northwest Normal University, Lanzhou, China
| | - Siyuan Wang
- College of Geography and Environmental Science, Northwest Normal University, Lanzhou, China
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He C, Yin P, Liu Z, Huang J, Chen Y, Gao X, Xu Y, Wang C, Cai W, Gong P, Luo Y, Ji JS, Kan H, Chen R, Zhou M. Projections of excess deaths related to cold spells under climate and population change scenarios: A nationwide time series modeling study. ENVIRONMENT INTERNATIONAL 2023; 178:108034. [PMID: 37348158 DOI: 10.1016/j.envint.2023.108034] [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: 03/10/2023] [Revised: 05/23/2023] [Accepted: 06/09/2023] [Indexed: 06/24/2023]
Abstract
BACKGROUND Future climate change is likely to alter cold spell-related disease burden. Few projection studies have considered the potential impact of the aging population with changing population size on cold spell-related disease burdens. METHODS We derived the association between cold spells and daily mortality for 272 main cities in mainland China. We combined these associations with modeled daily temperatures from three different climate models under two climate change scenarios and three population scenarios to project excess deaths related to cold spells. Furthermore, we used the factor separation method to calculate the independent contribution of future population size, age structure, and climate change on projected deaths attributable to cold spells. FINDINGS Compared to the baseline period, future excess deaths related to cold spells are expected to increase over most of the decades under RCP 2.6 (81.5% in 2050 s and 37% in 2090 s) and RCP 4.5 (55.5% in 2050 s and -19% in 2090 s). The factor analysis indicated that the rise of the aged population (≥65) substantially would amplify the excess deaths related to cold spells (increase by 101.1% in the 2050 s and 146.2% in the 2090 s). For the near future (2021-2040), population aging could fully offset the influence of decreased cold-spell days. In the middle of this century (2051-2070), the total excess deaths will exhibit significant variation across three scenarios. By the end of 21 century (2081-2100), the population shrinking would reduce the total excess deaths. INTERPRETATION Excess deaths related to cold spells may still increase in a warming climate and future demographic shifts would produce considerable influences in this increase for different periods.
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Affiliation(s)
- Cheng He
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China; Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Peng Yin
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhao Liu
- School of Linkong Economics and Management, Beijing Institute of Economics and Management, Beijing, China
| | - Jianbin Huang
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing, China
| | - Yidan Chen
- State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing, China
| | - Xuejie Gao
- College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, China; Climate Change Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Ying Xu
- National Climate Center, China Meteorological Administration, Beijing, China
| | - Can Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing, China
| | - Wenjia Cai
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing, China
| | - Peng Gong
- Institute for Climate and Carbon Neutrality, Department of Earth Sciences and Geography, University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Yong Luo
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing, China
| | - John S Ji
- Vanke School of Public Health, Tsinghua University, Beijing, 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 NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China; Children's Hospital of Fudan University, National Center for Children's Health, Shanghai, China
| | - Renjie Chen
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 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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10
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Lei J, Chen R, Liu C, Zhu Y, Xue X, Jiang Y, Shi S, Gao Y, Kan H, Xuan J. Fine and coarse particulate air pollution and hospital admissions for a wide range of respiratory diseases: a nationwide case-crossover study. Int J Epidemiol 2023; 52:715-726. [PMID: 37159523 DOI: 10.1093/ije/dyad056] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 04/20/2023] [Indexed: 05/11/2023] Open
Abstract
BACKGROUND The associations between fine and coarse particulate matter (PM2.5 and PM2.5-10) air pollution and hospital admissions for full-spectrum respiratory diseases were rarely investigated, especially for age-specific associations. We aim to estimate the age-specific associations of short-term exposures to PM2.5 and PM2.5-10 with hospital admissions for full-spectrum respiratory diseases in China. METHODS We conducted an individual-level case-crossover study based on a nationwide hospital-based registry including 153 hospitals across 20 provincial regions in China in 2013-20. We applied conditional logistic regression models and distributed lag models to estimate the exposure- and lag-response associations. RESULTS A total of 1 399 955 hospital admission records for various respiratory diseases were identified. The associations of PM2.5 and PM2.5-10 with total respiratory hospitalizations lasted for 4 days, and an interquartile range increase in PM2.5 (34.5 μg/m3) and PM2.5-10 (26.0 μg/m3) was associated with 1.73% [95% confidence interval (95% CI): 1.34%, 2.12%)] and 1.70% (95% CI: 1.31%, 2.10%) increases, respectively, in total respiratory hospitalizations over lag 0-4 days. Acute respiratory infections (i.e. pneumonia, bronchitis and bronchiolitis) were consistently associated with PM2.5 or PM2.5-10 exposure across different age groups. We found the disease spectrum varied by age, including rarely reported findings (i.e. acute laryngitis and tracheitis, and influenza) among children and well-established associations (i.e. chronic obstructive pulmonary disease, asthma, acute bronchitis and emphysema) among older populations. Besides, the associations were stronger in females, children and older populations. CONCLUSIONS This nationwide case-crossover study provides robust evidence that short-term exposure to both PM2.5 and PM2.5-10 was associated with increased hospital admissions for a wide range of respiratory diseases, and the spectra of respiratory diseases varied by age. Females, children and older populations were more susceptible.
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Affiliation(s)
- Jian Lei
- Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Renjie Chen
- Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Cong Liu
- Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Yixiang Zhu
- Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Xiaowei Xue
- Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Yixuan Jiang
- Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Su Shi
- Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Ya Gao
- Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Haidong Kan
- Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
- National Center for Children's Health, Children's Hospital of Fudan University, Shanghai, China
| | - Jianwei Xuan
- Health Economic Research Institute, School of Pharmacy, Sun Yat-Shen University, Guangzhou, China
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11
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Li X, Wang P, Wang W, Zhang H, Shi S, Xue T, Lin J, Zhang Y, Liu M, Chen R, Kan H, Meng X. Mortality burden due to ambient nitrogen dioxide pollution in China: Application of high-resolution models. ENVIRONMENT INTERNATIONAL 2023; 176:107967. [PMID: 37244002 DOI: 10.1016/j.envint.2023.107967] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 04/07/2023] [Accepted: 05/07/2023] [Indexed: 05/29/2023]
Abstract
BACKGROUND A large gap exists between the latest Global Air Quality Guidelines (AQG 2021) and Chinese air quality standards for NO2. Assessing whether and to what extent air quality standards for NO2 should be tightened in China requires a comprehensive understanding of the spatiotemporal characteristics of population exposure to ambient NO2 and related health risks, which have not been studied to date. OBJECTIVE We predicted ground NO2 concentrations with high resolution in mainland China, explored exposure characteristics to NO2 pollution, and assessed the mortality burden attributable to NO2 exposure. METHODS Daily NO2 concentrations in 2019 were predicted at 1-km spatial resolution in mainland China using random forest models incorporating multiple predictors. From these high-resolution predictions, we explored the spatiotemporal distribution of NO2, population and area percentages with NO2 exposure exceeding criterion levels, and premature deaths attributable to long- and short-term NO2 exposure in China. RESULTS The cross-validation R2and root mean squared error of the NO2 predicting model were 0.80 and 7.78 μg/m3, respectively,at the daily level in 2019.The percentage of people (population number) with annual NO2 exposure over 40 μg/m3 in mainland China in 2019 was 10.40 % (145,605,200), and it reached 99.68 % (1,395,569,840) with the AQG guideline value of 10 μg/m3. NO2 levels and population exposure risk were elevated in urban areas than in rural. Long- and short-term exposures to NO2 were associated with 285,036 and 121,263 non-accidental deaths, respectively, in China in 2019. Tightening standards in steps gradually would increase the potential health benefit. CONCLUSION In China, NO2 pollution is associated with significant mortality burden. Spatial disparities exist in NO2 pollution and exposure risks. China's current air quality standards may no longer objectively reflect the severity of NO2 pollution and exposure risk. Tightening the national standards for NO2 is needed and will lead to significant health benefits.
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Affiliation(s)
- Xinyue Li
- School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai 200302, China
| | - Peng Wang
- Department of Atmospheric and Oceanic Sciences, Fudan University, Shanghai 200438, China
| | - Weidong Wang
- School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai 200302, China
| | - Hongliang Zhang
- Department of Atmospheric and Oceanic Sciences, Fudan University, Shanghai 200438, China
| | - Su Shi
- School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai 200302, China
| | - Tao Xue
- Institute of Reproductive and Child Health/National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing, China
| | - Jintai Lin
- Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
| | - Yuhang Zhang
- Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
| | - Mengyao Liu
- Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
| | - Renjie Chen
- School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai 200302, China
| | - Haidong Kan
- School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai 200302, China
| | - Xia Meng
- School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai 200302, China; Shanghai Typhoon Institute/CMA, Shanghai Key Laboratory of Meteorology and Health, Shanghai 200030, China.
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12
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Wikuats CFH, Nogueira T, Squizzato R, de Freitas ED, Andrade MDF. Health Risk Assessment of Exposure to Air Pollutants Exceeding the New WHO Air Quality Guidelines (AQGs) in São Paulo, Brazil. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:ijerph20095707. [PMID: 37174225 PMCID: PMC10177979 DOI: 10.3390/ijerph20095707] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 04/25/2023] [Accepted: 04/27/2023] [Indexed: 05/15/2023]
Abstract
We applied the AirQ+ model to analyze the 2021 data within our study period (15 December 2020 to 17 June 2022) to quantitatively estimate the number of specific health outcomes from long- and short-term exposure to atmospheric pollutants that could be avoided by adopting the new World Health Organization Air Quality Guidelines (WHO AQGs) in São Paulo, Southeastern Brazil. Based on temporal variations, PM2.5, PM10, NO2, and O3 exceeded the 2021 WHO AQGs on up to 54.4% of the days during sampling, mainly in wintertime (June to September 2021). Reducing PM2.5 values in São Paulo, as recommended by the WHO, could prevent 113 and 24 deaths from lung cancer (LC) and chronic obstructive pulmonary disease (COPD) annually, respectively. Moreover, it could avoid 258 and 163 hospitalizations caused by respiratory (RD) and cardiovascular diseases (CVD) due to PM2.5 exposure. The results for excess deaths by RD and CVD due to O3 were 443 and 228, respectively, and 90 RD hospitalizations due to NO2. Therefore, AirQ+ is a useful tool that enables further elaboration and implementation of air pollution control strategies to reduce and prevent hospital admissions, mortality, and economic costs due to exposure to PM2.5, O3, and NO2 in São Paulo.
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Affiliation(s)
- Caroline Fernanda Hei Wikuats
- Departamento de Ciências Atmosféricas, Instituto de Astronomia, Geofísica de Ciências Atmosféricas, Universidade de São Paulo, São Paulo 05508-090, Brazil
| | - Thiago Nogueira
- Departamento de Saúde Ambiental, Faculdade de Saúde Pública, Universidade de São Paulo, São Paulo 01246-904, Brazil
| | - Rafaela Squizzato
- Departamento de Ciências Atmosféricas, Instituto de Astronomia, Geofísica de Ciências Atmosféricas, Universidade de São Paulo, São Paulo 05508-090, Brazil
| | - Edmilson Dias de Freitas
- Departamento de Ciências Atmosféricas, Instituto de Astronomia, Geofísica de Ciências Atmosféricas, Universidade de São Paulo, São Paulo 05508-090, Brazil
| | - Maria de Fatima Andrade
- Departamento de Ciências Atmosféricas, Instituto de Astronomia, Geofísica de Ciências Atmosféricas, Universidade de São Paulo, São Paulo 05508-090, Brazil
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Meng Y, Liu Z, Hao J, Tao F, Zhang H, Liu Y, Liu S. Association between ambient air pollution and daily hospital visits for cardiovascular diseases in Wuhan, China: a time-series analysis based on medical insurance data. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2023; 33:452-463. [PMID: 35333137 DOI: 10.1080/09603123.2022.2035323] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Accepted: 01/24/2022] [Indexed: 06/14/2023]
Abstract
Although evidence showed the adverse effects of air pollution on cardiovascular disease (CVDs), few studies were based on medically insured populations. We applied a generalized additive Poisson model (GAM) to estimate the short-term effects of ambient air pollution on a group of medically insured population in Wuhan, China. We extracted daily air pollution data, meteorological data, and daily hospital visits for CVDs. We found that the ambient air pollutants sulfur dioxide (SO2), nitrogen dioxide (NO2), ground-level ozone (O3) particulate matter (PM) with an aerodynamic diameter ≤10 μm (PM10), and those ≤2.5 μm (PM2.5) all increased the risk of daily hospital visits for CVDs. We also found that the effect of air pollution on daily hospital visits for CVDs is greater in the cold season than in the warm season. Our findings can be used as evidence that supports the formulation of policies for air pollution and CVDs.
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Affiliation(s)
- Yongna Meng
- School of Health Sciences, Wuhan University, Wuhan, China
| | - Zhihui Liu
- School of Health Sciences, Wuhan University, Wuhan, China
| | - Jiayuan Hao
- Department of Biostatistics, Harvard University, Cambridge, MA, USA
| | - Fengxi Tao
- School of Health Sciences, Wuhan University, Wuhan, China
| | - Huihui Zhang
- School of Health Sciences, Wuhan University, Wuhan, China
| | - Yuehua Liu
- Vanke School of Public Health, Tsinghua university, Beijing, China
| | - Suyang Liu
- School of Health Sciences, Wuhan University, Wuhan, China
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Fernández-Pampillón J, Palacios M, Núñez L, Pujadas M, Artíñano B. Potential ambient NO 2 abatement by applying photocatalytic materials in a Spanish city and analysis of short-term effect on human mortality. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 323:121203. [PMID: 36738878 DOI: 10.1016/j.envpol.2023.121203] [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: 12/14/2022] [Revised: 01/20/2023] [Accepted: 02/01/2023] [Indexed: 06/18/2023]
Abstract
Road traffic is the main contributor to NO2 emissions in many European cities, causing that the current limit values for the protection of human health are exceeded. The use of photocatalytic compounds that incorporate titanium dioxide (TiO2) is frequently proposed as abatement technology but its depolluting effectiveness on a real scale is still being investigated. In this work, the potential removal capacity of NO2 that selected TiO2-based materials would have if they were implemented in a street in the municipality of Alcobendas (Community of Madrid, Spain) has been evaluated. The number of avoided NO2-related deaths over the locality across the period 2001-2019 have been inferred. Moreover, the saving associated with the estimated removal of ambient NO2 due to the use of photocatalytic materials and costs generated by their acquisition and implementation in the selected urban environment were briefly studied. Attributable mortality due to NO2 concentrations for Alcobendas has been estimated in 289 deaths, being 9241 the total deaths due to natural cause. This presents a monthly variation associated with the evolution of both mortality due to natural causes and the average concentrations of NO2. The reduction in mortality via the hypothetical implantation of photocatalytic materials throughout the municipality, assuming ideal conditions for their optimal performance, would be a maximum of 3%. In addition, a saving of €5708 yr-1 km-2 related to NOx damage costs of transport was obtained. A total cost of k€4750.5 km-2 was associated to the purchase of photocatalytic materials and their application to all surfaces in that area. This technology has a big elimination potential in controlled conditions but a low reduction of ambient NO2 is provided when implemented in real outdoor urban scenarios. Its use can be recommended incorporated into engineering designs and applications, complementing other abatement measures, to reduce NO2 mortality in urban areas.
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Affiliation(s)
- Jaime Fernández-Pampillón
- Research Centre for Energy, Environment and Technology (CIEMAT), Madrid, 28040, Spain; The National Distance Education University (UNED), Madrid, 28232, Spain
| | - Magdalena Palacios
- Research Centre for Energy, Environment and Technology (CIEMAT), Madrid, 28040, Spain
| | - Lourdes Núñez
- Research Centre for Energy, Environment and Technology (CIEMAT), Madrid, 28040, Spain.
| | - Manuel Pujadas
- Research Centre for Energy, Environment and Technology (CIEMAT), Madrid, 28040, Spain
| | - Begoña Artíñano
- Research Centre for Energy, Environment and Technology (CIEMAT), Madrid, 28040, Spain
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Xue T, Tong M, Wang M, Yang X, Wang Y, Lin H, Liu H, Li J, Huang C, Meng X, Zheng Y, Tong D, Gong J, Zhang S, Zhu T. Health Impacts of Long-Term NO 2 Exposure and Inequalities among the Chinese Population from 2013 to 2020. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:5349-5357. [PMID: 36959739 DOI: 10.1021/acs.est.2c08022] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Nitrogen dioxide (NO2) is associated with mortality and many other adverse health outcomes. In 2021, the World Health Organization established a new NO2 air quality guideline (AQG) (annual average <10 μg/m3). However, the burden of diseases attributable to long-term NO2 exposure above the AQG is unknown in China. Nitrogen oxide is a major air pollutant in populous cities, which are disproportionately impacted by NO2; this represents a form of environmental inequality. We conducted a nationwide risk assessment of premature deaths attributable to long-term NO2 exposure from 2013 to 2020 based on the exposure-response relationship, high-resolution annual NO2 concentrations, and gridded population data (considering sex, age, and residence [urban vs rural]). We calculated health metrics including attributable deaths, years of life lost (YLL), and loss of life expectancy (LLE). Inequality in the distribution of attributable deaths and YLLs was evaluated by the Lorenz curve and Gini index. According to the health impact assessments, in 2013, long-term NO2 exposure contributed to 315,847 (95% confidence interval [CI]: 306,709-319,269) premature deaths, 7.90 (7.68-7.99) million YLLs, and an LLE of 0.51 (0.50-0.52) years. The high-risk subgroup (top 20%) accounted for 85.7% of all NO2-related deaths and 85.2% of YLLs, resulting in Gini index values of 0.81 and 0.67, respectively. From 2013 to 2020, the estimated health impact from NO2 exposure was significantly reduced, but inequality displayed a slightly increasing trend. Our study revealed a considerable burden of NO2-related deaths in China, which were disproportionally frequent in a small high-risk subgroup. Future clean air initiatives should focus not only on reducing the average level of NO2 exposure but also minimizing inequality.
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Affiliation(s)
- Tao Xue
- Institute of Reproductive and Child Health/National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing 100191, China
- Center for Environment and Health, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Mingkun Tong
- Institute of Reproductive and Child Health/National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing 100191, China
| | - Meng Wang
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, New York 14214, United States
- Research and Education in Energy, Environment and Water Institute, University at Buffalo, Buffalo, New York 14214, United States
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington 98115, United States
| | - Xinyue Yang
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Yanying Wang
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Huan Lin
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Hengyi Liu
- Institute of Reproductive and Child Health/National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing 100191, China
| | - Jiajianghui Li
- Institute of Reproductive and Child Health/National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing 100191, China
| | - Conghong Huang
- College of Land Management, Nanjing Agricultural University, Nanjing 210095, China
- National & Local Joint Engineering, Research Center for Rural Land Resources Use and Consolidation, Nanjing 210095, China
| | - Xia Meng
- School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education, and Key Laboratory of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai 200032, China
| | - Yixuan Zheng
- Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, Beijing 100012, China
| | - Dan Tong
- Department of Earth System Science, Tsinghua University, Beijing 100084, China
| | - Jicheng Gong
- SKL-ESPC, College of Environmental Sciences and Engineering, Center for Environment and Health, Peking University, Beijing 100871, China
| | - Shiqiu Zhang
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Tong Zhu
- SKL-ESPC, College of Environmental Sciences and Engineering, Center for Environment and Health, Peking University, Beijing 100871, China
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16
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Zhang J, Dong C, Xu H, Chen T, Chen F, Wang D, Shi Y, Liu Y, Su J. Use of symptom diary in primary students: association of nitrogen dioxide with prevalence of symptoms. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2023:10.1007/s10653-023-01541-8. [PMID: 36973524 DOI: 10.1007/s10653-023-01541-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Accepted: 03/12/2023] [Indexed: 06/18/2023]
Abstract
Air pollution is a global public health concern, and numerous studies have attempted to identify the health effects of air pollutants, including nitrogen dioxide (NO2). In China, there are few studies investigating the relationship between NO2 exposure and symptoms among children at an individual level. The aim of the study was to evaluate the acute effects of NO2 on prevalence of symptoms of primary students. An environmental and health questionnaire survey was administered to 4240 primary students in seven districts of Shanghai. Daily symptoms, as well as the daily air pollution and meteorological data from each community, were recorded during the corresponding period. A multivariable logistic regression model was utilized to analyze the relationship between the prevalence of symptoms and NO2 exposure in school-age children. A model with interaction items was adopted to estimate the interactive effects of NO2 and confounding factors on symptoms. The average NO2 level in central urban, industrial and rural areas were 62.07 ± 21.66, 54.86 ± 18.32 and 36.62 ± 21.23 μg m-3, respectively. Our findings demonstrate that the occurrence of symptoms was significantly affected by NO2 exposure in the short-term. The largest associations were observed for a 10 μg m-3 increase in 5-day moving average (lag04) NO2 concentration with prevalence of general symptoms (odds ratio [OR] = 1.15, 95% confidence interval [95% CI]: 1.07-1.22), throat symptoms (OR = 1.23, 95% CI: 1.13-1.35) and nasal symptoms (OR = 1.142, 95% CI: 1.02-1.27). Subgroup analysis showed that non-rural areas, boys, nearby environmental pollution source and history of present illness were all susceptible factors to the effects of NO2 exposure. Furthermore, there were interactive effects between NO2 exposure and area types on reported symptoms. NO2 can increase the risk of symptoms in primary students in the short-term, which could be significantly enhanced in central urban and industrial areas.
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Affiliation(s)
- Jianghua Zhang
- Division of Health Risk Factors Monitoring and Control, Shanghai Municipal Center for Disease Control and Prevention, Changning District, Shanghai, 200336, China
| | - Chunyang Dong
- Division of Health Risk Factors Monitoring and Control, Shanghai Municipal Center for Disease Control and Prevention, Changning District, Shanghai, 200336, China
| | - Huihui Xu
- Division of Health Risk Factors Monitoring and Control, Shanghai Municipal Center for Disease Control and Prevention, Changning District, Shanghai, 200336, China.
| | - Tian Chen
- Division of Public Health Service and Safety Assessment, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, 200336, China
| | - Feier Chen
- Division of Health Risk Factors Monitoring and Control, Shanghai Municipal Center for Disease Control and Prevention, Changning District, Shanghai, 200336, China
| | - Duo Wang
- Division of Health Risk Factors Monitoring and Control, Shanghai Municipal Center for Disease Control and Prevention, Changning District, Shanghai, 200336, China
| | - Yewen Shi
- Division of Health Risk Factors Monitoring and Control, Shanghai Municipal Center for Disease Control and Prevention, Changning District, Shanghai, 200336, China
| | - Yongping Liu
- School of Public Health, Fudan University, Shanghai, 200032, China
| | - Jin Su
- Division of Health Risk Factors Monitoring and Control, Shanghai Municipal Center for Disease Control and Prevention, Changning District, Shanghai, 200336, China.
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17
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Lin X, Luo J, Liao M, Su Y, Lv M, Li Q, Xiao S, Xiang J. Wearable Sensor-Based Monitoring of Environmental Exposures and the Associated Health Effects: A Review. BIOSENSORS 2022; 12:1131. [PMID: 36551098 PMCID: PMC9775571 DOI: 10.3390/bios12121131] [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: 11/04/2022] [Revised: 11/24/2022] [Accepted: 12/02/2022] [Indexed: 06/17/2023]
Abstract
Recent advances in sensor technology have facilitated the development and use of personalized sensors in monitoring environmental factors and the associated health effects. No studies have reviewed the research advancement in examining population-based health responses to environmental exposure via portable sensors/instruments. This study aims to review studies that use portable sensors to measure environmental factors and health responses while exploring the environmental effects on health. With a thorough literature review using two major English databases (Web of Science and PubMed), 24 eligible studies were included and analyzed out of 16,751 total records. The 24 studies include 5 on physical factors, 19 on chemical factors, and none on biological factors. The results show that particles were the most considered environmental factor among all of the physical, chemical, and biological factors, followed by total volatile organic compounds and carbon monoxide. Heart rate and heart rate variability were the most considered health indicators among all cardiopulmonary outcomes, followed by respiratory function. The studies mostly had a sample size of fewer than 100 participants and a study period of less than a week due to the challenges in accessing low-cost, small, and light wearable sensors. This review guides future sensor-based environmental health studies on project design and sensor selection.
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Affiliation(s)
- Xueer Lin
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen 518107, China
| | - Jiaying Luo
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen 518107, China
| | - Minyan Liao
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen 518107, China
| | - Yalan Su
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen 518107, China
| | - Mo Lv
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen 518107, China
| | - Qing Li
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110819, China
| | - Shenglan Xiao
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
| | - Jianbang Xiang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen 518107, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
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18
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Zhang Y, Wang S, Feng Z, Song Y. Influenza incidence and air pollution: Findings from a four-year surveillance study of prefecture-level cities in China. Front Public Health 2022; 10:1071229. [PMID: 36530677 PMCID: PMC9755172 DOI: 10.3389/fpubh.2022.1071229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Accepted: 11/14/2022] [Indexed: 12/04/2022] Open
Abstract
Background Influenza is a serious public health problem, and its prevalence and spread show significant spatiotemporal characteristics. Previous studies have found that air pollutants are linked to an increased risk of influenza. However, the mechanism of influence and the degree of their association have not been determined. This study aimed to determine the influence of the air environment on the spatiotemporal distribution of influenza. Methods The kernel density estimation and Getis-Ord Gi * statistic were used to analyze the spatial distribution of the influenza incidence and air pollutants in China. A simple analysis of the correlation between influenza and air pollutants was performed using Spearman's correlation coefficients. A linear regression analysis was performed to examine changes in the influenza incidence in response to air pollutants. The sensitivity of the influenza incidence to changes in air pollutants was evaluated by performing a gray correlation analysis. Lastly, the entropy weight method was used to calculate the weight coefficient of each method and thus the comprehensive sensitivity of influenza incidence to six pollution elements. Results The results of the sensitivity analysis using Spearman's correlation coefficients showed the following ranking of the contributions of the air pollutants to the influenza incidence in descending order: SO2 >NO2 >CO> PM2.5 >O3 >PM10. The sensitivity results obtained from the linear regression analysis revealed the following ranking: CO>NO2 >SO2 >O3 >PM2.5 >PM10. Lastly, the sensitivity results obtained from the gray correlation analysis showed the following ranking: NO2 >CO>PM10 >PM2.5 >SO2 >O3. According to the sensitivity score, the study area can be divided into hypersensitive, medium-sensitive, and low-sensitive areas. Conclusion The influenza incidence showed a strong spatial correlation and associated sensitivity to changes in concentrations of air pollutants. Hypersensitive areas were mainly located in the southeastern part of northeastern China, the coastal areas of the Yellow River Basin, the Beijing-Tianjin-Hebei region and surrounding areas, and the Yangtze River Delta. The influenza incidence was most sensitive to CO, NO2, and SO2, with the occurrence of influenza being most likely in areas with elevated concentrations of these three pollutants. Therefore, the formulation of targeted influenza prevention and control strategies tailored for hypersensitive, medium-sensitive, low-sensitive, and insensitive areas are urgently needed.
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Affiliation(s)
- Yu Zhang
- School of Geographical Sciences, Northeast Normal University, Changchun, China
| | - Shijun Wang
- School of Geographical Sciences, Northeast Normal University, Changchun, China
- Key Laboratory of Geographical Processes and Ecological Security in Changbai Mountains, Ministry of Education, Changchun, China
| | - Zhangxian Feng
- School of Geographical Sciences, Northeast Normal University, Changchun, China
- Key Laboratory of Geographical Processes and Ecological Security in Changbai Mountains, Ministry of Education, Changchun, China
| | - Yang Song
- School of Geographical Sciences, Northeast Normal University, Changchun, China
- Key Laboratory of Geographical Processes and Ecological Security in Changbai Mountains, Ministry of Education, Changchun, China
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19
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Chung CY, Yang J, Yang X, He J. Mathematical modeling in the health risk assessment of air pollution-related disease burden in China: A review. Front Public Health 2022; 10:1060153. [PMID: 36504933 PMCID: PMC9727382 DOI: 10.3389/fpubh.2022.1060153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 11/08/2022] [Indexed: 11/24/2022] Open
Abstract
This review paper covers an overview of air pollution-related disease burden in China and a literature review on the previous studies which have recently adopted a mathematical modeling approach to demonstrate the relative risk (RR) of air pollution-related disease burden. The associations between air pollution and disease burden have been explored in the previous studies. Therefore, it is necessary to quantify the impact of long-term exposure to ambient air pollution by using a suitable mathematical model. The most common way of estimating the health risk attributable to air pollution exposure in a population is by employing a concentration-response function, which is often based on the estimation of a RR model. As most of the regions in China are experiencing rapid urbanization and industrialization, the resulting high ambient air pollution is influencing more residents, which also increases the disease burden in the population. The existing RR models, including the integrated exposure-response (IER) model and the global exposure mortality model (GEMM), are critically reviewed to provide an understanding of the current status of mathematical modeling in the air pollution-related health risk assessment. The performances of different RR models in the mortality estimation of disease are also studied and compared in this paper. Furthermore, the limitations of the existing RR models are pointed out and discussed. Consequently, there is a need to develop a more suitable RR model to accurately estimate the disease burden attributable to air pollution in China, which contributes to one of the key steps in the health risk assessment. By using an updated RR model in the health risk assessment, the estimated mortality risk due to the impacts of environment such as air pollution and seasonal temperature variation could provide a more realistic and reliable information regarding the mortality data of the region, which would help the regional and national policymakers for intensifying their efforts on the improvement of air quality and the management of air pollution-related disease burden.
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Affiliation(s)
- Chee Yap Chung
- Department of Chemical and Environmental Engineering, University of Nottingham Ningbo China, Ningbo, Zhejiang Province, China,*Correspondence: Chee Yap Chung
| | - Jie Yang
- Department of Mathematics, University of Hull, Hull, United Kingdom
| | - Xiaogang Yang
- Department of Mechanical, Materials and Manufacturing Engineering, University of Nottingham Ningbo China, Ningbo, Zhejiang Province, China,Xiaogang Yang
| | - Jun He
- Department of Chemical and Environmental Engineering, University of Nottingham Ningbo China, Ningbo, Zhejiang Province, China
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20
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Huang Z, Xu X, Ma M, Shen J. Assessment of NO 2 population exposure from 2005 to 2020 in China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:80257-80271. [PMID: 35713829 PMCID: PMC9204072 DOI: 10.1007/s11356-022-21420-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 06/08/2022] [Indexed: 05/30/2023]
Abstract
Nitrogen dioxide (NO2) is a major air pollutant with serious environmental and human health impacts. A random forest model was developed to estimate ground-level NO2 concentrations in China at a monthly time scale based on ground-level observed NO2 concentrations, tropospheric NO2 column concentration data from the Ozone Monitoring Instrument (OMI), and meteorological covariates (the MAE, RMSE, and R2 of the model were 4.16 µg/m3, 5.79 µg/m3, and 0.79, respectively, and the MAE, RMSE, and R2 of the cross-validation were 4.3 µg/m3, 5.82 µg/m3, and 0.77, respectively). On this basis, this article analyzed the spatial and temporal variation in NO2 population exposure in China from 2005 to 2020, which effectively filled the gap in the long-term NO2 population exposure assessment in China. NO2 population exposure over China has significant spatial aggregation, with high values mainly distributed in large urban clusters in the north, east, south, and provincial capitals in the west. The NO2 population exposure in China shows a continuous increasing trend before 2012 and a continuous decreasing trend after 2012. The change in NO2 population exposure in western and southern cities is more influenced by population density compared to northern cities. NO2 pollution in China has substantially improved from 2013 to 2020, but Urumqi, Lanzhou, and Chengdu still maintain high NO2 population exposure. In these cities, the Environmental Protection Agency (EPA) could reduce NO2 population exposure through more monitoring instruments and limiting factory emissions.
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Affiliation(s)
- Zhongyu Huang
- Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing, 400715, China
- Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing, 400715, China
| | - Xiankang Xu
- Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing, 400715, China
- Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing, 400715, China
| | - Mingguo Ma
- Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing, 400715, China
- Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing, 400715, China
| | - Jingwei Shen
- Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing, 400715, China.
- Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing, 400715, China.
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21
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Chen Z, Liu N, Tang H, Gao X, Zhang Y, Kan H, Deng F, Zhao B, Zeng X, Sun Y, Qian H, Liu W, Mo J, Zheng X, Huang C, Sun C, Zhao Z. Health effects of exposure to sulfur dioxide, nitrogen dioxide, ozone, and carbon monoxide between 1980 and 2019: A systematic review and meta-analysis. INDOOR AIR 2022; 32:e13170. [PMID: 36437665 DOI: 10.1111/ina.13170] [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: 08/05/2022] [Revised: 10/23/2022] [Accepted: 10/25/2022] [Indexed: 06/16/2023]
Abstract
The burden of disease attributed to the indoor exposure to sulfur dioxide (SO2 ), nitrogen dioxide (NO2 ), ozone (O3 ), and carbon monoxide (CO) is not clear, and the quantitative concentration-response relationship is a prerequisite. This is a systematic review to summarize the quantitative concentration-response relationships by screening and analyzing the polled effects of population-based epidemiological studies. After collecting literature published between 1980 and 2019, a total of 19 health outcomes in 101 studies with 182 health risk estimates were recruited. By meta-analysis, the leave-one-out sensitivity analysis and Egger's test for publication bias, the robust and reliable effects were found for SO2 (per 10 μg/m3 ) with chronic obstructive pulmonary diseases (COPD) (pooled relative risks [RRs] 1.016, 95% CI: 1.012-1.021) and cardiovascular diseases (CVD) (RR 1.012, 95%CI: 007-1.018), respectively. NO2 (per 10 μg/m3 ) had the pooled RRs for childhood asthma, preterm birth, lung cancer, diabetes, and COPD by 1.134 (1.084-1.186), 1.079 (1.007-1.157), 1.055 (1.010-1.101), 1.019 (1.009-1.029), and 1.016 (1.012-1.120), respectively. CO (per 1 mg/m3 ) was significantly associated with Parkinson's disease (RR 1.574, 95% CI: 1.069-2.317) and CVD (RR 1.024, 95% CI: 1.011-1.038). No robust effects were observed for O3 . This study provided evidence and basis for further estimation of the health burden attributable to the four gaseous pollutants.
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Affiliation(s)
- Zhuoru Chen
- School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety of the Ministry of Education, NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China
| | - Ningrui Liu
- Department of Building Science, Tsinghua University, Beijing, China
| | - Hao Tang
- School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety of the Ministry of Education, NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China
| | - Xuehuan Gao
- Anhui Provincial Center for Disease Control and Prevention, Hefei, China
| | - Yinping Zhang
- Department of Building Science, Tsinghua University, Beijing, China
| | - Haidong Kan
- School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety of the Ministry of Education, NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China
| | - Furong Deng
- School of Public Health, Peking University, Beijing, China
| | - Bin Zhao
- Department of Building Science, Tsinghua University, Beijing, China
| | - Xiangang Zeng
- School of Environment and Natural Resources, Renmin University of China, Beijing, China
| | - Yuexia Sun
- School of Environmental Science and Engineering, Tianjin University, Tianjin, China
| | - Hua Qian
- School of Energy and Environment, Southeast University, Nanjing, China
| | - Wei Liu
- Institute for Health and Environment, Chongqing University of Science and Technology, Chongqing, China
| | - Jinhan Mo
- Department of Building Science, Tsinghua University, Beijing, China
| | - Xiaohong Zheng
- School of Energy and Environment, Southeast University, Nanjing, China
| | - Chen Huang
- School of Environment and Architecture, University of Shanghai for Science and Technology, Shanghai, China
| | - Chanjuan Sun
- School of Environment and Architecture, University of Shanghai for Science and Technology, Shanghai, China
| | - Zhuohui Zhao
- School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety of the Ministry of Education, NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China
- Shanghai Typhoon Institute/CMA, Shanghai Key Laboratory of Meteorology and Health, IRDR International Center of Excellence on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, WMO/IGAC MAP-AQ Asian Office Shanghai, Fudan University, Shanghai, China
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22
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Jia H, Xu J, Ning L, Feng T, Cao P, Gao S, Shang P, Yu X. Ambient air pollution, temperature and hospital admissions due to respiratory diseases in a cold, industrial city. J Glob Health 2022; 12:04085. [PMID: 36243957 PMCID: PMC9569423 DOI: 10.7189/jogh.12.04085] [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] [Indexed: 11/21/2022] Open
Abstract
Background The influences of air pollution exposure and temperature on respiratory diseases have become major global health concerns. This study investigated the relationship between ambient air pollutant concentrations and temperature in cold industrial cities that have the risk of hospitalization for respiratory diseases. Methods A time-series study was conducted in Changchun, China, from 2015 to 2019 to analyse the number of daily admissions for respiratory diseases, air pollutant concentrations, and meteorological factors. Time-series decomposition was applied to analyse the trend and characteristics of the number of admissions. Generalized additive models and distributed lag nonlinear models were constructed to explore the effects of air pollutant concentrations and temperature on the number of admissions. Results The number of daily admissions showed an increasing trend, and the seasonal fluctuation was obvious, with more daily admissions in winter and spring than in summer and autumn. There were positive and gradually decreasing lag effects of PM10, PM2.5, NO2, and CO concentrations on the number of admissions, whereas O3 showed a J-shaped trend. The results showed that within the 7-day lag period, 0.5°C was the temperature associated with the lowest relative risk of admission due to respiratory disease, and extremely low and high temperatures (<-18°C, >27°C, respectively) increased the risk of hospitalization for respiratory diseases by 8.3% and 12.1%, respectively. Conclusions From 2015 to 2019, respiratory diseases in Changchun showed an increasing trend with obvious seasonality. The increased concentrations of SO2, NO2, CO, PM2.5, O3 and PM10 lead to an increased risk of hospitalization for respiratory diseases, with a significant lag effect. Both extreme heat and cold could lead to increases in the risk of admission due to respiratory disease.
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Affiliation(s)
- Huanhuan Jia
- School of Public Health, Jilin University, Changchun City, Jilin Province, China
| | - Jiaying Xu
- School of Public Health, Jilin University, Changchun City, Jilin Province, China
| | - Liangwen Ning
- School of Public Administration, Jilin University, Changchun City, Jilin Province, China
| | - Tianyu Feng
- School of Public Health, Jilin University, Changchun City, Jilin Province, China
| | - Peng Cao
- School of Public Health, Jilin University, Changchun City, Jilin Province, China
| | - Shang Gao
- School of Public Health, Jilin University, Changchun City, Jilin Province, China
| | - Panpan Shang
- School of Public Health, Jilin University, Changchun City, Jilin Province, China
| | - Xihe Yu
- School of Public Health, Jilin University, Changchun City, Jilin Province, China
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23
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Li S, Wang G, Wang B, Cao S, Zhang K, Duan X, Wu W. Has the Risk of Outpatient Visits for Allergic Rhinitis, Related to Short-Term Exposure to Air Pollution, Changed over the Past Years in Beijing, China? INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:12529. [PMID: 36231829 PMCID: PMC9566797 DOI: 10.3390/ijerph191912529] [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: 09/06/2022] [Revised: 09/20/2022] [Accepted: 09/22/2022] [Indexed: 06/16/2023]
Abstract
A number of studies have found associations between the short-term exposure to ambient air pollution and hospital admissions. However, little is known about the temporal variations in ambient air pollution associated with health exposure, especially in China. We evaluated whether the risks of allergic rhinitis (AR) outpatient visits from short-term exposure to air pollution varied over time (2014-2020) in Beijing, China. A quasi-Poisson generalized additive model was used to evaluate the relative risks (RRs) and 95% confidence intervals (CIs) associated with the pollutant concentrations during the entire study period and three specific periods. We also analyzed the temporal variations of the period-specific associations and tested the trend of change using the Mann-Kendall test. The concentration-response relationships for the specific periods were further investigated. The RRs (95%CI) for an interquartile range (IQR) increased in PM10 (70 μg/m3) and CO (0.5 mg/m3) decreased from period 1 to period 3. However, The RRs (95%CI) of PM2.5 (55 μg/m3), SO2 (7 μg/m3) and NO2 (27 μg/m3) increased from 1.015 (0.978, 1.054), 1.027 (1.009, 1.044) and 1.086 (1.037, 1.137) in period 1 to 1.069 (1.005, 1.135), 1.074 (1.003, 1.149) and 1.214 (1.149, 1.282) in period 3, respectively. A statistically significant temporal change and the stable effects were observed between the NO2 exposure and AR visits over time. Despite a substantial reduction in ambient air pollution, the short-term effects on AR outpatient visits remained significant. Our findings provide a rationale for continued air pollution control efforts in the future to minimize air pollution and to protect the public.
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Affiliation(s)
- Sai Li
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
| | - Gang Wang
- Department of Otolaryngology-Head and Neck Surgery, PLA Strategic Support Force Characteristic Medical Center, Beijing 100101, China
| | - Beibei Wang
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
| | - Suzhen Cao
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
| | - Kai Zhang
- Department of Environmental Health Sciences, School of Public Health, University at Albany, Rensselaer, NY 12144-2345, USA
| | - Xiaoli Duan
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
| | - Wei Wu
- Department of Otolaryngology-Head and Neck Surgery, PLA Strategic Support Force Characteristic Medical Center, Beijing 100101, China
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Liu RA, Wei Y, Qiu X, Kosheleva A, Schwartz JD. Short term exposure to air pollution and mortality in the US: a double negative control analysis. Environ Health 2022; 21:81. [PMID: 36068579 PMCID: PMC9446691 DOI: 10.1186/s12940-022-00886-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 07/29/2022] [Indexed: 05/21/2023]
Abstract
RATIONALE Studies examining the association of short-term air pollution exposure and daily deaths have typically been limited to cities and used citywide average exposures, with few using causal models. OBJECTIVES To estimate the associations between short-term exposures to fine particulate matter (PM2.5), ozone (O3), and nitrogen dioxide (NO2) and all-cause and cause-specific mortality in multiple US states using census tract or address exposure and including rural areas, using a double negative control analysis. METHODS We conducted a time-stratified case-crossover study examining the entire population of seven US states from 2000-2015, with over 3 million non-accidental deaths. Daily predictions of PM2.5, O3, and NO2 at 1x1 km grid cells were linked to mortality based on census track or residential address. For each pollutant, we used conditional logistic regression to quantify the association between exposure and the relative risk of mortality conditioning on meteorological variables, other pollutants, and using double negative controls. RESULTS A 10 μg/m3 increase in PM2.5 exposure at the moving average of lag 0-2 day was significantly associated with a 0.67% (95%CI: 0.34-1.01%) increase in all-cause mortality. 10 ppb increases in NO2 or O3 exposure at lag 0-2 day were marginally associated with and 0.19% (95%CI: -0.01-0.38%) and 0.20 (95% CI-0.01, 0.40), respectively. The adverse effects of PM2.5 persisted when pollution levels were restricted to below the current global air pollution standards. Negative control models indicated little likelihood of omitted confounders for PM2.5, and mixed results for the gases. PM2.5 was also significantly associated with respiratory mortality and cardiovascular mortality. CONCLUSIONS Short-term exposure to PM2.5 and possibly O3 and NO2 are associated with increased risks for all-cause mortality. Our findings delivered evidence that risks of death persisted at levels below currently permissible.
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Affiliation(s)
- Rongqi Abbie Liu
- Department of Environmental Health, Harvard T H Chan School of Public Health, 677 Huntington Ave, Boston, MA, 02115, USA.
| | - Yaguang Wei
- Department of Environmental Health, Harvard T H Chan School of Public Health, 677 Huntington Ave, Boston, MA, 02115, USA
| | - Xinye Qiu
- Department of Environmental Health, Harvard T H Chan School of Public Health, 677 Huntington Ave, Boston, MA, 02115, USA
| | - Anna Kosheleva
- Department of Environmental Health, Harvard T H Chan School of Public Health, 677 Huntington Ave, Boston, MA, 02115, USA
| | - Joel D Schwartz
- Department of Environmental Health, Harvard T H Chan School of Public Health, 677 Huntington Ave, Boston, MA, 02115, USA
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Yang J, Ma J, Sun Q, Han C, Guo Y, Li M. Health benefits by attaining the new WHO air quality guideline targets in China: A nationwide analysis. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 308:119694. [PMID: 35777592 DOI: 10.1016/j.envpol.2022.119694] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/27/2021] [Revised: 04/15/2022] [Accepted: 06/25/2022] [Indexed: 06/15/2023]
Abstract
To reduce the high disease burden caused by air pollution, World Health Organization (WHO) issued a new air quality guideline (AQG) on the 22nd September 2021. A timely quantitative assessment of health benefits by meeting these targets is a key measure to advocate and inform national and regional disease control policies. We collected daily major air pollution data in 315 Chinese cities from the 1st January to the 31st December 2019, and the corresponding annual population and mortality rate in the whole population of each city. Then, the mortality benefits were estimated when daily air pollution levels attained WHO's new AQG targets (15 μg/m3 for PM2.5, 25 μg/m3 for NO2 and 100 μg/m3 for O3) in 315 Chinese cities and 31 provinces by using pollutant- and cause-specific concentration-response functions. In total, 134,025 (95%CI: 92,768; 173,029) air pollution-associated non-accidental deaths could be avoided in 315 Chinese cities in 2019 by attaining WHO's new AQG targets, with 43,800 (95%CI: 29,945; 55,616) avoidable deaths from PM2.5, 58,070 (95%CI: 45,333; 70,714) from NO2, and 32,155 (95%CI: 17,490; 46,699) from O3. Cardiovascular diseases and respiratory diseases accounted for 72,698 (95%CI: 46,561; 101,680) and 17,726 (95%CI: 8603; 26,925) avoidable deaths, respectively. Health benefits from reduction in air pollution levels were 99.26 avoided non-accidental deaths per million population at national level, ranging from 12.48 per million in Tibet to 166.26 per million in Hebei. These findings suggest that the compliance with the WHO updated AQG standards would save substantial amount of air pollution-related premature deaths in China. More stringent air pollution control and management measures are urgently warranted to reduce the disease burden from air pollutants in China, particularly for the worsening O3 pollution.
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Affiliation(s)
- Jun Yang
- School of Public Health, Guangzhou Medical University, Guangzhou, 511436, China
| | - Jinxiang Ma
- School of Public Health, Guangzhou Medical University, Guangzhou, 511436, China
| | - Qinghua Sun
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Chunlei Han
- School of Public Health and Management, Binzhou Medical University, Yantai, Shandong Province, 264003, China; School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
| | - Yuming Guo
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
| | - Mengmeng Li
- Department of Cancer Prevention, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China.
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Tian Y, Xiang M, Peng J, Duan Y, Wen Y, Huang S, Li L, Yu S, Cheng J, Zhang X, Wang P. Modification effects of seasonal and temperature variation on the association between exposure to nitrogen dioxide and ischemic stroke onset in Shenzhen, China. INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 2022; 66:1747-1758. [PMID: 35750990 DOI: 10.1007/s00484-022-02315-0] [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: 12/24/2021] [Revised: 05/16/2022] [Accepted: 06/14/2022] [Indexed: 06/15/2023]
Abstract
The independent associations of extreme temperature and ambient air pollutant with the admission to hospital and mortality of ischemic stroke have been widely investigated. However, knowledge about the modification effects of variation in season and temperature on the association between exposure to nitrogen dioxide (NO2) and ischemic stroke onset is still limited. This study purposed to explore the effect of NO2 on daily ischemic stroke onset modified by season and ambient temperature, and identify the potential population that susceptible to ischemic stroke onset connected with NO2 and ambient temperature. Data on daily ischemic stroke counts, weather conditions, and ambient air pollutant concentrations in Shenzhen were collected between January 1, 2008, and December 31, 2014. The seasonal effect on the NO2-associated onset was measured by a distributed-lag linear model. Furthermore, a generalized additive model that incorporated with stratification analyses was used to calculate the interactive effects between NO2 and ambient temperature. During the winter, the average percentage increase in daily ischemic stroke onset for each 10 μg/m3 increment in NO2 concentration on lagged 2 days was 3.05% (95% CI: 1.31-4.82%), while there was no statistically significant effect of NO2 during summer. And the low-temperature days ([Formula: see text] mean temperature), with a 2.23% increase in incidence (95% CI: 1.18-3.29%) for the same concentration increase in NO2, were significant higher than high temperature days ([Formula: see text] mean temperature). The modification effects of temperature on the study association were more pronounced in individuals aged 65 years or more and in males. The adverse health effects of NO2 on ischemic stroke are more pronounced during winter or low temperature periods. Elderly adults or males presented higher risks with these exposures.
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Affiliation(s)
- Yuchen Tian
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Ming Xiang
- Department of Hospital Infection Control, Wuhan No. 1 Hospital (Wuhan Hospital of Integrated Traditional Chinese and Western Medicine), Wuhan, Hubei, China
| | - Ji Peng
- Shenzhen Center for Chronic Disease Control, 2021 Buxin Road, Shenzhen, 518020, Guangdong, China
| | - Yanran Duan
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Ying Wen
- Shenzhen Center for Disease Control and Prevention, 8 Longyuan Rd, Shenzhen, 518055, Guangdong, China
| | - Suli Huang
- Shenzhen Center for Disease Control and Prevention, 8 Longyuan Rd, Shenzhen, 518055, Guangdong, China
| | - Lei Li
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Shuyuan Yu
- Shenzhen Center for Disease Control and Prevention, 8 Longyuan Rd, Shenzhen, 518055, Guangdong, China
| | - Jinquan Cheng
- Shenzhen Center for Disease Control and Prevention, 8 Longyuan Rd, Shenzhen, 518055, Guangdong, China.
| | - Xia Zhang
- The First People's Hospital of Jingzhou, 40 Daqing Rd, Jingzhou, 434000, Hubei, China.
| | - Peng Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
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Chen T, Norback D, Deng Q, Huang C, Qian H, Zhang X, Sun Y, Wang T, Zhang Y, Li B, Kan H, Wei L, Liu C, Xu Y, Zhao Z. Maternal exposure to PM 2.5/BC during pregnancy predisposes children to allergic rhinitis which varies by regions and exclusive breastfeeding. ENVIRONMENT INTERNATIONAL 2022; 165:107315. [PMID: 35635966 DOI: 10.1016/j.envint.2022.107315] [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: 02/18/2022] [Revised: 05/02/2022] [Accepted: 05/18/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Increasing prevalence of childhood allergic rhinitis(AR) needs a deeper understanding on the potential adverse effects of early life exposure to air pollution. OBJECTIVES The main aim was to evaluate the effects of maternal exposure to PM2.5 and chemical constituents during pregnancy on preschool children's AR, and further to explore the modification effects of regions and exclusive breastfeeding. METHODS A multi-center population-based study was performed in 6 cities from 3 regions of China in 2011-2012. Maternal exposure to ambient PM2.5 and main chemical constituents(BC, OM, SO42-, NO3-, NH4+) during pregnancy was assessed and a longitudinal prospective analysis was applied on preschool children's AR. The modification effects of regions and exclusive breastfeeding were investigated. RESULTS A total of 8.8% and 9.8% of children reported doctor-diagnosed allergic rhinitis(DDAR) and current hay fever, respectively, and 48.6% had less than 6 months of exclusive breastfeeding. The means of PM2.5 during pregnancy were 52.7 μg/m3, 70.3 μg/m3 and 76.4 μg/m3 in the east, north and central south of China, respectively. Multilevel log-binomial model regression showed that each interquartile range(IQR) increase of PM2.5 during pregnancy was associated with an average increase in prevalence ratio (PR) of DDAR by 1.43(95% confidence interval(CI): 1.11, 1.84) and current hay fever by 1.79(95% CI: 1.26, 2.55), respectively. Among chemical constituents, black carbon (BC) had the strongest associations. Across 3 regions, the eastern cities had the highest associations, followed by those in the central south and the north. For those equal to or longer than 6 months of exclusive breastfeeding, the associations were significantly reduced. CONCLUSIONS Children in east of China had the highest risks of developing AR per unit increase of maternal exposure to PM2.5 during pregnancy, especially BC constituent. Remarkable decline was found in association with an increase in breastfeeding for ≥6 months, in particular in east of China.
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Affiliation(s)
- Tianyi Chen
- Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China
| | - Dan Norback
- Department of Medical Sciences, Uppsala University, Uppsala SE-751, Sweden
| | - Qihong Deng
- School of Energy Science and Engineering, Central South University, Changsha 410083, China
| | - Chen Huang
- School of Environment and Architecture, University of Shanghai for Science and Technology, Shanghai 200093, China
| | - Hua Qian
- School of Energy & Environment, Southeast University, Nanjing 210096, China
| | - Xin Zhang
- Research Center for Environmental Science and Engineering, Shanxi University, Taiyuan 030006, China
| | - Yuexia Sun
- Tianjin Key Lab of Indoor Air Environmental Quality Control, Tianjin University, Tianjin 300072, China
| | - Tingting Wang
- School of Nursing & Health Management, Shanghai University of Medicine & Health Sciences, Shanghai 201318, China
| | - Yinping Zhang
- Department of Building Science, Tsinghua University, Beijing 100084, China
| | - Baizhan Li
- Key Laboratory of Three Gorges Reservoir Region's Eco-Environment, Chongqing University, Chongqing 400030, China
| | - Haidong Kan
- Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety of the Ministry of Education, NHC Key Laboratory of Health Technology Assessment (Fudan University), Shanghai Typhoon Institute/CMA, Shanghai Key Laboratory of Meteorology and Health, Shanghai 200030, China; IRDR International Center of Excellence on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai 200438, China; WMO/IGAC MAP-AQ Asian Office Shanghai, Fudan University, Shanghai 200438, China
| | - Lan Wei
- Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China
| | - Cong Liu
- Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China.
| | - Yanyi Xu
- Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety of the Ministry of Education, NHC Key Laboratory of Health Technology Assessment (Fudan University), Shanghai Typhoon Institute/CMA, Shanghai Key Laboratory of Meteorology and Health, Shanghai 200030, China; IRDR International Center of Excellence on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai 200438, China; WMO/IGAC MAP-AQ Asian Office Shanghai, Fudan University, Shanghai 200438, China.
| | - Zhuohui Zhao
- Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety of the Ministry of Education, NHC Key Laboratory of Health Technology Assessment (Fudan University), Shanghai Typhoon Institute/CMA, Shanghai Key Laboratory of Meteorology and Health, Shanghai 200030, China; IRDR International Center of Excellence on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai 200438, China; WMO/IGAC MAP-AQ Asian Office Shanghai, Fudan University, Shanghai 200438, China.
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Wang H, Tang R, Liu Y. Potential Health Benefit of NO 2 Abatement in China's Urban Areas: Inspirations for Source-specific Pollution Control Strategy. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2022; 24:100482. [PMID: 35664441 PMCID: PMC9160485 DOI: 10.1016/j.lanwpc.2022.100482] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Affiliation(s)
- Haikun Wang
- Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
- Collaborative Innovation Center of Climate Change, Jiangsu Province, Nanjing, 210023, China
- Frontiers Science Center for Critical Earth Material Cycling, Nanjing University, Nanjing, 210023, PR China
- Correspondence to: Haikun Wang
| | - Rong Tang
- Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
| | - Yifan Liu
- State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing, 210023, China
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29
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Thermal Stress Simulation and Structure Failure Analyses of Nitrogen–Oxygen Sensors under a Gradual Temperature Field. ENERGIES 2022. [DOI: 10.3390/en15082799] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
Abstract
Nitrogen–oxygen sensors are pivotal for NOX emission detection, and they have been designed as key components in vehicles’ exhaust systems. However, severe thermal stress concentrations during thermal cycling in the sensors create knotty structural damage issues, which are inevitable during the frequent start–stop events of the vehicles. Herein, to illustrate the effect of thermal concentration on a sensor’s structure, we simulated the temperature and stress field of a sensor through finite element analysis. The failure modes of the sensor based on the multilayer structure model were analyzed. Our simulation indicated that the thermal deformation and stress of the sensors increased significantly when the heating temperature in the sensors increased from 200 to 800 °C. High stress regions were located at the joint between the layers and the right angle of the air chamber. These results are consistent with the sensor failure locations that were observed by SEM, and the sensor’s failures mainly manifested in the form of cracks and delamination. The results suggest that both the multilayer interfaces and the shape of the air chamber could be optimized to reduce the thermal stress concentrations of the sensors. It is beneficial to improve the reliability of the sensor under thermal cycling operation.
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Xu R, Wang Q, Wei J, Lu W, Wang R, Liu T, Wang Y, Fan Z, Li Y, Xu L, Shi C, Li G, Chen G, Zhang L, Zhou Y, Liu Y, Sun H. Association of short-term exposure to ambient air pollution with mortality from ischemic and hemorrhagic stroke. Eur J Neurol 2022; 29:1994-2005. [PMID: 35363940 DOI: 10.1111/ene.15343] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2022] [Accepted: 03/28/2022] [Indexed: 11/26/2022]
Abstract
BACKGROUND Short-term exposure to ambient air pollution has been linked to increased risk of stroke mortality, but its adverse effects on mortality from specific types of stroke including ischemic stroke and hemorrhagic stroke remain poorly understood. METHODS Using the China National Mortality Surveillance System, we conducted a time-stratified case-crossover study among 412,567 stroke deaths in Jiangsu province, China during 2015-2019. Residential daily PM2.5 , PM10 , SO2 , NO2 , CO and O3 exposure concentration was extracted from the ChinaHighAirPollutants dataset for each subject. Conditional logistic regression models were performed to conduct exposure-response analysis. RESULTS Each 10 μg/m3 increase of PM2.5 , PM10 , SO2 , NO2 , CO and O3 was respectively associated with a 1.44%, 0.93%, 5.55%, 2.90%, 0.148%, and 0.54% increase in odds of mortality from ischemic stroke, which was significantly stronger than that from hemorrhagic stroke (percent change in odds: 0.74%, 0.51%, 3.11%, 1.15%, 0.090%, and 0.10%). The excess fraction of ischemic stroke mortality associated with PM2.5 , PM10 , SO2 , NO2 , CO, and O3 exposure was 6.90%, 6.48%, 8.21%, 8.61%, 9.67%, and 4.76%, respectively, which was also significantly higher than that of hemorrhagic stroke mortality (excess fraction: 3.49%, 3.48%, 4.69%, 3.48%, 5.86%, and 0.88%). These differences in adverse effects generally remained across sex, age, and season. CONCLUSIONS Short-term exposure to ambient air pollution was significantly associated with increased risk of both ischemic and hemorrhagic stroke mortality and posed considerable excess mortality. Our results suggest that air pollution exposure may lead to substantially greater adverse effects on mortality from ischemic stroke than that from hemorrhagic stroke.
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Affiliation(s)
- Ruijun Xu
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Qingqing Wang
- Department of Environment and Health, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, USA
| | - Wenfeng Lu
- State Key Laboratory of Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China.,Department of Preventive Medicine, School of Public Health, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Rui Wang
- Luohu District Chronic Disease Hospital, Shenzhen, Guangdong, China
| | - Tingting Liu
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Yaqi Wang
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Zhaoyu Fan
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Yingxin Li
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Luxi Xu
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Chunxiang Shi
- Meteorological Data Laboratory, National Meteorological Information Center, Beijing, China
| | - Guo Li
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Gongbo Chen
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Lan Zhang
- Institute of Chronic Noncommunicable Disease Control and Prevention, Hubei Provincial Center for Disease Control and Prevention, Wuhan, Hubei, China
| | - Yun Zhou
- State Key Laboratory of Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China.,Department of Preventive Medicine, School of Public Health, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Yuewei Liu
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Hong Sun
- Department of Environment and Health, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu, China
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Yuan Z, Chen P, Yang L, Miao L, Wang H, Xu D, Lin Z. Combined oxidant capacity, redox-weighted oxidant capacity and elevated blood pressure: A panel study. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2022; 234:113364. [PMID: 35255254 DOI: 10.1016/j.ecoenv.2022.113364] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 02/22/2022] [Accepted: 02/27/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND Evidence is limited on the potential health effects of Ox (sum value) and Oxwt(weighted value), the two surrogates for ozone (O3) and nitrogen dioxides (NO2). OBJECTIVES To investigate the impacts of Ox and redox-weighted oxidant capacity (Oxwt) on blood pressure (BP). METHODS A panel study was conducted with four repeated follow-up visits among 40 healthy college students in Hefei, Anhui Province, China from August to October, 2021. We measured BP by using an automated sphygmomanometer and obtained hourly data of air pollutants at a nearby site. The sum of O3 and NO2 (Ox) and their weighted average (Oxwt) were obtained as exposure variables. We applied linear mixed-effect models to evaluate the effects of Ox and Oxwton systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP) and pulse pressure (PP). RESULTS Totally, 160 pairs of valid BP values were obtained. The 24-h mean levels of Ox and Oxwt were 64.38 μg/m3 and 110.28 μg/m3, respectively. Overall, both Ox and Oxwt were significantly linked with SBP, DBP and MAP at most lag periods, whereas non-significant with PP. A 10-μg/m3 increase in Oxwt at lag 0-24 h was linked to increases of 2.43 mmHg (95% CI: 0.96, 3.91) in SBP, 2.31 mmHg (95% CI: 1.37, 3.26) in DBP and 2.35 mmHg (95% CI: 1.35, 3.36) in MAP, while the corresponding effect estimates for Ox were 1.51 mmHg (95%CI: 0.60, 2.43), 1.43 mmHg (95% CI: 0.85, 2.02) and 1.46 mmHg (95%CI: 0.83, 2.09). In two-pollutant models, our results were almost unchanged after controlling for simultaneous exposure to other pollutants. The effects were more pronounced among males and those with physical activity. CONCLUSIONS The findings provide first-hand evidence that short-term exposure to Ox and Oxwt was associated with BP increases in young adults.
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Affiliation(s)
- Zhi Yuan
- Department of Toxicology, School of Public Health, Anhui Medical University, Hefei 230032, China
| | - Ping Chen
- Department of Toxicology, School of Public Health, Anhui Medical University, Hefei 230032, China
| | - Liyan Yang
- Department of Toxicology, School of Public Health, Anhui Medical University, Hefei 230032, China
| | - Lin Miao
- Department of Toxicology, School of Public Health, Anhui Medical University, Hefei 230032, China
| | - Hua Wang
- Department of Toxicology, School of Public Health, Anhui Medical University, Hefei 230032, China; Key Laboratory of Environmental Toxicology of Anhui Higher Education Institutes, Anhui Medical University, Hefei 230032, China
| | - Dexiang Xu
- Department of Toxicology, School of Public Health, Anhui Medical University, Hefei 230032, China; Key Laboratory of Environmental Toxicology of Anhui Higher Education Institutes, Anhui Medical University, Hefei 230032, China.
| | - Zhijing Lin
- Department of Toxicology, School of Public Health, Anhui Medical University, Hefei 230032, China.
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Lei J, Chen R, Yin P, Meng X, Zhang L, Liu C, Qiu Y, Ji JS, Kan H, Zhou M. Association between Cold Spells and Mortality Risk and Burden: A Nationwide Study in China. ENVIRONMENTAL HEALTH PERSPECTIVES 2022; 130:27006. [PMID: 35157500 PMCID: PMC8843087 DOI: 10.1289/ehp9284] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
BACKGROUND Few multicity studies have evaluated the association between cold spells and mortality risk and burden. OBJECTIVES We aimed to estimate the association between cold spells and cause-specific mortality and to evaluate the mortality burden in China. METHODS We conducted a time-series analysis with a nationally representative Disease Surveillance Points System database during the cool seasons spanning from 2013 to 2015 in 272 Chinese cities. We used 12 cold-spell definitions and overdispersed generalized additive models with distributed lag models to estimate the city-specific cumulative association of cold spells over lags of 0-28 d. We controlled for the nonlinear and lagged effects of cold temperature over 0-28 d to evaluate the added effect estimates of cold spell. We also quantified the nationwide mortality burden and pooled the estimated association at national and different climatic levels with meta-regression models. RESULTS For the cold-spell definition of daily mean temperatures of ≤5th percentile of city-specific daily mean temperature and duration of ≥4 consecutive d, the relative risks (i.e., risk ratios) associated with cold spells were 1.39 [95% confidence interval (CI): 1.15, 1.69] for non-accidental mortality, 1.66 (95% CI: 1.20, 2.31) for coronary heart disease mortality, 1.49 (95% CI: 1.12, 1.97) for stroke mortality, and 1.26 (95% CI: 0.85, 1.87) for chronic obstructive pulmonary disease mortality. Cold spells showed a maximal lagged association of 28 d with the risks peaked at 10-15 d. A statistically significant attributable fraction (AF) of non-accidental mortality [2.10% (95% CI: 0.94%, 3.04%)] was estimated. The risks were higher in the temperate continental and the temperate monsoon zones than in the subtropical monsoon zone. The elderly population was especially vulnerable to cold spells. DISCUSSION Our study provides evidence for the significant relative risks of non-accidental, cardiovascular, and respiratory mortality associated with cold spells. The findings on vulnerable populations and differential risks in different climatic zones may help establish region-specific forecasting systems against the hazardous impact of cold spells. https://doi.org/10.1289/EHP9284.
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Affiliation(s)
- Jian Lei
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and National Health Commission (NHC) Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Renjie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and National Health Commission (NHC) Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
- Integrated Research on Disaster Risk International Center of Excellence (IRDR ICoE) on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Peng Yin
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xia Meng
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and National Health Commission (NHC) Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Lina Zhang
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and National Health Commission (NHC) Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Cong Liu
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and National Health Commission (NHC) Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Yang Qiu
- Department of Environmental Sciences and Engineering, School of Architecture and Environmental Sciences, Sichuan University, Chengdu, China
| | - John S. Ji
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and National Health Commission (NHC) Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
- Integrated Research on Disaster Risk International Center of Excellence (IRDR ICoE) on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, 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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Differential impact of government lockdown policies on reducing air pollution levels and related mortality in Europe. Sci Rep 2022; 12:726. [PMID: 35082316 PMCID: PMC8791935 DOI: 10.1038/s41598-021-04277-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 11/08/2021] [Indexed: 01/08/2023] Open
Abstract
Previous studies have reported a decrease in air pollution levels following the enforcement of lockdown measures during the first wave of the COVID-19 pandemic. However, these investigations were mostly based on simple pre-post comparisons using past years as a reference and did not assess the role of different policy interventions. This study contributes to knowledge by quantifying the association between specific lockdown measures and the decrease in NO2, O3, PM2.5, and PM10 levels across 47 European cities. It also estimated the number of avoided deaths during the period. This paper used new modelled data from the Copernicus Atmosphere Monitoring Service (CAMS) to define business-as-usual and lockdown scenarios of daily air pollution trends. This study applies a spatio-temporal Bayesian non-linear mixed effect model to quantify the changes in pollutant concentrations associated with the stringency indices of individual policy measures. The results indicated non-linear associations with a stronger decrease in NO2 compared to PM2.5 and PM10 concentrations at very strict policy levels. Differences across interventions were also identified, specifically the strong effects of actions linked to school/workplace closure, limitations on gatherings, and stay-at-home requirements. Finally, the observed decrease in pollution potentially resulted in hundreds of avoided deaths across Europe.
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Association of short-term exposure to air pollution with recurrent ischemic cerebrovascular events in older adults. Int J Hyg Environ Health 2022; 240:113925. [PMID: 35045384 DOI: 10.1016/j.ijheh.2022.113925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Revised: 01/09/2022] [Accepted: 01/11/2022] [Indexed: 11/22/2022]
Abstract
The acute effects of ambient air pollution on recurrence of ischemic cerebrovascular events (ICEs) remains largely unknown. We therefore conducted a time-stratified case-crossover study of 43,896 patients who were 60 years or older and were admitted to hospital for recurrent ICEs including ischemic stroke and transient ischemic attack in Guangzhou, China during 2016-2019. Based on each patient's home address and pollutant data from its neighboring air quality monitoring stations, we used an inverse distance weighting method to assess exposures to particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5), particulate matter with an aerodynamic diameter ≤10 μm (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO) and ozone (O3). Conditional logistic regression models were used to quantify exposure-response associations. During the study period, there were 43,896 case days and 149,131 control days. In single-pollutant models, each 10 μg/m3 increase in exposure to PM10, NO2 and CO (mean exposure on date of admission and 1 day prior) was significantly associated with a 0.74% (95% confidence interval [CI]: 0.13-1.36%), 2.15% (1.38-2.93%) and 0.14% (0.07-0.21%) increase in odds of hospital admissions for recurrent ICEs, respectively, and no significant departures from linearity were detected. The association for NO2 exposure remained consistent in 2-pollutant models, while the associations for PM10 and CO disappeared or changed materially with adjustment for other pollutants. Stronger association for NO2 exposure was observed in cool season than that in warm season. We found that short-term exposure to ambient air pollutants, especially NO2, was associated with increased risk of hospital admissions for recurrent ICEs in older adults.
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Gao P, Wu Y, He L, Wang L, Fu Y, Zhang F, Krafft T, Martens P. Acute effects of ambient nitrogen oxides and interactions with temperature on cardiovascular mortality in Shenzhen, China. CHEMOSPHERE 2022; 287:132255. [PMID: 34826935 DOI: 10.1016/j.chemosphere.2021.132255] [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: 06/14/2021] [Revised: 09/07/2021] [Accepted: 09/13/2021] [Indexed: 05/22/2023]
Abstract
BACKGROUND Though inconsistent, acute effects of ambient nitrogen oxides on cardiovascular mortality have been reported. Whereas, interactive roles of temperature on their relationships and joint effects of different indicators of nitrogen oxides were less studied. This study aimed to extrapolate the independent roles of ambient nitrogen oxides and temperature interactions on cardiovascular mortality. METHODS Data on mortality, air pollutants, and meteorological factors in Shenzhen from 2013 to 2019 were collected. Three indicators including nitric oxide (NO), nitrogen dioxide (NO2), and nitrogen oxides (NOX) were studied. Adjusted generalized additive models (GAMs) were applied to analyse their associations with cardiovascular mortality in different groups. RESULTS The average daily concentrations of NO, NO2, and NOX were 11.7 μg/m3, 30.7 μg/m3, and 53.2 μg/m3, respectively. Significant associations were shown with each indicator. Cumulative effects of nitrogen oxides were more obvious than distributed lag effects. Males, population under 65 years old, and population with stroke-related condition were more susceptible to nitrogen oxides. Adverse effects of nitrogen oxides were more significant at low temperature. Impacts of NO2 on cardiovascular mortality, and NO on stroke mortality were the most robust in the multi-pollutant models, whereas variations were shown in the other relationships. CONCLUSIONS Low levels of nitrogen oxides showed acute and adverse impacts and the interactive roles of temperature on cardiovascular mortality. Cumulative effects were most significant and joint effects of nitrogen oxides required more attention. Population under 65 years old and population with stroke-related health condition were susceptible, especially days at lower temperature.
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Affiliation(s)
- Panjun Gao
- Department of Health, Ethics & Society, CAPHRI Care and Public Health Research Institute, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
| | - Yongsheng Wu
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Lihuan He
- China National Environmental Monitoring Centre, Beijing, China
| | - Li Wang
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Yingbin Fu
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Fengying Zhang
- China National Environmental Monitoring Centre, Beijing, China.
| | - Thomas Krafft
- Department of Health, Ethics & Society, CAPHRI Care and Public Health Research Institute, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
| | - Pim Martens
- Maastricht Sustainability Institute (MSI), Maastricht University, Maastricht, the Netherlands
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Zhu Y, Peng L, Li H, Pan J, Kan H, Wang W. Temporal variations of short-term associations between PM 10 and NO 2 concentrations and emergency department visits in Shanghai, China 2008-2019. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2022; 229:113087. [PMID: 34922167 DOI: 10.1016/j.ecoenv.2021.113087] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 12/06/2021] [Accepted: 12/12/2021] [Indexed: 06/14/2023]
Abstract
Levels and constituents of ambient air pollution have substantially changed in China over the last decade. Such changes may lead to the variations in health effects of air pollution. Very limited studies, however, have investigated the temporal variations in health effects of air pollution on a long-term scale, especially in China. We evaluated the temporal variations in short-term associations between PM10 and NO2 concentrations and emergency department (ED) visits during a 12-year period from 2008 to 2019 in Shanghai, China. A quasi-Poisson generalized linear regression was performed to assess the associations between PM10 and NO2 concentrations and ED visits during entire study period and three specific periods. We evaluated the temporal variations of period-specific associations with an interaction variable between pollutant concentrations and period indicators. We further investigated the concentration-response relationships for specific periods. The effects on specific subpopulations (males and females; 18-65 years old and >65 years old) were also examined. A 10 μg/m3 increase of PM10 and NO2 corresponded to 0.48% (95% CI: 0.36%, 0.59%) and 1.51% (95% CI: 1.25%, 1.78%) increase in ED visits at lag0-7 day for entire study period, respectively. The short-term associations between ED visits and NO2 remained unchanged over time (P-value > 0.05), while the effects from PM10 were significantly inconsistent (P-value < 0.05), with the highest effect observed during the intermediate period of 2012-2015 and the lowest effect observed during the initial period of 2008-2011. Similar temporal trends were found in subgroups, except for elderly group. Despite substantial reduction in ambient PM10 and NO2 concentrations, the short-term effects on ED visits for NO2 remained stable and even increased for PM10. More efforts were needed to reduce harmful components in air pollution mixture to reduce the health hazards of air pollution.
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Affiliation(s)
- Yue Zhu
- School of Public Health, Fudan University, Shanghai 200032, China
| | - Li Peng
- Shanghai Key Laboratory of Meteorology and Health, Shanghai, China
| | - Hao Li
- School of Public Health, Fudan University, Shanghai 200032, China
| | - Jinhua Pan
- School of Public Health, Fudan University, Shanghai 200032, China
| | - Haidong Kan
- School of Public Health, Fudan University, Shanghai 200032, China
| | - Weibing Wang
- School of Public Health, Fudan University, Shanghai 200032, China; Shanghai Key Laboratory of Meteorology and Health, Shanghai, China; Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai 200032, China.
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Saucy A, de Hoogh K, Vienneau D, Tangermann L, Schäffer B, Wunderli JM, Probst-Hensch N, Röösli M. Mutual effects of fine particulate matter, nitrogen dioxide, and fireworks on cause-specific acute cardiovascular mortality: A case-crossover study in communities affected by aircraft noise. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 291:118066. [PMID: 34536646 DOI: 10.1016/j.envpol.2021.118066] [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: 04/15/2021] [Revised: 08/19/2021] [Accepted: 08/27/2021] [Indexed: 06/13/2023]
Abstract
Ambient air pollution is the leading cause of environmental mortality and morbidity worldwide. However, the individual contributions to acute mortality of traffic-related air pollutants such as nitrogen dioxide (NO2) and fine particulate matter (PM2.5) are still debated. We conducted a time-stratified case-crossover study for a population located around Zurich airport in Switzerland, including 24,886 adult cardiovascular deaths from the Swiss National Cohort. We estimated the risk of cause-specific cardiovascular mortality associated with daily NO2 and PM2.5 concentrations at home using distributed lag models up to 7 days preceding death, adjusted for daily temperature, precipitation, acute night-time aircraft noise, firework celebrations, and holidays. Cardiovascular mortality was associated with NO2, whereas the association with PM2.5 disappeared upon adjustment for NO2. The strongest association was observed between NO2 and ischemic stroke mortality (odds ratio = 1.55 per 10 μg/m3, 95% confidence intervals = 1.20-2.00). Cause-specific mortality analyses showed differences in terms of delayed effect: odds ratios were highest at 1-3 days after exposure for most outcomes but at lags of 3-5 days for heart failure. Individual vulnerabilities to NO2 associated cardiovascular mortality also varied by cause of death, possibly highlighting the role of different behaviours and risk factors in the most susceptible groups. The risk of cardiovascular mortality was also increased on firework days and after public holidays, independent from NO2 and PM2.5 concentrations. This study confirms the association between ambient NO2, as a marker for primary emissions, and acute cardiovascular mortality in a specific setting around a major airport. Future research should clarify the role of additional air pollutants including ultra-fine particles on cardiovascular diseases to inform most efficient control measures.
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Affiliation(s)
- Apolline Saucy
- Swiss Tropical and Public Health Institute (SwissTPH), Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Kees de Hoogh
- Swiss Tropical and Public Health Institute (SwissTPH), Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Danielle Vienneau
- Swiss Tropical and Public Health Institute (SwissTPH), Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Louise Tangermann
- Swiss Tropical and Public Health Institute (SwissTPH), Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Beat Schäffer
- Empa, Swiss Federal Laboratories for Materials Science and Technology, Dübendorf, Switzerland
| | - Jean-Marc Wunderli
- Empa, Swiss Federal Laboratories for Materials Science and Technology, Dübendorf, Switzerland
| | - Nicole Probst-Hensch
- Swiss Tropical and Public Health Institute (SwissTPH), Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Martin Röösli
- Swiss Tropical and Public Health Institute (SwissTPH), Basel, Switzerland; University of Basel, Basel, Switzerland.
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Wang M, Li H, Huang S, Qian Y, Steenland K, Xie Y, Papatheodorou S, Shi L. Short-term exposure to nitrogen dioxide and mortality: A systematic review and meta-analysis. ENVIRONMENTAL RESEARCH 2021; 202:111766. [PMID: 34331919 PMCID: PMC8578359 DOI: 10.1016/j.envres.2021.111766] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 07/18/2021] [Accepted: 07/23/2021] [Indexed: 05/05/2023]
Abstract
BACKGROUND Ambient air pollution has been characterized as a leading cause of mortality worldwide and has been associated with cardiovascular and respiratory diseases. There is increasing evidence that short-term exposure to nitrogen dioxide (NO2), is related to adverse health effects and mortality. METHODS We conducted a systematic review of short-term NO2 and daily mortality, which were indexed in PubMed and Embase up to June 2021. We calculated random-effects estimates by different continents and globally, and tested for heterogeneity and publication bias. RESULTS We included 87 articles in our quantitative analysis. NO2 and all-cause as well as cause-specific mortality were positively associated in the main analysis. For all-cause mortality, a 10 ppb increase in NO2 was associated with a 1.58% (95%CI 1.28%-1.88%, I2 = 96.3%, Eggers' test p < 0.01, N = 57) increase in the risk of death. For cause-specific mortality, a 10 ppb increase in NO2 was associated with a 1.72% (95%CI 1.41%-2.04%, I2 = 87.4%, Eggers' test p < 0.01, N = 42) increase in cardiovascular mortality and a 2.05% (95%CI 1.52%-2.59%, I2 = 78.5%, Eggers' test p < 0.01, N = 38) increase in respiratory mortality. In the sensitivity analysis, the meta-estimates for all-cause mortality, cardiovascular and respiratory mortality were nearly identical. The heterogeneity would decline to varying degrees through regional and study-design stratification. CONCLUSIONS This study provides evidence of an association between short-term exposure to NO2, a proxy for traffic-sourced air pollutants, and all-cause, cardiovascular and respiratory mortality.
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Affiliation(s)
- Mingrui Wang
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Haomin Li
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Shiwen Huang
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Yaoyao Qian
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Kyle Steenland
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Yang Xie
- School of Economics and Management, Beihang University, Beijing, China
| | | | - Liuhua Shi
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
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Gong W, Reich BJ, Chang HH. Multivariate Spatial Prediction of Air Pollutant Concentrations with INLA. ENVIRONMENTAL RESEARCH COMMUNICATIONS 2021; 3:101002. [PMID: 35694083 PMCID: PMC9187197 DOI: 10.1088/2515-7620/ac2f92] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Estimates of daily air pollution concentrations with complete spatial and temporal coverage are important for supporting epidemiologic studies and health impact assessments. While numerous approaches have been developed for modeling air pollution, they typically only consider each pollutant separately. We describe a spatial multipollutant data fusion model that combines monitoring measurements and chemical transport model simulations that leverages dependence between pollutants to improve spatial prediction. For the contiguous United States, we created a data product of daily concentration for 12 pollutants (CO, NOx, NO2, SO2, O3, PM10, and PM2.5 species EC, OC, NO3, NH4, SO4) during the period 2005 to 2014. Out-of-sample prediction showed good performance, particularly for daily PM2.5 species EC (R2 = 0.64), OC (R2 = 0.75), NH4 (R2 = 0.84), NO3 (R2 = 0.73), and SO4 (R2 = 0.80). By employing the integrated nested Laplace approximation (INLA) for Bayesian inference, our approach also provides model-based prediction error estimates. The daily data product at 12km spatial resolution will be publicly available immediately upon publication. To our knowledge this is the first publicly available data product for major PM2.5 species and several gases at this spatial and temporal resolution.
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Ye T, Guo S, Xie Y, Chen Z, Abramson MJ, Heyworth J, Hales S, Woodward A, Bell M, Guo Y, Li S. Health and related economic benefits associated with reduction in air pollution during COVID-19 outbreak in 367 cities in China. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2021; 222:112481. [PMID: 34229169 PMCID: PMC8241793 DOI: 10.1016/j.ecoenv.2021.112481] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 06/24/2021] [Accepted: 06/28/2021] [Indexed: 05/17/2023]
Abstract
Due to the COVID-19 outbreak, the Chinese government implemented nationwide traffic restrictions and self-quarantine measures from January 23 to April 8 (in Wuhan), 2020. We estimated how these measures impacted ambient air pollution and the subsequent consequences on health and the health-related economy in 367 Chinese cities. A random forests modeling was used to predict the business-as-usual air pollution concentrations in 2020, after adjusting for the impact of long-term trend and weather conditions. We calculated changes in mortality attributable to reductions in air pollution in early 2020 and health-related economic benefits based on the value of statistical life (VSL). Compared with the business-as-usual scenario, we estimated 1239 (95% CI: 844-1578) PM2.5-related deaths were avoided, as were 2777 (95% CI: 1565-3995) PM10-related deaths, 1587 (95% CI: 98-3104) CO-related deaths, 4711 (95% CI: 3649-5781) NO2-related deaths, 215 (95% CI: 116-314) O3-related deaths, and 1088 (95% CI: 774-1421) SO2-related deaths. Based on the reduction in deaths, economic benefits for in PM2.5, PM10, CO, NO2, O3, and SO2 were 1.22, 2.60, 1.36, 4.05, 0.20, and 0.95 billion USD, respectively. Our findings demonstrate the substantial benefits in human health and health-related costs due to improved urban air quality during the COVID lockdown period in China in early 2020.
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Affiliation(s)
- Tingting Ye
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Level 2, 553 St Kilda Road, Melbourne, VIC 3004, Australia; School of Public Health and Management, Binzhou Medical University, Yantai, Shandong 264003, China
| | - Suying Guo
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); NHC Key Laboratory of Parasite and Vector Biology (National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention), Shanghai 200025, China
| | - Yang Xie
- School of Economics and Management, Beihang University, Beijing 100191, China; Beijing Advanced Innovation Center for Big Data-based Precision Medicine, Beihang University, Beijing 100191, China
| | - Zhaoyue Chen
- Barcelona Institute for Global Health (ISGlobal), Barcelona 08003, Spain
| | - Michael J Abramson
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Level 2, 553 St Kilda Road, Melbourne, VIC 3004, Australia
| | - Jane Heyworth
- School of Population and Global Health, The University of Western Australia, Crawley, WA 6009, Australia
| | - Simon Hales
- Department of Public Health, University of Otago, Wellington, Otago 9016, New Zealand
| | - Alistair Woodward
- School of Population Health, University of Auckland, Auckland 1010, New Zealand
| | - Michelle Bell
- School of the Environment, Yale University, New Haven, CT 06520, USA
| | - Yuming Guo
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Level 2, 553 St Kilda Road, Melbourne, VIC 3004, Australia; School of Public Health and Management, Binzhou Medical University, Yantai, Shandong 264003, China.
| | - Shanshan Li
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Level 2, 553 St Kilda Road, Melbourne, VIC 3004, Australia.
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Song Y, Zhang Y, Wang T, Qian S, Wang S. Spatio-temporal Differentiation in the Incidence of Influenza and Its Relationship with Air Pollution in China from 2004 to 2017. CHINESE GEOGRAPHICAL SCIENCE 2021; 31:815-828. [PMID: 34580569 PMCID: PMC8457542 DOI: 10.1007/s11769-021-1228-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Accepted: 03/25/2021] [Indexed: 05/19/2023]
Abstract
The Healthy China Initiative is a major health strategy being pursued by the country. To prevent and control different types of diseases as well as their complex variants, research on the spatio-temporal differentiation among and mechanisms of influence of epidemic diseases is growing worldwide. This study analyzed monthly data on the incidence of influenza by using different methods, including Moran's I, the hotspot analysis model, concentration analysis, and correlation analysis, to determine the characteristics of spatio-temporal differentiation in the incidence of influenza across prefecture-level cities in China from 2004 to 2017, and to examine its relationship with air pollution. According to the results, the overall incidence of influenza in China exhibited a trend of increase from 2004 to 2017, with small peaks in 2009 and 2014. More cases of influenza were recorded in the first and fourth quarters of each year. Regions with higher incidences of influenza were concentrated in northwestern and northern China, and in the coastal areas of southeastern China. Over time, the distribution of regions with a higher incidence of influenza has shifted from the west to the east of the country. A significant relationship was observed between the incidence of influenza and factors related to air pollution. The contents of five air pollutants (PM2.5, PM10, SO2, NO2, and CO) were significantly positively correlated with the incidence of influenza, with a decreasing order of contribution to it of SO2 > CO > NO2 > PM2.5 > PM10. The content of O3 in the air was negatively correlated with the incidence of influenza. The influence of air pollution-related factors on the incidence of influenza in different regions and seasons showed minor differences. The large-scale empirical results provided here can supply a scientific basis for governmental disease control authorities to formulate strategies for regional prevention and control.
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Affiliation(s)
- Yang Song
- School of Geographical Sciences, Northeast Normal University, Changchun, 130024 China
- Key Laboratory of Geographical Processes and Ecological Security in Changbai Mountains, Ministry of Education, Changchun, 130024 China
| | - Yu Zhang
- School of Geographical Sciences, Northeast Normal University, Changchun, 130024 China
| | - Tingting Wang
- School of Geographical Sciences, Northeast Normal University, Changchun, 130024 China
| | - Sitong Qian
- School of Geographical Sciences, Northeast Normal University, Changchun, 130024 China
| | - Shijun Wang
- School of Geographical Sciences, Northeast Normal University, Changchun, 130024 China
- Key Laboratory of Geographical Processes and Ecological Security in Changbai Mountains, Ministry of Education, Changchun, 130024 China
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Chao L, Lu M, An Z, Li J, Li Y, Zhao Q, Wang Y, Liu Y, Wu W, Song J. Short-term effect of NO 2 on outpatient visits for dermatologic diseases in Xinxiang, China: a time-series study. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2021; 43:1-11. [PMID: 33559783 PMCID: PMC7871127 DOI: 10.1007/s10653-021-00831-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Accepted: 01/23/2021] [Indexed: 05/10/2023]
Abstract
OBJECTIVES As the largest organ of the human body, the skin is the major exposure route of NO2. However, the evidence for a relationship between NO2 exposure and dermatologic diseases (DMs) is limited. This time-series study was conducted to assess the short-term effect of nitrogen dioxide (NO2) exposure on DMs outpatient visits in Xinxiang, China. METHODS Daily recordings of NO2 concentrations, meteorological data, and the outpatient visits data for DMs were collected in Xinxiang from January 1st, 2015, to December 31st, 2018. The analysis method used was based on the generalized additive model (GAM) with quasi-Poisson regression to investigate the relationship between NO2 exposure and DMs outpatient visits. Several covariates, such as long-term trends, seasonality, and weather conditions were controlled. RESULTS A total of 164,270 DMs outpatients were recorded. A 10 μg/m3 increase in NO2 concentrations during the period was associated with a 1.86% increase in DMs outpatient visits (95% confidence intervals [Cl]: 1.06-2.66%). The effect was stronger (around 6 times) in the cool seasons than in warmer seasons and younger patients (< 15 years of age) appeared to be more vulnerable. CONCLUSIONS The findings of this study indicate that short-term exposure to NO2 increases the risk of DMs in Xinxiang, China, especially in the cool seasons. Policymakers should implement more stringent air quality standards to improve air quality.
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Affiliation(s)
- Ling Chao
- Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, School of Public Health, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China
| | - Mengxue Lu
- Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, School of Public Health, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China
| | - Zhen An
- Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, School of Public Health, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China
| | - Juan Li
- Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, School of Public Health, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China
| | - Yuchun Li
- Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, School of Public Health, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China
| | - Qian Zhao
- Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, School of Public Health, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China
| | - Yinbiao Wang
- Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, School of Public Health, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China
| | - Yue Liu
- Chinese Center for Disease Control and Prevention, National Institute of Environmental Health, Beijing, 100021, China
| | - Weidong Wu
- Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, School of Public Health, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China
| | - Jie Song
- Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, School of Public Health, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China.
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The Improvement of Air Quality and Associated Mortality during the COVID-19 Lockdown in One Megacity of China: An Empirical Strategy. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18168702. [PMID: 34444451 PMCID: PMC8391611 DOI: 10.3390/ijerph18168702] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 08/09/2021] [Accepted: 08/14/2021] [Indexed: 11/17/2022]
Abstract
Although the lockdown policy implemented during the COVID-19 pandemic indeed improved the air quality and reduced the related health risks, the real effects of the lockdown and its resulting health risks remain unclear considering the effects of unobserved confounders and the longstanding efforts of the government regarding air pollution. We compared air pollution between the lockdown period and the period before the lockdown using a difference-in-differences (DID) model and estimated the mortality burden caused by the number of deaths related to air pollution changes. The NO2 and CO concentrations during the lockdown period (17 days) declined by 8.94 μg/m3 (relative change: 16.94%; 95% CI: 3.71, 14.16) and 0.20 mg/m3 (relative change: 16.95%; 95% CI: 0.04, 0.35) on an average day, respectively, and O3 increased by 8.41 μg/m3 (relative change: 32.80%; 95% CI: 4.39, 12.43); no meaningful impacts of the lockdown policy on the PM2.5, PM10, SO2, or the AQI values were observed. Based on the three clearly changed air pollutants, the lockdown policy prevented 8.22 (95% CI: 3.97, 12.49) all-cause deaths. Our findings suggest that the overall excess deaths caused by air pollution during the lockdown period declined. It is beneficial for human health when strict control measures, such as upgrading industry structure and promoting green transportation, are taken to reduce emissions, especially in cities with serious air pollution in China, such as Shijiazhuang.
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Jia C, Li W, Wu T, He M. Road traffic and air pollution: Evidence from a nationwide traffic control during coronavirus disease 2019 outbreak. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 781:146618. [PMID: 33780836 PMCID: PMC9671408 DOI: 10.1016/j.scitotenv.2021.146618] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 02/10/2021] [Accepted: 03/15/2021] [Indexed: 06/12/2023]
Abstract
Existing estimations of air pollution from automobile sources are based on either experiments or small-scale governmental interventions. China's nationwide traffic control during the coronavirus disease 2019 outbreak provided us a unique opportunity to assess the direct dose-effect relationship between vehicle density and air pollution. We found that, during the coronavirus disease 2019 outbreak, the nationwide reduced air pollution (except for O3) could be largely explained by traffic control measures. During the traffic control period, every doubling of vehicle density was associated with a decrease of 4.2 (2.0, 6.4) μg/m3 in PM2.5, 5.5 (2.9, 8.1) μg/m3 in PM10, 1.5 (0.9, 2.0) μg/m3 in NO2, and 0.04 (0.02, 0.07) mg/m3 in CO comparing cities with different vehicle densities. Similarly, for every 10% increase in the truck proportion, PM2.5 decreased by 12.3 (4.1, 20.6) μg/m3, PM10 decreased by 14.3 (4.6, 23.9) μg/m3, and CO decreased by 0.14 (0.05, 0.23) mg/m3. Moreover, the associations between vehicle density and reduction in PM2.5, PM10, and CO during the traffic control period were stronger and showed near-complete linearity in cities with low green coverage rate (All P < 0.05 for interaction). According to our estimation, PM2.5 emissions from every doubling of vehicle density can lead to over 8000 excess deaths per year, 66% of which were caused by cardiopulmonary diseases. This natural experiment study is the first to observe the dose-effect relationship between on-road traffic and traffic-generated air pollution, as well as the mitigating effect of urban greening. Findings provide key evidence to the assessment and control of traffic-generated air pollution and its public health impact.
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Affiliation(s)
- Chengyong Jia
- Department of Occupational and Environmental Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan 430030, Hubei, China
| | - Wending Li
- Department of Occupational and Environmental Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan 430030, Hubei, China
| | - Tangchun Wu
- Department of Occupational and Environmental Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan 430030, Hubei, China
| | - Meian He
- Department of Occupational and Environmental Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan 430030, Hubei, China.
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45
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Qiu W, He H, Xu T, Jia C, Li W. The air quality changes and related mortality benefits during the coronavirus disease 2019 pandemic in China: Results from a nationwide forecasting study. JOURNAL OF CLEANER PRODUCTION 2021; 308:127327. [PMID: 34690451 PMCID: PMC8525877 DOI: 10.1016/j.jclepro.2021.127327] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 04/25/2021] [Accepted: 04/27/2021] [Indexed: 06/13/2023]
Abstract
Air quality changes during the coronavirus disease 2019 (COVID-19) pandemic in China has attracted increasing attention. However, more details in the changes, future air quality trends, and related death benefits on a national scale are still unclear. In this study, a total of 352 Chinese cities were included. We collected air pollutants (including fine particulate matter [PM2.5], inhalable particulate matter [PM10], nitrogen dioxide [NO2], and ozone [O3]) data for each city from January 2015 to July 2020. Convolutional neural network-quantile regression (CNN-QR) forecasting model was used to predict pollutants concentrations from February 2020 to January 2021 and the changes in air pollutants were compared. The relationships between the socioeconomic factors and the changes and the avoided mortality due to the changes were further estimated. We found sharp declines in all air pollutants from February 2020 to January 2021. Specifically, PM2.5, PM10, NO2, and O3 would drop by 3.86 μg/m3 (10.81%), 4.84 μg/m3 (7.65%), 0.55 μg/m3 (2.18%), and 3.14 μg/m3 (3.36%), respectively. The air quality changes were significantly related to many of the socioeconomic factors, including the size of built-up area, gross regional product, population density, gross regional product per capita, and secondary industry share. And the improved air quality would avoid a total of 7237 p.m.2.5-related deaths (95% confidence intervals [CI]: 4935, 9209), 9484 p.m.10-related deaths (95%CI: 5362, 13604), 4249 NO2-related deaths (95%CI: 3305, 5193), and 6424 O3-related deaths (95%CI: 3480, 9367), respectively. Our study shows that the interventions to control COVID-19 would improve air quality, which had significant relationships with some socioeconomic factors. Additionally, improved air quality would reduce the number of non-accidental deaths.
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Affiliation(s)
- Weihong Qiu
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, And State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Heng He
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Tao Xu
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, And State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Chengyong Jia
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, And State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Wending Li
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
- Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, And State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
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46
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Huang J, Li J, Yin P, Wang L, Pan X, Zhou M, Li G. Ambient nitrogen dioxide and years of life lost from chronic obstructive pulmonary disease in the elderly: A multicity study in China. CHEMOSPHERE 2021; 275:130041. [PMID: 33652282 DOI: 10.1016/j.chemosphere.2021.130041] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 01/29/2021] [Accepted: 02/16/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality worldwide, and nitrogen dioxide (NO2) is a potential environmental risk factor for COPD. However, association between ambient NO2 and COPD risk remains underrecognized, especially in the elderly. This study aimed to explore association between NO2 and years of life lost (YLL) from COPD in the elderly from 2013 to 2017 in 37 major cities in China. METHODS Ambient NO2 data and COPD morality information were obtained from the National Urban Air Quality Real-time Publishing Platform and the Chinese Centers for Disease Control and Prevention, respectively. City-specific relative changes in YLL were estimated by generalized additive models, and meta-analysis was used to combine city-specific results. Potential modifications were evaluated. Economic loss due to excess YLL from COPD associated with ambient NO2 was evaluated. RESULTS An increase of 10 μg/m3 in NO2 for 2-day moving average led to 0.94% (95% CI: 0.56%, 1.31%) relative increase in COPD YLL. The associations were significantly higher in South than North China. Higher estimated effects were found in the warm than the cool season in the southern region. The relevant economic loss accounted for 0.04% (95% CI: 0.02%, 0.05%) of the gross domestic product (GDP) in China during the same period. CONCLUSIONS The findings provide evidence on the impact of short-term NO2 exposure on COPD YLL in the elderly, which indicated more stringent control of NO2 pollution and highlighted the need to protect the elderly during the warm season in South China.
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Affiliation(s)
- Jing Huang
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing, China
| | - Jie Li
- Department of Occupational Health and Environmental Health, School of Public Health, Capital Medical University, Beijing, China; National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Peng Yin
- 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
| | - Xiaochuan Pan
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing, China
| | - Maigeng Zhou
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
| | - Guoxing Li
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing, China.
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Association between Atrial Fibrillation Incidence and Temperatures, Wind Scale and Air Quality: An Exploratory Study for Shanghai and Kunming. SUSTAINABILITY 2021. [DOI: 10.3390/su13095247] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
As a common cardiovascular disease, atrial fibrillation has the characteristics of high morbidity, high disability, and high fatality rates, seriously endangering human health and sustainability. Some research has confirmed that environmental factors are related to the risk of illness and death from cardiovascular diseases (including atrial fibrillation), while there is still little comparison on the situation of the two cities in China. This research uses medical data in Shanghai and Kunming establishing, through two-step research, logistic models to compare the impacts on atrial fibrillation incidence to figure out the association between environmental factors (including air pollution, weather, temperature, and wind scales) and atrial fibrillation. Finally, this research shows that environmental impacts on atrial fibrillation prevalence have generality, regionality, and lagging characteristics. The result is significant for atrial fibrillation patients and provides a reliable medical theory basis for nursing measures. Besides, this research provides a prospective method of offering early warning for potential atrial fibrillation patients, helping to maintain human beings’ sustainable development.
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48
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Chossière GP, Xu H, Dixit Y, Isaacs S, Eastham SD, Allroggen F, Speth RL, Barrett SRH. Air pollution impacts of COVID-19-related containment measures. SCIENCE ADVANCES 2021; 7:eabe1178. [PMID: 34020946 PMCID: PMC8139585 DOI: 10.1126/sciadv.abe1178] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Accepted: 04/02/2021] [Indexed: 05/05/2023]
Abstract
Responses to the COVID-19 outbreak resulted in one of the largest short-term decreases in anthropogenic emissions in modern history. To date, there has been no comprehensive assessment of the impact of lockdowns on air quality and human health. Using global satellite observations and ground measurements from 36 countries in Europe, North America, and East Asia, we find that lockdowns led to reductions in NO2 concentrations globally, resulting in ~32,000 avoided premature mortalities, including ~21,000 in China. However, we do not find corresponding reductions in PM2.5 and ozone globally. Using satellite measurements, we show that the disconnect between NO2 and ozone changes stems from local chemical regimes. The COVID-related lockdowns demonstrate the need for targeted air quality policies to reduce the global burden of air pollution, especially related to secondary pollutants.
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Affiliation(s)
- Guillaume P Chossière
- Laboratory for Aviation and the Environment, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Haofeng Xu
- Laboratory for Aviation and the Environment, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Yash Dixit
- Laboratory for Aviation and the Environment, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Stewart Isaacs
- Laboratory for Aviation and the Environment, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Sebastian D Eastham
- Laboratory for Aviation and the Environment, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA, USA
- Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Florian Allroggen
- Laboratory for Aviation and the Environment, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA, USA
- Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Raymond L Speth
- Laboratory for Aviation and the Environment, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA, USA
- Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Steven R H Barrett
- Laboratory for Aviation and the Environment, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Mechanical Engineering, Seoul National University, Seoul, South Korea
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49
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Ling C, Li Y. Substantial Changes of Gaseous Pollutants and Health Effects During the COVID-19 Lockdown Period Across China. GEOHEALTH 2021; 5:e2021GH000408. [PMID: 34084983 PMCID: PMC8144698 DOI: 10.1029/2021gh000408] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 04/15/2021] [Accepted: 05/03/2021] [Indexed: 05/09/2023]
Abstract
The human movement and economic activities have been drastically reduced due to the Coronavirus Disease 2019 (COVID-19) outbreak, leading to the sharp decreases of pollutant emissions and remarkable air quality improvement. Nevertheless, however, the changes of gaseous pollutant concentrations and health effects across China during the COVID-19 lockdown period remained poorly understood. Here, a random forest model was applied to assess the impact of COVID-19 lockdown on pollutant concentrations and potential health effects. The results suggested that estimated NO2, SO2, and CO concentrations in China during January 23-March 31, 2020 decreased by 13.68%, 25.71%, and 7.42%, respectively compared with the same periods in 2018-2019. Nonetheless, the predicted 8-h O3 concentrations across China suffered from 1.29% increases during this period. The avoided premature all-cause, cardiovascular disease (CVD), respiratory disease (RD), and chronic obstructive pulmonary disease (COPD) mortalities induced by NO2 decrease during COVID-19 lockdown period reached 3,954 (3,076-4,832), 635 (468-801), 612 (459-765), and 920 (653-1,186) cases. However, the increases of all-cause, CVD, RD, and COPD mortalities due to O3 increase during COVID-19 lockdown period achieved 462 (250-674), 79 (29-129), 40 (-25-105), and 52 (-34-138) cases. The natural experiment demonstrated the drastic emission reduction measures could significantly decrease the NO2, SO2, and CO concentrations, while they significantly elevated the O3 concentration. It is highly imperative to propose more coordinated air pollution control strategies to control O3 pollution.
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Affiliation(s)
- Chaohao Ling
- State Key Laboratory of Lake Science and EnvironmentNanjing Institute of Geography and LimnologyChinese Academy of SciencesNanjingChina
- University of Chinese Academy of SciencesBeijingChina
| | - Yongfei Li
- Hunan Provincial Key Laboratory of Ecological TourismCollege of Tourism & Management ProjectJishou UniversityZhangjiajieChina
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50
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Meng X, Liu C, Chen R, Sera F, Vicedo-Cabrera AM, Milojevic A, Guo Y, Tong S, Coelho MDSZS, Saldiva PHN, Lavigne E, Correa PM, Ortega NV, Osorio S, Garcia, Kyselý J, Urban A, Orru H, Maasikmets M, Jaakkola JJK, Ryti N, Huber V, Schneider A, Katsouyanni K, Analitis A, Hashizume M, Honda Y, Ng CFS, Nunes B, Teixeira JP, Holobaca IH, Fratianni S, Kim H, Tobias A, Íñiguez C, Forsberg B, Åström C, Ragettli MS, Guo YLL, Pan SC, Li S, Bell ML, Zanobetti A, Schwartz J, Wu T, Gasparrini A, Kan H. Short term associations of ambient nitrogen dioxide with daily total, cardiovascular, and respiratory mortality: multilocation analysis in 398 cities. BMJ 2021; 372:n534. [PMID: 33762259 PMCID: PMC7988454 DOI: 10.1136/bmj.n534] [Citation(s) in RCA: 73] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
OBJECTIVE To evaluate the short term associations between nitrogen dioxide (NO2) and total, cardiovascular, and respiratory mortality across multiple countries/regions worldwide, using a uniform analytical protocol. DESIGN Two stage, time series approach, with overdispersed generalised linear models and multilevel meta-analysis. SETTING 398 cities in 22 low to high income countries/regions. MAIN OUTCOME MEASURES Daily deaths from total (62.8 million), cardiovascular (19.7 million), and respiratory (5.5 million) causes between 1973 and 2018. RESULTS On average, a 10 μg/m3 increase in NO2 concentration on lag 1 day (previous day) was associated with 0.46% (95% confidence interval 0.36% to 0.57%), 0.37% (0.22% to 0.51%), and 0.47% (0.21% to 0.72%) increases in total, cardiovascular, and respiratory mortality, respectively. These associations remained robust after adjusting for co-pollutants (particulate matter with aerodynamic diameter ≤10 μm or ≤2.5 μm (PM10 and PM2.5, respectively), ozone, sulfur dioxide, and carbon monoxide). The pooled concentration-response curves for all three causes were almost linear without discernible thresholds. The proportion of deaths attributable to NO2 concentration above the counterfactual zero level was 1.23% (95% confidence interval 0.96% to 1.51%) across the 398 cities. CONCLUSIONS This multilocation study provides key evidence on the independent and linear associations between short term exposure to NO2 and increased risk of total, cardiovascular, and respiratory mortality, suggesting that health benefits would be achieved by tightening the guidelines and regulatory limits of NO2.
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Affiliation(s)
- Xia Meng
- School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of Health, Fudan University, P O Box 249, 130 Dong-An Road, Shanghai 200032, China
| | - Cong Liu
- School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of Health, Fudan University, P O Box 249, 130 Dong-An Road, Shanghai 200032, China
| | - Renjie Chen
- School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of Health, Fudan University, P O Box 249, 130 Dong-An Road, Shanghai 200032, China
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Fudan University, Shanghai, China
| | - Francesco Sera
- Department of Public Health, Environments and Society, London School of Hygiene and Tropical Medicine, London, UK
- Department of Statistics, Computer Science and Applications "G Parenti," University of Florence, Florence, Italy
| | - Ana Maria Vicedo-Cabrera
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
- Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
| | - Ai Milojevic
- Department of Public Health, Environments and Society, London School of Hygiene and Tropical Medicine, London, UK
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
- School of Public Health and Management, Binzhou Medical University, Yantai, Shandong, China
| | - Shilu Tong
- Shanghai Children's Medical Centre, Shanghai Jiao Tong 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, QLD, Australia
- Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | | | | | - Eric Lavigne
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada
- Air Health Science Division, Health Canada, Ottawa, ON, Canada
| | | | | | | | - Garcia
- Instituto Nacional de Salud Pública de México, Cuernavaca, México
| | - Jan Kyselý
- Institute of Atmospheric Physics, Czech Academy of Sciences, Prague, Czech Republic
- Faculty of Environmental Sciences, Czech University of Life Sciences, Prague, Czech Republic
| | - Aleš Urban
- Institute of Atmospheric Physics, Czech Academy of Sciences, Prague, Czech Republic
- Faculty of Environmental Sciences, Czech University of Life Sciences, Prague, Czech Republic
| | - Hans Orru
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
- Institute of Family Medicine and Public Health, University of Tartu, Tartu, Estonia
| | | | - Jouni J K Jaakkola
- Center for Environmental and Respiratory Health Research (CERH), University of Oulu, Oulu, Finland
| | - Niilo Ryti
- Center for Environmental and Respiratory Health Research (CERH), University of Oulu, Oulu, Finland
| | - Veronika Huber
- Potsdam Institute for Climate Impact Research, Potsdam, Germany
- Universidad Pablo de Olavide, Department of Physical, Chemical, and Natural Systems, Sevilla, Spain
| | - Alexandra Schneider
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Klea Katsouyanni
- Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
- School of Population Health & Environmental Sciences, King's College London, London, UK
| | - Antonis Analitis
- Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Masahiro Hashizume
- Department of Global Health Policy, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Yasushi Honda
- Faculty of Health and Sport Sciences, University of Tsukuba, Tsukuba, Japan
| | - Chris Fook Sheng Ng
- School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan
| | - Baltazar Nunes
- Department of Environmental Health, Portuguese National Institute of Health, Porto, Portugal
| | - João Paulo Teixeira
- Department of Environmental Health, Portuguese National Institute of Health, Porto, Portugal
- EPIUnit - Instituto de Saúde Pública, Universidade do Porto, Porto, Portugal
| | | | | | - Ho Kim
- Department of Public Health Science, Graduate School of Public Health and Institute of Health and Environment, Seoul National University, Seoul, South Korea
| | - 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
| | - Carmen Íñiguez
- Department of Statistics and Operational Research, Universitat de València, València, Spain
- CIBER of Epidemiology and Public Health, Madrid, Spain
| | - Bertil Forsberg
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Christofer Åström
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Martina S Ragettli
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Yue-Liang Leon Guo
- Environmental and Occupational Medicine, National Taiwan University College of Medicine and NTU Hospital, Taipei, Taiwan
- National Institute of Environmental Health Sciences, National Health Research Institute, Miaoli, Taiwan
| | - Shih-Chun Pan
- National Institute of Environmental Health Sciences, National Health Research Institute, Miaoli, Taiwan
| | - Shanshan Li
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Michelle L Bell
- School of the Environment, Yale University, New Haven, CT, USA
| | - Antonella Zanobetti
- Department of Environmental Health, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Joel Schwartz
- Department of Environmental Health, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Tangchun Wu
- Key Laboratory of Environment and Health, Ministry of Education, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Antonio Gasparrini
- Department of Public Health, Environments and Society, London School of Hygiene and Tropical Medicine, London, UK
- Centre for Statistical Methodology, London School of Hygiene and Tropical Medicine, London, UK
- Centre on Climate Change and Planetary Health, London School of Hygiene and Tropical Medicine, London, UK
| | - Haidong Kan
- School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of Health, Fudan University, P O Box 249, 130 Dong-An Road, Shanghai 200032, China
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Fudan University, Shanghai, China
- Children's Hospital of Fudan University, National Centre for Children's Health, Shanghai, China
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