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Wang Y, Chang J, Hu P, Deng C, Luo Z, Zhao J, Zhang Z, Yi W, Zhu G, Zheng G, Wang S, He K, Liu J, Liu H. Key factors in epidemiological exposure and insights for environmental management: Evidence from meta-analysis. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 362:124991. [PMID: 39303936 PMCID: PMC7616677 DOI: 10.1016/j.envpol.2024.124991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2024] [Revised: 08/14/2024] [Accepted: 09/17/2024] [Indexed: 09/22/2024]
Abstract
In recent years, the precision of exposure assessment methods has been rapidly improved and more widely adopted in epidemiological studies. However, such methodological advancement has introduced additional heterogeneity among studies. The precision of exposure assessment has become a potential confounding factors in meta-analyses, whose impacts on effect calculation remain unclear. To explore, we conducted a meta-analysis to integrate the long- and short-term exposure effects of PM2.5, NO2, and O3 on all-cause, cardiovascular, and respiratory mortality in the Chinese population. Literature was identified through Web of Science, PubMed, Scopus, and China National Knowledge Infrastructure before August 28, 2023. Sub-group analyses were performed to quantify the impact of exposure assessment precisions and pollution levels on the estimated risk. Studies achieving merely city-level resolution and population exposure are classified as using traditional assessment methods, while those achieving sub-kilometer simulations and individual exposure are considered finer assessment methods. Using finer assessment methods, the RR (under 10 μg/m3 increment, with 95% confidence intervals) for long-term NO2 exposure to all-cause mortality was 1.13 (1.05-1.23), significantly higher (p-value = 0.01) than the traditional assessment result of 1.02 (1.00-1.03). Similar trends were observed for long-term PM2.5 and short-term NO2 exposure. A decrease in short-term PM2.5 levels led to an increase in the RR for all-cause and cardiovascular mortality, from 1.0035 (1.0016-1.0053) and 1.0051 (1.0021-1.0081) to 1.0055 (1.0035-1.0075) and 1.0086 (1.0061-1.0111), with weak between-group significance (p-value = 0.13 and 0.09), respectively. Based on the quantitative analysis and literature information, we summarized four key factors influencing exposure assessment precision under a conceptualized framework: pollution simulation resolution, subject granularity, micro-environment classification, and pollution levels. Our meta-analysis highlighted the urgency to improve pollution simulation resolution, and we provide insights for researchers, policy-makers and the public. By integrating the most up-to-date epidemiological research, our study has the potential to provide systematic evidence and motivation for environmental management.
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Affiliation(s)
- Yongyue Wang
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Jie Chang
- National Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, Beijing, 100084, China; Centre for Clinical and Epidemiologic Research, Beijing an Zhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, 100029, China
| | - Piaopiao Hu
- Centre for Clinical and Epidemiologic Research, Beijing an Zhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, 100029, China
| | - Chun Deng
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Zhenyu Luo
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Junchao Zhao
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Zhining Zhang
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Wen Yi
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Guanlin Zhu
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Guangjie Zheng
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Shuxiao Wang
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Kebin He
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Jing Liu
- Centre for Clinical and Epidemiologic Research, Beijing an Zhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, 100029, China
| | - Huan Liu
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China.
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Shi Y, Li N, Li Z, Chen M, Chen Z, Wan X. Impact of comprehensive air pollution control policies on six criteria air pollutants and acute myocardial infarction morbidity, Weifang, China: A quasi-experimental study. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 922:171206. [PMID: 38408668 DOI: 10.1016/j.scitotenv.2024.171206] [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: 10/31/2023] [Revised: 02/06/2024] [Accepted: 02/21/2024] [Indexed: 02/28/2024]
Abstract
Comprehensive air pollution control policies may reduce pollutant emissions. However, the impact on disease morbidity of the change for the concentration of air pollutants following the policies has been insufficiently studied. We aim to assess the impact of comprehensive air pollution control policies on the levels of six criteria air pollutants and acute myocardial infarction (AMI) morbidity in Weifang, China. This study performed an interrupted time series analysis. The linear model with spline terms and generalized additive quasi-Poisson model were used to estimate the immediate change from 2016 to 2019 in the daily concentration of six air pollutants (PM2.5, PM10, SO2, NO2, O3, and, CO) and AMI incident cases (Age ≥35) associated with the implementation of air pollution control policies in Weifang, respectively. After the implementation of air pollution control policies, air quality in Weifang had been improved. Specifically, the daily concentrations of PM2.5, PM10, SO2, and, CO immediately decreased by 27.9 % (95 % CI: 6.6 % to 44.3 %), 32.9 % (95 % CI: 17.5 % to 45.5 %), 14.6 % (95 % CI: 0.4 % to 26.8 %), and 33.9 % (95 % CI: 22.0 % to 44.0 %), respectively. In addition, the policies implementation was also associate with the immediate decline in the AMI morbidity (-6.5 %, 95 % CI: -10.4 % to -2.3 %). And subgroup analyses indicate that the health effects of the policy intervention were only observed in female (-9.4 %, 95 % CI: -14.4 % to -4.2 %) and those aged ≥65 years (-10.5 %, 95 % CI: -14.6 % to -6.2 %). During the final 20 months of the study period, the policy intervention was estimated to prevent 1603 (95 % CI: 574 to 2587) cases of incident AMI in Weifang. Our results provide strong rationale that the policy intervention significantly reduced ambient pollutant concentrations and AMI morbidity, which highlighted the importance for a comprehensive and rigorous air pollution control policy in regions with severe air pollution.
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Affiliation(s)
- Yulin Shi
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine Peking Union Medical College, Beijing 100005, China
| | - Ning Li
- Weifang Center for Disease Control and Prevention, Weifang 261061, Shandong, China
| | - Zhongyan Li
- Weifang People's Hospital, Weifang 261044, Shandong, China
| | - Min Chen
- Weifang Center for Disease Control and Prevention, Weifang 261061, Shandong, China
| | - Zuosen Chen
- Weifang Center for Disease Control and Prevention, Weifang 261061, Shandong, China
| | - Xia Wan
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine Peking Union Medical College, Beijing 100005, China.
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Mu J, Zhong H, Jiang M. Effects of ambient PM 2.5 on non-accidental death: a time-series study in Shenzhen, China during 2014-2019. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2024:1-12. [PMID: 38602490 DOI: 10.1080/09603123.2024.2341430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2024] [Accepted: 04/06/2024] [Indexed: 04/12/2024]
Abstract
This study aims to investigate the impact of PM2.5 on non-accidental death of residents. The single-pollutant model revealed that the influence of PM2.5 on non-accidental death was significant at lag0 and lag4-6, and was greatest at lag5. A 10 µg/m3 increase in PM2.5 was related with a 1.31% increase in non-accidental deaths. The connection between PM2.5 and non-accidental death was stronger in femalesthan males, in people aged ≥ 65 years than people aged < 65 years, and in people below high school education than people with high school education or above. Two-pollutant model revealed that the influence of PM2.5 on non-accidental death was essentially unchanged when CO, SO2, and O3 were included and reduced when NO2 was included. The multiple-pollutant model showed that the effect of ambient PM2.5 on non-accidental death was reduced. An increase in PM2.5 concentrations may cause an increase in non-accidental death.
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Affiliation(s)
- Jingfeng Mu
- Department of Public Health, Shenzhen Eye Hospital, Shenzhen, China
| | - Haoxi Zhong
- Department of Public Health, Shenzhen Eye Hospital, Shenzhen, China
| | - Mingjie Jiang
- Department of Public Health, Shenzhen Eye Hospital, Shenzhen, China
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Guo X, Su W, Wang H, Li N, Song Q, Liang Q, Sun C, Liang M, Zhou Z, Song EJ, Sun Y. Short-term exposure to ambient ozone and cardiovascular mortality in China: a systematic review and meta-analysis. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2023; 33:958-975. [PMID: 35438585 DOI: 10.1080/09603123.2022.2066070] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 04/09/2022] [Indexed: 06/14/2023]
Abstract
Air pollution is a major public health concern in China. Notwithstanding this, there is limited evidence regarding the impact of short-term exposure to ambient ozone on cardiovascular mortality in the Chinese population. Therefore, we conducted this meta-analysis to address this important question. The random-effects model was applied to pool the results from individual studies. Finally, 32 effect estimates extracted from 19 studies were pooled in this meta-analysis. The pooled relative risk for cardiovascular mortality for each 10 µg/m3 increment in ozone concentration was 1.0068 (95% CI: 1.0049, 1.0086). Ths significant positive association between ozone exposure and cardiovascular mortality was also observed in different two-pollutant models. This meta-analysis revealed that exposure to ozone was associated with an increased risk of cardiovascular mortality in China, and more efforts on controlling the population from ozone are needed to improve cardiovascular health of Chinese population.
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Affiliation(s)
- Xianwei Guo
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, P.R. China
| | - Wanying Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, P.R. China
| | - Hao Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, P.R. China
| | - Ning Li
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, P.R. China
| | - Qiuxia Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, P.R. China
| | - Qiwei Liang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, P.R. China
| | - Chenyu Sun
- Internal Medicine, AMITA Health Saint Joseph Hospital Chicago, Chicago, IL, USA
| | - Mingming Liang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, P.R. China
| | - Zhen Zhou
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia
| | - Evelyn J Song
- Division of Hospital Medicine, Department of Medicine, University of California, San Francisco, CA, USA
| | - Yehuan Sun
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, P.R. China
- Chaohu Hospital of Anhui Medical University, Hefei, Anhui Province, P.R. China
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5
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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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Zhang X, Yan B, Zhou Y, Osei F, Li Y, Zhao H, Cheng C, Stein A. Short-term health impacts related to ozone in China before and after implementation of policy measures: A systematic review and meta-analysis. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 847:157588. [PMID: 35882322 DOI: 10.1016/j.scitotenv.2022.157588] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 07/10/2022] [Accepted: 07/19/2022] [Indexed: 05/29/2023]
Abstract
This paper presents a meta-analysis of the impacts of short-term exposure to ozone (O3) on three health endpoints: all-cause, cardiovascular, and respiratory mortality in China. All relevant studies from January 1990 to December 2021 were searched from four databases. After screening, 30 studies were included for the meta-analysis. The results showed that a significant rise of 0.41 % (95 % confidence interval (CI): 0.35 %-0.48 %) in all-cause, 0.60 % (95 % CI: 0.51 %-0.68 %) in cardiovascular and 0.45 % (95 % CI: 0.28 %-0.62 %) in respiratory mortality for each 10 μg m-3 increase in the maximum daily 8 h average O3 concentration (MDA8 O3). Moreover, results stratified by heterogeneous time periods before and after implementing a policy measure in 2013, showed that the pooled effects for all-cause and respiratory mortality before were greater than those after, while the pooled effects for cardiovascular mortality before 2013 were slightly smaller than those after. The finding that short-term exposure to O3 was positively related to the three health endpoints was validated by means of a sensitivity analysis. Furthermore, we did not observe any publication bias. Our results present an updated and better understanding of the relationship between short-term exposure to O3 and the three health endpoints, while providing a reference for further assessment of the impact of short-term O3 exposure on human health.
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Affiliation(s)
- Xiangxue Zhang
- Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China; Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede 7514AE, the Netherlands
| | - Bin Yan
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Yinying Zhou
- School of Information Science and Technology, Hangzhou Normal University, Hangzhou 311121, China
| | - Frank Osei
- Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede 7514AE, the Netherlands
| | - Yao Li
- Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede 7514AE, the Netherlands
| | - Hui Zhao
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
| | - Changxiu Cheng
- Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China; National Tibetan Plateau Data Center, Beijing 100101, China.
| | - Alfred Stein
- Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede 7514AE, the Netherlands.
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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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8
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Guan Y, Xiao Y, Chu C, Zhang N, Yu L. Trends and characteristics of ozone and nitrogen dioxide related health impacts in Chinese cities. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2022; 241:113808. [PMID: 35759982 DOI: 10.1016/j.ecoenv.2022.113808] [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: 12/23/2021] [Revised: 06/02/2022] [Accepted: 06/21/2022] [Indexed: 06/15/2023]
Abstract
Ambient ozone pollution has been becoming severe and attributed to considerable health impacts in China. Nitrogen dioxide (NO2) is involved in atmospheric ozone production while also affecting public health directly. Joint control ozone and NO2 pollution would be of significance. This study quantitatively assessed the health impact attributed to ambient ozone and NO2 pollution in 338 Chinese cities from 2015 to 2020. The results reveal the generally opposite trends of ozone- and NO2-related health impacts in China. From 2015-2020, respiratory and chronic obstructive pulmonary disease (COPD) health impacts attributed to ozone in 338 cities increased by 65.30% and 63.98%. The NO2-attributed health impacts decreased by 24.80% and 24.62%. In 2020, the ozone- and NO2-related respiratory health impacts were 3.96 million DALYs (disability-adjusted life years) and 1.47 million DALYs. High health impacts are concentrated in big cities and city clusters. In 2020, the sum of ozone- and NO2-related respiratory health impacts in the top 20 cities was 0.98 million DALYs and 0.44 million DALYs, accounting for 24.70% and 30.24% of the 338 cities. The population attribution fraction analysis identified the increasing distributional consistency of ozone and NO2-related health impacts, emphasizing the necessity and possible efficiency of ozone-NO2 joint control. Emission source analysis based on gridded data provided a reference for understanding health impacts and developing targeted strategies.
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Affiliation(s)
- Yang Guan
- Institute of Strategic Planning, Chinese Academy of Environmental Planning, Beijing 100012, China; The Center for Beautiful China, Chinese Academy of Environmental Planning, Beijing 100012, China
| | - Yang Xiao
- Institute of Strategic Planning, Chinese Academy of Environmental Planning, Beijing 100012, China; The Center for Beautiful China, Chinese Academy of Environmental Planning, Beijing 100012, China
| | - Chengjun Chu
- Center of Environmental Status and Plan Assessment, Chinese Academy of Environmental Planning, Beijing 100012, China
| | - Nannan Zhang
- Institute of Strategic Planning, Chinese Academy of Environmental Planning, Beijing 100012, China; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China.
| | - Lei Yu
- Institute of Strategic Planning, Chinese Academy of Environmental Planning, Beijing 100012, China.
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Gao J, Li Y, Xie Z, Hu B, Wang L, Bao F, Fan S. The impact of the aerosol reduction on the worsening ozone pollution over the Beijing-Tianjin-Hebei region via influencing photolysis rates. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 821:153197. [PMID: 35063532 DOI: 10.1016/j.scitotenv.2022.153197] [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: 12/10/2021] [Revised: 01/10/2022] [Accepted: 01/12/2022] [Indexed: 06/14/2023]
Abstract
Due to the implementation of the toughest-ever emission control actions across China from 2013 to present, the aerosols are decreasing annually but ozone is simultaneously increasing, especially over the Beijing-Tianjin-Hebei (BTH) region, where ozone pollution can even spread into winter. Quantifying each impact of aerosols on ozone in all seasons is urgent for the worsening ozone pollution in the improved aerosol air quality. In this study, we focused on the impact of aerosols on ozone via influencing photolysis rates. The air pollutants were simulated over the Central East China (CEC) in 2018 by using the Weather Research and Forecasting with Chemistry (WRF-Chem) model. By implementing emissions with base years of 2014 and 2018, we quantified the increase in ozone (ΔOzone_photolysis) caused by the decreasing aerosol concentrations (ΔPM2.5) by influencing photolysis rates over the BTH region in all seasons. Furthermore, combined with the ozone observations, the contribution of ΔOzone_photolysis to the total changes in ozone (ΔOzone_total) in all seasons was quantitatively discussed. Our results showed that ΔPM2.5 showed obvious seasonal variations, which PM2.5 decreased more significantly in winter and autumn than in spring and summer, although significant reductions in anthropogenic emissions were observed in all seasons. Consistent seasonal variations were also observed in ΔOzone_photolysis, and the mean increases reached 5.5 μg m-3, 2.6 μg m-3, 1.2 μg m-3, and 1.4 μg m-3 in winter, autumn, spring, spring, and summer, respectively. Compared with ΔOzone_total, ΔOzone_photolysis accounted for 36.3%, 17.2%, 3.5% and 10.6% of ΔOzone_total in winter, autumn, spring, and summer, respectively, suggesting that ΔOzone_photolysis was not the primary contributor to the current changes in ozone over the BTH region. However, the 36.3% contribution to ΔOzone_total in winter suggested that ΔOzone_photolysis is still an important contributor and should not be ignored when discussing the formation of high ozone episodes occurring in winter.
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Affiliation(s)
- Jinhui Gao
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, China; Department of Ocean Science and Engineering, Southern University of Science and Technology, Shenzhen, China; Center for the Oceanic and Atmospheric Science at SUSTech (COAST), Southern University of Science and Technology, Shenzhen, China
| | - Ying Li
- Department of Ocean Science and Engineering, Southern University of Science and Technology, Shenzhen, China; Center for the Oceanic and Atmospheric Science at SUSTech (COAST), Southern University of Science and Technology, Shenzhen, China.
| | - Zhouqing Xie
- Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei, China
| | - Bo Hu
- State Key Laboratory of Atmosphere Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Lili Wang
- State Key Laboratory of Atmosphere Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Fangwen Bao
- Department of Ocean Science and Engineering, Southern University of Science and Technology, Shenzhen, China; Center for the Oceanic and Atmospheric Science at SUSTech (COAST), Southern University of Science and Technology, Shenzhen, China
| | - Shidong Fan
- Department of Ocean Science and Engineering, Southern University of Science and Technology, Shenzhen, China; Center for the Oceanic and Atmospheric Science at SUSTech (COAST), Southern University of Science and Technology, Shenzhen, China
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10
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Wu R, Guo Q, Fan J, Guo C, Wang G, Wu W, Xu J. Association between air pollution and outpatient visits for allergic rhinitis: Effect modification by ambient temperature and relative humidity. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 821:152960. [PMID: 35016948 DOI: 10.1016/j.scitotenv.2022.152960] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 01/02/2022] [Accepted: 01/04/2022] [Indexed: 06/14/2023]
Abstract
Mounting evidence indicated the associations between air pollution and outpatient visits for allergic rhinitis (AR), while few studies assessed the effect modification of these associations by ambient temperature and relative humidity (RH). In this study, dataset of AR outpatients was obtained from Chinese People's Liberation Army Strategic Support Force Characteristic Medical Center in Beijing during 2014 to 2019, and the average concentrations of air pollutants including particulate matter ≤2.5 μm in diameter (PM2.5) and ≤10 μm (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), and meteorological factors (temperature and RH) at the same period were collected from one nearby air monitoring station. We performed a time-series study with Poisson regression model to examine the effects of air pollutants on AR outpatients after adjustment for potential confounders. And the effects modification analysis was further conducted by stratifying temperature and RH by tertiles into three groups of low, middle and high. In total of 33,599 outpatient visits for AR were recorded during the study period. Results found that a 10 μg/m3 increase in PM2.5, PM10, NO2 and SO2 was associated with significant increases in AR outpatients of 1.24% (95% confidence interval (CI): 0.69%, 1.78%), 0.79% (95% CI: 0.43%, 1.15%), 3.05% (95% CI: 1.72%, 4.40%) and 5.01% (95% CI: 1.18%, 8.96%), respectively. Stronger associations were observed in males than those in females, as well as in young adults (18-44 years) than those in other age groups. Air pollution effects on AR outpatients increased markedly at low temperature (<33.3th percentile) and high RH (>66.7th percentile). Findings in this study indicate that air pollution is associated with increased risk of AR outpatients, and the effects of air pollution on AR could be enhanced at low temperature and high RH.
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Affiliation(s)
- Rongshan Wu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; State Environmental Protection Key Laboratory of Ecological Effect and Risk Assessment of Chemicals, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; Center for Environmental Health Risk Assessment and Research, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Qun Guo
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; State Environmental Protection Key Laboratory of Ecological Effect and Risk Assessment of Chemicals, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; Center for Environmental Health Risk Assessment and Research, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Jingpu Fan
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; State Environmental Protection Key Laboratory of Ecological Effect and Risk Assessment of Chemicals, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; Center for Environmental Health Risk Assessment and Research, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Changsheng Guo
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; State Environmental Protection Key Laboratory of Ecological Effect and Risk Assessment of Chemicals, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; Center for Environmental Health Risk Assessment and Research, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Gang Wang
- Department of Otolaryngology, Strategic Support Force Medical Center, Beijing 100005, China; State Environmental Protection Key Laboratory of Environmental Sense Organ Stress and Health, Beijing 100005, China
| | - Wei Wu
- Department of Otolaryngology, Strategic Support Force Medical Center, Beijing 100005, China; State Environmental Protection Key Laboratory of Environmental Sense Organ Stress and Health, Beijing 100005, China.
| | - Jian Xu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; State Environmental Protection Key Laboratory of Ecological Effect and Risk Assessment of Chemicals, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; Center for Environmental Health Risk Assessment and Research, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
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11
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Zou X, Fang J, Yang Y, Wu R, Wang S, Xu H, Jia J, Yang H, Yuan N, Hu M, Zhao Y, Xie Y, Zhu Y, Wang T, Deng Y, Song X, Ma X, Huang W. Maternal exposure to traffic-related ambient particles and risk of gestational diabetes mellitus with isolated fasting hyperglycaemia: A retrospective cohort study in Beijing, China. Int J Hyg Environ Health 2022; 242:113973. [PMID: 35447399 DOI: 10.1016/j.ijheh.2022.113973] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Revised: 04/12/2022] [Accepted: 04/13/2022] [Indexed: 10/18/2022]
Abstract
BACKGROUND Ambient particles have been associated with gestational diabetes mellitus (GDM), however, no study has evaluated the effects of traffic-related ambient particles on the risks of GDM subgroups classified by oral glucose tolerance test (OGTT) values. METHODS A retrospective analysis was conducted among 24,001 pregnant women who underwent regular prenatal care and received OGTT at Haidian Maternal and Child Health Hospital in Beijing, China, 2014-2017. A total of 3,168 (13.2%) pregnant women were diagnosed with GDM, including 1,206 with isolated fasting hyperglycaemia (GDM-IFH). At a fixed-location monitoring station, routinely monitored ambient particles included fine particulate matter (PM2.5), black carbon (BC) and particles in size ranges of 5-560 nm (PNC5-560). Contributions of PNC5-560 sources were apportioned by positive matrix factorization model. Logistic regression model was applied to estimate odds ratio (OR) of ambient particles on GDM risk. RESULTS Among the 24,001 pregnancy women recruited in this study, 3,168 (13.2%) were diagnosed with GDM, including 1,206 with isolated fasting hyperglycaemia (GDM-IFH) and 1,295 with isolated post-load hyperglycaemia (GDM-IPH). We observed increased GDM-IFH risk with per interquartile range increase in first-trimester exposures to PM2.5 (OR = 1.94; 95% Confidence Intervals: 1.23-3.07), BC (OR = 2.14; 1.73-2.66) and PNC5-560 (OR = 2.46; 1.90-3.19). PNC5-560 originated from diesel and gasoline vehicle emissions were found in associations with increases in GDM-IFH risk, but not in GDM-IPH risk. CONCLUSION Our findings suggest that exposure to traffic-related ambient particles may increase GDM risk by exerting adverse effects on fasting glucose levels during pregnancy, and support continuing efforts to reduce traffic emissions for protecting vulnerable population who are at greater risk of glucose metabolism disorder.
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Affiliation(s)
- Xiaoxuan Zou
- Hadian Maternal and Child Health Hospital, Haidian District, Beijing, China
| | - Jiakun Fang
- Department of Occupational and Environmental Health, Peking University School of Public Health, And Peking University Institute of Environmental Medicine, Beijing, China
| | - Ying Yang
- National Research Institute for Family Planning, China; Graduate School of Peking Union Medical College, Dongcheng District, Beijing, China; National Human Genetic Resources Center, Haidian District, Beijing, China.
| | - Rongshan Wu
- Department of Occupational and Environmental Health, Peking University School of Public Health, And Peking University Institute of Environmental Medicine, Beijing, China; State Key Laboratory of Environmental Criteria and Risk Assessment, State Environmental Protection Key Laboratory of Ecological Effect and Risk Assessment of Chemicals, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Shuo Wang
- Hadian Maternal and Child Health Hospital, Haidian District, Beijing, China
| | - Hongbing Xu
- Department of Occupational and Environmental Health, Peking University School of Public Health, And Peking University Institute of Environmental Medicine, Beijing, China
| | - Jiajing Jia
- National Research Institute for Family Planning, China; Graduate School of Peking Union Medical College, Dongcheng District, Beijing, China
| | - Haishan Yang
- Hadian Maternal and Child Health Hospital, Haidian District, Beijing, China
| | - Ningman Yuan
- Department of Occupational and Environmental Health, Peking University School of Public Health, And Peking University Institute of Environmental Medicine, Beijing, China
| | - Meina Hu
- Hadian Maternal and Child Health Hospital, Haidian District, Beijing, China
| | - Yinzhu Zhao
- Hadian Maternal and Child Health Hospital, Haidian District, Beijing, China
| | - Yunfei Xie
- Department of Occupational and Environmental Health, Peking University School of Public Health, And Peking University Institute of Environmental Medicine, Beijing, China
| | - Yutong Zhu
- Department of Occupational and Environmental Health, Peking University School of Public Health, And Peking University Institute of Environmental Medicine, Beijing, China
| | - Tong Wang
- Department of Occupational and Environmental Health, Peking University School of Public Health, And Peking University Institute of Environmental Medicine, Beijing, China
| | - Yuzhi Deng
- National Research Institute for Family Planning, China; Graduate School of Peking Union Medical College, Dongcheng District, Beijing, China
| | - Xiaoming Song
- Department of Occupational and Environmental Health, Peking University School of Public Health, And Peking University Institute of Environmental Medicine, Beijing, China
| | - Xu Ma
- National Research Institute for Family Planning, China; Graduate School of Peking Union Medical College, Dongcheng District, Beijing, China; National Human Genetic Resources Center, Haidian District, Beijing, China
| | - Wei Huang
- Hadian Maternal and Child Health Hospital, Haidian District, Beijing, China; Key Laboratory of Molecular Cardiovascular Sciences of Ministry of Education, Peking University, Beijing, China.
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12
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Fang J, Yang Y, Zou X, Xu H, Wang S, Wu R, Jia J, Xie Y, Yang H, Yuan N, Hu M, Deng Y, Zhao Y, Wang T, Zhu Y, Ma X, Fan M, Wu J, Song X, Huang W. Maternal exposures to fine and ultrafine particles and the risk of preterm birth from a retrospective study in Beijing, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 812:151488. [PMID: 34742962 DOI: 10.1016/j.scitotenv.2021.151488] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 11/02/2021] [Accepted: 11/02/2021] [Indexed: 06/13/2023]
Abstract
Maternal exposure to fine particulate matter (PM2.5) has been associated with increased risk of preterm birth (PTB), but evidence on particles in smaller sizes and PTB risk remains limited. In this retrospective analysis, we included birth records of 24,001 singleton live births from Haidian Maternal and Child Health Hospital in Beijing, China, 2014-2017. Concurrently, number concentrations of size-fractioned particles in size ranges of 5-560 nm (PNC5-560) and mass concentrations of PM2.5, black carbon (BC) and gaseous pollutants were measured from a fixed-location monitoring station in central Haidian District. Logistic regression models were used to estimate the odds ratio (OR) of air pollutants on PTB risk after controlling for temperature, relative humidity, and individual covariates (e.g., maternal age, ethnicity, gravidity, parity, gestational weight gain, fetal gender, the year and season of conception). Positive matrix factorization models were then used to apportion the sources of PNC5-560. Among the 1062 (4.4%) PTBs, increased PTB risk was observed during the third trimester of pregnancy per 10 μg/m3 increase in PM2.5 [OR = 1.92; 95% Confidence Interval (95% CI): 1.76, 2.09], per 1000 particles/cm3 increase in PNC25-100 (OR = 1.09; 95% CI: 1.03, 1.15) and PNC100-560 (OR = 1.22; 95% CI: 1.05, 1.42). Among the identified sources of PNC5-560, emissions from gasoline and diesel vehicles were significantly associated with increased PTB risk, with ORs of 1.14 (95% CI: 1.01, 1.29) and 1.11 (95% CI: 1.04, 1.18), respectively. Exposures to other traffic-related air pollutants, such as BC and nitrogen dioxide (NO2) were also significantly associated with increased PTB risk. Our findings highlight the importance of traffic emission reduction in urban areas.
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Affiliation(s)
- Jiakun Fang
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China
| | - Ying Yang
- National Research Institute for Family Planning, Beijing, China; Graduate School of Peking Union Medical College, Beijing, China; National Human Genetic Resources Center, Beijing, China.
| | - Xiaoxuan Zou
- Hadian Maternal and Child Health Hospital, Beijing, China
| | - Hongbing Xu
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China
| | - Shuo Wang
- Hadian Maternal and Child Health Hospital, Beijing, China
| | - Rongshan Wu
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China; State Key Laboratory of Environmental Criteria and Risk Assessment, State Environmental Protection Key Laboratory of Ecological Effect and Risk Assessment of Chemicals, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Jiajing Jia
- Graduate School of Peking Union Medical College, Beijing, China
| | - Yunfei Xie
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China
| | - Haishan Yang
- Graduate School of Peking Union Medical College, Beijing, China
| | - Ningman Yuan
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China
| | - Meina Hu
- Graduate School of Peking Union Medical College, Beijing, China
| | - Yuzhi Deng
- Graduate School of Peking Union Medical College, Beijing, China
| | - Yinzhu Zhao
- Graduate School of Peking Union Medical College, Beijing, China
| | - Tong Wang
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China
| | - Yutong Zhu
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China
| | - Xu Ma
- National Human Genetic Resources Center, Beijing, China; Hadian Maternal and Child Health Hospital, Beijing, China; State Key Laboratory of Environmental Criteria and Risk Assessment, State Environmental Protection Key Laboratory of Ecological Effect and Risk Assessment of Chemicals, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Meng Fan
- Aerospace Information Research Institute, Chinese Academy of Sciences, State Key Laboratory of Remote Sensing Science, Beijing, China
| | - Jianbin Wu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Xiaoming Song
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China
| | - Wei Huang
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China; Key Laboratory of Molecular Cardiovascular Sciences of Ministry of Education, Peking University, Beijing, China.
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13
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Huang WZ, He WY, Knibbs LD, Jalaludin B, Guo YM, Morawska L, Heinrich J, Chen DH, Yu YJ, Zeng XW, Yu HY, Yang BY, Hu LW, Liu RQ, Feng WR, Dong GH. Improved morbidity-based air quality health index development using Bayesian multi-pollutant weighted model. ENVIRONMENTAL RESEARCH 2022; 204:112397. [PMID: 34798120 DOI: 10.1016/j.envres.2021.112397] [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: 08/20/2021] [Revised: 11/12/2021] [Accepted: 11/13/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND The widely used Air Quality Index (AQI) has been criticized due to its inaccuracy, leading to the development of the air quality health index (AQHI), an improvement on the AQI. However, there is currently no consensus on the most appropriate construction strategy for the AQHI. OBJECTIVES In this study, we aimed to evaluate the utility of AQHIs constructed by different models and health outcomes, and determine a better strategy. METHODS Based on the daily time-series outpatient visits and hospital admissions from 299 hospitals (January 2016-December 2018), and mortality (January 2017-December 2019) in Guangzhou, China, we utilized cumulative risk index (CRI) method, Bayesian multi-pollutant weighted (BMW) model and standard method to construct AQHIs for different health outcomes. The effectiveness of AQHIs constructed by different strategies was evaluated by a two-stage validation analysis and examined their exposure-response relationships with the cause-specific morbidity and mortality. RESULTS Validation by different models showed that AQHI constructed with the BMW model (BMW-AQHI) had the strongest association with the health outcome either in the total population or subpopulation among air quality indexes, followed by AQHI constructed with the CRI method (CRI-AQHI), then common AQHI and AQI. Further validation by different health outcomes showed that AQHI constructed with the risk of outpatient visits generally exhibited the highest utility in presenting mortality and morbidity, followed by AQHI constructed with the risk of hospitalizations, then mortality-based AQHI and AQI. The contributions of NO2 and O3 to the final AQHI were prominent, while the contribution of SO2 and PM2.5 were relatively small. CONCLUSIONS The BMW model is likely to be more effective for AQHI construction than CRI and standard methods. Based on the BMW model, the AQHI constructed with the outpatient data may be more effective in presenting short-term health risks associated with the co-exposure to air pollutants than the mortality-based AQHI and existing AQIs.
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Affiliation(s)
- Wen-Zhong Huang
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne VIC, 3004, Australia
| | - Wei-Yun He
- Department of Environmental Health, Guangzhou Center for Disease Control and Prevention, Guangzhou, 510440, China
| | - Luke D Knibbs
- School of Public Health, The University of Queensland, Herston, Queensland, 4006, Australia
| | - Bin Jalaludin
- Centre for Air Quality and Health Research and Evaluation, Glebe, NSW, 2037, Australia; Ingham Institute for Applied Medial Research, Liverpool, NSW, 2170, Australia; School of Public Health and Community Medicine, The University of New South Wales, Kensington, NSW, 2052, Australia
| | - Yu-Ming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne VIC, 3004, Australia
| | - Lidia Morawska
- International Laboratory for Air Quality and Health, Queensland University of Technology (QUT), GPO Box 2434, Brisbane, Queensland, 4001, Australia
| | - Joachim Heinrich
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, Munich, 80336, Germany; Comprehensive Pneumology Center Munich, German Center for Lung Research, Munich, 80336, Germany
| | - Duo-Hong Chen
- Department of Air Quality Forecasting and Early Warning, Guangdong Environmental Monitoring Center, State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangdong Environmental Protection Key Laboratory of Atmospheric Secondary Pollution, Guangzhou, 510308, China
| | - Yun-Jiang Yu
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Environmental Protection, Guangzhou, 510655, China
| | - Xiao-Wen Zeng
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Hong-Yao Yu
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Bo-Yi Yang
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Li-Wen Hu
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Ru-Qing Liu
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Wen-Ru Feng
- Department of Environmental Health, Guangzhou Center for Disease Control and Prevention, Guangzhou, 510440, China.
| | - Guang-Hui Dong
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China.
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14
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Shang J, Zhang Y, Schauer JJ, Chen S, Yang S, Han T, Zhang D, Zhang J, An J. Prediction of the oxidation potential of PM 2.5 exposures from pollutant composition and sources. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 293:118492. [PMID: 34785286 DOI: 10.1016/j.envpol.2021.118492] [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: 04/01/2021] [Revised: 11/11/2021] [Accepted: 11/11/2021] [Indexed: 06/13/2023]
Abstract
The inherent oxidation potential (OP) of atmospheric particulate matter has been shown to be an important metric in assessing the biological activity of inhaled particulate matter and is associated with the composition of PM2.5. The current study examined the chemical composition of 388 personal PM2.5 samples collected from students and guards living in urban and suburban areas of Beijing, and assessed the ability to predict OP from the calculated metrics of carcinogenic risk, represented by ELCR (excess lifetime cancer risk), non-carcinogenic risk represented by HI (hazard index), and the composition and sources of the particulate matter using multiple linear regression methods. The correlations between calculated ELCR and HI and the measured OP were 0.37 and 0.7, respectively. HI was a better predictor of OP than ELCR. The prediction models based on pollutants (Model_1) and pollution sources (Model_2) were constructed by multiple linear regression method, and Pearson correlation coefficients between the predicted results of Model_1 and Model_2 with the measured volume normalized OP are 0.81 and 0.80, showing good prediction ability. Previous investigations in Europe and North America have developed location-specific relationships between the chemical composition of particulate matter and OP using regression methods. We also examined the ability of relationships between OP and composition, sources, developed in Europe and North America, to predict the OP of particulate matter in Beijing from the composition and sources determined in Beijing. The relationships developed in Europe and North America provided good predictive ability in Beijing and it suggests that these relationships can be used to predict OP from the chemical composition measured in other regions of the world.
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Affiliation(s)
- Jing Shang
- Institute of Urban Meteorology, China Meteorological Administration, Beijing, 100089, China; Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), China
| | - Yuanxun Zhang
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 101408, China; CAS Center for Excellence in Regional Atmospheric Environment, Chinese Academy of Sciences, Xiamen, 361021, China; Institute of Eco-Environmental Forensics, Shandong University, Qingdao, 266237, China.
| | - James J Schauer
- Wisconsin State Laboratory of Hygiene, University of Wisconsin-Madison, Madison, WI, 53718, USA
| | - Sumin Chen
- Beijing Municipal Research Institute of Environmental Protection, China
| | - Shujian Yang
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 101408, China
| | - Tingting Han
- Institute of Urban Meteorology, China Meteorological Administration, Beijing, 100089, China
| | - Dong Zhang
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 101408, China
| | - Jinjian Zhang
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 101408, China
| | - Jianxiong An
- Department of Anesthesiology, Pain Medicine and Critical Care Medicine, Aviation General Hospital of China Medical University, Beijing, China
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15
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Liu L, Zhu Y, Xu H, Wang Y, Wang T, Zhao Q, Zhang Y, Chen J, Liu S, Yi T, Wu R, Liu S, Song X, Li J, Huang W. Short-term exposure to ambient ozone associated with cardiac arrhythmias in healthy adults. GLOBAL HEALTH JOURNAL 2022. [DOI: 10.1016/j.glohj.2022.01.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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16
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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: 22] [Impact Index Per Article: 7.3] [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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17
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Fang J, Song X, Xu H, Wu R, Song J, Xie Y, Xu X, Zeng Y, Wang T, Zhu Y, Yuan N, Jia J, Xu B, Huang W. Associations of ultrafine and fine particles with childhood emergency room visits for respiratory diseases in a megacity. Thorax 2021; 77:391-397. [PMID: 34301742 DOI: 10.1136/thoraxjnl-2021-217017] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Accepted: 06/26/2021] [Indexed: 11/04/2022]
Abstract
BACKGROUND Ambient fine particulate matter with aerodynamic diameter less than 2.5 µm (PM2.5) has been associated with deteriorated respiratory health, but evidence on particles in smaller sizes and childhood respiratory health has been limited. METHODS We collected time-series data on daily respiratory emergency room visits (ERVs) among children under 14 years old in Beijing, China, during 2015-2017. Concurrently, size-fractioned number concentrations of particles in size ranges of 5-560 nm (PNC5-560) and mass concentrations of PM2.5, black carbon (BC) and nitrogen dioxide (NO2) were measured from a fixed-location monitoring station in the urban area of Beijing. Confounder-adjusted Poisson regression models were used to estimate excessive risks (ERs) of particle size fractions on childhood respiratory ERVs, and positive matrix factorisation models were applied to apportion the sources of PNC5-560. RESULTS Among the 136 925 cases of all-respiratory ERVs, increased risks were associated with IQR increases in PNC25-100 (ER=5.4%, 95% CI 2.4% to 8.6%), PNC100-560 (4.9%, 95% CI 2.5% to 7.3%) and PM2.5 (1.3%, 95% CI 0.1% to 2.5%) at current and 1 prior days (lag0-1). Major sources of PNC5-560 were identified, including nucleation (36.5%), gasoline vehicle emissions (27.9%), diesel vehicle emissions (18.9%) and secondary aerosols (10.6%). Emissions from gasoline and diesel vehicles were found of significant associations with all-respiratory ERVs, with increased ERs of 6.0% (95% CI 2.5% to 9.7%) and 4.4% (95% CI 1.7% to 7.1%) at lag0-1 days, respectively. Exposures to other traffic-related pollutants (BC and NO2) were also associated with increased respiratory ERVs. CONCLUSION Our findings suggest that exposures to higher levels of PNC5-560 from traffic emissions could be attributed to increased childhood respiratory morbidity, which supports traffic emission control priority in urban areas.
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Affiliation(s)
- Jiakun Fang
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China
| | - Xiaoming Song
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China
| | - Hongbing Xu
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China
| | - Rongshan Wu
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China.,State Key Laboratory of Environmental Criteria and Risk Assessment, State Environmental Protection Key Laboratory of Ecological Effect and Risk Assessment of Chemicals, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Jing Song
- Beijing Children's Hospital, Capital Medical University, Beijing, China
| | - Yunfei Xie
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China
| | - Xin Xu
- Beijing Children's Hospital, Capital Medical University, Beijing, China
| | - Yueping Zeng
- Beijing Children's Hospital, Capital Medical University, Beijing, China
| | - Tong Wang
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China
| | - Yutong Zhu
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China
| | - Ningman Yuan
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China
| | - Jinzhu Jia
- Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing, China
| | - Baoping Xu
- Beijing Children's Hospital, Capital Medical University, Beijing, China
| | - Wei Huang
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China .,Key Laboratory of Molecular Cardiovascular Sciences of Ministry of Education, Peking University, Beijing, China
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18
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Hou X, Huang H, Hu H, Wang D, Sun B, Zhang XD. Short-term exposure to ambient air pollution and hospital visits for IgE-mediated allergy: A time-stratified case-crossover study in southern China from 2012 to 2019. EClinicalMedicine 2021; 37:100949. [PMID: 34386741 PMCID: PMC8343265 DOI: 10.1016/j.eclinm.2021.100949] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 05/18/2021] [Accepted: 05/19/2021] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Because of the limited epidemiological evidence on the association between acute air pollutants and allergy, there is a need to investigate this association, especially between the short-term exposure to air pollution and the serum Immunoglobulin E (IgE)-mediated allergy. METHODS A total of 39,569 IgE test results and demographic characteristics were obtained in the First Affiliated Hospital of Guangzhou Medical University between August 2012 and September 2019. Ninety-nine specific allergens were tested according to clinical diagnosis. The logistic regression was used to assess the effects of CO, NO2 and PM2.5 exposure on the risk of sensitization to specific inhalant/food allergens. Generalized additive models with multivariate adjustments were utilized to model the exposure-response relationship. Stratified analyses were performed to estimate the reliability of correlations in various subgroups. FINDINGS Single-pollutant models indicate that the 3-day moving average (lag2-4) of CO, PM2.5 or NO2 is associated with the increased risk for allergic diseases related to specific inhaled allergens. In multi-pollutant models, the adjusted Odds Ratio (OR) 95% (Confidence Interval, CI) increases by 8% (95% CI, 2%-15%) for per increment of 0.2 mg/m3 in CO levels, and rises by 8% (95% CI, 2%-13%) for each increase of 16.3 μg/m3 in PM2.5 concentration. The associations are stronger in youngsters (<18, years) but not significantly different by gender. Particularly, a significantly stronger association between PM2.5 exposure and hospital visits for inhaled allergy is observed in patients who are exposed to lower concentration of SO2 (<10.333 μg/m3) and higher levels of NO2 (≥42.0 μg/m3), as well as patients enrolled after 2017. INTERPRETATION The short-term exposure to CO/PM2.5 increases the number of hospital visits for IgE-mediated allergy, especially for the sensitization to specific inhalant allergens. Therefore, to prevent inhaled allergies, the public policy for controlling air pollution needs to be considered seriously. FUNDING This study was supported by the University of Macau (grant numbers: FHS-CRDA-029-002-2017 and MYRG2018-00,071-FHS) as well as the Science and Technology Development Fund, Macau SAR (File no. 0004/2019/AFJ and 0011/2019/AKP). This work was also supported by the National Natural Science Foundation of China (81,871,736), the National Key Technology R&D Program (2018YFC1311902), the Guangdong Science and Technology Foundation (2019B030316028), the Guangzhou Municipal Health Foundation (20191A011073), and the Guangzhou Science and Technology Foundation (201,804,020,043).
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Affiliation(s)
- Xiangqing Hou
- Faculty of Health Sciences, University of Macau, Macao, China
| | - Huimin Huang
- Department of Allergy and Clinical Immunology, State Key Laboratory of Respiratory Disease, National Clinical Research Center of Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangdong, China
| | - Haisheng Hu
- Department of Allergy and Clinical Immunology, State Key Laboratory of Respiratory Disease, National Clinical Research Center of Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangdong, China
| | - Dandan Wang
- Faculty of Health Sciences, University of Macau, Macao, China
| | - Baoqing Sun
- Department of Allergy and Clinical Immunology, State Key Laboratory of Respiratory Disease, National Clinical Research Center of Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangdong, China
- Corresponding author.
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19
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Zhang Y, Ma Y, Feng F, Cheng B, Shen J, Wang H, Jiao H, Li M. Respiratory mortality associated with ozone in China: A systematic review and meta-analysis. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 280:116957. [PMID: 33773305 DOI: 10.1016/j.envpol.2021.116957] [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: 10/11/2020] [Revised: 03/13/2021] [Accepted: 03/15/2021] [Indexed: 06/12/2023]
Abstract
This systematic review and meta-analysis was performed to obtain updated evidence regarding the short-term effect of ozone on respiratory mortality in China. We systematically searched the Embase, PubMed, Scopus, Web of Science, China National Knowledge Internet, and Wanfang databases for relevant studies. After screening based on the inclusion criteria, 12 studies with 19 estimates were selected for further meta-analysis. The results revealed that respiratory mortality significantly increased by 0.55% (95% confidence interval: 0.24%-0.85%; Q = 39.47, I2 = 54.4%, P = 0.002, tau2 < 10-5) for every 10-μg/m3 increase in the maximum 8-h average concentration of ozone. Furthermore, differences in combined estimates were observed between various regions and lag structures. The combined effect of single-day lags was generally larger than that of multiday lags; the estimate of mortality for the population in the north was larger than that for the population in the south. The sensitivity analysis demonstrated that the main findings were stable; funnel plots with Egger's and Begg's tests indicated no significant publication bias in our analysis.
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Affiliation(s)
- Yifan Zhang
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Yuxia Ma
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China.
| | - Fengliu Feng
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Bowen Cheng
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Jiahui Shen
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Hang Wang
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Haoran Jiao
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Mingji Li
- Resource and Environment Department, Ningxia University, Yinchuan, 750021, China
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20
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Fang J, Song J, Wu R, Xie Y, Xu X, Zeng Y, Zhu Y, Wang T, Yuan N, Xu H, Song X, Zhang Q, Xu B, Huang W. Association between ambient temperature and childhood respiratory hospital visits in Beijing, China: a time-series study (2013-2017). ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:29445-29454. [PMID: 33555475 DOI: 10.1007/s11356-021-12817-w] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Accepted: 02/01/2021] [Indexed: 06/12/2023]
Abstract
Little is known on the potential impact of temperature on respiratory morbidity, especially for children whose respiratory system can be more vulnerable to climate changes. In this time-series study, Poisson generalized additive models combined with distributed lag nonlinear models were used to assess the associations between ambient temperature and childhood respiratory morbidity. The impacts of extreme cold and hot temperatures were calculated as cumulative relative risks (cum.RRs) at the 1st and 99th temperature percentiles relative to the minimum morbidity temperature percentile. Attributable fractions of respiratory morbidity due to cold or heat were calculated for temperatures below or above the minimum morbidity temperature. Effect modifications by air pollution, age, and sex were assessed in stratified analyses. A total of 877,793 respiratory hospital visits of children under 14 years old between 2013 and 2017 were collected from Beijing Children's Hospital. Overall, we observed J-shaped associations with greater respiratory morbidity risks for exposure to lower temperatures, and higher fraction of all-cause respiratory hospital visits was caused by cold (33.1%) than by heat (0.9%). Relative to the minimum morbidity temperature (25 °C, except for rhinitis, which is 31 °C), the cum.RRs for extreme cold temperature (-6 °C) were 2.64 (95%CI: 1.51-4.61) for all-cause respiratory hospital visits, 2.73 (95%CI: 1.44-5.18) for upper respiratory infection, 2.76 (95%CI: 1.56-4.89) for bronchitis, 2.12 (95%CI: 1.30-3.47) for pneumonia, 2.06 (95%CI: 1.27-3.34) for rhinitis, and 4.02 (95%CI: 2.14-7.55) for asthma, whereas the associations between extreme hot temperature (29 °C) and respiratory hospital visits were not significant. The impacts of extreme cold temperature on asthma hospital visits were greater at higher levels of ozone (O3) exposure (> 50th percentile). Our findings suggest significantly increased childhood respiratory morbidity risks at extreme cold temperature, and the impact of extreme cold temperature on asthma hospital visits can be enhanced under higher level exposure to O3.
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Affiliation(s)
- Jiakun Fang
- Department of Occupational and Environmental Health, School of Public Health, Peking University, Beijing, China
| | - Jing Song
- Beijing Children's Hospital, Capital Medical University, Beijing, China
| | - Rongshan Wu
- Department of Occupational and Environmental Health, School of Public Health, Peking University, Beijing, China
- State Key Laboratory of Environmental Criteria and Risk Assessment, State Environmental Protection Key Laboratory of Ecological Effect and Risk Assessment of Chemicals, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Yunfei Xie
- Department of Occupational and Environmental Health, School of Public Health, Peking University, Beijing, China
| | - Xin Xu
- Beijing Children's Hospital, Capital Medical University, Beijing, China
| | - Yueping Zeng
- Beijing Children's Hospital, Capital Medical University, Beijing, China
| | - Yutong Zhu
- Department of Occupational and Environmental Health, School of Public Health, Peking University, Beijing, China
| | - Tong Wang
- Department of Occupational and Environmental Health, School of Public Health, Peking University, Beijing, China
| | - Ningman Yuan
- Department of Occupational and Environmental Health, School of Public Health, Peking University, Beijing, China
| | - Hongbing Xu
- Department of Occupational and Environmental Health, School of Public Health, Peking University, Beijing, China
| | - Xiaoming Song
- Department of Occupational and Environmental Health, School of Public Health, Peking University, Beijing, China
| | - Qinghong Zhang
- Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, China
| | - Baoping Xu
- Beijing Children's Hospital, Capital Medical University, Beijing, China.
| | - Wei Huang
- Department of Occupational and Environmental Health, School of Public Health, Peking University, Beijing, China.
- Key Laboratory of Molecular Cardiovascular Sciences of Ministry of Education, Peking University, Beijing, China.
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21
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Galán-Madruga D. A methodological framework for improving air quality monitoring network layout. Applications to environment management. J Environ Sci (China) 2021; 102:138-147. [PMID: 33637239 DOI: 10.1016/j.jes.2020.09.009] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Revised: 09/07/2020] [Accepted: 09/07/2020] [Indexed: 06/12/2023]
Abstract
This work aims to provide a methodology framework which allows to improve the performance and efficiency of an air quality monitoring network (AQMN). It requires to be constituted by a minimum and reliable number of measurement sites. Nevertheless, the AQMN efficiency should be assessed over time, as a consequence of the possible emergence of new emission sources of air pollutants, which could lead to variations on their spatial distribution within the target area. PM10 particles data monitored by the Community of Madrid's (Spain) AQMN between 2008 and 2017 were used to develop a methodology to optimize the AQMN performance. The annual spatial distribution of average PM10 levels over the studied period monitored by all current stations vs those more representative was provided by a geographic information system (GIS), and the percentage of similarity between both postulates was quantified using simple linear regression (> 95%). As one innovative tool of this study, the practical application of the proposed methodology was validated using PM10 particles data measured by AQMN during 2007 and 2018, reaching a similitude degree higher than 95%. The influence of temporal variation on the proposed methodological framework was around 20%. The proposed methodology sets criteria for identifying non-redundant stations within AQMN, it is also able to appropriately assess the representativeness of fixed monitoring sites within an AQMN and it complements the guidelines set by European legislation on air pollutants monitoring at fixed stations, which could help to tackle efforts to improve the air quality management.
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Affiliation(s)
- David Galán-Madruga
- Department of Atmospheric Pollution, National Center for Environment Health, Health Institute Carlos III, Ctra. Majadahonda a Pozuelo km 2,2 28220 Madrid, Spain.
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22
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Shen Y, Jiang F, Feng S, Zheng Y, Cai Z, Lyu X. Impact of weather and emission changes on NO 2 concentrations in China during 2014-2019. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 269:116163. [PMID: 33280908 DOI: 10.1016/j.envpol.2020.116163] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 11/03/2020] [Accepted: 11/25/2020] [Indexed: 05/16/2023]
Abstract
Nitrogen dioxide (NO2) is one of the most important air pollutants that highly affect the formation of secondary fine particles and tropospheric ozone. In this study based on hourly NO2 observations from June 2014 to May 2019 and a regional air quality model (WRF-CMAQ), we comprehensively analyzed the spatiotemporal variations of NO2 concentrations throughout China and in 12 urban agglomerations (UAs) and quantitatively showed the anthropogenic and meteorological factors controlling the interannual variations (IAVs). The ground observations and tropospheric columns show that high NO2 concentrations are predominantly concentrated in UAs such as Beijing-Tianjin-Hebei (BTH), the Shandong Peninsula (SP), the Central Plain (CP), Central Shaanxi (CS), and the Yangtze River Delta (YRD). For different UAs, the NO2 IAVs are different. The NO2 increased first and then decreased in 2016 or 2017 in BTH, YRD, CS, and Cheng-Yu, and decreased from 2014 to 2019 in Harbin-Changchun, CP, SP, Northern Slope of Tianshan Mountain, and Beibu-Gulf, while increased slightly in the Pearl River Delta (PRD) and Hohhot-Baotou-Erdos-Yulin (HBEY). The NO2 IAVs were primarily dominated by emission changes. The net wintertime decreases of NO2 in BTH, Yangtze River Middle-Reach, and PRD were mostly contributed by emission reductions from 2014 to 2018, and the significant increase in the wintertime in HBEY was also dominated by emission changes (93%). Weather conditions also have an important effect on the NO2 IAVS. In BTH and HBEY, the increases of NO2 in winter of 2016 are mainly attributed to the unfavorable weather conditions and for the significant decreases in the winter of 2017, the favorable weather conditions also play a very important role. This study provides a basic understanding on the current situation of NO2 pollution and are helpful for policymakers as well as those interested in the study of tropospheric ozone changes in China and downwind areas.
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Affiliation(s)
- Yang Shen
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing, 210023, China
| | - Fei Jiang
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing, 210023, China; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, 210023, China.
| | - Shuzhuang Feng
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing, 210023, China
| | - Yanhua Zheng
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing, 210023, China
| | - Zhe Cai
- Nanjing Climblue Technology Co., LTD, Nanjing, Jiangsu, 211135, China
| | - Xiaopu Lyu
- Department of Civil and Environmental Engineering, Hong Kong Polytechnic University, Hong Kong
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23
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Zhu G, Zhu Y, Wang Z, Meng W, Wang X, Feng J, Li J, Xiao Y, Shi F, Wang S. The association between ambient temperature and mortality of the coronavirus disease 2019 (COVID-19) in Wuhan, China: a time-series analysis. BMC Public Health 2021; 21:117. [PMID: 33430851 PMCID: PMC7797893 DOI: 10.1186/s12889-020-10131-7] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Accepted: 12/25/2020] [Indexed: 01/08/2023] Open
Abstract
Background The COVID-19 has caused a sizeable global outbreak and has been declared as a public health emergency of international concern. Sufficient evidence shows that temperature has an essential link with respiratory infectious diseases. The objectives of this study were to describe the exposure-response relationship between ambient temperature, including extreme temperatures, and mortality of COVID-19. Methods The Poisson distributed lag non-linear model (DLNM) was constructed to evaluate the non-linear delayed effects of ambient temperature on death, by using the daily new death of COVID-19 and ambient temperature data from January 10 to March 31, 2020, in Wuhan, China. Results During the period mentioned above, the average daily number of COVID-19 deaths was approximately 45.2. Poisson distributed lag non-linear model showed that there was a non-linear relationship (U-shape) between the effect of ambient temperature and mortality. With confounding factors controlled, the daily cumulative relative death risk decreased by 12.3% (95% CI [3.4, 20.4%]) for every 1.0 °C increase in temperature. Moreover, the delayed effects of the low temperature are acute and short-term, with the most considerable risk occurring in 5–7 days of exposure. The delayed effects of the high temperature appeared quickly, then decrease rapidly, and increased sharply 15 days of exposure, mainly manifested as acute and long-term effects. Sensitivity analysis results demonstrated that the results were robust. Conclusions The relationship between ambient temperature and COVID-19 mortality was non-linear. There was a negative correlation between the cumulative relative risk of death and temperature. Additionally, exposure to high and low temperatures had divergent impacts on mortality.
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Affiliation(s)
- Gaopei Zhu
- Department of Health Statistics, School of Public Health, Weifang Medical University, No. 7166 Baotong West Street, Weifang, 261053, People's Republic of China
| | - Yuhang Zhu
- Department of Health Statistics, School of Public Health, Weifang Medical University, No. 7166 Baotong West Street, Weifang, 261053, People's Republic of China.,Department of Child and Adolescent Psychiatry, Psychotherapy, and Psychosomatics, Center for Psychosocial Medicine, University Medical Center Hamburg-Eppendorf, Martinistraße 52, W 29, 20246, Hamburg, Germany
| | - Zhongli Wang
- School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, People's Republic of China
| | - Weijing Meng
- School of Life Sciences and Technology, Weifang Medical University, No. 7166 Baotong West Street, Weifang, 261053, People's Republic of China
| | - Xiaoxuan Wang
- Department of Health Statistics, School of Public Health, Weifang Medical University, No. 7166 Baotong West Street, Weifang, 261053, People's Republic of China
| | - Jianing Feng
- Department of Health Statistics, School of Public Health, Weifang Medical University, No. 7166 Baotong West Street, Weifang, 261053, People's Republic of China
| | - Juan Li
- Department of Health Statistics, School of Public Health, Weifang Medical University, No. 7166 Baotong West Street, Weifang, 261053, People's Republic of China
| | - Yufei Xiao
- Department of Health Statistics, School of Public Health, Weifang Medical University, No. 7166 Baotong West Street, Weifang, 261053, People's Republic of China
| | - Fuyan Shi
- Department of Health Statistics, School of Public Health, Weifang Medical University, No. 7166 Baotong West Street, Weifang, 261053, People's Republic of China.
| | - Suzhen Wang
- Department of Health Statistics, School of Public Health, Weifang Medical University, No. 7166 Baotong West Street, Weifang, 261053, People's Republic of China.
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Wu Y, Wang W, Liu C, Chen R, Kan H. The association between long-term fine particulate air pollution and life expectancy in China, 2013 to 2017. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 712:136507. [PMID: 32050378 DOI: 10.1016/j.scitotenv.2020.136507] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2019] [Revised: 12/25/2019] [Accepted: 01/02/2020] [Indexed: 06/10/2023]
Abstract
BACKGROUND China is experiencing one of the worst air quality problems in the world. China implemented the Air Pollution Prevention and Control Action Plan (APPCAP) and the air quality has recently achieved remarkable improvement. OBJECTIVE To evaluate the associations of variations in annual fine particulate matter (PM2.5) levels and changes in life expectancy in Chinese urban populations from 2013 to 2017. METHOD We collected annual-average concentrations of PM2.5 and average life expectancy of urban residents in 214 cities from 2013 to 2017. We conducted a longitudinal panel analysis applying linear mixed-effect models to evaluate the association between PM2.5 reduction and life expectancy increase with and without adjustment for socioeconomic and medical-care confounders. RESULT The nationwide-average annual PM2.5 concentrations decreased from 67.78 μg/m3 in 2013 to 45.25 μg/m3 in 2017; meanwhile, the average life expectancy of urban residents increased from 78.53 to 79.86 years. A decrease of 10 μg/m3 in PM2.5 was associated with an increment of 0.18 (95% confidence interval: 0.06, 0.30) year in life expectancy. After simultaneously adjusting for GDP per capita, smoking prevalence, urbanization rate and maternal mortality, the association turned to be insignificant at the national level, but remained significant in the eastern region with life expectancy gained 0.16 (95% CI: 0.04, 0.27) year per 10 μg/m3 reduction of PM2.5. CONCLUSION Lower PM2.5 air pollution might be associated with extended life expectancy in east of China. The implementation of APPCAP during 2013 to 2017 might have resulted in benefits on life expectancy, especially in east of China.
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Affiliation(s)
- Yihan Wu
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200032, China
| | - Weidong Wang
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200032, China
| | - Cong Liu
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200032, China
| | - Renjie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200032, China.
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200032, China.
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Urban Form, Air Quality, and Cardiorespiratory Mortality: A Path Analysis. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17041202. [PMID: 32069972 PMCID: PMC7068322 DOI: 10.3390/ijerph17041202] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Revised: 02/05/2020] [Accepted: 02/06/2020] [Indexed: 12/14/2022]
Abstract
With the unprecedented urbanization during the past three decades, air quality in many Chinese cities has been a serious issue which poses great challenges for urban sustainability. This study examines the health consequences of development patterns in China by establishing the linkage between urban form, air pollution level, and cardiorespiratory mortality rate. We assembled a dataset by compiling a series of variables from multiple sources, including China's Disease Surveillance Points (DSP) system, which forms a nationally representative sample of mortality for the year 2005, Chinese census, satellite imagery, and the Chinese National Land Use Database. After controlling for local climate, demography, socioeconomics, and other pollution factors, this study finds that urban form elements (e.g., urban density, fragmentation level, forest/green space ratio) have significant influences on PM2.5 (atmospheric particulate matter with a diameter of less than 2.5 micrometers) concentration, thus influencing the incidence of cardiorespiratory mortality at the county level. These results may help explain how the type and pattern of development shape public health by influencing air quality and form an evidence-based land use policy to improve environmental quality and public health.
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Xue W, Zhan Q, Zhang Q, Wu Z. Spatiotemporal Variations of Particulate and Gaseous Pollutants and Their Relations to Meteorological Parameters: The Case of Xiangyang, China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 17:ijerph17010136. [PMID: 31878125 PMCID: PMC6981905 DOI: 10.3390/ijerph17010136] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Revised: 12/08/2019] [Accepted: 12/18/2019] [Indexed: 11/16/2022]
Abstract
High air pollution levels have become a nationwide problem in China, but limited attention has been paid to prefecture-level cities. Furthermore, different time resolutions between air pollutant level data and meteorological parameters used in many previous studies can lead to biased results. Supported by synchronous measurements of air pollutants and meteorological parameters, including PM2.5, PM10, total suspended particles (TSP), CO, NO2, O3, SO2, temperature, relative humidity, wind speed and direction, at 16 urban sites in Xiangyang, China, from 1 March 2018 to 28 February 2019, this paper: (1) analyzes the overall air quality using an air quality index (AQI); (2) captures spatial dynamics of air pollutants with pollution point source data; (3) characterizes pollution variations at seasonal, day-of-week and diurnal timescales; (4) detects weekend effects and holiday (Chinese New Year and National Day holidays) effects from a statistical point of view; (5) establishes relationships between air pollutants and meteorological parameters. The principal results are as follows: (1) PM2.5 and PM10 act as primary pollutants all year round and O3 loses its primary pollutant position after November; (2) automobile manufacture contributes to more particulate pollutants while chemical plants produce more gaseous pollutants. TSP concentration is related to on-going construction and road sprinkler operations help alleviate it; (3) an unclear weekend effect for all air pollutants is confirmed; (4) celebration activities for the Chinese New Year bring distinctly increased concentrations of SO2 and thereby enhance secondary particulate pollutants; (5) relative humidity and wind speed, respectively, have strong negative correlations with coarse particles and fine particles. Temperature positively correlates with O3.
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Affiliation(s)
- Wei Xue
- School of Urban Design, Wuhan University, Wuhan 430072, China
| | - Qingming Zhan
- School of Urban Design, Wuhan University, Wuhan 430072, China
- Correspondence: ; Tel.: +86-139-9566-8639
| | - Qi Zhang
- Bank of Communications, Wuhan 430015, China
| | - Zhonghua Wu
- The Xiangyang Environmental Monitoring Center, Xiangyang 441000, China
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