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Qin P, Ma Y, Zhao Y, Liu Z, Wang W, Feng F, Cheng B. Temperature modification of air pollutants and their synergistic effects on respiratory diseases in a semi-arid city in Northwest China. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2024; 46:284. [PMID: 38963443 DOI: 10.1007/s10653-024-02044-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2023] [Accepted: 05/21/2024] [Indexed: 07/05/2024]
Abstract
Air pollutants and temperature are significant threats to public health, and the complex linkages between the environmental factors and their interactions harm respiratory diseases. This study is aimed to analyze the impact of air pollutants and meteorological factors on respiratory diseases and their synergistic effects in Dingxi, a city in northwestern China, from 2018 to 2020 using a generalized additive model (GAM). Relative risk (RR) was employed to quantitatively evaluate the temperature modification on the short-term effects of PM2.5 and O3 and the synergistic effects of air pollutants (PM2.5 and O3) and meteorological elements (temperature and relative humidity) on respiratory diseases. The results indicated that the RRs per inter-quatile range (IQR) rise in PM2.5 and O3 concentrations were (1.066, 95% CI: 1.009-1.127, lag2) and (1.037, 95% CI: 0.975-1.102, lag4) for respiratory diseases, respectively. Temperature stratification suggests that the influence of PM2.5 on respiratory diseases was significantly enhanced at low and moderate temperatures, and the risk of respiratory diseases caused by O3 was significantly increased at high temperatures. The synergy analysis demonstrated significant a synergistic effect of PM2.5 with low temperature and high relative humidity and an antagonistic effect of high relative humidity and O3 on respiratory diseases. The findings would provide a scientific basis for the impact of pollutants on respiratory diseases in Northwest China.
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Affiliation(s)
- Pengpeng Qin
- 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.
| | - Yuhan Zhao
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Zongrui Liu
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Wanci Wang
- 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
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Hu K, Cao B, Lu H, Xu J, Zhang Y, Wang C. Changes in PM 2.5-related diabetes risk under the implementation of the clean air act in Shanghai. Diabetes Res Clin Pract 2024; 212:111716. [PMID: 38777130 DOI: 10.1016/j.diabres.2024.111716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Revised: 05/15/2024] [Accepted: 05/19/2024] [Indexed: 05/25/2024]
Abstract
OBJECTIVES We examined the associations between PM2.5 exposure and Type 2 diabetes mellitus risk under the implementation of the Clean Air Act (CAA) among high-risk population for diabetes in Shanghai. METHODS A total of 10,499 subjects from the Shanghai High-Risk Diabetic Screen (SHiDS) project between 2002 and 2018, linked with remotely sensed PM2.5 concentrations, were enrolled in this study. Ordinary least squares and logistic regression were applied to explore associations between PM2.5 and diabetes risk in various exposure periods. RESULTS In year 2002-2013 (before CAA), the diabetes risk increased 7.5 % (95 % CI: 1.018-1.137), 8.0 % (95 % CI: 1.022-1.142) and 7.9 % (95 % CI: 1.021-1.141) under each 10 μg/m3 increase of long-term (1, 2 and 3 years) PM2.5 exposure, respectively. Elevated PM2.5 exposure were also associated with a significant increase in glycemic parameters before CAA implementation. However, in the year 2014-2018 (after CAA), the associations between PM2.5 exposure and diabetes risk were not significant after controlling for potential confounders. CONCLUSION Our findings suggest that long-term and high-level exposure to PM2.5 was associated with increased prevalence of diabetes. Moreover, the implementation of CAA might ameliorate PM2.5-related diabetes risk.
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Affiliation(s)
- Kai Hu
- Department of Sociology, School of Social and Public Administration, East China University of Science and Technology, Meilong Road 130, Xuhui District, Shanghai 200237, China
| | - Baige Cao
- Department of Endocrinology & Metabolism, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai 200434, China
| | - Huijuan Lu
- Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, The Metabolic Disease Biobank, Shanghai, China
| | - Jinfang Xu
- Department of Health Statistics, Naval Medical University, Shanghai 200433, China
| | - Yinan Zhang
- Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, The Metabolic Disease Biobank, Shanghai, China.
| | - Congrong Wang
- Department of Endocrinology & Metabolism, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai 200434, China.
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Zhang R, Liu M, Zhang W, Ling J, Dong J, Ruan Y. Short-term association between air pollution and daily genitourinary disorder admissions in Lanzhou, China. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2024; 46:74. [PMID: 38367071 DOI: 10.1007/s10653-023-01821-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 11/27/2023] [Indexed: 02/19/2024]
Abstract
The aim of this study was to determine the relationship between short-term exposure to ambient air pollution and the number of daily hospital admissions for genitourinary disorders in Lanzhou. Hospital admission data and air pollutants, including PM2.5, PM10, SO2, NO2, O38h and CO, were obtained from the period 2013 to 2020. A generalized additive model (GAM) combined with distribution lag nonlinear model (DLNM) based on quasi-Poisson distribution was used by the controlling for trends, weather, weekdays and holidays. Short-term exposure to PM2.5, NO2 and CO increased the risk of genitourinary disorder admissions with RR of 1.0096 (95% CI 1.0002-1.0190), 1.0255 (95% CI 1.0123-1.0389) and 1.0686 (95% CI 1.0083-1.1326), respectively. PM10, O38h and SO2 have no significant effect on genitourinary disorders. PM2.5 and NO2 are more strongly correlated in female and ≥ 65 years patients. CO is more strongly correlated in male and < 65 years patients. PM2.5, NO2 and CO are risk factors for genitourinary morbidity, and public health interventions should be strengthened to protect vulnerable populations.
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Affiliation(s)
- Runping Zhang
- School of Public Health, Lanzhou University, Lanzhou, 730000, People's Republic of China
| | - Miaoxin Liu
- School of Public Health, Lanzhou University, Lanzhou, 730000, People's Republic of China
| | - Wancheng Zhang
- School of Public Health, Lanzhou University, Lanzhou, 730000, People's Republic of China
| | - Jianglong Ling
- School of Public Health, Lanzhou University, Lanzhou, 730000, People's Republic of China
| | - Jiyuan Dong
- School of Public Health, Lanzhou University, Lanzhou, 730000, People's Republic of China
| | - Ye Ruan
- School of Public Health, Lanzhou University, Lanzhou, 730000, People's Republic of China.
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Zhang Y, Yang X, Jiang W, Gao X, Yang B, Feng XL, Yang L. Short-term effects of air pollutants on hospital admissions for asthma among older adults: a multi-city time series study in Southwest, China. Front Public Health 2024; 12:1346914. [PMID: 38347929 PMCID: PMC10859495 DOI: 10.3389/fpubh.2024.1346914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 01/12/2024] [Indexed: 02/15/2024] Open
Abstract
Background This study aimed to explore the relationship between air pollution and hospital admissions for asthma in older adults, and to further assess the health and economic burden of asthma admissions attributable to air pollution. Methods We collected information on asthma cases in people over 65 years of age from nine cities in Sichuan province, as well as air pollution and meteorological data. The relationship between short-term air pollutant exposure and daily asthma hospitalizations was analyzed using the generalized additive model (GAM), and stratified by gender, age, and season. In addition, we assessed the economic burden of hospitalization for air pollution-related asthma in older adults using the cost of disease approach. Results The single pollutant model showed that every 1 mg/m3 increase in CO was linked with an increase in daily hospitalizations for older adults with asthma, with relative risk values of 1.327 (95% CI: 1.116-1.577) at lag7. Each 10 μg/m3 increase in NO2, O3, PM10, PM2.5 and SO2, on asthma hospitalization, with relative risk values of 1.044 (95% CI: 1.011-1.078), 1.018 (95% CI: 1.002-1.034), 1.013 (95% CI: 1.004-1.022), 1.015 (95% CI: 1.003-1.028) and 1.13 (95% CI: 1.041-1.227), respectively. Stratified analysis shows that stronger associations between air pollution and asthma HAs among older adult in females, those aged 65-69 years, and in the warm season, although all of the differences between subgroups did not reach statistical significance. During the study period, the number of asthma hospitalizations attributable to PM2.5, PM10, and NO2 pollution was 764, 581 and 95, respectively, which resulted in a total economic cost of 6.222 million CNY, 4.73 million CNY and 0.776 million CNY, respectively. Conclusion This study suggests that short-term exposure to air pollutants is positively associated with an increase in numbers of asthma of people over 65 years of age in Sichuan province, and short-term exposure to excessive PM and NO2 brings health and economic burden to individuals and society.
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Affiliation(s)
- Yuqin Zhang
- School of Public Health, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Xi Yang
- School of Public Health, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Wanyanhan Jiang
- School of Public Health, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Xi Gao
- School of Public Health, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Biao Yang
- School of Public Health, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Xing Lin Feng
- School of Public Health, Peking University, Beijing, China
| | - Lian Yang
- School of Public Health, Chengdu University of Traditional Chinese Medicine, Chengdu, China
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5
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Honda A, Inoue KI, Higashihara M, Ichinose T, Ueda K, Takano H. Differential Pattern of Cell Death and ROS Production in Human Airway Epithelial Cells Exposed to Quinones Combined with Heated-PM2.5 and/or Asian Sand Dust. Int J Mol Sci 2023; 24:10544. [PMID: 37445720 DOI: 10.3390/ijms241310544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 06/15/2023] [Accepted: 06/19/2023] [Indexed: 07/15/2023] Open
Abstract
The combined toxicological effects of airborne particulate matter (PM), such as PM2.5, and Asian sand dust (ASD), with surrounding chemicals, particularly quinones, on human airway epithelial cells remain underexplored. In this study, we established an in vitro combination exposure model using 1,2-naphthoquinones (NQ) and 9,10-phenanthroquinones (PQ) along with heated PM (h-PM2.5 and h-ASD) to investigate their potential synergistic effects. The impacts of quinones and heated PM on tetrazolium dye (WST-1) reduction, cell death, and cytokine and reactive oxygen species (ROS) production were examined. Results revealed that exposure to 9,10-PQ with h-PM2.5 and/or h-ASD dose-dependently increased WST-1 reduction at 1 μM compared to the corresponding control while markedly decreasing it at 10 μM. Higher early apoptotic, late apoptotic, or necrotic cell numbers were detected in 9,10-PQ + h-PM2.5 exposure than in 9,10-PQ + h-ASD or 9,10-PQ + h-PM2.5 + h-ASD. Additionally, 1,2-NQ + h-PM2.5 exposure also resulted in an increase in cell death compared to 1,2-NQ + h-ASD and 1,2-NQ + h-PM2.5 + h-ASD. Quinones with or without h-PM2.5, h-ASD, or h-PM2.5 + h-ASD significantly increased ROS production, especially with h-PM2.5. Our findings suggest that quinones, at relatively low concentrations, induce cell death synergistically in the presence of h-PM2.5 rather than h-ASD and h-PM2.5 + h-ASD, partially through the induction of apoptosis with increased ROS generation.
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Affiliation(s)
- Akiko Honda
- Graduate School of Engineering, Kyoto University, Kyoto 615-8540, Japan
| | - Ken-Ichiro Inoue
- School of Nursing, University of Shizuoka, Shizuoka 422-8526, Japan
| | | | - Takamichi Ichinose
- Graduate School of Global Environmental Studies, Kyoto University, Kyoto 615-8540, Japan
- Department of Health Science, Oita University of Nursing and Health Sciences, Oita 870-1201, Japan
| | - Kayo Ueda
- Department of Hygiene, Graduate School of Medicine, Hokkaido University, Hokkaido 060-8638, Japan
| | - Hirohisa Takano
- Graduate School of Global Environmental Studies, Kyoto University, Kyoto 615-8540, Japan
- Institute for International Academic Research, Kyoto University of Advanced Science, Kyoto 615-8577, Japan
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Shen J, Ma Y, Zhang Y, Zhang C, Wang W, Qin P, Yang L. Temperature modifies the effects of air pollutants on respiratory diseases. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:61778-61788. [PMID: 36933135 DOI: 10.1007/s11356-023-26322-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Accepted: 03/03/2023] [Indexed: 05/10/2023]
Abstract
Increasing studies have reported temperature modification effects on air pollutants-induced respiratory diseases. In the current study, daily data of respiratory emergency room visits (ERVs), meteorological factors, and concentrations of air pollutants were collected from 2013 to 2016 in Lanzhou, a northwest city in China. Daily average temperature was stratified into low (≤ 25 percentile, P25), medium (25-75 percentile, P25-P75) and high (≥ 75 percentile, P75) to explore how temperature modifies the effects of air pollutants (PM2.5, PM10, SO2, and NO2) on respiratory ERVs by using generalized additive Poisson regression model (GAM). Seasonal modification was also investigated. Results showed that (a) PM10, PM2.5, and NO2 had the strongest effects on respiratory ERVs in low temperature; (b) males and 15-and-younger were more vulnerable in low temperature while females and those older than 46 years were highly affected in high temperature; (c) PM10, PM2.5, and NO2 were mostly associated with the total and both males and females in winter, while SO2 resulted in the highest risk for the total and males in autumn and females in spring. In conclusion, this study found significant temperature modification effects and seasonal differences on the risks of respiratory ERVs due to air pollutants in Lanzhou, China.
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Affiliation(s)
- Jiahui Shen
- 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
| | - Yifan Zhang
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Caixia Zhang
- First People's Hospital of Dingxi, Dingxi, 743000, China.
| | - Wanci Wang
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Pengpeng Qin
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Lijie Yang
- Qingyang Meteorological Bureau, Qingyang, 745000, China
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Bai L, Lu K, Dong Y, Wang X, Gong Y, Xia Y, Wang X, Chen L, Yan S, Tang Z, Li C. Predicting monthly hospital outpatient visits based on meteorological environmental factors using the ARIMA model. Sci Rep 2023; 13:2691. [PMID: 36792764 PMCID: PMC9930044 DOI: 10.1038/s41598-023-29897-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 02/13/2023] [Indexed: 02/17/2023] Open
Abstract
Accurate forecasting of hospital outpatient visits is beneficial to the rational planning and allocation of medical resources to meet medical needs. Several studies have suggested that outpatient visits are related to meteorological environmental factors. We aimed to use the autoregressive integrated moving average (ARIMA) model to analyze the relationship between meteorological environmental factors and outpatient visits. Also, outpatient visits can be forecast for the future period. Monthly outpatient visits and meteorological environmental factors were collected from January 2015 to July 2021. An ARIMAX model was constructed by incorporating meteorological environmental factors as covariates to the ARIMA model, by evaluating the stationary [Formula: see text], coefficient of determination [Formula: see text], mean absolute percentage error (MAPE), and normalized Bayesian information criterion (BIC). The ARIMA [Formula: see text] model with the covariates of [Formula: see text], [Formula: see text], and [Formula: see text] was the optimal model. Monthly outpatient visits in 2019 can be predicted using average data from past years. The relative error between the predicted and actual values for 2019 was 2.77%. Our study suggests that [Formula: see text], [Formula: see text], and [Formula: see text] concentration have a significant impact on outpatient visits. The model built has excellent predictive performance and can provide some references for the scientific management of hospitals to allocate staff and resources.
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Affiliation(s)
- Lu Bai
- grid.263761.70000 0001 0198 0694Department of Biostatistics, School of Public Health, Medical College of Soochow University, Suzhou, 215123 China ,grid.263761.70000 0001 0198 0694Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, Suzhou, 215123 China
| | - Ke Lu
- grid.452273.50000 0004 4914 577XDepartment of Orthopedics, Affiliated Kunshan Hospital of Jiangsu University, No. 91 West of Qianjin Road, Suzhou, 215300 Jiangsu China
| | - Yongfei Dong
- grid.263761.70000 0001 0198 0694Department of Biostatistics, School of Public Health, Medical College of Soochow University, Suzhou, 215123 China ,grid.263761.70000 0001 0198 0694Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, Suzhou, 215123 China
| | - Xichao Wang
- grid.263761.70000 0001 0198 0694Department of Biostatistics, School of Public Health, Medical College of Soochow University, Suzhou, 215123 China ,grid.263761.70000 0001 0198 0694Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, Suzhou, 215123 China
| | - Yaqin Gong
- grid.452273.50000 0004 4914 577XInformation Department, Affiliated Kunshan Hospital of Jiangsu University, Suzhou, 215300 Jiangsu China
| | - Yunyu Xia
- Meteorological Bureau of Kunshan City, Suzhou, 215337 Jiangsu China
| | - Xiaochun Wang
- Meteorological Bureau of Kunshan City, Suzhou, 215337 Jiangsu China
| | - Lin Chen
- Ecology and Environment Bureau of Kunshan City, Suzhou, 215330 Jiangsu China
| | - Shanjun Yan
- Ecology and Environment Bureau of Kunshan City, Suzhou, 215330 Jiangsu China
| | - Zaixiang Tang
- Department of Biostatistics, School of Public Health, Medical College of Soochow University, Suzhou, 215123, China. .,Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, Suzhou, 215123, China.
| | - Chong Li
- Department of Orthopedics, Affiliated Kunshan Hospital of Jiangsu University, No. 91 West of Qianjin Road, Suzhou, 215300, Jiangsu, China.
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Lin G, Wang Z, Zhang X, Stein A, Maji KJ, Cheng C, Osei F, Yang FF. Comparison of the association between different ozone indicators and daily respiratory hospitalization in Guangzhou, China. Front Public Health 2023; 11:1060714. [PMID: 36794065 PMCID: PMC9922759 DOI: 10.3389/fpubh.2023.1060714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 01/03/2023] [Indexed: 02/03/2023] Open
Abstract
Background Epidemiological studies have widely proven the impact of ozone (O3) on respiratory mortality, while only a few studies compared the association between different O3 indicators and health. Methods This study explores the relationship between daily respiratory hospitalization and multiple ozone indicators in Guangzhou, China, from 2014 to 2018. It uses a time-stratified case-crossover design. Sensitivities of different age and gender groups were analyzed for the whole year, the warm and the cold periods. We compared the results from the single-day lag model and the moving average lag model. Results The results showed that the maximum daily 8 h average ozone concentration (MDA8 O3) had a significant effect on the daily respiratory hospitalization. This effect was stronger than for the maximum daily 1 h average ozone concentration (MDA1 O3). The results further showed that O3 was positively associated with daily respiratory hospitalization in the warm season, while there was a significantly negative association in the cold season. Specifically, in the warm season, O3 has the most significant effect at lag 4 day, with the odds ratio (OR) equal to 1.0096 [95% confidence intervals (CI): 1.0032, 1.0161]. Moreover, at the lag 5 day, the effect of O3 on the 15-60 age group was less than that on people older than 60 years, with the OR value of 1.0135 (95% CI: 1.0041, 1.0231) for the 60+ age group; women were more sensitive than men to O3 exposure, with an OR value equal to 1.0094 (95% CI: 0.9992, 1.0196) for the female group. Conclusion These results show that different O3 indicators measure different impacts on respiratory hospitalization admission. Their comparative analysis provided a more comprehensive insight into exploring associations between O3 exposure and respiratory health.
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Affiliation(s)
- Geng Lin
- School of Geography and Planning, Sun Yat-sen University, Guangzhou, China
| | - Zhuoqing Wang
- Department of Scientific Research and Discipline Development, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China,*Correspondence: Zhuoqing Wang ✉
| | - Xiangxue Zhang
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China,Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, Netherlands,Xiangxue Zhang ✉
| | - Alfred Stein
- Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, Netherlands
| | - Kamal Jyoti Maji
- School of Civil and Environment Engineering, Georgia Institute of Technology, Atlanta, GA, United States
| | - Changxiu Cheng
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China,National Tibetan Plateau Data Center, Beijing, China
| | - Frank Osei
- Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, Netherlands
| | - Fiona Fan Yang
- School of Geography and Planning, Sun Yat-sen University, Guangzhou, China
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9
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Zhang X, Maji KJ, Wang Z, Yang FF, Wang G, Cheng C. Associations between Different Ozone Indicators and Cardiovascular Hospital Admission: A Time-Stratified Case-Crossover Analysis in Guangzhou, China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:ijerph20032056. [PMID: 36767423 PMCID: PMC9916254 DOI: 10.3390/ijerph20032056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2022] [Accepted: 01/13/2023] [Indexed: 05/17/2023]
Abstract
Epidemiological studies reported that ozone (O3) is associated with cardiovascular diseases. However, only few of these studies examined the impact of multiple O3 indicators on cardiovascular hospital admissions. This study aimed to explore and compare the impacts of different O3 indicators on cardiovascular hospital admissions in Guangzhou, China. Based upon the data on daily cardiovascular hospital admissions, air pollution, and meteorological factors in Guangzhou from 2014 to 2018, a time-stratified case-crossover design model was used to analyze the associations between different O3 indicators and cardiovascular hospital admissions. Moreover, the sensitivities of different age and gender groups were analyzed for the whole year and different seasons (i.e., warm and cold). During the warm season, for the single-pollutant model, the odds ratio (OR) value of cardiovascular hospital admissions was 1.0067 (95% confidence interval (CI): 1.0037, 1.0098) for every IQR increase in MDA8 O3 at a lag of five days. The effect of O3 on people over 60 year was stronger than that on the 15-60 years age group. Females were more sensitive than males to O3 exposure. These results provided valuable references for further scientific research and environmental improvement in Guangzhou. Given that short-term O3 exposure poses a threat to human health, the government should therefore pay attention to prevention and control policies to reduce and eliminate O3 pollution and protect human health.
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Affiliation(s)
- Xiangxue Zhang
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
- Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7514 AE Enschede, The Netherlands
| | - Kamal Jyoti Maji
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Zhuoqing Wang
- Department of Scientific Research & Discipline Development, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou 510080, China
| | - Fiona Fan Yang
- School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510006, China
| | - Guobin Wang
- School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510006, China
| | - Changxiu Cheng
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
- National Tibetan Plateau Data Center, Beijing 100101, China
- Correspondence:
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Chen S, Xu B, Shi T, Yang Q. Short-term effect of ambient air pollution on outpatient visits for children in Guangzhou, China. Front Public Health 2023; 11:1058368. [PMID: 36741946 PMCID: PMC9895100 DOI: 10.3389/fpubh.2023.1058368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 01/03/2023] [Indexed: 01/21/2023] Open
Abstract
This study examined the short-term relationship between ambient air pollutants and children's outpatient visits, and identified the effect of modifications by season. Daily recordings of air pollutants (CO, NO2, O3, SO2, PM10, and PM2.5) and children's outpatient visit data were collected in Guangzhou from 2015 to 2019. A generalized additive model adjusted for potential confounding was introduced to verify the association between ambient air pollution and outpatient visits for children. Subgroup analysis by season was performed to evaluate the potential effects. A total of 5,483,014 children's outpatient visits were recorded. The results showed that a 10 μg/m3 increase in CO, NO2, O3, SO2, PM10, and PM2.5 corresponded with a 0.19% (95% CI: 0.15-0.24%), 2.46% (2.00-2.92%), 0.27% (0.07-0.46%), 7.16% (4.80-9.57%), 1.16% (0.83-1.49%), and 1.35% (0.88-1.82%) increase in children's outpatient visits on the lag0 of exposure, respectively. The relationships were stronger for O3, PM10, and PM2.5 in the warm seasons, and for CO, NO2, and SO2 in the cool seasons. When adjusting for the co-pollutants, the effects of CO, NO2, and PM10 were robust. The results of this study indicate that six air pollutants might increase the risk of children's outpatient visits in Guangzhou, China, especially in the cool season.
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Affiliation(s)
- Sili Chen
- Department of Preventive Medicine, School of Public Health, Guangzhou Medical University, Guangzhou, China
| | - Binhe Xu
- Department of Clinical Medicine, Basic Medicine College, Zunyi Medical University, Zunyi, China
| | - Tongxing Shi
- Department of Environmental Hygiene, Guangzhou Center for Disease Control and Prevention, Guangzhou, China,Department of Environmental Health, Institute of Public Health, Guangzhou Medical University, Guangzhou, China
| | - Qiaoyuan Yang
- Department of Preventive Medicine, School of Public Health, Guangzhou Medical University, Guangzhou, China,Department of Environmental Health, Institute of Public Health, Guangzhou Medical University, Guangzhou, China,*Correspondence: Qiaoyuan Yang ✉
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11
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Fang X, Huang S, Zhu Y, Lei J, Xu Y, Niu Y, Chen R. Short-term exposure to ozone and asthma exacerbation in adults: A longitudinal study in China. Front Public Health 2023; 10:1070231. [PMID: 36684992 PMCID: PMC9854395 DOI: 10.3389/fpubh.2022.1070231] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 12/13/2022] [Indexed: 01/09/2023] Open
Abstract
Background The relationships between short-term ozone exposure and the acute exacerbations of asthma in adults have not been fully studied. Existing studies commonly ignored the effects of ozone on mild or early asthma exacerbations. Objective To investigate the associations between short-term ozone exposure and asthma exacerbations in Chinese adults. Methods We administered health management for adult asthma patients through the Respiratory Home Platform and required them to monitor their lung function every morning and evening by themselves. Finally, a total of 4,467 patients in 18 Chinese cities were included in the current analyses, with 79,217 pairs of lung function records. The maximum daily 8-h average ozone concentrations were collected from fixed-site air quality monitoring stations. We calculated diurnal peak expiratory flow (PEF) variation using morning and evening measurements of PEF and then defined different severity of asthma exacerbations with diurnal PEF variations >10, 15, and 20%, respectively. A binomial distributed generalized additive mixture model combined with distribution non-linear models was applied to examine the association of ozone with asthma exacerbations. We further conducted stratified analyses by sex, age, season of lung function tests, and region. Measurements and results We found that short-term ozone exposure was independently associated with an elevated risk of asthma exacerbations defined by lung function and the effects could last for about 2 days. At lag 0-2 days, each 10 μg/m3 increment in ozone concentration was associated with odds ratios of 1.010 [95% confidence interval (CI): 1.003, 1.017], 1.014 (95% CI: 1.005, 1.023), and 1.017 (95% CI: 1.006, 1.028) for asthma exacerbations that were defined by diurnal PEF variation over 10, 15, and 20%, respectively. The associations remained significant after adjusting for other pollutants, and became unstable when using 24-h average ozone concentration. We also found that the associations were relatively stronger in males, those aged 45 years and older, and in the warm season. Conclusions Our results suggest that short-term ozone exposure can increase the risk of asthma exacerbations, even in the early stage of exacerbation. Male and older asthma patients may be more vulnerable to ozone air pollution, especially in the warm season.
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Affiliation(s)
- Xinyi Fang
- Key Laboratory of Public Health Safety of the Ministry of Education, NHC Key Laboratory of Health Technology Assessment, School of Public Health, Fudan University, Shanghai, China
| | - Suijie Huang
- Guangzhou Homesun Medical Technology Co. Ltd., Guangzhou, Guangdong Province, China
| | - Yixiang Zhu
- Key Laboratory of Public Health Safety of the Ministry of Education, NHC Key Laboratory of Health Technology Assessment, School of Public Health, Fudan University, Shanghai, China
| | - Jian Lei
- Key Laboratory of Public Health Safety of the Ministry of Education, NHC Key Laboratory of Health Technology Assessment, School of Public Health, Fudan University, Shanghai, China
| | - Yanyi Xu
- Key Laboratory of Public Health Safety of the Ministry of Education, NHC Key Laboratory of Health Technology Assessment, School of Public Health, Fudan University, Shanghai, China
| | - Yue Niu
- Key Laboratory of Public Health Safety of the Ministry of Education, NHC Key Laboratory of Health Technology Assessment, School of Public Health, Fudan University, Shanghai, China
| | - Renjie Chen
- Key Laboratory of Public Health Safety of the Ministry of Education, NHC Key Laboratory of Health Technology Assessment, School of Public Health, Fudan University, Shanghai, China
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12
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Ma Y, Shen J, Zhang Y, Wang H, Li H, Cheng Y, Guo Y. Short-term effect of ambient ozone pollution on respiratory diseases in western China. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2022; 44:4129-4140. [PMID: 35001229 DOI: 10.1007/s10653-021-01174-9] [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: 07/20/2021] [Accepted: 11/30/2021] [Indexed: 06/14/2023]
Abstract
Ambient air pollution has been regarded as an important cause of the morbidity and mortality of respiratory diseases. In the current work, a total of 469,490 respiratory emergency room (ER) visits in Lanzhou, China from Jan 1, 2013 to Dec 31, 2016 were collected. A generalized additive model (GAM) was used to investigate the association between O3 and respiratory ER visits for the different gender and age subgroups. The results showed that: (a) with per inter-quartile range (IQR) (31 µg/m3) increase in O3, the greatest relative risk (RR) of respiratory ER visits for the total was 1.014 (95% CI 1.008-1.020) at lag 4 days. Females and 16-to-45-year-olds were relatively more sensitive to O3; (b) the significant lag effects were found in single-day lag models, with the highest RR values for different groups were observed at lag 3-lag 5 days. The multi-day cumulative lag effects were stronger for the total; (c) in the multiple-pollutant models, the effects of O3 were generally increased when introducing other pollutants (PM10, PM2.5, SO2 and NO2) for adjustment. This study demonstrated that short-term exposure to O3 increased the RR of respiratory ER visits in Lanzhou, China.
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Affiliation(s)
- Yuxia Ma
- 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
| | - Yifan Zhang
- 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
| | - Heping Li
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Yifan Cheng
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Yongtao Guo
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
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13
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Wang Y, Hu J, Huang L, Li T, Yue X, Xie X, Liao H, Chen K, Wang M. Projecting future health burden associated with exposure to ambient PM 2.5 and ozone in China under different climate scenarios. ENVIRONMENT INTERNATIONAL 2022; 169:107542. [PMID: 36194980 DOI: 10.1016/j.envint.2022.107542] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 09/18/2022] [Accepted: 09/23/2022] [Indexed: 06/16/2023]
Abstract
Projecting future air pollution and related health burdens remains challenging because of the complex interactions among future emissions, population, and climate change. In this study, we estimated the premature deaths attributed to ambient fine particulate matter (PM2.5) and ozone (O3) from 2015 to 2100 under four socioeconomic climate scenarios based on an age-stratified assessment method. We found that PM2.5 will decrease in all shared socioeconomic pathway (SSP) scenarios and O3 will decrease in the SSP1-2.6 and SSP2-4.5 scenarios, contributing to a decrease in premature mortality together with the declining total population in China. However, the benefits of a decline in population size and PM2.5 and O3 concentrations over time will be largely offset by population aging, and premature death caused by PM2.5 and O3 will continue to rise till 2060-2080. This impact was greater for the O3-related deaths than those for PM2.5. Our study highlights the importance of future prevention strategies that must jointly improve air quality and susceptibility to aging.
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Affiliation(s)
- Yiyi Wang
- Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing 210044, China; State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Jianlin Hu
- Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing 210044, China.
| | - Lei Huang
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Tiantian Li
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xu Yue
- Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing 210044, China
| | - Xiaodong Xie
- Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing 210044, China
| | - Hong Liao
- Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing 210044, China
| | - Kai Chen
- Yale Center on Climate Change and Health, Yale School of Public Health, 60 College Street, New Haven, CT 06520-8034, USA
| | - Meng Wang
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY, USA; RENEW Institute, University at Buffalo, Buffalo, NY, USA; Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, WA, USA.
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14
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Sharma S, Chandra M, Harsha Kota S. Four year long simulation of carbonaceous aerosols in India: Seasonality, sources and associated health effects. ENVIRONMENTAL RESEARCH 2022; 213:113676. [PMID: 35728639 DOI: 10.1016/j.envres.2022.113676] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 05/26/2022] [Accepted: 06/10/2022] [Indexed: 06/15/2023]
Abstract
India's air quality is in a dismal state, with many studies ascribing it to PM2.5. Most of these corroborate that carbonaceous aerosol (CA) constitute significant fraction of PM2.5. However, investigations on the effect of long-term meteorological or emission changes on PM2.5 and its components, and their associated health effects are rare. In this work, WRF-Chem simulations for three seasons over four years (2016-2019) were carried out to cogitate the spatial and temporal changes in PM2.5 and its components in India. Model predicted PM2.5 concentrations were in good agreement with the ground-based observations for 25 cities. PM2.5 was highest in winter and lowest in pre-monsoon. PM2.5 reduced by ∼8% in Indo-Gangetic Plain (IGP) but increased by ∼38% and ∼130% in south and northeast India, respectively, from 2016 to 2019. IGP witnessed three times higher average PM2.5 concentrations than south India. No significant interannual change in CA contributions was observed, however, it peaked in the winter season. Other inorganics (OIN) were the major component of PM2.5, contributing more than 40%. Primary organic aerosol (POA) fractions were higher in north India, while secondary inorganic aerosol (SIA) dominated south India. Transport and residential sectors were the chief contributors to CA across India. Biomass burning contributed up to ∼23% of PM2.5 in regions of IGP during post-monsoon, with CA fractions up to 50%. Associations between PM2.5 and its components with daily inpatient admissions from a tertiary care centre in Delhi showed that PM2.5 and OIN had lower associations with daily hospital admissions than CA. Every 10 μg/m3 increase in POA, black carbon (BC), and secondary organic aerosol (SOA) were associated with ∼1.09%, ∼3.07% and ∼4.93% increase in the risk of daily hospital admissions. This invigorates the need for more policies targeting CA rather than PM2.5 to mitigate associated health risks, in India.
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Affiliation(s)
- Shubham Sharma
- Department of Civil Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, 110 016, India
| | - Mina Chandra
- Department of Psychiatry, Centre of Excellence in Mental Health, Atal Bihari Vajpayee Institute of Medical Sciences and Dr Ram Manohar Lohia Hospital, New Delhi, 110001, India
| | - Sri Harsha Kota
- Department of Civil Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, 110 016, India; Arun Duggal Centre of Excellence for Research in Climate Change and Air Pollution (CERCA), IIT Delhi, New Delhi, 110016, India.
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15
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Owusu C, Flanagan B, Lavery AM, Mertzlufft CE, McKenzie BA, Kolling J, Lewis B, Dunn I, Hallisey E, Lehnert EA, Fletcher K, Davis RT, Conn M, Owen LR, Smith MM, Dent A. Developing a granular scale environmental burden index (EBI) for diverse land cover types across the contiguous United States. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 838:155908. [PMID: 35588849 DOI: 10.1016/j.scitotenv.2022.155908] [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: 02/08/2022] [Revised: 04/15/2022] [Accepted: 05/09/2022] [Indexed: 06/15/2023]
Abstract
Critical to identifying the risk of environmentally driven disease is an understanding of the cumulative impact of environmental conditions on human health. Here we describe the methodology used to develop an environmental burden index (EBI). The EBI is calculated at U.S. census tract level, a finer scale than many similar national-level tools. EBI scores are also stratified by tract land cover type as per the National Land Cover Database (NLCD), controlling for urbanicity. The EBI was developed over the course of four stages: 1) literature review to identify potential indicators, 2) data source acquisition and indicator variable construction, 3) index creation, and 4) stratification by land cover type. For each potential indicator, data sources were assessed for completeness, update frequency, and availability. These indicators were: (1) particulate matter (PM2.5), (2) ozone, (3) Superfund National Priority List (NPL) locations, (4) Toxics Release Inventory (TRI) facilities, (5) Treatment, Storage, and Disposal (TSD) facilities, (6) recreational parks, (7) railways, (8) highways, (9) airports, and (10) impaired water sources. Indicators were statistically normalized and checked for collinearity. For each indicator, we computed and summed percentile ranking scores to create an overall ranking for each tract. Tracts having the same plurality of land cover type form a 'peer' group. We re-ranked the tracts into percentiles within each peer group for each indicator. The percentile scores were combined for each tract to obtain a stratified EBI. A higher score reveals a tract with increased environmental burden relative to other tracts of the same peer group. We compared our results to those of related indices, finding good convergent validity between the overall EBI and CalEnviroScreen 4.0. The EBI has many potential applications for research and use as a tool to develop public health interventions at a granular scale.
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Affiliation(s)
- Claudio Owusu
- Centers for Disease Control and Prevention, Agency for Toxic Substances and Disease Registry, National Center for Environmental Health, Office of Innovation and Analytics, Geospatial Research, Analysis, and Services Program, USA.
| | - Barry Flanagan
- Centers for Disease Control and Prevention, Agency for Toxic Substances and Disease Registry, National Center for Environmental Health, Office of Innovation and Analytics, Geospatial Research, Analysis, and Services Program, USA.
| | - Amy M Lavery
- Centers for Disease Control and Prevention, Agency for Toxic Substances and Disease Registry, National Center for Environmental Health, Office of Innovation and Analytics, Geospatial Research, Analysis, and Services Program, USA; Centers for Disease Control and Prevention, Agency for Toxic Substances and Disease Registry, National Center for Environmental Health, Office of Emergency Management, USA.
| | - Caitlin E Mertzlufft
- Centers for Disease Control and Prevention, Agency for Toxic Substances and Disease Registry, National Center for Environmental Health, Office of Innovation and Analytics, Geospatial Research, Analysis, and Services Program, USA.
| | - Benjamin A McKenzie
- Centers for Disease Control and Prevention, Agency for Toxic Substances and Disease Registry, National Center for Environmental Health, Office of Innovation and Analytics, Geospatial Research, Analysis, and Services Program, USA.
| | - Jessica Kolling
- Centers for Disease Control and Prevention, Agency for Toxic Substances and Disease Registry, National Center for Environmental Health, Office of Innovation and Analytics, Geospatial Research, Analysis, and Services Program, USA
| | - Brian Lewis
- Centers for Disease Control and Prevention, Agency for Toxic Substances and Disease Registry, National Center for Environmental Health, Office of Innovation and Analytics, Geospatial Research, Analysis, and Services Program, USA.
| | - Ian Dunn
- The Ohio Colleges of Medicine Government Resource Center, Columbus, OH, USA.
| | - Elaine Hallisey
- Centers for Disease Control and Prevention, Agency for Toxic Substances and Disease Registry, National Center for Environmental Health, Office of Innovation and Analytics, Geospatial Research, Analysis, and Services Program, USA.
| | - Erica Adams Lehnert
- Centers for Disease Control and Prevention, Agency for Toxic Substances and Disease Registry, National Center for Environmental Health, Office of Innovation and Analytics, Geospatial Research, Analysis, and Services Program, USA.
| | - Kelly Fletcher
- Centers for Disease Control and Prevention, Agency for Toxic Substances and Disease Registry, National Center for Environmental Health, Office of Innovation and Analytics, Geospatial Research, Analysis, and Services Program, USA.
| | - Ryan T Davis
- Centers for Disease Control and Prevention, Agency for Toxic Substances and Disease Registry, National Center for Environmental Health, Office of Innovation and Analytics, Geospatial Research, Analysis, and Services Program, USA.
| | - Michel Conn
- Centers for Disease Control and Prevention, Agency for Toxic Substances and Disease Registry, National Center for Environmental Health, Office of Innovation and Analytics, Geospatial Research, Analysis, and Services Program, USA.
| | - Lance R Owen
- Centers for Disease Control and Prevention, Agency for Toxic Substances and Disease Registry, National Center for Environmental Health, Office of Innovation and Analytics, Geospatial Research, Analysis, and Services Program, USA.
| | - Melissa M Smith
- Centers for Disease Control and Prevention, Agency for Toxic Substances and Disease Registry, National Center for Environmental Health, Office of Innovation and Analytics, Geospatial Research, Analysis, and Services Program, USA.
| | - Andrew Dent
- Centers for Disease Control and Prevention, Agency for Toxic Substances and Disease Registry, National Center for Environmental Health, Office of Innovation and Analytics, Geospatial Research, Analysis, and Services Program, USA.
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16
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Association between out-patient visits and air pollution in Chiang Mai, Thailand: Lessons from a unique situation involving a large data set showing high seasonal levels of air pollution. PLoS One 2022; 17:e0272995. [PMID: 35980887 PMCID: PMC9387779 DOI: 10.1371/journal.pone.0272995] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Accepted: 07/29/2022] [Indexed: 11/19/2022] Open
Abstract
Chiang Mai is one of the most known cities of Northern Thailand, representative for various cities in the East and South-East Asian region exhibiting seasonal smog crises. While a few studies have attempted to address smog crises effects on human health in that geographic region, research in this regard is still in its infancy. We exploited a unique situation based on two factors: large pollutant concentration variations due to the Chiang Mai smog crises and a relatively large sample of out-patient visits. About 216,000 out-patient visits in the area of Chiang Mai during the period of 2011 to 2014 for upper (J30-J39) and lower (J44) respiratory tract diseases were evaluated with respect to associations with particulate matter (PM10), ozone (O3), and nitrogen dioxide (NO2) concentrations using single-pollutant and multiple-pollutants Poisson regression models. All three pollutants were found to be associated with visits due to upper respiratory tract diseases (with relative risks RR = 1.023 at cumulative lag 05, 95% CI: 1.021–1.025, per 10 μg/m3 PM10 increase, RR = 1.123 at lag 05, 95% CI: 1.118–1.129, per 10 ppb O3 increase, and RR = 1.110 at lag 05, 95% CI: 1.102–1.119, per 10 ppb NO2 increase). Likewise, all three pollutants were found to be associated with visits due to lower respiratory tract diseases (with RR = 1.016 at lag 06, 95% CI: 1.015–1.017, per 10 μg/m3 PM10 increase, RR = 1.073 at lag 06, 95% CI: 1.070–1.076, per 10 ppb O3 increase, and RR = 1.046 at lag 06, 95% CI: 1.040–1.051, per 10 ppb NO2 increase). Multi-pollutants modeling analysis identified O3 as a relatively independent risk factor and PM10-NO2 pollutants models as promising two-pollutants models. Overall, these results demonstrate the adverse effects of all three air pollutants on respiratory morbidity and call for air pollution reduction and control.
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Xie X, Hu J, Qin M, Guo S, Hu M, Wang H, Lou S, Li J, Sun J, Li X, Sheng L, Zhu J, Chen G, Yin J, Fu W, Huang C, Zhang Y. Modeling particulate nitrate in China: Current findings and future directions. ENVIRONMENT INTERNATIONAL 2022; 166:107369. [PMID: 35772313 DOI: 10.1016/j.envint.2022.107369] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 06/07/2022] [Accepted: 06/20/2022] [Indexed: 06/15/2023]
Abstract
Particulate nitrate (pNO3) is now becoming the principal component of PM2.5 during severe winter haze episodes in many cities of China. To gain a comprehensive understanding of the key factors controlling pNO3 formation and driving its trends, we reviewed the recent pNO3 modeling studies which mainly focused on the formation mechanism and recent trends of pNO3 as well as its responses to emission controls in China. The results indicate that although recent chemical transport models (CTMs) can reasonably capture the spatial-temporal variations of pNO3, model-observation biases still exist due to large uncertainties in the parameterization of dinitrogen pentoxide (N2O5) uptake and ammonia (NH3) emissions, insufficient heterogeneous reaction mechanism, and the predicted low sulfate concentrations in current CTMs. The heterogeneous hydrolysis of N2O5 dominates nocturnal pNO3 formation, however, the contribution to total pNO3 varies among studies, ranging from 21.0% to 51.6%. Moreover, the continuously increasing PM2.5 pNO3 fraction in recent years is mainly due to the decreased sulfur dioxide emissions, the enhanced atmospheric oxidation capacity (AOC), and the weakened nitrate deposition. Reducing NH3 emissions is found to be the most effective control strategy for mitigating pNO3 pollution in China. This review suggests that more field measurements are needed to constrain the parameterization of heterogeneous N2O5 and nitrogen dioxide (NO2) uptake. Future studies are also needed to quantify the relationships of pNO3 to AOC, O3, NOx, and volatile organic compounds (VOCs) in different regions of China under different meteorological conditions. Research on multiple-pollutant control strategies involving NH3, NOX, and VOCs is required to mitigate pNO3 pollution, especially during severe winter haze events.
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Affiliation(s)
- Xiaodong Xie
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Jianlin Hu
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China.
| | - Momei Qin
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Song Guo
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Min Hu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Hongli Wang
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Shengrong Lou
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Jingyi Li
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Jinjin Sun
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Xun Li
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Li Sheng
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Jianlan Zhu
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Ganyu Chen
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Junjie Yin
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Wenxing Fu
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Cheng Huang
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Yuanhang Zhang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; CAS Center for Excellence in Regional Atmospheric Environment, Chinese Academy of Science, Xiamen 361021, China.
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18
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Thongphunchung K, Charoensuk P, U-tapan S, Loonsamrong W, Phosri A, Mahikul W. Outpatient Department Visits and Mortality with Various Causes Attributable to Ambient Air Pollution in the Eastern Economic Corridor of Thailand. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19137683. [PMID: 35805343 PMCID: PMC9265572 DOI: 10.3390/ijerph19137683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 06/20/2022] [Accepted: 06/21/2022] [Indexed: 11/16/2022]
Abstract
The Eastern Economic Corridor in Thailand is undergoing development, but industrial activities are causing serious air pollution. This study aimed to examine the effects of particulate matter (PM10), fine particulate matter (PM2.5), SO2, NO2, O3, and CO on outpatient department (OPD) visits and mortality with various causes in the Eastern Economic Corridor, Thailand between 2013 and 2019 using a case-crossover design and conditional Poisson model. The corresponding burden of disease due to air pollution exposure was calculated. A 1 µg/m3 increase in the PM10 was associated with significant increases in OPD visits for circulatory diseases (0.22, 95% CI 0.01, 0.34), respiratory diseases (0.21, 95% CI 0.13, 0.28), and skin and subcutaneous tissue diseases (0.18, 95% CI 0.10, 0.26). By contrast, a 1 µg/m3 increase in the PM10 was associated with significant increases in mortality from skin and subcutaneous tissue diseases (0.79, 95% CI 0.04, 1.56). A 1 µg/m3 increase in PM2.5 was associated with significant increases in mortality from circulatory diseases (0.75, 95% CI 0.20, 1.34), respiratory diseases (0.82, 95% CI 0.02, 1.63), and skin and subcutaneous tissue diseases (2.91, 95% CI 0.99, 4.86). The highest OPD burden was for circulatory diseases. Respiratory effects were attributed to PM10 exceeding the national ambient air quality standards (NAAQS) of Thailand (120 μg/m3). The highest morbidity burden was for skin and subcutaneous tissue diseases attributed to PM2.5 concentrations that exceeded the NAAQs (50 μg/m3). PM pollution in the EEC could strongly contribute to OPD visits and morbidity from various diseases. Preventing PM10 concentrations from being higher than 60 µg/m3 could decrease OPD visits by more than 33,265 and 29,813 for circulatory and respiratory diseases, respectively. Our study suggests that such pollution increases the risks of OPD visits and mortality in various causes in the Thai EEC. Reducing the ambient air pollution concentration of NAAQSs in Thailand could reduce the health effect on the Thai population.
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Affiliation(s)
- Khanut Thongphunchung
- Health Impact Assessment Division, Department of Health, Ministry of Public Health, Nonthaburi 11000, Thailand; (K.T.); (P.C.); (S.U.-t.); (W.L.)
| | - Panita Charoensuk
- Health Impact Assessment Division, Department of Health, Ministry of Public Health, Nonthaburi 11000, Thailand; (K.T.); (P.C.); (S.U.-t.); (W.L.)
| | - Sutida U-tapan
- Health Impact Assessment Division, Department of Health, Ministry of Public Health, Nonthaburi 11000, Thailand; (K.T.); (P.C.); (S.U.-t.); (W.L.)
| | - Wassana Loonsamrong
- Health Impact Assessment Division, Department of Health, Ministry of Public Health, Nonthaburi 11000, Thailand; (K.T.); (P.C.); (S.U.-t.); (W.L.)
| | - Arthit Phosri
- Department of Environmental Health Sciences, Faculty of Public Health, Mahidol University, Bangkok 10400, Thailand;
- Center of Excellence on Environmental Health and Toxicology, Bangkok 10400, Thailand
| | - Wiriya Mahikul
- Princess Srisavangavadhana College of Medicine, Chulabhorn Royal Academy, Bangkok 10210, Thailand
- Correspondence: ; Tel.: +66-93194-2944
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Yang L, Yang J, Liu M, Sun X, Li T, Guo Y, Hu K, Bell ML, Cheng Q, Kan H, Liu Y, Gao H, Yao X, Gao Y. Nonlinear effect of air pollution on adult pneumonia hospital visits in the coastal city of Qingdao, China: A time-series analysis. ENVIRONMENTAL RESEARCH 2022; 209:112754. [PMID: 35074347 DOI: 10.1016/j.envres.2022.112754] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 12/31/2021] [Accepted: 01/14/2022] [Indexed: 06/14/2023]
Abstract
Many studies have illustrated adverse effects of short-term exposure to air pollution on human health, which usually assumes a linear exposure-response (E-R) function in the delineation of health effects due to air pollution. However, nonlinearity may exist in the association between air pollutant concentrations and health outcomes such as adult pneumonia hospital visits, and there is a research gap in understanding the nonlinearity. Here, we utilized both the distributed lag model (DLM) and nonlinear model (DLNM) to compare the linear and nonlinear impacts of air pollution on adult pneumonia hospital visits in the coastal city of Qingdao, China. While both models show adverse effects of air pollutants on adult pneumonia hospital visits, the DLNM shows an attenuation of E-R curves at high concentrations. Moreover, the DLNM may reveal delayed health effects that may be missed in the DLM, e.g., ozone exposure and pneumonia hospital visits. With the stratified analysis of air pollutants on adult pneumonia hospital visits, both models consistently reveal that the influence of air pollutants is higher during the cold season than during the warm season. Nevertheless, they may behave differently in terms of other subgroups, such as age, gender and visit types. For instance, while no significant impact due to PM2.5 in any of the subgroups abovementioned emerges based on DLM, the results from DLNM indicate statistically significant impacts for the subgroups of elderly, female and emergency department (ED) visits. With respect to adjustment by two-pollutants, PM10 effect estimates for pneumonia hospital visits were the most robust in both DLM and DLNM, followed by NO2 and SO2 based on the DLNM. Considering the estimated health effects of air pollution relying on the assumed E-R functions, our results demonstrate that the traditional linear association assumptions may overlook some potential health risks.
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Affiliation(s)
- Lingyue Yang
- Frontiers Science Center for Deep Ocean Multispheres and Earth System, and Key Laboratory of Marine Environmental Science and Ecology, Ministry of Education, Ocean University of China, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266100, China
| | - Jiuli Yang
- Frontiers Science Center for Deep Ocean Multispheres and Earth System, and Key Laboratory of Marine Environmental Science and Ecology, Ministry of Education, Ocean University of China, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266100, China
| | - Mingyang Liu
- Department of Emergency Internal Medicine, The Affiliated Hospital of Qingdao University, Qingdao, 266100, China
| | - Xiaohui Sun
- Department of Chronic Disease Prevention, Qingdao Municipal Center for Disease Control & Prevention, Qingdao, 266100, China
| | - Tiantian Li
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing,100021, China
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Vic 3004, Australia
| | - Kejia Hu
- Institute of Big Data in Health Science, School of Public Health, Zhejiang University, Hangzhou, 310058, China
| | - Michelle L Bell
- School of the Environment, Yale University, New Haven, CT, 06511, USA
| | - Qu Cheng
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, Berkeley, CA, 94720, USA
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, Fudan University, Shanghai, 200433, China
| | - Yang Liu
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, 30322, USA
| | - Huiwang Gao
- Frontiers Science Center for Deep Ocean Multispheres and Earth System, and Key Laboratory of Marine Environmental Science and Ecology, Ministry of Education, Ocean University of China, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266100, China
| | - Xiaohong Yao
- Frontiers Science Center for Deep Ocean Multispheres and Earth System, and Key Laboratory of Marine Environmental Science and Ecology, Ministry of Education, Ocean University of China, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266100, China
| | - Yang Gao
- Frontiers Science Center for Deep Ocean Multispheres and Earth System, and Key Laboratory of Marine Environmental Science and Ecology, Ministry of Education, Ocean University of China, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266100, China.
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Peng W, Li H, Peng L, Wang Y, Wang W. Effects of particulate matter on hospital admissions for respiratory diseases: an ecological study based on 12.5 years of time series data in Shanghai. Environ Health 2022; 21:12. [PMID: 35027064 PMCID: PMC8756174 DOI: 10.1186/s12940-021-00828-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 12/27/2021] [Indexed: 05/08/2023]
Abstract
BACKGROUND Previous epidemiological studies on the association between short-term exposure to particulate matter (PM) with hospital admission in major cities in China were limited to shorter study periods or a single hospital. The aim of this ecological study based on a 12.5-year time series was to investigate the association of short-term exposure to PM with aerodynamic diameter ≤ 2.5 μm (PM2.5) and aerodynamic diameter ≤ 10 μm (PM10) with hospital admissions for respiratory diseases. METHODS Daily hospital admissions data were from the Shanghai Medical Insurance System for the period January 1, 2008 to July 31, 2020. We estimated the percentage change with its 95% confidence interval (CI) for each 10 μg/m3 increase in the level of PM2.5 and PM10 after adjustment for calendar time, day of the week, public holidays, and meteorological factors applying a generalized additive model with a quasi-Poisson distribution. RESULTS There were 1,960,361 hospital admissions for respiratory diseases in Shanghai during the study period. A 10 μg/m3 increase in the level of each class of PM was associated with increased total respiratory diseases when the lag time was 0 day (PM2.5: 0.755%; 95% CI: 0.422, 1.089%; PM10: 0.250%; 95% CI: 0.042, 0.459%). The PM2.5 and PM10 levels also had positive associations with admissions for COPD, asthma, and pneumonia. Stratified analyses demonstrated stronger effects in patients more than 45 years old and during the cold season. Total respiratory diseases increased linearly with PM concentration from 0 to 100 μg/m3, and increased more slowly at higher PM concentrations. CONCLUSIONS This time-series study suggests that short-term exposure to PM increased the risk for hospital admission for respiratory diseases, even at low concentrations. These findings suggest that reducing atmospheric PM concentrations may reduce hospital admissions for respiratory diseases.
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Affiliation(s)
- Wenjia Peng
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, 200032, China
| | - Hao Li
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, 200032, China
| | - Li Peng
- Department of Epidemiology, Shanghai Key Laboratory of Meteorology and Health, Shanghai, 200032, China
| | - Ying Wang
- Key Laboratory of Health Technology Assessment, National Health and Family Planning Commission of the People's Republic of China, Fudan University, Shanghai, China.
- IRDR-ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, 200032, China.
| | - Weibing Wang
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, 200032, China.
- Department of Epidemiology, Shanghai Key Laboratory of Meteorology and Health, Shanghai, 200032, China.
- Department of Social Medicine, School of Public Health, Fudan University, Shanghai, 200032, China.
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Liu WY, Yi JP, Tung TH, Yan JB. Association Between the Ambient Fine Particulate Pollution and the Daily Internal Medicine Outpatient Visits in Zhoushan, China: A Time-Series Study. Front Public Health 2021; 9:749191. [PMID: 34765582 PMCID: PMC8575696 DOI: 10.3389/fpubh.2021.749191] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 09/24/2021] [Indexed: 11/13/2022] Open
Abstract
Background: There has been a recent worsening of air pollution in China, which poses a huge threat to public health by inducing and promoting circulatory and respiratory diseases. This study aimed to explore the association between the concentration of air pollution and daily internal medicine outpatient visits registered for the treatment of circulatory and respiratory symptoms in Zhoushan, China using a time-series method. Methods: We validated and acquired the daily internal medicine outpatient visits records between January 1, 2014, and December 31, 2019, from the Zhoushan Center for Disease Control and Prevention in Zhejiang, China. Further, we collected the daily average records of the ambient air pollutants from the Zhoushan Environmental Monitoring Centre within the same duration. A generalized additive model with the natural splines was constructed to explore the association between the ambient air pollutants and daily internal medicine outpatient visits. Further, we conducted a lag analysis by using the distributed lag non-linear model to estimate the time-delayed effects of the air pollutants on the daily internal medicine outpatient visits. Results: A total of 2,190,258 daily internal medicine outpatient visits with a mean of 202.4 visits per day were recorded. The non-linear relationships were found among particulate matter2.5 (PM2.5), sulfur dioxide (SO2), and the daily internal medicine outpatient visits. Overall, PM2.5 was positively correlated with the daily internal medicine outpatient visits. Both ozone (O3) and SO2 had significant delayed effects on the daily internal medical outpatient numbers; however, PM2.5 only showed a short-term risk. Conclusion: Short-term exposure to PM2.5 was associated with an increase in the daily internal medicine outpatient visits for circulatory and respiratory diseases/symptoms in Zhoushan, China. SO2 and O3 were shown to induce significant effects after a concentration-dependent time lag.
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Affiliation(s)
- Wen-Yi Liu
- Department of Health Policy Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States.,Shanghai Bluecross Medical Science Institute, Shanghai, China.,Institute for Hospital Management, Tsing Hua University, Beijing, China
| | - Jing-Ping Yi
- Zhoushan Municipal Center for Disease Control and Prevention, Zhoushan, China
| | - Tao-Hsin Tung
- Evidence-Based Medicine Center, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, China
| | - Jian-Bo Yan
- Zhoushan Municipal Center for Disease Control and Prevention, Zhoushan, China
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22
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Li Y, Li C, Liu J, Meng C, Xu C, Liu Z, Wang Q, Liu Y, Han J, Xu D. An association between PM 2.5 and pediatric respiratory outpatient visits in four Chinese cities. CHEMOSPHERE 2021; 280:130843. [PMID: 34162098 DOI: 10.1016/j.chemosphere.2021.130843] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 04/14/2021] [Accepted: 05/05/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND The effects of exposure to particulate matter with aerodynamic diameter less than 2.5 μm (PM2.5) on children's respiratory system were investigated in numerous epidemiological literatures. However, studies on the association between PM2.5 and pediatric outpatient visits for respiratory diseases, especially considering the multicenter studies were limited in China. OBJECTIVES To study the association between the short-term exposure to PM2.5 and the number of children's outpatient visits for respiratory diseases in four Chinese cities as well as the pooled health effects. METHODS Data of pediatric outpatient visits for respiratory diseases (RD, ICD: J00-J99) from representative hospitals in Shijiazhuang (SJZ), Xi'an (XA), Nanjing (NJ) and Guangzhou (GZ) in China from 2015 to 2018 were collected and the air quality data for the same period were collected from environmental protection departments. Generalized additive model (GAM) with quasi-Poisson regression was conducted to analyze the effects of PM2.5 on the number of pediatric outpatient visits in each city. Single-day lag model (lag0 to lag7) and moving average lag model (lag01 and lag07) were used to examine the lag effects and cumulative effects. Random-effects meta-analysis was used to pool the estimated risks of four cities. The interactions between PM2.5 and temperature were also explored. RESULTS The average daily/total outpatient visits for RD, in SJZ, XA, NJ and GZ from 2015 to 2018 were 854.2/1,245,384, 2353.9/3,439,025, 1267.2/1,851,438 and 1399.5/2,044,740 respectively. The percentages of acute upper respiratory infections (URD, ICD: J00-J06) and other acute lower respiratory infections (LRD, ICD: J20-J22) in RD were 33%, 13% (SJZ), 43%, 32% (XA), 26%, 21% (NJ) and 54%, 26% (GZ). The largest pooled estimates of single-day lag effects for RD, URD, and LRD were at lag0, lag0 and lag1. Every 10 μg/m3 increase in PM2.5 concentration was associated with a 0.46% (95%CI: 0.21%-0.70%), 0.50% (95%CI: 0.19%-0.81%) and 0.42% (95%CI: 0.06%-0.79%) increased number of outpatient visits significantly. While max cumulative effects which were all at lag 07 were 1.10% (95%CI: 0.46%-1.74%), 0.96% (95%CI: 0.20%-1.73%) and 1.06% (95%CI: 0.12%-2.00%). Less polluted cities (GZ and NJ) showed greater city-specific excess risks, but the excess risks significantly decreased after adjusting for NO2 in two-pollutant models. Generally, PM2.5 showed larger health hazards on lower temperature days. CONCLUSIONS Our study showed that exposure to the ambient PM2.5 was associated with the increase of the number of outpatient visits with pediatric respiratory diseases in four Chinese cities. The health effects of PM2.5 may not be independent of other air pollutants and could be modified by temperature.
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Affiliation(s)
- Yawei Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, China
| | - Chengcheng Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, China
| | - Jingyi Liu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, China
| | - Congshen Meng
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, China
| | - Chunyu Xu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, China
| | - Zhe Liu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, China
| | - Qin Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, China
| | - Yue Liu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, China
| | - Jingxiu Han
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, China.
| | - Dongqun Xu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, China.
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Leão MLP, Penteado JO, Ulguim SM, Gabriel RR, Dos Santos M, Brum AN, Zhang L, da Silva Júnior FMR. Health impact assessment of air pollutants during the COVID-19 pandemic in a Brazilian metropolis. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:41843-41850. [PMID: 33788092 PMCID: PMC8010497 DOI: 10.1007/s11356-021-13650-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 03/22/2021] [Indexed: 05/13/2023]
Abstract
Studies around the world have revealed reduced levels of atmospheric particulate matter in periods of greatest human mobility restriction to contain the spread of SARS-CoV-2 during the COVID-19 pandemic. The present study aimed to carry out a health impact assessment in Recife, Brazil, hypothesizing a scenario in which the levels of PM10 and PM2.5 remained, throughout the year, as in the most restrictive period of human mobility. Particular material data (PM10 and PM2.5) were measured during the pandemic and population and health (mortality, hospital admissions for heart and respiratory problems) data from 2018 were used. We observed a reduction in the concentration of PM2.5 in up to 43.7% and PM10 up to 29.5% during the period of social isolation in the city of Recife. The reduction in PM2.5 would avoid 106 annual deaths from non-external causes and 58 annual deaths from cardiovascular diseases. In this scenario, $ 294.88 million would be saved ($ 114.88 million from heart problems and $ 180 million from non-external causes). When considering hospitalizations avoided by the decrease in PM10, we observed 57 fewer hospitalizations for respiratory diseases, 42 for heart diseases and a reduction of 37 deaths due to non-external causes. The reduction in spending on respiratory and cardiovascular hospitalizations would exceed $ 330,000. Therefore, the reduction of particulate matter could prevent hospital admissions, deaths and consequently there would be a reduction in disease burden in developing countries where economic resources are scarce. In this sense, governments should seek to reduce levels of pollution in order to improve the life quality and health of the population.
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Affiliation(s)
- Marcos Lorran Paranhos Leão
- Faculdade de Ciências Médicas (FCM) e Hospital Universitário Oswaldo Cruz (HUOC) da Universidade de Pernambuco (UPE) Campus Santo Amaro, Recife. Rua Arnóbio Marques, 310 - Santo Amaro, Recife, PE, CEP: 50100-130, Brazil
| | - Julia Oliveira Penteado
- Laboratório de Ensaios Farmacológicos e Toxicológicos, Instituto de Ciências Biológicas, Universidade Federal Do Rio Grande, Avenida Itália, km 8, Campus Carreiros, Rio Grande, RS, CEP: 96203-900, Brazil
- Programa de Pós-Graduação em Ciências Da Saúde, Faculdade de Medicina, Rua Visconde de Paranaguá 102 Centro, Rio Grande, RS, Brasil, CEP: 96203-900
| | - Sabrina Morales Ulguim
- Laboratório de Ensaios Farmacológicos e Toxicológicos, Instituto de Ciências Biológicas, Universidade Federal Do Rio Grande, Avenida Itália, km 8, Campus Carreiros, Rio Grande, RS, CEP: 96203-900, Brazil
| | - Rômulo Reginato Gabriel
- Laboratório de Ensaios Farmacológicos e Toxicológicos, Instituto de Ciências Biológicas, Universidade Federal Do Rio Grande, Avenida Itália, km 8, Campus Carreiros, Rio Grande, RS, CEP: 96203-900, Brazil
| | - Marina Dos Santos
- Laboratório de Ensaios Farmacológicos e Toxicológicos, Instituto de Ciências Biológicas, Universidade Federal Do Rio Grande, Avenida Itália, km 8, Campus Carreiros, Rio Grande, RS, CEP: 96203-900, Brazil
- Programa de Pós-Graduação em Ciências Da Saúde, Faculdade de Medicina, Rua Visconde de Paranaguá 102 Centro, Rio Grande, RS, Brasil, CEP: 96203-900
| | - Aline Neutzling Brum
- Programa de Pós-Graduação em Ciências Da Saúde, Faculdade de Medicina, Rua Visconde de Paranaguá 102 Centro, Rio Grande, RS, Brasil, CEP: 96203-900
| | - Linjie Zhang
- Programa de Pós-Graduação em Ciências Da Saúde, Faculdade de Medicina, Rua Visconde de Paranaguá 102 Centro, Rio Grande, RS, Brasil, CEP: 96203-900
| | - Flavio Manoel Rodrigues da Silva Júnior
- Laboratório de Ensaios Farmacológicos e Toxicológicos, Instituto de Ciências Biológicas, Universidade Federal Do Rio Grande, Avenida Itália, km 8, Campus Carreiros, Rio Grande, RS, CEP: 96203-900, Brazil.
- Programa de Pós-Graduação em Ciências Da Saúde, Faculdade de Medicina, Rua Visconde de Paranaguá 102 Centro, Rio Grande, RS, Brasil, CEP: 96203-900.
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Zoran MA, Savastru RS, Savastru DM, Tautan MN, Baschir LA, Tenciu DV. Exploring the linkage between seasonality of environmental factors and COVID-19 waves in Madrid, Spain. PROCESS SAFETY AND ENVIRONMENTAL PROTECTION : TRANSACTIONS OF THE INSTITUTION OF CHEMICAL ENGINEERS, PART B 2021; 152:583-600. [PMID: 36285289 PMCID: PMC9584827 DOI: 10.1016/j.psep.2021.06.043] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 06/14/2021] [Accepted: 06/27/2021] [Indexed: 05/07/2023]
Abstract
Like several countries, Spain experienced a multi wave pattern of COVID-19 pandemic over more than one year period, between spring 2020 and spring 2021. The transmission of SARS-CoV-2 pandemics is a multi-factorial process involving among other factors outdoor environmental variables and viral inactivation.This study aims to quantify the impact of climate and air pollution factors seasonality on incidence and severity of COVID-19 disease waves in Madrid metropolitan region in Spain. We employed descriptive statistics and Spearman rank correlation tests for analysis of daily in-situ and geospatial time-series of air quality and climate data to investigate the associations with COVID-19 incidence and lethality in Madrid under different synoptic meteorological patterns. During the analyzed period (1 January 2020-28 February 2021), with one month before each of three COVID-19 waves were recorded anomalous anticyclonic circulations in the mid-troposphere, with positive anomalies of geopotential heights at 500 mb and favorable stability conditions for SARS-CoV-2 fast diffusion. In addition, the results reveal that air temperature, Planetary Boundary Layer height, ground level ozone have a significant negative relationship with daily new COVID-19 confirmed cases and deaths. The findings of this study provide useful information to the public health authorities and policymakers for optimizing interventions during pandemics.
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Affiliation(s)
- Maria A Zoran
- IT Department, National Institute of R&D for Optoelectronics, Atomistilor Street 409, MG5, Magurele-Bucharest, 077125, Romania
| | - Roxana S Savastru
- IT Department, National Institute of R&D for Optoelectronics, Atomistilor Street 409, MG5, Magurele-Bucharest, 077125, Romania
| | - Dan M Savastru
- IT Department, National Institute of R&D for Optoelectronics, Atomistilor Street 409, MG5, Magurele-Bucharest, 077125, Romania
| | - Marina N Tautan
- IT Department, National Institute of R&D for Optoelectronics, Atomistilor Street 409, MG5, Magurele-Bucharest, 077125, Romania
| | - Laurentiu A Baschir
- IT Department, National Institute of R&D for Optoelectronics, Atomistilor Street 409, MG5, Magurele-Bucharest, 077125, Romania
| | - Daniel V Tenciu
- IT Department, National Institute of R&D for Optoelectronics, Atomistilor Street 409, MG5, Magurele-Bucharest, 077125, Romania
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Zhang F, Zhang H, Wu C, Zhang M, Feng H, Li D, Zhu W. Acute effects of ambient air pollution on clinic visits of college students for upper respiratory tract infection in Wuhan, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:29820-29830. [PMID: 33566291 DOI: 10.1007/s11356-021-12828-7] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Accepted: 02/02/2021] [Indexed: 06/12/2023]
Abstract
Ambient air pollutants have been linked to adverse health outcomes, but evidence is still relatively rare in college students. Upper respiratory tract infection (URTI) is a common disease of respiratory system among college students. In this study, we assess the acute effect of air pollution on clinic visits of college students for URTI in Wuhan, China. Data on clinic visits due to URTI were collected from Wuhan University Hospital, meteorological factors (including daily temperature and relative humidity) provided by Wuhan Meteorological Bureau, and air pollutants by Wuhan Environmental Protection Bureau. In the present study, generalized additive model with a quasi-Poisson distribution link function was used to examine the association between ambient air pollutants (fine particulate matter (PM2.5), particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3)) and the daily number of clinic visits of college students for URTI at Wuhan University Hospital in Wuhan, China. In the meantime, the model was adjusted for the confounding effects of long-term trends, seasonality, day of the week, public holidays, vacation, and meteorological factors. The best degrees of free in model were selected based on AIC (Akaike Information Criteria). The effect modification by gender was also examined. A total of 44,499 cases with principal diagnosis of URTI were included from January 1, 2016, to December 31, 2018. In single-pollutant models, the largest increment of URTI visits were found at lag 0 day in single-day lags, and the effect values in cumulative lags were greater than those in single-day lags. PM2.5 (0.74% (95%CI: 0.05, 1.44)) at lag 0 day, PM10 (0.61% (95%CI: 0.12, 1.11)) and O3 (1.01% (95%CI: 0.24, 1.79)) at lag 0-1 days, and SO2 (9.18% (95%CI: 3.27, 15.42)) and NO2 (3.40% (95% CI:1.64, 5.19)) at lag 0-3 days were observed to be strongly and significantly associated with clinic visits for URTI. PM10 and NO2 were almost still significantly associated with URTI after controlling for the other pollutants in our two-pollutant models, where the effect value of SO2 after inclusion of O3 appeared to be the largest and the effects of NO2 were also obvious compared with the other pollutants. Subgroups analysis demonstrated that males were more vulnerable to PM10 and O3, while females seemed more vulnerable to exposure to SO2 and NO2. This study implied that short-term exposure to ambient air pollution was associated with increased risk of URTI among college students at Wuhan University Hospital in Wuhan, China. And gaseous pollutants had more negative health impact than solid pollutants. SO2 and NO2 were the major air pollutants affecting the daily number of clinic visits on URTI, to which females seemed more vulnerable than males.
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Affiliation(s)
- Faxue Zhang
- Department of Occupational and Environmental Health, School of Health Sciences, Wuhan University, Wuhan, 430071, China
| | - Han Zhang
- Department of Occupational and Environmental Health, School of Health Sciences, Wuhan University, Wuhan, 430071, China
| | - Chuangxin Wu
- Department of Global Health, School of Health Sciences, Wuhan University, Wuhan, 430071, China
| | - Miaoxuan Zhang
- Hospital of Wuhan University, Wuhan, 430072, Hubei, China
| | - Huan Feng
- Department of Epidemiology and Biostatistics, School of Health Sciences, Wuhan University, Wuhan, 430071, China
| | - Dejia Li
- Department of Occupational and Environmental Health, School of Health Sciences, Wuhan University, Wuhan, 430071, China.
| | - Wei Zhu
- Department of Occupational and Environmental Health, School of Health Sciences, Wuhan University, Wuhan, 430071, China.
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Zhang S, Chen X, Wang J, Dai C, Gou Y, Wang H. Particulate air pollution and respiratory Haemophilus influenzae infection in Mianyang, southwest China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:10.1007/s11356-021-13103-5. [PMID: 33638077 DOI: 10.1007/s11356-021-13103-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 02/18/2021] [Indexed: 02/05/2023]
Abstract
Particulate air pollution is correlated with many respiratory diseases. However, few studies have focused on the relationship between air particulate exposure and respiratory Heamophilus influenzae infection. Therefore, we detected respiratory Heamophilus influenzae infection by bacterial culture of sputum of patients, and we collected particulate air pollution data (including PM2.5 and PM10) from a national real-time urban air quality platform to analyze the relationship between particulate air pollution and respiratory Heamophilus influenzae infection. The mean concentrations of PM2.5 and PM10 were 37.58 μg/m3 and 58.44 μg/m3, respectively, showing particulate air pollution remains a severe issue in Mianyang. A total of 828 strains of Heamophilus influenzae were detected in sputum by bacterial culture. Multiple correspondence analysis suggested the heaviest particulate air pollution and the highest Heamophilus influenzae infection rates were all in winter, while the lowest particulate air pollution and the lowest Heamophilus influenzae infection rates were all in summer. In a single-pollutant model, each elevation of 10 μg/m3 of PM2.5, PM10, and PM2.5/10 (combined exposure level) increased the risk of respiratory Heamophilus influenzae infection by 34%, 23%, and 29%, respectively. Additionally, in the multiple-pollutant model, only PM2.5 was significantly associated with respiratory Heamophilus influenzae infection (B, 0.46; 95% confidence interval, 0.05-0.87), showing PM2.5 is an independent risk factor for respiratory Heamophilus influenzae infection. In summary, this study highlights air particulate exposure could increase the risk of respiratory Heamophilus influenzae infection, implying that stronger measures need to be taken to protect against respiratory infection induced by particulate air pollution.
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Affiliation(s)
- Shaocheng Zhang
- Department of Clinical Laboratory Medicine, Suining Central Hospital, Suining, 629000, Sichuan, China
| | - Xi Chen
- Department of Clinical Laboratory Medicine, Mianyang Central Hospital, 12 Changjia Lane, Jingzhong St, Mianyang, 621000, Sichuan, China.
| | - Jing Wang
- Department of Clinical Laboratory Medicine, Mianyang Central Hospital, 12 Changjia Lane, Jingzhong St, Mianyang, 621000, Sichuan, China
| | - Chunmei Dai
- Department of Clinical Laboratory Medicine, Mianyang Central Hospital, 12 Changjia Lane, Jingzhong St, Mianyang, 621000, Sichuan, China
| | - Yeran Gou
- Department of Respiratory and Critical Care Medicine, Chengdu Second People's Hospital, Chengdu, 610017, Sichuan, China
| | - Huanhuan Wang
- Department of Cell Biology and Genetics, Shantou University Medical College, 22 Xinling Rd, Shantou, 515041, Guangdong, China.
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Zhao X, Lu M, An Z, Li J, Li H, Zhao Q, Wu Z, Wu W, Liu Y, Song J. Acute effects of ambient air pollution on hospital outpatients with chronic pharyngitis in Xinxiang, China. INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 2020; 64:1923-1931. [PMID: 32780156 DOI: 10.1007/s00484-020-01980-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Revised: 06/19/2020] [Accepted: 07/28/2020] [Indexed: 06/11/2023]
Abstract
We present results on a time-series study that analyzed the acute effects of six criteria air pollutants on hospital outpatient with chronic pharyngitis (CP) in Xinxiang, China. Data on the concentration of air pollutants and CP outpatient records were collected daily in Xinxiang, China, from January 1, 2015 to December 31, 2018. This study identified 62,823 outpatients with CP. The annual average concentrations of PM2.5, PM10, SO2, NO2, CO, and O3 are 75.7, 132.1, 33.2, 48.4, 1377, and 59.4 μg/m3, respectively. Further, a 10 μg/m3 increment in the concentration of PM10, SO2, NO2, and CO corresponds to an increase of 0.28% (95% confidence interval (CI): 0.03-0.53%), 1.10% (95% CI: 0.09-2.11%), 1.82% (95% CI: 0.84-2.80%), and 0.03% (95% CI: 0.01-0.06%) in daily CP hospital outpatients, respectively. Furthermore, results indicated that outpatients under the age of 15 are more susceptible to the air pollutants, excluding O3. Meanwhile, males might be more susceptible, and effect estimates appear slightly stronger in the cool season. Therefore, we should implement effective measures to manage air pollutants and reinforce protection of the high-risk population.
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Affiliation(s)
- Xiangmei Zhao
- Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, School of Public Health, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China
| | - Mengxue Lu
- Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, School of Public Health, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China
| | - Zhen An
- Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, School of Public Health, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China
| | - Juan Li
- Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, School of Public Health, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China
| | - Huijun Li
- Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, School of Public Health, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China
| | - Qian Zhao
- Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, School of Public Health, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China
| | - Zhineng Wu
- Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, School of Public Health, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China
| | - Weidong Wu
- Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, School of Public Health, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China
| | - Yue Liu
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China.
| | - Jie Song
- Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, School of Public Health, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China.
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Yang H, Yan C, Li M, Zhao L, Long Z, Fan Y, Zhang Z, Chen R, Huang Y, Lu C, Zhang J, Tang J, Liu H, Liu M, Guo W, Yang L, Zhang X. Short term effects of air pollutants on hospital admissions for respiratory diseases among children: A multi-city time-series study in China. Int J Hyg Environ Health 2020; 231:113638. [PMID: 33080524 DOI: 10.1016/j.ijheh.2020.113638] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Revised: 09/03/2020] [Accepted: 09/08/2020] [Indexed: 12/21/2022]
Abstract
Evidence concerning short-term acute association between air pollutants and hospital admissions for respiratory diseases among children in a multi-city setting was quite limited. We conducted a time-series analysis to evaluate the association of six common air pollutants with hospital admissions for respiratory diseases among children aged 0-14 years in 4 cities (Guangzhou, Shanghai, Wuhan and Xining), China during 2013-2018. We used generalized additive models incorporating penalized smoothing splines and random-effect meta-analysis to calculate city-specific and pooled estimates, respectively. The exposure-response relationship curves were fitted using the cubic spline regression. Subgroup analyses by gender, age, season and disease subtype were also performed. A total of 183,036 respiratory diseases hospitalizations were recorded during the study period, and 94.1% of the cases were acute respiratory infections. Overall, we observed that increased levels of air pollutants except O3, were significantly associated with increased hospital admissions for respiratory disease. Each 10 μg/m3 increase in PM2.5, SO2 and NO2 at lag 07, PM10 at lag 03 and per 1 mg/m3 increase in CO at lag 01 corresponded to increments of 1.19%, 3.58%, 2.23%, 0.51% and 6.10% in total hospitalizations, respectively. Generally, exposure-response relationships of PM2.5 and SO2 in Guangzhou, SO2, NO2 and CO in Wuhan, as well as SO2 and NO2 in Xining with respiratory disease hospitalizations were also found. Moreover, the adverse effects of these pollutants apart from PM2.5 in certain cities remained significant even at exposure levels below the current Chinese Ambient Air Quality Standards (CAAQS) Grade II. Children aged 4-14 years appeared to be more vulnerable to the adverse effects of PM2.5, SO2 and NO2. Furthermore, with the exception of O3, the associations were stronger in cold season than in warm season. Short-term exposure to PM2.5, SO2, NO2 and CO were associated, in dose-responsive manners, with increased risks of hospitalizations for childhood respiratory diseases, and adverse effects of air pollutants except PM2.5 held even at exposure levels below the current CAAQS Grade II in certain cities.
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Affiliation(s)
- Huihua Yang
- Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, And State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology (HUST), Wuhan, China
| | - Chunxiang Yan
- Wuhan Children's Hospital, Tongji Medical College, HUST, Wuhan, China
| | - Meng Li
- Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, And State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology (HUST), Wuhan, China
| | - Lei Zhao
- Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, And State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology (HUST), Wuhan, China
| | - Zhen Long
- Department of Pediatric Respiratory Medicine, Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, HUST, Wuhan, China
| | - Yali Fan
- Qinghai Provincial Women and Children's Hospital, Xining, China
| | - Zhonggang Zhang
- Qinghai Provincial Women and Children's Hospital, Xining, China
| | - Renjie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Yihui Huang
- Guangzhou Red Cross Hospital, Jinan University, Guangzhou, China
| | - Congbin Lu
- Guangzhou Red Cross Hospital, Jinan University, Guangzhou, China
| | - Jianduan Zhang
- Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, And State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology (HUST), Wuhan, China
| | - Jie Tang
- Department of Preventive Medicine, School of Public Health, Guangzhou Medical University, Guangzhou, China
| | - Hua Liu
- The First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou, China
| | - Miao Liu
- Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, And State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology (HUST), Wuhan, China
| | - Wenting Guo
- Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, And State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology (HUST), Wuhan, China
| | - Liangle Yang
- Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, And State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology (HUST), Wuhan, China
| | - Xiaomin Zhang
- Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, And State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology (HUST), Wuhan, China.
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Zoran MA, Savastru RS, Savastru DM, Tautan MN. Assessing the relationship between surface levels of PM2.5 and PM10 particulate matter impact on COVID-19 in Milan, Italy. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 738:139825. [PMID: 32512362 PMCID: PMC7265857 DOI: 10.1016/j.scitotenv.2020.139825] [Citation(s) in RCA: 255] [Impact Index Per Article: 63.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2020] [Accepted: 05/28/2020] [Indexed: 04/13/2023]
Abstract
The novel coronavirus disease (COVID-19) is a highly pathogenic, transmittable and invasive pneumococcal disease caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which emerged in December 2019 and January 2020 in Wuhan city, Hubei province, China and fast spread later on the middle of February 2020 in the Northern part of Italy and Europe. This study investigates the correlation between the degree of accelerated diffusion and lethality of COVID-19 and the surface air pollution in Milan metropolitan area, Lombardy region, Italy. Daily average concentrations of inhalable particulate matter (PM) in two size fractions PM2.5, PM10 and maxima PM10 ground level atmospheric pollutants together air quality and climate variables (daily average temperature, relative humidity, wind speed, atmospheric pressure field and Planetary Boundary Layer-PBL height) collected during 1 January-30 April 2020 were analyzed. In spite of being considered primarily transmitted by indoor bioaerosols droplets and infected surfaces, or direct human-to-human personal contacts, it seems that high levels of urban air pollution, weather and specific climate conditions have a significant impact on the increased rates of confirmed COVID-19 Total number, Daily New and Total Deaths cases, possible attributed not only to indoor but also to outdoor airborne bioaerosols distribution. Our analysis demonstrates the strong influence of daily averaged ground levels of particulate matter concentrations, positively associated with average surface air temperature and inversely related to air relative humidity on COVID-19 cases outbreak in Milan. Being a novel pandemic coronavirus (SARS-CoV-2) version, COVID-19 might be ongoing during summer conditions associated with higher temperatures and low humidity levels. Presently is not clear if this protein "spike" of the new coronavirus COVID-19 is involved through attachment mechanisms on indoor or outdoor airborne aerosols in the infectious agent transmission from a reservoir to a susceptible host in some agglomerated urban areas like Milan is.
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Affiliation(s)
- Maria A Zoran
- IT Department, National Institute of R&D for Optoelectronics, Atomistilor Street 409, MG5, Magurele-Bucharest 077125, Romania.
| | - Roxana S Savastru
- IT Department, National Institute of R&D for Optoelectronics, Atomistilor Street 409, MG5, Magurele-Bucharest 077125, Romania
| | - Dan M Savastru
- IT Department, National Institute of R&D for Optoelectronics, Atomistilor Street 409, MG5, Magurele-Bucharest 077125, Romania
| | - Marina N Tautan
- IT Department, National Institute of R&D for Optoelectronics, Atomistilor Street 409, MG5, Magurele-Bucharest 077125, Romania
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Jiang Y, Chen J, Wu C, Lin X, Zhou Q, Ji S, Yang S, Zhang X, Liu B. Temporal cross-correlations between air pollutants and outpatient visits for respiratory and circulatory system diseases in Fuzhou, China. BMC Public Health 2020; 20:1131. [PMID: 32690064 PMCID: PMC7370472 DOI: 10.1186/s12889-020-08915-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Accepted: 05/13/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Previous studies have suggested that there is an association between air pollutants and circulatory and respiratory diseases; however, relatively few have analyzed the association between air pollutants and outpatient visits based on the mortality, hospitalization rates, etc., especially in areas with relatively good air quality. Therefore, we conducted this study to research the association between air pollutants and outpatient visits in Fuzhou, China. METHODS We used a generalized linear Poisson model to study the association between air pollution and outpatient visits for respiratory and circulatory diseases from 2016 to 2018 in Fuzhou, China. RESULTS In the single pollutant model, nitrogen dioxide (NO2) had a significant effect. For lag day 0 to lag day 5, the effect decreased with every 10 μg/L increase in NO2. The daily maximum 8-h mean ozone (O3-8h) and upper respiratory outpatient visits were positively associated during the cold period [lag2, excess risk (ER) (95% confidence interval (CI)): 1.68% (0.44-2.94%)], while O3-8h and respiratory disease were positively associated during the warm period [lag5, ER (95% CI): 1.10% (0.11-2.10%) and lag4, ER (95% CI): 1.02% (0.032-2.02%)]. Similarly, particulate matter (PM) with an average aerodynamic diameter of less than 10 μm (PM10) and lower respiratory diseases were positively associated during the warm period [lag0, ER (95% CI): 1.68% (0.44-2.94%)]. When the concentration of O3-8h was higher than 100 μg/L, there was a positive effect on circulatory [lag5, ER (95% CI): 2.83% (0.65-5.06%)], respiratory [lag5, ER (95% CI): 2.47% (0.85-4.11%)] and upper respiratory [lag5, ER (95% CI): 3.06% (1.38-4.77%)] outpatient visits. The variation in O3-8h changed slightly when we adjusted for other air pollutants, and after adjusting for O3-8h, the ERs of the other air pollutants changed slightly. After adjusting for PM with an average aerodynamic diameter of less than 2.5 μm (PM2.5), the ERs of the other air pollutants increased, and after adjusting for NO2, the ER of PM decreased. CONCLUSION Exposure to ambient NO2, O3, PM2.5 and PM10 was associated with an increase in respiratory and circulatory system-related outpatient visits in Fuzhou, China.
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Affiliation(s)
- Yu Jiang
- Department of Preventive Medicine, Fujian Provincial Key Laboratory of Environment Factors and Cancer, Key Laboratory of Environment and Health, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Jiedong Chen
- Department of Preventive Medicine, Fujian Provincial Key Laboratory of Environment Factors and Cancer, Key Laboratory of Environment and Health, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Chuancheng Wu
- Department of Preventive Medicine, Fujian Provincial Key Laboratory of Environment Factors and Cancer, Key Laboratory of Environment and Health, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Xin Lin
- Fuzhou Center for Disease Control and Prevention, Fuzhou, China
| | - Quan Zhou
- Fuzhou Center for Disease Control and Prevention, Fuzhou, China
| | - Shumi Ji
- Department of Preventive Medicine, Fujian Provincial Key Laboratory of Environment Factors and Cancer, Key Laboratory of Environment and Health, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Shuangfeng Yang
- Department of Preventive Medicine, Fujian Provincial Key Laboratory of Environment Factors and Cancer, Key Laboratory of Environment and Health, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Xiaoyang Zhang
- Fuzhou Center for Disease Control and Prevention, Fuzhou, China
| | - Baoying Liu
- Department of Preventive Medicine, Fujian Provincial Key Laboratory of Environment Factors and Cancer, Key Laboratory of Environment and Health, School of Public Health, Fujian Medical University, Fuzhou, China
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Fuller CH, Jones JW, Roblin DW. Evaluating changes in ambient ozone and respiratory-related healthcare utilization in the Washington, DC metropolitan area. ENVIRONMENTAL RESEARCH 2020; 186:109603. [PMID: 32668548 PMCID: PMC8079178 DOI: 10.1016/j.envres.2020.109603] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Revised: 12/11/2019] [Accepted: 04/25/2020] [Indexed: 05/21/2023]
Abstract
Ozone pollution is a known respiratory irritant, yet we do not fully understand the magnitude or timing of respiratory effects based on short-term exposure. We investigated the associations between ambient ozone concentrations and respiratory symptoms as measured by healthcare utilization events. We used comprehensive electronic health records to identify respiratory responses to changes in ambient ozone levels. We constructed a dataset from Kaiser Permanente Mid-Atlantic States (KPMAS) that included information on 2013 and 2014 daily utilization rates for a broad range of healthcare utilization - nurse calls/emails, provider visits, emergency department and urgent care visits (ED/UC) and hospital admissions - by census block. We used 8-h average ozone concentrations collected from 48 air monitoring stations in the region via the Air Data database of the USEPA. We estimated the association between changes in ambient ozone (exposure windows of current day, 1-day lag and 3-day moving average) and changes in healthcare utilization using linear regression controlling for census tract-level socioeconomic indicators and temperature. Increases in ozone were associated with increases in three of the four utilization event types. A 10 ppb increase in 1-day ozone was associated with a 2.95% (95% CI: 1.93%, 3.96%) increase in calls/emails, a 1.56% (95% CI: 0.38%, 2.74%) increase in ED/UC visits and a 1.10% (95% CI: 0.48%, 1.73%) increase in provider visits. We did not find associations between ozone and hospital admissions. Proportionally, highest effects were found for nurse calls/emails possibly indicating a high number of mild effects that may be underreported in studies that examine only ED visits or hospital admissions.
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Affiliation(s)
- Christina H Fuller
- Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, GA, USA.
| | - Jordan W Jones
- Department of Economics, Andrew Young School of Policy Studies, Georgia State University, Atlanta, GA, USA
| | - Douglas W Roblin
- Kaiser Permanente Mid-Atlantic State, Rockville, MD, USA; Department of Health Policy & Behavioral Sciences, School of Public Health, Georgia State University, Atlanta, GA, USA
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Guo H, Li W, Wu J. Ambient PM2.5 and Annual Lung Cancer Incidence: A Nationwide Study in 295 Chinese Counties. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17051481. [PMID: 32106556 PMCID: PMC7084498 DOI: 10.3390/ijerph17051481] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 02/13/2020] [Accepted: 02/21/2020] [Indexed: 12/20/2022]
Abstract
Most studies have examined PM2.5 effects on lung cancer mortalities, while few nationwide studies have been conducted in developing countries to estimate the effects of PM2.5 on lung cancer incidences. To fill this gap, this work aims to examine the effects of PM2.5 exposure on annual incidence rates of lung cancer for males and females in China. We performed a nationwide analysis in 295 counties (districts) from 2006 to 2014. Two regression models were employed to analyse data controlling for time, location and socioeconomic characteristics. We also examined whether the estimates of PM2.5 effects are sensitive to the adjustment of health and behaviour covariates, and the issue of the changing cancer registries each year. We further investigated the modification effects of region, temperature and precipitation. Generally, we found significantly positive associations between PM2.5 and incidence rates of lung cancer for males and females. If concurrent PM2.5 changes by 10 g/m3, then the incidence rate relative to its baseline significantly changes by 4.20% (95% CI: 2.73%, 5.88%) and 2.48% (95% CI: 1.24%, 4.14%) for males and females, respectively. The effects of exposure to PM2.5 were still significant when further controlling for health and behaviour factors or using 5 year consecutive data from 91 counties. We found the evidence of long-term lag effects of PM2.5. We also found that temperature appeared to positively modify the effects of PM2.5 on the incidence rates of lung cancer for males. In conclusion, there were significantly adverse effects of PM2.5 on the incidence rates of lung cancer for both males and females in China. The estimated effect sizes might be considerably lower than those reported in developed countries. There were long-term lag effects of PM2.5 on lung cancer incidence in China.
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Affiliation(s)
- Huagui Guo
- Department of Urban Planning and Design, The University of Hong Kong, Hong Kong 999077, China;
- Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen 518057, China
| | - Weifeng Li
- Department of Urban Planning and Design, The University of Hong Kong, Hong Kong 999077, China;
- Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen 518057, China
- Correspondence: ; Tel.: +86-(852)-39172566
| | - Jiansheng Wu
- Key Laboratory for Urban Habitat Environmental Science and Technology, Shenzhen Graduate School, Peking University, Shenzhen 518055, China;
- Key Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
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Zhu Y, Wang Y, Xu H, Luo B, Zhang W, Guo B, Chen S, Zhao X, Li W. Joint effect of multiple air pollutants on daily emergency department visits in Chengdu, China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2019; 257:113548. [PMID: 31733961 DOI: 10.1016/j.envpol.2019.113548] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2019] [Revised: 10/23/2019] [Accepted: 10/30/2019] [Indexed: 02/05/2023]
Abstract
Existing studies have typically investigated only the association between single pollutants and health outcomes. However, in the real world, people are exposed to multiple air pollutants simultaneously. The effect of air pollutants on emergency department (ED) visits has not been previously studied in the Sichuan Basin, which is one of the most polluted areas. We collected nonaccidental, respiratory and cardiovascular daily ED visits and daily concentrations of PM2.5, PMc, CO, SO2, NO2 and O3 in Chengdu, China, from 2014 to 2016. A weighted variable for the combination of multiple air pollutants was constructed to assess the joint adverse health effects. Each air pollutant was assigned a health-related weight, which indicated the pollutant's relative contribution to the joint effect. The effects on specific subpopulations (males and females; 15-65 years old and >65 years old) were also examined. With an increase of 10 μg/m3 of the combined multiple air pollutants, the daily ED visits for nonaccidental, respiratory and cardiovascular causes increased by 0.96% (95% CI: 0.51%-1.39%), 1.19% (95% CI: 0.53%, 1.85%) and 4.36% (95% CI: 1.06%, 7.76%) at lag 1, respectively. Males presented more pronounced effects, except for cardiovascular disease, than females. Elderly individuals were found to be more sensitive than young individuals. For nonaccidental and respiratory diseases, the contributions of particulate matter (PM) were dominant among the air pollutants, whereas cardiovascular disease was mainly affected by gaseous air pollutants. The combination of multiple air pollutants was significantly associated with ED visits in the Sichuan Basin, China. The joint effect of the combination of multiple air pollutants was highest for cardiovascular disease at lag 1. The relative contributions of individual pollutants varied by disease and subpopulation. These findings suggest that under different pollution scenarios, preventive strategies should target those with different diseases and different subpopulations.
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Affiliation(s)
- Yue Zhu
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, Sichuan Province, China
| | - Yanyan Wang
- National Clinical Research Center of Geriatrics, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan Province, China
| | - Huan Xu
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, Sichuan Province, China
| | - Bin Luo
- Sichuan Environmental Monitoring Center, Chengdu, 610041, Sichuan Province, China
| | - Wei Zhang
- Sichuan Environmental Monitoring Center, Chengdu, 610041, Sichuan Province, China
| | - Bing Guo
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, Sichuan Province, China
| | - Shiqi Chen
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, Sichuan Province, China; Sichuan Province Hospital for Women and Children, Chengdu, 610041, Sichuan Province, China
| | - Xing Zhao
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, Sichuan Province, China.
| | - Weimin Li
- Department of Respiratory and Critical Care Medicine, West China Medical School/West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
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The short-term effects of air pollutants on influenza-like illness in Jinan, China. BMC Public Health 2019; 19:1319. [PMID: 31638933 PMCID: PMC6805627 DOI: 10.1186/s12889-019-7607-2] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Accepted: 09/09/2019] [Indexed: 11/10/2022] Open
Abstract
Background There is valid evidence that air pollution is associated with respiratory disease. However, few studies have quantified the short-term effects of six air pollutants on influenza-like illness (ILI). This study explores the potential relationship between air pollutants and ILI in Jinan, China. Methods Daily data on the concentration of particulate matters < 2.5 μm (PM 2.5), particulate matters < 10 μm (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) and ILI counts from 2016 to 2017 were retrieved. The wavelet coherence analysis and generalized poisson additive regression model were employed to qualify the relationship between air pollutants and ILI risk. The effects of air pollutants on different age groups were investigated. Results A total of 81,459 ILI counts were collected, and the average concentrations of PM2.5, PM10, O3, CO, SO2 and NO2 were 67.8 μg/m3, 131.76 μg/ m3, 109.85 μg/ m3, 1133 μg/ m3, 33.06 μg/ m3 and 44.38 μg/ m3, respectively. A 10 μg/ m3 increase in concentration of PM2.5, PM10, CO at lag0 and SO2 at lag01, was positively associated with a 1.0137 (95% confidence interval (CI): 1.0083–1.0192), 1.0074 (95% CI: 1.0041–1.0107), 1.0288 (95% CI: 1.0127–1.0451), and 1.0008 (95% CI: 1.0003–1.0012) of the relative risk (RR) of ILI, respectively. While, O3 (lag5) was negatively associated with ILI (RR 0.9863; 95%CI: 0.9787–0.9939), and no significant association was observed with NO2, which can increase the incidence of ILI in the two-pollutant model. A short-term delayed impact of PM2.5, PM10, SO2 at lag02 and CO, O3 at lag05 was also observed. People aged 25–59, 5–14 and 0–4 were found to be significantly susceptible to PM2.5, PM10, CO; and all age groups were significantly susceptible to SO2; People aged ≥60 year, 5–14 and 0–4 were found to be significantly negative associations with O3. Conclusion Air pollutants, especially PM2.5, PM10, CO and SO2, can increase the risk of ILI in Jinan. The government should create regulatory policies to reduce the level of air pollutants and remind people to practice preventative and control measures to decrease the incidence of ILI on pollution days.
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Wang Y, Shi Z, Shen F, Sun J, Huang L, Zhang H, Chen C, Li T, Hu J. Associations of daily mortality with short-term exposure to PM 2.5 and its constituents in Shanghai, China. CHEMOSPHERE 2019; 233:879-887. [PMID: 31340414 DOI: 10.1016/j.chemosphere.2019.05.249] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2019] [Revised: 05/20/2019] [Accepted: 05/27/2019] [Indexed: 06/10/2023]
Abstract
Epidemiological studies have shown that fine particulate matter (PM2.5) has adverse impacts on human health. However, limited studies have investigated the effects of short-term exposure to PM2.5 and its constituents on mortality in China. This study used the generalized linear model (GLM) to investigate the effects of PM2.5 and its constituents, including organic carbon (OC), element carbon (EC), ammonium (NH4+), nitrate (NO3-), sulfate (SO42-), on different causes of mortality in Shanghai from January 1, 2013 to December 31, 2015. The single-day lagged model and the moving average lagged model were used to examine the lagging effects of pollutants on mortality. At lag0 day, PM2.5 had a significant effect on all-cause mortality, and a 10 μg/m3 increase leads to 0.68% increase in all-cause mortality (RR 1.0068, 95%CI 1.0013-1.0123). Among the five constituents, EC had the greatest impact on all-cause mortality in Shanghai, with 10.48% increase of mortality (RR 1.1048, 95%CI 1.0266-1.1891) per 10 μg/m3 increase of concentrations, followed by OC (RR 1.0577, 95%CI 1.0277-1.0886), NH4+ (RR 1.0272, 95%CI 1.0028-1.0522) and SO42- (RR 1.0104, 95%CI 1.0003-1.0206). For respiratory diseases mortality, EC, OC, NO3- and NH4+ had significant impacts and caused an increase of mortality by 44.99% (RR 1.4499, 95%CI 1.1813-1.7794), 10.40% (RR 1.1040, 95%CI 1.0260-1.1880), 5.338% (RR 1.0533, 95%CI 1.0097-1.0989) and 7.34% (RR 1.0734, 95%CI 1.0015-1.1505) per 10 μg/m3 increase of concentrations, respectively. The cumulative effect of PM2.5 on mortality was significant in Shanghai. Except for SO42-, the RR value of the single-day lagged model was smaller than the moving average lagged model.
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Affiliation(s)
- Yiyi Wang
- Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing, 210044, China
| | - Zhihao Shi
- Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing, 210044, China
| | - Fuzhen Shen
- Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing, 210044, China
| | - Jinjin Sun
- Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing, 210044, China
| | - Lin Huang
- Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing, 210044, China
| | - Hongliang Zhang
- Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA, 70803, United States
| | - Chen Chen
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China
| | - Tiantian Li
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China.
| | - Jianlin Hu
- Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing, 210044, China.
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Yao L, Zhan B, Xian A, Sun W, Li Q, Chen J. Contribution of transregional transport to particle pollution and health effects in Shanghai during 2013-2017. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 677:564-570. [PMID: 31067477 DOI: 10.1016/j.scitotenv.2019.03.488] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Revised: 03/31/2019] [Accepted: 03/31/2019] [Indexed: 06/09/2023]
Abstract
Transregional transport plays an important role in air pollution. This study investigated the impact of transregional transport on particle pollution in Shanghai from 2013 to 2017. A conditional potential source contribution function (CPSCF) method with high time resolution (1 h) PM2.5 and PM10 data was used to quantify the contribution of transregional transport. The corresponding health impact was also assessed. The average annual contribution of transregional transport to PM2.5 (PM2.5_CTRT) and PM10 (PM10_CTRT) was 22 and 30 μg/m3, 18 and 24 μg/m3, 19 and 24 μg/m3, 14 and 19 μg/m3, and 14 and 19 μg/m3, for 2013 to 2017, respectively, thus accounting for 31-37% of total PM2.5 and PM10. As PM2.5_CTRT is a dominant component of PM10_CTRT, the health effects related to PM2.5_CTRT were assessed to avoid double counting. The number of annual deaths associated with PM2.5_CTRT in Shanghai during the study period ranged from 636 (95% confidence intervals: 350, 936) to 1039 (573, 1530), among which cardiovascular disease and respiratory disease accounted for 62.8-67.6% and 16.6-19.5% of mortality, respectively. PM2.5_CTRT-related deaths accounted for 5.3-8.2‰ of the total mortality in Shanghai during the study period. Between 9764 (9251, 10,277) and 12,190 (11,549, 12,830) cases of all-cause hospital admissions were attributable to PM2.5_CTRT in Shanghai in one year, among which cardiovascular disease and respiratory disease hospital admissions accounted for 15.9-20.0% and 7.9-9.2%, respectively. Internal medicine and pediatrics outpatient visits related to PM2.5_CTRT ranged from 70,684 (39,009, 100,829) to 97,380 (53,788, 138,793) cases and 23,185 (8302, 37,173) to 32,702 (11,726, 52,361) cases, respectively. The current work provides scientific evidence of the impact of transregional transport on air pollution and its health burden in Shanghai.
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Affiliation(s)
- Lan Yao
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200433, China
| | - Bixin Zhan
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200433, China
| | - Aiyong Xian
- Yellow River Shandong Bureau, Jinan 250000, China
| | - Wenwen Sun
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200433, China
| | - Qing Li
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200433, China
| | - Jianmin Chen
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200433, China; Shanghai Institute of Eco-Chongming (SIEC), No. 3663 Northern Zhongshan Road, Shanghai 200062, China.
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Mokoena KK, Ethan CJ, Yu Y, Shale K, Liu F. Ambient air pollution and respiratory mortality in Xi'an, China: a time-series analysis. Respir Res 2019; 20:139. [PMID: 31277656 PMCID: PMC6612149 DOI: 10.1186/s12931-019-1117-8] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2019] [Accepted: 07/01/2019] [Indexed: 12/17/2022] Open
Abstract
Background Although air pollution is a known fundamental problem in China, few studies have investigated the associations between ambient air pollution and respiratory mortality in non-metropolitan cities of China. The study aimed to investigate a potential relationship between short-term exposure to ambient air pollutants and respiratory mortality in Xi’an, China. Methods Daily averages of PM2.5, SO2, O3, temperature, relative humidity and daily counts of respiratory mortality were obtained (2014–2016). Using a single and multi-pollutant approach in time-series analysis, the generalized additive model with natural splines was used for analysis. Subgroup analysis stratified by gender and age group (≤ 64 years and ≥ 65 years) was conducted. Results Seven thousand nine hundred sixty-five cases of respiratory mortality were assessed, with 62.9, 28.5, and 8.6% of mortality attributed to chronic lower respiratory diseases, influenza and pneumonia, as well as other forms of respiratory diseases, respectively. Observed pollutants were significantly associated with respiratory mortality. In the single pollutant model, 10 μg/m3 increase in a two-day moving average of PM2.5, and SO2 concentrations were significantly associated with relative risk 1.313(1.032, 1.708) and 1.4020(0.827, 2.854) of respiratory mortality, respectively. The effects of both air pollutants remained statistically significant after adjusting for collinearity in the multi-pollutant model. Ozone was only statistically associated with respiratory mortality in females at lag 0 [RR: 0.964(0.938, 0.991)]. Conclusion This study provided evidence that respiratory mortality in Xi’an was significantly associated with exposure to ambient air pollutants from 2014 to 2016.
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Affiliation(s)
- Kingsley Katleho Mokoena
- School of Public Health, Health Science Center, Xi'an Jiaotong University, 76, Yanta West Road, Xi'an, 710061, Shaanxi Province, China.,Department of Life Sciences, Central University of Technology, Free State, Bloemfontein, Free State, 9300, South Africa
| | - Crystal Jane Ethan
- School of Public Health, Health Science Center, Xi'an Jiaotong University, 76, Yanta West Road, Xi'an, 710061, Shaanxi Province, China
| | - Yan Yu
- School of Public Health, Health Science Center, Xi'an Jiaotong University, 76, Yanta West Road, Xi'an, 710061, Shaanxi Province, China.
| | - Karabo Shale
- Department of Environmental and Occupational Studies, Cape Peninsula University of Technology, Cape Town, 8000, South Africa
| | - Feng Liu
- Shaanxi Provincial Center for Disease Control and Prevention, Xi'an, 710054, Shaanxi, China.
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Fuller CH, Roblin D, Jones J. Using Syndromic Surveillance to Evaluate the Respiratory Effects of Fine Particulate Matter. Ann Am Thorac Soc 2019; 16:930-933. [PMID: 30840829 PMCID: PMC6600839 DOI: 10.1513/annalsats.201902-118rl] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Affiliation(s)
| | - Douglas Roblin
- Kaiser Permanente Mid-Atlantic StatesRockville, Maryland
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Wang C, Feng L, Chen K. The impact of ambient particulate matter on hospital outpatient visits for respiratory and circulatory system disease in an urban Chinese population. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 666:672-679. [PMID: 30812001 DOI: 10.1016/j.scitotenv.2019.02.256] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2018] [Revised: 01/26/2019] [Accepted: 02/16/2019] [Indexed: 05/27/2023]
Abstract
There are limited evidence on the association between short-term exposure to ambient particulate matter (PM) and overall hospital outpatient visits for respiratory system disease (RESD) and cardio-cerebrovascular system disease (CCD) in high-polluted countries like China. Though previous epidemiological studies of RESD and CCD generally applied a linear relationship of the acute PM effects, it is unclear whether this linear exposure-response relationship holds in high pollution area. In this study, a time-series study during 2013 through 2016 was conducted to investigate 245,442 and 430,486 hospital visits for RESD and CCD respectively from Nanjing city, China. A combination of logistic generalized additive model (GAM) was used to evaluate the exposure-response associations. The results disclosed that a 10 μg/m3 increase in PM2.5 and PM10 concentration on the current day of exposure (lag 0) was associated with 0.36% (95% CI: -0.02%-0.73%) and 0.33% (0.07%-0.60%) increase in RESD; and 0.42% (0.00%-0.85%) and 0.37% (0.08%-0.67%) increase in CCD. The exposure-response association was approximately linear within 0-150 μg/m3 of PM concentration and non-linear across the full range of exposures. The effects of PM on RESD and CCD were sensitive to additional adjustment for co-pollutants, indicating the health effects of air pollution mixture in Nanjing city. There was no evidence of potential effect modification of RESD and CCD by season (cold and warm), age (5-64, 65-74, ≧75 years) and sex (male and female) groups. Though not statistically significant, the estimated risks in warm season were higher than those in cold season, suggesting potential synergistic effects of ambient PM pollution and temperature on triggering RESD and CCD.
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Affiliation(s)
- Ce Wang
- School of Energy and Environment, Southeast University, Nanjing, 210096, PR China; State Key Laboratory of Environmental Medicine Engineering, Ministry of Education, Southeast University, Nanjing, 210096, PR China.
| | - Lan Feng
- National-Provincial Joint Engineering Research Center of Electromechanical Product Packaging, College of Civil Engineering, Nanjing Forestry University, Nanjing, 210037, PR China.
| | - Kai Chen
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
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The impact of outdoor air pollutants on outpatient visits for respiratory diseases during 2012-2016 in Jinan, China. Respir Res 2018; 19:246. [PMID: 30541548 PMCID: PMC6292059 DOI: 10.1186/s12931-018-0958-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Accepted: 11/30/2018] [Indexed: 12/30/2022] Open
Abstract
Background Few studies have investigated the associations between outdoor air pollution and outpatient visits for respiratory diseases (RDs) in general population. Methods We collected daily outpatient data of primary RDs from five hospitals in Jinan during January 2012 and December 2016, as well as daily measurements of air pollutants from the Jinan Environmental Monitoring Center and daily meteorological variables from the China Meteorological Data Sharing Service System. A generalized additive model (GAM) with quasi-Poisson regression was constructed to estimate the associations between daily average concentrations of outdoor air pollutants (PM2.5,PM10, SO2, NO2, CO and O3) and daily outpatient visits of RDs after adjusting for long-time trends, seasonality, the “day of the week” effect, and weather conditions. Subgroup analysis stratified by gender, age group and the type of RDs was conducted. Results A total of 1,373,658 outpatient visits for RDs were identified. Increases of 10 μg/m3 in PM2.5, PM10, NO2, CO and O3 were associated with0.168% (95% CI, 0.072–0.265%), 0.149% (95% CI, 0.082–0.215%), 0.527% (95% CI, 0.211–0.843%), 0.013% (95% CI, 0.003–0.023%), and 0.189% (95% CI, 0.032–0.347%) increases in daily outpatient visits for RDs, respectively. PM2.5 and PM10 showed instant and continuous effects, while NO2, CO and O3 showed delayed effects on outpatient visits for RDs. In stratification analysis, PM2.5 and PM10 were associated with acute RDs only. Conclusions Exposure to outdoor air pollutants including PM2.5, PM10, NO2, CO and O3 associated with increased risk of outpatient visits for RDs. Electronic supplementary material The online version of this article (10.1186/s12931-018-0958-x) contains supplementary material, which is available to authorized users.
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Song J, Lu M, Zheng L, Liu Y, Xu P, Li Y, Xu D, Wu W. Acute effects of ambient air pollution on outpatient children with respiratory diseases in Shijiazhuang, China. BMC Pulm Med 2018; 18:150. [PMID: 30189886 PMCID: PMC6127994 DOI: 10.1186/s12890-018-0716-3] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2018] [Accepted: 08/28/2018] [Indexed: 01/21/2023] Open
Abstract
Background Associations between ambient air pollution and child health outcomes have been well documented in developed countries such as the United States; however, only a limited number of studies have been conducted in developing countries. This study aimed to explore the acute effects of five ambient air pollutants (inhalable particles [PM10], fine particles [PM2.5], sulfur dioxide [SO2], nitrogen dioxide [NO2] and 0zone [O3]) on children hospital outpatients with respiratory diseases in Shijiazhuang, China. Methods Three years (2013–2015) of daily data, including cause-specific respiratory outpatient records and the concentrations of five air pollutants, were collected to examine the short-term association between air pollution and children’s respiratory diseases; using a quasi-Poisson regression generalized additive model. Stratified analyses by season and age were also performed. Results From 2013 to 2015, a total of 551,678 hospital outpatient records for children with respiratory diseases were collected in Shijiazhuang, China. A 10 μg/m3 increase in a two-day average concentration (lag01) of NO2, PM2.5, and SO2 corresponded to an increase of 0.66% (95% confidence interval [CI]: 0.30–1.03%), 0.13% (95% CI: 0.02–0.24%), and 0.33% (95% CI: 0.10–0.56%) in daily hospital outpatient visits for children with respiratory diseases, respectively. The effects were stronger in the transition season (April, May, September and October) than in other seasons (the hot season [June to August] and the cool season [November to March]). Furthermore, results indicated a generally stronger association in older (7–14 years of age) than younger children (< 7 years of age). Conclusions This research found a significant association between ambient NO2, PM2.5, and SO2 levels and hospital outpatient visits in child with respiratory diseases in Shijiazhuang, China.
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Affiliation(s)
- Jie Song
- School of Public Health, Xinxiang Medical University, Xinxiang, 453003, China. .,Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, Xinxiang, 453003, China.
| | - Mengxue Lu
- Xinxiang Medical University, Xinxiang, 453003, China
| | - Liheng Zheng
- Hebei Chest Hospital, Shijiazhuang, 050041, China
| | - Yue Liu
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China
| | - Pengwei Xu
- School of Public Health, Xinxiang Medical University, Xinxiang, 453003, China
| | - Yuchun Li
- School of Public Health, Xinxiang Medical University, Xinxiang, 453003, China
| | - Dongqun Xu
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China
| | - Weidong Wu
- School of Public Health, Xinxiang Medical University, Xinxiang, 453003, China.,Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, Xinxiang, 453003, China
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